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After focal damage, cerebral networks reorganise their structural and functional anatomy to compensate for both the lesion itself and remote effects. Novel developments in the analysis of functional neuroimaging data enable us to assess in vivo the specific contributions of individual brain areas to recovery of function and the effect of treatment on cortical reorganisation. Connectivity analyses can be used to investigate the effect of stroke on cerebral networks, and help us to understand why some patients make a better recovery than others. This systems-level view also provides insights into how neuromodulatory interventions might target pathological network configurations associated with incomplete recovery. In the future, such analyses of connectivity could help to optimise treatment regimens based on the individual network pathology underlying a particular neurological deficit, thereby opening the way for stratification of patients based on the possible response to an intervention.

Stroke is a leading cause of acquired, permanent disability worldwide. Although the treatment of acute stroke has been improved considerably, the majority of patients to date are left disabled with a considerable impact on functional independence and quality of life. As the absolute number of stroke survivors is likely to further increase due to the demographic changes in our aging societies, new strategies are needed in order to improve neurorehabilitation. The most critical driver of functional recovery post-stroke is neural reorganization. For developing novel, neurobiologically informed strategies to promote recovery of function, an improved understanding of the mechanisms enabling plasticity and recovery is mandatory. This review provides a comprehensive survey of recent developments in the field of stroke recovery using neuroimaging and non-invasive brain stimulation. We discuss current concepts of how the brain reorganizes its functional architecture to overcome stroke-induced deficits, and also present evidence for maladaptive effects interfering with recovery. We demonstrate that the combination of neuroimaging and neurostimulation techniques allows a better understanding of how brain plasticity can be modulated to promote the reorganization of neural networks. Finally, neurotechnology-based treatment strategies allowing patient-tailored interventions to achieve enhanced treatment responses are discussed. The review also highlights important limitations of current models, and finally closes with possible solutions and future directions.

The increasing interest in Virtual Reality (VR) as a tool for neuroscientific research contrasts with the current lack of established toolboxes and standards. In several recent studies, game engines like Unity or Unreal Engine were used. It remains to be tested whether these software packages provide sufficiently precise and accurate stimulus timing and time measurements that allow inferring ongoing mental and neural processes. We here investigated the precision and accuracy of the timing mechanisms of Unreal Engine 4 and SteamVR in combination with the HTC Vive VR system. In a first experiment, objective external measures revealed that stimulus durations were highly accurate. In contrast, in a second experiment, the assessment of the precision of built-in timing procedures revealed highly variable reaction time measurements and inaccurate determination of stimulus onsets. Hence, we developed a new software-based method that allows precise and accurate reaction time measurements with Unreal Engine and SteamVR. Instead of using the standard timing procedures implemented within Unreal Engine, time acquisition was outsourced to a background application. Timing benchmarks revealed that the newly developed method allows reaction time measurements with a precision and accuracy in the millisecond range. Overall, the present results indicate that the HTC Vive together with Unreal Engine and SteamVR can achieve high levels of precision and accuracy both concerning stimulus duration and critical time measurements. The latter can be achieved using a newly developed routine that allows not only accurate reaction time measures but also provides precise timing parameters that can be used in combination with time-sensitive functional measures such as electroencephalography (EEG) or transcranial magnetic stimulation (TMS).

ObjectiveTo study the frequency of neurological symptoms and complications in COVID-19 patients in a systematic review of the literature.MethodsRelevant studies were identified through electronic explorations of PubMed, medRxiv, and bioRxiv. Besides, three Chinese databases were searched. A snowballing method searching the bibliographies of the retrieved references was applied to identify potentially relevant articles. Articles published within 1 year prior to April 20th, 2020, were screened with no language restriction imposed. Databases were searched for terms related to SARS-CoV-2/COVID-19 and neurological manifestations, using a pre-established protocol registered on the International Prospective Register of Systematic Reviews database (ID: CRD42020187994).ResultsA total of 2441 articles were screened for relevant content, of which 92 full-text publications were included in the analyses of neurological manifestations of COVID-19. Headache, dizziness, taste and smell dysfunctions, and impaired consciousness were the most frequently described neurological symptoms, the latter more often among patients with a severe or critical disease course. To date, only smaller cohort studies or single cases have reported cerebrovascular events, seizures, meningoencephalitis, and immune-mediated neurological diseases, not suitable for quantitative analysis.ConclusionThe most frequent neurological symptoms reported in association with COVID-19 are non-specific for the infection with SARS-CoV-2. Although SARS-CoV-2 may have the potential to gain direct access to the nervous system, so far, SARS-CoV-2 was detected in the cerebrospinal fluid in two cases only. Standardized international registries are needed to clarify the clinical relevance of the neuropathogenicity of SARS-CoV-2 and to elucidate a possible impact of SARS-CoV-2 infection on common neurological disease, such as Alzheimer’s, Parkinson’s disease or multiple sclerosis.

