Neural mechanisms underlying improved new-word learning with high-density transcranial direct current stimulation.

Neurobehavioral studies have provided evidence for the effectiveness of anodal tDCS on language production, by stimulation of the left Inferior Frontal Gyrus (IFG) or of left Temporo-Parietal Junction (TPJ). However, tDCS is currently not used in clinical practice outside of trials, because behavioral effects have been inconsistent and underlying neural effects unclear. Here, we propose to elucidate the neural correlates of verb and noun learning and to determine if they can be modulated with anodal high-definition (HD) tDCS stimulation. Thirty-six neurotypical participants were randomly allocated to anodal HD-tDCS over either the left IFG, the left TPJ, or sham stimulation. On day one, participants performed a naming task (pre-test). On day two, participants underwent a new-word learning task with rare nouns and verbs concurrently to HD-tDCS for 20 min. The third day consisted of a post-test of naming performance. EEG was recorded at rest and during naming on each day. Verb learning was significantly facilitated by left IFG stimulation. HD-tDCS over the left IFG enhanced functional connectivity between the left IFG and TPJ and this correlated with improved learning. HD-tDCS over the left TPJ enabled stronger local activation of the stimulated area (as indexed by greater alpha and beta-band power decrease) during naming, but this did not translate into better learning. Thus, tDCS can induce local activation or modulation of network interactions. Only the enhancement of network interactions, but not the increase in local activation, leads to robust improvement of word learning. This emphasizes the need to develop new neuromodulation methods influencing network interactions. Our study suggests that this may be achieved through behavioral activation of one area and concomitant activation of another area with HD-tDCS.

Recovery after stroke: the severely impaired are a distinct group.

INTRODUCTION: Stroke causes different levels of impairment and the degree of recovery varies greatly between patients. The majority of recovery studies are biased towards patients with mild-to-moderate impairments, challenging a unified recovery process framework. Our aim was to develop a statistical framework to analyse recovery patterns in patients with severe and non-severe initial impairment and concurrently investigate whether they recovered differently. METHODS: We designed a Bayesian hierarchical model to estimate 3-6 months upper limb Fugl-Meyer (FM) scores after stroke. When focusing on the explanation of recovery patterns, we addressed confounds affecting previous recovery studies and considered patients with FM-initial scores <45 only. We systematically explored different FM-breakpoints between severe/non-severe patients (FM-initial=5-30). In model comparisons, we evaluated whether impairment-level-specific recovery patterns indeed existed. Finally, we estimated the out-of-sample prediction performance for patients across the entire initial impairment range. RESULTS: Recovery data was assembled from eight patient cohorts (n=489). Data were best modelled by incorporating two subgroups (breakpoint: FM-initial=10). Both subgroups recovered a comparable constant amount, but with different proportional components: severely affected patients recovered more the smaller their impairment, while non-severely affected patients recovered more the larger their initial impairment. Prediction of 3-6 months outcomes could be done with an R2=63.5% (95% CI=51.4% to 75.5%). CONCLUSIONS: Our work highlights the benefit of simultaneously modelling recovery of severely-to-non-severely impaired patients and demonstrates both shared and distinct recovery patterns. Our findings provide evidence that the severe/non-severe subdivision in recovery modelling is not an artefact of previous confounds. The presented out-of-sample prediction performance may serve as benchmark to evaluate promising biomarkers of stroke recovery.

The structural connectome and motor recovery after stroke: predicting natural recovery.

Stroke patients vary considerably in terms of outcomes: some patients present 'natural' recovery proportional to their initial impairment (fitters), while others do not (non-fitters). Thus, a key challenge in stroke rehabilitation is to identify individual recovery potential to make personalized decisions for neuro-rehabilitation, obviating the 'one-size-fits-all' approach. This goal requires (i) the prediction of individual courses of recovery in the acute stage; and (ii) an understanding of underlying neuronal network mechanisms. 'Natural' recovery is especially variable in severely impaired patients, underscoring the special clinical importance of prediction for this subgroup. Fractional anisotropy connectomes based on individual tractography of 92 patients were analysed 2 weeks after stroke (TA) and their changes to 3 months after stroke (TC - TA). Motor impairment was assessed using the Fugl-Meyer Upper Extremity (FMUE) scale. Support vector machine classifiers were trained to separate patients with natural recovery from patients without natural recovery based on their whole-brain structural connectomes and to define their respective underlying network patterns, focusing on severely impaired patients (FMUE < 20). Prediction accuracies were cross-validated internally, in one independent dataset and generalized in two independent datasets. The initial connectome 2 weeks after stroke was capable of segregating fitters from non-fitters, most importantly among severely impaired patients (TA: accuracy = 0.92, precision = 0.93). Secondary analyses studying recovery-relevant network characteristics based on the selected features revealed (i) relevant differences between networks contributing to recovery at 2 weeks and network changes over time (TC - TA); and (ii) network properties specific to severely impaired patients. Important features included the parietofrontal motor network including the intraparietal sulcus, premotor and primary motor cortices and beyond them also attentional, somatosensory or multimodal areas (e.g. the insula), strongly underscoring the importance of whole-brain connectome analyses for better predicting and understanding recovery from stroke. Computational approaches based on structural connectomes allowed the individual prediction of natural recovery 2 weeks after stroke onset, especially in the difficult to predict group of severely impaired patients, and identified the relevant underlying neuronal networks. This information will permit patients to be stratified into different recovery groups in clinical settings and will pave the way towards personalized precision neurorehabilitative treatment.

Spontaneous Network Coupling Enables Efficient Task Performance without Local Task-Induced Activations.

Neurobehavioral studies in humans have long concentrated on changes in local activity levels during repetitive executions of a task. Spontaneous neural coupling within extended networks has latterly been found to also influence performance. Here, we intend to uncover the underlying mechanisms, the relative importance, and the interaction between spontaneous coupling and task-induced activations. To do so, we recorded two groups of healthy participants (male and female) during rest and while they performed either a visual perception or a motor sequence task. We demonstrate that, for both tasks, stronger activations during the task as well as greater network coupling through spontaneous α rhythms at rest predict performance. However, high performers present an absence of classical task-induced activations and, instead, stronger spontaneous network coupling. Activations were thus a compensation mechanism needed only in subjects with lower spontaneous network interactions. This challenges classical models of neural processing and calls for new strategies in attempts to train and enhance performance.SIGNIFICANCE STATEMENT Our findings challenge the widely accepted notion that task-induced activations are of paramount importance for behavior. This will have an important impact on interpretations of human neurobehavioral research. They further link the widely used techniques of quantifying network communication in the brain with classical neuroscience methods and demonstrate possible ways of how network communication influences human behavior. Traditional training methods attempt to enhance neural activations through task repetitions. Our findings suggest a more efficient neural target for learning: enhancing spontaneous neural interactions. This will be of major interest for a large variety of scientific fields with very broad applications in schools, work, and others.

Disconnectomics of the Rich Club Impacts Motor Recovery After Stroke.

BACKGROUND AND PURPOSE: Structural brain networks possess a few hubs, which are not only highly connected to the rest of the brain but are also highly connected to each other. These hubs, which form a rich-club, play a central role in global brain organization. To investigate whether the concept of rich-club sheds new light on poststroke recovery, we applied a novel network-theoretical quantification of lesions to patients with stroke and compared the outcomes with what lesion size alone would indicate. METHODS: Whole-brain structural networks of 73 patients with ischemic stroke were reconstructed using diffusion-weighted imaging data. Disconnectomes, a new type of network analyses, were constructed using only those fibers that pass through the lesion. Fugl-Meyer upper extremity scores and their changes were used to determine whether the patients show natural recovery or not. RESULTS: Cluster analysis revealed 3 patient clusters: small-lesion-good-recovery, midsized-lesion-poor-recovery (MLPR), and large-lesion-poor-recovery (LLPR). The small-lesion-good-recovery consisted of subjects whose lesions were small, and whose prospects for recovery were relatively good. To explain the nondifference in recovery between the MLPR and LLPR clusters despite the difference (LLPR>MLPR) in lesion volume, we defined the [Formula: see text] metric to be the sum of the entries in the disconnectome and, more importantly, the [Formula: see text] to be the sum of all entries in the disconnectome corresponding to edges with at least one node in the rich-club. Unlike lesion volume and corticospinal tract damage (MLPRLLPR) or showed no difference for [Formula: see text]. CONCLUSIONS: Smaller lesions that focus on the rich-club can be just as devastating as much larger lesions that do not focus on the rich-club, pointing to the role of the rich-club as a backbone for functional communication within brain networks and for recovery from stroke.

