{"title":"Preparatory activity and the expansive null-space","authors":"Mark M. Churchland, Krishna V. Shenoy","doi":"10.1038/s41583-024-00796-z","DOIUrl":null,"url":null,"abstract":"The study of the cortical control of movement experienced a conceptual shift over recent decades, as the basic currency of understanding shifted from single-neuron tuning towards population-level factors and their dynamics. This transition was informed by a maturing understanding of recurrent networks, where mechanism is often characterized in terms of population-level factors. By estimating factors from data, experimenters could test network-inspired hypotheses. Central to such hypotheses are ‘output-null’ factors that do not directly drive motor outputs yet are essential to the overall computation. In this Review, we highlight how the hypothesis of output-null factors was motivated by the venerable observation that motor-cortex neurons are active during movement preparation, well before movement begins. We discuss how output-null factors then became similarly central to understanding neural activity during movement. We discuss how this conceptual framework provided key analysis tools, making it possible for experimenters to address long-standing questions regarding motor control. We highlight an intriguing trend: as experimental and theoretical discoveries accumulate, the range of computational roles hypothesized to be subserved by output-null factors continues to expand. How does motor-cortex activity well before movement not drive motor outputs? In this Review, Churchland and Shenoy detail how searching for answers transitioned the understanding of neural activity during movement from single-neuron tuning towards population-level factors and revealed an essential computational role of output-null factors.","PeriodicalId":49142,"journal":{"name":"Nature Reviews Neuroscience","volume":"25 4","pages":"213-236"},"PeriodicalIF":28.7000,"publicationDate":"2024-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nature Reviews Neuroscience","FirstCategoryId":"3","ListUrlMain":"https://www.nature.com/articles/s41583-024-00796-z","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"NEUROSCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
The study of the cortical control of movement experienced a conceptual shift over recent decades, as the basic currency of understanding shifted from single-neuron tuning towards population-level factors and their dynamics. This transition was informed by a maturing understanding of recurrent networks, where mechanism is often characterized in terms of population-level factors. By estimating factors from data, experimenters could test network-inspired hypotheses. Central to such hypotheses are ‘output-null’ factors that do not directly drive motor outputs yet are essential to the overall computation. In this Review, we highlight how the hypothesis of output-null factors was motivated by the venerable observation that motor-cortex neurons are active during movement preparation, well before movement begins. We discuss how output-null factors then became similarly central to understanding neural activity during movement. We discuss how this conceptual framework provided key analysis tools, making it possible for experimenters to address long-standing questions regarding motor control. We highlight an intriguing trend: as experimental and theoretical discoveries accumulate, the range of computational roles hypothesized to be subserved by output-null factors continues to expand. How does motor-cortex activity well before movement not drive motor outputs? In this Review, Churchland and Shenoy detail how searching for answers transitioned the understanding of neural activity during movement from single-neuron tuning towards population-level factors and revealed an essential computational role of output-null factors.
期刊介绍:
Nature Reviews Neuroscience is a multidisciplinary journal that covers various fields within neuroscience, aiming to offer a comprehensive understanding of the structure and function of the central nervous system. Advances in molecular, developmental, and cognitive neuroscience, facilitated by powerful experimental techniques and theoretical approaches, have made enduring neurobiological questions more accessible. Nature Reviews Neuroscience serves as a reliable and accessible resource, addressing the breadth and depth of modern neuroscience. It acts as an authoritative and engaging reference for scientists interested in all aspects of neuroscience.