A robust brain network for sustained attention from adolescence to adulthood that predicts later substance use.

Substance use, including cigarettes and cannabis, is associated with poorer sustained attention in late adolescence and early adulthood. Previous studies were predominantly cross-sectional or under-powered and could not indicate if impairment in sustained attention was a consequence of substance-use or a marker of the inclination to engage in such behaviour. This study explored the relationship between sustained attention and substance use across a longitudinal span from ages 14 to 23 in over 1,000 participants. Behaviours and brain connectivity associated with diminished sustained attention at age 14 predicted subsequent increases in cannabis and cigarette smoking, establishing sustained attention as a robust biomarker for vulnerability to substance use. Individual differences in network strength relevant to sustained attention were preserved across developmental stages and sustained attention networks generalized to participants in an external dataset. In summary, brain networks of sustained attention are robust, consistent, and able to predict aspects of later substance use.

White matter fibre density in the brain's inhibitory control network is associated with falling in low activity older adults.

Recent research has indicated that the relationship between age-related cognitive decline and falling may be mediated by the individual's capacity to quickly cancel or inhibit a motor response. This longitudinal investigation demonstrates that higher white matter fibre density in the motor inhibition network paired with low physical activity was associated with falling in elderly participants. We measured the density of white matter fibre tracts connecting key nodes in the inhibitory control network in a large sample (n = 414) of older adults. We modelled their self-reported frequency of falling over a 4-year period with white matter fibre density in pathways corresponding to the direct and hyperdirect cortical-subcortical loops implicated in the inhibitory control network. Only connectivity between right inferior frontal gyrus and right subthalamic nucleus was associated with falling as measured cross-sectionally. The connectivity was not, however, predictive of future falling when measured 2 and 4 years later. Higher white matter fibre density was associated with falling, but only in combination with low levels of physical activity. No such relationship existed for selected control brain regions that are not implicated in the inhibitory control network. Albeit statistically robust, the direction of this effect was counterintuitive (more dense connectivity associated with falling) and warrants further longitudinal investigation into whether white matter fibre density changes over time in a manner correlated with falling, and mediated by physical activity.

Structural brain signatures of frailty, defined as accumulation of self-reported health deficits in older adults.

Background: Frailty in older adults has been associated with reduced brain health. However, structural brain signatures of frailty remain understudied. Our aims were: (1) Explore associations between a frailty index (FI) and brain structure on magnetic resonance imaging (MRI). (2) Identify the most important FI features driving the associations. Methods: We designed a cross-sectional observational study from a population-based study (The Irish Longitudinal Study on Aging: TILDA). Participants aged ≥50 years who underwent the wave 3 MRI sub-study were included. We measured cortex, basal ganglia, and each of the Desikan-Killiany regional volumes. Age-and sex-adjusted correlations were performed with a 32-item self-reported FI that included conditions commonly tested for frailty in research and clinical settings. A graph theory analysis of the network composed by each FI item and cortex volume was performed. White matter fiber integrity was quantified using diffusion tensor imaging (DTI). Results: In 523 participants (mean age 69, 49% men), lower cortex and thalamic volumes were independently associated with higher FI. Sensory and functional difficulties, diabetes, polypharmacy, knee pain, and self-reported health were the main FI associations with cortex volume. In the network analysis, cortex volume had a modest influence within the frailty network. Regionally, higher FI was significantly associated with lower volumes in both orbitofrontal and temporal cortices. DTI analyses revealed inverse associations between the FI and the integrity of some association bundles. Conclusion: The FI used had a recognizable but subtle structural brain signature in this sample. Only some FI deficits were directly associated with cortex volume, suggesting scope for developing FIs that include metrics more specifically related with brain health in future aging neuroscience studies.

Self-regulation of the brain's right frontal Beta rhythm using a brain-computer interface.

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 noninvasive 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), either up or down, over the right inferior frontal cortex. Training to downregulate Beta was more effective than training to upregulate Beta. 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 to up or downregulate 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 in healthy individuals. Whether this form of neurofeedback training could serve as a useful therapeutic target for disorders with dysfunctional inhibitory control as their basis remains to be tested in a context where performance is abnormally poor and neural dynamics are different.

A method to assess response inhibition during a balance recovery step.

BACKGROUND: 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. RESEARCH QUESTION: Can we apply the stop signal task to measure response inhibition in a balance recovery task? METHODS: 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. RESULTS: 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). SIGNIFICANCE: 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.

