Autonomy support encourages use of more-affected arm post-stroke.

BACKGROUND: Autonomy support, which involves providing individuals the ability to control their own behavior, is associated with improved motor control and learning in various populations in clinical and non-clinical settings. This study aimed to investigate whether autonomy support combined with an information technology (IT) device facilitated success in using the more-affected arm during training in individuals with stroke. Consequently, we examined whether increased success influenced the use of the more-affected arm in mild to moderate subacute to chronic stroke survivors. METHODS: Twenty-six participants with stroke were assigned to the autonomy support or control groups. Over a 5-week period, training and test sessions were conducted using the Individualized Motivation Enhancement System (IMES), a device developed specifically for this study. In the autonomy support group, participants were able to adjust the task difficulty parameter, which controlled the time limit for reaching targets. The control group did not receive this option. The evaluation of the more-affected arm's use, performance, and impairment was conducted through clinical tests and the IMES. These data were then analyzed using mixed-effect models. RESULTS: In the IMES test, both groups showed a significant improvement in performance (p < 0.0001) after the training period, without any significant intergroup differences (p > 0.05). However only the autonomy support group demonstrated a significant increase in the use of the more-affected arm following the training (p < 0.001). Additionally, during the training period, the autonomy support group showed a significant increase in successful experiences with using the more-affected arm (p < 0.0001), while the control group did not exhibit the same level of improvement (p > 0.05). Also, in the autonomy support group, the increase in the use of the more-affected arm was associated with the increase in the successful experience significantly (p = 0.007). CONCLUSIONS: Combining autonomy support with an IT device is a practical approach for enhancing performance and promoting the use of the more-affected upper extremity post-stroke. Autonomy support facilitates the successful use of the more-affected arm, thereby increasing awareness of the training goal of maximizing its use. TRIAL REGISTRATION: The study was registered retrospectively with the Clinical Research Information Service (KCT0008117; January 13, 2023; https://cris.nih.go.kr/cris/search/detailSearch.do/23875 ).

Effort, success, and side of lesion determine arm choice in individuals with chronic stroke.

In neurotypical individuals, arm choice in reaching movements depends on expected biomechanical effort, expected success, and a handedness bias. Following a stroke, does arm choice change to account for the decreased motor performance, or does it follow a preinjury habitual preference pattern? Participants with mild-to-moderate chronic stroke who were right-handed before stroke performed reaching movements in both spontaneous and forced-choice blocks, under no-time, medium-time, and fast-time constraint conditions designed to modulate reaching success. Mixed-effects logistic regression models of arm choice revealed that expected effort predicted choices. However, expected success only strongly predicted choice in left-hemiparetic individuals. In addition, reaction times decreased in left-hemiparetic individuals between the no-time and the fast-time constraint conditions but showed no changes in right-hemiparetic individuals. Finally, arm choice in the no-time constraint condition correlated with a clinical measure of spontaneous arm use for right-, but not for left-hemiparetic individuals. Our results are consistent with the view that right-hemiparetic individuals show a habitual pattern of arm choice for reaching movements relatively independent of failures. In contrast, left-hemiparetic individuals appear to choose their paretic left arm more optimally: that is, if a movement with the paretic arm is predicted to be not successful in the upcoming movement, the nonparetic right arm is chosen instead.NEW & NOTEWORTHY Although we are seldom aware of it, we constantly make decisions to use one arm or the other in daily activities. Here, we studied whether these decisions change following stroke. Our results show that effort, success, and side of lesion determine arm choice in a reaching task: whereas left-paretic individuals modified their arm choice in response to failures in reaching the target, right-paretic individuals showed a pattern of choice independent of failures.

The effects of cerebral amyloidopathy on regional glucose metabolism in older adults with depression and mild cognitive impairment while performing memory tasks.

