As data analysis pipelines grow more complex in brain imaging research, understanding how methodological choices affect results is essential for ensuring reproducibility and transparency. This is especially relevant for functional Near-Infrared Spectroscopy (fNIRS), a rapidly growing technique for assessing brain function in naturalistic settings and across the lifespan, yet one that still lacks standardized analysis approaches. In the fNIRS Reproducibility Study Hub (FRESH) initiative, we asked 38 research teams worldwide to independently analyze the same two fNIRS datasets. Despite using different pipelines, nearly 80% of teams agreed on group-level results, particularly when hypotheses were strongly supported by literature. Teams with higher self-reported analysis confidence, which correlated with years of fNIRS experience, showed greater agreement. At the individual level, agreement was lower but improved with better data quality. The main sources of variability were related to how poor-quality data were handled, how responses were modeled, and how statistical analyses were conducted. These findings suggest that while flexible analytical tools are valuable, clearer methodological and reporting standards could greatly enhance reproducibility. By identifying key drivers of variability, this study highlights current challenges and offers direction for improving transparency and reliability in fNIRS research.

Motor cortical high-gamma oscillations (60-90 Hz) occur at movement onset and are spatially focused over the contralateral primary motor cortex. Although high-gamma oscillations are widely recognized for their significance in human motor control, their precise function on a cortical level remains elusive. Importantly, their relevance in human stroke pathophysiology is unknown. Because motor deficits are fundamental determinants of symptom burden after stroke, understanding the neurophysiological processes of motor coding could be an important step in improving stroke rehabilitation. We recorded magnetoencephalography data during a thumb movement rate task in 14 chronic stroke survivors, 15 age-matched control participants and 29 healthy young participants. Motor cortical high-gamma oscillations showed a strong relation with movement rate as trials with higher movement rate were associated with greater high-gamma power. Although stroke survivors showed reduced cortical high-gamma power, this reduction primarily reflected the scaling of high-gamma power with movement rate, yet after matching movement rate in stroke survivors and age-matched controls, the reduction of high-gamma power exceeded the effect of their decreased movement rate alone. Even though motor skill acquisition was evident in all three groups, it was not linked to high-gamma power. Our study quantifies high-gamma oscillations after stroke, revealing a reduction in movement-related high-gamma power. Moreover, we provide strong evidence for a pivotal role of motor cortical high-gamma oscillations in encoding movement rate. KEY POINTS: Neural oscillations in the high-gamma frequency range (60-90 Hz) emerge in the human motor cortex during movement. The precise function of these oscillations in motor control remains unclear, and they have never been characterized in stroke survivors. In a magnetoencephalography study, we demonstrate that high-gamma oscillations in motor cortical areas scale with movement rate, and we further explore their temporal and spatial characteristics. Stroke survivors exhibit lower high-gamma power during movement than age-matched control participants, even after matching for movement rate. The results contribute to the understanding of the role of high-gamma oscillations in motor control and have important implications for neuromodulation in stroke rehabilitation.

BACKGROUND:Parkinson's disease (PD) is a system-level disorder that implicates brain network dynamics across multiple scales. Detecting the 'arrow of time', or temporal reversibility of the brain's information processing flow enables quantification of equilibrium in the brain and inferences on the hierarchical organization. Therefore we aimed to explore disturbances in resting-state equilibrium levels as well as changes in the hierarchical organization due to PD. METHODS:Structural and functional MRI of 29 PD patients and 19 healthy controls were acquired and analyzed. Empirical non-reversibility was computed as the distance between time-shifted forward- and artificially-reversed time series. Levels of equilibrium were subsequently assessed globally and within two cortico-subcortical motor networks implicated in PD. Moreover, whole-brain generative computational models consisting of 1051 Hopf oscillators were constructed to evaluate effective connectivities and alterations of the functional hierarchical organization. RESULTS:We found that PD is characterized by disrupted equilibrium regimes, marked by distinct effective connectivity patterns, particularly within the motor networks. Additionally, we observed a flatter hierarchical organization in PD, with the cerebellum and thalamus exerting increased influence. CONCLUSION:The arrow of time methodology effectively identifies distinct and informative characteristics of PD. Our analyses suggest that PD shifts the brain towards less efficient, non-equilibrium dynamics that impair intrinsic flexibility and disrupt motor coordination. Thus, these findings not only provide insight into widespread system alterations in PD that could serve as potential biomarkers, but also lay the groundwork for next-generation stimulation techniques aimed at restoring balance in the Parkinsonian brain.

