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This paper describes a group-level analysis of 14 subjects with prefrontal cortex (pFC) lesions and 20 healthy controls performing multiple lateralized visuospatial working memory (WM) trials. Using effective brain connectivity measures inferred from directed information (DI) during memory encoding, we first show that DI features can correctly classify 18 control subjects and 11 subjects with pFC lesions, providing an overall accuracy of 85.3%. Second, we show that differential DI, the change in DI during the encoding phase from pretrial, can successfully overcome inter-subject variability and correctly identify the class of all 34 subjects (100% accuracy). These accuracy results are based on two-thirds majority thresholding among all trials. Finally, we use Welch’s t-test to identify the crucial differences in the two classes’ sub-networks responsible for memory encoding. While the inflow of information to the prefrontal region is significant among subjects with pFC lesions, the outflow from the prefrontal to the frontal and central regions is diminished compared to the control subjects. We further identify specific neural pathways that are exclusively activated for each group during the encoding phase.
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Spectral Features Based Decoding of Task Engagement: The Role of Theta and High Gamma Bands in Cognitive Control
This paper analyzes local field potentials (LFP) from 10 human subjects to discover frequency-dependent biomarkers of cognitive conflict. We utilize cortical and sub-cortical LFP recordings from the subjects during a cognitive task known as the Multi-Source Interference Task (MSIT). We decode the task engagement and discover biomarkers that may facilitate closed-loop neuromodulation to enhance cognitive control. First, we show that spectral power features in predefined frequency bands can be used to classify task and non-task segments with a median accuracy of 88.1%. Here the features are first ranked using the Bayes Factor and then used as inputs to subject-specific linear support vector machine classifiers. Second, we show that theta (4–8 Hz) band, and high gamma (65–200 Hz) band oscillations are modulated during the task performance. Third, by isolating time-series from specific brain regions of interest, we observe that a subset of the dorsolateral prefrontal cortex features is sufficient to decode the task states. The paper shows that cognitive control evokes robust neurological signatures, especially in the prefrontal cortex (PFC).
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- Award ID(s):
- 1954749
- PAR ID:
- 10313637
- Date Published:
- Journal Name:
- Proc. 2021 IEEE Engineering and Medicine in Biology (EMBC) Conference
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1109/EMBC46164.2021.9630923