Co-occurring depression and mild cognitive impairment (MCI) in older adults are important because they have a high risk of conversion to dementia. In the present study, task-related F-18 fluorodeoxyglucose positron emission tomography (FDG-PET) was used to analyse older adults with concomitant depression and MCI. We recruited 20 older adults with simultaneous depression and MCI and 10 older adults with normal cognition (NC). The Verbal Paired Associates test and digit span test were used for the task-related FDG-PET. The 20 older adults with depression and MCI were classified into two groups based on the F-18 florbetaben PET results: depressed MCI patients with (LLD-MCI-A[+]; n = 11) and without amyloid accumulation (LLD-MCI-A[-]; n = 9). Reduced regional cerebral glucose metabolism (rCMglc) in the left superior frontal region was observed in the LLD-MCI-A(-) group compared with the NC group. Analyses of the NC and LLD-MCI-A(+) groups showed significantly decreased rCMglc in the right inferior parietal and left middle frontal regions in the LLD-MCI-A(+) group. rCMglc in the left precuneus was lower in the LLD-MCI-A(+) group than in the LLD-MCI-A(-) group. Significant correlations between the rCMglc in the right inferior parietal/left precuneus regions and memory task scores were observed based on correlation analyses of NC and LLD-MCI-A(+) groups. The findings in the present study indicate the presence of amyloid accumulation influences glucose metabolism in depressed elderly subjects with MCI while performing cognitive tasks. Task-related FDG-PET examinations may help differentiate MCI associated with depression from comorbid depression in patients with prodromal Alzheimer's disease.

Towards simulations of long-term behavior of neural networks: Modeling synaptic plasticity of connections within and between human brain regions.

Simulations of neural networks can be used to study the direct effect of internal or external changes on brain dynamics. However, some changes are not immediate but occur on the timescale of weeks, months, or years. Examples include effects of strokes, surgical tissue removal, or traumatic brain injury but also gradual changes during brain development. Simulating network activity over a long time, even for a small number of nodes, is a computational challenge. Here, we model a coupled network of human brain regions with a modified Wilson-Cowan model representing dynamics for each region and with synaptic plasticity adjusting connection weights within and between regions. Using strategies ranging from different models for plasticity, vectorization and a different differential equation solver setup, we achieved one second runtime for one second biological time.

Diffusion tensor imaging reveals abnormal brain networks in elderly subjects with subjective cognitive deficits.

PURPOSE: Some elders with subjective cognitive deficits (SCD) develop prodromal phase of dementia over time; however, little is known about how they differ from those with normal cognition (NC). Thus, we aim to distinguish the differences in the brain network of elders with SCD and NC. METHODS: Multiple diffusion-weighted images (DWI) and T1-weighted images were obtained from 18 subjects with NC and 26 subjects with SCD. Using network-based statistics (NBS) analysis, we extracted abnormal brain subnetworks and localized abnormal brain connectivity. We also ran correlation analysis to compare the affected regions and the results of the neurocognitive assessments. RESULTS: Altered subnetworks were found in the superior parietal gyrus, angular gyrus, precuneus, posterior cingulum, putamen, precentral gyrus, postcentral gyrus, and paracentral lobule. They were also associated with scores on the word list recall, word list recognition, and Boston naming test. CONCLUSIONS: Elders with SCD had distinctive brain network alterations when compared with those of elders with NC. The results are also in line with the previously identified characteristics of mild cognitive impairment (MCI) and of Alzheimer's disease (AD) in a milder form. We speculate that it may be possible to predict AD progression early in the SCD stage using NBS analysis.

Predicting Surgery Targets in Temporal Lobe Epilepsy through Structural Connectome Based Simulations.

Temporal lobe epilepsy (TLE) is a prevalent neurological disorder resulting in disruptive seizures. In the case of drug resistant epilepsy resective surgery is often considered. This is a procedure hampered by unpredictable success rates, with many patients continuing to have seizures even after surgery. In this study we apply a computational model of epilepsy to patient specific structural connectivity derived from diffusion tensor imaging (DTI) of 22 individuals with left TLE and 39 healthy controls. We validate the model by examining patient-control differences in simulated seizure onset time and network location. We then investigate the potential of the model for surgery prediction by performing in silico surgical resections, removing nodes from patient networks and comparing seizure likelihood post-surgery to pre-surgery simulations. We find that, first, patients tend to transit from non-epileptic to epileptic states more often than controls in the model. Second, regions in the left hemisphere (particularly within temporal and subcortical regions) that are known to be involved in TLE are the most frequent starting points for seizures in patients in the model. In addition, our analysis also implicates regions in the contralateral and frontal locations which may play a role in seizure spreading or surgery resistance. Finally, the model predicts that patient-specific surgery (resection areas chosen on an individual, model-prompted, basis and not following a predefined procedure) may lead to better outcomes than the currently used routine clinical procedure. Taken together this work provides a first step towards patient specific computational modelling of epilepsy surgery in order to inform treatment strategies in individuals.

Preferential detachment during human brain development: age- and sex-specific structural connectivity in diffusion tensor imaging (DTI) data.

Human brain maturation is characterized by the prolonged development of structural and functional properties of large-scale networks that extends into adulthood. However, it is not clearly understood which features change and which remain stable over time. Here, we examined structural connectivity based on diffusion tensor imaging (DTI) in 121 participants between 4 and 40 years of age. DTI data were analyzed for small-world parameters, modularity, and the number of fiber tracts at the level of streamlines. First, our findings showed that the number of fiber tracts, small-world topology, and modular organization remained largely stable despite a substantial overall decrease in the number of streamlines with age. Second, this decrease mainly affected fiber tracts that had a large number of streamlines, were short, within modules and within hemispheres; such connections were affected significantly more often than would be expected given their number of occurrences in the network. Third, streamline loss occurred earlier in females than in males. In summary, our findings suggest that core properties of structural brain connectivity, such as the small-world and modular organization, remain stable during brain maturation by focusing streamline loss to specific types of fiber tracts.

Use it and improve it or lose it: interactions between arm function and use in humans post-stroke.

"Use it and improve it, or lose it" is one of the axioms of motor therapy after stroke. There is, however, little understanding of the interactions between arm function and use in humans post-stroke. Here, we explored putative non-linear interactions between upper extremity function and use by developing a first-order dynamical model of stroke recovery with longitudinal data from participants receiving constraint induced movement therapy (CIMT) in the EXCITE clinical trial. Using a Bayesian regression framework, we systematically compared this model with competitive models that included, or not, interactions between function and use. Model comparisons showed that the model with the predicted interactions between arm function and use was the best fitting model. Furthermore, by comparing the model parameters before and after CIMT intervention in participants receiving the intervention one year after randomization, we found that therapy increased the parameter that controls the effect of arm function on arm use. Increase in this parameter, which can be thought of as the confidence to use the arm for a given level of function, lead to increase in spontaneous use after therapy compared to before therapy.

Feasibility study of immersive virtual prism adaptation therapy with depth-sensing camera using functional near-infrared spectroscopy in healthy adults.

Prism Adaptation (PA) is used to alleviate spatial neglect. We combined immersive virtual reality with a depth-sensing camera to develop virtual prism adaptation therapy (VPAT), which block external visual cues and easily quantify and monitor errors than conventional PA. We conducted a feasibility study to investigate whether VPAT can induce behavioral adaptations by measuring after-effect and identifying which cortical areas were most significantly activated during VPAT using functional near-infrared spectroscopy (fNIRS). Fourteen healthy subjects participated in this study. The experiment consisted of four sequential phases (pre-VPAT, VPAT-10°, VPAT-20°, and post-VPAT). To compare the most significantly activated cortical areas during pointing in different phases against pointing during the pre-VPAT phase, we analyzed changes in oxyhemoglobin concentration using fNIRS during pointing. The pointing errors of the virtual hand deviated to the right-side during early pointing blocks in the VPAT-10° and VPAT-20° phases. There was a left-side deviation of the real hand to the target in the post-VPAT phase, demonstrating after-effect. The most significantly activated channels during pointing tasks were located in the right hemisphere, and possible corresponding cortical areas included the dorsolateral prefrontal cortex and frontal eye field. In conclusion, VPAT may induce behavioral adaptation with modulation of the dorsal attentional network.

White matter tracts involved in subcortical unilateral spatial neglect in subacute stroke.

Background: Unilateral spatial neglect (USN) is common and associated with poor motor and cognitive outcomes as well as impaired quality of life following stroke. Traditionally, the neural substrates underlying USN have been thought to be cortical areas, such as the posterior parietal cortex. However, patients with stroke involving only subcortical structures may also present with USN. While only a few studies have reported on USN in subcortical stroke, the involvement of white matter tracts related to brain networks of visuospatial attention is one possible explanation for subcortical neglect. Therefore, this study aimed to investigate which specific white matter tracts are neural substrates for USN in patients with subcortical stroke. Methods: Twenty-two patients with subcortical stroke without cortical involvement who were admitted to the Department of Rehabilitation Medicine at Seoul National University Bundang Hospital were retrospectively enrolled. Nine subjects were subclassified into a "USN(+)" group, as they had at least two positive results on three tests (the Schenkenberg line bisection test, Albert's test, and house drawing test) and a score of 1 or higher on the Catherine Bergego scale. The remaining 13 subjects without abnormalities on those tests were subclassified into the "USN(-)" group. Stroke lesions on MRI were manually drawn using MRIcron software. Lesion overlapping and atlas-based analyses of MRI images were conducted. The correlation was analyzed between the overlapped lesion volumes with white matter tracts and the severity of USN (in the Albert test and the Catherine Bergego scale). Results: Lesions were more widespread in the USN(+) group than in the USN(-) group, although their locations in the right hemisphere were similar. The atlas-based analyses identified that the right cingulum in the cingulate cortex, the temporal projection of the superior longitudinal fasciculus, and the forceps minor significantly overlapped with the lesions in the USN(+) group than in the USN(-) group. The score of the Catherine Bergego scale correlated with the volume of the involved white matter tracts. Conclusion: In this study, white matter tracts associated with USN were identified in patients with subcortical stroke without any cortical involvement. Our study results, along with previous findings on subcortical USN, support that USN may result from damage to white matter pathways.

Disrupted structural network of inferomedial temporal regions in relapsing-remitting multiple sclerosis compared with neuromyelitis optica spectrum disorder.

Multiple sclerosis (MS) and neuromyelitis optica spectrum disorder (NMOSD) are two representative chronic inflammatory demyelinating disorders of the central nervous system. We aimed to determine and compare the alterations of white matter (WM) connectivity between MS, NMOSD, and healthy controls (HC). This study included 68 patients with relapsing-remitting MS, 50 with NMOSD, and 26 HC. A network-based statistics method was used to assess disrupted patterns in WM networks. Topological characteristics of the three groups were compared and their associations with clinical parameters were examined. WM network analysis indicated that the MS and NMOSD groups had lower total strength, clustering coefficient, global efficiency, and local efficiency and had longer characteristic path length than HC, but there were no differences between the MS and NMOSD groups. At the nodal level, the MS group had more brain regions with altered network topologies than did the NMOSD group when compared with the HC group. Network alterations were correlated with Expanded Disability Status Scale score and disease duration in both MS and NMOSD groups. Two distinct subnetworks that characterized the disease groups were also identified. When compared with NMOSD, the most discriminative connectivity changes in MS were located between the thalamus, hippocampus, parahippocampal gyrus, amygdala, fusiform gyrus, and inferior and superior temporal gyri. In conclusion, MS patients had greater network dysfunction compared to NMOSD and altered short connections within the thalamus and inferomedial temporal regions were relatively spared in NMOSD compared with MS.

