Figure-ground segregation is the process by which the visual system identifies image elements of figures and segregates them from the background. Previous studies examined figure-ground segregation in the visual cortex of monkeys where figures elicit stronger neuronal responses than backgrounds. It was demonstrated in anesthetized mice that neurons in the primary visual cortex (V1) of mice are sensitive to orientation contrast, but it is unknown whether mice can perceptually segregate figures from a background. Here, we examined figure-ground perception of mice and found that mice can detect figures defined by an orientation that differs from the background while the figure size, position or phase varied. Electrophysiological recordings in V1 of awake mice revealed that the responses elicited by figures were stronger than those elicited by the background and even stronger at the edge between figure and background. A figural response could even be evoked in the absence of a stimulus in the V1 receptive field. Current-source-density analysis suggested that the extra activity was caused by synaptic inputs into layer 2/3. We conclude that the neuronal mechanisms of figure-ground segregation in mice are similar to those in primates, enabling investigation with the powerful techniques for circuit analysis now available in mice.
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http://dx.doi.org/10.1038/s41598-018-36087-8 | DOI Listing |
Exp Neurobiol
December 2024
Department of Brain and Cognitive Engineering, Korea University, Seoul 02841, Korea.
Research on brain aging using resting-state functional magnetic resonance imaging (rs-fMRI) has typically focused on comparing "older" adults to younger adults. Importantly, these studies have often neglected the middle age group, which is also significantly impacted by brain aging, including by early changes in motor, memory, and cognitive functions. This study aims to address this limitation by examining the resting state networks in middle-aged adults via an exploratory whole-brain ROI-to-ROI analysis.
View Article and Find Full Text PDFProc Natl Acad Sci U S A
January 2025
Department of Psychology, University of Pennsylvania, Philadelphia, PA 19104.
Human brain evolution is marked by a disproportionate expansion of cortical regions associated with advanced perceptual and cognitive functions. While this expansion is often attributed to the emergence of novel specialized brain areas, modifications to evolutionarily conserved cortical regions also have been linked to species-specific behaviors. Distinguishing between these two evolutionary outcomes has been limited by the ability to make direct comparisons between species.
View Article and Find Full Text PDFGigascience
January 2025
School of Computer Science, Hunan University of Technology, Zhuzhou 412007, Hunan, China.
Background: The accurate deciphering of spatial domains, along with the identification of differentially expressed genes and the inference of cellular trajectory based on spatial transcriptomic (ST) data, holds significant potential for enhancing our understanding of tissue organization and biological functions. However, most of spatial clustering methods can neither decipher complex structures in ST data nor entirely employ features embedded in different layers.
Results: This article introduces STMSGAL, a novel framework for analyzing ST data by incorporating graph attention autoencoder and multiscale deep subspace clustering.
J Vis
January 2025
Neural Information Processing Group, University of Tübingen, Tübingen, Germany.
Human performance in psychophysical detection and discrimination tasks is limited by inner noise. It is unclear to what extent this inner noise arises from early noise (e.g.
View Article and Find Full Text PDFUnlabelled: Neurophysiology studies propose that predictive coding is implemented via alpha/beta (8-30 Hz) rhythms that prepare specific pathways to process predicted inputs. This leads to a state of relative inhibition, reducing feedforward gamma (40-90 Hz) rhythms and spiking to predictable inputs. We refer to this model as predictive routing.
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