Stable representation of a naturalistic movie emerges from episodic activity with gain variability

AbstractVisual cortical responses are known to be highly variable across trials within an experimental session. However, the long-term stability of visual cortical responses is poorly understood. Here using chronic imaging of V1 in mice we show that neural responses to repeated natural movie clips are unstable across weeks. Individual neuronal responses consist of sparse episodic activity which are stable in time but unstable in gain across weeks. Further, we find that the individual episode, instead of neuron, serves as the basic unit of the week-to-week fluctuation. To investigate how population activity encodes the stimulus, we extract a stable one-dimensional representation of the time in the natural movie, using an unsupervised method. Most week-to-week fluctuation is perpendicular to the stimulus encoding direction, thus leaving the stimulus representation largely unaffected. We propose that precise episodic activity with coordinated gain changes are keys to maintain a stable stimulus representation in V1.

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Stable representation of a naturalistic movie emerges from episodic activity with gain variability

10.21203/rs.3.rs-126977/v1 ◽

2021 ◽

Author(s):

Ji Xia ◽

Tyler Marks ◽

Michael Goard ◽

Ralf Wessel

Keyword(s):

Basic Unit ◽

Experimental Session ◽

Population Activity ◽

Long Term Stability ◽

Stimulus Representation ◽

Cortical Responses ◽

Stable Representation ◽

The Individual ◽

Visual Cortical ◽

Episodic Activity

Abstract Visual cortical responses are known to be highly variable across trials within an experimental session. However, the long-term stability of visual cortical responses is poorly understood. Chronic imaging experiments in V1 showed that neural responses to repeated natural movie clips were unstable across weeks. Single neuronal responses consisted of sparse episodic activity which were stable in time but unstable in spike rates across weeks. Further, we found that the individual episode, instead of neuron, served as the basic unit of the week-to-week fluctuation. To investigate how population activity encodes the stimulus, we extracted a stable one-dimensional representation of the time in the natural movie, using an unsupervised method. Moreover, most week-to-week fluctuation was perpendicular to the stimulus encoding direction, thus leaving the stimulus representation largely unaffected. We propose that precise episodic activity with coordinated gain changes are keys to maintain a stable stimulus representation in V1.

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Spontaneous behaviors drive multidimensional, brain-wide activity

10.1101/306019 ◽

2018 ◽

Cited By ~ 29

Author(s):

Carsen Stringer ◽

Marius Pachitariu ◽

Nicholas Steinmetz ◽

Charu Bai Reddy ◽

Matteo Carandini ◽

...

Keyword(s):

Visual Cortex ◽

Spontaneous Activity ◽

Random Noise ◽

Population Activity ◽

Sensory Stimuli ◽

Cortical Responses ◽

Ongoing Behavior ◽

Visual Cortical ◽

Mouse Visual Cortex ◽

Behavioral Information

Cortical responses to sensory stimuli are highly variable, and sensory cortex exhibits intricate spontaneous activity even without external sensory input. Cortical variability and spontaneous activity have been variously proposed to represent random noise, recall of prior experience, or encoding of ongoing behavioral and cognitive variables. Here, by recording over 10,000 neurons in mouse visual cortex, we show that spontaneous activity reliably encodes a high-dimensional latent state, which is partially related to the mouse’s ongoing behavior and is represented not just in visual cortex but across the forebrain. Sensory inputs do not interrupt this ongoing signal, but add onto it a representation of visual stimuli in orthogonal dimensions. Thus, visual cortical population activity, despite its apparently noisy structure, reliably encodes an orthogonal fusion of sensory and multidimensional behavioral information.

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Cortical idiosyncrasies predict the perception of object size

10.1101/026989 ◽

2015 ◽

Author(s):

Christina Moutsiana ◽

Benjamin de Haas ◽

Andriani Papageorgiou ◽

Jelle A. van Dijk ◽

Annika Balraj ◽

...

Keyword(s):

Neuronal Population ◽

Size Perception ◽

Visual Object ◽

Object Size ◽

Population Activity ◽

Neuronal Populations ◽

Individual Perception ◽

The Individual ◽

Visual Size ◽

Visual Cortical

AbstractPerception is subjective. Even basic judgments, like those of visual object size, vary substantially between observers and also across the visual field within the same observer. The way in which the visual system determines the size of objects remains unclear, however. We hypothesize that object size is inferred from neuronal population activity in V1 and predict that idiosyncrasies in cortical functional architecture should therefore explain individual differences in size judgments. Indeed, using novel behavioral methods and functional magnetic resonance imaging (fMRI) we demonstrate that biases in size perception are correlated with the spatial tuning of neuronal populations in healthy volunteers. To explain this relationship, we formulate a population read-out model that directly links the spatial distribution of V1 representations to our perceptual experience of visual size. Altogether, we suggest that the individual perception of simple stimuli is warped by idiosyncrasies in visual cortical organization.

