Effects of top-down influence suppression on behavioral and V1 neuronal contrast sensitivity functions in cats.
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ABSTRACT:
SUBMITTER: Ding J
PROVIDER: S-EPMC8760559 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:How top-down influence affects neuronal activity and information encoding in the primary visual cortex (V1) remains elusive. This study examined changes of neuronal excitability and contrast sensitivity in cat V1 cortex after top-down influence of area 7 (A7) was modulated by transcranial direct current stimulation (tDCS). The neuronal excitability in V1 cortex was evaluated by visually evoked field potentials (VEPs), and contrast sensitivity (CS) was assessed by the inverse of threshold contrast of neurons in response to visual stimuli at different performance accuracy. We found that the amplitude of VEPs in V1 cortex lowered after top-down influence suppression with cathode-tDCS in A7, whereas VEPs in V1 did not change after sham-tDCS in A7 and nonvisual cortical area 5 (A5) or cathode-tDCS in A5 and lesioned A7. Moreover, the mean CS of V1 neurons decreased after cathode-tDCS but not sham-tDCS in A7, which could recover after tDCS effect vanished. Comparisons of neuronal contrast-response functions showed that cathode-tDCS increased the stimulus contrast required to generate the half-maximum response, with a weakly-correlated reduction in maximum response but not baseline response. Therefore, top-down influence of A7 enhanced neuronal excitability in V1 cortex and improved neuronal contrast sensitivity by both contrast gain and response gain.
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Project description:Perceptual learning has been documented in adult humans over a wide range of tasks. Although the often-observed specificity of learning is generally interpreted as evidence for training-induced plasticity in early cortical areas, physiological evidence for training-induced changes in early visual cortical areas is modest, despite reports of learning-induced changes of cortical activities in fMRI studies. To reveal the physiological bases of perceptual learning, we combined psychophysical measurements with extracellular single-unit recording under anesthetized preparations and examined the effects of training in grating orientation identification on both perceptual and neuronal contrast sensitivity functions of cats.We have found that training significantly improved perceptual contrast sensitivity of the cats to gratings with spatial frequencies near the "trained" spatial frequency, with stronger effects in the trained eye. Consistent with behavioral assessments, the mean contrast sensitivity of neurons recorded from V1 of the trained cats was significantly higher than that of neurons recorded from the untrained cats. Furthermore, in the trained cats, the contrast sensitivity of V1 neurons responding preferentially to stimuli presented via the trained eyes was significantly greater than that of neurons responding preferentially to stimuli presented via the "untrained" eyes. The effect was confined to the trained spatial frequencies. In both trained and untrained cats, the neuronal contrast sensitivity functions derived from the contrast sensitivity of the individual neurons were highly correlated with behaviorally determined perceptual contrast sensitivity functions.We suggest that training-induced neuronal contrast gain in area V1 underlies behaviorally determined perceptual contrast sensitivity improvements.
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Project description:Lateral inhibition is a central principle for sensory system function. It is thought to operate by the activation of inhibitory neurons that restrict the spatial spread of sensory excitation. Much work on the role of inhibition in sensory systems has focused on visual cortex; however, the neurons, computations, and mechanisms underlying cortical lateral inhibition remain debated, and its importance for visual perception remains unknown. Here, we tested how lateral inhibition from PV or SST neurons in mouse primary visual cortex (V1) modulates neural and perceptual sensitivity to stimulus contrast. Lateral inhibition from PV neurons reduced neural and perceptual sensitivity to visual contrast in a uniform subtractive manner, whereas lateral inhibition from SST neurons more effectively changed the slope (or gain) of neural and perceptual contrast sensitivity. A neural circuit model identified spatially extensive lateral projections from SST neurons as the key factor, and we confirmed this with direct subthreshold measurements of a larger spatial footprint for SST versus PV lateral inhibition. Together, these results define cell-type specific computational roles for lateral inhibition in V1, and establish their unique consequences on sensitivity to contrast, a fundamental aspect of the visual world.
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Project description:Contrast sensitivity (CS) is widely used as a measure of visual function in both basic research and clinical evaluation. There is conflicting evidence on the extent to which measuring the full contrast sensitivity function (CSF) offers more functionally relevant information than a single measurement from an optotype CS test, such as the Pelli-Robson chart. Here we examine the relationship between functional CSF parameters and other measures of visual function, and establish a framework for predicting individual CSFs with effectively a zero-parameter model that shifts a standard-shaped template CSF horizontally and vertically according to independent measurements of high contrast acuity and letter CS, respectively. This method was evaluated for three different CSF tests: a chart test (CSV-1000), a computerized sine-wave test (M&S Sine Test), and a recently developed adaptive test (quick CSF). Subjects were 43 individuals with healthy vision or impairment too mild to be considered low vision (acuity range of -0.3 to 0.34 logMAR). While each test demands a slightly different normative template, results show that individual subject CSFs can be predicted with roughly the same precision as test-retest repeatability, confirming that individuals predominantly differ in terms of peak CS and peak spatial frequency. In fact, these parameters were sufficiently related to empirical measurements of acuity and letter CS to permit accurate estimation of the entire CSF of any individual with a deterministic model (zero free parameters). These results demonstrate that in many cases, measuring the full CSF may provide little additional information beyond letter acuity and contrast sensitivity.
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Project description:Human contrast sensitivity in low scotopic conditions is regulated according to the deVries-Rose law. Previous cat behavioral data, as well as cat and mice electrophysiological data, have not confirmed this relationship. To resolve this discrepancy at the behavioral level, we compared sensitivity in dim light for cats and humans in parallel experiments using the same visual stimuli and similar behavioral paradigms. Both species had to detect Gabor functions (SD = 1.5 degrees, spatial frequencies from 0 to 4 cpd, temporal frequency 4 Hz) presented 8 degrees to the right or left of a central fixation point over an 8 log-unit range of adaptation levels spanning scotopic vision and extending well into the mesopic range. Cats had 0.74 log unit greater absolute sensitivity than that of humans for spatial frequencies <or=1/8 cpd. Cats had better contrast sensitivity overall for spatial frequencies <1/2 cpd, whereas humans were more sensitive for spatial frequencies above this. However, most of the cat's sensitivity advantage for low spatial frequencies could be accounted for by the greater light-concentrating abilities of its optics. Contrast sensitivity to 4 cpd was poor or absent in the scotopic range for both species. For both, scotopic increment thresholds were proportional to the square root of retinal illuminance, in accordance with the deVries-Rose law. Overall, cat and human visual systems appear to operate under very similar constraints for rod vision, including the regulation of contrast sensitivity across adaptation levels. A companion paper compares sensitivity of neurons in the lateral geniculate nucleus to these behavioral data.
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