Object recognition in primates is mediated by the ventral visual pathway and is classically described as a feedforward hierarchy of increasingly sophisticated representations. Neurons in macaque monkey area V4, an intermediate stage along the ventral pathway, have been shown to exhibit selectivity to complex boundary conformation and invariance to spatial translation. How could such a representation be derived from the signals in lower visual areas such as V1? We show that a quantitative model of hierarchical processing, which is part of a larger model of object recognition in the ventral pathway, provides a plausible mechanism for the translation-invariant shape representation observed in area V4. Simulated model neurons successfully reproduce V4 selectivity and invariance through a nonlinear, translation-invariant combination of locally selective subunits, suggesting that a similar transformation may occur or culminate in area V4. Specifically, this mechanism models the selectivity of individual V4 neurons to boundary conformation stimuli, exhibits the same degree of translation invariance observed in V4, and produces observed V4 population responses to bars and non-Cartesian gratings. This work provides a quantitative model of the widely described shape selectivity and invariance properties of area V4 and points toward a possible canonical mechanism operating throughout the ventral pathway.
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http://dx.doi.org/10.1152/jn.01265.2006 | DOI Listing |
Sci Rep
January 2025
Advanced Power and Energy Center (APEC), Electrical Engineering Department, Khalifa University, Abu Dhabi, UAE.
Although detailed analytical models for droop-controlled microgrids are available, they are computationally complex and do not consider real-time variations in microgrid parameters and operating conditions. This paper proposes Kurtosis-Estimation of Signal Parameters via Rotational Invariance Technique (ESPRIT) to identify the dominant modes in droop-controlled inverter-based microgrids (IBMGs) using local real-time measurements. In the proposed approach, a short-duration small disturbance is applied to the selected DG's active power droop gain, and then, the system's dominant modes are estimated from its local measurements.
View Article and Find Full Text PDFUnlabelled: Sensory stimuli vary across a variety of dimensions, like contrast, orientation, or texture. The brain must rely on population representations to disentangle changes in one dimension from changes in another. To understand how the visual system might extract separable stimulus representations, we recorded multiunit neuronal responses to texture images varying along two dimensions: contrast, a property represented as early as the retina, and naturalistic statistical structure, a property that modulates neuronal responses in V2 and V4, but not in V1.
View Article and Find Full Text PDFActas Esp Psiquiatr
January 2025
Psychology Department, College of Education, Umm Al-Qura University, 24381 Mecca, Saudi Arabia.
Background: Measuring adolescents' and youths' perception of their Cyber-Self can enhance the understanding of how digital technology influences identity formation. While psychological literature offers numerous measures of the self, there is a notable lack of studies addressing the measurement of the Cyber-Self. This study aims to evaluate the reliability, factorial- and criterion-related validity, and measurement invariance of the Cyber-Self Scale (CSS) across age and gender among the youth and adolescents in Saudi Arabia.
View Article and Find Full Text PDFCell Biol Toxicol
January 2025
Department of Medical Oncology, the First Hospital of China Medical University, Shenyang, Liaoning, China.
Background: Microsatellite instability-high (MSI-H) metastatic colorectal cancer (CRC) patients are the dominant population in immune checkpoint blockade treatments, while more than half of them could not benefit from single-agent immunotherapy. We tried to identify the biomarker of MSI-H CRC and explore its role and mechanism in anti-PD-1 treatments. Tumor-specific MHC-II was linked to a better response to anti-PD-1 in MSI-H CRC and CD74 promoted assembly and transport of HLA-DR dimers.
View Article and Find Full Text PDFBiol Imaging
November 2024
IBENS, Ecole Normale Supérieure PSL, Paris, 75005, France.
Self-supervised representation learning (SSRL) in computer vision relies heavily on simple image transformations such as random rotation, crops, or illumination to learn meaningful and invariant features. Despite acknowledged importance, there is a lack of comprehensive exploration of the impact of transformation choice in the literature. Our study delves into this relationship, specifically focusing on microscopy imaging with subtle cell phenotype differences.
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