Bringing proportional recovery into proportion: Bayesian modelling of post-stroke motor impairment.

Accurate predictions of motor impairment after stroke are of cardinal importance for the patient, clinician, and healthcare system. More than 10 years ago, the proportional recovery rule was introduced by promising that high-fidelity predictions of recovery following stroke were based only on the initially lost motor function, at least for a specific fraction of patients. However, emerging evidence suggests that this recovery rule is subject to various confounds and may apply less universally than previously assumed. Here, we systematically revisited stroke outcome predictions by applying strategies to avoid confounds and fitting hierarchical Bayesian models. We jointly analysed 385 post-stroke trajectories from six separate studies-one of the largest overall datasets of upper limb motor recovery. We addressed confounding ceiling effects by introducing a subset approach and ensured correct model estimation through synthetic data simulations. Subsequently, we used model comparisons to assess the underlying nature of recovery within our empirical recovery data. The first model comparison, relying on the conventional fraction of patients called 'fitters', pointed to a combination of proportional to lost function and constant recovery. 'Proportional to lost' here describes the original notion of proportionality, indicating greater recovery in case of a more severe initial impairment. This combination explained only 32% of the variance in recovery, which is in stark contrast to previous reports of >80%. When instead analysing the complete spectrum of subjects, 'fitters' and 'non-fitters', a combination of proportional to spared function and constant recovery was favoured, implying a more significant improvement in case of more preserved function. Explained variance was at 53%. Therefore, our quantitative findings suggest that motor recovery post-stroke may exhibit some characteristics of proportionality. However, the variance explained was substantially reduced compared to what has previously been reported. This finding motivates future research moving beyond solely behaviour scores to explain stroke recovery and establish robust and discriminating single-subject predictions.

Feasibility of Reconstructing Source Functional Connectivity with Low-Density EEG.

OBJECTIVES: Functional connectivity (FC) is increasingly used as target for neuromodulation and enhancement of performance. A reliable assessment of FC with electroencephalography (EEG) currently requires a laboratory environment with high-density montages and a long preparation time. This study investigated the feasibility of reconstructing source FC with a low-density EEG montage towards a usage in real life applications. METHODS: Source FC was reconstructed with inverse solutions and quantified as node degree of absolute imaginary coherence in alpha frequencies. We used simulated coherent point sources as well as two real datasets to investigate the impact of electrode density (19 vs. 128 electrodes) and usage of template vs. individual MRI-based head models on localization accuracy. In addition, we checked whether low-density EEG is able to capture inter-individual variations in coherence strength. RESULTS: In numerical simulations as well as real data, a reduction of the number of electrodes led to less reliable reconstructions of coherent sources and of coupling strength. Yet, when comparing different approaches to reconstructing FC from 19 electrodes, source FC obtained with beamformers outperformed sensor FC, FC computed after independent component analysis, and source FC obtained with sLORETA. In particular, only source FC based on beamformers was able to capture neural correlates of motor behavior. CONCLUSION: Reconstructions of FC from low-density EEG is challenging, but may be feasible when using source reconstructions with beamformers.

Focal versus distributed temporal cortex activity for speech sound category assignment.

Percepts and words can be decoded from distributed neural activity measures. However, the existence of widespread representations might conflict with the more classical notions of hierarchical processing and efficient coding, which are especially relevant in speech processing. Using fMRI and magnetoencephalography during syllable identification, we show that sensory and decisional activity colocalize to a restricted part of the posterior superior temporal gyrus (pSTG). Next, using intracortical recordings, we demonstrate that early and focal neural activity in this region distinguishes correct from incorrect decisions and can be machine-decoded to classify syllables. Crucially, significant machine decoding was possible from neuronal activity sampled across different regions of the temporal and frontal lobes, despite weak or absent sensory or decision-related responses. These findings show that speech-sound categorization relies on an efficient readout of focal pSTG neural activity, while more distributed activity patterns, although classifiable by machine learning, instead reflect collateral processes of sensory perception and decision.

The "implicit" serial reaction time task induces rapid and temporary adaptation rather than implicit motor learning.

The serial reaction time task (SRTT) has been widely used to induce learning of a repeated motor sequence without the participants' awareness. The task has also been of major influence for defining current concepts of offline consolidation after motor learning. The present study intended to replicate previous findings in a larger population of 53 healthy individuals. We were unable to reproduce previous results of online and offline implicit motor learning with the SRTT. Trials with a repeated sequence rapidly induced shorter reaction times compared to random trials, but this improvement was lost in a post-test obtained a few minutes after the training block. Furthermore, no offline consolidation was observed as there was no change in sequence specific reaction time gain between the post-test immediately after training and a re-test obtained 8 h after training. Online or offline learning remained absent when we modulated the number of sequence repetitions, the error levels, and the structure of random sequences. We conclude that the SRTT induces a rapid and temporary adaptation to the sequence rather than learning, since the repeated motor sequence does not seem to be encoded in memory.

[Fatigue after acquired brain injury and its impact on socio-professional reintegration]. / La fatigue chez le patient cérébrolésé et son impact sur la réinsertion socioprofessionnelle.

Patients with acquired brain injury often suffer from pathological fatigue that differs from "normal" fatigue in that it appears more quickly and during non-demanding tasks, and recovery is not complete despite rest. It limits physical and cognitive activities, interferes with rehabilitation and return to work. The underlying mechanisms are poorly understood but appear to involve dysfunction of brain interactions. Current management combining physical reconditioning, cognitive compensatory strategies, and treatment of associated factors often leads to significant clinical improvement and promotes socio-professional reintegration. However, the effect remains insufficient in some patients, which underlines the importance of developing new therapeutic approaches based on a better understanding of the underlying neuronal deficits.

Les patients cérébrolésés présentent souvent une fatigue pathologique qui diffère de la fatigue « normale ¼, car elle apparaît plus rapidement, lors de tâches peu exigeantes, et ne disparaît pas complètement avec le repos. Elle limite les activités physiques et cognitives,et interfère avec la réadaptation et la reprise du travail. Les mécanismes sous-jacents, peu connus, semblent impliquer une altération des interactions cérébrales. La prise en charge actuelle combine reconditionnement physique, apprentissage de stratégies de compensation et traitement des facteurs associés ; cela favorise souvent l'amélioration clinique et la réinsertion socioprofessionnelle. L'effet reste cependant insuffisant chez certains patients, d'où l'importance de développer des thérapies se basant sur une meilleure compréhension des déficits neuronaux sous-jacents.

Resting-state connectivity predicts visuo-motor skill learning.

Spontaneous brain activity at rest is highly organized even when the brain is not explicitly engaged in a task. Functional connectivity (FC) in the alpha frequency band (α, 8-12 Hz) during rest is associated with improved performance on various cognitive and motor tasks. In this study we explored how FC is associated with visuo-motor skill learning and offline consolidation. We tested two hypotheses by which resting-state FC might achieve its impact on behavior: preparing the brain for an upcoming task or consolidating training gains. Twenty-four healthy participants were assigned to one of two groups: The experimental group (n = 12) performed a computerized mirror-drawing task. The control group (n = 12) performed a similar task but with concordant cursor direction. High-density 156-channel resting-state EEG was recorded before and after learning. Subjects were tested for offline consolidation 24h later. The Experimental group improved during training and showed offline consolidation. Increased α-FC between the left superior parietal cortex and the rest of the brain before training and decreased α-FC in the same region after training predicted learning. Resting-state FC following training did not predict offline consolidation and none of these effects were present in controls. These findings indicate that resting-state alpha-band FC is primarily implicated in providing optimal neural resources for upcoming tasks.

Comparison of Neuroplastic Responses to Cathodal Transcranial Direct Current Stimulation and Continuous Theta Burst Stimulation in Subacute Stroke.

OBJECTIVE: To investigate the effects of cathodal transcranial direct current stimulation (tDCS) and continuous theta burst stimulation (cTBS) on neural network connectivity and motor recovery in individuals with subacute stroke. DESIGN: Double-blinded, randomized, placebo-controlled study. SETTING: University hospital rehabilitation unit. PARTICIPANTS: Inpatients with stroke (N=41; mean age, 65y; range, 28-85y; mean weeks poststroke, 5; range, 2-10) with resultant paresis in the upper extremity (mean Fugl-Meyer score, 14; range, 3-48). INTERVENTIONS: Subjects with stroke were randomly assigned to neuronavigated cTBS (n=14), cathodal tDCS (n=14), or sham transcranial magnetic stimulation/sham tDCS (n=13) over the contralesional primary motor cortex (M1). Each subject completed 9 stimulation sessions over 3 weeks, combined with physical therapy. MAIN OUTCOME MEASURES: Brain function was assessed with directed and nondirected functional connectivity based on high-density electroencephalography before and after stimulation sessions. Primary clinical end point was the change in slope of the multifaceted motor score composed of the upper extremity Fugl-Meyer Assessment score, Box and Block test score, 9-Hole Peg Test score, and Jamar dynamometer results between the baseline period and the treatment time. RESULTS: Neither stimulation treatment enhanced clinical motor gains. Cathodal tDCS and cTBS induced different neural effects. Only cTBS was able to reduce transcallosal influences from the contralesional to the ipsilesional M1 during rest. Conversely, tDCS enhanced perilesional beta-band oscillation coherence compared with cTBS and sham groups. Correlation analyses indicated that the modulation of interhemispheric driving and perilesional beta-band connectivity were not independent mediators for functional recovery across all patients. However, exploratory subgroup analyses suggest that the enhancement of perilesional beta-band connectivity through tDCS might have more robust clinical gains if started within the first 4 weeks after stroke. CONCLUSIONS: The inhibition of the contralesional M1 or the reduction of interhemispheric interactions was not clinically useful in the heterogeneous group of subjects with subacute stroke. An early modulation of perilesional oscillation coherence seems to be a more promising strategy for brain stimulation interventions.

Rapid memory stabilization by transient theta coherence in the human medial temporal lobe.

Presenting stimuli again after presentation of intervening stimuli improves their retention, an effect known as the spacing effect. However, using event-related potentials (ERPs), we had observed that immediate, in comparison to spaced, repetition of pictures induced a positive frontal potential at 200-300 ms. This potential appeared to emanate from the left medial temporal lobe (MTL), a structure critical for memory consolidation. In this study, we tested the behavioral relevance of this signal and explored functional connectivity changes during picture repetition. We obtained high-density electroencephalographic recordings from 14 healthy subjects performing a continuous recognition task where pictures were either repeated immediately or after 9 intervening items. Conventional ERP analysis replicated the positive frontal potential emanating from the left MTL at 250-350 ms in response to immediately repeated stimuli. Connectivity analysis showed that this ERP was associated with increased coherence in the MTL region--left more that right--in the theta-band (3.5-7 Hz) 200-400 ms following immediate, but not spaced, repetition. This increase was stronger in subjects who better recognized immediately repeated stimuli after 30 min. These findings indicate that transient theta-band synchronization between the MTL and the rest of the brain at 200-400 ms reflects a memory stabilizing signal.

Coherent neural oscillations predict future motor and language improvement after stroke.

Recent findings have demonstrated that stroke lesions affect neural communication in the entire brain. However, it is less clear whether network interactions are also relevant for plasticity and repair. This study investigated whether the coherence of neural oscillations at language or motor nodes is associated with future clinical improvement. Twenty-four stroke patients underwent high-density EEG recordings and standardized motor and language tests at 2-3 weeks (T0) and 3 months (T1) after stroke onset. In addition, EEG and motor assessments were obtained from a second population of 18 stroke patients. The graph theoretical measure of weighted node degree at language and motor areas was computed as the sum of absolute imaginary coherence with all other brain regions and compared to the amount of clinical improvement from T0 to T1. At T0, beta-band weighted node degree at the ipsilesional motor cortex was linearly correlated with better subsequent motor improvement, while beta-band weighted node degree at Broca's area was correlated with better language improvement. Clinical recovery was further associated with contralesional theta-band weighted node degree. These correlations were each specific to the corresponding brain area and independent of initial clinical severity, age, and lesion size. Findings were reproduced in the second stroke group. Conversely, later coherence increases occurring between T0 and T1 were associated with less clinical improvement. Improvement of language and motor functions after stroke is therefore associated with inter-regional synchronization of neural oscillations in the first weeks after stroke. A better understanding of network mechanisms of plasticity may lead to new prognostic biomarkers and therapeutic targets.See Ward (doi:10.1093/brain/awv265) for a scientific commentary on this article.

An electrophysiological dissociation between orbitofrontal reality filtering and context source monitoring.

