Dataset Information

Encoding of spatio-temporal input characteristics by a CA1 pyramidal neuron model.

ABSTRACT: The in vivo activity of CA1 pyramidal neurons alternates between regular spiking and bursting, but how these changes affect information processing remains unclear. Using a detailed CA1 pyramidal neuron model, we investigate how timing and spatial arrangement variations in synaptic inputs to the distal and proximal dendritic layers influence the information content of model responses. We find that the temporal delay between activation of the two layers acts as a switch between excitability modes: short delays induce bursting while long delays decrease firing. For long delays, the average firing frequency of the model response discriminates spatially clustered from diffused inputs to the distal dendritic tree. For short delays, the onset latency and inter-spike-interval succession of model responses can accurately classify input signals as temporally close or distant and spatially clustered or diffused across different stimulation protocols. These findings suggest that a CA1 pyramidal neuron may be capable of encoding and transmitting presynaptic spatiotemporal information about the activity of the entorhinal cortex-hippocampal network to higher brain regions via the selective use of either a temporal or a rate code.

SUBMITTER: Pissadaki EK

PROVIDER: S-EPMC3002985 | biostudies-literature | 2010 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Encoding of spatio-temporal input characteristics by a CA1 pyramidal neuron model.

Pissadaki Eleftheria Kyriaki EK Sidiropoulou Kyriaki K Reczko Martin M Poirazi Panayiota P

PLoS computational biology 20101216 12

The in vivo activity of CA1 pyramidal neurons alternates between regular spiking and bursting, but how these changes affect information processing remains unclear. Using a detailed CA1 pyramidal neuron model, we investigate how timing and spatial arrangement variations in synaptic inputs to the distal and proximal dendritic layers influence the information content of model responses. We find that the temporal delay between activation of the two layers acts as a switch between excitability modes: ...[more]

PMID: 21187899

Similar Datasets

Project description:To evaluate molecular signatures of an individual cell type in comparison to the associated region relevant towards understanding the pathogenesis of Alzheimer's disease (AD), CA1 pyramidal neurons and the surrounding hippocampal formation were microaspirated via laser capture microdissection (LCM) from neuropathologically confirmed AD and age-matched control (CTR) subjects as well as from wild type mouse brain using single population RNA amplification methodology coupled with custom-designed microarray analysis with real-time quantitative polymerase-chain reaction (qPCR) validation. CA1 pyramidal neurons predominantly displayed downregulation of classes of transcripts related to synaptic transmission in AD versus CTR. Regional hippocampal dissections displayed downregulation of several overlapping genes found in the CA1 neuronal population related to neuronal expression, as well as upregulation of select transcripts indicative of admixed cell types including glial-associated markers and immediate-early and cell death genes. Gene level distributions observed in CA1 neurons and regional hippocampal dissections in wild type mice paralleled expression mosaics seen in postmortem human tissue. Microarray analysis was validated in qPCR studies using human postmortem brain tissue and CA1 sector and regional hippocampal dissections obtained from a mouse model of AD/Down syndrome (Ts65Dn mice) and normal disomic (2N) littermates. Classes of transcripts that have a greater percentage of the overall hybridization signal intensity within single neurons tended to be genes related to neuronal communication. The converse was also found, as classes of transcripts such as glial-associated markers were under represented in CA1 pyramidal neuron expression profiles relative to regional hippocampal dissections. These observations highlight a dilution effect that is likely to occur in conventional regional microarray and qPCR studies. Thus, single population studies of specific neurons and intrinsic circuits will likely yield informative gene expression profile data that may be subthreshold and/or underrepresented in regional studies with an admixture of cell types.

Project description:Over the past two decades, substantial amount of work has been conducted to characterize different odorant receptors, neuroanatomy and odorant response properties of the early olfactory system of Drosophila melanogaster. Yet many odorant receptors remain only partially characterized, and the odorant transduction process and the axon hillock spiking mechanism of the olfactory sensory neurons (OSNs) have yet to be fully determined. Identity and concentration, two key characteristics of the space of odorants, are encoded by the odorant transduction process. Detailed molecular models of the odorant transduction process are, however, scarce for fruit flies. To address these challenges we advance a comprehensive model of fruit fly OSNs as a cascade consisting of an odorant transduction process (OTP) and a biophysical spike generator (BSG). We model odorant identity and concentration using an odorant-receptor binding rate tensor, modulated by the odorant concentration profile, and an odorant-receptor dissociation rate tensor, and quantitatively describe the mechanics of the molecular ligand binding/dissociation of the OTP. We model the BSG as a Connor-Stevens point neuron. The resulting spatio-temporal encoding model of the Drosophila antenna provides a theoretical foundation for understanding the neural code of both odorant identity and odorant concentration and advances the state-of-the-art in a number of ways. First, it quantifies on the molecular level the spatio-temporal level of complexity of the transformation taking place in the antennae. The concentration-dependent spatio-temporal code at the output of the antenna circuits determines the level of complexity of olfactory processing in the downstream neuropils, such as odorant recognition and olfactory associative learning. Second, the model is biologically validated using multiple electrophysiological recordings. Third, the model demonstrates that the currently available data for odorant-receptor responses only enable the estimation of the affinity of the odorant-receptor pairs. The odorant-dissociation rate is only available for a few odorant-receptor pairs. Finally, our model calls for new experiments for massively identifying the odorant-receptor dissociation rates of relevance to flies.

Dataset Information

Encoding of spatio-temporal input characteristics by a CA1 pyramidal neuron model.

Publications

Encoding of spatio-temporal input characteristics by a CA1 pyramidal neuron model.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets