Modeling plateau potentials

We are attempting to run simulations of the C. Elegans neuronal network by building upon work of the OpenWorm team. We are looking into implementing a neuron model that produces plateau potentials rather than action potentials, as suggested by this paper. Thanks to @Comte for pointing me to this paper (see this link for another question related to our project).

Here is my question: What are known-to-work mathematical models of neurons that produce plateau potentials, rather than action potentials? Ideally, the model should be formulated as a system of differential equations (as is for example the Hodgkin-Huxley model), hence easy to implement in NEURON.

(A note on my personal background: I am a student of mathematics, and this is a project for university.)

i once wrote a paper doing biophysical modeling of neurons that could create plateau potentials. While the paper itself is not exactly what you are looking for, there should be lots of good references in there:
http://www.jneurosci.org/content/33/2/424.short
Sanders H, Berends M, Major G, Goldman MS, Lisman JE. (2013) NMDA and GABAB (KIR) Conductances: The “Perfect Couple” for Bistability. J. Neurosci. 33, 424-429

also, check other articles that cited that paper: https://scholar.google.com/scholar?cites=2120401607202660739

Event-related potential

An event-related potential (ERP) is the measured brain response that is the direct result of a specific sensory, cognitive, or motor event. [1] More formally, it is any stereotyped electrophysiological response to a stimulus. The study of the brain in this way provides a noninvasive means of evaluating brain functioning.

ERPs are measured by means of electroencephalography (EEG). The magnetoencephalography (MEG) equivalent of ERP is the ERF, or event-related field. [2] Evoked potentials and induced potentials are subtypes of ERPs.

Cognition and Brain Sciences

The Cognition and Brain Sciences Program is actively seeking new graduate students. If you are interested in applying, please explore this site, including our Tips for Getting into Graduate School in Research Oriented Psychology.

To see some of the UVic campus, check out this virtual tour. For information about Victoria and its many attractions, visit UVic's About Victoria webpage.

The Cognition and Brain Sciences Program faculty and graduate students share interests in a range of interconnected topics.

Our goal is to understand the nature of the representations and processes that give rise to mental events, and the influence of memory for past mental events on subsequent experience and behaviour.

We adopt a variety of empirical approaches to this enterprise, including naturalistic studies of children and adults, experiments conducted in laboratory contexts, brain imaging, case studies of brain-damaged patients, and computational modeling.

We are a closely integrated group, and we often work together on collaborative research enterprises. Every one of our faculty has an active, productive lab in which graduate students are conducting and publishing new research on current topics. Our faculty are major players in the world of cognitive and brain science, as indicated by their grants, journal editorships, leadership positions in large professional organizations, etc..

Resources

The Cognition and Brain Sciences Program brings a wide range of tools to bear on the study of the brain/mind in action.

Clay Holroyd and Jim Tanaka run the Brain and Cognition Event-related Potential Laboratory, which houses 4 state-of-the-art 64-channel systems for recording and analyzing the electroencephalogram (i.e., “brainwaves”). Holroyd’s EEG research focuses on the neural mechanisms of learning and cognitive control and Tanaka’s lab explores how experience, culture and biology converge to shape that way we perceive the world. Each year Holroyd teaches a graduate course on this technique and students from multiple labs utilize the facility for their own research.

CABS members Holroyd, Lindsay, and Krawitz and affiliated faculty Gawryluk, Medler and MacDonald all have experience using functional magnetic resonance imaging (MRI), with many of these studies published in high-impact journals. Faculty currently maintain collaborative contracts to access magnetic resonance imaging (MRI) resources with both West Coast Medical Imaging and Island Health. Our data is primarily collected on a 3T MRI scanner with functional magnetic resonance imaging, diffusion tensor imaging, and high resolution anatomical acquisitions. With a growing interest from students and faculty in these techniques, we are actively working on building neuroimaging capacity and commonly offer courses on how to analyze MRI based data.

Mike Masson and Daniel Bub utilize an eye-tracking system that yields real-time measures of what subjects are looking at moment to moment, a 3-D kinematic tracking system that can measure (for example) the trajectory of a person’s hand reaching to grasp an object, and a “Graspasaurus”, a response device consisting of a set of three-dimensional, aluminum forms mounted on a curved base and placed in front of the subject.

To conduct research on the neural mechanisms of pain regulation, Holroyd’s lab utilizes transcutaneous electrical nerve stimulation (TENS).

Our colleagues in Lifespan Development have also acquired a near-infrared spectroscopy (NIRS) set-up, which uses laser lights to measure activity in the outer part of the brain’s cortex.

Finally, the computational resources of the CABS group are continuously refreshed with research grant funding (mainly from federal agencies such as the Natural Sciences and Engineering Research Council of Canada. Students on the cutting edge can also take advantage of Westgrid, a high performance parallel computing facility that encompasses fourteen partner institutions across four provinces.”

Core faculty

: Professor
Cognitive neuropsychology : Assistant Teaching Professor
Neural bases of working memory, executive control, and decision making : Professor
Memory and cognition : Adjunct Professor
Computational modeling : Professor
Memory and cognition : Professor
Visual Object and Face Recognition

Affiliated faculty

: Associate Professor
Clinical Neuropsychology : Assistant Professor
Neuroimaging and neuropsychology Professor
Lifespan Development : Professor
Socio-cognitive development in childhood : Associate Professor
Lifespan Development .: Assistant Teaching Professor
Cognitive neuroscience and computational modeling : Professor
Cognitive and social development in infancy and childhood : Professor
Lifespan Development

• Kaitlyn Fallow
• Tom Ferguson
• Sepideh Heydari
• Eric Mah
• Morgan Teskey
• Emma Ullrich

Program philosophy on coursework

Our graduate program emphasizes collaborative research activities more than coursework. Courses are viewed as important to the extent that they are likely to help the student succeed as a scholar. Consequently, we offer courses that we believe will be of direct relevance and value for our students' research, and the program is designed to permit a good deal of flexibility regarding how and when university coursework requirements are met.

Recommended courses

Throughout each academic winter session (i.e., September through April), students are encouraged to participate in the weekly meetings of the Cognition and Brain Sciences Seminar (for which they can earn credit as PSYC 577). Seminar participants (faculty, graduate students, and selected undergraduate students) take turns hosting the meeting, typically by talking about their ongoing cognitive research. There are occasional guest speakers from other universities. This may well be the best seminar of its sort in Canada.

Students are also encouraged to consider PSYC 500, "Professional Development," which focuses on practical skills such as applying for research grants, working with institutional review boards (ethics committees), giving scholarly presentations, and getting your research published. We also recommend that students take PSYC 575, "Cognitive Psychology," which is a team-taught class focused on areas of particular interest to our faculty. Later in their studies, students may also benefit from PSYC 605, "Practicum in the Teaching of Psychology."

The Cognition and Brain Sciences Program also offers a variety of seminar-style courses in cognitive psychology (typically at least one per year, ideally one per semester), and graduate students in the program are expected to take whatever such courses are relevant to their interests and goals. Each of these courses has a quite general title, because the specific content of the course varies over the years (such that students might take a given course [e.g., 576B] in two different years with different content being covered each time).

• PSYC 511: Perception
• PSYC 576 A: Memory
• PSYC 576 B: Computational Modelling
• PSYC 576 C: Mind and Brain
• PSYC 576 D: Attention

Students interested in brain science may wish to take PSYC 574: Electroencephalography and Event-related Brain Potentials and PSYC 579: fMRI Theory and Methods

In addition, special-interest courses are occasionally put together in response to student demand. For example, Mike Masson recently offered a grad seminar on Bayesian analyses that will provide an alternative to null-hypothesis-significance testing. (A course such as that one could also be used toward the Methods and Statistics requirement). As another example, a few years ago a group of graduate students got together and developed their own syllabus for a course of readings and discussions on the nature of consciousness, for which they earned course credit.

Other relevant Psychology courses

Social cognition courses

There are a variety of courses in the domain of social cognition that may be of interest to CABS students (e.g., PSYC 521: Human Motivation PSYC 523: Psychology and Law PSYC 531: Environmental Psychology).

Neuropsych courses

• PSYC 540 (History and Theory in Neuropsychology)
• PSYC 541 (Research Design and Methods in Neuropsychology)
• PSYC 543 (Human Neuroanatomy)
• PSYC 548 (Special Topics in Neuropsychology)
• PSYC 550 (Physiological Psychology: Introduction)
• PSYC 551 (Neuropsychopharmacology)
• PSYC 552 (Special Topics in Physiological Psychology)

Developmental courses

• PSYC 562 (Infancy and Childhood)
• PSYC 565 (Cognitive Development in Adulthood and Aging)
• PSYC 571 (Developmental Psycholinguistics)

This is not a complete list, but serves to highlight the sorts of courses UVic offers that may be useful for students in the Cognition and Brain Sciences Program.

Coursework requirements for MA/MSc students

Students must satisfactorily complete at least 15 units, of which at least 12 units must be classified as graduate-level work (i.e., courses numbered 500 and above). A typical one-semester course meeting for 3 hours per week is worth 1.5 units. The program must include the following:

At least 1.5 units of PSYC 502 (Research Apprenticeship, which consists of doing research with collaborative supervision by your adviser and/or another faculty member usually our students do more than 1.5 units of this [max = 4.5 units per year]).

At least 1.5 units of PSYC 504 (Individual Study, which is essentially a more advanced version of 502 -- that is, doing research with collaborative supervision by your adviser and/or another faculty member usually our students do more than 1.5 units of this [max = 6 units per year]).

At least 3.0 units of approved statistics courses. Typically these are selected from the following:

• PSYC 513: Quantitative Analysis
• PSYC 517: Research Methods in Psychology
• PSYC 532: Applied Multiple Regression
• PSYC 533: Applied Multivariate Analysis
• PSYC 534: Univariate Design and Analysis
• PSYC 561: Theories and Methods in Lifespan Development
• PSYC 564: Statistical Methods in Lifespan Development

The important thing is to take the statistics classes that will give you the tools you need to do the research you want to do.

At least 3.0 units of PSYC 599 (Thesis), including successfully defending a Master's thesis. (Our students typically earn 6.0 units for PSYC 599.)

Students whose undergraduate background is judged to be incomplete may also be required to demonstrate competence (e.g., by succeeding in an appropriate course or passing an exam) in certain areas of psychology this would be negotiated when an offer of admission is made.

Students are to consult with their supervisor regarding which courses (within the general requirements described above) they should take to complete their requirements.

Coursework requirements for PhD students

Students must satisfactorily complete at least 30 units of post-Master's coursework. Of the last 15 units of coursework for the Doctoral degree, not more than 6 units may be derived from undergraduate courses (i.e., all or most must be graduate-level courses). A typical one-semester course meeting for 3 hours per week is worth 1.5 units. The program must include the following:

• At least 1.5 units of PSYC 602 (Independent Research max 6.0 units per year)
• At least 1.5 units of PSYC 604 (Individual Study max 6.0 units per year)
• At least 1.5 units of PSYC 576A, B, C, or D.
• Registration in PSYC 577 each year.
• At least 3.0 units of approved statistics and/or research methods courses. Statistics courses include those listed under the Master's requirements. Methods classes of particular relevance to CABS students include PSYC 574A (EEG/ERP), PSYC 574B (fMRI), and PSYC 574C (Computational Modeling).
• At least 15.0 units of PSYC 699 (Dissertation), including successfully defending a Doctoral dissertation. (Max = 30 units, typically across 2 or 3 years.)

Students are to consult with their supervisor regarding which courses (within the general requirements described above) they should take to complete their requirements.

Faculty in the Cognition and Brain Science Program are committed to fully supporting our graduate students through various funding sources including research fellowships, teaching stipends, and scholarships. Each student is guaranteed a minimum of \$17,500/year for five years most students get more than this

This level of funding is sufficient for a person to get by in Victoria (even after paying tuition). The sources of this support will vary from student to student and from year to year. Those sources include (a) research assistantships (typically, this consists of getting paid to do cool research with your supervisor), (b) teaching assistantships (typically limited to no more than 10 hours per week, starting at about \$20/hour), and (c) scholarships. These sources of support can often be combined to produce income over the \$17,500 minimum (although there are certain limitations on how funds can be combined).

Students with major postgraduate scholarship and fellowships also receive a \$4,000 top-up from UVic (for NSERC, SSHRC, and CIHR scholarships \$2,000 top-up for some other major scholarships). For example, a student with a \$17,500 Canadian Graduate Scholarship C from NSERC would get an additional \$4,000 from UVic (roughly equivalent to having tuition paid). It's often possible for students with such scholarships to further supplement their incomes by working as Teaching Assistants.

Faculty in the Cognition and Brain Sciences Program provide grad students with workspace and basic work tools. We also often cover part of the costs of attending conferences at which the student presents or co-authors present research (and UVic's Faculty of Graduate Studies provides up to \$600/year to support conference travel).