Memory influences behavior in multiple ways. One important aspect is to remember in what precise context in the past a piece of information was acquired (context source monitoring). Another important aspect is to sense whether an upcoming thought, composed of fragments of memories, refers to present reality and can be acted upon (orbitofrontal reality filtering). Whether these memory control processes share common underlying mechanisms is unknown. Failures of both have been held accountable for false memories, including confabulation. Electrophysiological and imaging studies suggest a dissociation but used very different paradigms. In this study, we juxtaposed the requirements of context source monitoring and reality filtering within a unique continuous recognition task, which healthy participants performed while high-resolution evoked potentials were recorded. The mechanisms dissociated both behaviorally and electrophysiologically: Reality filtering induced a frontal positivity, absence of a specific electrocortical configuration, and posterior medial orbitofrontal activity at 200-300 msec. Context source monitoring had no electrophysiological expression in this early period. It was slower and less accurate than reality filtering and induced a prolonged positive potential over frontal leads starting at 400 msec. The study demonstrates a hitherto unrecognized separation between orbitofrontal reality filtering and source monitoring. Whereas deficient orbitofrontal reality filtering is associated with reality confusion in thinking, the behavioral correlates of deficient source monitoring should be verified with controlled experimental exploration.

Two intrinsic coupling types for resting-state integration in the human brain.

Recent findings indicate that synchronous neural activity at rest influences human performance in subsequent tasks. Synchronization can occur in form of phase coupling or amplitude correlation. It is unknown whether these coupling types have differing behavioral significance at rest. To address this, we performed resting-state electroencephalography (EEG) and source connectivity analysis in several populations of healthy subjects and patients with brain lesions. We systematically compared different types and frequencies of neural synchronization and investigated their association with behavioral performance in verbal and spatial attention tasks. Behavioral performance could be consistently predicted by two distinct resting-state coupling patterns: (1) amplitude envelope correlation of beta activity between homologous areas of both hemispheres, (2) lagged phase synchronization in EEG alpha activity between a brain area and the entire cortex. A disruption of these coupling patterns was also associated with neurological deficits in patients with stroke lesions. This suggests the existence of two distinct network systems responsible for resting-state integration. Lagged phase synchronization in the alpha band is associated with global interaction across networks while amplitude envelope correlation seems to be behaviorally relevant for interactions within networks and between hemispheres. These two coupling types may therefore provide complementary insights on brain physiology and pathology.

Neural Correlate of Anterograde Amnesia in Wernicke-Korsakoff Syndrome.

The neural correlate of anterograde amnesia in Wernicke-Korsakoff syndrome (WKS) is still debated. While the capacity to learn new information has been associated with integrity of the medial temporal lobe (MTL), previous studies indicated that the WKS is associated with diencephalic lesions, mainly in the mammillary bodies and anterior or dorsomedial thalamic nuclei. The present study tested the hypothesis that amnesia in WKS is associated with a disrupted neural circuit between diencephalic and hippocampal structures. High-density evoked potentials were recorded in four severely amnesic patients with chronic WKS, in five patients with chronic alcoholism without WKS, and in ten age matched controls. Participants performed a continuous recognition task of pictures previously shown to induce a left medial temporal lobe dependent positive potential between 250 and 350 ms. In addition, the integrity of the fornix was assessed using diffusion tensor imaging (DTI). WKS, but not alcoholic patients without WKS, showed absence of the early, left MTL dependent positive potential following immediate picture repetitions. DTI indicated disruption of the fornix, which connects diencephalic and hippocampal structures. The findings support an interpretation of anterograde amnesia in WKS as a consequence of a disconnection between diencephalic and MTL structures with deficient contribution of the MTL to rapid consolidation.

Post-stroke cognitive impairment remains highly prevalent and disabling despite state-of-the-art stroke treatment.

