Spatial clustering of tuning in mouse primary visual cortex

Ringach, Dario L.; Mineault, Patrick J.; Tring, Elaine; Olivas, Nicholas D.; García-Junco-Clemente, Pablo; Trachtenberg, Joshua T.

doi:10.1038/ncomms12270

Cited by 115 publications

(134 citation statements)

References 48 publications

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“…Similar receptive field studies in other rodent cortical areas, such as the auditory and visual cortices, have also found local breakdowns in maps of sensory space (Bandyopadhyay et al, 2010; Rothschild et al, 2010; Smith and Hausser, 2010), despite some evidence of an underlying organization (Ringach et al, 2016). Nonetheless, these works analyzed maps of a fixed sensor array and not of scanned space.…”

Section: Introductionsupporting

confidence: 64%

Surround Integration Organizes a Spatial Map during Active Sensation

Pluta

Lyall

Telian

et al. 2017

Neuron

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During active sensation, sensors scan space in order to generate a representation of the outside world. However, since spatial coding in sensory systems is typically addressed by measuring receptive fields in a fixed, sensor-based coordinate frame, the cortical representation of scanned space is poorly understood. To address this question, we probed spatial coding in the rodent whisker system using a combination of two photon imaging and electrophysiology during active touch. We found that surround whiskers powerfully transform the cortical representation of scanned space. On the single neuron level, surround input profoundly alters response amplitude and modulates spatial preference in the cortex. On the population level, surround input organizes the spatial preference of neurons into a continuous map of the space swept out by the whiskers. These data demonstrate how spatial summation over a moving sensor array is critical to generating population codes of sensory space.

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Section: Introductionsupporting

confidence: 64%

Surround Integration Organizes a Spatial Map during Active Sensation

Pluta

Lyall

Telian

et al. 2017

Neuron

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“…GABAergic neurons in the visual cortex of carnivores exhibit selective responses for stimulus features such as orientation and direction of motion (Azouz et al, 1997; Cardin et al, 2007; Hirsch et al, 2003; Keller and Martin, 2015; Martin et al, 1983), suggesting a potentially different organizing principle for interneuron wiring. However, this interpretation is complicated by the spatial clustering of neurons with similar functional properties into columnar maps in the carnivore and primate (Blasdel and Salama, 1986; Grinvald et al, 1986; Kara and Boyd, 2009; Nauhaus et al, 2012; Ohki et al, 2006; Smith et al, 2015b), which is not present in the rodent (Ohki et al, 2005; but see Ringach et al, 2016). As a result, the selective responses of GABAergic neurons in species with columnar maps could arise from the same non-specific local pooling principle applied to an environment in which nearby pyramidal neurons have similar functional properties.…”

Section: Introductionmentioning

confidence: 99%

GABAergic Neurons in Ferret Visual Cortex Participate in Functionally Specific Networks

Wilson

Smith

Jacob

et al. 2017

Neuron

104

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Summary Functional circuits in the visual cortex require the coordinated activity of excitatory and inhibitory neurons. Molecular genetic approaches in the mouse have led to the ‘local nonspecific pooling principle’ of inhibitory connectivity, in which inhibitory neurons are untuned for stimulus features due to the random pooling of local inputs. However, it remains unclear whether this principle generalizes to species with a columnar organization of feature selectivity such as carnivores, primates, and humans. Here we use virally-mediated GABAergic-specific GCaMP6f expression to demonstrate that inhibitory neurons in ferret visual cortex respond robustly and selectively to oriented stimuli. We find that the tuning of inhibitory neurons is inconsistent with the local non-specific pooling of excitatory inputs, and that inhibitory neurons exhibit orientation-specific noise correlations with local and distant excitatory neurons. These findings challenge the generality of the non-specific pooling principle for inhibitory neurons, suggesting different rules for functional excitatory-inhibitory interactions in non-murine species.

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“…One known example is the absence of robust orientation columns in V1 of mouse (Schuett, Bonhoeffer, & H€ ubener, 2002), rat (Ohki, Chung, Ch'ng, Kara, & Reid, 2005), and squirrel (Van Hooser, Heimel, Chung, Nelson, & Toth, 2005), although a degraded version has recently been shown in mouse (Ringach et al, 2016). One known example is the absence of robust orientation columns in V1 of mouse (Schuett, Bonhoeffer, & H€ ubener, 2002), rat (Ohki, Chung, Ch'ng, Kara, & Reid, 2005), and squirrel (Van Hooser, Heimel, Chung, Nelson, & Toth, 2005), although a degraded version has recently been shown in mouse (Ringach et al, 2016).…”

mentioning

confidence: 99%

V1 connections reveal a series of elongated higher visual areas in the California ground squirrel, Otospermophilus beecheyi

Negwer

Liu

Schubert³

et al. 2017

J of Comparative Neurology

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For studies of visual cortex organization, mouse is becoming an increasingly more often used model. In addition to its genetic tractability, the relatively small area of cortical surface devoted to visual processing simplifies efforts in relating the structure of visual cortex to visual function. However, the nature of this compact organization can make some comparisons to the much larger non-human primate visual cortex difficult. The squirrel, as a highly visual rodent offers a useful means for better understanding how mouse and monkey cortical organization compares. More in line with primates than their nocturnal rodent cousin, squirrels rely much more on sight and have evolved a larger expanse of cortex devoted to visual processing. To reveal the detailed organization of visual cortex in squirrels, we injected a highly sensitive monosynaptic retrograde tracer (glycoprotein deleted rabies virus) into several locations of primary visual cortex (V1) in California ground squirrels. The resulting pattern of connectivity revealed an organizational scheme in the squirrel that retains some of the basic features of the mouse visual cortex along the medial and posterior borders of V1, but unlike mouse has an elaborate and extensive pattern laterally that is more similar to the early visual cortex organization found in monkeys. In this way, we show that the squirrel can serve as a useful model for comparison to both mouse and primate visual systems, and may help facilitate comparisons between these two very different yet widely used animal models of visual processing.

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Spatial clustering of tuning in mouse primary visual cortex

Cited by 115 publications

References 48 publications

Surround Integration Organizes a Spatial Map during Active Sensation

Surround Integration Organizes a Spatial Map during Active Sensation

GABAergic Neurons in Ferret Visual Cortex Participate in Functionally Specific Networks

V1 connections reveal a series of elongated higher visual areas in the California ground squirrel, Otospermophilus beecheyi

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