{"title":"Unraveling the Neural Code: Analysis of Large-Scale Two-Photon Microscopy Data.","authors":"Yoshihito Saito, Yuma Osako, Masanori Murayama","doi":"10.1093/jmicro/dfaf010","DOIUrl":null,"url":null,"abstract":"<p><p>The brain is an intricate neuronal network that orchestrates our thoughts, emotions, and actions through dynamic interactions between neurons. If we could record the activity of all neurons simultaneously in detail, it could revolutionize our understanding of brain function and lead to breakthroughs in treating neurological diseases. Recent technological innovations, particularly in large field-of-view two-photon microscopes, have made it possible to record the activity of tens of thousands of neurons simultaneously. However, the size and complexity of the datasets present significant challenges in extracting interpretable information. Conventional analysis methods are often insufficient, necessitating the development of new theoretical frameworks and computational efficiencies. In this review, we describe the characteristics of the data obtained from advanced imaging techniques and discuss analytical methods to facilitate mutual understanding between experimentalists and theorists. This interdisciplinary approach is crucial for effectively managing and interpreting large-scale neural activity datasets, ultimately advancing our understanding of brain function.</p>","PeriodicalId":74193,"journal":{"name":"Microscopy (Oxford, England)","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2025-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Microscopy (Oxford, England)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1093/jmicro/dfaf010","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The brain is an intricate neuronal network that orchestrates our thoughts, emotions, and actions through dynamic interactions between neurons. If we could record the activity of all neurons simultaneously in detail, it could revolutionize our understanding of brain function and lead to breakthroughs in treating neurological diseases. Recent technological innovations, particularly in large field-of-view two-photon microscopes, have made it possible to record the activity of tens of thousands of neurons simultaneously. However, the size and complexity of the datasets present significant challenges in extracting interpretable information. Conventional analysis methods are often insufficient, necessitating the development of new theoretical frameworks and computational efficiencies. In this review, we describe the characteristics of the data obtained from advanced imaging techniques and discuss analytical methods to facilitate mutual understanding between experimentalists and theorists. This interdisciplinary approach is crucial for effectively managing and interpreting large-scale neural activity datasets, ultimately advancing our understanding of brain function.