BACKGROUND: State-of-the-art stroke treatment significantly reduces lesion size and stroke severity, but it remains unclear whether these therapeutic advances have diminished the burden of post-stroke cognitive impairment (PSCI). AIMS: In a cohort of patients receiving modern state-of-the-art stroke care including endovascular therapy, we assessed the frequency of PSCI and the pattern of domain-specific cognitive deficits, identified risk factors for PSCI, and determined the impact of acute PSCI on stroke outcome. METHODS: In this prospective monocentric cohort study, we examined patients with first-ever anterior circulation ischemic stroke without pre-stroke cognitive decline, using a comprehensive neuropsychological assessment ⩽10 days after symptom onset. Normative data were stratified by demographic variables. We defined PSCI as at least moderate (<1.5 standard deviation) deficits in ⩾2 cognitive domains. Multivariable regression analysis was applied to define risk factors for PSCI. RESULTS: We analyzed 329 non-aphasic patients admitted from December 2020 to July 2023 (67.2 ± 14.4 years old, 41.3% female, 13.1 ± 2.7 years of education). Although most patients had mild stroke (median National Institutes of Health Stroke Scale (NIHSS) 24 h = 1.00 (0.00; 3.00); 87.5% with NIHSS ⩽ 5), 69.3% of them presented with PSCI 2.7 ± 2.0 days post-stroke. The most severely and often affected cognitive domains were verbal learning, episodic memory, executive functions, selective attention, and constructive abilities (39.1%-51.2% of patients), whereas spatial neglect was less frequent (18.5%). The risk of PSCI was reduced with more years of education (odds ratio (OR) = 0.47, 95% confidence interval (CI) = 0.23-0.99) and right hemisphere lesions (OR = 0.47, 95% CI = 0.26-0.84), and increased with stroke severity (NIHSS 24 h, OR = 4.19, 95% CI = 2.72-6.45), presence of hyperlipidemia (OR = 1.93, 95% CI = 1.01-3.68), but was not influenced by age. After adjusting for stroke severity and depressive symptoms, acute PSCI was associated with poor functional outcome (modified Rankin Scale > 2, F = 13.695, p < 0.001) and worse global cognition (Montreal Cognitive Assessment (MoCA) score, F = 20.069, p < 0.001) at 3 months post-stroke. CONCLUSION: Despite modern stroke therapy and many strokes having mild severity, PSCI in the acute stroke phase remains frequent and associated with worse outcome. The most prevalent were learning and memory deficits. Cognitive reserve operationalized as years of education independently protects post-stroke cognition.

Network mechanisms of responsiveness to continuous theta-burst stimulation.

Continuous theta-burst stimulation (cTBS) can modify behavior, but effects are inconsistent and their mechanisms insufficiently understood. As coherence in resting-state networks influences human behavior, we hypothesized that cTBS may act via modulation of neural oscillation coherence. This study used electroencephalography (EEG) to investigate whether behavioral effects of cTBS on visuospatial attention are associated with coherence changes in the attention network. In healthy human subjects, cTBS of the right posterior parietal cortex (PPC) and the right frontal eye field was compared with sham stimulation. Effects on visuospatial attention were quantified with a visual exploration task, and network effects were assessed from surface EEG with inverse solutions and source coherence analyses. Before stimulation, left visual exploration was linearly correlated with alpha-band coherence between the right temporo-parietal cortex and the rest of the brain. Posterior parietal cortex stimulation induced neglect-like visual exploration behavior in the majority, but not all, subjects. It reduced alpha-band coherence between the stimulation site and the rest of the brain but also enhanced it between the contralateral left parietal cortex and the rest of the brain. The contralateral increase correlated with the induced reduction in left visual attention. The behavioral response of individual participants to cTBS could be predicted by coherence in the right temporo-parietal junction before stimulation. Behavioral effects of cTBS therefore depend on network states before stimulation and are linearly associated with changes in network interactions. In particular, cTBS modulates an interhemispheric competition in alpha-band coherence. EEG network imaging might help to optimize therapeutic cTBS in the future.

Modulation of environmental reduplicative paramnesia by perceptual experience.

Environmental reduplicative paramnesia (ERP) is characterized by the involuntary attribution of a false identity to a place. ERP has rarely been examined experimentally; its mechanisms therefore remain speculative. Here, we describe a patient with extended traumatic right fronto-temporal damage and severe persistent ERP, in whom we were able to modulate ERP by exposing him to various typical landmarks of the town where he was hospitalized. When landmarks were ambiguous as regards location (e.g., unknown buildings), the patient erroneously localized himself in his hometown, which was more than two thousand kilometers away. In contrast, when he visited distinct landmarks of the place where he actually resided, his ERP was immediately corrected, and spatial orientation was restored. These findings indicate that ERP may be temporarily modifiable through perception of unequivocal topographic information.