Biology subjects

Schall, J. D.

Publications and source records attributed to Schall, J. D..

5 recordsLinked to original sources

bioRxiv2017

Functional categories in macaque frontal eye field

Frontal eye field (FEF) in macaque monkeys contributes to visual attention, visual-motor transformations and production of eye movements. Traditionally, neurons in FEF have been classified by the magnitude of increased discharge rates following visual stimulus presentation, during a waiting period, and associated with eye movement production. However, considerable heterogeneity remains within the traditional visual, visuomovement and movement categories. Cluster analysis is a data-driven method of identifying self-segregating groups within a dataset. Because many cluster analysis techniques exist and cluster outcomes vary with analysis assumptions, consensus clustering aggregates over multiple cluster analyses, identifying robust groups. To describe more comprehensively the neuronal composition of FEF, we applied a consensus clustering technique for unsupervised categorization of patterns of spike rate modulation measured during a memory-guided saccade task. We report ten functional categories, expanding on the traditional three. Categories were distinguished by latency, magnitude, and sign of visual response, presence of sustained activity, and dynamics, magnitude and sign of saccade-related modulation. Consensus clustering can include other metrics and can be applied to datasets from other brain regions to provides better information guiding microcircuit models of cortical function.\n\nSIGNIFICANCE STATEMENTThe contribution of a brain region cannot be understood without knowing the diversity, arrangement, and circuitry of constituent neurons. Traditional descriptions of frontal eye field include visual, visuo-saccadic, and saccadic categories. Here, we employ a novel consensus clustering method to identify more reliably functional categories in neural data. While confirming the traditional categories, consensus clustering distinguishes additional, previously unappreciated diversity in neural activity patterns. Such information is necessary to formulate correct microcircuit models of cortical function.

neuroscience↗

bioRxiv2017

Neural mechanisms of speed-accuracy tradeoff of visual search: Saccade vigor, targeting errors, superior colliculus and frontal eye field

Balancing the speed-accuracy tradeoff (SAT) is necessary for successful behavior. Using a visual search task with interleaved cues emphasizing speed or accuracy, we recently reported diverse contributions of frontal eye field (FEF) neurons instantiating salience evidence and response preparation. Here we report replication of visual search SAT performance in two macaque monkeys, new information about variation of saccade dynamics with SAT, extension of the neurophysiological investigation to describe processes in the superior colliculus, and description of the origin of search errors in this task. Saccade vigor varied idiosyncratically across SAT conditions and monkeys, but tended to decrease with response time. As observed in the FEF, speed-accuracy tradeoff was accomplished through several distinct adjustments in the superior colliculus. Visually-responsive neurons modulated baseline firing rate and the time course of salience evidence. Unlike FEF, the magnitude of visual responses in SC did not vary across SAT conditions, but the time to locate the target was longer in Accurate as compared to Fast trials. Also unlike FEF, the activity of SC movement neurons when saccades were initiated was equivalent in Fast and Accurate trials. Search errors occurred when visual salience neurons in FEF and SC treated distractors as targets, even in the Accurate condition. Saccade-related neural activity in SC but less FEF varied with saccade peak velocity. These results extend our understanding of the cortical and subcortical contributions to SAT.\n\nSignificance statementNeurophysiological mechanisms of speed-accuracy tradeoff (SAT) have only recently been investigated. This paper reports the first replication of SAT performance in nonhuman primates, the first report of variation of saccade dynamics with SAT, the first description of superior colliculus contributions to SAT, and the first description of the origin of errors during SAT. These results inform and constrain new models of distributed decision-making.