Neural substrates of subcortical aphasia in subacute stroke: Voxel-based lesion symptom mapping study.

Subcortical aphasia develops as a result of damage to subcortical brain areas without loss of cortical functions. Although earlier voxel-based lesion-symptom mapping (VLSM) studies have shown possible neural correlates for aphasia, it remains to be clarified which brain regions are associated with subcortical aphasia. The aim of this study was to investigate the neural substrates associated with subcortical aphasia in patients with stroke using VLSM and atlas-based analyses to explore the involvement of white matter tracts and subcortical structures. Fifty patients with subacute subcortical stroke without cortical involvement were retrospectively enrolled: 24 with and 26 without aphasia. We performed VLSM and atlas-based analyses of the patients' fluid-attenuated inversion recovery images and found that the left perisylvian white matter, left fronto-occipital fasciculus, uncinate fasciculus, and forceps minor were significantly more greatly affected in the aphasia than in the non-aphasia group. The left anterior thalamic radiation, cingulum (cingulate gyrus), and superior longitudinal fasciculus also showed higher involvement in this group (marginal significance). Among the subcortical regions, the left caudate and putamen were more greatly involved in the aphasia group. Our findings confirm language processing as one of the integrated sensory-motor processes that occur in the region around the left sylvian fissure. Our atlas-based analysis approach can be used to complement VLSM analyses.

Decreased Cortical Thickness and Local Gyrification in Individuals with Subjective Cognitive Impairment.

OBJECTIVE: Subjective cognitive impairment (SCI) is associated with future cognitive decline. This study aimed to compare cortical thickness and local gyrification index (LGI) between individuals with SCI and normal control (NC) subjects. METHODS: Forty-seven participants (27 SCI and 20 NC) were recruited. All participants underwent brain magnetic resonance imaging scanning and were clinically assessed using the Consortium to Establish a Registry for Alzheimer's Disease (CERAD) battery of tests. We compared cortical thickness and LGI between the two groups and analyzed correlations between cortical thickness/LGI and scores on CERAD protocol subtests in the SCI group for region of interests with significant between-group differences. RESULTS: Cortical thickness reduction in the left entorhinal, superior temporal, insular, rostral middle frontal, precentral, superior frontal, and supramarginal regions, and right supramarginal, precentral, insular, postcentral, and posterior cingulate regions was observed in the SCI compared to the NC group. Cortical thickness in these regions correlated with scores of constructional praxis, word list memory, word list recall, constructional recall, trail making test A, and verbal fluency under the CERAD protocol. Significantly decreased gyrification was observed in the left lingual gyrus of the SCI group. In addition, gyrification of this region was positively associated with scores of constructional praxis. CONCLUSION: Our results may provide an additional reference to the notion that SCI may be associated with future cognitive impairment. This study may help clinicians to assess individuals with SCI who may progress to mild cognitive impairment and Alzheimer's dementia.

Brain network analysis reveals that amyloidopathy affects comorbid cognitive dysfunction in older adults with depression.

Late-life depression (LLD) may increase the risk of Alzheimer's dementia (AD). While amyloidopathy accelerates AD progression, its role in such patients has not yet been elucidated. We hypothesized that cerebral amyloidopathy distinctly affects the alteration of brain network topology and may be associated with distinct cognitive symptoms. We recruited 26 and 27 depressed mild cognitive impairment (MCI) patients with (LLD-MCI-A(+)) and without amyloid accumulation (LLD-MCI-A(-)), respectively, and 21 normal controls. We extracted structural brain networks using their diffusion-weighted images. We aimed to compare the distinct network deterioration in LLD-MCI with and without amyloid accumulation and the relationship with their distinct cognitive decline. Thus, we performed a group comparison of the network topological measures and investigated any correlations with neurocognitive testing scores. Topological features of brain networks were different according to the presence of amyloid accumulation. Disrupted network connectivity was highly associated with impaired recall and recognition in LLD-MCI-A(+) patients. Inattention and dysexecutive function were more influenced by the altered networks involved in fronto-limbic circuitry dysfunction in LLD-MCI-A(-) patients. Our results show that alterations in brain network topology may reflect different cognitive dysfunction depending on amyloid accumulation in depressed older adults with MCI.

