attracting dynamics of frontal cortex ensembles during memory-guided decision-making吸引动力学的额叶皮层乐团在memory-guided决策.pdf

Attracting Dynamics of Frontal Cortex Ensembles during Memory-Guided Decision-Making 1. 2. 3 1 Emili Balaguer-Ballester *, Christopher C. Lapish , Jeremy K. Seamans , Daniel Durstewitz * 1 Bernstein-Center for Computational Neuroscience Heidelberg-Mannheim, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany, 2 Department of Psychology, Indiana University-Purdue University, Indianapolis, Indiana, United States of America, 3 Brain Research Center Department of Psychiatry, University of British Columbia, Vancouver, Canada Abstract A common theoretical view is that attractor-like properties of neuronal dynamics underlie cognitive processing. However, although often proposed theoretically, direct experimental support for the convergence of neural activity to stable population patterns as a signature of attracting states has been sparse so far, especially in higher cortical areas. Combining state space reconstruction theorems and statistical learning techniques, we were able to resolve details of anterior cingulate cortex (ACC) multiple single-unit activity (MSUA) ensemble dynamics during a higher cognitive task which were not accessible previously. The approach worked by constructing high-dimensional state spaces from delays of the original single-unit firing rate variables and the interactions among them, which were then statistically analyzed using kernel methods. We observed cognitive-epoch-specific neural ensemble states in ACC which were stable across many trials (in the sense of being predictive) and depended on behavioral performance. More intere