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Top-left panel: Averaged beta-band (13–30 Hz) power spectral density half-violin plots. During the pre-processing stage, beta-band power magnitude measures from hippocampal contacts were used for both the ‘Go’ and ‘No-go’ conditions as input features. Top-right panel: Clusters were extracted by principal component analysis from all frequency bins within the beta-band power (13–30 Hz) and gray-matter contacts in the hippocampus, the first two principal components were used for cross-validated DA. Bottom panel: <t>Silhouette</t> score box plots from all participants grouped by ‘Combined’ (gray), ‘Go’ (green), and ‘No-go’ (red) trials.
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Top-left panel: Averaged beta-band (13–30 Hz) power spectral density half-violin plots. During the pre-processing stage, beta-band power magnitude measures from hippocampal contacts were used for both the ‘Go’ and ‘No-go’ conditions as input features. Top-right panel: Clusters were extracted by principal component analysis from all frequency bins within the beta-band power (13–30 Hz) and gray-matter contacts in the hippocampus, the first two principal components were used for cross-validated DA. Bottom panel: <t>Silhouette</t> score box plots from all participants grouped by ‘Combined’ (gray), ‘Go’ (green), and ‘No-go’ (red) trials.
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Top-left panel: Averaged beta-band (13–30 Hz) power spectral density half-violin plots. During the pre-processing stage, beta-band power magnitude measures from hippocampal contacts were used for both the ‘Go’ and ‘No-go’ conditions as input features. Top-right panel: Clusters were extracted by principal component analysis from all frequency bins within the beta-band power (13–30 Hz) and gray-matter contacts in the hippocampus, the first two principal components were used for cross-validated DA. Bottom panel: <t>Silhouette</t> score box plots from all participants grouped by ‘Combined’ (gray), ‘Go’ (green), and ‘No-go’ (red) trials.
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Top-left panel: Averaged beta-band (13–30 Hz) power spectral density half-violin plots. During the pre-processing stage, beta-band power magnitude measures from hippocampal contacts were used for both the ‘Go’ and ‘No-go’ conditions as input features. Top-right panel: Clusters were extracted by principal component analysis from all frequency bins within the beta-band power (13–30 Hz) and gray-matter contacts in the hippocampus, the first two principal components were used for cross-validated DA. Bottom panel: Silhouette score box plots from all participants grouped by ‘Combined’ (gray), ‘Go’ (green), and ‘No-go’ (red) trials.

Journal: Journal of Neural Engineering

Article Title: Beta-band power classification of go/no-go arm-reaching responses in the human hippocampus

doi: 10.1088/1741-2552/ad5b19

Figure Lengend Snippet: Top-left panel: Averaged beta-band (13–30 Hz) power spectral density half-violin plots. During the pre-processing stage, beta-band power magnitude measures from hippocampal contacts were used for both the ‘Go’ and ‘No-go’ conditions as input features. Top-right panel: Clusters were extracted by principal component analysis from all frequency bins within the beta-band power (13–30 Hz) and gray-matter contacts in the hippocampus, the first two principal components were used for cross-validated DA. Bottom panel: Silhouette score box plots from all participants grouped by ‘Combined’ (gray), ‘Go’ (green), and ‘No-go’ (red) trials.

Article Snippet: The Silhouette score (calculated using the Matlab function ‘silhouette’) measures how closely a data point resides within its own cluster (cohesion or tightness), as well as how distinct the same data point is from other clusters (separation).

Techniques:

Evaluation of Go and No-Go clusters: Silhouette scores for ‘Go’ and ‘No-go’ task conditions for each participant, detailing mean and median values for each task condition and for both conditions combined. The final two rows display the average and median silhouette scores across all participants for each task condition and for both conditions combined.

Journal: Journal of Neural Engineering

Article Title: Beta-band power classification of go/no-go arm-reaching responses in the human hippocampus

doi: 10.1088/1741-2552/ad5b19

Figure Lengend Snippet: Evaluation of Go and No-Go clusters: Silhouette scores for ‘Go’ and ‘No-go’ task conditions for each participant, detailing mean and median values for each task condition and for both conditions combined. The final two rows display the average and median silhouette scores across all participants for each task condition and for both conditions combined.

Article Snippet: The Silhouette score (calculated using the Matlab function ‘silhouette’) measures how closely a data point resides within its own cluster (cohesion or tightness), as well as how distinct the same data point is from other clusters (separation).

Techniques: