02625nas a2200421 4500008004100000022001400041245010100055210006900156260000900225300001100234490000600245520128700251100002101538700002101559700002801580700002201608700002001630700002101650700002301671700001901694700002501713700002201738700002201760700002401782700002101806700002201827700002101849700002701870700001801897700002901915700002001944700002501964700002501989700002402014700002202038700002002060856012302080 2022 eng d a2326-263X00aWorkshops of the Eighth International Brain-Computer Interface Meeting: BCIs: The Next Frontier.0 aWorkshops of the Eighth International BrainComputer Interface Me c2022 a69-1010 v93 a

The Eighth International Brain-Computer Interface (BCI) Meeting was held June 7-9th, 2021 in a virtual format. The conference continued the BCI Meeting series' interactive nature with 21 workshops covering topics in BCI (also called brain-machine interface) research. As in the past, workshops covered the breadth of topics in BCI. Some workshops provided detailed examinations of specific methods, hardware, or processes. Others focused on specific BCI applications or user groups. Several workshops continued consensus building efforts designed to create BCI standards and increase the ease of comparisons between studies and the potential for meta-analysis and large multi-site clinical trials. Ethical and translational considerations were both the primary topic for some workshops or an important secondary consideration for others. The range of BCI applications continues to expand, with more workshops focusing on approaches that can extend beyond the needs of those with physical impairments. This paper summarizes each workshop, provides background information and references for further study, presents an overview of the discussion topics, and describes the conclusion, challenges, or initiatives that resulted from the interactions and discussion at the workshop.

1 aHuggins, Jane, E1 aKrusienski, Dean1 aVansteensel, Mariska, J1 aValeriani, Davide1 aThelen, Antonia1 aStavisky, Sergey1 aNorton, James, J S1 aNijholt, Anton1 aMüller-Putz, Gernot1 aKosmyna, Nataliya1 aKorczowski, Louis1 aKapeller, Christoph1 aHerff, Christian1 aHalder, Sebastian1 aGuger, Christoph1 aGrosse-Wentrup, Moritz1 aGaunt, Robert1 aDusang, Aliceson, Nicole1 aClisson, Pierre1 aChavarriaga, Ricardo1 aAnderson, Charles, W1 aAllison, Brendan, Z1 aAksenova, Tetiana1 aAarnoutse, Erik uhttps://www.neurotechcenter.org/publications/2022/workshops-eighth-international-brain-computer-interface-meeting-bcis04066nas a2200277 4500008004100000022001400041245007100055210006900126260001200195300001100207490000700218520327200225653001003497653002003507653002703527653001103554653001103565653001603576653000903592653004103601653002803642100002703670700001803697700002503715856004803740 2011 eng d a1095-957200aCausal influence of gamma oscillations on the sensorimotor rhythm.0 aCausal influence of gamma oscillations on the sensorimotor rhyth c05/2011 a837-420 v563 a

Gamma oscillations of the electromagnetic field of the brain are known to be involved in a variety of cognitive processes, and are believed to be fundamental for information processing within the brain. While gamma oscillations have been shown to be correlated with brain rhythms at different frequencies, to date no empirical evidence has been presented that supports a causal influence of gamma oscillations on other brain rhythms. In this work, we study the relation of gamma oscillations and the sensorimotor rhythm (SMR) in healthy human subjects using electroencephalography. We first demonstrate that modulation of the SMR, induced by motor imagery of either the left or right hand, is positively correlated with the power of frontal and occipital gamma oscillations, and negatively correlated with the power of centro-parietal gamma oscillations. We then demonstrate that the most simple causal structure, capable of explaining the observed correlation of gamma oscillations and the SMR, entails a causal influence of gamma oscillations on the SMR. This finding supports the fundamental role attributed to gamma oscillations for information processing within the brain, and is of particular importance for brain-computer interfaces (BCIs). As modulation of the SMR is typically used in BCIs to infer a subject's intention, our findings entail that gamma oscillations have a causal influence on a subject's capability to utilize a BCI for means of communication.

10aAdult10aCerebral Cortex10aElectroencephalography10aFemale10aHumans10aImagination10aMale10aSignal Processing, Computer-Assisted10aUser-Computer Interface1 aGrosse-Wentrup, Moritz1 aSchölkopf, B1 aHill, Jeremy, Jeremy uhttp://www.ncbi.nlm.nih.gov/pubmed/2045162602734nas a2200349 4500008004100000022001400041245009000055210006900145260001200214300001100226490000600237520175300243653001001996653002902006653003702035653002802072653001102100653001102111653001602122653000902138653001302147653001302160653001002173653002802183100002302211700001402234700002502248700001802273700001802291700002702309856004802336 2011 eng d a1741-255200aClosing the sensorimotor loop: haptic feedback facilitates decoding of motor imagery.0 aClosing the sensorimotor loop haptic feedback facilitates decodi c06/2011 a0360050 v83 a

The combination of brain-computer interfaces (BCIs) with robot-assisted physical therapy constitutes a promising approach to neurorehabilitation of patients with severe hemiparetic syndromes caused by cerebrovascular brain damage (e.g. stroke) and other neurological conditions. In such a scenario, a key aspect is how to reestablish the disrupted sensorimotor feedback loop. However, to date it is an open question how artificially closing the sensorimotor feedback loop influences the decoding performance of a BCI. In this paper, we answer this issue by studying six healthy subjects and two stroke patients. We present empirical evidence that haptic feedback, provided by a seven degrees of freedom robotic arm, facilitates online decoding of arm movement intention. The results support the feasibility of future rehabilitative treatments based on the combination of robot-assisted physical therapy with BCIs.

10aBrain10aEvoked Potentials, Motor10aEvoked Potentials, Somatosensory10aFeedback, Physiological10aFemale10aHumans10aImagination10aMale10aMovement10aRobotics10aTouch10aUser-Computer Interface1 aGomez-Rodriguez, M1 aPeters, J1 aHill, Jeremy, Jeremy1 aSchölkopf, B1 aGharabaghi, A1 aGrosse-Wentrup, Moritz uhttp://www.ncbi.nlm.nih.gov/pubmed/21474878