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Stop-signal reaction time (SSRT), the time needed to cancel an already-initiated motor response, quantifies individual differences in inhibitory control. Electrophysiological correlates of SSRT have primarily focused on late event-related potential (ERP) components over midline scalp regions from successfully inhibited stop trials. SSRT is robustly associated with the P300, there is mixed evidence for N200 involvement, and there is little information on the role of early ERP components. Here, machine learning was first used to interrogate ERPs during both successful and failed stop trials from 64 scalp electrodes at 4 ms resolution (n = 148). The most predictive model included data from both successful and failed stop trials, with a cross-validated Pearson's r of 0.32 between measured and predicted SSRT, significantly higher than null models. From successful stop trials, spatio-temporal features overlapping the N200 in right frontal areas and the P300 in frontocentral areas predicted SSRT, as did early ERP activity (200 ms). As a demonstration of the reproducibility of these findings, the application of this model to a separate dataset of 97 participants was also significant (r = 0.29). These results show that ERPs during failed stops are relevant to SSRT, and that both early and late ERP activity contribute to individual differences in SSRT. Notably, the right lateralized N200, which predicted SSRT here, is not often observed in neurotypical adults. Both the ascending slope and peak of the P300 component predicted SSRT. These results were replicable, both within the training sample and when applied to ERPs from a separate dataset.

In humans, impaired response inhibition is characteristic of a wide range of psychiatric diseases and of normal aging. It is hypothesised that the right inferior frontal cortex plays a key role by inhibiting the motor cortex via the basal ganglia. The electroencephalography-derived beta rhythm (15-29 Hz) is thought to reflect communication within this network, with increased right frontal beta power often observed prior to successful response inhibition. Recent literature suggests that averaging spectral power obscures the transient, burst-like nature of beta activity. There is evidence that the rate of beta bursts following a Stop signal is higher when a motor response is successfully inhibited. However, other characteristics of beta burst events, and their topographical properties, have not yet been examined. Here, we used a large human (male and female) electroencephalography Stop Signal Task dataset (n=218) to examine averaged normalised beta power, beta burst rate and beta burst ‘volume’ (which we defined as burst duration x frequency span x amplitude). We first sought to optimise the beta burst detection method. In order to find predictors across the whole scalp, and with high temporal precision, we then used machine learning to (1) classify successful vs. failed stopping and to (2) predict individual Stop Signal Reaction Time. Beta burst volume was significantly more predictive of successful and fast stopping than beta burst rate and normalised beta power. The classification model generalised to an external dataset (n=201). We suggest beta burst volume is a sensitive and reliable measure for investigation of human response inhibition. SIGNIFICANCE STATEMENT The electroencephalography-derived beta rhythm (15-29 Hz) is associated with the ability to inhibit ongoing actions. In this study, we sought to identify the specific characteristics of beta activity that contribute to successful and fast inhibition. In order to search for the most relevant features of beta activity – across the whole scalp and with high temporal precision – we employed machine learning on two large datasets. Spatial and temporal features of beta burst ‘volume’ (duration x frequency span x amplitude) predicted response inhibition outcomes in our data significantly better than beta burst rate and normalised beta power. These findings suggest that multidimensional measures of beta bursts, such as burst volume, can add to our understanding of human response inhibition.

Correlations between falls and individual differences in inhibitory control, suggest the ability to suppress automatic, but unwanted, action is important in fall prevention. Response inhibition has been a topic of considerable interest in the cognitive neuroscience community for many decades, bringing a wealth of techniques that could potentially inform assessment of reactive balance. For example, the stop signal task is a popular method to quantify inhibitory control ability.Can we apply the stop signal task to measure response inhibition in a balance recovery task?Twenty healthy, young adults completed a novel reactive balance test that required occasional suppression of a balance recovery step. Participants were released from a supported lean ('Go' cue) requiring them to quickly step forward to regain balance. On some trials, a tone ('Stop' cue) instructed participants to suppress a step and relax into a harness. Step trials were more frequent (80%) than stop trials (20%) to bias a rapid stepping response. The stop tone was presented at various delays following cable release, to manipulate task difficulty (i.e., longer delays make step suppression difficult). Individual differences in inhibitory control were determined using lift off times from force plates, and by contrasting muscle activation in failed compared to successful stop trials.Most participants were able to successfully suppress a balance recovery step on occasion, allowing for accurate estimation of individual differences in inhibitory control. The successful suppression of a balance recovery step was more likely in the group (n = 10) where shorter stop signal delays were used (i.e., the task was easier).While balance assessments often stress reflexive action, there is a need for methods that evaluate response inhibition. The present study leveraged a well-established cognitive test of inhibitory control to develop a method to quantify stopping ability in a reactive balance context.

