Dataset Information

Altered phase precession and compression of temporal sequences by place cells in epileptic rats.

ABSTRACT: In the hippocampus, pyramidal cells encode information in two major ways: rate coding and temporal coding. Rate coding, in which information is coded through firing frequency, is exemplarily illustrated by place cells, characterized by their location-specific firing. In addition, the precise temporal organization of firing of multiple place cells provides information, in a compressed time window, about the temporal sequence of the locations visited by the animal. This encoding is accomplished through phase precession, a phenomenon whereby unit firing is linked to theta rhythm, one of the major hippocampal EEG oscillations. Although it is likely that this type of processing is critical for normal brain function, its involvement in pathologies associated with cognitive disorders is unknown. In this experiment, we determined whether the temporal organization of place cell firing is affected in an animal model of mesial temporal lobe epilepsy (MTLE), a disease accompanied with cognitive impairment. We investigated hippocampal coding and its relationship to theta rhythm in rats after status epilepticus (SE), a condition that leads to MTLE. We found a great proportion of SE place cells had aberrant phase/precession pattern and temporal organization of firing among pairs of neurons, which constitutes the compression of temporal sequences, was altered in SE rats. The same animals were also markedly impaired in the water maze task, a measure of spatial memory. We propose that the synaptic and cellular alterations observed in MTLE induce aberrant temporal coding in the hippocampus, contributing in turn to cognitive dysfunction.

SUBMITTER: Lenck-Santini PP

PROVIDER: S-EPMC3304586 | biostudies-literature | 2008 May

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Altered phase precession and compression of temporal sequences by place cells in epileptic rats.

Lenck-Santini Pierre-Pascal PP Holmes Gregory L GL

The Journal of neuroscience : the official journal of the Society for Neuroscience 20080501 19

In the hippocampus, pyramidal cells encode information in two major ways: rate coding and temporal coding. Rate coding, in which information is coded through firing frequency, is exemplarily illustrated by place cells, characterized by their location-specific firing. In addition, the precise temporal organization of firing of multiple place cells provides information, in a compressed time window, about the temporal sequence of the locations visited by the animal. This encoding is accomplished th ...[more]

PMID: 18463258

Similar Datasets

Project description:Neural codes have been postulated to build efficient representations of the external world. The hippocampus, an encoding system, employs neuronal firing rates and spike phases to encode external space. Although the biophysical origin of such codes is at a single neuronal level, the role of neural components in efficient coding is not understood. The complexity of this problem lies in the dimensionality of the parametric space encompassing neural components, and is amplified by the enormous biological heterogeneity observed in each parameter. A central question that spans encoding systems therefore is how neurons arrive at efficient codes in the face of widespread biological heterogeneities. To answer this, we developed a conductance-based spiking model for phase precession, a phase code of external space exhibited by hippocampal place cells. Our model accounted for several experimental observations on place cell firing and electrophysiology: the emergence of phase precession from exact spike timings of conductance-based models with neuron-specific ion channels and receptors; biological heterogeneities in neural components and excitability; the emergence of subthreshold voltage ramp, increased firing rate, enhanced theta power within the place field; a signature reduction in extracellular theta frequency compared to its intracellular counterpart; and experience-dependent asymmetry in firing-rate profile. We formulated phase-coding efficiency, using Shannon's information theory, as an information maximization problem with spike phase as the response and external space within a single place field as the stimulus. We employed an unbiased stochastic search spanning an 11-dimensional neural space, involving thousands of iterations that accounted for the biophysical richness and neuron-to-neuron heterogeneities. We found a small subset of models that exhibited efficient spatial information transfer through the phase code, and investigated the distinguishing features of this subpopulation at the parametric and functional scales. At the parametric scale, which spans the molecular components that defined the neuron, several nonunique parametric combinations with weak pairwise correlations yielded models with similar high phase-coding efficiency. Importantly, placing additional constraints on these models in terms of matching other aspects of hippocampal neural responses did not hamper parametric degeneracy. We provide quantitative evidence demonstrating this parametric degeneracy to be a consequence of a many-to-one relationship between the different parameters and phase-coding efficiency. At the functional scale, involving the cellular-scale neural properties, our analyses revealed an important higher-order constraint that was exclusive to models exhibiting efficient phase coding. Specifically, we found a counterbalancing negative correlation between neuronal gain and the strength of external synaptic inputs as a critical functional constraint for the emergence of efficient phase coding. These observations implicate intrinsic neural properties as important contributors in effectuating such counterbalance, which can be achieved by recruiting nonunique parametric combinations. Finally, we show that a change in afferent statistics, manifesting as input asymmetry onto these neuronal models, induced an adaptive shift in the phase code that preserved its efficiency. Together, our analyses unveil parametric degeneracy as a mechanism to harness widespread neuron-to-neuron heterogeneity towards accomplishing stable and efficient encoding, provided specific higher-order functional constraints on the relationship of neural gain to external inputs are satisfied.

Dataset Information

Altered phase precession and compression of temporal sequences by place cells in epileptic rats.

Publications

Altered phase precession and compression of temporal sequences by place cells in epileptic rats.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets