Top 6 Psyarxiv Papers Today in Neuroscience


2.01 Mikeys
#1. Artificial neural networks reveal multivariate integration of information from multiple category-selective regions
Mengting Fang, Aidas Aglinskas, Yichen Li, Stefano Anzellotti
Human visual cortex is organized into regions that respond preferentially to different categories of objects (i.e. faces, bodies, artifacts, scenes). However, often people need to integrate information about objects from different categories to make inferences about the world. How does the brain integrate information represented in different category-selective regions? In this work, we investigated this question taking advantage of a new analysis approach. Using artificial neural networks, we modeled the multivariate statistical dependence between fMRI responses in different brain regions. Regions whose responses were predicted significantly better by a combination of multiple category-selective regions than by the best-predicting category-selective region taken individually were identified as integration hubs. We used this approach to analyze fMRI responses to complex dynamic stimuli (the movie Forrest Gump), and identified five integration hubs: 1) the posterior medial thalamus, 2) the middle cingulate gyrus, 3) the posterior...
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Multivariate Pattern Dependence Network

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Language: Python
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Total Words: 6875
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1.998 Mikeys
#2. Gaussian Process Linking Functions for Mind, Brain and Behavior
Giwon Bahg, Daniel G. Evans, Matthew Galdo, Brandon Turner
The link between mind, brain, and behavior has mystified philosophers and scientists for millennia. Recent progress has been made by forming statistical associations between manifest variables of the brain (e.g., EEG, fMRI) and manifest variables of behavior (e.g., response times, accuracy) through hierarchical latent variable models \cite{TurForSte18}. Within this framework, one can make inferences about the mind in a statistically principled way, such that complex patterns of brain-behavior associations drive the inference procedure. However, previous approaches were limited in the flexibility of the linking function, which has proven prohibitive for understanding the complex dynamics exhibited by the brain. In this article, we propose a data-driven, non-parametric approach that allows complex linking functions to emerge from fitting a hierarchical latent representation of the mind to multivariate, multimodal data. Furthermore, to enforce biological plausibility, we impose both spatial and temporal structure so that the types...
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Authors: 4
Total Words: 11717
Unqiue Words: 3253

1.997 Mikeys
#3. Involvement of the Cortico-Basal Ganglia-Thalamo-Cortical Loop in Developmental Stuttering
Soo-Eun Chang, Frank H Guenther
Stuttering is a complex neurodevelopmental disorder that has to date eluded a clear explication of its pathophysiological bases. In this review, we utilize the Directions Into Velocities of Articulators (DIVA) neurocomputational modeling framework to mechanistically interpret relevant findings from the behavioral and neurological literatures on stuttering. Within this theoretical framework, we propose that the primary impairment underlying stuttering behavior is malfunction in the cortico-basal ganglia-thalamocortical (hereafter, cortico-BG) loop that is responsible for initiating speech motor programs. This theoretical perspective predicts three possible loci of impaired neural processing within the cortico-BG loop that could lead to stuttering behaviors: impairment within the basal ganglia proper, impairment of axonal projections between cerebral cortex, basal ganglia, and thalamus, and impairment in cortical processing. These theoretical perspectives are presented in detail, followed by a review of empirical data that make...
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Total Words: 13986
Unqiue Words: 5271

1.997 Mikeys
#4. On the nature of explanations offered by network science: A perspective from and for practicing neuroscientists
Maxwell Bertolero, Danielle S Bassett
This article is part a forthcoming Topics in Cognitive Science Special Issue: "Levels of Explanation in Cognitive Science: From Molecules to Culture," Matteo Colombo and Markus Knauff (Topic Editors). Network neuroscience represents the brain as a collection of regions and inter-regional connections. Given its ability to formalize systems-level models, network neuroscience has generated unique explanations of neural function and behavior. The mechanistic status of these explanations and how they can contribute to and fit within the field of neuroscience as a whole has received careful treatment from philosophers. However, these philosophical contributions have not yet reached many neuroscientists. Here we complement formal philosophical efforts by providing an applied perspective from and for neuroscientists. We discuss the mechanistic status of the explanations offered by network neuroscience and how they contribute to, enhance, and interdigitate with other types of explanations in neuroscience. In doing so, we rely on...
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1.997 Mikeys
#5. Inhibition in selective attention
Dirk van Moorselaar, Heleen Slagter
Our ability to focus on goal-relevant aspects of the environment is critically dependent on our ability to ignore or inhibit distracting information. It is commonly assumed that distractor inhibition is under similar voluntary control as attentional facilitation of target processing. In contrast, a rapidly growing body of research shows that distractor inhibition often relies on prior experience with the distracting information or other mechanisms that by-pass working memory. Yet, how and when these different forms of inhibition are neurally implemented remains largely unclear. Here, we review findings from recent behavioral and neuroimaging studies in humans to address this outstanding question. We specifically explore how experience with distracting information may change the processing of that information in the context of current predictive processing views of perception: by modulating a distractor’s representation already in anticipation of the distractor, or after integration of top-down and bottom-up sensory signals. We...
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1.946 Mikeys
#6. The radically embodied conscious cybernetic Bayesian brain: Towards explaining the emergence of agency
Adam Safron
Enactivists have criticized traditional cognitive science as hamstrung by naïve Cartesian assumptions that mischaracterize minds as analyzable apart from the context of embedded bodies. Indeed, the starting place for understanding minds must be in terms of their evolution and development as control systems for niche-constructing organisms. Here, I will draw from both enactivist and cognitivist perspectives on mind, proposing that an adequate characterization of teleological phenomena may require a reappraisal of mental homunculi as embodied self models (ESMs), understood as body maps with quasi-agentic properties. Further, these homunculi may attain awareness through inner theaters (i.e., generative models of space and causation), with which they experience and modify representational content. In brief, this manuscript is an attempt at unification in cognitive science, endeavoring to show how a radically embodied cybernetic Bayesian brain may create foundations for intelligence, consciousness, and will.
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