Objective: Since the development of new deep brain stimulation (DBS) devices in recent years, there is an increased need for assessing the safety of the combination with transcranial magnetic stimulation (TMS). Methods: We applied a combined ex vivo and computational approach to investigate the safety of TMS using a Boston Scientific segmented electrode. TMS-induced current was measured between the electrode and lead extension, using different TMS coil positions (center, off-center right, off-center left) and numbers of loops of the DBS lead (no loop, one loop, two loops). The same TMS-DBS conditions were simulated on an individual head model of a DBS patient and exposure of the lead to the electric field and induced currents were analyzed. Results: TMS-induced currents ex vivo varied between 16 and 165 mA with different combinations of coil positions and loops. The highest current was measured in the off-center condition with two loops. In the same condition, the simulation revealed an induced current as high as 93 mA. Conclusions: TMS-induced current can lead to excessive stimulation through the DBS lead and thus exceed safety limits. Significance: The present findings pose a safety concern for the application of TMS in patients with new generation DBS electrodes. Research Category and Technology and Methods Translational Research: 10. Transcranial Magnetic Stimulation (TMS) Keywords: DBS, TMS, electric field, finite-element simulation

BACKGROUND:Neuroscience research has contributed significantly to understanding alterations in brain structure and function after ischemic stroke. Technical limitations have excluded the spinal cord from imaging-based research. Available data are restricted to a few microstructural analyses, and functional connectivity data are absent. The present study attempted to close this knowledge gap and assess alterations in corticospinal coupling in chronic stroke and their relation to motor deficits. METHODS:In this cross-sectional study, patients with chronic stroke and healthy controls underwent corticospinal functional magnetic resonance imaging while performing a simple force generation task at the University Medical Center Hamburg-Eppendorf between September 2021 and June 2023. Task-related activation was localized in the ipsilesional ventral premotor cortex, the supplementary motor area, and the cervical spinal cord. Psycho-physiological interactions and linear modeling were used to infer functional connectivity between cortical motor regions and the cervical spinal cord and their associations with clinical scores. RESULTS:Thirteen well-recovered patients with stroke (1 woman, 12 men; mean age, 62.6 years; mean time after stroke: 47.6 months) and 13 healthy controls (5 women, 8 men; mean age, 64.5 years) were included. The main finding was that ventral premotor cortex and supplementary motor area showed topographically distinct alterations in their connectivity with the spinal cord. Specifically, we found a reduced coupling between the supplementary motor area and the ipsilateral ventral spinal cord and an enhanced coupling between the ventral premotor cortex and ventral and intermediate central spinal zones. Lower supplementary motor area and higher ventral premotor cortex-related spinal cord couplings were correlated with residual deficits. CONCLUSIONS:This work provides first-in-human functional insights into stroke-related alterations in the functional connectivity between cortical premotor areas and the spinal cord, suggesting that different premotor areas and spinal neuronal assemblies might be involved in coupling changes. It adds a novel, promising approach to better understanding stroke recovery and developing innovative models to comprehend treatment strategies with spinal cord stimulation.