White matter abnormalities in the amputation variant of body integrity dysphoria.

"Body integrity dysphoria" (BID) is a severe condition affecting nonpsychotic individuals. In the amputation variant of BID, a limb may be experienced as not being part of the body, despite normal anatomical development and intact sensorimotor functions. We previously demonstrated altered brain structural (gray matter) and functional connectivity in 16 men with BID with a long-lasting and exclusive desire for left leg amputation. Here, we aimed to identify, in the same sample, altered patterns of white matter structural connectivity. Fractional anisotropy (FA), derived from diffusion tensor imaging data, was considered as a measure of structural connectivity. Results showed reduced structural connectivity of: (i) the right superior parietal lobule (rSPL) with the right cuneus, with the superior occipital and with the posterior cingulate gyri, (ii) the pars orbitalis of the right middle frontal gyrus (rMFGOrb) with the putamen, and (iii) the left middle temporal gyrus (lMTG) with the pars triangularis of the left inferior frontal gyrus. Increased connectivity was found between the right paracentral lobule (rPLC) and the right caudate nucleus. By using a complementary method of investigation, we confirmed and extended previous results from the same sample of individuals with BID, showing structural alterations between areas tuned to the processing of the sensorimotor representations of the affected leg (rPCL), and to higher-order components of bodily representation such as the body image (rSPL) and visual processing. Alongside this network for bodily awareness, other networks such as the limbic (rMFGOrb) and the mirror (lMTG) systems showed alterations in structural connectivity. These findings consolidate current understanding of the neural correlates of the amputation variant of BID, which might in turn guide diagnostics and rehabilitative treatments.

Mental individuation of imagined finger movements can be achieved using TMS-based neurofeedback.

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.

Could Brain-Computer Interface Be a New Therapeutic Approach for Body Integrity Dysphoria?

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.

Challenges and Opportunities for the Future of Brain-Computer Interface in Neurorehabilitation.

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.

Relationship between Speed of Response Inhibition and Ability to Suppress a Step in Midlife and Older Adults.

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.

Volume of ß-Bursts, But Not Their Rate, Predicts Successful Response Inhibition.

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

Neuronal response variability as a product of divisive normalization; neurobiological implications at a macroscale level.

The occurrence of neuronal spikes recorded directly from sensory cortex is highly irregular within and between presentations of an invariant stimulus. The traditional solution has been to average responses across many trials. However, with this approach, response variability is downplayed as noise, so it is assumed that statistically controlling it will reveal the brain's true response to a stimulus. A mounting body of evidence suggests that this approach is inadequate. For example, experiments show that response variability itself varies as a function of stimulus dimensions like contrast and state dimensions like attention. In other words, response variability has structure, is therefore potentially informative and should be incorporated into models which try to explain neural encoding. In this article we provide commentary on a recently published study by Coen-Cagli and Solomon that incorporates spike variability in a quantitative model, by explaining it as a function of divisive normalization. We consider the potential role of neural oscillations in this process as a potential bridge between the current microscale findings and response variability at the mesoscale/macroscale level.

Muscle-specific modulation of indirect inputs to primary motor cortex during action observation.

Single-pulse transcranial magnetic stimulation (spTMS) studies report that movement observation facilitates corticospinal excitability in primary motor cortex (M1) in a muscle-specific manner. However, motor evoked potentials (MEPs) elicited by spTMS are known to reflect the summation of several descending volleys in corticospinal neurons which are evoked via mono- and polysynaptic inputs (so-called indirect waves or I-waves). It is unclear which of these components contribute to the muscle-specific modulation of M1 during action observation. The interactions between different I-waves are reflected in the facilitatory peaks elicited with a short-intracortical facilitation (SICF) protocol when two pulses are sent to M1 at precise intervals (i.e., 1.3, 2.5 or 4.1 ms). Here, we explored the modulation of early and late SICF peaks during action observation by measuring highly specific MEP amplitude changes measured in two muscles (index, FDI and little finger, ADM) while participants observed two different actions (precision and whole-hand grip). Our results demonstrate that both early (1.3 ms) and late (2.5 and 4.1 ms) SICF peaks are modulated in the context of movement observation. However, only the second peak (ISI 2.5 ms) was significantly associated with the muscle-specific modulation of corticospinal excitability as measured with spTMS. This late SICF peak is believed to reflect the activity cortico-cortical pathways involved in the facilitation of muscle-specific representations in M1. Thus, our findings suggest that movement observation leads to widespread activation of different neural circuits within M1, including those mediating cortico-cortical communication.

