Dr. Michael A. Silver Profile

Dr. Michael A. Silver

at Univ of California Berkeley

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Proceedings Article | 18 February 2010 Paper

Isolating human brain functional connectivity associated with a specific cognitive process

Michael Silver, Ayelet Landau, Thomas Lauritzen, William Prinzmetal, Lynn Robertson

Proceedings Volume 7527, 75270B (2010) https://doi.org/10.1117/12.849120

KEYWORDS: Visualization, Functional magnetic resonance imaging, Brain, Blood, Modulation, Neuroimaging, Visual cortex, Signal processing, Neural networks, Electronic imaging

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The use of functional magnetic resonance imaging (fMRI) to measure functional connectivity among brain areas has the potential to identify neural networks associated with particular cognitive processes. However, fMRI signals are not a direct measure of neural activity but rather represent blood oxygenation level-dependent (BOLD) signals. Correlated BOLD signals between two brain regions are therefore a combination of neural, neurovascular, and vascular coupling. Here, we describe a procedure for isolating brain functional connectivity associated with a specific cognitive process. Coherency magnitude (measuring the strength of coupling between two time series) and phase (measuring the temporal latency differences between two time series) are computed during performance of a particular cognitive task and also for a control condition. Subtraction of the coherency magnitude and phase differences for the two conditions removes sources of correlated BOLD signals that do not modulate as a function of cognitive task, resulting in a more direct measure of functional connectivity associated with changes in neuronal activity. We present two applications of this task subtraction procedure, one to measure changes in strength of coupling associated with sustained visual spatial attention, and one to measure changes in temporal latencies between brain areas associated with voluntary visual spatial attention.

Proceedings Article | 9 February 2006 Paper

Modeling the time course of attention signals in human primary visual cortex

Michael Silver

Proceedings Volume 6057, 605714 (2006) https://doi.org/10.1117/12.674149

KEYWORDS: Visualization, Functional magnetic resonance imaging, Visual cortex, Target detection, Signal detection, Visual process modeling, Data modeling, Neuroimaging, Brain, Hemodynamics

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Previous neuroimaging studies have documented the existence of attention signals in human visual cortex, but little is known about the time course of these signals. A recent study reported persistent activity in early visual cortex whose duration was correlated with the duration of sustained attention¹. The present study extends these findings by modeling the time course of sustained attention signals with a linear function with duration equal to the period of sustained attention but with variable amplitude and slope. Subjects performed a visual detection task in which a variable-duration delay period occurred before every target presentation. This design required the subjects to allocate visuospatial attention throughout the delay period. Functional magnetic resonance imaging (fMRI) was used to record activity in primary visual cortex (cortical area V1) during performance of the task. There were significant individual differences in the time course of attention signals, with some subjects displaying time courses consistent with constant amplitude attention signals, while others showed decreasing amplitude of attention-related activity during the delay period. These individual differences in time course of attention signals were correlated with behavioral response bias, suggesting that they may reflect differences in the types of attention used by the subjects to perform the detection task. In particular, those subjects who had constant amplitude sustained attention signals may have been employing relatively more endogenous, or top-down attention, while the subjects who exhibited attention signals that decreased over time may have been using relatively more exogenous, or bottom-up attention.

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