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Swissa, Y., Hacohen, S., Friedman, J., & Frenkel-Toledo, S. (2022). Sensorimotor performance after high-definition transcranial direct current stimulation over the primary somatosensory or motor cortices in men versus women. Sci Rep, 12, 11117.
Abstract: The primary somatosensory (S1) cortex is a central structure in motor performance. However, transcranial direct current stimulation (tDCS) research aimed at improving motor performance usually targets the primary motor cortex (M1). Recently, sex was found to mediate tDCS response. Thus, we investigated whether tDCS with an anodal electrode placed over S1 improves motor performance and sensation perception in men versus women. Forty-five participants randomly received 15-min high-definition tDCS (HD-tDCS) at 1 mA to S1, M1, or sham stimulation. Reaching performance was tested before and immediately following stimulation. Two-point orientation discrimination (TPOD) of fingers and proprioception of a reaching movement were also tested. Although motor performance did not differ between groups, reaching reaction time improved in the M1 group men. Reaching movement time and endpoint error improved in women and men, respectively. Correct trials percentage for TPOD task was higher in the S1 compared to the M1 group in the posttest and improved only in the S1 group. Reaching movement time for the proprioception task improved, overall, and endpoint error did not change. Despite the reciprocal connections between S1 and M1, effects of active tDCS over S1 and M1 may specifically influence sensation perception and motor performance, respectively. Also, sex may mediate effects of HD-tDCS on motor performance.
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Thorpe, A., Friedman, J., Evans, S., Nesbitt, K., & Eidels, A. (2022). Mouse Movement Trajectories as an Indicator of Cognitive Workload. International Journal of Human-Computer Interaction, 38(15), 1464–1479.
Abstract: Assessing the cognitive impact of user interfaces is a shared focus of human-computer interaction researchers and cognitive scientists. Methods of cognitive assessment based on data derived from the system itself, rather than external apparatus, have the potential to be applied in a range of scenarios. The current study applied methods of analyzing kinematics to mouse movements in a computer-based task, alongside the detection response task, a standard workload measure. Sixty-five participants completed a task in which stationary stimuli were tar;geted using a mouse, with a within-subjects factor of task workload based on the number of targets to be hovered over with the mouse (one/two), and a between-subjects factor based on whether both targets (exhaustive) or just one target (minimum-time) needed to be hovered over to complete a trial when two targets were presented. Mouse movement onset times were slower and mouse movement trajectories exhibited more submovements when two targets were presented, than when one target was presented. Responses to the detection response task were also slower in this condition, indicating higher cognitive workload. However, these differences were only found for participants in the exhaustive condition, suggesting those in the minimum-time condition were not affected by the presence of the second target. Mouse movement trajectory results agreed with other measures of workload and task performance. Our findings suggest this analysis can be applied to workload assessments in real-world scenarios.
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Mimouni-Bloch, A., Shaklai, S., Levin, M., Ingber, M., Karolitsky, T., Grunbaum, S., et al. (2023). Developmental and acquired brain injury have opposite effects on finger coordination in children. Front. Hum. Neurosci., 17, 1083304.
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Frenkel-Toledo, S., Yamanaka, J., Friedman, J., Feldman, A. G., & Levin, M. F. (2019). Referent control of anticipatory grip force during reaching in stroke: an experimental and modeling study. Exp Brain Res, 237(7), 1655–1672.
Abstract: To evaluate normal and impaired control of anticipatory grip force (GF) modulation, we compared GF production during horizontal arm movements in healthy and post-stroke subjects, and, based on a physiologically feasible dynamic model, determined referent control variables underlying the GF-arm motion coordination in each group. 63% of 13 healthy and 48% of 13 stroke subjects produced low sustained initial force (< 10 N) and increased GF prior to arm movement. Movement-related GF increases were higher during fast compared to self-paced arm extension movements only in the healthy group. Differences in the patterns of anticipatory GF increases before the arm movement onset between groups occurred during fast extension arm movement only. In the stroke group, longer delays between the onset of GF change and elbow motion were related to clinical upper limb deficits. Simulations showed that GFs could emerge from the difference between the actual and the referent hand aperture (Ra) specified by the CNS. Similarly, arm movement could result from changes in the referent elbow position (Re) and could be affected by the co-activation (C) command. A subgroup of stroke subjects, who increased GF before arm movement, could specify different patterns of the referent variables while reproducing the healthy typical pattern of GF-arm coordination. Stroke subjects, who increased GF after arm movement onset, also used different referent strategies than controls. Thus, altered anticipatory GF behavior in stroke subjects may be explained by deficits in referent control.
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Salzer, Y., & Friedman, J. (2020). Reaching trajectories unravel modality-dependent temporal dynamics of the automatic process in the Simon task: a model-based approach. Psychol Res, 84(6), 1700–1713.
Abstract: The Simon effect represents a phenomenon in which the location of the stimuli affects the speed and accuracy of the response, despite being irrelevant for the task demands. This is believed to be due to an automatic activation of a response corresponding to the location of the stimuli, which conflicts with the controlled decision process based on relevant stimuli features. Previously, differences in the nature of the Simon effect (i.e., the pattern of change of the effect across the distribution of response times) between visual and somatosensory stimuli were reported. We hypothesize that the temporal dynamics of visual and somatosensory automatic and controlled processes vary, thus driving the reported behavioral differences. While most studies have used response times to study the underlying mechanisms involved, in this study we had participants reach out to touch the targets and recorded their arm movements using a motion capture system. Importantly, the participants started their movements before a final decision was made. In this way, we could analyze the movements to gain insights into the competition between the automatic and controlled processes. We used this technique to describe the results in terms of a model assuming automatic activation due to location-based evidence, followed by inhibition. We found that for the somatosensory Simon effect, the decay of the automatic process is significantly slower than for the visual Simon effect, suggesting quantitative differences in this automatic process between the visual and somatosensory modalities.
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