Cognition and action

When you hear a sentence describing someone interacting with an object or simply read a word that is the name of some object that you can manipulate with your hand, parts of the brain responsible for motor planning and actions become active.

Professors Daniel Bub and Michael Masson are examining the nature of hand action representations that become active when processing language or viewing objects that are associated with hand actions. They are particularly interested in the role that these motor-based representations play in understanding language or enabling efficient identification of objects.

They are also measuring subtle aspects of actual reach and grasp actions and the way in which these actions are influenced by context and prior experience. By using motion-monitoring equipment, they are able to detect very small differences in hand shape and trajectory that can reveal important changes in brain states that govern the interface between cognition and action.

Reinforcement learning, errors and decision making

You know that feeling you get when you are about to do something risky? Or the feeling when you realize that something you just did wasn't optimal?

Maybe you gambled some money you couldn’t afford to lose, or you threw a dirty look at some scary-looking thug and almost immediately you just KNEW that it wasn't the best thing to do. These examples suggest the importance of both predicting and evaluating outcomes in learning and decision making.

Reinforcement learning provides a powerful computational framework for understanding these processes in the mind and brain.According to this view, our choices are guided by the prediction of expected outcomes, followed by an evaluation of the difference between those predictions and the actual reward or punishment we experience (i.e. prediction errors). Recent research suggests a central role for the dopamine system (including the substantia nigra, basal ganglia, anterior cingulate, and related brain areas) in implementing reinforcement learning in the human brain. Clay Holroyd, Adam Krawitz, and their co-workers combine studies of event-related potentials and functional MRI with computational modeling and more traditional behavioural studies to develop and test theories of how reinforcement learning guides decision making and action selection.

Cognitive Control and Working Memory

Some behaviors are instinctual and stimulus driven – if someone throws a ball at your face, you will put your hands up and duck down in an instant. Some behaviors are so well learned they require nary a thought – you can walk down the street without focusing on how to place each foot in front of the other.

But many of our most interesting and uniquely human behaviors require active attention and control, particularly as we are first learning them – say, baking chocolate-chip cookies. These goal-driven activities require top-down processes, cognitive control, to overcome our impulses – why not just eat the batter? – and the maintenance and updating of temporary information, working memory, to track our progress – better remember you’ve added the butter, but not the flour.

Brain areas that are centrally involved in these processes include the dorsolateral prefrontal cortex and the anterior cingulate. Clay Holroyd, Adam Krawitz, and colleagues apply converging methods, including event-related potentials, functional brain-imaging, computational modeling, and behavioral experimentation, to understand the mental and neural bases of cognitive control and working memory. One central issue they are addressing is understanding how we learn when to apply control, with reinforcement learning playing an important role. A second central issue is explaining how these control systems interact with other systems in the brain, including the medial-temporal lobe system for spatial processing, and the limbic system for emotion.

In related work, Michael Masson is examining episodic influences on cognitive control, and more specifically how recent experiences change the efficiency of switching from performing one skilled task to another. Mike uses behavioural methods and tracking of eye movements during task performance to undercover the cognitive mechanisms that enable or interfere with smooth task transitions.

From visual input to meaning

When you look at an object (e.g., a coffee cup), a two-dimensional pattern of light falls on your retinas (the sensory surface inside your eyes). Almost instantly, you perceive the object and can access a wide variety of kinds of knowledge about it (what it's called, what it's used for, what it feels like and how heavy it is, etc.).

How do you do this? How are the various kinds of knowledge linked together? How and why does the system sometimes break down?

Anchored chiefly by Prof. Daniel Bub, several faculty and graduate students at UVic apply cognitive and neuroscience approaches to study object recognition and face perception in healthy individuals and in special populations such as agnosics, alexics, and children with Asperger's syndrome.

Visual expertise

To most of us, a rose is a rose is a rose, but to a keen horticulturalist it may be a Double Blush Burnet Spinosissima.

Research by Prof. Jim Tanaka reveals that experts in a domain differ from novices not only in how they name objects within that domain, but also in how they see them. For example, one line of studies discovered differences in visual processing between bird-watching afficionados and people who aren't bird experts when viewing pictures of birds. Jim's research on visual expertise combines Event-Related Potentials (ERPs), behavioural measures, computational modeling.

A particularly interesting domain in which Jim has studied visual expertise is face perception. Most people are "face-perception experts," but children diagnosed with autism or Asperger's syndrome may not develop expertise in face perception. Jim and his students and colleagues are working on programs designed to help such children improve their face-perceiving expertise.

Memory in action: basic theory

Most people think of memory as being akin to a library or storehouse, in which a record of each past experience is filed in a discrete little package, and of remembering as a matter of locating and playing back the appropriate record.

Cognitive psychologists know that memory is much more than, and much different from, such a storehouse. For one thing, virtually every aspect of human behaviour and experience (from ice skating to getting a joke to solving a math problem to enjoying a piece of music) relies on and reflects the use of memory. For another, people are often influenced by memories of particular past episodes without being consciously aware of remembering (as in cases of involuntary plagiarism), and they sometimes have the subjective experience of remembering past episodes that they never in fact experienced (as in deja vu or various false memory phenomena).

Much of the research conducted by Profs. Mike Masson and Steve Lindsay and their students and collaborators focuses on understanding how memory (both with and without awareness) works.

Memory in action: applied domains

In the past decade, memory has emerged as perhaps the most controversially relevant area of cognitive psychology.

As one example, the debate about recovered memories of childhood sexual abuse created a huge stir in the popular media as well as in professional psychology, and Steve Lindsay and Don Read have been actively engaged in that controversy since the early 1990s. As another example, the development of DNA testing has led to the realization that false convictions occur frighteningly frequently (e.g., the US National Institute of Justice estimates that as many as 10% of the hundreds of thousands of inmates in US jails are innocent of the charges for which they were imprisoned), and faulty eyewitness identification evidence appears to play a huge role in false convictions.

Don Read is one of Canada's foremost researchers in the area of eyewitness identification, and in recent years he and Steve Lindsay have been collaborating on research on that topic (see also Affiliated Member Elizabeth Brimacombe). At a more general level, perhaps the broadest application of the study of memory is research on autobiographical memory (i.e., individuals' reminiscences and beliefs about their own personal histories), and this too is another active research area in Steve's lab at UVic.

Cognitive development

You started out as a baby, now you're an adult. How'd you do that?

Babies are more cognitively skilled than once was thought, but breathtakingly huge developments in cognitive complexity and sophistication are accomplished between birth and adulthood.

Chris Lalonde is particularly interested in developmental changes in children's ability to think about their own and others' mental states and beliefs (including beliefs about their own self identities). Although development is not his focus, Steve Lindsay occasionally collaborates on research on children's ability to differentiate between mental experiences with different sources (e.g., between memories and fantasies, or memories of an actual experience vs. memories of what someone else said about that experience).

Graduate students in the Cognition and Brain Sciences Program are provided with one or more computers for their work. The University also offers a number of up-to-date facilities and services for computing. We provide licences for major statistical packages (e.g., SPSS and Systat). Programming languages and other specialized software (e.g., MATLAB, Visual Basic, E-Prime) are also available in individual faculty labs.

As noted above, the Cognition and Brain Sciences group uses a wide variety of methods, including electroencephalography (“brain waves”), MRI, eye tracking, kinematic tracking, and computational modeling. Through collaborations, several of our faculty also draw on other methods such as endocrinology (e.g., stress hormones) and genetic analyses.

Research methods

Our primary research method involves the use of experimental designs to test hypothesis. Many of our studies involve computer-controlled presentations of visual and/or auditory stimuli and electronic measures of responses (e.g., key press, voice key, eye movements, measurement of brain activity).

But our methods are not narrowly restricted to highly controlled laboratory experiments. For example, Daniel Bub's research often involves exploratory observational work (as well as formal experiments) with individuals who have suffered various kinds of brain damage.

Steve Lindsay has used survey methods to explore adults' recollections of long-past autobiographical events.

Clay Holroyd, Adam Krawitz, and Mike Masson use computer simulations to articulate and refine theoretical models (computational cognitive neuroscience).

As experimental psychologists, we are committed to the idea that experiments are the most compelling way to test hypotheses, but we also believe that observational and correlational research can play key roles in helping to understand psychological phenomena and in formulating hypotheses for subsequent experimental tests.

Basic research facilities

Each faculty member in the Cognition and Brain Science Program has a microcomputer-based laboratory for data collection, data analysis, and computational modeling. In addition, the group collectively holds a variety of other specialized equipment and software (e.g., state-of-the-art eye tracking and 3-D kinematics). We also have connections with medical facilities that provide opportunities for research with neurological cases.

Graduate students in the program are provided with office space and shared access to laboratory facilities. To the extent that funds allow, graduate students receive support for attending conferences for presentations of their collaborative research with faculty.

Brain imaging

Jim Tanaka having his brain waves recorded.

Clay Holroyd and Jim Tanaka run the Brain and Cognition Event-related Potential Laboratory, which houses 4 state-of-the-art 64-channel systems for recording and analyzing the electroencephalogram (i.e., “brainwaves”). Holroyd’s EEG research focuses on the neural mechanisms of learning and cognitive control and Tanaka’s lab explores how experience, culture and biology converge to shape that way we perceive the world. Each year Holroyd teaches a graduate course on this technique and students from multiple labs utilize the facility for their own research.

CABS members Holroyd, Krawitz and Lindsay, and affiliated faculty Gawryluk, Medler and MacDonald all have experience using functional magnetic resonance imaging (MRI), with many of their studies published in high-impact journals. Faculty currently maintain collaborative contracts to access magnetic resonance imaging (MRI) resources with both West Coast Medical Imaging and Island Health. Our data is primarily collected on a 3T MRI scanner with functional magnetic resonance imaging, diffusion tensor imaging, and high resolution anatomical acquisitions. With a growing interest from students and faculty in these techniques, we are actively working on building neuroimaging capacity and commonly offer courses on how to analyze MRI based data.

Our colleagues in Lifespan Development have also acquired a near-infrared spectroscopy (NIRS) set-up, which uses laser lights to measure activity in the outer part of the brain’s cortex.

Statistical expertise and resources

Our group has substantial statistical/quantitative sophistication. In particular, Clay Holroyd, Adam Krawitz, and Mike Masson all have advanced quantitative skills, and Tony Marley is a mathematical psychologist. Stuart MacDonald, Associate Professor of Psychology in the Lifespan Development program, is also available for consultation on statistical issues.

Social Cognitive Theory: Concept and Applications | Theories | Psychology

In this article we will discuss about:- 1. Concept of Social Cognitive Theory 2. Identification, Self-Efficacy of Social Cognitive Theory 3. Central Idea 4. Applications.

Concept of Social Cognitive Theory:

Social cognitive theory, used in psychology, education, and communication, posits that portions of an individual’s knowledge acquisition can be directly related to observing others within the context of social interactions, experiences, and outside media influences. In other words, people do not learn new behaviors solely by trying them and either succeeding or failing, but rather, the survival of humanity is dependent upon the replication of the actions of others.

Depending on whether people are rewarded or punished for their behavior and the outcome of the behavior, that behavior may be modeled. Further, media provide models for a vast array of people in many different environmental settings.

Social cognitive theory is a learning theory based on the ideas that people learn by watching what others do and will not do, these processes are central to understanding personality. While social cognitists agree that there is a fair amount of influence on development generated by learned behavior displayed in the environment in which one grows up, they believe that the individual person (and therefore cognition) is just as important in determining moral development.

People learn by observing others, with the environment, behavior, and cognition all as the chief factors in influencing development. These three factors are not static or independent elements rather, they influence each other in a process of triadic reciprocal determinism.

For example, each behavior witnessed can change a person’s way of thinking (cognition). Similarly, the environment one is raised in may influence later behaviors, just as a father’s mindset (also cognition) will determine the environment in which his children are raised.

It is important to note that learning can occur without a change in behavior. According to J.E. Ormrod’s general principles of social learning, while a visible change in behavior is the most common proof of learning, it is not absolutely necessary. Social learning theorists say that because people can learn through observation alone, their learning may not necessarily be shown in their performance.

Observation of Models:

Social cognitive theory revolves around the process of knowledge acquisition or learning directly correlated to the observation of models. The models can be those of an interpersonal imitation or media sources. Effective modeling teaches general rules and strategies for dealing with different situations.

To illustrate that people learn from watching others, Albert Bandura and his colleagues constructed a series of experiments using a Bobo doll. In the first experiment, children were exposed to either an aggressive or non- aggressive model of either the same sex or opposite sex as the child.

There was also a control group. The aggressive models played with the Bobo doll in an aggressive manner, while the non-aggressive models played with other toys. They found that children who were exposed to the aggressive models performed more aggressive actions toward the Bobo doll afterward, and that boys were more likely to do so than girls.

