Behavior as a Window to the Brain: How Fine-Grained Behavioral Modelling Can Advance Neuroscience
A special issue of Behavioral Sciences (ISSN 2076-328X). This special issue belongs to the section "Cognition".
Deadline for manuscript submissions: closed (29 February 2024) | Viewed by 735
Special Issue Editors
Interests: discovering the behavioural and neural mechanisms underlying learning and flexibility through fine-grained data analysis and modelling, with a focus on the prefrontal cortex’s neural mechanisms during rule learning and shift
Interests: investigating the neuroscience of learning in songbirds, rodents, and humans through a combination of computational and statistical approaches, including reinforcement learning and latent variable models
Special Issue Information
Dear Colleagues,
In recent years, our knowledge of neural circuitry and its relation to behavior has progressed due to the fast advancement of technologies and computational tools to record, manipulate and analyse neurons in the brain. However, a deeper understanding of behavior has not yet received the same attention. Indeed, it is particularly challenging to investigate high cognitive functions and complex behaviors, such as decision-making, learning and cognitive flexibility. These complex behaviors rely on the coordinated activity of multiple brain regions, thus preventing full characterisation of behavior from the activity of single regions. Another caveat is that most available tools do not take into account individual variations and behavioral idiosyncrasies, focusing instead on group-level behavioral analysis. Furthermore, it is becoming clearer that specifics of the experimental protocol, such as training schedules and food-restriction considerations, introduce another source of variability in behavior and neural activity. In this Special Issue, we invite contributions on fine-grained behavioral modelling that can broaden our understanding of the computational principles of complex behavior, the importance of individual variations, and how behavior can advance our understanding of neural computation.
Dr. Silvia Maggi
Dr. Hazem Toutounji
Guest Editors
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Keywords
- behavioral modelling
- decision-making
- learning
- cognitive flexibility
- computational modelling
- behavioral neuroscience
- reinforcement learning
- algorithms
- protocol design
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