Neural oscillations, or brain rhythms, fluctuate in a manner reflecting ongoing behavior. Whether these fluctuations are instrumental or epiphenomenal to the behavior remains elusive. Attempts to experimentally manipulate neural oscillations exogenously using non-invasive brain stimulation have shown some promise, but difficulty with tailoring stimulation parameters to individuals has hindered progress in this field. We demonstrate here using electroencephalography (EEG) neurofeedback in a brain-computer interface that human participants (n=44) learned over multiple sessions across a 6-day period to self-regulate their Beta rhythm (13-20 Hz) over the right inferior frontal cortex (rIFC). The modulation was evident only during neurofeedback task performance but did not lead to offline alteration of Beta rhythm characteristics at rest, nor to changes in subsequent cognitive behavior. Likewise, a control group (n=38) who underwent training of the Alpha rhythm (8-12 Hz) did not exhibit behavioral changes. Although the right frontal Beta rhythm has been repeatedly implicated as a key component of the brain’s inhibitory control system, the present data suggest that its manipulation offline prior to cognitive task performance does not result in behavioral change. Thus, this form of neurofeedback training of the tonic Beta rhythm would not serve as a useful therapeutic target for disorders with dysfunctional inhibitory control as their basis.

Patients suffering from body integrity dysphoria (BID) desire to become disabled, arising from a mismatch between the desired body and the physical body. We focus here on the most common variant, characterized by the desire for amputation of a healthy limb. In most reported cases, amputation of the rejected limb entirely alleviates the distress of the condition and engenders substantial improvement in quality of life. Since BID can lead to life-long suffering, it is essential to identify an effective form of treatment that causes the least amount of alteration to the person’s anatomical structure and functionality. Treatment methods involving medications, psychotherapy, and vestibular stimulation have proven largely ineffective. In this hypothesis article, we briefly discuss the characteristics, etiology, and current treatment options available for BID before highlighting the need for new, theory driven approaches. Drawing on recent findings relating to functional and structural brain correlates of BID, we introduce the idea of brain–computer interface (BCI)/neurofeedback approaches to target altered patterns of brain activity, promote re-ownership of the limb, and/or attenuate stress and negativity associated with the altered body representation.

Brain-computer interfaces (BCIs) provide a unique technological solution to circumvent the damaged motor system. For neurorehabilitation, the BCI can be used to translate neural signals associated with movement intentions into tangible feedback for the patient, when they are unable to generate functional movement themselves. Clinical interest in BCI is growing rapidly, as it would facilitate rehabilitation to commence earlier following brain damage and provides options for patients who are unable to partake in traditional physical therapy. However, substantial challenges with existing BCI implementations have prevented its widespread adoption. Recent advances in knowledge and technology provide opportunities to facilitate a change, provided that researchers and clinicians using BCI agree on standardisation of guidelines for protocols and shared efforts to uncover mechanisms. We propose that addressing the speed and effectiveness of learning BCI control are priorities for the field, which may be improved by multimodal or multi-stage approaches harnessing more sensitive neuroimaging technologies in the early learning stages, before transitioning to more practical, mobile implementations. Clarification of the neural mechanisms that give rise to improvement in motor function is an essential next step towards justifying clinical use of BCI. In particular, quantifying the unknown contribution of non-motor mechanisms to motor recovery calls for more stringent control conditions in experimental work. Here we provide a contemporary viewpoint on the factors impeding the scalability of BCI. Further, we provide a future outlook for optimal design of the technology to best exploit its unique potential, and best practices for research and reporting of findings.

