Contributions of I h to feature selectivity in layer II stellate cells of the entorhinal cortex
Authors: Haas, Julie; Dorval II, Alan; White, John1
Source: Journal of Computational Neuroscience, Volume 22, Number 2, April 2007 , pp. 161-171(11)
Publisher: Springer
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Abstract:
Stellate cells (SCs) of the entorhinal cortex generate prominent subthreshold oscillations that are believed to be important contributors to the hippocampal theta rhythm. The slow inward rectifier I h is expressed prominently in SCs and has been suggested to be a dominant factor in their integrative properties. We studied the input-output relationships in stellate cells (SCs) of the entorhinal cortex, both in control conditions and in the presence of the I h antagonist ZD7288. Our results show that I h is responsible for SCs' subthreshold resonance, and contributes to enhanced spiking reliability to theta-rich stimuli. However, SCs still exhibit other traits of rhythmicity, such as subthreshold oscillations, under I h blockade. To clarify the effects of I h on SC spiking, we used a generalized form of principal component analysis to show that SCs select particular features with relevant temporal signatures from stimuli. The spike-selected mix of those features varies with the frequency content of the stimulus, emphasizing the inherent nonlinearity of SC responses. A number of controls confirmed that this selectivity represents a stimulus-induced change in the cellular input-output relationship rather than an artifact of the analysis technique. Sensitivity to slow features remained statistically significant in ZD7288. However, with I h blocked, slow stimulus features were less predictive of spikes and spikes conveyed less information about the stimulus over long time scales. Together, these results suggest that I h is an important contributor to the input-output relationships expressed by SCs, but that other factors in SCs also contribute to subthreshold oscillations and nonlinear selectivity to slow features.Keywords: Inward rectifier; Reliability; Information theory; Spike-triggered covariance; Principal component analysis; Single-neuron computation
Document Type: Research article
DOI: 10.1007/s10827-006-0005-7
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