AVÊÓƵ

School of Engineering and Informatics (for staff and students)

Neural Circuits (C1098)

Neural Circuits

Module C1098

Module details for 2021/22.

15 credits

FHEQ Level 5

Module Outline

Topics covered include:
- Organisation and modulation of central pattern generator (CPG) circuits
- Advanced techniques for monitoring and manipulating neural circuits
- Modelling of neural circuits
- Sensory and motor functions of spinal cord circuits
- Brain circuits underlying motor control
- Circuits underlying non-associative and associative learning
- Addiction and learning circuits
- Defects in circuits
- Development of neural circuits

Module learning outcomes

To develop knowledge and critical understanding of the well-established principles of how simple and complex neural circuits operate and of the way in which those principles have developed. Understand that the output of neural circuits is controlled by a number of mechanisms that give the brain flexibility. These mechanisms include sensory feedback, neuromodulation and synaptic plasticity.

To acquire the ability to apply concepts and principles underlying circuit function outside the context in which they were first studied, e.g., in a behavioural context. Appreciate that understanding the neural mechanisms involved in the generation of behaviour depends on studying all levels of organization, behavioural, neural and cellular. Cellular analysis of neural circuits must have a behavioural context to be valuable.

To obtain a knowledge of the main methods of enquiry into the operation and functions of neural circuits, and an ability to evaluate critically the appropriateness of different approaches to solving problems in the field of neural circuits. Understand the importance of using advanced techniques in tracing and modelling circuit activity.

To understand the limits of our current knowledge of neural circuits, and how these limits influence analyses and interpretations based on the current level of knowledge.

To be able to use a range of established techniques to initiate and undertake critical analysis of information related to neural circuits, and to propose solutions to problems arising from that analysis.

To learn how to effectively communicate information, arguments and analysis in the form of a short written precis with critique type exercise and a longer essay.

TypeTimingWeighting
Computer Based ExamSemester 2 Assessment70.00%
Coursework30.00%
Coursework components. Weighted as shown below.
EssayT2 Week 9 100.00%
Timing

Submission deadlines may vary for different types of assignment/groups of students.

Weighting

Coursework components (if listed) total 100% of the overall coursework weighting value.

TermMethodDurationWeek pattern
Spring SemesterLecture1 hour22222222222

How to read the week pattern

The numbers indicate the weeks of the term and how many events take place each week.

Prof George Kemenes

Assess convenor, Convenor
/profiles/1469

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School of Engineering and Informatics (for staff and students)

School Office:
School of Engineering and Informatics, AVÊÓƵ, Chichester 1 Room 002, Falmer, Brighton, BN1 9QJ
ei@sussex.ac.uk
T 01273 (67) 8195

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