2020
DOI: 10.1111/ejn.14864
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Assessing within‐trial and across‐trial neural variability in macaque frontal eye fields and their relation to behaviour

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 … Show more

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Cited by 8 publications
(10 citation statements)
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“…2 B and C; B-nG: P = 0.74, t test; G-nG: P < 0.001, t test). Although the neural activity was spatially tuned, the FF was untuned, consistent with previous reports (3,7,15). That is, the changes in FFs were similar for saccades into the RF and saccades out of the RF (aRF) for both types of saccades (G: RF-aRF: P = 0.10, ranksum test; nG: RF-aRF: P = 0.62, rank-sum test) even though the firing rates were significantly different between RF and aRF by definition (G: RF-aRF: P < 0.001, paired t test; nG: RF-aRF: P < 0.001, paired t test).…”
Section: Significancesupporting
confidence: 89%
See 1 more Smart Citation
“…2 B and C; B-nG: P = 0.74, t test; G-nG: P < 0.001, t test). Although the neural activity was spatially tuned, the FF was untuned, consistent with previous reports (3,7,15). That is, the changes in FFs were similar for saccades into the RF and saccades out of the RF (aRF) for both types of saccades (G: RF-aRF: P = 0.10, ranksum test; nG: RF-aRF: P = 0.62, rank-sum test) even though the firing rates were significantly different between RF and aRF by definition (G: RF-aRF: P < 0.001, paired t test; nG: RF-aRF: P < 0.001, paired t test).…”
Section: Significancesupporting
confidence: 89%
“…We studied two characteristics of neural response not directly visible in the firing rate but which precede movements: a decrease in neural response variability (3) and a decrease in local field potential (LFP) beta oscillatory activity (4,5). Previous studies have shown that decreases in response variability are correlated with attention (6), planning of saccades (3,7,8), the onset of a visual stimulus (3,9), and the amount of expected reward (10), among other processes. Decreases in beta power have been correlated with motor preparation and inhibitory control (11,12), among other processes (13).…”
mentioning
confidence: 99%
“…The activity of FEF movement neurons closely follows accumulator dynamics and represents a decisionmaking stage, which has been found to be capacity-limited in computational models Ray et al, 2012;Sigman & Dehaene, 2005). Further, FEF is a higher-order control center for goal-directed saccadic planning (Sendhilnathan, Basu, Goldberg, Schall, & Murthy, 2019;Sendhilnathan, Basu, & Murthy, 2017, 2020. Finally, FEF movement neurons encode two saccade plans in parallel (Basu and Murthy, 2019).…”
Section: Introductionmentioning
confidence: 96%
“…To investigate the neural architecture of saccade-related bottlenecks, we recorded neural activity from the frontal eye field (FEF) of macaque monkeys performing a sequential saccade task. FEF is a good candidate region to study the neural imprints of processing bottlenecks since it is a higher-order control center for goal-directed saccadic planning (Sendhilnathan et al, 2021; Sendhilnathan et al, 2017, 2020). Further, the activity of FEF movement neurons follow the dynamics of accumulator models and resemble the central capacity-limited stage observed in computational models of dual-task studies (Hanes and Schall, 1996; Ray et al, 2012; Sigman and Dehaene, 2005).…”
Section: Introductionmentioning
confidence: 99%
“…Some of the methods that were used in this study have been described in detail elsewhere (49)(50)(51). Here, we describe them briefly.…”
Section: Methodsmentioning
confidence: 99%