A model of flexible motor sequencing through thalamic control of cortical dynamics

AbstractThe mechanisms by which neural circuits generate an extensible library of motor motifs and flexibly string them into arbitrary sequences are unclear. We developed a model in which inhibitory basal ganglia output neurons project to thalamic units that are themselves bidirectionally connected to a recurrent cortical network. During movement sequences, electrophysiological recordings of basal ganglia output neurons show sustained activity patterns that switch at the boundaries between motifs. Thus, we model these inhibitory patterns as silencing some thalamic neurons while leaving others disinhibited and free to interact with cortex during specific motifs. We show that a small number of disinhibited thalamic neurons can control cortical dynamics to generate specific motor output in a noise robust way. If the thalamic units associated with each motif are segregated, many motor outputs can be learned without interference and then combined in arbitrary orders for the flexible production of long and complex motor sequences.

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Distributed Dynamical Computation in Neural Circuits with Propagating Coherent Activity Patterns

PLoS Computational Biology ◽

10.1371/journal.pcbi.1000611 ◽

2009 ◽

Vol 5 (12) ◽

pp. e1000611 ◽

Cited By ~ 35

Author(s):

Pulin Gong ◽

Cees van Leeuwen

Keyword(s):

Neural Circuits ◽

Activity Patterns

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Recurrent circuitry is required to stabilize piriform cortex odor representations across brain states

eLife ◽

10.7554/elife.53125 ◽

2020 ◽

Vol 9 ◽

Cited By ~ 2

Author(s):

Kevin A Bolding ◽

Shivathmihai Nagappan ◽

Bao-Xia Han ◽

Fan Wang ◽

Kevin M Franks

Keyword(s):

Neural Activity ◽

Neural Circuits ◽

Activity Patterns ◽

Piriform Cortex ◽

Theoretical Studies ◽

Pattern Completion ◽

Attractor Networks ◽

Attractor Dynamics ◽

Brain States ◽

Associative Function

Pattern completion, or the ability to retrieve stable neural activity patterns from noisy or partial cues, is a fundamental feature of memory. Theoretical studies indicate that recurrently connected auto-associative or discrete attractor networks can perform this process. Although pattern completion and attractor dynamics have been observed in various recurrent neural circuits, the role recurrent circuitry plays in implementing these processes remains unclear. In recordings from head-fixed mice, we found that odor responses in olfactory bulb degrade under ketamine/xylazine anesthesia while responses immediately downstream, in piriform cortex, remain robust. Recurrent connections are required to stabilize cortical odor representations across states. Moreover, piriform odor representations exhibit attractor dynamics, both within and across trials, and these are also abolished when recurrent circuitry is eliminated. Here, we present converging evidence that recurrently-connected piriform populations stabilize sensory representations in response to degraded inputs, consistent with an auto-associative function for piriform cortex supported by recurrent circuitry.

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Representational drift in the mouse visual cortex

10.1101/2020.10.05.327049 ◽

2020 ◽

Cited By ~ 1

Author(s):

Daniel Deitch ◽

Alon Rubin ◽

Yaniv Ziv

Keyword(s):

Large Scale ◽

Activity Patterns ◽

Population Level ◽

Population Activity ◽

Cortical Areas ◽

Electrophysiological Recordings ◽

The Face ◽

Visual Cortical ◽

Mouse Visual Cortex ◽

Over Time

AbstractNeuronal representations in the hippocampus and related structures gradually change over time despite no changes in the environment or behavior. The extent to which such ‘representational drift’ occurs in sensory cortical areas and whether the hierarchy of information flow across areas affects neural-code stability have remained elusive. Here, we address these questions by analyzing large-scale optical and electrophysiological recordings from six visual cortical areas in behaving mice that were repeatedly presented with the same natural movies. We found representational drift over timescales spanning minutes to days across multiple visual areas. The drift was driven mostly by changes in individual cells’ activity rates, while their tuning changed to a lesser extent. Despite these changes, the structure of relationships between the population activity patterns remained stable and stereotypic, allowing robust maintenance of information over time. Such population-level organization may underlie stable visual perception in the face of continuous changes in neuronal responses.

