运动编码:测量自然行为中的信息

IF 13.7 1区 生物学 Q1 BIOLOGY
Cristina Becchio , Kiri Pullar , Eugenio Scaliti , Stefano Panzeri
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引用次数: 0

摘要

近年来,人们对自然行为和自动跟踪自然行为的机器学习工具的兴趣激增。然而,关于测量什么、如何测量以及如何将自然行为与神经活动和认知过程联系起来等问题仍未得到解决。在本《视角》中,我们提出了一个通用的实验和计算框架--运动编码--用于测量认知状态信息如何被编码到结构化的行为模式中,以及在社会交往中他人如何读出这些信息。通过这一框架,可以设计新的实验并提出可检验的假设,从而在单次试验水平上将行为、认知和神经活动联系起来。研究人员可以利用这一框架来确定单个受试者、单次试验的编码和读出计算,并解决有关身体运动中编码的信息如何传递和交流的有意义的问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Kinematic coding: Measuring information in naturalistic behaviour
Recent years have seen an explosion of interest in naturalistic behaviour and in machine learning tools for automatically tracking it. However, questions about what to measure, how to measure it, and how to relate naturalistic behaviour to neural activity and cognitive processes remain unresolved. In this Perspective, we propose a general experimental and computational framework – kinematic coding – for measuring how information about cognitive states is encoded in structured patterns of behaviour and how this information is read out by others during social interactions. This framework enables the design of new experiments and the generation of testable hypotheses that link behaviour, cognition, and neural activity at the single-trial level. Researchers can employ this framework to identify single-subject, single-trial encoding and readout computations and address meaningful questions about how information encoded in bodily motion is transmitted and communicated.
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来源期刊
Physics of Life Reviews
Physics of Life Reviews 生物-生物物理
CiteScore
20.30
自引率
14.50%
发文量
52
审稿时长
8 days
期刊介绍: Physics of Life Reviews, published quarterly, is an international journal dedicated to review articles on the physics of living systems, complex phenomena in biological systems, and related fields including artificial life, robotics, mathematical bio-semiotics, and artificial intelligent systems. Serving as a unifying force across disciplines, the journal explores living systems comprehensively—from molecules to populations, genetics to mind, and artificial systems modeling these phenomena. Inviting reviews from actively engaged researchers, the journal seeks broad, critical, and accessible contributions that address recent progress and sometimes controversial accounts in the field.
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