02846nas a2200241   4500008004100000245008500041210006900126260001200195490000600207520209000213653000802303653002502311653001902336653001302355653003002368100002002398700001702418700001902435700002002454700002402474700001702498856008902515       2020                        eng d00aBCI-based sensorimotor rhythm training can affect individuated finger movements 0 aBCIbased sensorimotor rhythm training can affect individuated fi  c06/20200 v73 aBrain-computer interface (BCI) technology can restore communication and control to people who are severely paralyzed. BCI technology might also be able to enhance rehabilitation of motor function. We have previously shown that pre-movement sensorimotor rhythm (SMR) amplitude affects reaction time and performance on a joystick-based cursor movement task. The present study explores in adults without motor impairment the possibility that pre-movement SMR amplitude affects performance of individuated finger movements. In Phase 1, 8 individuals performed a finger flexion task that was monitored by an exoskeleton. During a 1-sec preparatory period, two colored targets on a video monitor cued flexion of the index finger, middle finger, both fingers, or neither finger; sudden color change then triggered the movement (or non-movement). SMR features (i.e. EEG amplitudes in specific frequency bands at specific scalp locations) in the pre-movement EEG that correlated with movement versus no movement were identified. In Phase 2, the participants learned to increase or decrease these SMR features to control a two-target BCI task. Finally, in Phase 3, they were asked to increase or decrease the SMR features to initiate the finger flexion task of Phase 1 and the impact on finger flexion performance was assessed. After BCI training, pre-movement SMR feature amplitude affected performance in a subset of individuals: lower amplitude was associated with shorter movement onset. In a subset of individuals, the beneficial effect on performance of lower SMR amplitude was greater when both fingers were flexed than when one was flexed and the other remained extended; thus, the impact of SMR amplitude modulation depended on the specificity of the subsequent motor task. These results indicate that BCI-based training of SMR activity in the pre-movement preparatory period can affect finger movements in a subset of individuals. They encourage studies that integrate such training into rehabilitation protocols and examine its capacity to enhance restoration of useful hand function.10aBCI10amovement preparation10aRehabilitation10aRobotics10asensorimotor beta rhythms1 aMcFarland, D.J.1 aNorman, S.L.1 aSarnacki, W.A.1 aWolbrecht, E.T.1 aReinkensmeyer, D.J.1 aWolpaw, J.R.  uhttps://www.tandfonline.com/doi/abs/10.1080/2326263X.2020.1763060?journalCode=tbci2003989nas a2200193   4500008004100000245005800041210005600099260001200155490000800167520340900175653000803584653000803592653002903600653003003629100001703659700002703676700001703703856007503720       2020                        eng d00aBrain-computer interfaces: Definitions and principles0 aBraincomputer interfaces Definitions and principles  c03/20200 v1683 aThroughout life, the central nervous system (CNS) interacts with the world and with the body by activating muscles and excreting hormones. In contrast, brain-computer interfaces (BCIs) quantify CNS activity and translate it into new artificial outputs that replace, restore, enhance, supplement, or improve the natural CNS outputs. BCIs thereby modify the interactions between the CNS and the environment. Unlike the natural CNS outputs that come from spinal and brainstem motoneurons, BCI outputs come from brain signals that represent activity in other CNS areas, such as the sensorimotor cortex. If BCIs are to be useful for important communication and control tasks in real life, the CNS must control these brain signals nearly as reliably and accurately as it controls spinal motoneurons. To do this, they might, for example, need to incorporate software that mimics the function of the subcortical and spinal mechanisms that participate in normal movement control. The realization of high reliability and accuracy is perhaps the most difficult and critical challenge now facing BCI research and development.

The ongoing adaptive modifications that maintain effective natural CNS outputs take place primarily in the CNS. The adaptive modifications that maintain effective BCI outputs can also take place in the BCI. This means that the BCI operation depends on the effective collaboration of two adaptive controllers, the CNS and the BCI. Realization of this second adaptive controller, the BCI, and management of its interactions with concurrent adaptations in the CNS comprise another complex and critical challenge for BCI development.

BCIs can use different kinds of brain signals recorded in different ways from different brain areas. Decisions about which signals recorded in which ways from which brain areas should be selected for which applications are empirical questions that can only be properly answered by experiments.

BCIs, like other communication and control technologies, often face artifacts that contaminate or imitate their chosen signals. Noninvasive BCIs (e.g., EEG- or fNIRS-based) need to take special care to avoid interpreting nonbrain signals (e.g., cranial EMG) as brain signals. This typically requires comprehensive topographical and spectral evaluations.

In theory, the outputs of BCIs can select a goal or control a process. In the future, the most effective BCIs will probably be those that combine goal selection and process control so as to distribute control between the BCI and the application in a fashion suited to the current action. Through such distribution, BCIs may most effectively imitate natural CNS operation.

The primary measure of BCI development is the extent to which BCI systems benefit people with neuromuscular disorders. Thus, BCI clinical evaluation, validation, and dissemination is a key step. It is at the same time a complex and difficult process that depends on multidisciplinary collaboration and management of the demanding requirements of clinical studies.

Twenty-five years ago, BCI research was an esoteric endeavor pursued in only a few isolated laboratories. It is now a steadily growing field that engages many hundreds of scientists, engineers, and clinicians throughout the world in an increasingly interconnected community that is addressing the key issues and pursuing the high potential of BCI technology.10aBCI10aBMI10abrain-computer interface10abrain–machine interface1 aWolpaw, J.R.1 aMillán, José, del R.1 aRamsey, N.F.  uhttps://www.sciencedirect.com/science/article/pii/B978044463934900002001263nas a2200253   4500008004100000245006000041210005900101260001200160490000800172520057900180653000800759653000800767653001300775653002500788653001900813100001400832700001500846700001500861700001500876700001700891700001200908700001700920856007200937       2020                        eng d00aOperant Condition of the Flexor Carpi Radialis H-reflex0 aOperant Condition of the Flexor Carpi Radialis Hreflex  c12/20200 v1013 aOperant conditioning of the largely monosynaptic H-reflex is a targeted and non-invasive therapeutic intervention for people with motor dysfunction after spinal cord injury and possibly stroke.1,2,3 It can complement other therapies and has no known adverse side effects. To date, H-reflex operant conditioning has focused on the leg. Here, we extend it to the arm by asking participants to either increase or decrease the flexor carpi radialis (FCR) H-reflex. In addition, we examine concurrent changes in brain activity by recording electroencephalographic activity (EEG).10aBCI10aFCR10aH-Reflex10aoperant conditioning10aRehabilitation1 aNorton, J1 aVaughan, T1 aGemoets, D1 aHeckman, S1 aToliou, S.D.1 aCarp, J1 aWolpaw, J.R.  uhttps://www.archives-pmr.org/article/S0003-9993(20)31081-9/abstract