R Cuneus 1.73 R Inferior Temporal Gyrus 0.5 L Caudate 1.66 L Parahippocampal 0.48 R Precentral 1.66 R Hippocampus 0.46 L Precentral 1.55 R Middle Orbitofrontal Gyrus 0.44 R Postcentral 1.54 R Lateral Orbitofrontal 0.44 R Superior Occipital Gyrus 1.52 L Inferior Temporal Gyrus 0.43 L Cuneus 1.44 L Hippocampus 0.4 Table 5.1., continued. Anatomical Region Dipole Density Anatomical Region Dipole Density Ratio L Postcentral 1.42 L Lateral Orbitofrontal Gyrus 0.4 R Superior Parietal 1.27 L Middle Orbitofrontal Gyrus 0.36
L Superior Occipital 1.26 Cerebellum 0.32 L Superior Frontal Gyrus 1.23 Brodmann Area 24 2.73 R Superior Frontal 1.22 Brodmann Area 33 2.71 L Superior Parietal 1.19 Brodmann Area 23 2.61 R Lingual Gyrus 1.14 Brodmann Area 31 2.54 R Inferior Occipital 1.09 Brodmann Area 29 2.05 R Angular Gyrus 1.06 Brodmann Area 3 Primary Somatosensory 1.82 L Lingual Gyrus 1.04 Brodmann Area 4 Primary Motor 1.81 L Middle Occipital Gyrus 1.01 Brodmann Area 30 1.62 L Angular 0.98 Brodmann Area 5 1.59 Table 5.1., continued. Anatomical Region Dipole Density Ratio Anatomical Region Dipole Density Ratio
R Gyrus Rectus 0.91 Brodmann Area 6 Premotor and Supplementary Motor 1.43 L Inferior Occipital 0.9 Brodmann Area 7 Somatosensory Association 1.31 R Middle Frontal Gyrus 0.87 Brodmann Area 18 Secondary visual (V2) 1.24 R Putamen 0.84 Brodmann Area 2 Primary Somatosensory 1.22 L Supramarginal Gyrus 0.83 Brodmann Area 41 Primary and Association Auditory 1.2 L Insular Cortex 0.81 Brodmann Area 17 Primary visual (V1) 1.17 L Superior Temporal Gyrus 0.8 Brodmann Area 27 0.95 L Gyrus Rectus 0.79 Brodmann Area 19 Associative visual (V3) 0.94
Table 5.1., continued. Anatomical Region Dipole Density Ratio Anatomical Region Dipole Density Ratio R Superior Temporal Gyrus 0.73 Brodmann Area 22 Auditory processing 0.92 L Middle Frontal Gyrus 0.73 R Insular Cortex 0.7 L Middle Temporal Gyrus 0.7 R Inferior Frontal Gyrus 0.66 Table Average residual variance (RV) of anatomical regions with significantly low or high RV
(FDR-corrected two-tailed p value < 0.05). Each area is marked as ‘High’ or ‘Low’ in the table as ‘type of significance’ depending on whether the average RV was higher or lower than what would be observed if the distribution of RVs was random. Region Average Residual (%) Type of significance Region Average Residual Variance (%) Type of R Inferior Occipital Gyrus 4.9 Low R Inferior Temporal Gyrus 7.4 High L Inferior Occipital Gyrus 5 Low L Gyrus 7.4 High R Middle Occipital Gyrus Low L Inferior Frontal Gyrus 7.4 High R Superior Occipital Gyrus 5.5 Low R Superior Frontal Gyrus 7.4 High R Cuneus Low R Superior Temporal Gyrus 7.5 High Table continued.