•Contralesional TMS effects strongly depend on the ipsilesional structural integrity.•The impact of the ipsilesional structural reserve is regional specific.•Individual functional and structural data could optimize treatment strategies. The concept of structural reserve in stroke reorganization assumes that the relevance of the contralesional hemisphere strongly depends on the brain tissue spared by the lesion in the affected hemisphere. Recent studies, however, have indicated that the contralesional hemisphere's impact exhibits region-specific variability with concurrently existing maladaptive and supportive influences. This challenges traditional views, necessitating a nuanced investigation of contralesional motor areas and their interaction with ipsilesional networks. Our study focused on the functional role of contralesional key motor areas and lesion-induced connectome disruption early after stroke. Online TMS data of twenty-five stroke patients was analyzed to disentangle interindividual differences in the functional roles of contralesional primary motor cortex (M1), dorsal premotor cortex (dPMC), and anterior interparietal sulcus (aIPS) for motor function. Connectome-based lesion symptom mapping and corticospinal tract lesion quantification were used to investigate how TMS effects depend on ipsilesional structural network properties. At group and individual levels, TMS interference with contralesional M1 and aIPS but not dPMC led to improved performance early after stroke. At the connectome level, a more disturbing role of contralesional M1 was related to a more severe disruption of the structural integrity of ipsilesional M1 in the affected motor network. In contrast, a detrimental influence of contralesional aIPS was linked to less disruption of the ipsilesional M1 connectivity. Our findings indicate that contralesional areas distinctively interfere with motor performance early after stroke depending on ipsilesional structural integrity, extending the concept of structural reserve to regional specificity in recovery of function.

Peripheral neuropathy represents a spectrum of diseases with different etiologies. The most common causes are diabetes, exposure to toxic substances including alcohol and chemotherapeutics, immune-mediated conditions, and gene mutations. A thorough workup including clinical history and examination, nerve conduction studies, and comprehensive laboratory tests is warranted to identify treatable causes. The variability of symptoms allows distinguishing characteristic clinical phenotypes of peripheral neuropathy that should be recognized in order to stratify the diagnostic workup accordingly. Nerve conduction studies are essential to determine the phenotype (axonal versus demyelinating) and severity. Laboratory tests, including genetic testing, CSF examination, nerve imaging, and nerve biopsy, represent additional clinical tests that can be useful in specific clinical scenarios. We propose a flow chart based on five common basic clinical patterns of peripheral neuropathy. Based on these five clinical phenotypes, we suggest differential diagnostic pathways in order to establish the underlying cause. The recognition of characteristic clinical phenotypes combined with nerve conduction studies allows pursuing subsequent diagnostic pathways that incorporate nerve conduction studies and additional diagnostic tests. This two-tiered approach promises higher yield and better cost-effectiveness in the diagnostic workup in patients with peripheral neuropathy.

Functional neuroimaging studies frequently demonstrated that stroke patients show bilateral activity in motor and premotor areas during movements of the paretic hand in contrast to a more lateralized activation observed in healthy subjects. Moreover, a few studies modeling functional or effective connectivity reported performance-related changes in the motor network after stroke. Here, we investigated the temporal evolution of intra- and interhemispheric (dys-) connectivity during motor recovery from the acute to the early chronic phase post-stroke. Twelve patients performed hand movements in an fMRI task in the acute (≤72hours) and subacute stage (2weeks) post-stroke. A subgroup of 10 patients participated in a third assessment in the early chronic stage (3–6months). Twelve healthy subjects served as reference for brain connectivity. Changes in effective connectivity within a bilateral network comprising M1, premotor cortex (PMC), and supplementary motor area (SMA) were estimated by dynamic causal modeling. Motor performance was assessed by the Action Research Arm Test and maximum grip force. Results showed reduced positive coupling of ipsilesional SMA and PMC with ipsilesional M1 in the acute stage. Coupling parameters among these areas increased with recovery and predicted a better outcome. Likewise, negative influences from ipsilesional areas to contralesional M1 were attenuated in the acute stage. In the subacute stage, contralesional M1 exerted a positive influence on ipsilesional M1. Negative influences from ipsilesional areas on contralesional M1 subsequently normalized, but patients with poorer outcome in the chronic stage now showed enhanced negative coupling from contralesional upon ipsilesional M1. These findings show that the reinstatement of effective connectivity in the ipsilesional hemisphere is an important feature of motor recovery after stroke. The shift of an early, supportive role of contralesional M1 into enhanced inhibitory coupling might indicate maladaptive processes which could be a target of non-invasive brain stimulation techniques. ► Bilateral breakdown of effective connectivity among motor areas in acute stroke. ► Coupling increase from premotor areas to affected M1 predicts better recovery. ► Transient promoting influence from contralesional M1 in the subacute phase. ► Putative maladaptive inhibition from contralesional M1 in the chronic phase.

