scholarly journals Spontaneous behaviors drive multidimensional, brainwide activity

Science ◽  
2019 ◽  
Vol 364 (6437) ◽  
pp. eaav7893 ◽  
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 ◽  
Neuronal Populations ◽  
Ongoing Behavior ◽  
Visual Cortical ◽  
Mouse Visual Cortex ◽  
External Stimuli

Neuronal populations in sensory cortex produce variable responses to sensory stimuli and exhibit 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. Recording more than 10,000 neurons in mouse visual cortex, we observed that spontaneous activity reliably encoded a high-dimensional latent state, which was partially related to the mouse’s ongoing behavior and was represented not just in visual cortex but also across the forebrain. Sensory inputs did not interrupt this ongoing signal but added onto it a representation of external 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.

scholarly journals Spontaneous behaviors drive multidimensional, brain-wide activity

2018 ◽  
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.

scholarly journals Long-term stability of neuronal ensembles in mouse visual cortex

2020 ◽  
Author(s):  
Jesús Pérez-Ortega ◽  
Tzitzitlini Alejandre-García ◽  
Rafael Yuste
Keyword(s):  
Visual Cortex ◽  
Spontaneous Activity ◽  
Internal Representation ◽  
Mental States ◽  
Long Term Stability ◽  
Neuronal Ensembles ◽  
Neuronal Populations ◽  
Evoked Activity ◽  
Mouse Visual Cortex ◽  
Over Time

AbstractCoactive neuronal ensembles are found in spontaneous and evoked cortical activity and are thought to participate in the internal representation of memories, perceptions, and mental states. In mouse visual cortex, ensembles can be optogenetically imprinted and are causally related to visual percepts, but it is still unknown how stable they are over time. Using two-photon volumetric microscopy, we performed calcium imaging over several weeks of the same neuronal populations in layer 2/3 of visual cortex of awake mice, tracking over time the activity of the same neurons in response to visual stimuli and under spontaneous activity. Only a small number of neurons remained active across days. Analyzing them, we found both stable ensembles, lasting up to 46 days, and transient ones, observed during only one imaging session. The majority of ensembles in visually-evoked activity were stable, whereas in spontaneous activity similar numbers of stable and transient ensembles were found. Among stable ensembles, more than 60 % of neurons still belonged to the same ensemble even after several weeks. These core ensemble cells had stronger functional connectivity than neurons that stopped belonging to the ensemble. Our results demonstrate that spontaneous and evoked neuronal ensembles can last weeks, providing a neuronal mechanism for the long-lasting representation of perceptual states or memories.

scholarly journals Representational drift in the mouse visual cortex

2020 ◽  
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.

scholarly journals A Disinhibitory Circuit for Contextual Modulation in Primary Visual Cortex

2020 ◽  
Author(s):  
Andreas J. Keller ◽  
Mario Dipoppa ◽  
Morgane M. Roth ◽  
Matthew S. Caudill ◽  
Alessandro Ingrosso ◽  
...  
Keyword(s):  
Visual Cortex ◽  
Vasoactive Intestinal Peptide ◽  
Primary Visual Cortex ◽  
Computational Modelling ◽  
Visual Scene ◽  
Inhibitory Neurons ◽  
Contextual Modulation ◽  
Sensory Stimuli ◽  
Excitatory Neurons ◽  
Mouse Visual Cortex

Context guides perception by influencing the saliency of sensory stimuli. Accordingly, in visual cortex, responses to a stimulus are modulated by context, the visual scene surrounding the stimulus. Responses are suppressed when stimulus and surround are similar but not when they differ. The mechanisms that remove suppression when stimulus and surround differ remain unclear. Here we use optical recordings, manipulations, and computational modelling to show that a disinhibitory circuit consisting of vasoactive-intestinal-peptide-expressing (VIP) and somatostatin-expressing (SOM) inhibitory neurons modulates responses in mouse visual cortex depending on the similarity between stimulus and surround. When the stimulus and the surround are similar, VIP neurons are inactive and SOM neurons suppress excitatory neurons. However, when the stimulus and the surround differ, VIP neurons are active, thereby inhibiting SOM neurons and relieving excitatory neurons from suppression. We have identified a canonical cortical disinhibitory circuit which contributes to contextual modulation and may regulate perceptual saliency.

