The convincing argument that Brette makes for the neural coding metaphor as imposing one view of brain behavior can be further explained through discourse analysis. Instead of a unified view, we argue, the coding metaphor's plasticity, versatility, and robustness throughout time explain its success and conventionalization to the point that its rhetoric became overlooked.
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http://dx.doi.org/10.1017/S0140525X1900133X | DOI Listing |
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 PDFNat 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 PDFJ 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 PDFMol 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.
View Article and Find Full Text PDFAquat Toxicol
January 2025
School of Computer Science and Software Engineering, University of Science and Technology Liaoning, Anshan, 114051, China; Wenzhou Institute, University of Chinese Academy of Sciences, Wenzhou, 325001, China. Electronic address:
As compound concentrations in aquatic environments increase, the habitat degradation of aquatic organisms underscores the growing importance of studying the impact of chemicals on diverse aquatic populations. Understanding the potential impacts of different chemical substances on different species is a necessary requirement for protecting the environment and ensuring sustainable human development. In this regard, deep learning methods offer significant advantages over traditional experimental approaches in terms of cost, accuracy, and generalization ability.
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