Stroke is a devastating disease leading to cell death and disconnection between neurons both locally and remote, often resulting in severe long-term disability. Spontaneous reorganization of areas and pathways not primarily affected by ischemia is, however, associated with albeit limited recovery of function. Quantitative mapping of whole-brain changes of structural connectivity concerning the ischemia-induced sensorimotor deficit and recovery thereof would help to target structural plasticity in order to improve rehabilitation. Currently, only in vivo diffusion MRI can extract the structural whole-brain connectome noninvasively. This approach is, however, used primarily in human studies. Here, we applied atlas-based MRI analysis and graph theory to DTI in wild-type mice with cortical stroke lesions. Using a DTI network approach and graph theory, we aimed at gaining insights into the dynamics of the spontaneous reorganization after stroke related to the recovery of function. We found evidence for altered structural integrity of connections of specific brain regions, including the breakdown of connections between brain regions directly affected by stroke as well as long-range rerouting of intra- and transhemispheric connections related to improved sensorimotor behavior. •Application of in vivo longitudinal DTI in a mouse model of cortical stroke.•Monitoring of spontaneous functional recovery using three behavior tests.•Network analysis of degree, edge strength and shortest path.•Local breakdown and long-range rerouting of intra- and transhemispheric connections.•Correlations of region-spqecific connectivity changes to functional improvement.

The responsiveness to non-invasive neuromodulation protocols shows high inter-individual variability, the reasons of which remain poorly understood. We here tested whether the response to intermittent theta-burst stimulation (iTBS) – an effective repetitive transcranial magnetic stimulation (rTMS) protocol for increasing cortical excitability – depends on network properties of the cortical motor system. We furthermore investigated whether the responsiveness to iTBS is dose-dependent. To this end, we used a sham-stimulation controlled, single-blinded within-subject design testing for the relationship between iTBS aftereffects and (i) motor-evoked potentials (MEPs) as well as (ii) resting-state functional connectivity (rsFC) in 16 healthy subjects. In each session, three blocks of iTBS were applied, separated by 15min. We found that non-responders (subjects not showing an MEP increase of ≥10% after one iTBS block) featured stronger rsFC between the stimulated primary motor cortex (M1) and premotor areas before stimulation compared to responders. However, only the group of responders showed increases in rsFC and MEPs, while most non-responders remained close to baseline levels after all three blocks of iTBS. Importantly, there was still a large amount of variability in both groups. Our data suggest that responsiveness to iTBS at the local level (i.e., M1 excitability) depends upon the pre-interventional network connectivity of the stimulated region. Of note, increasing iTBS dose did not turn non-responders into responders. The finding that higher levels of pre-interventional connectivity precluded a response to iTBS could reflect a ceiling effect underlying non-responsiveness to iTBS at the systems level. •Non-responders to iTBS feature stronger baseline premotor-M1 connectivity.•Responders show a lasting increase in MEPs and rsFC after multiple iTBS blocks.•Increasing the iTBS dose does not induce responsiveness.

While some researchers propose the existence of a special numerosity sense, others challenge this view and argue that numerosity is derived from low-level features as density information. Here, we used size adaptation to manipulate the apparent area size of an object set without changing its physical density. After size adaptation, two probe patches were shown, each of which contained a specific numerosity of dots. Subjects were required to report, which probe patch contained more dots. Numerosity perception was compared between conditions where probe patches were adapted to appear smaller or larger. Size adaptation affected numerosity perception in a logarithmic fashion, increasing with the numerosity in the probe patch. No changes in density perception were found after size adaptation. Data suggest that size and density information play only a minor role in the estimation of low numerosities. In stark contrast, high numerosities strongly depend on size and density information. The data reinforce recent claims of separate mechanism for the perception of low and high numerosities.