Background: The effects of intravenous alteplase in patients with prior antiplatelet therapy (APT) remain controversial. We aimed to assess the efficacy and safety of imaging-based intravenous alteplase in patients with unknown onset stroke with prior APT. Methods: Data from randomized controlled trials comparing alteplase with placebo/standard care in patients with unknown onset acute ischemic stroke from the Evaluation of Unknown Onset Stroke Thrombolysis (EOS) individual patient data meta-analysis collaboration were analyzed. Favorable outcome was defined as a modified Rankin Scale score of 0–1 at 90 days post-stroke. Safety outcomes included symptomatic intracranial hemorrhage (sICH) at 22–36 h and 90-day mortality. Results: Overall, 780 patients had available baseline data on prior APT. Compared with the no prior APT group (n = 523), the prior APT group (n = 257) was older (72 vs. 66 years) and had a higher prevalence of vascular risk factors. There was no interaction between prior APT and treatment effects of alteplase (p for interaction = 0.23). In the prior APT patients, 55/125 (45%) patients in the alteplase group and 39/132 (30%) patients in the control group had a favorable outcome (adjusted odds ratio [aOR], 2.07 [95% confidence interval, 1.18–3.64]). The rates of sICH and mortality in the alteplase and control groups were 5.6% and 0.8% (aOR, 7.78 [0.94–63.37]) and 6.5% and 6.1% (aOR, 1.12 [0.38–3.36]), respectively. In the no prior APT patients, 136 patients (50%) in the alteplase group and 112 patients (45%) in the control group had a favorable outcome (aOR, 1.39 [0.94–2.05]). Safety outcomes were not significantly different between the groups (sICH: 3 [1.1%] vs. 1 [0.4%]; mortality: 13 [4.9%] vs. 3 [1.2%]). Conclusions: Alteplase has consistent efficacy regardless of prior APT in patients with unknown onset stroke. In addition, prior APT does not significantly increase the risk of sICH or mortality.

Cognitive aging is a heterogeneous process characterized by a varied decline in brain performance. While the neurophysiological basis of this decline remains poorly understood, age-related alterations in structural connectivity (SC) and functional connectivity (FC) have been implicated. Understanding the relationship between these changes is crucial for identifying early markers of cognitive impairment. In our previous work, we observed that in healthy older adults, diminished performance in a tactile recognition task was associated with reduced fractional anisotropy (FA) in the anterior corpus callosum (aCC). The aim of this study was to investigate the impact of this age-related SC degeneration on the FC between the connected regions. In the current analysis, we examined resting-state functional MRI data from 29 healthy older adults, who were categorized into two subgroups - high and low performers - based on their performance in a tactile recognition task and a younger control group (N = 20). We conducted a region of interest (ROI) to ROI analysis to evaluate FC between frontal regions connected via the aCC. Subsequently, we compared the FC between the groups and assessed its correlation with FA values in the aCC across all older participants based on a TBSS analysis from our previous work. We found that poorer performance in a tactile recognition task was associated with increased FC between frontal regions. The second main finding was a negative correlation between FA in the aCC and FC between frontal regions. Our findings suggest that structural degradation of the underlying pathways may initially lead to increased FC within the connected regions, possibly as a compensatory mechanism to preserve cognitive function. However, as no direct brain–behavior correlation was assessed, this interpretation remains tentative. The aCC appears to be particularly vulnerable to age-related structural decline, which may underlie functional changes in frontal regions observed with aging.

White matter hyperintensities of presumed vascular origin (WMH) are associated with various clinical sequelae. In stroke patients, the total WMH burden is linked to recurrent cerebrovascular events and worse clinical outcomes. As WMH also affect the integrity of large-scale structural brain networks, we hypothesize that the extent of WMH-related network damage carries relevant information to explain outcome variability in addition to global WMH volume. Clinical and structural brain imaging data of 33 severely affected acute stroke patients were analyzed from two independent cohorts. Imaging data were acquired within the first two weeks after stroke. WMH-related localized and global network damage was derived. WMH network effects were differentially assessed for total, periventricular (pWMH), and deep WMH (dWMH). Using ordinal logistic regression analyses, network damage was associated with functional outcome at follow-up after three to six months. WMH were linked to a significant disconnection of multiple cortical and subcortical brain regions. Global and localized pWMH-related network damage affecting distinct brain regions of both hemispheres were independently associated with a worse outcome after adjustment for baseline symptom burden, age, brain infarct volume, and total WMH volume. Total and dWMH-related network disturbances did not show similar associations. This study indicates that pWMH-related network damage affecting specific brain regions is linked to functional outcome in acute stroke patients. It underscores the potential significance of pre-existing WMH-related network damage as a crucial factor in comprehending outcome variability after severe stroke.

