On and off domains of geniculate afferents in cat primary visual cortex

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Astronomers and physicists noticed centuries ago that visual spatial resolution is higher for dark than light stimuli, but the neuronal mechanisms for this perceptual asymmetry remain unknown. Here we demonstrate that the asymmetry is caused by a neuronal nonlinearity in the early visual pathway. We show that neurons driven by darks (OFF neurons) increase their responses roughly linearly with luminance decrements, independent of the background luminance. However, neurons driven by lights (ON neurons) saturate their responses with small increases in luminance and need bright backgrounds to approach the linearity of OFF neurons. We show that, as a consequence of this difference in linearity, receptive fields are larger in ON than OFF thalamic neurons, and cortical neurons are more strongly driven by darks than lights at low spatial frequencies. This ON/OFF asymmetry in linearity could be demonstrated in the visual cortex of cats, monkeys, and humans and in the cat visual thalamus. Furthermore, in the cat visual thalamus, we show that the neuronal nonlinearity is present at the ON receptive field center of ONcenter neurons and ON receptive field surround of OFF-center neurons, suggesting an origin at the level of the photoreceptor. These results demonstrate a fundamental difference in visual processing between ON and OFF channels and reveal a competitive advantage for OFF neurons over ON neurons at low spatial frequencies, which could be important during cortical development when retinal images are blurred by immature optics in infant eyes.neuronal coding | lateral geniculate nucleus | area V1 | irradiation illusion | LFP L ight and dark stimuli are separately processed by ON and OFF channels in the retina and visual thalamus. Surprisingly, although most textbooks assume that ON and OFF visual responses are balanced throughout the visual system, recent studies have identified a pronounced overrepresentation of the OFF visual responses in primary visual cortex (area V1) (1-3). This recent discovery resonates with pioneering studies by Galilei (4) and von Helmholtz (5) who noticed that visual spatial resolution was higher for dark than light stimuli. Galilei (4) related the difference in resolution to the observation that a light patch on a dark background appears larger than the same sized dark patch on a light background, an illusion that von Helmholtz (5) named the "irradiation illusion." Although this illusion has been studied in the past (6, 7), its underlying neuronal mechanisms remain unknown. It has been suggested that the perceived size differences could be caused by the light scatter in the optics of the eye followed by a neuronal nonlinearity (6, 7), but there are no neuronal measurements of a nonlinearity that fits the explanation. Previous studies revealed differences in response linearity between ON and OFF retinal ganglion cells (8, 9) and horizontal cells (10). However, a main conclusion from these studies was that ON retinal ganglion cells were roughly linear and less rectified than OFF retinal gangl...

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confidence: 69%

“…Details of the surgical procedures have been described previously (3,37). All procedures were performed in accordance to the guidelines of the US Department of Agriculture and approved by the Institutional Animal Care and Use Committee at the State University of New York, State College of Optometry.…”

Section: Methodsmentioning

confidence: 99%

Neuronal nonlinearity explains greater visual spatial resolution for darks than lights

Kremkow

Jin

Komban

et al. 2014

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229

“…Several groups have studied V1 laminar variation (5,8,9,25,(47)(48)(49) by using spike-field coherence analysis (25), current source density analysis (5,49,50), or the BOLD signal in functional MRI (47). In this study, we used drifting gratings with spatial frequency equal to two cycles per degree, which are optimal stimuli for stimulating neurons in the V1 network (20,51).…”

