Unraveling the neural code: analysis of large-scale two-photon microscopy data
Open Access
- 15 February 2025
- journal article
- Published by Oxford University Press (OUP) in Microscopy
- Vol. 74 (3) , 146-163
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.Keywords
Funding Information
- Japan Agency for Medical Research and Development (JP15dm0207001 JP23wm0625001)
- Toray Science Foundation
- Japan Society for the Promotion of Science (JP20H05775 JP24H02313)
This publication has 142 references indexed in Scilit:
- Targeted Activation of Hippocampal Place Cells Drives Memory-Guided Spatial BehaviorCell, 2020
- Controlling Visually Guided Behavior by Holographic Recalling of Cortical EnsemblesCell, 2019
- Area-Specificity and Plasticity of History-Dependent Value Coding During LearningCell, 2019
- Rational Engineering of XCaMPs, a Multicolor GECI Suite for In Vivo Imaging of Complex Brain Circuit DynamicsCell, 2019
- Past, present and future of spike sorting techniquesBrain Research Bulletin, 2015
- Regression Modeling Strategies2015
- The Elements of Statistical Learning2009
- Tetrodes markedly improve the reliability and yield of multiple single-unit isolation from multi-unit recordings in cat striate cortexJournal of Neuroscience Methods, 1995
- The stereotrode: A new technique for simultaneous isolation of several single units in the central nervous system from multiple unit recordsJournal of Neuroscience Methods, 1983
- Reduced-rank regression for the multivariate linear modelJournal of Multivariate Analysis, 1975