Significance:A shared understanding of terminology is essential for clear scientific communication and minimizing misconceptions. This is particularly challenging in rapidly expanding, interdisciplinary domains that utilize functional near-infrared spectroscopy (fNIRS), where researchers come from diverse backgrounds and apply their expertise in fields such as engineering, neuroscience, and psychology. Aim:The fNIRS Glossary Project was established to develop a community-sourced glossary covering key fNIRS terms, including those related to the continuous-wave (CW), frequency-domain (FD), and time-domain (TD) NIRS techniques. Approach:The glossary was collaboratively developed by a diverse group of 76 fNIRS researchers, representing a wide range of career stages (from PhD students to experts) and disciplines. This collaborative process, structured across five phases, ensured the glossary's depth and comprehensiveness. Results:The glossary features over 300 terms categorized into six key domains: analysis, experimental design, hardware, neuroscience, mathematics, and physics. It also includes abbreviations, symbols, synonyms, references, alternative definitions, and figures where relevant. Conclusions:The fNIRS glossary provides a community-sourced resource that facilitates education and effective scientific communication within the fNIRS community and related fields. By lowering barriers to learning and engaging with fNIRS, the glossary is poised to benefit a broad spectrum of researchers, including those with limited access to educational resources.

Introduction: The effects of imaging-based intravenous thrombolysis on outcomes based on patient sex remain unclear. We aimed to investigate whether outcomes among patients with stroke with an unknown onset time and treated with imaging-based intravenous thrombolysis are influenced by their sex.Patients and Methods: This study was a pooled analysis of individual patient-level data acquired from the Evaluation of unknown Onset Stroke thrombolysis trials. Patients treated with imaging-based intravenous thrombolysis for stroke with an unknown onset time were included. The primary outcome was a favourable outcome (modified Rankin Scale score 0-1) at 90 days. The sex-based difference in outcomes was studied using mixed-effect logistic or ordinal regression models, considering potential heterogeneity across trials.Results: Out of 509 patients in total, 204 (40.1%) were women. Compared with men, women were older and more likely to have atrial fibrillation. Baseline National Institutes of Health Stroke Scale score was higher and hours from last-known-well to treatment were longer for women than for men. Favourable outcomes occurred less often among women than among men. However, multivariate adjustment revealed a non-significant association between female sex and favourable outcome (adjusted odds ratio: 1.04 [95% confidence interval: 0.66-1.52], p = 0.98).Discussion and conclusion: Pooled data from the included clinical trials showed that women with ischaemic stroke with an unknown onset time had worse functional outcomes following imaging-based intravenous thrombolysis than did men. However, this sex-based difference can be explained by the higher age and more severe clinical status at onset among women.

BACKGROUND AND OBJECTIVES:Data from randomized trials on the treatment effect of pure thrombolysis in patients with vessel occlusion are lacking. We examined data from a corresponding subsample of patients from the multicenter, randomized, placebo-controlled WAKE-UP trial to determine whether MRI-guided IV thrombolysis with alteplase in unknown-onset ischemic stroke benefits patients presenting with vessel occlusion. METHODS:Patients with an acute ischemic lesion visible on MRI diffusion-weighted imaging but no marked parenchymal hyperintensity on fluid-attenuated inversion recovery images were randomized to treatment with IV alteplase or placebo. The primary end point was a favorable outcome defined by a modified Rankin Scale score of 0-1 at 90 days after stroke. We investigated the interaction between vessel status and treatment effect using an unconditional logistic regression model. Treatment effects (adjusted odds ratio [aOR]) and their 95% CI were compared in patients with and without any vessel occlusion (AVO) and large vessel occlusion (LVO). RESULTS:185 patients (mean age 64.5 years, 46% female, median NIH Stroke Scale score 9, median time between last seen well and MRI 10.26 hours) received treatment and presented with an occlusion. 98 (20%) had LVO (defined as occlusion of the internal carotid artery, middle cerebral artery trunk, or combination). A favorable outcome was observed in 30 of 94 patients with AVO (31.9%) in the alteplase group and in 18 of 91 (19.8%) in the placebo group (aOR 2.04, 95% CI 1.00-4.18). In the subgroup of patients with LVO, a favorable outcome was observed in 16 of 53 (30.2%) in the alteplase group and in 7 of 44 (15.9%) in the placebo group (aOR 2.08, 95% CI 0.71-6.10). Treatment with alteplase was associated with higher odds of favorable outcomes with no heterogeneity of treatment effect between patients with AVO and patent vessel (p = 0.56), or between patients with and without LVO (p = 0.69). DISCUSSION:Although the WAKE-UP study was not powered to demonstrate treatment efficacy in patient subpopulations, this subgroup analysis points to a benefit of MRI-guided thrombolysis in patients with unknown-onset ischemic stroke, independent of vessel occlusion. CLINICAL TRIAL REGISTRATION:Registered at ClinicalTrials.gov with unique identifier NCT01525290 (clinicaltrials.gov/study/NCT01525290). The study was first posted on February 2, 2012; the first patient was enrolled on September 24, 2012. CLASSIFICATION OF EVIDENCE:This study provides Class II evidence that for patients with unknown-onset ischemic stroke with AVO, MRI-guided treatment with IV tissue plasminogen activator improves outcomes.

