The Experimental Scenario.

<div><p> <b>a,</b>The participant in the Cave is seated behind a desk that contains the electric shock machine.</p> <p>The experimenter is seated to the participant's right.</p> <p>The virtual character (Learner) appears to be on the other side of a partition and seen through a window.</p> <p>The cue word and four possible associated words are displayed with the correct associated word shown in capitals.</p> <p>After the participant reads out the five words the Learner answers with one of the four possible answers.</p> <p>If the answer is incorrect the participant turns up a voltage dial on the shock machine <b>b,</b> and then presses a button to administer the shock.</p> <p>For the HC condition the window area where the Learner is displayed is covered, and the Learner's answer appears in text underneath the cue word and possible answers.</p></div

Skin conductance waveform average around the shock times.

<div><p> <b>a,</b> Event triggered average of 20 s segments of skin conductance waveform, the events being the times when the button that gave an electric shock to the virtual character was pressed.</p> <p>The grand mean was calculated over each shock and each person and the result for the VC is shown here (n = 439*).</p> <p>Each waveform was adjusted by subtracting the corresponding individual's mean SCL during the baseline period.</p> <p>For each participant a number of pseudo random shock times distributed over the learning period, equal to the actual number for that person, were generated – also with the adjustment for the individual's mean baseline SCL.</p> <p>An average curve was formed like this 500 times, and these are shown as the many overlapping thinner curves.</p> <p>A histogram of the values of these pseudo random curves at the 0 time point is shown inset.</p> <p> <b>b,</b> shows the event triggered means of skin conductance waveforms for the VC (black line) and the HC (grey line), but where each segment is translated to start at zero, so that both mean curves start at the same point for comparison purposes.</p> <p>The additional curves shown are 95% normal (non-simultaneous) confidence intervals.</p> <p> ^*The time of one administered shock was lost.</p></div

Significance Levels for differences between the SCLs for the VC and HC by shock number.

<div><p>For each shock the SCL (adjusted by subtracting the mean baseline value) at the time that the shock is administered is found for each of the n = 23 in the VC and n = 11 in the HC.</p> <p>A rank sum test is used to test the hypothesis that these are drawn from the same population.</p> <p>The vertical axis shows the significance level for rejection of the null hypothesis.</p> <p>By examination of the medians of the samples in each case it is clear that for the later shocks the null hypothesis would be rejected in favour of the alternative that the SCL is higher for the VC.</p></div

Times between asking the question and indicating the intention to shock.

<div><p>The vertical axis is the time between the participant finishing reading out the 5 words forming the question and saying “Incorrect” after the Learner did not respond, at questions 28 and 29 (the last two).</p> <p>The horizontal axis labels refer to the question number and the condition VC or HC.</p> <p>The plots are standard box plots, where the box shows the median and interquartile range, and the whiskers extend to 1.5 times the interquartile range.</p> <p>Values outside the whiskers are outliers, the single outlier shown as a cross.</p> <p>At the 28^th question the time difference ranged from 8 s to 78 s with a median of 23 s for the VC (n = 19) and from 4 s to 13 s with a median of 7 s for those in the HC (n = 11).</p> <p>The Wilcoxon rank sum test rejects the hypothesis that the two samples are from the same population with P = 4.4×10⁻⁴.</p> <p>At the time of the 29^th (and last) question the equivalent results are: 5–43 s with a median of 13 s for the VC (n = 16), and 5–14 s with a median of 8 s for the HC (n = 11).</p> <p>Here the difference is significant with P = 0.0175.</p></div

Data_Sheet_1_EEG Biomarkers Related With the Functional State of Stroke Patients.PDF

IntroductionRecent studies explored promising new quantitative methods to analyze electroencephalography (EEG) signals. This paper analyzes the correlation of two EEG parameters, Brain Symmetry Index (BSI) and Laterality Coefficient (LC), with established functional scales for the stroke assessment.MethodsThirty-two healthy subjects and thirty-six stroke patients with upper extremity hemiparesis were recruited for this study. The stroke patients where subdivided in three groups according to the stroke location: Cortical, Subcortical, and Cortical + Subcortical. The participants performed assessment visits to record the EEG in the resting state and perform functional tests using rehabilitation scales. Then, stroke patients performed 25 sessions using a motor-imagery based Brain Computer Interface system (BCI). BSI was calculated with the EEG data in resting state and LC was calculated with the Event-Related Synchronization maps.ResultsThe results of this study demonstrated significant differences in the BSI between the healthy group and Subcortical group (P = 0.001), and also between the healthy and Cortical+Subcortical group (P = 0.019). No significant differences were found between the healthy group and the Cortical group (P = 0.505). Furthermore, the BSI analysis in the healthy group based on gender showed statistical differences (P = 0.027). In the stroke group, the correlation between the BSI and the functional state of the upper extremity assessed by Fugl-Meyer Assessment (FMA) was also significant, ρ = −0.430 and P = 0.046. The correlation between the BSI and the FMA-Lower extremity was not significant (ρ = −0.063, P = 0.852). Similarly, the LC calculated in the alpha band has significative correlation with FMA of upper extremity (ρ = −0.623 and P ConclusionThe quantitative EEG tools used here may help support our understanding of stroke and how the brain changes during rehabilitation therapy. These tools can help identify changes in EEG biomarkers and parameters during therapy that might lead to improved therapy methods and functional prognoses.</p

Movement of rats and humans (a) Rat A with (b) corresponding participant, (c) Rat B with (d) corresponding participant.

<p>Axes are in metres, and all movements are measured in the rat arena. Hence the human movements are those of the slaved robot.</p

Screenshot of the virtual environment.

<p>Three of the four posters are visible in the image as well as the two avatars representing both the participant and the rat.</p

Scatter diagram of the proportion of time that the rat was within a radius of 20 cm from the arena centre by the number of rat points over all participants, for both rats.

<p>The number of rat points is the number of collisions between rat and robot that occurred away from the correct poster for the human to obtain a point. The Pearson correlation is significant for each rat separately (Rat A: r = 0.70, P<0.04; Rat B: r = 0.82, P<0.008).</p

Waveform of distance between Rat A and the robot device for an arbitrary participant.

<p>Waveform of distance between Rat A and the robot device for an arbitrary participant.</p

Distance between rat and robot by rat position.

<p>The vertical axis is the distance between the rat and robot corresponding to the position of the rat on the horizontal plane representing the rat arena. (a) Representing all 9 participants for rat A over trial 1 where the participants knew that the avatar represented a rat (b) The same participants for rat A over trial 2 where participants thought that the rat represented a remote human. (c) All 9 participants for rat B over trial 1. (d) The same participants over trial 2 for rat B.</p