Uncertainty in contextual and kinematic cues jointly modulates motor resonance in primary motor cortex.

Contextual information accompanying others' actions modulates "motor resonance", i.e., neural activity within motor areas that is elicited by movement observation. One possibility is that we weigh and combine such information in a Bayesian manner according to their relative uncertainty. Therefore, contextual information becomes particularly useful when others' actions are difficult to discriminate. It is unclear, however, whether this uncertainty modulates the neural activity in primary motor cortex (M1) during movement observation. Here, we applied single-pulse transcranial magnetic stimulation (TMS) while subjects watched different grasping actions. We operationalized motor resonance as grip-specific modulation of corticomotor excitability measured in the index (FDI) versus the little finger abductor (ADM). We experimentally modulated either the availability of kinematic information ( experiment 1) or the reliability of contextual cues ( experiment 2). Our results indicate that even in the absence of movement kinematics, reliable contextual information is enough to trigger significant muscle-specific corticomotor excitability changes in M1, which are strongest when both kinematics and contextual information are available. These findings suggest that bottom-up mechanisms that activate motor representations as a function of the observed kinematics and top-down mechanisms that activate motor representations associated with arbitrary cues converge in M1. NEW & NOTEWORTHY Our study reveals new neurophysiological insights in support of the Bayesian account of action observation by showing that "motor resonance", i.e., neural activity evoked by observing others' actions, incorporates the uncertainty related to both contextual (prior beliefs) and kinematic (sensory evidence) cues. Notably, we show that muscle-specific modulation of M1 is strongest when context and movement kinematics are available, and it can be elicited even in the absence of movement kinematics.

Neural activity related to volitional regulation of cortical excitability.

To date there exists no reliable method to non-invasively upregulate or downregulate the state of the resting human 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.

Author Correction: Deep sleep maintains learning efficiency of the human brain.

This corrects the article DOI: 10.1038/ncomms15405.

Neural circuitry underlying sustained attention in healthy adolescents and in ADHD symptomatology.

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.

Repetitive reaching training combined with transcranial Random Noise Stimulation in stroke survivors with chronic and severe arm paresis is feasible: a pilot, triple-blind, randomised case series.

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.

Deep sleep maintains learning efficiency of the human brain.

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.

Structural and Functional Cortical Connectivity Mediating Cross Education of Motor Function.

Cross-education (CE) is the process whereby training with one limb leads to subsequent improvement in performance by the opposite untrained limb. We used multimodal neuroimaging in humans to investigate the mediating neural mechanisms by relating quantitative estimates of functional and structural cortical connectivity to individual levels of interlimb transfer. Resting-state (rs)-fMRI and diffusion weighted imaging (DWI) scans were undertaken before unilateral ballistic wrist flexion training. The rs-fMRI sequence was repeated immediately afterward. The increase in performance of the untrained limb was 83.6% of that observed for the trained limb and significantly greater than that of a control group who undertook no training. Functional connectivity in the resting motor network between right and left supplementary motor areas (SMA) was elevated after training. These changes were not, however, correlated with individual levels of transfer. Analysis of the DWI data using constrained spherical deconvolution-based tractography indicated that fractional anisotropy and apparent fiber density in tracts connecting bilateral SMA were negatively correlated with and predictive of transfer. The findings suggest that interhemispheric interactions between bilateral SMA play an instrumental role in CE and that the structural integrity of the connecting white matter pathways influences the level of transfer.SIGNIFICANCE STATEMENT Strength or skill training with one limb also brings about improvements in the performance of the opposite, untrained limb. This phenomenon, termed cross-education (CE), has obvious potential for the rehabilitation of functional capacity that has been lost through brain insult or musculoskeletal injury. The neural mechanisms that give rise to CE are, however, poorly understood. We used a combination of neuroimaging methods to investigate the pathways in the human brain that mediate CE. We determined that the supplementary motor area (SMA) plays an important role in the interlimb transfer of performance gains and demonstrate that the quality of the white matter fibers connecting right and left SMA predicts the benefit that an individual derives from CE.