Dataset Information

Differences in the emergent coding properties of cortical and striatal ensembles.

ABSTRACT: The function of a given brain region is often defined by the coding properties of its individual neurons, yet how this information is combined at the ensemble level is an equally important consideration. We recorded multiple neurons from the anterior cingulate cortex (ACC) and the dorsal striatum (DS) simultaneously as rats performed different sequences of the same three actions. Sequence and lever decoding was markedly similar on a per-neuron basis in the two regions. At the ensemble level, sequence-specific representations in the DS appeared synchronously, but transiently, along with the representation of lever location, whereas these two streams of information appeared independently and asynchronously in the ACC. As a result, the ACC achieved superior ensemble decoding accuracy overall. Thus, the manner in which information was combined across neurons in an ensemble determined the functional separation of the ACC and DS on this task.

SUBMITTER: Ma L

PROVIDER: S-EPMC4978541 | biostudies-literature | 2014 Aug

REPOSITORIES: biostudies-literature

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Differences in the emergent coding properties of cortical and striatal ensembles.

Ma Liya L Hyman James M JM Lindsay Adrian J AJ Phillips Anthony G AG Seamans Jeremy K JK

Nature neuroscience 20140629 8

The function of a given brain region is often defined by the coding properties of its individual neurons, yet how this information is combined at the ensemble level is an equally important consideration. We recorded multiple neurons from the anterior cingulate cortex (ACC) and the dorsal striatum (DS) simultaneously as rats performed different sequences of the same three actions. Sequence and lever decoding was markedly similar on a per-neuron basis in the two regions. At the ensemble level, seq ...[more]

PMID: 24974796

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Project description:Intracellular transport is an essential function in eucaryotic cells, facilitated by motor proteins-proteins converting chemical energy into kinetic energy. It is understood that motor proteins work in teams enabling unidirectional and bidirectional transport of intracellular cargo over long distances. Disruptions of the underlying transport mechanisms, often caused by mutations that alter single motor characteristics, are known to cause neurodegenerative diseases. For example, phosphorylation of kinesin motor domain at the serine residue is implicated in Huntington's disease, with a recent study of phosphorylated and phosphomimetic serine residues indicating lowered single motor stalling forces. In this article we report the effects of mutations of this nature on transport properties of cargo carried by multiple wild-type and mutant motors. Results indicate that mutants with altered stall forces might determine the average velocity and run-length even when they are outnumbered by wild type motors in the ensemble. It is shown that mutants gain a competitive advantage and lead to an increase in the expected run-length when the load on the cargo is in the vicinity of the mutant's stalling force or a multiple of its stalling force. A separate contribution of this article is the development of a semi-analytic method to analyze transport of cargo by multiple motors of multiple types. The technique determines transition rates between various relative configurations of motors carrying the cargo using the transition rates between various absolute configurations. This enables a computation of biologically relevant quantities like average velocity and run-length without resorting to Monte Carlo simulations. It can also be used to introduce alterations of various single motor parameters to model a mutation and to deduce effects of such alterations on the transport of a common cargo by multiple motors. Our method is easily implementable and we provide a software package for general use.

Dataset Information

Differences in the emergent coding properties of cortical and striatal ensembles.

Publications

Differences in the emergent coding properties of cortical and striatal ensembles.

Similar Datasets

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