Working Memory Gates Visual Input to Primate Prefrontal Neurons

Noudoost, Behrad; Clark, Kelsey; Moore, Tirin

doi:10.1101/2020.11.09.375287

Cited by 2 publications

(2 citation statements)

References 48 publications

(52 reference statements)

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“…parietal-prefrontal network, where persistent activity is seen during working memory tasks 55,88 . Indeed, recent studies of brain activity in humans has shown that functional network connectivity during spontaneous epochs is highly dynamic 89 , and that persistent activity during working memory gates the propagation of activity, and thus information, into the prefrontal network 90 .…”

Section: Discussionmentioning

confidence: 99%

Theory of spontaneous persistent activity and inactivity in vivo reveals differential cortico-entorhinal functional connectivity

Mehta

Choudhary

Berberich

et al. 2022

Preprint

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Persistent activity is thought to mediate working memory. While such stimulus evoked persistence is well studied, mechanisms of internally generated or spontaneous persistence in vivo are unknown. Further, current theories based on attractor dynamics focus on elevated activity as a memory substrate, while little attention has focused on the role of inactivity attractors. Here, we present a mean field model of functional interaction between large cortical networks that predicts both spontaneous persistent activity (SPA) and inactivity (SPI); the latter has never been seen before in experiments or models. We confirm these predictions using simultaneously recorded neocortical local field potential (LFP) and the membrane potential (Vm) of identified excitatory neurons from several brain areas in vivo during slow oscillations, especially from layer 3 of the medial (MECIII) and lateral entorhinal cortex (LECIII), which show SPA and SPI. By matching model and experimental statistics, we predict the relative strength of internal and external excitation in the LECIII and MECIII networks. Our predictions match anatomical data. Further, the model predicts, and the experiments confirm, that SPA and SPI are quantized by cortical UDS and follow the statistics of a history dependent Bernoulli process. These convergent, theory-experiment results thus reveal the differential nature of cortico-entorhinal functional connectivity, resulting in a unique pattern of persistent activity and persistent inactivity, a novel and energetically efficient memory substrate.

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Section: Discussionmentioning

confidence: 99%

Theory of spontaneous persistent activity and inactivity in vivo reveals differential cortico-entorhinal functional connectivity

Mehta

Choudhary

Berberich

et al. 2022

Preprint

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“…Such activity is characteristic of working memory [46][47][48] . During motor planning in tasks with working memory, DAN has been shown to maintain task-relevant information, such as target location, during delay periods using persistent activity in both whole-brain and single unit recordings [49][50][51] . DAN has also been linked to working memory closely tied to visual attenuation related to memory load and top-down memory attention control during visual working memory tasks [52] .…”

Section: Modulation Of Dorsal Attention Network With Error History An...mentioning

confidence: 99%

Internal states as a source of subject-dependent movement variability and their representation by large-scale networks

Breault

Sacré

Fitzgerald

et al. 2022

Preprint

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A human's ability to adapt and learn relies on reflecting on past performance. Such reflections form latent factors called internal states that induce variability of movement and behavior to improve performance. Internal states are critical for survival, yet their temporal dynamics and neural substrates are less understood. Here, we link internal states with motor performance and neural activity using state-space models and local field potentials captured from depth electrodes in over 100 brain regions. Ten human subjects performed a goal-directed center-out reaching task with perturbations applied to random trials, causing subjects to fail goals and reflect on their performance. Using computational methods, we identified two internal states, indicating that subjects kept track of past errors and perturbations, that predicted variability in reaction times and speed errors. These states granted access to latent information indicative of how subjects strategize learning from trial history, impacting their overall performance. We further found that large-scale brain networks differentially encoded these internal states. The dorsal attention network encoded past errors in frequencies above 100 Hz, suggesting a role in modulating attention based on tracking recent performance in working memory. The default network encoded past perturbations in frequencies below 15 Hz, suggesting a role in achieving robust performance in an uncertain environment. Moreover, these networks more strongly encoded internal states and were more functionally connected in higher performing subjects, whose learning strategy was to respond by countering with behavior that opposed accumulating error. Taken together, our findings suggest large-scale brain networks as a neural basis of strategy. These networks regulate movement variability, through internal states, to improve motor performance.

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Working Memory Gates Visual Input to Primate Prefrontal Neurons

Cited by 2 publications

References 48 publications

Theory of spontaneous persistent activity and inactivity in vivo reveals differential cortico-entorhinal functional connectivity

Theory of spontaneous persistent activity and inactivity in vivo reveals differential cortico-entorhinal functional connectivity

Internal states as a source of subject-dependent movement variability and their representation by large-scale networks

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