Deep Neural Networks and Brain Alignment: Brain Encoding and Decoding (Survey)

arXiv (Cornell University), Journal Year: 2023, Volume and Issue: unknown

Published: Jan. 1, 2023

How does the brain represent different modes of information? Can we design a system that automatically understands what user is thinking? Such questions can be answered by studying recordings like functional magnetic resonance imaging (fMRI). As first step, neuroscience community has contributed several large cognitive datasets related to passive reading/listening/viewing concept words, narratives, pictures and movies. Encoding decoding models using these have also been proposed in past two decades. These serve as additional tools for basic research science neuroscience. aim at generating fMRI representations given stimulus automatically. They practical applications evaluating diagnosing neurological conditions thus help therapies damage. Decoding solve inverse problem reconstructing stimuli fMRI. are useful designing brain-machine or brain-computer interfaces. Inspired effectiveness deep learning natural language processing, computer vision, speech, recently neural encoding proposed. In this survey, will discuss popular language, vision speech stimuli, present summary datasets. Further, review based architectures note their benefits limitations. Finally, conclude with brief discussion about future trends. Given amount published work `computational neuroscience' community, believe survey nicely organizes plethora presents it coherent story.

Language: Английский

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Retrieving and reconstructing conceptually similar images from fMRI with latent diffusion models and a neuro-inspired brain decoding model

Journal of Neural Engineering, Journal Year: 2024, Volume and Issue: 21(4), P. 046001 - 046001

Published: June 17, 2024

Brain decoding is a field of computational neuroscience that aims to infer mental states or internal representations perceptual inputs from measurable brain activity. This study proposes novel approach relies on semantic and contextual similarity.

Language: Английский

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A Dialectical Approach to the Question of Consciousness

Published: Aug. 31, 2024

Cognitive neuroscience is a multidisciplinary field at the intersection of neurophysiology, psychology and philosophy, among others. An important objective cognitive to explain nature conscious experience. Its associated research programme carried out in two directions: from neural correlates phenomenal experience, experience substrate. Each paradigm produces body work, but neither seems be able cross over other side. We think that problem not complexity biological consciousness itself, inadequacy main analytical tool. Formal logic assumes linear causality, which too simplistic for describing our evolving system. Here we present result dialectical approach consciousness: Hegelian dialectics conditionally utilitizes contradiction (rather than rejecting it), allows multi-vector causality. Surprisingly, led comprehensive account consciousness, including phenomenality ontology. show emerges vertebrate evolution as synthesis cellular pre-adaptations process encephalization, constitutes new mode behavioral control. Proven correct, results may future neuroscience.

Language: Английский

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Decoding Neural Activity of the Simplest Heterogeneous Neural Networks

Published: Jan. 1, 2024

Language: Английский

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