RT Journal Article
SR Electronic
T1 Automated long-term recording and analysis of neural activity in behaving animals
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 033266
DO 10.1101/033266
A1 Ashesh K. Dhawale
A1 Rajesh Poddar
A1 Evi Kopelowitz
A1 Valentin Normand
A1 Steffen B. E. Wolff
A1 Bence P. Ölveczky
YR 2015
UL http://biorxiv.org/content/early/2015/11/30/033266.abstract
AB Addressing how neural circuits underlie behavior is routinely done by measuring electrical activity from single neurons during experimental sessions. While such recordings yield snapshots of neural dynamics during specified tasks, they are ill-suited for tracking single-unit activity over longer timescales relevant for most developmental and learning processes, or for capturing neural dynamics outside of task context. Here we describe an automated platform for continuous long-term recordings of neural activity and behavior in freely moving animals. An unsupervised algorithm identifies and tracks the activity of single units over weeks of recording, dramatically simplifying the analysis of large datasets. Months-long recordings from motor cortex and striatum made and analyzed with our system revealed remarkable stability in basic neuronal properties, such as firing rates and inter-spike interval distributions. Interneuronal correlations and the representation of different movements and behaviors were similarly stable. This establishes the feasibility of high-throughput long-term extracellular recordings in behaving animals.