Following that study, in order to test whether the same was true for models presented through media, Albert Bandura constructed an experiment entitled “Bobo Doll Behavior: A Study of Aggression.” In this experiment Bandura exposed a group of children to a video featuring violent and aggressive action. After the video he then placed the children in a room with a Bobo doll to see how they behaved with it.

Through this experiment, Bandura discovered that children who had watched the violent video subjected the dolls to more aggressive and violent behavior, while children not exposed to the video did not.

This experiment displays the social cognitive theory because it depicts how people reenact behaviors they see in the media. In this case, the children in this experiment reenacted the model of violence they directly learned from the video.

As a result of the observations the reinforcement explains that the observer does not expect actual rewards or punishments but anticipates similar outcomes to his/her imitated behaviors and allows for these effects to work. This portion of social cognitive theory relies heavily on outcome expectancies. These expectancies are heavily influenced by the environment that the observer grows up in

for example, the expected consequences for a DUI (Driving in influence) in the United States of America are a fine, with possible jail time, whereas the same charge in another country might lead to the infliction of the death penalty.

In education, teachers play the role as model in a child’s learning acquisition. Teachers model both material objectives and underlying curriculum of virtuous living. Teachers should also be dedicated to the building of high self-efficacy levels in their students by recognizing their accomplishments.

Identification, Self-Efficacy of Social Cognitive Theory:

Albert Bandura also stressed that the easiest way to display moral development would be via the consideration of multiple factors, be they social, cognitive, or environmental. The relationship between the aforementioned three factors provides even more insight into the complex concept that is morality.

Further development in social cognitive theory posits that learning will most likely occur if there is a close identification between the observer and the model and if the observer also has a good deal of self-efficacy. Self- efficacy beliefs function as an important set of proximal determinants of human motivation, affect, and action which operate on action through motivational, cognitive, and affective intervening processes.

Identification allows the observer to feel a one-to-one connection with the individual being imitated and will be more likely to achieve those imitations if the observer feels that they have the ability to follow through with the imitated action.

Self-efficacy has also been used to predict behavior in various health related situations such as weight loss, quitting smoking, and recovery from heart attack. In relation to exercise science, self-efficacy has produced some of the most consistent results revealing an increase in participation in exercise as self-efficacy increases.

Vicarious Learning: Central Idea of Social Cognitive Theory:

Vicarious learning, or the process of learning from other people’s behavior, is a central idea of social cognitive theory and self-efficacy. This idea asserts, that individuals can witness observed behaviors of others and then reproduce the same actions. As a result of this, individuals refrain from making mistakes and can perform behaviors better if they see individuals complete them successfully.

Vicarious learning is a part of social modeling which is one of the four means to increase self-efficacy. Social modeling refers not just to observe behavior but also to receiving instruction and guidance of how to complete a behavior.

The other three methods include, mastery experience, improving physical and emotional states and verbal persuasion. Mastery experience is a process in which the therapist or interventionist facilitates the success of an individual by achieving simple incremental goals.

With the achievement of simple tasks, more complex objectives are introduced. The person essentially masters a behavior step by step. Improving physical and emotional states refers to ensuring a person is rested and relaxed prior to attempting a new behavior. The less relaxed, the less patient, the more likely the goal behavior will not be attained. Finally, verbal persuasion is providing encouragement for a person to complete a task or achieve a certain behavior.

Applications of Social Cognitive Theory:

Social cognitive theory is applied today in many different areas:

The use of celebrities to endorse and introduce any number of products to certain demographics: one way in which social cognitive theory encompasses all four of these domains, campaigns.

Aids which are issued in the favour of public like warning against drinking , smoking etc. are generally given by celebrities because of their charm in society, public enjoys following their footsteps.

Luo-Rudy dynamic model

To make a model cell alive, it needs the ion pumps to maintain the intracellular ion balance, i.e., the ions must return back after the firing of an action potential. In one shot of action potential, potassium ions leave out of the cell, but sodium ions get into the cell. Moreover, calcium ions get into the cells from the extracellular space and sarcoplasmic reticulum for muscle contraction, an important feature for human heart. So, ion pumps are required in the membranes of cell and sarcoplasmic reticulum to maintain the ion balance inside the cell. Fortunately, huge amount of experimental data have been published for cardiac cells in 1980s, even not for formulism. Dr. Luo screened and integrated those data together to be formulated as the components of the cardiac model cell.

In 1991, the most arguing issue to formulate a live cardiac cell model was the ambiguity of the calcium ion channels. Several famous labs announced the calcium ion channels but they were quite scattering with apparent differences, including species. Dr. Luo made a decision to skip the debate issue but, instead, put them all into the cell model to see how action potentials look like by using those published experimental data for calcium ion channels, especially sodium-calcium exchangers. It left the choice for scientists to pick up the calcium ion channels they wanted even Dr. Luo had suggestions in the Luo-Rudy dynamic model published in 1994.

Luo-Rudy dynamic model in 1994 not only includes the sodium and potassium channels in Luo-Rudy passive model but also introduces sodium-potassium pump, calcium pump, L-type calcium channel, non-specific calcium-activated channel, sodium-calcium exchanger on the membrane as well as calcium-induced calcium release channel and calcium pump on the membrane of sarcoplasmic reticulum with calcium buffers in the myoplasm.

For heart muscle contraction, a single heart cell is stimulated to raise the intracellular potential from the resting -80 mV to about +40 mV by flowing positive sodium ions due to the opening of the sodium channel. Such a potential rising is called depolarization. Sodium channel is closed very quickly (in 2 msec), then the opening of potassium and calcium channels fight against to maintain the intracellular potential at the positive level called the potential plateau for 200-300 msec. Potassium ions flows out of the cell but calcium ions flows into the cell to maintain such a high plateau potential moreover, the input of the extracellular calcium ions raises the intracellular calcium level up to a threshold to incite the spike calcium release from sarcoplasmic reticulum for cell contraction. Finally, potassium ion efflux brings the potential down to the resting level, called repolarization. The potential variation procedure from depolarization, plateau, to repolarization is called an action potential. Sodium-potassium pump and calcium pump keep working to return all the ions back their origin pools during or after an action potential. If keeping firing the action potential, the intracellular ion concentration will lose the balance gradually and it also takes more time for ion pumps to recover the steady status.

Modeling plateau potentials - Psychology

Embedded Ensemble Encoding (EEE)

This repo is for the detailed cell model CA229. It includes the simulation, analysis and plotting files to generate paper figures. The code is in python version 3.6 and using NEURON version 7.4, 7.5, or 7.6.

CA229.py - python class with all the cell membrane properties (the Geometry and 3d shape is defined in this python class as well --- for better usage in network or NetPyNE)

The ratio of sodium, calcium, A-type potassium and calcium activated potassium channels can be adjusted by call the class with different ratio parameters. For example,

Using all the default value in cell1

Setting the channel conductances to 50% of the default value in cell2

compile.py - compile all the mod files in folder: mod

analysis_utils.py - calculating the plateau amplitude, plateau duration, interspike interval and number of spikes of the voltage traces generated by model simulation.

utils.py - to save figures and simulation results in a folder with name of today's date or self-defined folder.

Fig2_bAP_exp.py - Inject current in soma and record the voltage traces at different locations on all basal dendrites. All the parameters and traces are saved in json file for further analysis.

Fig2_bAP_anaPlot.py - Load the data generated by Fig2_bAP_exp.py and measure the peak amplitude and latency. Plot all the data.

Fig3_exp_dms.py, Fig3_exp_major.py - Code to add AMPA and NMDA receptors on basal[34] - It will generate figures and json files to store the voltage traces - Modify the parameters in "main" to choose the input strength - "random_2" function is used to generate random activation time within a certain range. The seed is locked for now to get consistent results. - "random_beta" function is used to generate alpha random activation time within a certain range. The seed is locked for now to get consistent results.

Fig3_dms_trace_plot.py, Fig3_major_trace_plot.py - Generate trace plots in Fig 3. A2 and B2

Fig3_trace_analysis.py - Analyze the recorded traces and plot the plateau amplitude, duration and spikes per plateau against different input strength.

Fig5_exp_DMS.py, Fig5_exp_major.py
- batch simulation of glutamate input locations range from 0.1-0.9 (step size 0.1) on 6 different basal branches. At each branch and each location, there is also normal and TTX conditions. All the simulation results are saved into json files under each subfolder. - The data for generating paper fig5 are saved in subfolder("/Fig5/DMS or /Fig5/major")

Fig5_ana_DMS.py, Fig5_ana_major.py, Fig5_plot_DMS.py, Fig5_plot_major.py
- Analyze and plot the somatic plateau amplitude, dendritic plateau amplitude, plateau duration and spike numbers against the input distance from soma on basal dendrite.

Compile mod files: python compile.py

Fig 2.B2 and B3 (the study of backpropagated action potential)

Run: "Fig2_bAP_exp.py" run the simulation and save the data in folder "Fig2/" This step take

Fig 3. A2 and B2 - Trace plots

Run: "Fig3_exp_dms.py" or "Fig3_exp_major.py" run the simulation and save the data in folder "Fig3/DMS/Plot/" or "Fig3/Major/Plot/" This step take

Fig 3. D1 - D3 - analysis plots

Open "Fig3_exp_dms.py", add # before the code at line 77, remove # before the code in line 78 add # before the code at line 254, remove # before the code in line 256. This step take

Run: "Fig5_exp_DMS.py" or "Fig5_exp_major.py" Run the simulation and save json data in folder "Fig5/DMS/" or "Fig5/major/". This step take

NOTE: in all the "exp" files, the parameters can be adjusted in "main" manually, eg. Fig3_exp_dms.py (change number pool1 of synaptic AMPARs and NMDARs change number pool 2 of exsyantpic NMDARs change Beta and Cdur of NMDARs change of stimulation location change of syanptic weights change of stimuation locations)

Peng Penny Gao

Joe W Graham, Sergio L Angulo, Salvador Dura-Bernal, Michael L Hines, William W Lytton, Srdjan D Antic

INTRODUCTION

Midbrain dopamine neurons, which are involved in motivation and the control of movement, have been implicated in various pathologies such as Parkinson's disease (Bernheimer et al. 1973), schizophrenia (Weinberger et al. 1987), and drug abuse (Koob et al. 1987). As a result, considerable effort has been devoted to the study of dopamine signaling. The firing pattern in these neurons influences the extracellular concentration of dopamine in projection areas, and a burst firing pattern produces a greater transient increase in dopamine concentration than a tonic one (Chergui et al. 1996 Gonon 1988 Heien and Wightman 2006). Bursts in dopamine neurons are thought to convey signals pertaining to reward prediction and attribution of salience (Schultz 2006). An understanding of dopaminergic signaling must include an appreciation of how the firing pattern is regulated.

Dopamine (DA) neurons in the presence of their afferent inputs in vivo can exhibit one of several firing modes: silence, regular single-spike firing, irregular single-spike firing, and bursting (Grace and Bunney 1984a,b Hyland et al. 2002). By contrast, dopamine neurons in brain slice preparations exhibit a homogeneous pacemaker-like firing pattern that appears to result from an intrinsic slow oscillatory potential (SOP) (Fujimura and Matsuda 1989 Harris et al. 1989 Kang and Kitai 1993a Yung et al. 1991). Local application of the selective SK channel blocker apamin converts the SOP to an oscillatory plateau potential resembling a square wave. Apamin, applied in the absence of tetrodotoxin (TTX), induces bursting activity that is driven by these plateau oscillations (Ping and Shepard 1996). Johnson and Wu (2004) replicated these results and were also able to convert pacemaker firing to bursting by the application of Bay-K-8644 [3-pyridinecarboxylic acid (1,4-dihydro-2,6-dimethyl-5-nitro-4-(2-(trifluoromethyl)phenyl) methyl ester], which potentiates the opening of L-type Ca 2+ channels (Nowycky et al. 1985). In some cases, application of apamin in the absence of TTX induced irregular firing instead of bursting (Ping and Shepard 1996), but if a small applied current was injected, bursting could be established (Johnson and Wu 2004). The bursting observed in the two studies was qualitatively similar, with slow spiking during the trough of the oscillation that accelerates and diminishes in amplitude during the upstroke of the plateau. Spiking often ceases during the plateau, presumably as a result of inactivation of fast Na + channels. Plateau potentials similar to those observed in vitro may underlie burst firing in vivo as a result of endogenous neuromodulators acting to restrict access of the small-conductance (SK) channel to intracellular calcium (Brodie et al. 1999 Fiorillo and Williams 2000 Paladini et al. 2001) or by second-messenger cascades that alter the affinity of the channel for Ca 2+ (Allen et al. 2007 Bildl et al. 2004).

