This paper addresses perceptual synthesis by comparing responses evoked by visual stimuli before and after they are recognized, depending on prior exposure. Using magnetoencephalography, we analyzed distributed patterns of neuronal activity - evoked by Mooney figures - before and after they were recognized as meaningful objects. Recognition induced changes were first seen at 100-120 ms, for both faces and tools. These early effects - in right inferior and middle occipital regions - were characterized by an increase in power in the absence of any changes in spatial patterns of activity. Within a later 210-230 ms window, a quite different type of recognition effect appeared. Regions of the brain's value system (insula, entorhinal cortex and cingulate of the right hemisphere for faces and right orbitofrontal cortex for tools) evinced a reorganization of their neuronal activity without an overall power increase in the region. Finally, we found that during the perception of disambiguated face stimuli, a face-specific response in the right fusiform gyrus emerged at 240-290 ms, with a much greater latency than the well-known N170m component, and, crucially, followed the recognition effect in the value system regions. These results can clarify one of the most intriguing issues of perceptual synthesis, namely, how a limited set of high-level predictions, which is required to reduce the uncertainty when resolving the ill-posed inverse problem of perception, can be available before category-specific processing in visual cortex. We suggest that a subset of local spatial features serves as partial cues for a fast re-activation of object-specific appraisal by the value system. The ensuing top-down feedback from value system to visual cortex, in particular, the fusiform gyrus enables high levels of processing to form category-specific predictions. This descending influence of the value system was more prominent for faces than for tools, the fact that reflects different dependence of these categories on value-related information.
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http://dx.doi.org/10.1016/j.neuroimage.2020.117143 | DOI Listing |
J Nurs Scholarsh
January 2025
Nell Hodgson Woodruff School of Nursing, Emory University, Atlanta, Georgia, USA.
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January 2025
Faculty of Psychology, Tianjin Normal University, Tianjin, 300387, China.
Hypomanic personality traits (HPT) are susceptibility markers for psychiatric disorders, particularly bipolar disorder, and are strongly associated with aggressive behaviors. However, the neuropsychological mechanisms underlying this association remain unclear. This study utilized psychometric network analysis and (IS-RSA) to explore the neuropsychological circuits that link HPT to aggression in a large non-clinical population.
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February 2025
Department of Health Sciences, Interdisciplinary Research Center of Autoimmune Diseases-IRCAD, University of Eastern Piedmont, 28100, Novara, Italy.
Major Depressive Disorder (MDD) is a widespread psychiatric condition impacting social and occupational functioning, making it a leading cause of disability. The diagnosis of MDD remains clinical, based on the Diagnostic and Statistical Manual of Mental Disorders (DSM)-5 criteria, as biomarkers have not yet been validated for diagnostic purposes or as predictors of treatment response. Traditional treatment strategies often follow a one-size-fits-all approach obtaining suboptimal outcomes for many patients who fail to experience response or recovery.
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Imaging AI Group, Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Belvaux, Luxembourg.
Background: Publicly available data are essential for the progress of medical image analysis, in particular for crafting machine learning models. Glioma is the most common group of primary brain tumors, and magnetic resonance imaging (MRI) is a widely used modality in their diagnosis and treatment. However, the availability and quality of public datasets for glioma MRI are not well known.
View Article and Find Full Text PDFFront Digit Health
January 2025
Department of Information Engineering, University of Pisa, Pisa, Italy.
Wearable augmented reality in neurosurgery offers significant advantages by enabling the visualization of navigation information directly on the patient, seamlessly integrating virtual data with the real surgical field. This ergonomic approach can facilitate a more intuitive understanding of spatial relationships and guidance cues, potentially reducing cognitive load and enhancing the accuracy of surgical gestures by aligning critical information with the actual anatomy in real-time. This study evaluates the benefits of a novel AR platform, VOSTARS, by comparing its targeting accuracy to that of the gold-standard electromagnetic (EM) navigation system, Medtronic StealthStation S7.
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