In young adults, performance on a test of response inhibition was recently found to be correlated with performance on a reactive balance test where automated stepping responses must occasionally be inhibited. The present study aimed to determine whether this relationship holds true in older adults, wherein response inhibition is typically deficient and the control of postural equilibrium presents a greater challenge. Ten participants (50+ years of age) completed a seated cognitive test (stop signal task) followed by a reactive balance test. Reactive balance was assessed using a modified lean-and-release system where participants were required to step to regain balance following perturbation, or suppress a step if an obstacle was present. The stop signal task is a standardized cognitive test that provides a measure of the speed of response inhibition called the Stop Signal Reaction Time (SSRT). Muscle responses in the legs were compared between conditions where a step was allowed or blocked to quantify response inhibition of the step. The SSRT was significantly related to leg muscle suppression during balance recovery in the stance leg. Thus, participants that were better at inhibiting their responses in the stop signal task were also better at inhibiting an unwanted leg response in favor of grasping a supportive handle. The relationship between a seated cognitive test using finger responses and leg muscle suppression when a step was blocked indicates a context-independent, generalized capacity for response inhibition. This suggests that a simple cognitive test such as the stop signal task could be used clinically to predict an individual’s capacity for adapting balance reactions and fall risk. The present results provide support for future studies, with larger samples, to verify this relationship between stop signal reaction time and leg response during balance recovery.

Neurofeedback (NF) in combination with motor imagery (MI) can be used for training individuals to volitionally modulate sensorimotor activity without producing overt movements. However, until now, NF methods were of limited utility for mentally training specific hand and finger actions. Here we employed a novel transcranial magnetic stimulation (TMS) based protocol to probe and detect MI-induced motor activity patterns in the primary motor cortex (M1) with the aim to reinforce selective facilitation of single finger representations. We showed that TMS-NF training but not MI training with uninformative feedback enabled participants to selectively upregulate corticomotor excitability of one finger, while simultaneously downregulating excitability of other finger representations within the same hand. Successful finger individuation during MI was accompanied by strong desynchronization of sensorimotor brain rhythms, particularly in the beta band, as measured by electroencephalography. Additionally, informative TMS-NF promoted more dissociable EEG activation patterns underlying single finger MI, when compared to MI of the control group where no such feedback was provided. Our findings suggest that selective TMS-NF is a new approach for acquiring the ability of finger individuation even if no overt movements are performed. This might offer new treatment modality for rehabilitation after stroke or spinal cord injury., NeuroImage, 242, ISSN:1053-8119, ISSN:1095-9572

Moment-to-moment reaction time variability on tasks of attention, often quantified by intra-individual response variability (IRV), provides a good indication of the degree to which an individual is vulnerable to lapses in sustained attention. Increased IRV is a hallmark of several disorders of attention, including Attention-Deficit/Hyperactivity Disorder (ADHD). Here, task-based fMRI was used to provide the first examination of how average brain activation and functional connectivity patterns in adolescents are related to individual differences in sustained attention as measured by IRV. We computed IRV in a large sample of adolescents (n = 758) across 'Go' trials of a Stop Signal Task (SST). A data-driven, multi-step analysis approach was used to identify networks associated with low IRV (i.e., good sustained attention) and high IRV (i.e., poorer sustained attention). Low IRV was associated with greater functional segregation (i.e., stronger negative connectivity) amongst an array of brain networks, particularly between cerebellum and motor, cerebellum and prefrontal, and occipital and motor networks. In contrast, high IRV was associated with stronger positive connectivity within the motor network bilaterally and between motor and parietal, prefrontal, and limbic networks. Consistent with these observations, a separate sample of adolescents exhibiting elevated ADHD symptoms had increased fMRI activation and stronger positive connectivity within the same motor network denoting poorer sustained attention, compared to a matched asymptomatic control sample. With respect to the functional connectivity signature of low IRV, there were no statistically significant differences in networks denoting good sustained attention between the ADHD symptom group and asymptomatic control group. We propose that sustained attentional processes are facilitated by an array of neural networks working together, and provide an empirical account of how the functional role of the cerebellum extends to cognition in adolescents. This work highlights the involvement of motor cortex in the integrity of sustained attention, and suggests that atypically strong connectivity within motor networks characterizes poor attentional capacity in both typically developing and ADHD symptomatic adolescents.

Brain oscillations have been related to many aspects of human behavior. To understand a potential causal relationship, it is of great importance to develop methods for modulating ongoing neural activity. It has been shown that external rhythmic stimulation leads to an oscillatory brain response that follows the temporal structure of the presented stimulus and is assumed to reflect the synchronization of ongoing neural oscillations with the stimulation rhythm. This interaction between individual brain activity and so called steady-state evoked potentials (SSEPs) is the fundamental requirement of neural entrainment. Here, we investigate whether neural responses to rhythmic vibrotactile stimulation, measured with EEG, are dependent on ongoing individual brain oscillations, and therefore reflect entrained oscillatory activity. For this, we measured phase synchronization in response to rhythmic stimulation across various frequencies in the alpha and beta band. Three different stimulation intensities were applied for each frequency relative to the individual sensory threshold. We found that a higher stimulation intensity, compared to lower intensities, resulted in a more pronounced phase synchronization with the stimulation signal. Moreover, EEG responses to low stimulation frequencies closer to individual beta peak frequencies revealed a higher degree of entrainment, compared to stimulation conditions with frequencies that were more distant to endogenous oscillations. Our findings provide evidence that the efficacy of vibrotactile rhythmic beta stimulation to evoke a SSEPs is dependent on ongoing brain oscillations.

Background Response inhibition involves suppressing automatic, but unwanted action, which allows for behavioral flexibility. This capacity could theoretically contribute to fall prevention, especially in the cluttered environments we face daily. Although much has been learned from cognitive psychology regarding response inhibition, it is unclear if such findings translate to the intensified challenge of coordinating balance recovery reactions. Research question Is the ability to stop a prepotent response preserved when comparing performance on a standard test of response inhibition versus a reactive balance test where compensatory steps must be occasionally suppressed? Methods Twelve young adults completed a stop signal task and reactive balance test separately. The stop signal task evaluates an individual’s ability to quickly suppress a visually-cued button press upon hearing a ‘stop’ tone, and provides a measure of the speed of response inhibition called the Stop Signal Reaction Time (SSRT). Reactive balance was tested by releasing participants from a supported lean position, in situations where the environment was changed during visual occlusion. Upon receiving vision, participants were required to either step to regain balance following cable release (70% of trials), or suppress a step if an obstacle was present (30% of trials). The early muscle response of the stepping leg was compared between the ‘step blocked’ and ‘step allowed’ trials to quantify step suppression. Results SSRT was correlated with muscle activation of the stepping leg when sufficient time was provided to view the response environment (400 ms). Individuals with faster SSRTs exhibited comparably less leg muscle activity when a step was blocked, signifying a superior ability to inhibit an unwanted step. Significance Performance on a standardized test of response inhibition is related to performance on a reactive balance test where automated stepping responses must occasionally be inhibited. This highlights a generalizable neural mechanism for stopping action across different behavioral contexts.