Nifedipine blocks the plateau potential oscillations (Johnson and Wu 2004 Nedergaard et al. 1993 Shepard and Stump 1999). Thus it appears that the L-type calcium channel is responsible not only for the depolarizing phase of the SOP (Mercuri et al. 1994 Nedergaard et al. 1993), but also for the plateau potentials. Although the mechanism responsible for terminating the bursting plateau potentials observed in apamin has yet to be established, it could involve cytosolic Ca 2+ -dependent or -independent mechanisms. Potential cytosolic Ca 2+ -dependent candidates include the Ca 2+ -dependent inactivation of a Ca 2+ current, an electrogenic Ca 2+ pump, apamin-insensitive Ca +2 -activated K channel, or Ca 2+ -activated chloride channel. Alternatively, recent studies by Nedergaard (2004) suggest that a slow, cytosolic calcium-independent outward current resembling an ether-a-go-go–related gene (ERG) current might be involved in termination of plateau potentials. Additional evidence for the presence of this current is the clear ERG1 antibody labeling observed in the substantia nigra pars compacta (SNC Papa et al. 2003). Notably, ERG currents in the heart and CNS are potently blocked by a wide variety of antipsychotic drugs including haloperidol (Kongsamut et al. 2002 Suessbrich et al. 1997). In the present study, an experimental approach was used to assess the contribution of cytosolic Ca 2+ -dependent mechanisms to termination of plateau potential oscillations exhibited by DA neurons. In addition, we incorporated an ERG conductance into an existing computational model of oscillatory activity (Amini et al. 1999) to determine whether the kinetics of the conductance is consistent with its hypothesized role in terminating the plateau potentials. Furthermore, we examined both the sequential kinetic scheme postulated for the ERG current and an independent kinetic scheme with a similar steady-state open fraction to determine the unique contribution of the unusual sequential kinetic scheme.

Sexual Response Model - Master’s and Johnson’s Four-Phase Model

Before the sixties, sex was a topic that was considered taboo to talk about, and with little discussion about sex there was no information on sexual responses for either sexes during this time. That was until Williams Masters and Virginia Johnson decided it was time for the world to understand how our bodies work sexually. According to NPR (2013) the duo changed history,

“ William Masters and Virginia Johnson became famous in the 1960s for their groundbreaking and controversial research into the physiology of human sexuality. Instead of just asking people about their sex lives, Masters and Johnson actually observed volunteers engaging in self-stimulation and sexual intercourse. Changes throughout their bodies during arousal were measured with medical equipment”.

The two wanted to understand exactly how the body worked with sexual responses, they were primarily interested in studying the biology of sexuality. With the research they conducted they discovered that there were 4 different phases that take place during these sexual activities. An online article done by OurBodiesOurSelves (2011) explains the model, “ The Masters and Johnson model outlined four stages of physiological arousal: excitement, plateau, orgasm, and resolution”. Both men and women experience these phases, although the timing will typically be different between the male and female.

The first phase to take place is excitement, which can last from a few minutes to several hours. The general characteristics of excitement can include increase muscle tension, the heartrate will rise, nipples become hardened and erect, and the penis becomes erected. The second phase to take place is called plateau, which extends the brink of orgasm. The general characteristics for plateau can range from muscle spasms, the women’s clitoris becomes highly sensitive, the man’s testicles are withdrawn up to the scrotum, and all the characteristics from excitement are intensified. After these two phases occur phase three will take over, also known as orgasm. The ClevelandClinc (2012) describes phase three as, “The climax of the sexual response cycle. It is the shortest of the phases and generally lasts only a few seconds”. The characteristics of an orgasm include involuntary muscle contractions, a forceful release of sexual tension, in women the muscles of the vagina contract, and for men contractions at the base of the penis which results in ejaculation. When the climax in sexual activity is reached you go into phase four also known as resolution. This phase is where all body functions return back to a normal state, the heartrate returns to a steady pace and erected body parts go back to their previous size and color.

During Masters and Johnsons studies they discovered that women and men had the same similarities when going through the four phases, but differentiated when it came to recovery after reaching orgasm. While women were able to experience multiple orgasms, and were able to have a rapid return to the orgasm phase, men will typically need more time to recover after. According to Crooks and Baur (2014), “After orgasm the male typically enters a refractory period-a time when no amount of additional stimulation will result in orgasm”.

Kaplan’s Sexual Response Model

Helen Singer Kaplan a noted sex therapist and author, created the three-stage model which is distinguished by its identification of desire as a prelude to sexual response. This three-stage model includes three stages: desire, excitement, and orgasm. Although very similar to Masters and Johnsons four phase model, Kaplan’s model focuses on the aspect of desire. In this model it plays a big part in sexual response, Crooks and Baur (2014) wrote,

“One of the most distinctive features of Kaplan’s model is that it includes desire as a distinct stage of the sexual response cycle. Many other writers, including Masters and Johnson, do not discuss aspects of sexual response that are separate from genital changes”.

Before reaching any physical and bodily changes in sexual response, desire will allow someone to become psychologically interested. Which describes the first stage in Kaplan’s model, which makes it different from Masters and Johnson’s model. Once you reach the stage of desire your body will then processed into the excitement stage, where arousal begins from both physical and psychologic stimulation. The general characteristics of this phase include increased heartrate, erect penis, and the clitoris becoming highly sensitive. After reaching excitement, you enter the final stage in Kaplan’s model: the resolution stage which resembles Masters and Johnsons third and fourth stage. Your body will reach its climax resulting in an orgasm, proceeding to resolution where the body returns to its normal state.

Modeling plateau potentials - Psychology

• Integrate and Fire digital neurons which emphisize simple dynamics and can be connected together to form larger systems.
• Conductance-level neuron models which use analog techniques to simulate the dynamics of individual cells.

The circuits below were simulated in Electronics Workbench and will be built as hardware models for students.

Analog conductance-level circuits

Maeda and Makino (1) show how to model a neuron using 3 transistors for a FitzHugh-Nagumo (FHN) type neuron (simplified from Hodgkin-Huxley formulation). The FitzHugh-Nagumo scheme replaces the fast Na current of the HH model with a simplified fast, depolarizing, activation process, and replaces the slow Na inactivation and slow, repolarizing, K current by a single slow inactivation process. By adding one more repolarizing process, modeled by two more transistors, they can produce a neuron with bursting behavior.

The circuit is show below for the FHN neuron. The circuit produces a constant train of simulated action potentials (AP) when a constant current is applied. The Electronics Workbench file is here. Note that the amplitude of the simulated action potential is much larger than that of a physiological neuron. Simulated AP amplitude is around 5 volts, while in real life the AP amplitude is around 100 mV.

The neuron can be made to oscillate without an external current source by adding RL shown below. The resistor acts as an inward current leak. The usefulll range of RL is about 25 kohms (fast oscillation) to around 250 kohms.

It is easy to voltage clamp these model neurons. The image below shows a 3 volt step applied from resting potential. A transient inward current is seen, followed by an outward current. EWB file.

The circuit is show below for the FHN neuron, extended with an extra conductance process. The circuit produces a constant train of simulated AP bursts when a constant current is applied. The Electronics Workbench file is here.

Maeda, Yagi, and Makino (2) extend the model to include heart cells. They slightly modified one of the repolarizing processes to make a plateau potential. The circuit show below shows two traces. The bottom trace is membrane potential, the top is the deritivive, which is a simple approximation of an ECG. The Electronics Workbench file is here. Be sure to set the integration method to Gear in the menu item
Analysis. Analysis Options. Transient . The example below uses the default trapzoidal method, which causes spurious oscillations.

By turning one of the neurons into a macro (FHNbuild below), we can build an axon to investigate extracellular versus intracellular recording. The 50 kohm resistors model the axonal lumen. The 100 ohm resistors model the bath saline. The subtractor just below the axon simulates a perfect differential amplifier. Note that the voltage scale on the bottom (extracellular) trace is 100 times more sensitive than the top trace. The specific model built is decribed below in the Construction section. The Electronics Workbench file is here.

As few as 3 sections, terminated with a passive load, can be used as a teaching model.

The basic FHN models don't have an explicit sodium inactivation, but for teaching voltage clamp techniques, it would be nice to have this process represented. The following circuit uses an RC combination on the power supply to the fast inward current to limit the current to a short burst. The length of the burst is determined by the size of the capacitor, here 1uf, and the membrane resistance. The refractory period is determined by the RC time constant, here 20 mSec. In clamp mode, if you change the 620 ohm resistor in either the fast inward or delayed outward current to 1 Mohm, then that current is essentially eliminated, simulating a selective block of the approriate channel. The two currrents can thus be seen separately. Workbench file.

Conductance Models based on Guy Roy's NeuroFET (3)

These models use analog computation, combined with N-channel, enhancement-mode, field-effect transistors, to simulate conductance changes in the membrane. The circuit is scaled so that the timing and magnitude of the conductance changes (and voltage changes) are biologically realistic. The battery V1 sets the leakage through Na channels at resting potential. A more positive value stabilizes the membrane, while more negative can cause oscillations. Electronics Workbench file.

Model Synapses

Modifying the depolarizing process channel to depend on presynaptic voltage (and changing the reveral potential) makes an excitatory synapse. Top trace is the presynaptic cell. Bottom trace shows postsynaptic cell with EPSP and AP. The diode in the synapse represents the isolation of the presynaptic side due to transmitter release. The Electronics Workbench file is here.

Modifying the repolarizing process channel to depend on presynaptic voltage makes an inhibitory synapse. Top trace is the presynaptic cell. Bottom trace shows postsynaptic cell with IPSP and AP. Note that this inhibitory synapse exhibits shunting as well as hyperpolarization. The Electronics Workbench file is here.

A burster cell was turned into a macro, then two of them were connected through inhibitory synapses. By adjusting the strength and time constant of the synapse, you can get alternate bursting. The Electronics Workbench file is here.

With four bursters, connected as two sets of alternate bursters, you can get 2:1 locking by adding an excitatory synapse between the two sets. The faster set was adjusted to have a natural burst rate just slightly slower than 2:1 lock. The excitatory synapse adds a little extra current to lock the frequency. The Electronics Workbench file is here.

The burst macro:

The Fburst macro:

Adding a diode and resistors between the two cells results in an electrotonic connection with a stronger connection from left to right. The traces show a very complex interaction between the two cells. Note that any given electrotonic synapse can be rectifying in either direction, or not at all. The Electronics Workbench file is here.

Integrate-and-fire circuits

The circuit below uses monostables (e.g. 74HC123) as integrate and fire (IF) neurons. The Q output is the AP pulse. The W output is an inverted AP pulse. The diode to the W output discharges simulated membrane capacitance when an AP occurs. The 25k/0.1 uF components attached to RT/CT and CT inputs set the length of the AP pulse. The neuron on the left is driving the neuron on the right with an excitatory connection. The Electronics Workbench file is here.

The circuit below connects 2 IF neurons with an inhibitory synapse. The monostable was added to stretch the pulse and invert it. A better version of an excitatory synapse (than the one shown above) would be to use the Q output of the synaptic monostable as the input to the second cell through a diode which allows current to from from the Q terminal to the second cell's input capacitor. The Electronics Workbench file is here.

The following circuit implements a IF burster by using a second monostable to inhibit the first one. The top two monostables are the burster. The bottom monostable is an weakly inhibited non-burster. The Electronics Workbench file is here.

Construction

To actually build one of the Maeda neurons, it is handy to simplify the power supplies so that only one battery is needed. Elimanating the simulated potassium battery required changing the sodium current threshold by adding a diode. The battery voltage was changed to 6 volts to make it easier to use lithium batteries. The RL resistor allows the circuit to act as a pacemaker. Replacing RL with a CdS photoresistor makes a photosensor with output frequency related to light intensity. Lower resistance is a faster pacer. The userful range of RL is about 25 kohm to 450 kohm. The expanded simulated scope image should be compared with the photograph of the real scope screen. The Electronics Workbench file is here. A picture of the white board prototype is included below.

Expanded simulation scope on the left and output from the real circuit.

A first hack at a curcuit board is shown below. Transistors are (from left to right) 2N3904, 2N3906, 2N3904. The diode is a 1N914. A battery holder is mounted on the back of the board. the two vias on the left side of the board are the only two connections to the outside world. Top left is inside the cell, bottom left is outside. The resistor marked *** sets the pacemaker rate. Omitting this resistor makes the circuit more like a squid axon element. ExpressPCB file.

Elizabeth M. Brannon

Dr. Brannon's research program examines the evolution and development of quantitative cognition. She studies how adult humans, infants, young children and nonhuman animals without language represent number. She uses behavioral techniques, event-related potentials, functional magnetic resonance imaging, and single-unit physiology to explore the cognitive and neural underpinnings of numerical cognition in nonhuman primates and throughout the human lifespan. A major current focus is to study how training the primitive number sense might facilitate mathematical abilities in children and adults.

