Dataset Information

Cortical microcircuitry of performance monitoring.

ABSTRACT: The medial frontal cortex enables performance monitoring, indexed by the error-related negativity (ERN) and manifested by performance adaptations. We recorded electroencephalogram over and neural spiking across all layers of the supplementary eye field, an agranular cortical area, in monkeys performing a saccade-countermanding (stop signal) task. Neurons signaling error production, feedback predicting reward gain or loss, and delivery of fluid reward had different spike widths and were concentrated differently across layers. Neurons signaling error or loss of reward were more common in layers 2 and 3 (L2/3), whereas neurons signaling gain of reward were more common in layers 5 and 6 (L5/6). Variation of error- and reinforcement-related spike rates in L2/3 but not L5/6 predicted response time adaptation. Variation in error-related spike rate in L2/3 but not L5/6 predicted ERN magnitude. These findings reveal novel features of cortical microcircuitry supporting performance monitoring and confirm one cortical source of the ERN.

SUBMITTER: Sajad A

PROVIDER: S-EPMC6348027 | biostudies-literature | 2019 Feb

REPOSITORIES: biostudies-literature

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Cortical microcircuitry of performance monitoring.

Sajad Amirsaman A Godlove David C DC Schall Jeffrey D JD

Nature neuroscience 20190114 2

The medial frontal cortex enables performance monitoring, indexed by the error-related negativity (ERN) and manifested by performance adaptations. We recorded electroencephalogram over and neural spiking across all layers of the supplementary eye field, an agranular cortical area, in monkeys performing a saccade-countermanding (stop signal) task. Neurons signaling error production, feedback predicting reward gain or loss, and delivery of fluid reward had different spike widths and were concentra ...[more]

PMID: 30643297

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Project description:Real-time monitoring of the brain is potentially valuable for performance monitoring, communication, training or rehabilitation. In natural situations, the brain performs a complex mix of various sensory, motor or cognitive functions. Thus, real-time brain monitoring would be most valuable if (a) it could decode information from multiple brain systems simultaneously, and (b) this decoding of each brain system were robust to variations in the activity of other (unrelated) brain systems. Previous studies showed that it is possible to decode some information from different brain systems in retrospect and/or in isolation. In our study, we set out to determine whether it is possible to simultaneously decode important information about a user from different brain systems in real time, and to evaluate the impact of concurrent activity in different brain systems on decoding performance.We study these questions using electrocorticographic signals recorded in humans. We first document procedures for generating stable decoding models given little training data, and then report their use for offline and for real-time decoding from 12 subjects (six for offline parameter optimization, six for online experimentation). The subjects engage in tasks that involve movement intention, movement execution and auditory functions, separately, and then simultaneously. Main Results: Our real-time results demonstrate that our system can identify intention and movement periods in single trials with an accuracy of 80.4% and 86.8%, respectively (where 50% would be expected by chance). Simultaneously, the decoding of the power envelope of an auditory stimulus resulted in an average correlation coefficient of 0.37 between the actual and decoded power envelopes. These decoders were trained separately and executed simultaneously in real time.This study yielded the first demonstration that it is possible to decode simultaneously the functional activity of multiple independent brain systems. Our comparison of univariate and multivariate decoding strategies, and our analysis of the influence of their decoding parameters, provides benchmarks and guidelines for future research on this topic.

Dataset Information

Cortical microcircuitry of performance monitoring.

Publications

Cortical microcircuitry of performance monitoring.

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