Aims

To provide in depth knowledge and understanding of the conceptual foundations, benefits, theories, and methods of understanding brain function in terms of neural mechanisms, in particular:
i.       The historical and philosophical aspects of thinking of the brain/mind as a computational device that produces behaviour and cognition
ii.       Key concepts underpinning conceptual models of brain function, learning and behaviour
iii.       The variety of methods employed in this endeavour
a) The relationship between experiments and models
b) The relationship between models and biology
c) Levels of abstraction (close vs far from the biology)
d) The notion of complex behaviour arising from many simple, interacting mechanisms
iv.       What constitutes an explanation of brain function?
v.       Get to know simple, yet influential paradigmatic examples

Outline Of Syllabus

-       Introduction and concepts
Including a historical introduction and philosophy of mind relating to neural accounts of the mind
-       Biological and artificial neurons and networks
e.g. connectionist neurons, rate and spiking neurons. Learning as modification of synaptic connections
(Hebb)
-       Neural representation and computation
What is a neural representation? What does it mean for the brain to compute something?
Localist vs distributed representations and the evidence for them
-       Applications to case studies with a focus on spatial cognition, and memory
Can we reach a neural-level understanding of brain function?
      Relationship to neurological disorders and neuropsychology
E.g. hemi-spatial neglect
-       A new outlook: a mechanistic framework for thinking about the brain, neuropsychology and psychiatry

Teaching Rationale And Relationship

The initial lectures will be used to convey the basic knowledge, historical background, and key concepts about brain function from a biological and philosophical perspective. The latter will naturally lead into an introduction of neural accounts of the mind/brain and cognition/behaviour. These introductory lectures will set the stage for an in-depth exploration of the components that are needed to understand and develop the notion of a representational and computational account of the brain/mind. Following this groundwork, the ideas will be applied to several model systems (paradigmatic examples), and it will be explored how the emerging view (emerging during the progression of the module that is) can be used to frame behaviour, cognition, neurological disorders and neuropsychological findings.

Finally, students will also participate in a demonstration session (during the lecture hours of a lecture late in the module) in the computer lab, where they can run a few pre-programmed models under the guidance of the module leader, to observe the process of using models first-hand. This session will not be exam-relevant but will allow for a hands-on experience of how the approach that is taught in the module can be implemented in the real world.

Assessment Rationale And Relationship

In the mid module coursework assignment students will then be asked to apply their knowledge to create a poster on a specific topic or published paper. This will be the first summative assessment and will assess key skill outcomes Guidance, templates and software will be provided. Poster will be presented in a separate session with all students that will provide an opportunity for formative practice. Only the quality of the poster itself is assessed. Beyond an in-depth exploration of a particular topic, the students will thus also learn additional kills of making and presenting a poster, underlining the utility of the module for students with more research-oriented/academic ambitions (e.g., aiming at an MRes)

The final assessment of the module will consist of an exam where students answer a selection of short answer questions, with a targeted word count of approximately 2000 words for the 2-hour exam.  These questions will assess the module knowledge outcomes fully.

The formative assessment requires the student to submit answers to short answer questions indicative of the final exam. This will allow the module leader to give feedback, e.g., suggesting strategies for writing focused, concise answers to these exam-like question.