Over the last two decades numerous functional imaging studies have shown that higher order cognitive functions are crucially dependent on the formation of distributed, large-scale neuronal assemblies (neurocognitive networks), often for very short durations. This has fueled the development of a vast number of functional connectivity measures that attempt to capture the spatiotemporal evolution of neurocognitive networks. Unfortunately, interpreting the neural basis of goal directed behavior using connectivity measures on neuroimaging data are highly dependent on the assumptions underlying the development of the measure, the nature of the task, and the modality of the neuroimaging technique that was used. This paper has two main purposes. The first is to provide an overview of some of the different measures of functional/effective connectivity that deal with high temporal resolution neuroimaging data. We will include some results that come from a recent approach that we have developed to identify the formation and extinction of task-specific, large-scale neuronal assemblies from electrophysiological recordings at a ms-by-ms temporal resolution. The second purpose of this paper is to indicate how to partially validate the interpretations drawn from this (or any other) connectivity technique by using simulated data from large-scale, neurobiologically realistic models. Specifically, we applied our recently developed method to realistic simulations of MEG data during a delayed match-to-sample (DMS) task condition and a passive viewing of stimuli condition using a large-scale neural model of the ventral visual processing pathway. Simulated MEG data using simple head models were generated from sources placed in V1, V4, IT, and prefrontal cortex (PFC) for the passive viewing condition. The results show how closely the conclusions obtained from the functional connectivity method match with what actually occurred at the neuronal network level.
Using large-scale neural models to interpret connectivity measures of cortico-cortical dynamics at millisecond temporal resolution
A. Banerjee,Ajay S. Pillai,B. Horwitz
Published 2012 in Frontiers in Systems Neuroscience
ABSTRACT
PUBLICATION RECORD
- Publication year
2012
- Venue
Frontiers in Systems Neuroscience
- Publication date
2012-01-06
- Fields of study
Medicine, Computer Science
- Identifiers
- External record
- Source metadata
Semantic Scholar, PubMed
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EXTRACTION MAP
CLAIMS
CONCEPTS
- delayed match-to-sample (dms) task
A working-memory task in which a later stimulus must be compared with an earlier sample stimulus.
Aliases: DMS task, delayed match-to-sample task
- effective connectivity measures
Metrics used to infer directed influences or causal interactions among neural elements from neuroimaging data.
Aliases: effective connectivity, EC measures
- functional connectivity measures
Metrics used to estimate statistical relationships among brain regions from neuroimaging data.
Aliases: functional connectivity, FC measures
- high temporal resolution neuroimaging data
Neuroimaging recordings sampled fast enough to resolve rapid changes in brain activity over short time scales.
Aliases: high-temporal-resolution neuroimaging data
- passive viewing condition
An experimental condition in which stimuli are observed without an explicit decision or matching response.
Aliases: passive viewing
- simple head models
Simplified forward models used to map simulated neural sources to MEG sensor measurements.
Aliases: simple head model
- simulated meg data
Magnetoencephalography signals produced computationally from a model rather than measured directly from participants.
Aliases: simulated magnetoencephalography data, simulated MEG signals
- task-specific, large-scale neuronal assemblies
Distributed groups of neurons that transiently coordinate during a particular task.
Aliases: large-scale neuronal assemblies, task-specific assemblies
- ventral visual processing pathway
A modeled visual-processing pathway spanning early and higher-order visual areas used as the source network in the simulations.
Aliases: ventral visual pathway
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