NMDAR-dependent emergence of behavioral representation in primary visual cortex

Puścian, Alicja; Benisty, H.; Higley, Michael J.

doi:10.1101/688366

Cited by 4 publications

(5 citation statements)

References 52 publications

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“…The stimulus-choice associations that animals were trained on were not reflected in the cotuning preferences of single cells (Fig 4). This was surprising in light of previous studies (Poort et al 2015, Puscian et al 2020), in which coherence between visual encoding and behavioral response emerged over training. There are a number of differences in these tasks that could account for these differences.…”

Section: Discussioncontrasting

confidence: 63%

Diversity and task-dependence of task representations in V1 during freely-moving decisions

Zhang

Zador

2022

Preprint

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Neurons in primary visual cortex (area V1) are strongly driven by both sensory stimuli and non-sensory events. However, although the representation of sensory stimuli has been well characterized, much less is known about the representation of non-sensory events. Here, we characterize the specificity and organization of non-sensory representations in rat V1 during a freely-moving visual decision task. We find that single neurons encode diverse combinations of task features simultaneously and across task epochs. Despite heterogeneity at the level of single neuron response patterns, both visual and non-visual task variables could be reliably decoded from small neural populations (5-40 units) throughout a trial. Interestingly, in animals trained to make an auditory decision following passive observation of a visual stimulus, some but not all task features could also be decoded from V1 activity. Our results support the view that even in V1 - the earliest stage of the cortical hierarchy - bottom-up sensory information is combined with top-down non-sensory information in a task-dependent manner.

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Section: Discussioncontrasting

confidence: 63%

Diversity and task-dependence of task representations in V1 during freely-moving decisions

Zhang

Zador

2022

Preprint

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“…Notably, we did not find similarly strong representation of sensory information in mesoscopic network activity, although this may reflect a lack of behavioral relevance for the stimuli as presented here. We and others have shown that training can modify the sensory and motor representations by single cortical neurons 12,[40][41][42] , and future studies must determine if sensory inputs that gain salience through experience are differentially encoded by large-scale cortical dynamics.…”

Section: Dynamic Functional Connectivity Suggests Distinct Cortical Subnetworkmentioning

confidence: 94%

“…However, this result may also reflect a lack of behavioral relevance for the stimuli as presented here. We and others have shown that training can modify the sensory and motor representations by single cortical neurons ( 14, 47-49 ), and future studies must determine if development, experience, or learning produce functional reorganization of large-scale networks.…”

Section: Dynamic Functional Connectivity Suggests Distinct Cortical S...mentioning

confidence: 97%

Rapid fluctuations in functional connectivity of cortical networks encode spontaneous

Benisty

Moberly²,

Lohani³

et al. 2021

Preprint

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Experimental work across a variety of species has demonstrated that spontaneously generated behaviors are robustly coupled to variation in neural activity within the cerebral cortex. Indeed, functional magnetic resonance imaging (fMRI) data suggest that functional connectivity in cortical networks varies across distinct behavioral states, providing for the dynamic reorganization of patterned activity. However, these studies generally lack the temporal resolution to establish links between cortical signals and the continuously varying fluctuations in spontaneous behavior typically observed in awake animals. Here, we took advantage of recent developments in wide-field, mesoscopic calcium imaging to monitor neural activity across the neocortex of awake mice. Applying a novel approach to quantifying time-varying functional connectivity, we show that spontaneous behaviors are more accurately represented by fast changes in the correlational structure versus the magnitude of large-scale network activity. Moreover, dynamic functional connectivity reveals subnetworks that are not predicted by traditional anatomical atlas-based parcellation of the cortex. These results provide insight into how behavioral information is represented across the mammalian neocortex and demonstrate a new analytical framework for investigating time-varying functional connectivity in neural networks.

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“…Finally, in the context of perceptual learning, it has been demonstrated that repeated presentation of grating stimuli can induce gain changes in cortical responses over many days during the performance of visual perception tasks [56,57]. Passive stimulus viewing alone may be sufficient to induce perceptual learning and incite changes for both gratings and natural stimuli [58,59], possibly with differences across stimuli.…”

Section: Differences In Rdi Between Stimuli Are Not Explained By Stimulus Temporal Structurementioning

confidence: 99%

Stimulus-dependent representational drift in primary visual cortex

Marks

Goard²

2020

Preprint

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To produce consistent sensory perception, neurons must maintain stable representations of sensory input. However, neurons in many regions exhibit progressive drift across days. Longitudinal studies have found stable responses to artificial stimuli across sessions in primary sensory areas, but it is unclear whether this stability extends to naturalistic stimuli. We performed chronic 2-photon imaging of mouse V1 populations to directly compare the representational stability of artificial versus naturalistic visual stimuli over weeks. Responses to gratings were highly stable across sessions. However, neural responses to naturalistic movies exhibited progressive representational drift across sessions. Differential drift was present across cortical layers, in inhibitory interneurons, and could not be explained by differential response magnitude or higher order stimulus statistics. However, representational drift was accompanied by similar differential changes in local population correlation structure. These results suggest representational stability in V1 is stimulus-dependent and related to differences in preexisting circuit architecture of co-tuned neurons.

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NMDAR-dependent emergence of behavioral representation in primary visual cortex

Cited by 4 publications

References 52 publications

Diversity and task-dependence of task representations in V1 during freely-moving decisions

Diversity and task-dependence of task representations in V1 during freely-moving decisions

Rapid fluctuations in functional connectivity of cortical networks encode spontaneous

Stimulus-dependent representational drift in primary visual cortex

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