DeWind, N.K., G.K. Adams, Platt, M.L. Brannon, E. M., (2015). Modeling the approximate number system Quantifying the contribution of visual stimulus features, Cognition, 142, 247-265.

Drucker, C., & Brannon, E. M. (2014). Rhesus monkeys (Macaca mulatta) map number onto space, Cognition, 132(1), 57-67. PMCID: PMC4031030.

Park, J., & Brannon, E. M. (2014). Improving arithmetic performance with number sense training: An investigation of underlying mechanism ,Cognition, 133(1), 188-200. NIHMSID: NIHMS614955.

Event-related potential

An event-related potential (ERP) is the measured brain response that is the direct result of a specific sensory, cognitive, or motor event. [1] More formally, it is any stereotyped electrophysiological response to a stimulus. The study of the brain in this way provides a noninvasive means of evaluating brain functioning.

ERPs are measured by means of electroencephalography (EEG). The magnetoencephalography (MEG) equivalent of ERP is the ERF, or event-related field. [2] Evoked potentials and induced potentials are subtypes of ERPs.

Cognition and Brain Sciences

The Cognition and Brain Sciences Program is actively seeking new graduate students. If you are interested in applying, please explore this site, including our Tips for Getting into Graduate School in Research Oriented Psychology.

To see some of the UVic campus, check out this virtual tour. For information about Victoria and its many attractions, visit UVic's About Victoria webpage.

The Cognition and Brain Sciences Program faculty and graduate students share interests in a range of interconnected topics.

Our goal is to understand the nature of the representations and processes that give rise to mental events, and the influence of memory for past mental events on subsequent experience and behaviour.

We adopt a variety of empirical approaches to this enterprise, including naturalistic studies of children and adults, experiments conducted in laboratory contexts, brain imaging, case studies of brain-damaged patients, and computational modeling.

We are a closely integrated group, and we often work together on collaborative research enterprises. Every one of our faculty has an active, productive lab in which graduate students are conducting and publishing new research on current topics. Our faculty are major players in the world of cognitive and brain science, as indicated by their grants, journal editorships, leadership positions in large professional organizations, etc..

Resources

The Cognition and Brain Sciences Program brings a wide range of tools to bear on the study of the brain/mind in action.

Clay Holroyd and Jim Tanaka run the Brain and Cognition Event-related Potential Laboratory, which houses 4 state-of-the-art 64-channel systems for recording and analyzing the electroencephalogram (i.e., “brainwaves”). Holroyd’s EEG research focuses on the neural mechanisms of learning and cognitive control and Tanaka’s lab explores how experience, culture and biology converge to shape that way we perceive the world. Each year Holroyd teaches a graduate course on this technique and students from multiple labs utilize the facility for their own research.

CABS members Holroyd, Lindsay, and Krawitz and affiliated faculty Gawryluk, Medler and MacDonald all have experience using functional magnetic resonance imaging (MRI), with many of these studies published in high-impact journals. Faculty currently maintain collaborative contracts to access magnetic resonance imaging (MRI) resources with both West Coast Medical Imaging and Island Health. Our data is primarily collected on a 3T MRI scanner with functional magnetic resonance imaging, diffusion tensor imaging, and high resolution anatomical acquisitions. With a growing interest from students and faculty in these techniques, we are actively working on building neuroimaging capacity and commonly offer courses on how to analyze MRI based data.

Mike Masson and Daniel Bub utilize an eye-tracking system that yields real-time measures of what subjects are looking at moment to moment, a 3-D kinematic tracking system that can measure (for example) the trajectory of a person’s hand reaching to grasp an object, and a “Graspasaurus”, a response device consisting of a set of three-dimensional, aluminum forms mounted on a curved base and placed in front of the subject.

To conduct research on the neural mechanisms of pain regulation, Holroyd’s lab utilizes transcutaneous electrical nerve stimulation (TENS).

Our colleagues in Lifespan Development have also acquired a near-infrared spectroscopy (NIRS) set-up, which uses laser lights to measure activity in the outer part of the brain’s cortex.

Finally, the computational resources of the CABS group are continuously refreshed with research grant funding (mainly from federal agencies such as the Natural Sciences and Engineering Research Council of Canada. Students on the cutting edge can also take advantage of Westgrid, a high performance parallel computing facility that encompasses fourteen partner institutions across four provinces.”

Core faculty

: Professor
Cognitive neuropsychology : Assistant Teaching Professor
Neural bases of working memory, executive control, and decision making : Professor
Memory and cognition : Adjunct Professor
Computational modeling : Professor
Memory and cognition : Professor
Visual Object and Face Recognition

Affiliated faculty

: Associate Professor
Clinical Neuropsychology : Assistant Professor
Neuroimaging and neuropsychology Professor
Lifespan Development : Professor
Socio-cognitive development in childhood : Associate Professor
Lifespan Development .: Assistant Teaching Professor
Cognitive neuroscience and computational modeling : Professor
Cognitive and social development in infancy and childhood : Professor
Lifespan Development

• Kaitlyn Fallow
• Tom Ferguson
• Sepideh Heydari
• Eric Mah
• Morgan Teskey
• Emma Ullrich

Program philosophy on coursework

Our graduate program emphasizes collaborative research activities more than coursework. Courses are viewed as important to the extent that they are likely to help the student succeed as a scholar. Consequently, we offer courses that we believe will be of direct relevance and value for our students' research, and the program is designed to permit a good deal of flexibility regarding how and when university coursework requirements are met.

Recommended courses

Throughout each academic winter session (i.e., September through April), students are encouraged to participate in the weekly meetings of the Cognition and Brain Sciences Seminar (for which they can earn credit as PSYC 577). Seminar participants (faculty, graduate students, and selected undergraduate students) take turns hosting the meeting, typically by talking about their ongoing cognitive research. There are occasional guest speakers from other universities. This may well be the best seminar of its sort in Canada.

Students are also encouraged to consider PSYC 500, "Professional Development," which focuses on practical skills such as applying for research grants, working with institutional review boards (ethics committees), giving scholarly presentations, and getting your research published. We also recommend that students take PSYC 575, "Cognitive Psychology," which is a team-taught class focused on areas of particular interest to our faculty. Later in their studies, students may also benefit from PSYC 605, "Practicum in the Teaching of Psychology."

The Cognition and Brain Sciences Program also offers a variety of seminar-style courses in cognitive psychology (typically at least one per year, ideally one per semester), and graduate students in the program are expected to take whatever such courses are relevant to their interests and goals. Each of these courses has a quite general title, because the specific content of the course varies over the years (such that students might take a given course [e.g., 576B] in two different years with different content being covered each time).

• PSYC 511: Perception
• PSYC 576 A: Memory
• PSYC 576 B: Computational Modelling
• PSYC 576 C: Mind and Brain
• PSYC 576 D: Attention

Students interested in brain science may wish to take PSYC 574: Electroencephalography and Event-related Brain Potentials and PSYC 579: fMRI Theory and Methods

In addition, special-interest courses are occasionally put together in response to student demand. For example, Mike Masson recently offered a grad seminar on Bayesian analyses that will provide an alternative to null-hypothesis-significance testing. (A course such as that one could also be used toward the Methods and Statistics requirement). As another example, a few years ago a group of graduate students got together and developed their own syllabus for a course of readings and discussions on the nature of consciousness, for which they earned course credit.

Other relevant Psychology courses

Social cognition courses

There are a variety of courses in the domain of social cognition that may be of interest to CABS students (e.g., PSYC 521: Human Motivation PSYC 523: Psychology and Law PSYC 531: Environmental Psychology).

Neuropsych courses

• PSYC 540 (History and Theory in Neuropsychology)
• PSYC 541 (Research Design and Methods in Neuropsychology)
• PSYC 543 (Human Neuroanatomy)
• PSYC 548 (Special Topics in Neuropsychology)
• PSYC 550 (Physiological Psychology: Introduction)
• PSYC 551 (Neuropsychopharmacology)
• PSYC 552 (Special Topics in Physiological Psychology)

Developmental courses

• PSYC 562 (Infancy and Childhood)
• PSYC 565 (Cognitive Development in Adulthood and Aging)
• PSYC 571 (Developmental Psycholinguistics)

This is not a complete list, but serves to highlight the sorts of courses UVic offers that may be useful for students in the Cognition and Brain Sciences Program.

Coursework requirements for MA/MSc students

Students must satisfactorily complete at least 15 units, of which at least 12 units must be classified as graduate-level work (i.e., courses numbered 500 and above). A typical one-semester course meeting for 3 hours per week is worth 1.5 units. The program must include the following:

At least 1.5 units of PSYC 502 (Research Apprenticeship, which consists of doing research with collaborative supervision by your adviser and/or another faculty member usually our students do more than 1.5 units of this [max = 4.5 units per year]).

At least 1.5 units of PSYC 504 (Individual Study, which is essentially a more advanced version of 502 -- that is, doing research with collaborative supervision by your adviser and/or another faculty member usually our students do more than 1.5 units of this [max = 6 units per year]).

At least 3.0 units of approved statistics courses. Typically these are selected from the following:

• PSYC 513: Quantitative Analysis
• PSYC 517: Research Methods in Psychology
• PSYC 532: Applied Multiple Regression
• PSYC 533: Applied Multivariate Analysis
• PSYC 534: Univariate Design and Analysis
• PSYC 561: Theories and Methods in Lifespan Development
• PSYC 564: Statistical Methods in Lifespan Development

The important thing is to take the statistics classes that will give you the tools you need to do the research you want to do.

At least 3.0 units of PSYC 599 (Thesis), including successfully defending a Master's thesis. (Our students typically earn 6.0 units for PSYC 599.)

Students whose undergraduate background is judged to be incomplete may also be required to demonstrate competence (e.g., by succeeding in an appropriate course or passing an exam) in certain areas of psychology this would be negotiated when an offer of admission is made.

Students are to consult with their supervisor regarding which courses (within the general requirements described above) they should take to complete their requirements.

Coursework requirements for PhD students

Students must satisfactorily complete at least 30 units of post-Master's coursework. Of the last 15 units of coursework for the Doctoral degree, not more than 6 units may be derived from undergraduate courses (i.e., all or most must be graduate-level courses). A typical one-semester course meeting for 3 hours per week is worth 1.5 units. The program must include the following:

• At least 1.5 units of PSYC 602 (Independent Research max 6.0 units per year)
• At least 1.5 units of PSYC 604 (Individual Study max 6.0 units per year)
• At least 1.5 units of PSYC 576A, B, C, or D.
• Registration in PSYC 577 each year.
• At least 3.0 units of approved statistics and/or research methods courses. Statistics courses include those listed under the Master's requirements. Methods classes of particular relevance to CABS students include PSYC 574A (EEG/ERP), PSYC 574B (fMRI), and PSYC 574C (Computational Modeling).
• At least 15.0 units of PSYC 699 (Dissertation), including successfully defending a Doctoral dissertation. (Max = 30 units, typically across 2 or 3 years.)

Students are to consult with their supervisor regarding which courses (within the general requirements described above) they should take to complete their requirements.

Faculty in the Cognition and Brain Science Program are committed to fully supporting our graduate students through various funding sources including research fellowships, teaching stipends, and scholarships. Each student is guaranteed a minimum of \$17,500/year for five years most students get more than this

This level of funding is sufficient for a person to get by in Victoria (even after paying tuition). The sources of this support will vary from student to student and from year to year. Those sources include (a) research assistantships (typically, this consists of getting paid to do cool research with your supervisor), (b) teaching assistantships (typically limited to no more than 10 hours per week, starting at about \$20/hour), and (c) scholarships. These sources of support can often be combined to produce income over the \$17,500 minimum (although there are certain limitations on how funds can be combined).

Students with major postgraduate scholarship and fellowships also receive a \$4,000 top-up from UVic (for NSERC, SSHRC, and CIHR scholarships \$2,000 top-up for some other major scholarships). For example, a student with a \$17,500 Canadian Graduate Scholarship C from NSERC would get an additional \$4,000 from UVic (roughly equivalent to having tuition paid). It's often possible for students with such scholarships to further supplement their incomes by working as Teaching Assistants.

Faculty in the Cognition and Brain Sciences Program provide grad students with workspace and basic work tools. We also often cover part of the costs of attending conferences at which the student presents or co-authors present research (and UVic's Faculty of Graduate Studies provides up to \$600/year to support conference travel).

Cognition and action

When you hear a sentence describing someone interacting with an object or simply read a word that is the name of some object that you can manipulate with your hand, parts of the brain responsible for motor planning and actions become active.

Professors Daniel Bub and Michael Masson are examining the nature of hand action representations that become active when processing language or viewing objects that are associated with hand actions. They are particularly interested in the role that these motor-based representations play in understanding language or enabling efficient identification of objects.

