A new study has shown that monkeys detect transient external pulses delivered to the highest echelons of visual cortex in a way that depends on concomitant visual inputs. This new work, a technical tour de force, has implications for the development of future visual prosthetic devices.
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| http://dx.doi.org/10.1016/j.cub.2022.12.047 | DOI Listing |
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The canonical deep neural network as a model for human symmetry processing.
iScience
January 2025
Division of Optometry, Health Sciences, City University of London, London EC1V 0HB, UK.
A key property of our environment is the mirror symmetry of many objects, although symmetry is an abstract global property with no definable shape template, making symmetry identification a challenge for standard template-matching algorithms. We therefore ask whether Deep Neural Networks (DNNs) trained on typical natural environmental images develop a selectivity for symmetry similar to that of the human brain. We tested a DNN trained on such typical natural images with object-free random-dot images of 1, 2, and 4 symmetry axes.
View Article and Find Full Text PDFCoordinated representations for naturalistic memory encoding and retrieval in hippocampal neural subspaces.
Nat Commun
January 2025
Department of Intelligent Precision Healthcare Convergence, Sungkyunkwan University, Suwon, Republic of Korea.
Our naturalistic experiences are organized into memories through multiple processes, including novelty encoding, memory formation, and retrieval. However, the neural mechanisms coordinating these processes remain elusive. Using fMRI data acquired during movie viewing and subsequent narrative recall, we examine hippocampal neural subspaces associated with distinct memory processes and characterized their relationships.
View Article and Find Full Text PDFNeural Dynamics of the Processing of Speech Features: Evidence for a Progression of Features from Acoustic to Sentential Processing.
J Neurosci
January 2025
Department of Electrical and Computer Engineering, University of Maryland, College Park, MD, 20742
When we listen to speech, our brain's neurophysiological responses "track" its acoustic features, but it is less well understood how these auditory responses are enhanced by linguistic content. Here, we recorded magnetoencephalography (MEG) responses while subjects of both sexes listened to four types of continuous-speech-like passages: speech-envelope modulated noise, English-like non-words, scrambled words, and a narrative passage. Temporal response function (TRF) analysis provides strong neural evidence for the emergent features of speech processing in cortex, from acoustics to higher-level linguistics, as incremental steps in neural speech processing.
View Article and Find Full Text PDFDual-path neural network extracts tumor microenvironment information from whole slide images to predict molecular typing and prognosis of Glioma.
Comput Methods Programs Biomed
January 2025
School of Information Science and Technology, Fudan University, Shanghai, 200433, China; Key Laboratory of Medical Imaging, Computing and Computer Assisted Intervention, Shanghai, 200433, China. Electronic address:
Background And Objective: Utilizing AI to mine tumor microenvironment information in whole slide images (WSIs) for glioma molecular subtype and prognosis prediction is significant for treatment. Existing weakly-supervised learning frameworks based on multi-instance learning have potential in WSIs analysis, but the large number of patches from WSIs challenges the effective extraction of key local patch and neighboring patch microenvironment info. Therefore, this paper aims to develop an automatic neural network that effectively extracts tumor microenvironment information from WSIs to predict molecular typing and prognosis of glioma.
View Article and Find Full Text PDFSuboptimal but intact integration of Bayesian components during perceptual decision-making in autism.
Mol Autism
January 2025
Department of Special Education, University of Haifa, Haifa, Israel.
Background: Alterations in sensory perception, a core phenotype of autism, are attributed to imbalanced integration of sensory information and prior knowledge during perceptual statistical (Bayesian) inference. This hypothesis has gained momentum in recent years, partly because it can be implemented both at the computational level, as in Bayesian perception, and at the level of canonical neural microcircuitry, as in predictive coding. However, empirical investigations have yielded conflicting results with evidence remaining limited.
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