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506 results on '"Marmarelis, Vasilis Z."'

160. VLSI Implementation of a Nonlinear Neuronal Model: A "Neural Prosthesis" to Restore Hippocampal Trisynaptic Dynamics

Author

Hsiao, Min-Chi, primary, Chan, Chiu-Hsien, additional, Srinivasan, Vijay, additional, Ahuja, Ashish, additional, Erinjippurath, Gopal, additional, Zanos, Theodoros P., additional, Gholmieh, Ghassan, additional, Song, Dong, additional, Wills, Jack D., additional, LaCoss, Jeff, additional, Courellis, Spiros, additional, Tanguay, Armand R., additional, Granacki, John J., additional, Marmarelis, Vasilis Z., additional, and Berger, Theodore W., additional

Published
2006
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168. Functional connectivity between Layer 2/3 and Layer 5 neurons in prefrontal cortex of nonhuman primates during a delayed match-to-sample task.

Author

Song, Dong, Opris, Ioan, Chan, Rosa H. M., Marmarelis, Vasilis Z., Hampson, Robert E., Deadwyler, Sam A., and Berger, Theodore W.

Abstract

The prefrontal cortex (PFC) has been postulated to play critical roles in cognitive control and the formation of long-term memories. To gain insights into the neurobiological mechanism of such high-order cognitive functions, it is important to understand the input-output transformational properties of the PFC micro-circuitry. In this study, we identify the functional connectivity between the Layer 2/3 (input) neurons and the Layer 5 (output) neurons using a previously developed generalized Volterra model (GVM). Input-output spike trains are recorded from the PFCs of nonhuman primates performing a memory-dependent delayed match-to-sample task with a customized conformal ceramic multi-electrode array. The GVM describes how the input spike trains are transformed into the output spike trains by the PFC micro-circuitry and represents the transformation in the form of Volterra kernels. Results show that Layer 2/3 neurons have strong and transient facilitatory effects on the firings of Layer 5 neurons. The magnitude and temporal range of the input-output nonlinear dynamics are strikingly different from those of the hippocampal CA3-CA1. This form of functional connectivity may have important implications to understanding the computational principle of the PFC. [ABSTRACT FROM PUBLISHER]

Published
2012
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169. Analog low-power hardware implementation of a Laguerre-Volterra model of intracellular subthreshold neuronal activity.

Author

Ghaderi, Viviane S., Roach, Shane, Song, Dong, Marmarelis, Vasilis Z., Choma, John, and Berger, Theodore W.

Abstract

The right level of abstraction for a model mimicking a neural function is often difficult to determine. There are trade-offs between capturing biological complexities on one hand and the scalability and efficiency of the model on the other. In this work, we describe a nonlinear Laguerre-Volterra model of the synaptic temporal integration of input spikes to postsynaptic potentials. This model is then efficiently implemented using analog subthreshold circuits and can serve as a foundation for future large-scale hardware systems that can emulate multi-input multi-output (MIMO) spike transformations in populations of neurons. The normalized mean square error in estimating real data using the circuit implementation of this model is less than 15%. The model components are modular and its parameters are adjustable for modeling temporal integration by neurons in other brain regions. The total power consumption of this nonlinear Laguerre-Volterra system is less than 5nW. [ABSTRACT FROM PUBLISHER]

Published
2012
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191. Time-Varying Modeling of Cerebral Hemodynamics.

Author

Marmarelis, Vasilis Z., Shin, Dae C., Orme, Melissa, and Zhang, Rong

Subjects
*HEMODYNAMICS, *VASOMOTOR system, *PATHOLOGY, *BLOOD flow, *BRAIN function localization, *BLOOD pressure
Abstract

The scientific and clinical importance of cerebral hemodynamics has generated considerable interest in their quantitative understanding via computational modeling. In particular, two aspects of cerebral hemodynamics, cerebral flow autoregulation (CFA) and CO2 vasomotor reactivity (CVR), have attracted much attention because they are implicated in many important clinical conditions and pathologies (orthostatic intolerance, syncope, hypertension, stroke, vascular dementia, mild cognitive impairment, Alzheimer's disease, and other neurodegenerative diseases with cerebrovascular components). Both CFA and CVR are dynamic physiological processes by which cerebral blood flow is regulated in response to fluctuations in cerebral perfusion pressure and blood CO2 tension. Several modeling studies to date have analyzed beat-to-beat hemodynamic data in order to advance our quantitative understanding of CFA–CVR dynamics. A confounding factor in these studies is the fact that the dynamics of the CFA–CVR processes appear to vary with time (i.e., changes in cerebrovascular characteristics) due to neural, endocrine, and metabolic effects. This paper seeks to address this issue by tracking the changes in linear time-invariant models obtained from short successive segments of data from ten healthy human subjects. The results suggest that systemic variations exist but have stationary statistics and, therefore, the use of time-invariant modeling yields “time-averaged models” of physiological and clinical utility. [ABSTRACT FROM PUBLISHER]

Published
2014
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