Assessing within‐trial and across‐trial neural variability in macaque frontal eye fields and their relation to behaviour. (25th July 2020)

• Record Type: Journal Article
• Authors: Sendhilnathan, Naveen; Basu, Debaleena; Murthy, Aditya
• Is Part Of: European journal of neuroscience. Volume 52:Number 10(2020)
• Page Start: 4267
• Page End: 4282
• Publication Date: 2020-07-25
• Subjects: Saccade -- prefrontal cortex -- cognition -- computational model; Nervous system -- Periodicals; 612.8
• DOI: 10.1111/ejn.14864
• Languages: English
• ISSNs: 0953-816X

Abstract

Abstract: 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. Abstract : During computations, neural variability across trials decreases. In reality, multiple neurons contribute to a common computation on a single trial, rather than a single neuron contributing to a computation on multiple trials. We found that when neurons perform a common computation, they briefly fire with increased regularity in spike timings as well as decreased variability across trials (b). Lower variability was also correlated with faster reaction times.