Journal
EUROPEAN JOURNAL OF NEUROSCIENCE
Volume 52, Issue 10, Pages 4267-4282Publisher
WILEY
DOI: 10.1111/ejn.14864
Keywords
Saccade; prefrontal cortex; cognition; computational model
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Funding
- Department of Biotechnology - Indian Institute of Science (DBT-IISc) partnership programme grant
- Intensification of Research in High Priority Areas Grant from the Department of Science and Technology, Government of India
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The conventional approach to understanding neural responses underlying complex computations is to study across-trial averages of repeatedly performed computations from single neurons. When neurons perform complex computations, such as processing stimulus-related information or movement planning, it has been repeatedly shown, through measures such as the Fano factor (FF), that neural variability across trials decreases. However, multiple neurons contribute to a common computation on a single trial, rather than a single neuron contributing to a computation across multiple trials. Therefore, at the level of a single trial, the concept of FF loses significance. Here, using a combination of simulations and empirical data, we show that changes in the spiking regularity on single trials produce changes in FF. Further, at the behavioural level, the reaction time of the animal was faster when the neural spiking regularity both within and across trials was lower. Taken together, our results provide further constraints on how changes in spiking statistics help neurons optimally encode visual and saccade-related information across multiple timescales and its implication on behaviour.
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