scholarly journals Canonical and noncanonical features of the mouse visual cortical hierarchy

2020 ◽  
Author(s):  
Rinaldo D. D’Souza ◽  
Quanxin Wang ◽  
Weiqing Ji ◽  
Andrew M. Meier ◽  
Henry Kennedy ◽  
...  
Keyword(s):  
Visual Cortex ◽  
Receptive Field ◽  
Active Vision ◽  
Structural Features ◽  
Hierarchical Organization ◽  
Hierarchical Level ◽  
Continuous Measure ◽  
Axonal Projections ◽  
Visual Cortical ◽  
Mouse Visual Cortex

ABSTRACTNeocortical circuit computations underlying active vision are performed by a distributed network of reciprocally connected, functionally specialized areas. Mouse visual cortex is a dense, hierarchically organized network, comprising subnetworks that form preferentially interconnected processing streams. To determine the detailed layout of the mouse visual hierarchy, laminar patterns formed by interareal axonal projections, originating in each of ten visual areas were analyzed. Reciprocally connected pairs of areas, and shared targets of pairs of source areas, exhibited structural features consistent with a hierarchical organization. Beta regression analyses, which estimated a continuous measure of hierarchical distance, indicated that the network comprises multiple hierarchies embedded within overlapping processing levels. Single unit recordings showed that within each processing stream, receptive field sizes typically increased with increasing hierarchical level; however, ventral stream areas showed overall larger receptive field diameters. Together, the results reveal canonical and noncanonical hierarchical network motifs in mouse visual cortex.

scholarly journals Feature representation under crowding in V1 and V4 neuronal populations

2021 ◽  
Author(s):  
Christopher A Henry ◽  
Adam Kohn
Keyword(s):  
Visual Processing ◽  
Cortical Neurons ◽  
Information Loss ◽  
Feature Representation ◽  
Spatial Integration ◽  
Neural Basis ◽  
Sensory Stimuli ◽  
Neuronal Populations ◽  
Visual Cortical ◽  
Object Features

Visual perception depends strongly on spatial context. A profound example is visual crowding, whereby the presence of nearby stimuli impairs discriminability of object features. Despite extensive work on both perceptual crowding and the spatial integrative properties of visual cortical neurons, the link between these two aspects of visual processing remains unclear. To understand better the neural basis of crowding, we recorded simultaneously from neuronal populations in V1 and V4 of fixating macaque monkeys. We assessed the information about the orientation of a visual target available from the measured responses, both for targets presented in isolation and amid distractors. Both single neuron and population responses had less information about target orientation when distractors were present. Information loss was moderate in V1 and more substantial in V4. Information loss could be traced to systematic divisive and additive changes in neuronal tuning. Tuning changes were more severe in V4; in addition, tuning exhibited greater context-dependent distortions in V4, further restricting the ability of a fixed sensory readout strategy to extract accurate feature information across changing environments. Our results provide a direct test of crowding effects at different stages of the visual hierarchy, reveal how these effects alter the spiking activity of cortical populations by which sensory stimuli are encoded, and connect these changes to established mechanisms of neuronal spatial integration.

scholarly journals Adaptation in the visual cortex: a case for probing neuronal populations with natural stimuli

F1000Research ◽  
2017 ◽  
Vol 6 ◽  
pp. 1246 ◽  
Author(s):  
Michoel Snow ◽  
Ruben Coen-Cagli ◽  
Odelia Schwartz
Keyword(s):  
Cortical Neurons ◽  
Natural Environments ◽  
Single Neurons ◽  
Neural Responses ◽  
Complete Understanding ◽  
Sensory Stimuli ◽  
Neuronal Populations ◽  
Natural Stimuli ◽  
The Past ◽  
Visual Cortical

The perception of, and neural responses to, sensory stimuli in the present are influenced by what has been observed in the past—a phenomenon known as adaptation. We focus on adaptation in visual cortical neurons as a paradigmatic example. We review recent work that represents two shifts in the way we study adaptation, namely (i) going beyond single neurons to study adaptation in populations of neurons and (ii) going beyond simple stimuli to study adaptation to natural stimuli. We suggest that efforts in these two directions, through a closer integration of experimental and modeling approaches, will enable a more complete understanding of cortical processing in natural environments.

