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.

Responses of Primate Visual Cortical V4 Neurons to Simultaneously Presented Stimuli

2002 ◽  
Vol 88 (3) ◽  
pp. 1128-1135 ◽  
Author(s):  
Timothy J. Gawne ◽  
Julie M. Martin
Keyword(s):  
Visual Cortex ◽  
Receptive Field ◽  
Firing Rate ◽  
Cortical Neurons ◽  
Clear Relationship ◽  
Substantial Fraction ◽  
Receptive Field Properties ◽  
Direct Support ◽  
V4 Neurons ◽  
Visual Cortical

We report here results from 45 primate V4 visual cortical neurons to the preattentive presentations of seven different patterns located in two separate areas of the same receptive field and to combinations of the patterns in the two locations. For many neurons, we could not determine any clear relationship for the responses to two simultaneous stimuli. However, for a substantial fraction of the neurons we found that the firing rate was well modeled as the maximum firing rate of each stimulus presented separately. It has previously been proposed that taking the maximum of the inputs (“MAX” operator) could be a useful operation for neurons in visual cortex, although there has until now been little direct physiological evidence for this hypothesis. Our results here provide direct support for the hypothesis that the MAX operator plays a significant (although certainly not exclusive) role in generating the receptive field properties of visual cortical neurons.

scholarly journals Searching for object pointers in the visual cortex

2020 ◽  
Vol 123 (5) ◽  
pp. 1979-1994
Author(s):  
Shude D. Zhu ◽  
Li Alex Zhang ◽  
Rüdiger von der Heydt
Keyword(s):  
Visual Cortex ◽  
Receptive Field ◽  
Cortical Neurons ◽  
Visual Objects ◽  
Visual Cortical ◽  
The Way

The way we perceive objects as permanent contrasts with the short-lived responses of visual cortical neurons. A theory postulates pointers that give objects continuity, predicting a class of neurons that respond not only to visual objects but also when an occluded object moves into their receptive field. Here, we tested this theory with a novel paradigm in which a monkey freely scans an array of objects while some of them are transiently occluded.

scholarly journals Functional connectomics spanning multiple areas of mouse visual cortex

2021 ◽  
Author(s):  
◽  
Agnes L. Bodor ◽  
Akhilesh Halageri ◽  
Amy Sterling ◽  
Andreas S. Tolias ◽  
...  
Keyword(s):  
Visual Cortex ◽  
Functional Characterization ◽  
Data Access ◽  
Integrated Approach ◽  
Neuron Activity ◽  
Axonal Projections ◽  
Mouse Visual Cortex ◽  
Higher Visual Areas ◽  
Open Access Resource

The value of an integrated approach for understanding the neocortex by combining functional characterization of single neuron activity with the underlying circuit architecture has been understood since the dawn of modern neuroscience. However, in practice, anatomical connectivity and physiology have been studied mostly separately. Following in the footsteps of previous studies that have combined physiology and anatomy in the same tissue, here we present a unique functional connectomics dataset that contains calcium imaging of an estimated 75,000 neurons from primary visual cortex (VISp) and three higher visual areas (VISrl, VISal and VISlm), that were recorded while a mouse viewed natural movies and parametric stimuli. The functional data were co-registered with electron microscopy (EM) data of the same volume which were automatically segmented, reconstructing more than 200,000 cells (neuronal and non-neuronal) and 524 million synapses. Subsequent proofreading of some neurons in this volume yielded reconstructions that include complete dendritic trees as well the local and inter-areal axonal projections. The largest proofread excitatory axon reached a length of 19 mm and formed 1,893 synapses, while the largest inhibitory axon formed 10,081 synapses. Here we release this dataset as an open access resource to the scientific community including a set of analysis tools that allows easy data access, both programmatically and through a web user interface.