They are also measuring subtle aspects of actual reach and grasp actions and the way in which these actions are influenced by context and prior experience. By using motion-monitoring equipment, they are able to detect very small differences in hand shape and trajectory that can reveal important changes in brain states that govern the interface between cognition and action.

Reinforcement learning, errors and decision making

You know that feeling you get when you are about to do something risky? Or the feeling when you realize that something you just did wasn't optimal?

Maybe you gambled some money you couldn’t afford to lose, or you threw a dirty look at some scary-looking thug and almost immediately you just KNEW that it wasn't the best thing to do. These examples suggest the importance of both predicting and evaluating outcomes in learning and decision making.

Reinforcement learning provides a powerful computational framework for understanding these processes in the mind and brain.According to this view, our choices are guided by the prediction of expected outcomes, followed by an evaluation of the difference between those predictions and the actual reward or punishment we experience (i.e. prediction errors). Recent research suggests a central role for the dopamine system (including the substantia nigra, basal ganglia, anterior cingulate, and related brain areas) in implementing reinforcement learning in the human brain. Clay Holroyd, Adam Krawitz, and their co-workers combine studies of event-related potentials and functional MRI with computational modeling and more traditional behavioural studies to develop and test theories of how reinforcement learning guides decision making and action selection.

Cognitive Control and Working Memory

Some behaviors are instinctual and stimulus driven – if someone throws a ball at your face, you will put your hands up and duck down in an instant. Some behaviors are so well learned they require nary a thought – you can walk down the street without focusing on how to place each foot in front of the other.

But many of our most interesting and uniquely human behaviors require active attention and control, particularly as we are first learning them – say, baking chocolate-chip cookies. These goal-driven activities require top-down processes, cognitive control, to overcome our impulses – why not just eat the batter? – and the maintenance and updating of temporary information, working memory, to track our progress – better remember you’ve added the butter, but not the flour.

Brain areas that are centrally involved in these processes include the dorsolateral prefrontal cortex and the anterior cingulate. Clay Holroyd, Adam Krawitz, and colleagues apply converging methods, including event-related potentials, functional brain-imaging, computational modeling, and behavioral experimentation, to understand the mental and neural bases of cognitive control and working memory. One central issue they are addressing is understanding how we learn when to apply control, with reinforcement learning playing an important role. A second central issue is explaining how these control systems interact with other systems in the brain, including the medial-temporal lobe system for spatial processing, and the limbic system for emotion.

In related work, Michael Masson is examining episodic influences on cognitive control, and more specifically how recent experiences change the efficiency of switching from performing one skilled task to another. Mike uses behavioural methods and tracking of eye movements during task performance to undercover the cognitive mechanisms that enable or interfere with smooth task transitions.

From visual input to meaning

When you look at an object (e.g., a coffee cup), a two-dimensional pattern of light falls on your retinas (the sensory surface inside your eyes). Almost instantly, you perceive the object and can access a wide variety of kinds of knowledge about it (what it's called, what it's used for, what it feels like and how heavy it is, etc.).

How do you do this? How are the various kinds of knowledge linked together? How and why does the system sometimes break down?

Anchored chiefly by Prof. Daniel Bub, several faculty and graduate students at UVic apply cognitive and neuroscience approaches to study object recognition and face perception in healthy individuals and in special populations such as agnosics, alexics, and children with Asperger's syndrome.

Visual expertise

To most of us, a rose is a rose is a rose, but to a keen horticulturalist it may be a Double Blush Burnet Spinosissima.

Research by Prof. Jim Tanaka reveals that experts in a domain differ from novices not only in how they name objects within that domain, but also in how they see them. For example, one line of studies discovered differences in visual processing between bird-watching afficionados and people who aren't bird experts when viewing pictures of birds. Jim's research on visual expertise combines Event-Related Potentials (ERPs), behavioural measures, computational modeling.

A particularly interesting domain in which Jim has studied visual expertise is face perception. Most people are "face-perception experts," but children diagnosed with autism or Asperger's syndrome may not develop expertise in face perception. Jim and his students and colleagues are working on programs designed to help such children improve their face-perceiving expertise.

Memory in action: basic theory

Most people think of memory as being akin to a library or storehouse, in which a record of each past experience is filed in a discrete little package, and of remembering as a matter of locating and playing back the appropriate record.

Cognitive psychologists know that memory is much more than, and much different from, such a storehouse. For one thing, virtually every aspect of human behaviour and experience (from ice skating to getting a joke to solving a math problem to enjoying a piece of music) relies on and reflects the use of memory. For another, people are often influenced by memories of particular past episodes without being consciously aware of remembering (as in cases of involuntary plagiarism), and they sometimes have the subjective experience of remembering past episodes that they never in fact experienced (as in deja vu or various false memory phenomena).

Much of the research conducted by Profs. Mike Masson and Steve Lindsay and their students and collaborators focuses on understanding how memory (both with and without awareness) works.

Memory in action: applied domains

In the past decade, memory has emerged as perhaps the most controversially relevant area of cognitive psychology.

As one example, the debate about recovered memories of childhood sexual abuse created a huge stir in the popular media as well as in professional psychology, and Steve Lindsay and Don Read have been actively engaged in that controversy since the early 1990s. As another example, the development of DNA testing has led to the realization that false convictions occur frighteningly frequently (e.g., the US National Institute of Justice estimates that as many as 10% of the hundreds of thousands of inmates in US jails are innocent of the charges for which they were imprisoned), and faulty eyewitness identification evidence appears to play a huge role in false convictions.

Don Read is one of Canada's foremost researchers in the area of eyewitness identification, and in recent years he and Steve Lindsay have been collaborating on research on that topic (see also Affiliated Member Elizabeth Brimacombe). At a more general level, perhaps the broadest application of the study of memory is research on autobiographical memory (i.e., individuals' reminiscences and beliefs about their own personal histories), and this too is another active research area in Steve's lab at UVic.

Cognitive development

You started out as a baby, now you're an adult. How'd you do that?

Babies are more cognitively skilled than once was thought, but breathtakingly huge developments in cognitive complexity and sophistication are accomplished between birth and adulthood.

Chris Lalonde is particularly interested in developmental changes in children's ability to think about their own and others' mental states and beliefs (including beliefs about their own self identities). Although development is not his focus, Steve Lindsay occasionally collaborates on research on children's ability to differentiate between mental experiences with different sources (e.g., between memories and fantasies, or memories of an actual experience vs. memories of what someone else said about that experience).

Graduate students in the Cognition and Brain Sciences Program are provided with one or more computers for their work. The University also offers a number of up-to-date facilities and services for computing. We provide licences for major statistical packages (e.g., SPSS and Systat). Programming languages and other specialized software (e.g., MATLAB, Visual Basic, E-Prime) are also available in individual faculty labs.

As noted above, the Cognition and Brain Sciences group uses a wide variety of methods, including electroencephalography (“brain waves”), MRI, eye tracking, kinematic tracking, and computational modeling. Through collaborations, several of our faculty also draw on other methods such as endocrinology (e.g., stress hormones) and genetic analyses.

Research methods

Our primary research method involves the use of experimental designs to test hypothesis. Many of our studies involve computer-controlled presentations of visual and/or auditory stimuli and electronic measures of responses (e.g., key press, voice key, eye movements, measurement of brain activity).

But our methods are not narrowly restricted to highly controlled laboratory experiments. For example, Daniel Bub's research often involves exploratory observational work (as well as formal experiments) with individuals who have suffered various kinds of brain damage.

Steve Lindsay has used survey methods to explore adults' recollections of long-past autobiographical events.

Clay Holroyd, Adam Krawitz, and Mike Masson use computer simulations to articulate and refine theoretical models (computational cognitive neuroscience).

As experimental psychologists, we are committed to the idea that experiments are the most compelling way to test hypotheses, but we also believe that observational and correlational research can play key roles in helping to understand psychological phenomena and in formulating hypotheses for subsequent experimental tests.

Basic research facilities

Each faculty member in the Cognition and Brain Science Program has a microcomputer-based laboratory for data collection, data analysis, and computational modeling. In addition, the group collectively holds a variety of other specialized equipment and software (e.g., state-of-the-art eye tracking and 3-D kinematics). We also have connections with medical facilities that provide opportunities for research with neurological cases.

Graduate students in the program are provided with office space and shared access to laboratory facilities. To the extent that funds allow, graduate students receive support for attending conferences for presentations of their collaborative research with faculty.

Brain imaging

Jim Tanaka having his brain waves recorded.

Clay Holroyd and Jim Tanaka run the Brain and Cognition Event-related Potential Laboratory, which houses 4 state-of-the-art 64-channel systems for recording and analyzing the electroencephalogram (i.e., “brainwaves”). Holroyd’s EEG research focuses on the neural mechanisms of learning and cognitive control and Tanaka’s lab explores how experience, culture and biology converge to shape that way we perceive the world. Each year Holroyd teaches a graduate course on this technique and students from multiple labs utilize the facility for their own research.

CABS members Holroyd, Krawitz and Lindsay, and affiliated faculty Gawryluk, Medler and MacDonald all have experience using functional magnetic resonance imaging (MRI), with many of their studies published in high-impact journals. Faculty currently maintain collaborative contracts to access magnetic resonance imaging (MRI) resources with both West Coast Medical Imaging and Island Health. Our data is primarily collected on a 3T MRI scanner with functional magnetic resonance imaging, diffusion tensor imaging, and high resolution anatomical acquisitions. With a growing interest from students and faculty in these techniques, we are actively working on building neuroimaging capacity and commonly offer courses on how to analyze MRI based data.

Our colleagues in Lifespan Development have also acquired a near-infrared spectroscopy (NIRS) set-up, which uses laser lights to measure activity in the outer part of the brain’s cortex.

Statistical expertise and resources

Our group has substantial statistical/quantitative sophistication. In particular, Clay Holroyd, Adam Krawitz, and Mike Masson all have advanced quantitative skills, and Tony Marley is a mathematical psychologist. Stuart MacDonald, Associate Professor of Psychology in the Lifespan Development program, is also available for consultation on statistical issues.

Social Cognitive Theory: Concept and Applications | Theories | Psychology

In this article we will discuss about:- 1. Concept of Social Cognitive Theory 2. Identification, Self-Efficacy of Social Cognitive Theory 3. Central Idea 4. Applications.

Concept of Social Cognitive Theory:

Social cognitive theory, used in psychology, education, and communication, posits that portions of an individual’s knowledge acquisition can be directly related to observing others within the context of social interactions, experiences, and outside media influences. In other words, people do not learn new behaviors solely by trying them and either succeeding or failing, but rather, the survival of humanity is dependent upon the replication of the actions of others.

Depending on whether people are rewarded or punished for their behavior and the outcome of the behavior, that behavior may be modeled. Further, media provide models for a vast array of people in many different environmental settings.

Social cognitive theory is a learning theory based on the ideas that people learn by watching what others do and will not do, these processes are central to understanding personality. While social cognitists agree that there is a fair amount of influence on development generated by learned behavior displayed in the environment in which one grows up, they believe that the individual person (and therefore cognition) is just as important in determining moral development.

People learn by observing others, with the environment, behavior, and cognition all as the chief factors in influencing development. These three factors are not static or independent elements rather, they influence each other in a process of triadic reciprocal determinism.

For example, each behavior witnessed can change a person’s way of thinking (cognition). Similarly, the environment one is raised in may influence later behaviors, just as a father’s mindset (also cognition) will determine the environment in which his children are raised.

It is important to note that learning can occur without a change in behavior. According to J.E. Ormrod’s general principles of social learning, while a visible change in behavior is the most common proof of learning, it is not absolutely necessary. Social learning theorists say that because people can learn through observation alone, their learning may not necessarily be shown in their performance.

Observation of Models:

Social cognitive theory revolves around the process of knowledge acquisition or learning directly correlated to the observation of models. The models can be those of an interpersonal imitation or media sources. Effective modeling teaches general rules and strategies for dealing with different situations.

To illustrate that people learn from watching others, Albert Bandura and his colleagues constructed a series of experiments using a Bobo doll. In the first experiment, children were exposed to either an aggressive or non- aggressive model of either the same sex or opposite sex as the child.

There was also a control group. The aggressive models played with the Bobo doll in an aggressive manner, while the non-aggressive models played with other toys. They found that children who were exposed to the aggressive models performed more aggressive actions toward the Bobo doll afterward, and that boys were more likely to do so than girls.

Following that study, in order to test whether the same was true for models presented through media, Albert Bandura constructed an experiment entitled “Bobo Doll Behavior: A Study of Aggression.” In this experiment Bandura exposed a group of children to a video featuring violent and aggressive action. After the video he then placed the children in a room with a Bobo doll to see how they behaved with it.

Through this experiment, Bandura discovered that children who had watched the violent video subjected the dolls to more aggressive and violent behavior, while children not exposed to the video did not.