Cerebral amyloid accumulation is associated with distinct structural and functional alterations in the brain of depressed elders with mild cognitive impairment.

BACKGROUND: Elderly patients with late-life depression (LLD) often report mild cognitive impairment (MCI), so Alzheimer's disease (AD) is hard to identify in these patients. We aimed to identify the structural and functional differences between prodromal AD and LLD-related MCI. METHODS: We performed voxel-based morphometry and functional connectivity (FC) analyses in elderly patients with both LLD and MCI to compare alterations between those with cerebral amyloidopathy and those without. We subdivided patients into subthreshold depression (STD) and major depressive disorder (MDD) groups. Using florbetaben positron emission tomography (PET), we compared volume and connectivity between healthy controls and four STD and MDD groups with or without amyloid deposition(A): STD-MCI-A(+), MDD-MCI-A(+), STD-MCI-A(-), and MDD-MCI-A(-). RESULTS: Subjects with MDD or amyloid deposition showed greater volume reduction in the left middle temporal gyrus. MDD groups had lower FC than STD groups in the frontal, cortical, and limbic areas. The STD-MCI-A(+) group showed greater FC reduction than the MDD-MCI-A(-) and STD-MCI-A(-) groups, particularly in the hippocampus, parahippocampus, and frontal and temporal cortices. The functional differences associated with amyloid plaques were more evident in the STD group than in the MDD group. LIMITATIONS: Limitations include disproportional sex ratios, inability to determine the longitudinal effects of amyloidopathy in large populations. CONCLUSIONS: Regional gray matter loss and alterations in brain networks may reflect impairments caused by amyloid deposition and depression. Such changes may facilitate the detection of prodromal AD in elderly patients with both depression and cognitive dysfunction, allowing earlier intervention and more appropriate treatment.

Brain amyloid accumulation possibly exacerbates concurrent mild cognitive impairment with subthreshold depression in older adults: A 1-year follow-up study.

BACKGROUND: This study aimed to investigate the 1-year changes in neuropsychological test results in older adults with concomitant late-life depression (LLD) and mild cognitive impairment (MCI) according to the presence or absence of brain amyloidopathy. METHODS: All subjects underwent 18F-florbetaben-positron emission tomography and a standardized neuropsychological battery. The subjects were divided based on brain amyloidopathy and severity of depressive symptoms into the following groups: LLD-MCI-A(+), subthreshold depression (STD)-MCI-A(+), major depressive disorder (MDD)-MCI-A(+), LLD-MCI-A(-), STD-MCI-A(-), and MDD-MCI-A(-). After one year, follow-up neurocognitive tests were conducted. Fifty-nine participants completed both the baseline and 1-year follow-up neurocognitive tests. RESULTS: In the LLD-MCI-A(+) group, the word list recall and word list recognition scores decreased during the follow-up period. The STD-MCI-A(+) group also showed a significant decrease in word list recall score and the score/Z-score of word list recognition. On the other hand, the word list recall Z-score improved at the 1-year follow-up in the LLD-MCI-A(-) group. In particular, the MDD-MCI-A(-) group showed significant increases in word list memory score/Z-score and word list recall Z-score during the follow-up period. LIMITATIONS: Considering that AD progresses slowly, a longer follow-up period may be required. CONCLUSIONS: Our findings showed differences in the extent of change of neuropsychological test results depending on the severity of depressive symptoms and presence or absence of brain amyloidopathy. Our results suggest that clinicians might explore the underlying neuropathology when assessing older adults with concomitant depression and cognitive impairment, even if the symptoms of depression are not severe.

