Neural correlates of error prediction in a complex motor task

The goal of the study was to quantify error prediction processes via neural correlates in the Electroencephalogram (EEG). Access to such a neural signal will allow to gain insights into functional and temporal aspects of error perception in the course of learning. We focused on the error negativity (Ne) or error-related negativity (ERN) as a candidate index for the prediction processes. We have used a virtual goal-oriented throwing task where participants used a lever to throw a virtual ball displayed on a computer monitor with the goal of hitting a virtual target as often as possible. After one day of practice with 400 trials, participants performed another 400 trials on a second day with EEG measurement. After error trials (i.e., when the ball missed the target), we found a sharp negative deflection in the EEG peaking 250 ms after ball release (mean amplitude: t = -2.5, df = 20, p = 0.02) and another broader negative deflection following the first, reaching from about 300 ms after release until unambiguous visual knowledge of results (KR; hitting or passing by the target; mean amplitude: t = -7.5, df = 20, p < 0.001). According to shape and timing of the two deflections, we assume that the first deflection represents a predictive Ne/ERN (prediction based on efferent commands and proprioceptive feedback) while the second deflection might have arisen from action monitoring

31st Annual Meeting and Associated Programs of the Society for Immunotherapy of Cancer (SITC 2016) : part two

Background The immunological escape of tumors represents one of the main ob- stacles to the treatment of malignancies. The blockade of PD-1 or CTLA-4 receptors represented a milestone in the history of immunotherapy. However, immune checkpoint inhibitors seem to be effective in specific cohorts of patients. It has been proposed that their efficacy relies on the presence of an immunological response. Thus, we hypothesized that disruption of the PD-L1/PD-1 axis would synergize with our oncolytic vaccine platform PeptiCRAd. Methods We used murine B16OVA in vivo tumor models and flow cytometry analysis to investigate the immunological background. Results First, we found that high-burden B16OVA tumors were refractory to combination immunotherapy. However, with a more aggressive schedule, tumors with a lower burden were more susceptible to the combination of PeptiCRAd and PD-L1 blockade. The therapy signifi- cantly increased the median survival of mice (Fig. 7). Interestingly, the reduced growth of contralaterally injected B16F10 cells sug- gested the presence of a long lasting immunological memory also against non-targeted antigens. Concerning the functional state of tumor infiltrating lymphocytes (TILs), we found that all the immune therapies would enhance the percentage of activated (PD-1pos TIM- 3neg) T lymphocytes and reduce the amount of exhausted (PD-1pos TIM-3pos) cells compared to placebo. As expected, we found that PeptiCRAd monotherapy could increase the number of antigen spe- cific CD8+ T cells compared to other treatments. However, only the combination with PD-L1 blockade could significantly increase the ra- tio between activated and exhausted pentamer positive cells (p= 0.0058), suggesting that by disrupting the PD-1/PD-L1 axis we could decrease the amount of dysfunctional antigen specific T cells. We ob- served that the anatomical location deeply influenced the state of CD4+ and CD8+ T lymphocytes. In fact, TIM-3 expression was in- creased by 2 fold on TILs compared to splenic and lymphoid T cells. In the CD8+ compartment, the expression of PD-1 on the surface seemed to be restricted to the tumor micro-environment, while CD4 + T cells had a high expression of PD-1 also in lymphoid organs. Interestingly, we found that the levels of PD-1 were significantly higher on CD8+ T cells than on CD4+ T cells into the tumor micro- environment (p < 0.0001). Conclusions In conclusion, we demonstrated that the efficacy of immune check- point inhibitors might be strongly enhanced by their combination with cancer vaccines. PeptiCRAd was able to increase the number of antigen-specific T cells and PD-L1 blockade prevented their exhaus- tion, resulting in long-lasting immunological memory and increased median survival

Sensitivity to Error Tolerant Solutions in a Redundant Virtual Throwing Task

It is suggested that when learning a redundant goaloriented motor task, people explore and choose error tolerant solutions of the task to reduce result variability. This assumption was tested with a virtual throwing task where the error tolerant solutions were designed such that subjects needed to recurrently adapt to a new tolerant solution in order to achieve high performance. We tested 13 participants who practiced the task over six days. All of them adapted to changes in error tolerant solutions although the absolute number of adaptations as well as the rate of adaptation varied strongly between subjects. Results are discussed with reference to motor noise and the integration of practice trials according to error probability

Neural correlates of error prediction in a complex motor task

The goal of the study was to quantify error prediction processes via neural correlates in the Electroencephalogram. Access to such a neural signal will allow to gain insights into functional and temporal aspects of error perception in the course of learning. We focused on the error negativity (Ne) or error‐related negativity (ERN) as a candidate index for the prediction processes. We have used a virtual goal-oriented throwing task where participants used a lever to throw a virtual ball displayed on a computer monitor with the goal of hitting a virtual target as often as possible. After one day of practice with 400 trials, participants performed another 400 trials on a second day with EEG measurement. After error trials (i.e. when the ball missed the target), we found a sharp negative deflection in the EEG peaking 250 ms after ball release (mean amplitude: t = -2.5, df = 20, p = .02) and another broader negative deflection following the first, reaching from about 300 ms after release until unambiguous visual KR (hitting or passing by the target; mean amplitude: t = -7.5, df = 20, p < .001). According to shape and timing of the two deflections, we assume that the first deflection represents a predictive Ne/ERN (prediction based on efferent commands and proprioceptive feedback) while the second deflection might have arisen from action monitoring

Einsatz von EMedien im wissenschaftlichen Alltag der Generation Y in den Gesundheitsberufen

10. Forschungsforum der Österreichischen FachhochschulenGesundhei