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T A McMullen

Publications and source records attributed to T A McMullen.

5 recordsLinked to original sources
PubMed1994

The brain as a dynamic physical system.

The brain is a dynamic system that is non-linear at multiple levels of analysis. Characterization of its non-linear dynamics is fundamental to our understanding of brain function. Identifying families of attractors in phase space analysis, an approach which has proven valuable in describing non-linear mechanical and electrical systems, can prove valuable in describing a range of behaviors and associated neural activity including sensory and motor repertoires. Additionally, transitions between attractors may serve as useful descriptors for analysing state changes in neurons and neural ensembles. Recent observations of synchronous neural activity, and the emerging capability to record the spatiotemporal dynamics of neural activity by voltage-sensitive dyes and electrode arrays, provide opportunities for observing the population dynamics of neural ensembles within a dynamic systems context. New developments in the experimental physics of complex systems, such as the control of chaotic systems, selection of attractors, attractor switching and transient states, can be a source of powerful new analytical tools and insights into the dynamics of neural systems.

Action Potentials↗
PubMed1993

A computational model of echo processing and acoustic imaging in frequency-modulated echolocating bats: the spectrogram correlation and transformation receiver.

The spectrogram correlation and transformation (SCAT) model of the sonar receiver in the big brown bat (Eptesicus fuscus) consists of a cochlear component for encoding the bat's frequency modulated (FM) sonar transmissions and multiple FM echoes in a spectrogram format, followed by two parallel pathways for processing temporal and spectral information in sonar echoes to reconstruct the absolute range and fine range structure of multiple targets from echo spectrograms. The outputs of computations taking place along these parallel pathways converge to be displayed along a computed image dimension of echo delay or target range. The resulting image depicts the location of various reflecting sources in different targets along the range axis. This series of transforms is equivalent to simultaneous, parallel forward and inverse transforms on sonar echoes, yielding the impulse responses of targets by deconvolution of the spectrograms. The performance of the model accurately reproduces the images perceived by Eptesicus in a variety of behavioral experiments on two-glint resolution in range, echo phase sensitivity, amplitude-latency trading of range estimates, dissociation of time- and frequency-domain image components, and ranging accuracy in noise.

Animals↗
PubMed1988

Model of oscillatory activity in thalamic neurons: role of voltage- and calcium-dependent ionic conductances.

This paper describes a computer modeling study of the generation of 10 Hz oscillations in the electrical activity of guinea pig thalamic neurons in vitro. The computer model was based on experimental evidence suggesting that single thalamic neurons in guinea pig have a set of voltage- and calcium-dependent ionic conductances that is capable of generating self-sustained rhythmic oscillations. Simulation results are consistent with this hypothesis, and indicate that a model that contains dendritic calcium and calcium-dependent potassium conductances, as well as a voltage-dependent, slow sodium conductance, can indeed generate self-sustained oscillations like those seen in thalamic neurons. Moreover, simulations indicate that the occurrence of such oscillatory activity is strongly dependent on the location of the slow sodium conductance. Results predict that this slow sodium conductance is located in the dendrites.

Action Potentials↗
PubMed1985

Model of d.c. potentials in the cochlea: effects of voltage-dependent cilia stiffness.

The purpose of this study was to explore possible mechanisms for the generation of the summating potential. Computer simulation was used to model the effects of potential hair cell nonlinearities on extracellular and intracellular d.c. potentials in the cochlea. No one nonlinearity can account for both extracellular and intracellular experimental data. However, a model which includes two nonlinearities (voltage-dependent cilia stiffness and nonlinear transducer channel resistance) produces extracellular and intracellular responses which match experimental data very well.

Animals↗