Somatosensory information from the limbs reaches the contralateral Primary Sensory Cortex (S1) with a delay of 23 ms for finger, and 40 ms for leg (somatosensory N20/N40). Upon arrival of this input in the cortex, motor evoked potentials (MEPs) elicited by Transcranial Magnetic Stimulation (TMS) are momentarily inhibited. This phenomenon is called ‘short latency afferent inhibition (SAI)’ and can be used as a tool for investigating sensorimotor interactions in the brain. We used SAI to investigate the process of sensorimotor integration in the hemisphere ipsilateral to the stimulated limb. We hypothesized that ipsilateral SAI would occur with a delay following the onset of contralateral SAI, to allow for transcallosal conduction of the signal. We electrically stimulated the limb either contralateral or ipsilateral to the hemisphere receiving TMS, using a range of different interstimulus intervals (ISI). We tested the First Dorsal Interosseous (FDI) muscle in the hand, and Tibialis Anterior (TA) in the lower leg, in three separate experiments. Ipsilateral SAI was elicited in the upper limb (FDI) at all ISIs that were greater than N20+18 ms (all p < .05) but never at any earlier timepoint. No ipsilateral SAI was detected in the lower limb (TA) at any of the tested ISIs. The delayed onset timing of ipsilateral SAI suggests that transcallosal communication mediates this inhibitory process for the upper limb. The complete absence of ipsilateral SAI in the lower limb warrants consideration of the potential limb-specific differences in demands for bilateral sensorimotor integration., Neuroscience, 333, ISSN:0306-4522, ISSN:1873-7544

Highlights • Stroke patients are capable of learning to use Brain-Computer interface based on TMS. • Sub-acute stroke patients used TMS neurofeedback to increase MEP amplitude. • TMS neurofeedback increased corticospinal excitability in paretic muscles., Upper limb weakness following a stroke affects 80% of survivors and is a key factor in preventing their return to independence. State-of-the art approaches to rehabilitation often require that the patient can generate some activity in the paretic limb, which is not possible for many patients in the early period following stroke. Approaches that enable more patients to engage with upper limb therapy earlier are urgently needed. Motor imagery has shown promise as a potential means to maintain activity in the brain’s motor network, when the patient is incapable of generating functional movement. However, as imagery is a hidden mental process, it is impossible for individuals to gauge what impact this is having upon their neural activity. Here we used a novel brain-computer interface (BCI) approach allowing patients to gain an insight into the effect of motor imagery on their brain-muscle pathways, in real-time. Seven patients 2–26 weeks post stroke were provided with neurofeedback (NF) of their corticospinal excitability measured by the size of motor evoked potentials (MEP) in response to transcranial magnetic stimulation (TMS). The aim was to train patients to use motor imagery to increase the size of MEPs, using the BCI with a computer game displaying neurofeedback. Patients training finger muscles learned to elevate MEP amplitudes above their resting baseline values for the first dorsal interosseous (FDI) and abductor digiti minimi (ADM) muscles. By day 3 for ADM and day 4 for FDI, MEP amplitudes were sustained above baseline in all three NF blocks. Here we have described the first clinical implementation of TMS NF in a population of sub-acute stroke patients. The results show that in the context of severe upper limb paralysis, patients are capable of using neurofeedback to elevate corticospinal excitability in the affected muscles. This may provide a new training modality for early intervention following stroke.

eLife, 7, ISSN:2050-084X

To date there exists no reliable method to non-invasively upregulate or downregulate the state of the resting motor system over a large dynamic range. Here we show that an operant conditioning paradigm which provides neurofeedback of the size of motor evoked potentials (MEPs) in response to transcranial magnetic stimulation (TMS), enables participants to self-modulate their own brain state. Following training, participants were able to robustly increase (by 83.8%) and decrease (by 30.6%) their MEP amplitudes. This volitional up-versus down-regulation of corticomotor excitability caused an increase of late-cortical disinhibition (LCD), a TMS derived read-out of presynaptic GABAB disinhibition, which was accompanied by an increase of gamma and a decrease of alpha oscillations in the trained hemisphere. This approach paves the way for future investigations into how altered brain state influences motor neurophysiology and recovery of function in a neurorehabilitation context.