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PHARMACOLOGIC ANALYSIS OF NEUROTRANSMITTER SYSTEMS SUBSERVING BASAL GANGLIA AND BRAINSTEM SUPPRESSION OF INTRALAMINAR THALAMIC NEURONS

Abstracts ◽

10.1016/b978-0-08-023768-8.52160-5 ◽

1978 ◽

pp. 823

Author(s):

Howard K. Strahlendorf ◽

Charles D. Barnes

Keyword(s):

Basal Ganglia ◽

Thalamic Neurons ◽

Neurotransmitter Systems ◽

Pharmacologic Analysis

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A dynamical model for the basal ganglia-thalamo-cortical oscillatory activity and its implications in Parkinson’s disease

Cognitive Neurodynamics ◽

10.1007/s11571-020-09653-y ◽

2020 ◽

Author(s):

Eva M. Navarro-López ◽

Utku Çelikok ◽

Neslihan S. Şengör

Keyword(s):

Parkinson’S Disease ◽

Parkinson's Disease ◽

Basal Ganglia ◽

Activity Patterns ◽

Dynamical Model ◽

Substantia Nigra Pars Compacta ◽

Oscillatory Activity ◽

Subcortical Structures ◽

Neuron Models ◽

Neuronal Patterns

AbstractWe propose to investigate brain electrophysiological alterations associated with Parkinson’s disease through a novel adaptive dynamical model of the network of the basal ganglia, the cortex and the thalamus. The model uniquely unifies the influence of dopamine in the regulation of the activity of all basal ganglia nuclei, the self-organised neuronal interdependent activity of basal ganglia-thalamo-cortical circuits and the generation of subcortical background oscillations. Variations in the amount of dopamine produced in the neurons of the substantia nigra pars compacta are key both in the onset of Parkinson’s disease and in the basal ganglia action selection. We model these dopamine-induced relationships, and Parkinsonian states are interpreted as spontaneous emergent behaviours associated with different rhythms of oscillatory activity patterns of the basal ganglia-thalamo-cortical network. These results are significant because: (1) the neural populations are built upon single-neuron models that have been robustly designed to have eletrophysiologically-realistic responses, and (2) our model distinctively links changes in the oscillatory activity in subcortical structures, dopamine levels in the basal ganglia and pathological synchronisation neuronal patterns compatible with Parkinsonian states, this still remains an open problem and is crucial to better understand the progression of the disease.

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Recognition of neural brain activity patterns correlated with complex motor activity

Saratov Fall Meeting 2017: Laser Physics and Photonics XVIII; and Computational Biophysics and Analysis of Biomedical Data IV ◽

10.1117/12.2315161 ◽

2018 ◽

Author(s):

Semen Kurkin ◽

Anastasia Runnova ◽

Vadim Grubov ◽

Vyacheslav Musatov ◽

Tatyana Yu. Efremova ◽

...

Keyword(s):

Motor Activity ◽

Brain Activity ◽

Activity Patterns ◽

Complex Motor

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Oscillations in cortico-basal ganglia circuits: implications for Parkinson’s disease and other neurologic and psychiatric conditions

Journal of Neurophysiology ◽

10.1152/jn.00590.2018 ◽

2019 ◽

Vol 122 (1) ◽

pp. 203-231 ◽

Cited By ~ 7

Author(s):

Pär Halje ◽

Ivani Brys ◽

Juan J. Mariman ◽

Claudio da Cunha ◽

Romulo Fuentes ◽

...

Keyword(s):

Parkinson’S Disease ◽

Parkinson's Disease ◽

Basal Ganglia ◽

Neuronal Activity ◽

Pathophysiological Mechanism ◽

Electrophysiological Recordings ◽

Wide Range ◽

Psychiatric Conditions ◽

Higher Cognitive Functions ◽

And Control

Cortico-basal ganglia circuits are thought to play a crucial role in the selection and control of motor behaviors and have also been implicated in the processing of motivational content and in higher cognitive functions. During the last two decades, electrophysiological recordings in basal ganglia circuits have shown that several disease conditions are associated with specific changes in the temporal patterns of neuronal activity. In particular, synchronized oscillations have been a frequent finding suggesting that excessive synchronization of neuronal activity may be a pathophysiological mechanism involved in a wide range of neurologic and psychiatric conditions. We here review the experimental support for this hypothesis primarily in relation to Parkinson’s disease but also in relation to dystonia, essential tremor, epilepsy, and psychosis/schizophrenia.

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