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 A Convolutional Network Architecture Driven by Mouse Neuroanatomical Data

2020 ◽  
Author(s):  
Jianghong Shi ◽  
Michael A. Buice ◽  
Eric Shea-Brown ◽  
Stefan Mihalas ◽  
Bryan Tripp
Keyword(s):  
Visual Cortex ◽  
Visual System ◽  
Network Architecture ◽  
Structural Parameters ◽  
Cortical Layer ◽  
Hierarchical Organization ◽  
Visually Guided ◽  
Convolutional Network ◽  
Mouse Visual Cortex ◽  
Neuroanatomical Data

Convolutional neural networks trained on object recognition derive some inspiration from the neuroscience of the visual system in primates, and have been used as models of the feedforward computation performed in the primate ventral stream. In contrast to the hierarchical organization of primates, the visual system of the mouse has flatter hierarchy. Since mice are capable of visually guided behavior, this raises questions about the role of architecture in neural computation. In this work, we introduce a framework for building a biologically constrained convolutional neural network model of lateral areas of the mouse visual cortex. The structural parameters of the network are derived from experimental measurements, specifically estimates of numbers of neurons in each area and cortical layer, the interareal connec-tome, and the statistics of connections between cortical layers. This network is constructed to support detailed task-optimized models of mouse visual cortex, with neural populations that can be compared to specific corresponding populations in the mouse brain. The code is freely available to support such research.

scholarly journals A large-scale, standardized physiological survey reveals higher order coding throughout the mouse visual cortex

2018 ◽  
Author(s):  
Saskia E. J. de Vries ◽  
Jerome Lecoq ◽  
Michael A. Buice ◽  
Peter A. Groblewski ◽  
Gabriel K. Ocker ◽  
...  
Keyword(s):  
Visual Cortex ◽  
Large Scale ◽  
Sensory Information ◽  
Natural Scenes ◽  
Visual Coding ◽  
Adult Mice ◽  
Cortical Responses ◽  
Visual Cortical ◽  
Mouse Visual Cortex ◽  
Hierarchical Computation

SummaryTo understand how the brain processes sensory information to guide behavior, we must know how stimulus representations are transformed throughout the visual cortex. Here we report an open, large-scale physiological survey of neural activity in the awake mouse visual cortex: the Allen Brain Observatory Visual Coding dataset. This publicly available dataset includes cortical activity from nearly 60,000 neurons collected from 6 visual areas, 4 layers, and 12 transgenic mouse lines from 221 adult mice, in response to a systematic set of visual stimuli. Using this dataset, we reveal functional differences across these dimensions and show that visual cortical responses are sparse but correlated. Surprisingly, responses to different stimuli are largely independent, e.g. whether a neuron responds to natural scenes provides no information about whether it responds to natural movies or to gratings. We show that these phenomena cannot be explained by standard local filter-based models, but are consistent with multi-layer hierarchical computation, as found in deeper layers of standard convolutional neural networks.

scholarly journals A global map of orientation tuning in mouse visual cortex

2019 ◽  
Author(s):  
Paul G. Fahey ◽  
Taliah Muhammad ◽  
Cameron Smith ◽  
Emmanouil Froudarakis ◽  
Erick Cobos ◽  
...  
Keyword(s):  
Visual Cortex ◽  
Visual Processing ◽  
Large Fraction ◽  
Orientation Tuning ◽  
Wide Field ◽  
Two Photon ◽  
Visual Hierarchy ◽  
Visual Cortical ◽  
Mouse Visual Cortex ◽  
Salt And Pepper

In primates and most carnivores, neurons in primary visual cortex are spatially organized by their functional properties. For example, neurons with similar orientation preferences are grouped together in iso-orientation domains that smoothly vary over the cortical sheet. In rodents, on the other hand, neurons with different orientation preferences are thought to be spatially intermingled, a feature which has been termed “salt-and-pepper” organization. The apparent absence of any systematic structure in orientation tuning has been considered a defining feature of the rodent visual system for more than a decade, with broad implications for brain development, visual processing, and comparative neurophysiology. Here, we revisited this question using new techniques for wide-field two-photon calcium imaging that enabled us to collect nearly complete population tuning preferences in layers 2-4 across a large fraction of the mouse visual hierarchy. Examining the orientation tuning of these hundreds of thousands of neurons, we found a global map spanning multiple visual cortical areas in which orientation bias was organized around a single pinwheel centered in V1. This pattern was consistent across animals and cortical depth. The existence of this global organization in rodents has implications for our understanding of visual processing and the principles governing the ontogeny and phylogeny of the visual cortex of mammals.

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