It is hypothesized that deep sleep is essential for restoring the brain’s capacity to learn efficiently, especially in regions heavily activated during the day. However, causal evidence in humans has been lacking due to the inability to sleep deprive one target area while keeping the natural sleep pattern intact. Here we introduce a novel approach to focally perturb deep sleep in motor cortex, and investigate the consequences on behavioural and neurophysiological markers of neuroplasticity arising from dedicated motor practice. We show that the capacity to undergo neuroplastic changes is reduced by wakefulness but restored during unperturbed sleep. This restorative process is markedly attenuated when slow waves are selectively perturbed in motor cortex, demonstrating that deep sleep is a requirement for maintaining sustainable learning efficiency., Nature Communications, 8, ISSN:2041-1723

The organisational and architectural configuration of white matter pathways connecting brain regions has ramifications for all facets of the human condition, including manifestations of incipient neurodegeneration. Although diffusion tensor imaging (DTI) has been used extensively to visualise white matter connectivity, due to the widespread presence of crossing fibres, the lateral projections of the corpus callosum are not normally detected using this methodology. Detailed knowledge of the transcallosal connectivity of the human cortical motor network has, therefore, remained elusive. We employed constrained spherical deconvolution (CSD) tractography—an approach that is much less susceptible to the influence of crossing fibres, in order to derive complete in vivo characterizations of white matter pathways connecting specific motor cortical regions to their counterparts and other loci in the opposite hemisphere. The revealed patterns of connectivity closely resemble those derived from anatomical tracing in primates. It was established that dorsal premotor cortex (PMd) and supplementary motor area (SMA) have extensive interhemispheric connectivity—exhibiting both dense homologous projections, and widespread structural relations with every other region in the contralateral motor network. Through this in vivo portrayal, the importance of non-primary motor regions for interhemispheric communication is emphasised. Additionally, distinct connectivity profiles were detected for the anterior and posterior subdivisions of primary motor cortex. The present findings provide a comprehensive representation of transcallosal white matter projections in humans, and have the potential to inform the development of models and hypotheses relating structural and functional brain connectivity., Brain Structure and Function, 222 (3), ISSN:1863-2661, ISSN:1863-2653

Background Therapy that combines repetitive training with non-invasive brain stimulation is a potential avenue to enhance upper limb recovery after stroke. This study aimed to investigate the feasibility of transcranial Random Noise Stimulation (tRNS), timed to coincide with the generation of voluntary motor commands, during reaching training. Methods A triple-blind pilot RCT was completed. Four stroke survivors with chronic (6-months to 5-years) and severe arm paresis, not taking any medications that had the potential to alter cortical excitability, and no contraindications to tRNS or MRI were recruited. Participants were randomly allocated to 12 sessions of reaching training over 4-weeks with active or sham tRNS delivered over the lesioned hemisphere motor representation. tRNS was triggered to coincide with a voluntary movement attempt, ceasing after 5-s. At this point, peripheral nerve stimulation enabled full range reaching. To determine feasibility, we considered adverse events, training outcomes, clinical outcomes, corticospinal tract (CST) structural integrity, and reflections on training through in-depth interviews from each individual case. Results Two participants received active and two sham tRNS. There were no adverse events. All training sessions were completed, repetitive practice performed and clinically relevant improvements across motor outcomes demonstrated. The amount of improvement varied across individuals and appeared to be independent of group allocation and CST integrity. Conclusion Reaching training that includes tRNS timed to coincide with generation of voluntary motor commands is feasible. Clinical improvements were possible even in the most severely affected individuals as evidenced by CST integrity. Trial registration This study was registered on the Australian and New Zealand Clinical Trials Registry (ANZCTR) http://www.ANZCTR.org.au/ACTRN12614000952640.aspx. Registration date 4 September 2014, first participant date 9 September 2014.

Thirty years ago, the first magnetic device capable of stimulating the human brain without discomfort through the intact skull was unveiled in Sheffield, England (Barker et al. in Lancet 1:1106-1107, 1985). Since that time, transcranial magnetic stimulation (TMS) has become the tool of choice for many scientists investigating human motor control and learning. In light of the fact that there are limits to the information that can be provided by any experimental technique, we first make the case that the necessarily restricted explanatory scope of the TMS technique-and the motor-evoked potentials to which it gives rise, is not yet reflected adequately in the research literature. We also argue that this inattention, coupled with the pervasive adoption of TMS as an investigative tool, may be restricting the elaboration of knowledge concerning the neural processes that mediate human motor learning. In order to make these points, we use as an exemplar the study of cross-education-the interlimb transfer of functional capacity.

