Abstract
In 1949, Donald Hebb postulated that assemblies of synchronously activated neurons are the elementary units of information processing in the brain. Despite being one of the most influential theories in neuroscience, Hebb's cell assembly hypothesis only started to become testable in the past two decades due to technological advances. However, while the technology for the simultaneous recording of large neuronal populations undergoes fast development, there is still a paucity of analytical methods that can properly detect and track the activity of cell assemblies. Here we describe a principal component-based method that is able to (1) identify all cell assemblies present in the neuronal population investigated, (2) determine the number of neurons involved in ensemble activity, (3) specify the precise identity of the neurons pertaining to each cell assembly, and (4) unravel the time course of the individual activity of multiple assemblies. Application of the method to multielectrode recordings of awake and behaving rats revealed that assemblies detected in the cerebral cortex and hippocampus typically contain overlapping neurons. The results indicate that the PCA method presented here is able to properly detect, track and specify neuronal assemblies, irrespective of overlapping membership.
Highlights
Hebb’s seminal work constitutes a landmark of modern neuroscience [1]
Notice further that three other eigenvalues fall below the lower limit; the number of eigenvalues outside the theoretical limits is 5, which corresponds to the number of neurons participating in cell assemblies. (D) Autocorrelation matrix (ACM) eigenvectors associated with the two eigenvalues above the theoretical limit for random activity
The overall algorithm is based on Principal Component Analysis (PCA) and can be divided in three major steps: (1) Detection of the number of cell assemblies and assembly neurons; (2) Identification of cell assemblies; and (3) Computation of assembly activity as a function of time
Summary
Hebb’s seminal work constitutes a landmark of modern neuroscience [1]. His theory proposes detailed neural mechanisms for the processing and learning of information, from the molecular, cellular and circuit levels to the emergence of complex cognitive functions. Synchronization of spike times would play a critical role in the creation of new assemblies [2,3,4,5,6] In this context, a cell assembly is defined as a group of neurons that fire together and wire together. Hebb postulated that the activation of a cell assembly can lead to the sequential activation of other assemblies, a phenomenon he termed as phase-sequences, and proposed to underlie complex brain computations (see [10,11,12]). In line with this view, neocortical and hippocampal information has been shown to be widely distributed over neuronal populations, rather than encoded by the activity of highly specialized cells [13,14,15,16,17,18,19]
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