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Description
Content: Computational models play a fundamental role in neuroscience, both in terms of theory and in assisting data analysis. Likewise, neural network models inspired by the brain are powering the current AI revolution. The module will provide students with a broad and coherent overview of computational cognitive neuroscience. This overview should provide the scaffolding for students to dive deeper into specific topics.
Teaching delivery: This module is taught in 15 hours of in-person lectures spread over 10 teaching weeks (usually 5 1-hour lectures in one half of term and 5 2-hour sessions in the other half of term).
Indicative Topics: Indicative lecture topics (subject to possible changes): This module will cover topics ranging from simple learning rules to large-scale systems for object recognition. We'll consider what formal approaches have to say about popular topics in neuroscience, such as replay, cell types (e.g., place and grid cells), and manifolds.
Module Aims: By the end of the module students should gain:
- A broad and coherent overview of computational cognitive neuroscience
- Deeper insight into specific topics of interest
- The ability to integrate material across lecture topics to generate their own mock grant proposal
Module deliveries for 2024/25 academic year
Last updated
This module description was last updated on 19th August 2024.
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