Introduction: Endovascular thrombectomy stands as a pivotal component in the standard care for patients experiencing acute ischemic stroke with large vessel occlusion. Subsequent care for patients often extends to a neurological intensive care unit. While fluid management is integral to intensive care, the association between early fluid balance and neurological and functional outcomes post-thrombectomy has not yet been thoroughly investigated. Methods: In a retrospective analysis of an observational, single-center study spanning from 2015 to 2021 at the University Medical Center Hamburg-Eppendorf, Germany, we enrolled stroke patients who underwent thrombectomy and received subsequent treatment in the ICU. Unfavorable functional and neurological outcome was defined as a mRS > 2 on day 90 after admission (mRS d90) or NIHSS > 5 at discharge, respectively. A multivariate regression model, adjusting for confounders, utilized the average fluid balance in the first 5 days to predict outcomes. Patients were dichotomized by their average fluid balance (>1 L vs <1 L) within the first 5 days, and a multivariate mRS d90 shift analysis was conducted after adjusting for covariates. Results: Between 2015 and 2021, 1252 patients underwent thrombectomy, and 553 patients met the inclusion criteria (299 women [54%]). Unfavorable functional outcome was significantly associated with a higher daily average fluid balance in the first 5 days in the ICU (mRS d90 ⩽ 2: 0.3 ± 0.5 L, mRS d90 > 2: 0.7 ± 0.7 L, p = 0.02). The same association was observed for the NIHSS at discharge (NIHSS ⩽ 5: 0.3 ± 0.5 L; NIHSS > 5: 0.6 ± 0.6 L; p = 0.03). The mRS d90 shift analysis revealed significance for patients with an average fluid balance <1 L for better functional outcomes (adjusted odds ratio [AOR] 2.17; 95% confidence interval [CI] 1.54–3.07; p < 0.01). Discussion: Fluid retention in post-thrombectomy stroke patients in the ICU is associated with poorer functional and neurological outcomes. Consequently, fluid retention emerges as an additional potential predictor for post-intervention stroke outcomes. Our findings provide an initial indication that preventing excessive fluid retention in stroke patients after endovascular thrombectomy could be beneficial for both functional and neurological recovery. Therefore, fluid retention might be an element to consider in optimizing fluid management for stroke patients.

