Biomedical subjects

M C Quirk

Publications and source records attributed to M C Quirk.

5 recordsLinked to original sources

PubMed2001

Construction and analysis of non-Poisson stimulus-response models of neural spiking activity.

A paradigm for constructing and analyzing non-Poisson stimulus-response models of neural spike train activity is presented. Inhomogeneous gamma (IG) and inverse Gaussian (IIG) probability models are constructed by generalizing the derivation of the inhomogeneous Poisson (IP) model from the exponential probability density. The resultant spike train models have Markov dependence. Quantile-quantile (Q-Q) plots and Kolmogorov-Smirnov (K-S) plots are developed based on the rate-rescaling theorem to assess model goodness-of-fit. The analysis also expresses the spike rate function of the neuron directly in terms of its interspike interval (ISI) distribution. The methods are illustrated with an analysis of 34 spike trains from rat CA1 hippocampal pyramidal neurons recorded while the animal executed a behavioral task. The stimulus in these experiments is the animal's position in its environment and the response is the neural spiking activity. For all 34 pyramidal cells, the IG and IIG models gave better fits to the spike trains than the IP. The IG model more accurately described the frequency of longer ISIs, whereas the IIG model gave the best description of the burst frequency, i.e. ISIs < or = 20 ms. The findings suggest that bursts are a significant component of place cell spiking activity even when position and the background variable, theta phase, are taken into account. Unlike the Poisson model, the spatial and temporal rate maps of the IG and IIG models depend directly on the spiking history of the neurons. These rate maps are more physiologically plausible since the interaction between space and time determines local spiking propensity. While this statistical paradigm is being developed to study information encoding by rat hippocampal neurons, the framework should be applicable to stimulus-response experiments performed in other neural systems.

Action Potentials↗

PubMed2001

Experience-dependent changes in extracellular spike amplitude may reflect regulation of dendritic action potential back-propagation in rat hippocampal pyramidal cells.

Activity-dependent attenuations in extracellular spike amplitude have been shown to correlate with a decrease in the effectiveness with which somatic action potentials back-propagate into the dendritic arbor of hippocampal pyramidal cells. In this paper we demonstrate that activity-dependent attenuations in amplitude occur during behavior and that the amount of attenuation is reduced with an animal's experience in an environment. The observed reductions are caused by an animal's experience within a specific environmental context, are dependent on functional NMDA receptors, and are accompanied by an increase in the effective coupling of pyramidal cells and interneurons. These results provide an important step in linking together in vivo studies with in vitro data and suggest that mechanisms of plasticity engaged during behavior may be sufficient to alter the biophysical and integrative properties of hippocampal pyramidal cells.

Action Potentials↗

PubMed2000

Experience-dependent asymmetric shape of hippocampal receptive fields.

We propose a novel parameter, namely, the skewness, or asymmetry, of the shape of a receptive field to characterize two properties of hippocampal place fields. First, a majority of hippocampal receptive fields on linear tracks are negatively skewed, such that during a single pass the firing rate is low as the rat enters the field but high as it exits. Second, while the place fields are symmetric at the beginning of a session, they become highly asymmetric with experience. Further experiments suggest that these results are likely to arise due to synaptic plasticity during behavior. Using a purely feed forward neural network model, we show that following repeated directional activation, NMDA-dependent long-term potentiation/long-term depotentiation (LTP/LTD) could result in an experience-dependent asymmetrization of receptive fields.

Action Potentials↗

PubMed1999

Interaction between spike waveform classification and temporal sequence detection.

In vivo extracellular recordings have allowed researchers to study the response properties of neurons to behaviorally relevant stimuli. In this paper we use multiple tetrode recordings from the hippocampus of the freely behaving rat to show that the action potential amplitude of a given cell can vary in a systematic and activity dependent manner over behaviorally relevant time scales. Since the discrimination algorithms used by experimenters to isolate cells from extracellular recordings are based on differences in waveforms, we show how these systematic changes in waveform shape can lead to non-random errors in single cell isolation. We further demonstrate that these non-random errors can lead to apparent temporal ordering effects between neurons in the absence of any specific temporal relationship. A firm understanding of these naturally occurring physiological changes is therefore critical for the evaluation of higher order phenomena such as the temporally correlated firing of ensembles of neurons.

Action Potentials↗

PubMed1998

A statistical paradigm for neural spike train decoding applied to position prediction from ensemble firing patterns of rat hippocampal place cells.

The problem of predicting the position of a freely foraging rat based on the ensemble firing patterns of place cells recorded from the CA1 region of its hippocampus is used to develop a two-stage statistical paradigm for neural spike train decoding. In the first, or encoding stage, place cell spiking activity is modeled as an inhomogeneous Poisson process whose instantaneous rate is a function of the animal's position in space and phase of its theta rhythm. The animal's path is modeled as a Gaussian random walk. In the second, or decoding stage, a Bayesian statistical paradigm is used to derive a nonlinear recursive causal filter algorithm for predicting the position of the animal from the place cell ensemble firing patterns. The algebra of the decoding algorithm defines an explicit map of the discrete spike trains into the position prediction. The confidence regions for the position predictions quantify spike train information in terms of the most probable locations of the animal given the ensemble firing pattern. Under our inhomogeneous Poisson model position was a three to five times stronger modulator of the place cell spiking activity than theta phase in an open circular environment. For animal 1 (2) the median decoding error based on 34 (33) place cells recorded during 10 min of foraging was 8.0 (7.7) cm. Our statistical paradigm provides a reliable approach for quantifying the spatial information in the ensemble place cell firing patterns and defines a generally applicable framework for studying information encoding in neural systems.

Action Potentials↗