Region Average Residual (%) Type of significance Region Average Residual Variance (%) Type of L Precuneus Low R Gyrus 7.5 High R Lingual Gyrus 5.7 Low L Gyrus 7.5 High L Superior Occipital Gyrus 5.8 Low R Angular Gyrus 7.5 High L Lingual Gyrus 5.8 Low L Gyrus Rectus 7.6 High L Cuneus 6 Low R Middle Frontal Gyrus 7.6 High L Middle Occipital Gyrus 6 Low L Middle Frontal Gyrus 7.6 High 6 Low R Caudate 7.6 High
continued. Anatomical Region (%) Type of significance Region Average Residual Variance (%) Type of L Gyrus Low L Angular Gyrus 7.7 High L Precentral Gyrus 6.4 Low R Gyrus Rectus 7.8 High L Middle Temporal 6.7 High R Insular Cortex 7.8 High R Cingulate Gyrus 6.7 High Brainstem 7.8 High
L Cingulate Gyrus 6.8 High L Middle Orbitofrontal Gyrus 7.8 High L Lateral Gyrus 7 High R Middle Gyrus 7.9 High Table continued. Region (%) Type of significance Region Average Residual Variance (%) Type of L Inferior Temporal 7 High L 8 High R Middle Temporal 7.1 High R Putamen 8.2 High us
Table continued. ERSP Domain Nearby Clusters Anatomical Area(s) Brodmann Area(s) 3 1 L Superior Occipital (0.19) L Cuneus (0.16) L Middle Occipital (0.15) R Cuneus (0.12) R Superior Occipital Gyrus (0.10) L Superior Parietal (0.06) L Lingual Gyrus (0.04) L Precuneus (0.03) L Superior Temporal Gyrus (0.02) R Middle Occipital (0.02) BA 18 (0.33) Secondary visual (V2) BA 19 (0.15) Associative visual (V3) BA 31 (0.13) BA 17 (0.12) Primary visual (V1) BA 7 (0.06) Somatosensory Association
Table MPA performance scores for simulation results with a voxel significance threshold of 0.05 and varying noise levels. Mean MPA Performance Score (std) Cohen’s kappa Ratio (kappa, max possible) Domain Dipole Amplitude Mean Domain Dipole SNR (std) Extra Dipole Noise Amplitude Projected Gaussian std. deviation (mm) 0.82 (0.21) 0.82 (0.63, .78) 0 1 0.2 12 0.85 (0.20) 0.84 (0.62,0.73) 0 1 0.2 14 0.81 (0.19) 0.78 (0.63, 0.8) 0 1 0.2 10 0.93 (0.11) 0.9 (0.5, 0.56) 0.2 0.88 (0.09) 0.2 12 0.93 (0.10) 0.93 (0.47,0.51) 0.2 0.88 (0.09) 0.2 14 0.89 (0.16) 0.84 (0.51,0.61) 0.2 0.88 (0.09) 0.2 10
Based on the Scientific Method [], scientific models should be compared based on their predictive power. An 'EEG model' hence should predict the EEG patterns that will be observed at each brain area associated with an experimental event or state. A function that has a number of EEG activations (from channels or ICs) as its input and outputs a pattern that predicts (estimates) an unseen EEG is an example of an EEG predicative mode. One choice for this function, , for trial data is the average: (1) But there may be functions (models) that offer a better predictive power and hence favored by the Scientific Method. A simple example of such a function is ‘optimal low-pass’: (2) where and . (3) This equation refers to leave-one-out cross-validation in order to find the frequency threshold that maximizes the sum of reduction of variance ratios (ROVs) across trials. Here the ratio is used since the absolute reduction of variance value (the numerator in equation 3) is more sensitive to outlier trials with unusually high amplitudes.
Figure Percent ROV improvement using collaborative averaging compared to regular averaging for different number of trials. Figure Shows how many more trials, compared to using collaborative averaging, are needed to achieve the same level of correlation with the ERP calculated from all 118 trials. Figure Optimal weight for the average of other subjects, obtained by collaborative averaging for different number of trials. Figure Target ERP of the select IC from all trials (gray), the first 30 trials (blue) and collaborative averaging using the first 30 trials of the subject and individually weighted patterns from other subjects. The green rectangle highlights a period where the ERP from 30 trials contains extraneuous peaks that are corrected when using collaborative averaging. Figure Correlations between the average ERP from all (118) trials and ERPs from a subset of trials calculated by regular averaging (black)
Stimulus/Visual/Language, Stimulus/Instruction/Count, Stimulus/Visual/Uniform Color/White, Stimulus/Visual/Achromatic, Stimulus/Visual/Background/Uniform Color/Black Participant answers the question by pressing one of two buttons (here, to indicate a response of ‘1’) with his/her right hand: Response/Button Press, Response/Hand/Right Hand/Index Finger, Response/Count/1 Presentation of visual feedback (‘Correct’ or ‘Incorrect’) cue in training trials: Stimulus/Visual/Language/Word/Noun, Stimulus/Visual/Language/Latin/English, Stimulus/Feedback/Correct, (or /Incorrect) Stimulus/Visual/Uniform Color/White, Stimulus/Visual/Achromatic, Stimulus/Visual/Background/Uniform Color/Black Finally, we specify the paradigm as: Paradigm/Rapid Serial Visual Presentation/Visual Target Detection Paradigm, Paradigm/Oddball discrimination paradigm/Visual oddball paradigm HED Grammar HED tags consist of a series of identifiers separated by the forward slash '/' character. A HED identifier may contain any characters except the characters ‘/’ (forward slash), ’,’ (comma), ‘;’ (semicolon), and ‘”’ (quotes). To use these reserved characters in a HED identifier, the HED identifier may be wrapped in a pair of (“) characters. To use the quote character inside a quoted HED, use ‘\”’ (backslash double-quote).