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Feature selection in the human brain: electrophysiological correlates of sensory enhancement and feature integration.

ABSTRACT: This study examined the latency and amplitude of cortical processes associated with feature-based visual selective attention, using frequency-domain and time-domain measures derived from dense-array electroencephalography. Participants were asked to identify targets based on conjunctions of three types of object features (color, size, and completeness). This procedure aimed to examine (1) the modulation of sensory responses to one or more stimulus features characterizing an object and (2) the facilitation and reduction effects associated with competing features, attended and unattended, in the same object. The selection negativity, an event-related potential measure of sensory amplification for attended features, showed a parametric increase of amplitude as a function of the number of attended features. Late oscillations in the gamma band range were also smaller for stimuli with one or more non-attended visual features but were enhanced for stimuli sharing the overall gestalt with the target. The latency of this late gamma modulation was delayed when two target features were combined, compared to one single discriminative feature. Latency analyses also showed that late bursts of induced high-frequency oscillatory activity peaked around 60 ms later than the selection negativity. Oscillatory activity reflected both selective amplification and competition between object features. These results suggest that sensory amplification of selected features is followed by integrative processing in more widespread networks. Oscillatory activity in these networks is reduced by distraction and is enhanced when attended features can be mapped to specific action.

SUBMITTER: Keil A

PROVIDER: S-EPMC3664361 | biostudies-other | 2010 Feb

REPOSITORIES: biostudies-other

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Feature selection in the human brain: electrophysiological correlates of sensory enhancement and feature integration.

Keil Andreas A Müller Matthias M MM

Brain research 20091211

This study examined the latency and amplitude of cortical processes associated with feature-based visual selective attention, using frequency-domain and time-domain measures derived from dense-array electroencephalography. Participants were asked to identify targets based on conjunctions of three types of object features (color, size, and completeness). This procedure aimed to examine (1) the modulation of sensory responses to one or more stimulus features characterizing an object and (2) the fa ...[more]

PMID: 20005214

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Project description:Tools assaying the neural networks that modulate consciousness may facilitate tracking of recovery after acute severe brain injury. The ABCD framework classifies resting-state EEG into categories reflecting levels of thalamocortical network function that correlate with outcome in post-cardiac arrest coma. In this longitudinal cohort study, we applied the ABCD framework to 20 patients with acute severe traumatic brain injury requiring intensive care (12 of whom were also studied at ≥6-months post-injury) and 16 healthy controls. We tested four hypotheses: 1) EEG ABCD classifications are spatially heterogeneous and temporally variable; 2) ABCD classifications improve longitudinally, commensurate with the degree of behavioral recovery; 3) ABCD classifications correlate with behavioral level of consciousness; and 4) the Coma Recovery Scale-Revised arousal facilitation protocol yields improved ABCD classifications. Channel-level EEG power spectra were classified based on spectral peaks within pre-defined frequency bands: 'A' = no peaks above delta (<4 Hz) range (complete thalamocortical disruption); 'B' = theta (4-8 Hz) peak (severe thalamocortical disruption); 'C' = theta and beta (13-24 Hz) peaks (moderate thalamocortical disruption); or 'D' = alpha (8-13 Hz) and beta peaks (normal thalamocortical function). Acutely, 95% of patients demonstrated 'D' signals in at least one channel but exhibited within-session temporal variability and spatial heterogeneity in the proportion of different channel-level ABCD classifications. By contrast, healthy participants and patients at follow-up consistently demonstrated signals corresponding to intact thalamocortical network function. Patients demonstrated longitudinal improvement in ABCD classifications (p < .05) and ABCD classification distinguished patients with and without command-following in the subacute-to-chronic phase of recovery (p < .01). In patients studied acutely, ABCD classifications improved after the Coma Recovery Scale-Revised arousal facilitation protocol (p < .05) but did not correspond with behavioral level of consciousness. These findings support the use of the ABCD framework to characterize channel-level EEG dynamics and track fluctuations in functional thalamocortical network integrity in spatial detail.

Dataset Information

Feature selection in the human brain: electrophysiological correlates of sensory enhancement and feature integration.

Publications

Feature selection in the human brain: electrophysiological correlates of sensory enhancement and feature integration.

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