Thirty years ago, the first magnetic device capable of stimulating the human brain without discomfort through the intact skull was unveiled in Sheffield, England (Barker et al. in Lancet 1:1106–1107, 1985). Since that time, transcranial magnetic stimulation (TMS) has become the tool of choice for many scientists investigating human motor control and learning. In light of the fact that there are limits to the information that can be provided by any experimental technique, we first make the case that the necessarily restricted explanatory scope of the TMS technique—and the motor-evoked potentials to which it gives rise, is not yet reflected adequately in the research literature. We also argue that this inattention, coupled with the pervasive adoption of TMS as an investigative tool, may be restricting the elaboration of knowledge concerning the neural processes that mediate human motor learning. In order to make these points, we use as an exemplar the study of cross-education—the interlimb transfer of functional capacity.

The effect of vision on the excitability of corticospinal projections to the flexor carpi radialis (FCR) and extensor carpi radialis (ECR) muscles of right human forearm was investigated before and during discrete movement of the opposite limb. An external force opposed the initial phase of the movement (wrist flexion) and assisted the reverse phase, so that recruitment of the wrist extensors was minimized. Three conditions were used as follows: viewing the inactive right limb (Vision), viewing the mirror image of the moving left limb (Mirror), and with vision of the right limb occluded (No Vision). Transcranial magnetic stimulation was delivered to the left motor cortex: before, at the onset of, or during the left limb movement to obtain motor evoked potentials (MEPs) in the muscles of the right forearm. At and following movement onset, MEPs obtained in the right FCR were smaller in the Vision condition than in the Mirror and No Vision conditions. A distinct pattern of variation was obtained for the ECR. In all conditions, MEPs in this muscle were elevated upon or following movement of the opposite limb. An additional analysis of ipsilateral silent periods indicated that interhemispheric inhibition plays a role in mediating these effects. Activity-dependent changes in corticospinal output to a resting limb during discrete actions of the opposite limb are thus directly contingent upon where one looks. Furthermore, the extent to which vision exerts an influence upon projections to specific muscles varies in accordance with the functional contribution of their homologs to the intended action.

Nature Communications 8: Article number: 15405 (2017); Published online 22 May 2017; Updated 25 May 2018 The originally published version of this Article contained errors in Figure 4. In panels c and d, the labeling of the light and dark blue lines was inverted. These errors have now been corrected in both the PDF and HTML versions of the Article.

Cross education is the process whereby training of one limb gives rise to enhancements in the performance of the opposite, untrained limb. Despite interest in this phenomenon having been sustained for more than a century, a comprehensive explanation of the mediating neural mechanisms remains elusive. With new evidence emerging that cross education may have therapeutic utility, the need to provide a principled evidential basis upon which to design interventions becomes ever more pressing. Generally, mechanistic accounts of cross education align with one of two explanatory frameworks. Models of the ‘cross activation’ variety encapsulate the observation that unilateral execution of a movement task gives rise to bilateral increases in corticospinal excitability. The related conjecture is that such distributed activity, when present during unilateral practice, leads to simultaneous adaptations in neural circuits that project to the muscles of the untrained limb, thus facilitating subsequent performance of the task. Alternatively, ‘bilateral access’ models entail that motor engrams formed during unilateral practise, may subsequently be utilised bilaterally – that is, by the neural circuitry that constitutes the control centres for movements of both limbs. At present there is a paucity of direct evidence that allows the corresponding neural processes to be delineated, or their relative contributions in different task contexts to be ascertained. In the current review we seek to synthesise and assimilate the fragmentary information that is available, including consideration of knowledge that has emerged as a result of technological advances in structural and functional brain imaging. An emphasis upon task dependency is maintained throughout, the conviction being that the neural mechanisms that mediate cross education may only be understood in this context.