Study Objectives:The association of shift work (SW) and disrupted circadian rhythm with markers of large artery atherosclerosis and cerebral small vessel disease is uncertain. We aimed to study the separate association of current and former SW with these markers. Methods:We included participants from the population-based Hamburg City Health Study. SW was defined by monthly working hours between 06:00 pm and 07:00 am containing night shifts for at least 12 months. Cross-sectional data were obtained from structured questionnaires, laboratory analyses, physical examinations, brain magnetic resonance imaging, and carotid ultrasound. We performed multivariable regression analysis with carotid intima-media thickness (CIMT), and peak-width skeletonized mean diffusivity (PSMD) as dependent variables. Results:Three hundred and forty-four current, 238 former, and 7162 never-shift workers were included. The median age was 60 years for both current and former shift workers, and total duration of SW was comparable for the two groups. Current shift workers were less frequently female (27.3% vs. 44.5%; p < .001), had more frequent hyperlipidemia (31.5% vs. 22.3%; p = .024), and diabetes (16.2% vs. 3.2%; p < .001). After adjustment for age and sex, reduced quality of sleep (β = 1.61, p = .001) and low education (β = 2.63, p < .001) were associated with current but not former SW. Adjusted for age and sex, the current SW was associated with higher CIMT (β = 0.02, p = .001) and PSMD (β = 9.06e-06, p = .006), whereas former SW was not. Adjusted for risk factors, current SW remained associated with PSMD (β = 9.91e-06, p = .006) but not with CIMT. Conclusions:Current SW was associated with CIMT and with PSMD, with the latter association remaining after adjustment for risk factors. Former SW showed no associations with CIMT or PSMD. This may indicate that current SW is linked with increased neurovascular risk through disrupted circadian rhythms. Trial Registration Information:The trial was submitted at http://www.clinicaltrials.gov, under NCT03934957 on January 4, 2019. The first participant was enrolled in February 2016.

Introduction: Lacunar stroke represents around a quarter of all ischemic strokes, however, their identification with Computed Tomography in the hyperacute setting is challenging. We aimed to validate a clinical score to identify lacunar stroke in the acute setting, independently, with data from the WAKE-UP trial using magnetic resonance imaging. Methods: We analysed data from the WAKE-UP trial and extracted Oxfordshire Community Stroke Project (OCSP) classification. Lacunar score was defined by NIHSS<7 and OCSP lacunar syndrome. Assessment of lacunar infarct by two independent investigators was blinded to clinical data. We calculated sensitivity, specificity, negative and positive predictive value (NPV and PPV, respectively) of lacunar score. Results: We included 503 patients in the analysis, mean (±SD) age 65.2 (±11.6), 325 (65%) males, median (IQR) NIHSS=6 (4-9); 108 (22%) lacunar infarcts were identified on MR, patients fulfilling lacunar score criteria were 120 (24%), of which 47 (44%) had a lacunar infarct. Lacunar score correctly identified 322 (82%) of patients without lacunar infarct. Patients with lacunar score had lower NIHSS (4 vs 7,p<0.001), higher systolic (157 mmHg vs 151 mmHg,p=0.001) and diastolic (86 mmHg vs 83 mmHg,p=0.013) blood pressure and smaller infarct volume (2.4 ml vs 9.5 ml,p<0.001). Performance of lacunar score was: sensitivity 0.44; specificity 0.82; PPV 0.39; NPV 0.84; accuracy 0.73. Assuming a prevalence of lacunar stroke of 13%, PPV lowered to 0.30 but NPV was 0.90. Lacunar score performed better for supratentorial lacunar infarcts. Conclusions: Lacunar score had a very good specificity and NPV for screening of lacunar stroke. Implementation of this simple tool into clinical practice may help hyperacute management and guide patient selection in clinical trials.

The concept of brain reserve capacity has emerged in stroke recovery research in recent years. Imaging-based biomarkers of brain health have helped to better understand outcome variability in clinical cohorts. Still, outcome inferences are far from being satisfactory, particularly in patients with severe initial deficits. Neurorehabilitation after stroke is a complex process, comprising adaption and learning processes, which, on their part, are critically influenced by motivational and reward-related cognitive processes. Amongst others, dopaminergic neurotransmission is a key contributor to these mechanisms. The question arises, whether the amount of structural reserve capacity in the dopaminergic system might inform about outcome variability after severe stroke. For this purpose, this study analysed imaging and clinical data of 42 severely impaired acute stroke patients. Brain volumetry was performed within the first 2 weeks after the event using the Computational Anatomy Toolbox CAT12, grey matter volume estimates were collected for seven key areas of the human dopaminergic system along the mesocortical, mesolimbic and nigrostriatal pathways. Ordinal logistic regression models related regional volumes to the functional outcome, operationalized by the modified Rankin Scale, obtained 3-6 months after stroke. Models were adjusted for age, lesion volume and initial impairment. The main finding was that larger volumes of the amygdala and the nucleus accumbens at baseline were positively associated with a more favourable outcome. These data suggest a link between the structural state of mesolimbic key areas contributing to motor learning, motivational and reward-related brain networks and potentially the success of neurorehabilitation. They might also provide novel evidence to reconsider dopaminergic interventions particularly in severely impaired stroke patients to enhance recovery after stroke.

