Abstract
How do populations of neurons work together to control behavior? To study this issue, our group simultaneously records from populations of neurons across multiple electrodes in multiple brain regions during operant behavior. Here, we describe methods for quantifying the relationship between neuronal population activity and performance of operant behavioral tasks. We describe statistical techniques, based on time- and trial-shuffling, that can establish the significance of correlations between multiple and simultaneously recorded spike trains. Then, we describe several approaches to studying functional interactions between neurons, including principal component analysis, cross-correlation analysis, analyses of rate correlations, and analyses of shared predictive information. Finally, we compare these techniques using a sample data set and discuss how the combined use of these techniques can lead to novel insights regarding neuronal interactions during behavior.
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Acknowledgments
We thank Eyal Kimchi and Nicole Horst for critical comments and helpful discussions. This work was supported by funds from the Tourette Syndrome Association, Kavli Institute at Yale, and the John B. Pierce Laboratory for ML and from an NIH training grant to the Yale Medical Scientist Training Program and Army Research Office for NSN.
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Narayanan, N.S., Laubach, M. (2009). Methods for Studying Functional Interactions Among Neuronal Populations. In: Hyder, F. (eds) Dynamic Brain Imaging. METHODS IN MOLECULAR BIOLOGY™, vol 489. Humana Press. https://doi.org/10.1007/978-1-59745-543-5_7
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DOI: https://doi.org/10.1007/978-1-59745-543-5_7
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