Neuronal Activities in the Mouse Visual Cortex Predict Patterns of Sensory Stimuli

2018 ◽  
Vol 16 (3-4) ◽  
pp. 473-488 ◽  
Author(s):  
Lei Cai ◽  
Bian Wu ◽  
Shuiwang Ji
Keyword(s):  
Visual Cortex ◽  
Sensory Stimuli ◽  
Mouse Visual Cortex

scholarly journals Learning and attention reveal a general relationship between neuronal variability and perception

2017 ◽  
Author(s):  
Amy M. Ni ◽  
Douglas A. Ruff ◽  
Joshua J. Alberts ◽  
Jen Symmonds ◽  
Marlene R. Cohen
Keyword(s):  
Visual Cortex ◽  
Neuronal Population ◽  
Population Coding ◽  
Task Demands ◽  
Spike Count ◽  
Current Debate ◽  
Visually Guided ◽  
Population Activity ◽  
Neuronal Populations ◽  
And Performance

The trial-to-trial response variability that is shared between pairs of neurons (termed spike count correlations1 or rSC) has been the subject of many recent studies largely because it might limit the amount of information that can be encoded by neuronal populations. Spike count correlations are flexible and change depending on task demands2-7. However, the relationship between correlated variability and information coding is a matter of current debate2-14. This debate has been difficult to resolve because testing the theoretical predictions would require simultaneous recordings from an experimentally unfeasible number of neurons. We hypothesized that if correlated variability limits population coding, then spike count correlations in visual cortex should a) covary with subjects’ performance on visually guided tasks and b) lie along the dimensions in neuronal population space that contain information that is used to guide behavior. We focused on two processes that are known to improve visual performance: visual attention, which allows observers to focus on important parts of a visual scene15-17, and perceptual learning, which slowly improves observers’ ability to discriminate specific, well-practiced stimuli18-20. Both attention and learning improve performance on visually guided tasks, but the two processes operate on very different timescales and are typically studied using different perceptual tasks. Here, by manipulating attention and learning in the same task, subjects, trials, and neuronal populations, we show that there is a single, robust relationship between correlated variability in populations of visual neurons and performance on a change-detection task. We also propose an explanation for the mystery of how correlated variability might affect performance: it is oriented along the dimensions of population space used by the animal to make perceptual decisions. Our results suggest that attention and learning affect the same aspects of the neuronal population activity in visual cortex, which may be responsible for learning- and attention-related improvements in behavioral performance. More generally, our study provides a framework for leveraging the activity of simultaneously recorded populations of neurons, cognitive factors, and perceptual decisions to understand the neuronal underpinnings of behavior.

scholarly journals Low rank mechanisms underlying flexible visual representations

2020 ◽  
Vol 117 (47) ◽  
pp. 29321-29329 ◽  
Author(s):  
Douglas A. Ruff ◽  
Cheng Xue ◽  
Lily E. Kramer ◽  
Faisal Baqai ◽  
Marlene R. Cohen
Keyword(s):  
Visual Cortex ◽  
Cognitive Processes ◽  
Task Switching ◽  
Visual Processing ◽  
Neuronal Population ◽  
Low Rank ◽  
Visual Neurons ◽  
Sensory Stimuli ◽  
Neuronal Populations ◽  
Wide Range

Neuronal population responses to sensory stimuli are remarkably flexible. The responses of neurons in visual cortex have heterogeneous dependence on stimulus properties (e.g., contrast), processes that affect all stages of visual processing (e.g., adaptation), and cognitive processes (e.g., attention or task switching). Understanding whether these processes affect similar neuronal populations and whether they have similar effects on entire populations can provide insight into whether they utilize analogous mechanisms. In particular, it has recently been demonstrated that attention has low rank effects on the covariability of populations of visual neurons, which impacts perception and strongly constrains mechanistic models. We hypothesized that measuring changes in population covariability associated with other sensory and cognitive processes could clarify whether they utilize similar mechanisms or computations. Our experimental design included measurements in multiple visual areas using four distinct sensory and cognitive processes. We found that contrast, adaptation, attention, and task switching affect the variability of responses of populations of neurons in primate visual cortex in a similarly low rank way. These results suggest that a given circuit may use similar mechanisms to perform many forms of modulation and likely reflects a general principle that applies to a wide range of brain areas and sensory, cognitive, and motor processes.

Sign in / Sign up

Export Citation Format

Share Document