Magnetic resonance imaging (MRI) and MRI based computational modelling studies provide insights into severity and recovery of ischemic stroke patients. The presence of brain lesions, however, can heavily distort and impair state-of-the-art processing frameworks due to abnormal intensity values and tissue distortions. In this study, we introduce and validate the novel "Lesion Aware automated Processing Pipeline (LeAPP)." LeAPP automatically processes clinical stroke MRI data while significantly reducing the impact of pathological artefacts on processing outputs such as structural and functional connectomes (SC, FC). This helps to advance the identification of biomarkers for recovery and mechanism-based intervention planning using MRI as well as computational approaches. We extended existing frameworks, such as the Human Connectome Project (HCP) minimal processing pipeline, introducing correction steps, and implementing and modifying functional and diffusion processing to cope with MRI acquisition protocols more typical for the clinical context. A total of 51 participants (36 patients, 15 age-matched controls) were processed across four time points for patients (3-5, 30-40, 85-95, 340-380 days after stroke onset) and one time point for controls. We validated performance using artificial lesioned brains (N = 81), derived from healthy brains and informed by real stroke lesions. The quality of reconstructing the ground truth was quantified on whole brain level and for lesion affected and unaffected regions-of-interest (ROIs) for brain parcellations and for SCs. Volume based agreement was evaluated using metrics such as dice coefficient, volume difference or ROI center-of-gravity distance while SC based agreement was defined as the difference in network metrics (e.g., node strength, clustering coefficient, or centrality). The observed deviations in reconstructed ground truth brain parcellations and structural connectomes from lesioned brains were significantly reduced for LeAPP, compared to the performance of existing pipelines such as HCP minimal processing pipeline. For instance, in the case of lesion affected ROIS we achieved a mean dice coefficient (where a value of one represents total agreement as defined by an exact overlap of both ROIs) of 0.81 with LeAPP, compared to 0.75 for HCP (p < .0001*). Additionally, the average measured ROI distance (where a value of zero represents no difference) for lesion ROIs was 0.87 for LeAPP in contrast to 1.7 for HCP (p < .0001*), indicating an overall superior performance of LeAPP. The pipeline generates standardized output files ready for brain network modelling for instance with The Virtual Brain software. This novel open-source automated processing framework contributes to reproducible research and provides a robust framework for automated processing of clinical stroke MRI data, supporting the identification of brain network-based biomarkers of stroke recovery.

Significance:The increasing sample sizes and channel densities in functional near-infrared spectroscopy (fNIRS) necessitate precise and scalable identification of signals that do not permit reliable analysis to exclude them. Despite the relevance of detecting these "bad channels," little is known about the behavior of fNIRS detection methods, and the potential of unsupervised and semi-supervised machine learning remains unexplored. Aim:We developed three novel machine learning-based detectors, unsupervised, semi-supervised, and hybrid NiReject, and compared them with existing approaches. Approach:We conducted a systematic literature search and demonstrated the influence of bad channel detection. Based on 29,924 signals from two independently rated datasets and a simulated scenario space of diverse phenomena, we evaluated the NiReject models, six of the most established detection methods in fNIRS, and 11 prominent methods from other domains. Results:Although the results indicated that a lack of proper detection can strongly bias findings, detection methods were reported in only 32% of the included studies. Semi-supervised models, specifically semi-supervised NiReject, outperformed both established thresholding-based and unsupervised detectors. Hybrid NiReject, utilizing a human feedback loop, addressed the practical challenges of semi-supervised methods while maintaining precise detection and low rating effort. Conclusions:This work contributes toward more automated and reliable fNIRS signal quality control by comprehensively evaluating existing and introducing novel machine learning-based techniques and outlining practical considerations for bad channel detection.