This experiment displays the social cognitive theory because it depicts how people reenact behaviors they see in the media. In this case, the children in this experiment reenacted the model of violence they directly learned from the video.

As a result of the observations the reinforcement explains that the observer does not expect actual rewards or punishments but anticipates similar outcomes to his/her imitated behaviors and allows for these effects to work. This portion of social cognitive theory relies heavily on outcome expectancies. These expectancies are heavily influenced by the environment that the observer grows up in

for example, the expected consequences for a DUI (Driving in influence) in the United States of America are a fine, with possible jail time, whereas the same charge in another country might lead to the infliction of the death penalty.

In education, teachers play the role as model in a child’s learning acquisition. Teachers model both material objectives and underlying curriculum of virtuous living. Teachers should also be dedicated to the building of high self-efficacy levels in their students by recognizing their accomplishments.

Identification, Self-Efficacy of Social Cognitive Theory:

Albert Bandura also stressed that the easiest way to display moral development would be via the consideration of multiple factors, be they social, cognitive, or environmental. The relationship between the aforementioned three factors provides even more insight into the complex concept that is morality.

Further development in social cognitive theory posits that learning will most likely occur if there is a close identification between the observer and the model and if the observer also has a good deal of self-efficacy. Self- efficacy beliefs function as an important set of proximal determinants of human motivation, affect, and action which operate on action through motivational, cognitive, and affective intervening processes.

Identification allows the observer to feel a one-to-one connection with the individual being imitated and will be more likely to achieve those imitations if the observer feels that they have the ability to follow through with the imitated action.

Self-efficacy has also been used to predict behavior in various health related situations such as weight loss, quitting smoking, and recovery from heart attack. In relation to exercise science, self-efficacy has produced some of the most consistent results revealing an increase in participation in exercise as self-efficacy increases.

Vicarious Learning: Central Idea of Social Cognitive Theory:

Vicarious learning, or the process of learning from other people’s behavior, is a central idea of social cognitive theory and self-efficacy. This idea asserts, that individuals can witness observed behaviors of others and then reproduce the same actions. As a result of this, individuals refrain from making mistakes and can perform behaviors better if they see individuals complete them successfully.

Vicarious learning is a part of social modeling which is one of the four means to increase self-efficacy. Social modeling refers not just to observe behavior but also to receiving instruction and guidance of how to complete a behavior.

The other three methods include, mastery experience, improving physical and emotional states and verbal persuasion. Mastery experience is a process in which the therapist or interventionist facilitates the success of an individual by achieving simple incremental goals.

With the achievement of simple tasks, more complex objectives are introduced. The person essentially masters a behavior step by step. Improving physical and emotional states refers to ensuring a person is rested and relaxed prior to attempting a new behavior. The less relaxed, the less patient, the more likely the goal behavior will not be attained. Finally, verbal persuasion is providing encouragement for a person to complete a task or achieve a certain behavior.

Applications of Social Cognitive Theory:

Social cognitive theory is applied today in many different areas:

The use of celebrities to endorse and introduce any number of products to certain demographics: one way in which social cognitive theory encompasses all four of these domains, campaigns.

Aids which are issued in the favour of public like warning against drinking , smoking etc. are generally given by celebrities because of their charm in society, public enjoys following their footsteps.

Modeling plateau potentials - Psychology

• Integrate and Fire digital neurons which emphisize simple dynamics and can be connected together to form larger systems.
• Conductance-level neuron models which use analog techniques to simulate the dynamics of individual cells.

The circuits below were simulated in Electronics Workbench and will be built as hardware models for students.

Analog conductance-level circuits

Maeda and Makino (1) show how to model a neuron using 3 transistors for a FitzHugh-Nagumo (FHN) type neuron (simplified from Hodgkin-Huxley formulation). The FitzHugh-Nagumo scheme replaces the fast Na current of the HH model with a simplified fast, depolarizing, activation process, and replaces the slow Na inactivation and slow, repolarizing, K current by a single slow inactivation process. By adding one more repolarizing process, modeled by two more transistors, they can produce a neuron with bursting behavior.

The circuit is show below for the FHN neuron. The circuit produces a constant train of simulated action potentials (AP) when a constant current is applied. The Electronics Workbench file is here. Note that the amplitude of the simulated action potential is much larger than that of a physiological neuron. Simulated AP amplitude is around 5 volts, while in real life the AP amplitude is around 100 mV.

The neuron can be made to oscillate without an external current source by adding RL shown below. The resistor acts as an inward current leak. The usefulll range of RL is about 25 kohms (fast oscillation) to around 250 kohms.

It is easy to voltage clamp these model neurons. The image below shows a 3 volt step applied from resting potential. A transient inward current is seen, followed by an outward current. EWB file.

The circuit is show below for the FHN neuron, extended with an extra conductance process. The circuit produces a constant train of simulated AP bursts when a constant current is applied. The Electronics Workbench file is here.

Maeda, Yagi, and Makino (2) extend the model to include heart cells. They slightly modified one of the repolarizing processes to make a plateau potential. The circuit show below shows two traces. The bottom trace is membrane potential, the top is the deritivive, which is a simple approximation of an ECG. The Electronics Workbench file is here. Be sure to set the integration method to Gear in the menu item
Analysis. Analysis Options. Transient . The example below uses the default trapzoidal method, which causes spurious oscillations.

By turning one of the neurons into a macro (FHNbuild below), we can build an axon to investigate extracellular versus intracellular recording. The 50 kohm resistors model the axonal lumen. The 100 ohm resistors model the bath saline. The subtractor just below the axon simulates a perfect differential amplifier. Note that the voltage scale on the bottom (extracellular) trace is 100 times more sensitive than the top trace. The specific model built is decribed below in the Construction section. The Electronics Workbench file is here.

As few as 3 sections, terminated with a passive load, can be used as a teaching model.

The basic FHN models don't have an explicit sodium inactivation, but for teaching voltage clamp techniques, it would be nice to have this process represented. The following circuit uses an RC combination on the power supply to the fast inward current to limit the current to a short burst. The length of the burst is determined by the size of the capacitor, here 1uf, and the membrane resistance. The refractory period is determined by the RC time constant, here 20 mSec. In clamp mode, if you change the 620 ohm resistor in either the fast inward or delayed outward current to 1 Mohm, then that current is essentially eliminated, simulating a selective block of the approriate channel. The two currrents can thus be seen separately. Workbench file.

Conductance Models based on Guy Roy's NeuroFET (3)

These models use analog computation, combined with N-channel, enhancement-mode, field-effect transistors, to simulate conductance changes in the membrane. The circuit is scaled so that the timing and magnitude of the conductance changes (and voltage changes) are biologically realistic. The battery V1 sets the leakage through Na channels at resting potential. A more positive value stabilizes the membrane, while more negative can cause oscillations. Electronics Workbench file.

Model Synapses

Modifying the depolarizing process channel to depend on presynaptic voltage (and changing the reveral potential) makes an excitatory synapse. Top trace is the presynaptic cell. Bottom trace shows postsynaptic cell with EPSP and AP. The diode in the synapse represents the isolation of the presynaptic side due to transmitter release. The Electronics Workbench file is here.

Modifying the repolarizing process channel to depend on presynaptic voltage makes an inhibitory synapse. Top trace is the presynaptic cell. Bottom trace shows postsynaptic cell with IPSP and AP. Note that this inhibitory synapse exhibits shunting as well as hyperpolarization. The Electronics Workbench file is here.

A burster cell was turned into a macro, then two of them were connected through inhibitory synapses. By adjusting the strength and time constant of the synapse, you can get alternate bursting. The Electronics Workbench file is here.

With four bursters, connected as two sets of alternate bursters, you can get 2:1 locking by adding an excitatory synapse between the two sets. The faster set was adjusted to have a natural burst rate just slightly slower than 2:1 lock. The excitatory synapse adds a little extra current to lock the frequency. The Electronics Workbench file is here.

The burst macro:

The Fburst macro:

Adding a diode and resistors between the two cells results in an electrotonic connection with a stronger connection from left to right. The traces show a very complex interaction between the two cells. Note that any given electrotonic synapse can be rectifying in either direction, or not at all. The Electronics Workbench file is here.

Integrate-and-fire circuits

The circuit below uses monostables (e.g. 74HC123) as integrate and fire (IF) neurons. The Q output is the AP pulse. The W output is an inverted AP pulse. The diode to the W output discharges simulated membrane capacitance when an AP occurs. The 25k/0.1 uF components attached to RT/CT and CT inputs set the length of the AP pulse. The neuron on the left is driving the neuron on the right with an excitatory connection. The Electronics Workbench file is here.

The circuit below connects 2 IF neurons with an inhibitory synapse. The monostable was added to stretch the pulse and invert it. A better version of an excitatory synapse (than the one shown above) would be to use the Q output of the synaptic monostable as the input to the second cell through a diode which allows current to from from the Q terminal to the second cell's input capacitor. The Electronics Workbench file is here.

The following circuit implements a IF burster by using a second monostable to inhibit the first one. The top two monostables are the burster. The bottom monostable is an weakly inhibited non-burster. The Electronics Workbench file is here.

Construction

To actually build one of the Maeda neurons, it is handy to simplify the power supplies so that only one battery is needed. Elimanating the simulated potassium battery required changing the sodium current threshold by adding a diode. The battery voltage was changed to 6 volts to make it easier to use lithium batteries. The RL resistor allows the circuit to act as a pacemaker. Replacing RL with a CdS photoresistor makes a photosensor with output frequency related to light intensity. Lower resistance is a faster pacer. The userful range of RL is about 25 kohm to 450 kohm. The expanded simulated scope image should be compared with the photograph of the real scope screen. The Electronics Workbench file is here. A picture of the white board prototype is included below.

Expanded simulation scope on the left and output from the real circuit.

A first hack at a curcuit board is shown below. Transistors are (from left to right) 2N3904, 2N3906, 2N3904. The diode is a 1N914. A battery holder is mounted on the back of the board. the two vias on the left side of the board are the only two connections to the outside world. Top left is inside the cell, bottom left is outside. The resistor marked *** sets the pacemaker rate. Omitting this resistor makes the circuit more like a squid axon element. ExpressPCB file.

Luo-Rudy dynamic model

To make a model cell alive, it needs the ion pumps to maintain the intracellular ion balance, i.e., the ions must return back after the firing of an action potential. In one shot of action potential, potassium ions leave out of the cell, but sodium ions get into the cell. Moreover, calcium ions get into the cells from the extracellular space and sarcoplasmic reticulum for muscle contraction, an important feature for human heart. So, ion pumps are required in the membranes of cell and sarcoplasmic reticulum to maintain the ion balance inside the cell. Fortunately, huge amount of experimental data have been published for cardiac cells in 1980s, even not for formulism. Dr. Luo screened and integrated those data together to be formulated as the components of the cardiac model cell.

In 1991, the most arguing issue to formulate a live cardiac cell model was the ambiguity of the calcium ion channels. Several famous labs announced the calcium ion channels but they were quite scattering with apparent differences, including species. Dr. Luo made a decision to skip the debate issue but, instead, put them all into the cell model to see how action potentials look like by using those published experimental data for calcium ion channels, especially sodium-calcium exchangers. It left the choice for scientists to pick up the calcium ion channels they wanted even Dr. Luo had suggestions in the Luo-Rudy dynamic model published in 1994.

Luo-Rudy dynamic model in 1994 not only includes the sodium and potassium channels in Luo-Rudy passive model but also introduces sodium-potassium pump, calcium pump, L-type calcium channel, non-specific calcium-activated channel, sodium-calcium exchanger on the membrane as well as calcium-induced calcium release channel and calcium pump on the membrane of sarcoplasmic reticulum with calcium buffers in the myoplasm.

For heart muscle contraction, a single heart cell is stimulated to raise the intracellular potential from the resting -80 mV to about +40 mV by flowing positive sodium ions due to the opening of the sodium channel. Such a potential rising is called depolarization. Sodium channel is closed very quickly (in 2 msec), then the opening of potassium and calcium channels fight against to maintain the intracellular potential at the positive level called the potential plateau for 200-300 msec. Potassium ions flows out of the cell but calcium ions flows into the cell to maintain such a high plateau potential moreover, the input of the extracellular calcium ions raises the intracellular calcium level up to a threshold to incite the spike calcium release from sarcoplasmic reticulum for cell contraction. Finally, potassium ion efflux brings the potential down to the resting level, called repolarization. The potential variation procedure from depolarization, plateau, to repolarization is called an action potential. Sodium-potassium pump and calcium pump keep working to return all the ions back their origin pools during or after an action potential. If keeping firing the action potential, the intracellular ion concentration will lose the balance gradually and it also takes more time for ion pumps to recover the steady status.

Modeling plateau potentials - Psychology

Embedded Ensemble Encoding (EEE)

This repo is for the detailed cell model CA229. It includes the simulation, analysis and plotting files to generate paper figures. The code is in python version 3.6 and using NEURON version 7.4, 7.5, or 7.6.