neuroscience↗

bioRxiv2017

Prefrontal control of visual distraction

Avoiding distraction by salient irrelevant stimuli is critical to accomplishing daily tasks. Regions of prefrontal cortex control attention by enhancing the representation of task-relevant information in sensory cortex, which can be measured directly in modulation of both single neurons and averaging of the scalp-recorded electroencephalogram [1,2]. However, when irrelevant information is particularly conspicuous, it may distract attention and interfere with the selection of behaviorally relevant information. Many studies have shown that that distraction can be minimized via top-down control [3-5], but the cognitive and neural mechanisms giving rise to this control over distraction remain uncertain and vigorously debated [6-8]. Bridging neurophysiology to electrophysiology, we simultaneously recorded neurons in prefrontal cortex and event-related potentials (ERPs) over extrastriate visual cortex to track the processing of salient distractors during a visual search task. Critically, we observed robust suppression of salient distractor representations in both cortical areas, with suppression arising in prefrontal cortex before being manifest in the ERP signal over extrastriate cortex. Furthermore, only prefrontal neurons that participated in selecting the task-relevant target also showed suppression of the task-irrelevant distractor. This suggests a common prefrontal mechanism for target selection and distractor suppression, with input from prefrontal cortex being responsible for both selecting task-relevant and suppressing task-irrelevant information in sensory cortex. Taken together, our results resolve a long-standing debate over the mechanisms that prevent distraction, and provide the first evidence directly linking suppressed neural firing in prefrontal cortex with surface ERP measures of distractor suppression.

neuroscience↗

bioRxiv2017

Microcircuitry of Performance Monitoring

AcknowledgmentsThis work was supported by R01-MH55806, P30-EY08126, and by Robin and Richard Patton through the E. Bronson Ingram Chair in Neuroscience. We thank J. Easley M. Feurtado, M. Maddox, P. Middlebrooks, S. Motorny, J. Parker, M. Schall, C.R. Subraveti, A. Tomarken, and L. Toy for animal care and other technical assistance. We thank J. Brown, M. Cox, K. Dougherty, S. Errington, A. Maier, V. Stuphorn, A. Tomarken, and J. Westerberg for helpful discussions and comments on the manuscript.\n\nConflicts of interestNone\n\nCortical circuit mechanisms in medial frontal cortex enabling executive control are unknown. Hence, in monkeys performing a saccade countermanding task to earn larger or smaller fluid rewards, we sampled spiking and synaptic activity simultaneously across all layers of the supplementary eye field (SEF), an agranular cortical area contributing to performance monitoring in nonhuman primate and human studies. Laminar-specific synaptic currents with associated spike rate facilitation and suppression represented error production, reward gain or loss feedback, and reward delivery. The latency, polarity and magnitude of current and spike rate modulation were not predicted by the canonical cortical microcircuit. Pronounced synaptic currents in layer 2/3, which are modulated by loss magnitude, will contribute to the error-related negativity (ERN) and feedback-related negativity (FRN). These unprecedented findings reveal critical features of the cortical microcircuitry supporting performance monitoring and demonstrate that SEF can contribute to the error- and feedback-related negativity.\n\nSubject termscountermanding, stop signal task, goal selection, response inhibition, executive control, canonical cortical microcircuit, error-related negativity, reinforcement learning, reward prediction error

neuroscience↗

bioRxiv2017

Unification of Countermanding and Perceptual Decision-making

Perceptual decision-making, studied using two-alternative forced-choice tasks, is explained by sequential sampling models of evidence accumulation, which correspond to the dynamics of neurons in sensorimotor structures of the brain12. Response inhibition, studied using stop-signal (countermanding) tasks, is explained by a race model of the initiation or canceling of a response, which correspond to the dynamics of neurons in sensorimotor structures34. Neither standard model accounts for performance of the other task. Sequential sampling models incorporate response initiation as an uninterrupted non-decision time parameter independent of task-related variables. The countermanding race model does not account for the choice process. Here we show with new behavioral, neural and computational results that perceptual decision making of varying difficulty can be countermanded with invariant efficiency, that single prefrontal neurons instantiate both evidence accumulation and response inhibition, and that an interactive race between two GO and one STOP stochastic accumulator fits countermanding choice behavior. Thus, perceptual decision-making and response control, previously regarded as distinct mechanisms, are actually aspects of more flexible behavior supported by a common neural and computational mechanism. The identification of this aspect of decision-making with response production clarifies the component processes of decision-making.

neuroscience↗