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Reticular facilitation of cat visual cortical responses is mediated by nicotinic and muscarinic cholinergic mechanisms

Experimental Brain Research ◽

10.1007/bf00230433 ◽

1993 ◽

Vol 96 (1) ◽

pp. 1-7 ◽

Cited By ~ 19

Author(s):

M. H. Lewandowski ◽

C. M. Müller ◽

W. Singer

Keyword(s):

Cholinergic Mechanisms ◽

Cortical Responses ◽

Muscarinic Cholinergic ◽

Visual Cortical

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Context-Dependent Modulation of Early Visual Cortical Responses to Numerical and Nonnumerical Magnitudes

Journal of Cognitive Neuroscience ◽

10.1162/jocn_a_01774 ◽

2021 ◽

pp. 1-12

Author(s):

Joonkoo Park ◽

Sonia Godbole ◽

Marty G. Woldorff ◽

Elizabeth M. Brannon

Keyword(s):

Visual Processing ◽

Context Dependency ◽

Numerical Magnitude ◽

Continuous Variables ◽

Processing Stream ◽

Cortical Responses ◽

Early Visual Cortex ◽

Context Dependent ◽

Visual Cortical ◽

The Brain

Abstract Whether and how the brain encodes discrete numerical magnitude differently from continuous nonnumerical magnitude is hotly debated. In a previous set of studies, we orthogonally varied numerical (numerosity) and nonnumerical (size and spacing) dimensions of dot arrays and demonstrated a strong modulation of early visual evoked potentials (VEPs) by numerosity and not by nonnumerical dimensions. Although very little is known about the brain's response to systematic changes in continuous dimensions of a dot array, some authors intuit that the visual processing stream must be more sensitive to continuous magnitude information than to numerosity. To address this possibility, we measured VEPs of participants viewing dot arrays that changed exclusively in one nonnumerical magnitude dimension at a time (size or spacing) while holding numerosity constant and compared this to a condition where numerosity was changed while holding size and spacing constant. We found reliable but small neural sensitivity to exclusive changes in size and spacing; however, changing numerosity elicited a much more robust modulation of the VEPs. Together with previous work, these findings suggest that sensitivity to magnitude dimensions in early visual cortex is context dependent: The brain is moderately sensitive to changes in size and spacing when numerosity is held constant, but sensitivity to these continuous variables diminishes to a negligible level when numerosity is allowed to vary at the same time. Neurophysiological explanations for the encoding and context dependency of numerical and nonnumerical magnitudes are proposed within the framework of neuronal normalization.

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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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Early visual cortical responses produced by checkerboard pattern stimulation

NeuroImage ◽

10.1016/j.neuroimage.2016.03.078 ◽

2016 ◽

Vol 134 ◽

pp. 532-539 ◽

Cited By ~ 9

Author(s):

Yoshihito Shigihara ◽

Hideyuki Hoshi ◽

Semir Zeki

Keyword(s):

Checkerboard Pattern ◽

Cortical Responses ◽

Pattern Stimulation ◽

Visual Cortical

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Agenesis of Maxillary Lateral Incisors: Treatment Involves Much More Than Just Canine Guidance

The Open Dentistry Journal ◽

10.2174/1874210601610010019 ◽

2016 ◽

Vol 10 (1) ◽

pp. 19-27 ◽

Cited By ~ 2

Author(s):

Giordani Santos Silveira ◽

José Nelson Mucha

Keyword(s):

Decision Making ◽

Literature Review ◽

Clinical Features ◽

Congenital Absence ◽

Term Stability ◽

Long Term Stability ◽

Canine Guidance ◽

The Individual ◽

Inform Decision Making

Objective: In this study, we aimed highlight some clinical features present in patients whose maxillary lateral incisors are missing, and proposed more logical, rational and predictable solutions to inform decision making in rehabilitation procedures. Methods: Literature review and discussion. Conclusion: Choosing the best possible treatment for congenital absence of maxillary lateral incisors depends on the multidisciplinary diagnosis of facial, occlusal, functional and periodontal features. It also depends on the individual long-term stability, and it does not only rely on canine-guided disocclusion.

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Temporal Integration by Stochastic Recurrent Network Dynamics With Bimodal Neurons

Journal of Neurophysiology ◽

10.1152/jn.01100.2006 ◽

2007 ◽

Vol 97 (6) ◽

pp. 3859-3867 ◽

Cited By ~ 27

Author(s):

Hiroshi Okamoto ◽

Yoshikazu Isomura ◽

Masahiko Takada ◽

Tomoki Fukai

Keyword(s):

Cortical Neurons ◽

Cognitive Task ◽

Temporal Integration ◽

Activity Patterns ◽

Recurrent Network ◽

External Input ◽

Delay Period ◽

Anterior Cingulate ◽

Population Activity ◽

The Individual

Temporal integration of externally or internally driven information is required for a variety of cognitive processes. This computation is generally linked with graded rate changes in cortical neurons, which typically appear during a delay period of cognitive task in the prefrontal and other cortical areas. Here, we present a neural network model to produce graded (climbing or descending) neuronal activity. Model neurons are interconnected randomly by AMPA-receptor–mediated fast excitatory synapses and are subject to noisy background excitatory and inhibitory synaptic inputs. In each neuron, a prolonged afterdepolarizing potential follows every spike generation. Then, driven by an external input, the individual neurons display bimodal rate changes between a baseline state and an elevated firing state, with the latter being sustained by regenerated afterdepolarizing potentials. When the variance of background input and the uniform weight of recurrent synapses are adequately tuned, we show that stochastic noise and reverberating synaptic input organize these bimodal changes into a sequence that exhibits graded population activity with a nearly constant slope. To test the validity of the proposed mechanism, we analyzed the graded activity of anterior cingulate cortex neurons in monkeys performing delayed conditional Go/No-go discrimination tasks. The delay-period activities of cingulate neurons exhibited bimodal activity patterns and trial-to-trial variability that are similar to those predicted by the proposed model.

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