CA229.py - python class with all the cell membrane properties (the Geometry and 3d shape is defined in this python class as well --- for better usage in network or NetPyNE)

The ratio of sodium, calcium, A-type potassium and calcium activated potassium channels can be adjusted by call the class with different ratio parameters. For example,

Using all the default value in cell1

Setting the channel conductances to 50% of the default value in cell2

compile.py - compile all the mod files in folder: mod

analysis_utils.py - calculating the plateau amplitude, plateau duration, interspike interval and number of spikes of the voltage traces generated by model simulation.

utils.py - to save figures and simulation results in a folder with name of today's date or self-defined folder.

Fig2_bAP_exp.py - Inject current in soma and record the voltage traces at different locations on all basal dendrites. All the parameters and traces are saved in json file for further analysis.

Fig2_bAP_anaPlot.py - Load the data generated by Fig2_bAP_exp.py and measure the peak amplitude and latency. Plot all the data.

Fig3_exp_dms.py, Fig3_exp_major.py - Code to add AMPA and NMDA receptors on basal[34] - It will generate figures and json files to store the voltage traces - Modify the parameters in "main" to choose the input strength - "random_2" function is used to generate random activation time within a certain range. The seed is locked for now to get consistent results. - "random_beta" function is used to generate alpha random activation time within a certain range. The seed is locked for now to get consistent results.

Fig3_dms_trace_plot.py, Fig3_major_trace_plot.py - Generate trace plots in Fig 3. A2 and B2

Fig3_trace_analysis.py - Analyze the recorded traces and plot the plateau amplitude, duration and spikes per plateau against different input strength.

Fig5_exp_DMS.py, Fig5_exp_major.py
- batch simulation of glutamate input locations range from 0.1-0.9 (step size 0.1) on 6 different basal branches. At each branch and each location, there is also normal and TTX conditions. All the simulation results are saved into json files under each subfolder. - The data for generating paper fig5 are saved in subfolder("/Fig5/DMS or /Fig5/major")

Fig5_ana_DMS.py, Fig5_ana_major.py, Fig5_plot_DMS.py, Fig5_plot_major.py
- Analyze and plot the somatic plateau amplitude, dendritic plateau amplitude, plateau duration and spike numbers against the input distance from soma on basal dendrite.

Compile mod files: python compile.py

Fig 2.B2 and B3 (the study of backpropagated action potential)

Run: "Fig2_bAP_exp.py" run the simulation and save the data in folder "Fig2/" This step take

Fig 3. A2 and B2 - Trace plots

Run: "Fig3_exp_dms.py" or "Fig3_exp_major.py" run the simulation and save the data in folder "Fig3/DMS/Plot/" or "Fig3/Major/Plot/" This step take

Fig 3. D1 - D3 - analysis plots

Open "Fig3_exp_dms.py", add # before the code at line 77, remove # before the code in line 78 add # before the code at line 254, remove # before the code in line 256. This step take

Run: "Fig5_exp_DMS.py" or "Fig5_exp_major.py" Run the simulation and save json data in folder "Fig5/DMS/" or "Fig5/major/". This step take

NOTE: in all the "exp" files, the parameters can be adjusted in "main" manually, eg. Fig3_exp_dms.py (change number pool1 of synaptic AMPARs and NMDARs change number pool 2 of exsyantpic NMDARs change Beta and Cdur of NMDARs change of stimulation location change of syanptic weights change of stimuation locations)

Peng Penny Gao

Joe W Graham, Sergio L Angulo, Salvador Dura-Bernal, Michael L Hines, William W Lytton, Srdjan D Antic

Sexual Response Model - Master’s and Johnson’s Four-Phase Model

Before the sixties, sex was a topic that was considered taboo to talk about, and with little discussion about sex there was no information on sexual responses for either sexes during this time. That was until Williams Masters and Virginia Johnson decided it was time for the world to understand how our bodies work sexually. According to NPR (2013) the duo changed history,

“ William Masters and Virginia Johnson became famous in the 1960s for their groundbreaking and controversial research into the physiology of human sexuality. Instead of just asking people about their sex lives, Masters and Johnson actually observed volunteers engaging in self-stimulation and sexual intercourse. Changes throughout their bodies during arousal were measured with medical equipment”.

The two wanted to understand exactly how the body worked with sexual responses, they were primarily interested in studying the biology of sexuality. With the research they conducted they discovered that there were 4 different phases that take place during these sexual activities. An online article done by OurBodiesOurSelves (2011) explains the model, “ The Masters and Johnson model outlined four stages of physiological arousal: excitement, plateau, orgasm, and resolution”. Both men and women experience these phases, although the timing will typically be different between the male and female.

The first phase to take place is excitement, which can last from a few minutes to several hours. The general characteristics of excitement can include increase muscle tension, the heartrate will rise, nipples become hardened and erect, and the penis becomes erected. The second phase to take place is called plateau, which extends the brink of orgasm. The general characteristics for plateau can range from muscle spasms, the women’s clitoris becomes highly sensitive, the man’s testicles are withdrawn up to the scrotum, and all the characteristics from excitement are intensified. After these two phases occur phase three will take over, also known as orgasm. The ClevelandClinc (2012) describes phase three as, “The climax of the sexual response cycle. It is the shortest of the phases and generally lasts only a few seconds”. The characteristics of an orgasm include involuntary muscle contractions, a forceful release of sexual tension, in women the muscles of the vagina contract, and for men contractions at the base of the penis which results in ejaculation. When the climax in sexual activity is reached you go into phase four also known as resolution. This phase is where all body functions return back to a normal state, the heartrate returns to a steady pace and erected body parts go back to their previous size and color.

During Masters and Johnsons studies they discovered that women and men had the same similarities when going through the four phases, but differentiated when it came to recovery after reaching orgasm. While women were able to experience multiple orgasms, and were able to have a rapid return to the orgasm phase, men will typically need more time to recover after. According to Crooks and Baur (2014), “After orgasm the male typically enters a refractory period-a time when no amount of additional stimulation will result in orgasm”.

Kaplan’s Sexual Response Model

Helen Singer Kaplan a noted sex therapist and author, created the three-stage model which is distinguished by its identification of desire as a prelude to sexual response. This three-stage model includes three stages: desire, excitement, and orgasm. Although very similar to Masters and Johnsons four phase model, Kaplan’s model focuses on the aspect of desire. In this model it plays a big part in sexual response, Crooks and Baur (2014) wrote,

“One of the most distinctive features of Kaplan’s model is that it includes desire as a distinct stage of the sexual response cycle. Many other writers, including Masters and Johnson, do not discuss aspects of sexual response that are separate from genital changes”.

Before reaching any physical and bodily changes in sexual response, desire will allow someone to become psychologically interested. Which describes the first stage in Kaplan’s model, which makes it different from Masters and Johnson’s model. Once you reach the stage of desire your body will then processed into the excitement stage, where arousal begins from both physical and psychologic stimulation. The general characteristics of this phase include increased heartrate, erect penis, and the clitoris becoming highly sensitive. After reaching excitement, you enter the final stage in Kaplan’s model: the resolution stage which resembles Masters and Johnsons third and fourth stage. Your body will reach its climax resulting in an orgasm, proceeding to resolution where the body returns to its normal state.

Elizabeth M. Brannon

Dr. Brannon's research program examines the evolution and development of quantitative cognition. She studies how adult humans, infants, young children and nonhuman animals without language represent number. She uses behavioral techniques, event-related potentials, functional magnetic resonance imaging, and single-unit physiology to explore the cognitive and neural underpinnings of numerical cognition in nonhuman primates and throughout the human lifespan. A major current focus is to study how training the primitive number sense might facilitate mathematical abilities in children and adults.

DeWind, N.K., G.K. Adams, Platt, M.L. Brannon, E. M., (2015). Modeling the approximate number system Quantifying the contribution of visual stimulus features, Cognition, 142, 247-265.

Drucker, C., & Brannon, E. M. (2014). Rhesus monkeys (Macaca mulatta) map number onto space, Cognition, 132(1), 57-67. PMCID: PMC4031030.

Park, J., & Brannon, E. M. (2014). Improving arithmetic performance with number sense training: An investigation of underlying mechanism ,Cognition, 133(1), 188-200. NIHMSID: NIHMS614955.

INTRODUCTION

Midbrain dopamine neurons, which are involved in motivation and the control of movement, have been implicated in various pathologies such as Parkinson's disease (Bernheimer et al. 1973), schizophrenia (Weinberger et al. 1987), and drug abuse (Koob et al. 1987). As a result, considerable effort has been devoted to the study of dopamine signaling. The firing pattern in these neurons influences the extracellular concentration of dopamine in projection areas, and a burst firing pattern produces a greater transient increase in dopamine concentration than a tonic one (Chergui et al. 1996 Gonon 1988 Heien and Wightman 2006). Bursts in dopamine neurons are thought to convey signals pertaining to reward prediction and attribution of salience (Schultz 2006). An understanding of dopaminergic signaling must include an appreciation of how the firing pattern is regulated.

Dopamine (DA) neurons in the presence of their afferent inputs in vivo can exhibit one of several firing modes: silence, regular single-spike firing, irregular single-spike firing, and bursting (Grace and Bunney 1984a,b Hyland et al. 2002). By contrast, dopamine neurons in brain slice preparations exhibit a homogeneous pacemaker-like firing pattern that appears to result from an intrinsic slow oscillatory potential (SOP) (Fujimura and Matsuda 1989 Harris et al. 1989 Kang and Kitai 1993a Yung et al. 1991). Local application of the selective SK channel blocker apamin converts the SOP to an oscillatory plateau potential resembling a square wave. Apamin, applied in the absence of tetrodotoxin (TTX), induces bursting activity that is driven by these plateau oscillations (Ping and Shepard 1996). Johnson and Wu (2004) replicated these results and were also able to convert pacemaker firing to bursting by the application of Bay-K-8644 [3-pyridinecarboxylic acid (1,4-dihydro-2,6-dimethyl-5-nitro-4-(2-(trifluoromethyl)phenyl) methyl ester], which potentiates the opening of L-type Ca 2+ channels (Nowycky et al. 1985). In some cases, application of apamin in the absence of TTX induced irregular firing instead of bursting (Ping and Shepard 1996), but if a small applied current was injected, bursting could be established (Johnson and Wu 2004). The bursting observed in the two studies was qualitatively similar, with slow spiking during the trough of the oscillation that accelerates and diminishes in amplitude during the upstroke of the plateau. Spiking often ceases during the plateau, presumably as a result of inactivation of fast Na + channels. Plateau potentials similar to those observed in vitro may underlie burst firing in vivo as a result of endogenous neuromodulators acting to restrict access of the small-conductance (SK) channel to intracellular calcium (Brodie et al. 1999 Fiorillo and Williams 2000 Paladini et al. 2001) or by second-messenger cascades that alter the affinity of the channel for Ca 2+ (Allen et al. 2007 Bildl et al. 2004).

Nifedipine blocks the plateau potential oscillations (Johnson and Wu 2004 Nedergaard et al. 1993 Shepard and Stump 1999). Thus it appears that the L-type calcium channel is responsible not only for the depolarizing phase of the SOP (Mercuri et al. 1994 Nedergaard et al. 1993), but also for the plateau potentials. Although the mechanism responsible for terminating the bursting plateau potentials observed in apamin has yet to be established, it could involve cytosolic Ca 2+ -dependent or -independent mechanisms. Potential cytosolic Ca 2+ -dependent candidates include the Ca 2+ -dependent inactivation of a Ca 2+ current, an electrogenic Ca 2+ pump, apamin-insensitive Ca +2 -activated K channel, or Ca 2+ -activated chloride channel. Alternatively, recent studies by Nedergaard (2004) suggest that a slow, cytosolic calcium-independent outward current resembling an ether-a-go-go–related gene (ERG) current might be involved in termination of plateau potentials. Additional evidence for the presence of this current is the clear ERG1 antibody labeling observed in the substantia nigra pars compacta (SNC Papa et al. 2003). Notably, ERG currents in the heart and CNS are potently blocked by a wide variety of antipsychotic drugs including haloperidol (Kongsamut et al. 2002 Suessbrich et al. 1997). In the present study, an experimental approach was used to assess the contribution of cytosolic Ca 2+ -dependent mechanisms to termination of plateau potential oscillations exhibited by DA neurons. In addition, we incorporated an ERG conductance into an existing computational model of oscillatory activity (Amini et al. 1999) to determine whether the kinetics of the conductance is consistent with its hypothesized role in terminating the plateau potentials. Furthermore, we examined both the sequential kinetic scheme postulated for the ERG current and an independent kinetic scheme with a similar steady-state open fraction to determine the unique contribution of the unusual sequential kinetic scheme.