Overconnectivity of the right Heschl's and inferior temporal gyrus correlates with symptom severity in preschoolers with autism spectrum disorder.

Previous studies have reported varying findings regarding the association of brain connectivity in autism spectrum disorder (ASD) with overconnectivity, underconnectivity, or both. Despite the emerging understanding that ASD is a developmental disconnection syndrome, very little is known about structural brain networks in preschool-aged children with low-functioning ASD. We aimed to investigate the structural brain connectivity of low-functioning ASD using diffusion magnetic resonance imaging and graph theory to examine alterations in different brain network topologies and identify any correlations with the clinical severity of ASD in preschool-aged children. Fifty-two preschool-aged children (28 with ASD and 24 with typical development) were included in the analysis. Graph-based network analysis was performed to examine the global and local structural brain networks. Nodal network measures exhibited increased nodal strength in the right Heschl's gyrus, which was positively associated with all autistic clinical symptoms (Autism Diagnostic Observation Schedule and Childhood Autism Rating Scale [CARS]). The nodal strength of the right inferior temporal gyrus showed a moderate correlation with the CARS score. Using network-based statistics, we identified a subnetwork with increased connections encompassing the right Heschl's gyrus and the right inferior temporal gyrus in preschool-aged children with ASD. The asymmetric value in the inferior temporal gyrus exhibited right dominance of nodal strength in children with ASD compared to that in typically developing children. Our findings support the theory of aberrant brain growth and overconnectivity as the underlying mechanism of ASD and provides new insights into potential regional biomarkers that can detect low-functioning ASD in preschool-aged children. LAY SUMMARY: This study supports the theory of aberrant brain growth and overconnectivity as an explanation for ASD. Measuring the right HG and inferior temporal gyrus provides new insights of potential regional biomarkers underpinning ASD in preschool-aged children.

Motor learning without doing: trial-by-trial improvement in motor performance during mental training.

Although there is converging experimental and clinical evidences suggesting that mental training with motor imagery can improve motor performance, it is unclear how humans can learn movements through mental training despite the lack of sensory feedback from the body and the environment. In a first experiment, we measured the trial-by-trial decrease in durations of executed movements (physical training group) and mentally simulated movements (motor-imagery training group), by means of training on a multiple-target arm-pointing task requiring high accuracy and speed. Movement durations were significantly lower in posttest compared with pretest after both physical and motor-imagery training. Although both the posttraining performance and the rate of learning were smaller in motor-imagery training group than in physical training group, the change in movement duration and the asymptotic movement duration after a hypothetical large number of trials were identical. The two control groups (eye-movement training and rest groups) did not show change in movement duration. In the second experiment, additional kinematic analyses revealed that arm movements were straighter and faster both immediately and 24 h after physical and motor-imagery training. No such improvements were observed in the eye-movement training group. Our results suggest that the brain uses state estimation, provided by internal forward model predictions, to improve motor performance during mental training. Furthermore, our results suggest that mental practice can, at least in young healthy subjects and if given after a short bout of physical practice, be successfully substituted to physical practice to improve motor performance.

Computational modelling of the long-term effects of brain stimulation on the local and global structural connectivity of epileptic patients.

Computational studies of the influence of different network parameters on the dynamic and topological network effects of brain stimulation can enhance our understanding of different outcomes between individuals. In this study, a brain stimulation session along with the subsequent post-stimulation brain activity is simulated for a period of one day using a network of modified Wilson-Cowan oscillators coupled according to diffusion imaging based structural connectivity. We use this computational model to examine how differences in the inter-region connectivity and the excitability of stimulated regions at the time of stimulation can affect post-stimulation behaviours. Our findings indicate that the initial inter-region connectivity can heavily affect the changes that stimulation induces in the connectivity of the network. Moreover, differences in the excitability of the stimulated regions seem to lead to different post-stimulation connectivity changes across the model network, including on the internal connectivity of non-stimulated regions.