Section: Dynamics Of γ-Band Power At Different Cortical Depths In V1mentioning

confidence: 99%

Laminar analysis of visually evoked activity in the primary visual cortex

Xing

Yeh

Burns

et al. 2012

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Studying the laminar pattern of neural activity is crucial for understanding the processing of neural signals in the cerebral cortex. We measured neural population activity [multiunit spike activity (MUA) and local field potential, LFP] in Macaque primary visual cortex (V1) in response to drifting grating stimuli. Sustained visually driven MUA was at an approximately constant level across cortical depth in V1. However, sustained, visually driven, local field potential power, which was concentrated in the γ-band (20-60 Hz), was greatest at the cortical depth corresponding to corticocortical output layers 2, 3, and 4B. γ-band power also tends to be more sustained in the output layers. Overall, cortico-cortical output layers accounted for 67% of total γ-band activity in V1, whereas 56% of total spikes evoked by drifting gratings were from layers 2, 3, and 4B. The high-resolution layer specificity of γ-band power, the laminar distribution of MUA and γ-band activity, and their dynamics imply that neural activity in V1 is generated by laminar-specific mechanisms. In particular, visual responses of MUA and γ-band activity in cortico-cortical output layers 2, 3, and 4B seem to be strongly influenced by laminar-specific recurrent circuitry and/or feedback.B ased on anatomy and neurophysiology, our view of the cerebral cortex has changed. Instead of viewing the cortex as a single network, we now conceive of the cortical laminae as a stack of loosely interconnected but distinct neuronal networks (1-5). Each lamina has different specific inputs, projection targets, and feedback connections.The goal of this study is the determination of the spatial distribution of stimulus-driven neural activity throughout the depth of the cortex and across cortical laminae. Pursuing this goal, we chose to study Macaque primary visual cortex (V1), because V1 is a cortical area where the experimenter has control of the neuronal input by controlling visual stimulation. V1 laminar inputs, outputs, and local connections are well-known (1, 3, 6). Signals come from the thalamus [lateral geniculate nucleus (LGN)] into V1 layers 4C and 6. After intracortical processing, neuronal signals are routed to other cortical areas from cells in superficial layers 2, 3, and 4B of V1; subcortical targets receive cortical outputs from cells in layers 5 and 6. Extrastriate cortical feedback targets layers 2, 3, and 6 (1, 3, 7). The visual functional properties of cells in different layers are markedly different (2, 8-13), reflecting local circuitry that is layer-specific (1, 3, 6). Because of the similarities of laminar cortical circuitry throughout the cerebral cortex (14-16), we used V1 as a test bed to study laminar patterns of stimulus-driven responses.To sample from many neurons in each layer, we measured multiunit spike activity (MUA) and the local field potential (LFP) with multiple microelectrodes (Methods details the operational definitions of MUA and LFP). We measured the power in the LFP at frequencies < 100 Hz, because the largest changes in LFP power...

“…Psychophysical studies and measurements of visually evoked potentials show greater sensitivity to light decrements and dark spots in images (1,2). Also, more cortical cells respond to negative than positive contrasts (3). In fact, this asymmetry begins with the second order (bipolar) neurons in the retina, which rectify the local contrast signal from the cone array (Fig.…”

mentioning

confidence: 97%

Retina is structured to process an excess of darkness in natural scenes

Ratliff

Borghuis

Kao

et al. 2010

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Retinal ganglion cells that respond selectively to a dark spot on a brighter background (OFF cells) have smaller dendritic fields than their ON counterparts and are more numerous. OFF cells also branch more densely, and thus collect more synapses per visual angle. That the retina devotes more resources to processing dark contrasts predicts that natural images contain more dark information. We confirm this across a range of spatial scales and trace the origin of this phenomenon to the statistical structure of natural scenes. We show that the optimal mosaics for encoding natural images are also asymmetric, with OFF elements smaller and more numerous, matching retinal structure. Finally, the concentration of synapses within a dendritic field matches the information content, suggesting a simple principle to connect a concrete fact of neuroanatomy with the abstract concept of information: equal synapses for equal bits.ganglion cells | neural coding | vision T he brain separates light from dark unequally. Psychophysical studies and measurements of visually evoked potentials show greater sensitivity to light decrements and dark spots in images (1, 2). Also, more cortical cells respond to negative than positive contrasts (3). In fact, this asymmetry begins with the second order (bipolar) neurons in the retina, which rectify the local contrast signal from the cone array (Fig. 1A). OFF cone bipolar cells (responding mostly to negative contrasts) outnumber the ON cells (responding mostly to positive contrasts) by 2-fold (4); thus, right from the start, the brain provides more resources for signaling negative contrasts.This aspect of retinal structure continues through the ganglion-cell level, where some ganglion-cell types have paired ON and OFF polarities (e.g., P and M in monkey, brisk-transient and brisk-sustained in rabbit and guinea pig, and X and Y in cat). Of these, the OFF cells have narrower dendritic fields and correspondingly narrower receptive-field centers than their ON partners [guinea pig (Fig. 1B), rat (5), rabbit (6), monkey (7), human (8), and smaller differences in cat (9)]. Thus, to cover the retina, OFF cells outnumber their ON partners. OFF arbors are narrower across cell classes with different spatiotemporal bandwidths (e.g., they are narrower for both midget and parasol cells in humans) (8). Specifically, whereas in fovea, midget cells are paired (one ON and one OFF per cone), beyond fovea, where midget cells collect from many bipolar cells and cones, OFF cells have smaller arbors and hence, are more numerous.While OFF cells distribute more densely than their counterpart ON cells, both types have similar receptive-field overlap (spacing is about two times the SD of a Gaussian fit to the central receptive field) (6, 10, 11). Furthermore, OFF arbors (as we quantify here) branch more densely (5) and provide similar dendritic membrane areas as ON arbors. Because the membrane density of excitatory synapses (synapses/μm 2 ) is constant across an arbor and across cell types (12, 13), OFF cells receive simi...