The syndrome of Anosognosia for Hemiplegia (AHP) can provide unique insights into the neurocognitive processes of motor awareness. Yet, prior studies have only explored predominately discreet lesions. Using advanced structural neuroimaging methods in 174 patients with a right-hemisphere stroke, we were able to identify three neural systems that contribute to AHP, when disconnected or directly damaged: the (i) premotor loop (ii) limbic system, and (iii) ventral attentional network. Our results suggest that human motor awareness is contingent on the joint contribution of these three systems.

1The rare syndrome of Anosognosia for Hemiplegia (AHP) can provide unique insights into 2 the neurocognitive processes of motor awareness. Yet, prior studies have only explored 3 predominately discreet lesions. Using advanced structural neuroimaging methods in 174 patients with 4 a right-hemisphere stroke, we were able to identify three neural networks that contribute to AHP, 5 when disconnected: the (1) premotor loop (2) limbic system, and (3) ventral attention network. Our 6 results suggest that human motor awareness is contingent on the joint contribution of these three 7 systems. 83 Motor awareness allows individuals to have insight into their motor performance, a 9 fundamental aspect of self-awareness. However, following damage to the right hemisphere, patients 10 with left paralysis may show delusions of intact motor ability, or anosognosia for hemiplegia (AHP, 11 1). Hence, studying AHP offers unique opportunities to explore the neurocognitive mechanisms of 12 motor awareness. 13While early studies regarded AHP as secondary to concomitant spatial deficits such as hemineglect 14 2 caused by parietal lesions, more recent experimental and voxel-based, lesion-symptom mapping 15 (VLSM) results suggest that AHP is an independent syndrome. These earlier studies address AHP as 16 an impairment of action and body monitoring, with lesions to the lateral premotor cortex and the 17 anterior insula (3,4), affecting patients' ability to detect discrepancies between feed-forward motor 18 predictions and sensorimotor feedback. However, these hypotheses are insufficient to explain all the 19 AHP symptoms, such as patients' inability to update their beliefs based on social feedback or more 20 general difficulties experienced in their daily living (5,6). Indeed, others have suggested that AHP 21 can be caused by a functional disconnection between regions processing top-down beliefs about the 22

Stroke significantly impacts quality of life. However, the long-term cognitive evolution in stroke is poorly predictable at the individual level. There is an urgent need for a better prediction of long-term symptoms based on acute clinical neuroimaging data. Previous works have demonstrated a strong relationship between the location of white matter disconnections and clinical symptoms. However, rendering the entire space of possible disconnections-deficit associations optimally surveyable will allow for a systematic association between brain disconnections and cognitive-behavioural measures at the individual level. Here we present the most comprehensive framework, a composite morphospace to predict neuropsychological scores one year after stroke. Linking the latent disconnectome morphospace to neuropsychological outcomes yields biological insights available as the first comprehensive atlas of disconnectome-deficit relations across 86 neuropsychological scores. Out-of-sample prediction derived from this atlas achieved average accuracy over 80%, which is higher than any other framework. Our novel predictive framework is available as an interactive web application, the disconnectome symptoms discoverer (http://disconnectomestudio.bcblab.com), to provide the foundations for a new and practical approach to modelling cognition in stroke. Our atlas and web application will reduce the burden of cognitive deficits on patients, their families, and wider society while also helping to tailor personalized treatment programs and discover new targets for treatments. We expect the range of assessments and the predictive power of our framework to increase even further through future crowdsourcing.

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The diverging evidence for functional localization of response inhibition within the prefrontal cortex might be justified by the still unclear involvement of other intrinsically related cognitive processes like response selection and sustained attention. In this study, the main aim was to understand whether inhibitory impairments, previously found in patients with both left and right frontal lesions, could be better accounted for by assessing these potentially related cognitive processes. We tested 37 brain tumor patients with left prefrontal, right prefrontal and non-prefrontal lesions and a healthy control group on Go/No-Go and Foreperiod tasks. In both types of tasks inhibitory impairments are likely to cause false alarms, although additionally the former task requires response selection and the latter target detection abilities. Irrespective of the task context, patients with right prefrontal damage showed frequent Go and target omissions, probably due to sustained attention lapses. Left prefrontal patients, on the other hand, showed both Go and target omissions and high false alarm rates to No-Go and warning stimuli, suggesting a decisional rather than an inhibitory impairment. An exploratory whole-brain voxel-based lesion-symptom mapping analysis confirmed the association of left ventrolateral and dorsolateral prefrontal lesions with target discrimination failure, and right ventrolateral and medial prefrontal lesions with target detection failure. Results from this study show how left and right prefrontal areas, which previous research has linked to response inhibition, underlie broader cognitive control processes, particularly involved in response selection and target detection. Based on these findings, we suggest that successful inhibitory control relies on more than one functionally distinct process which, if assessed appropriately, might help us to better understand inhibitory impairments across different pathologies.

Neuropsychological disturbances in the sense of limb ownership provide unique opportunities to study the neurocognitive basis of body ownership. Previous small sample studies that showed discrete cortical lesions cannot explain why multisensory, affective, and cognitive manipulations alter disownership symptoms. We tested the novel hypothesis that disturbances in the sense of limb ownership would be associated not only with discrete cortical lesions but also with disconnections of white-matter tracts supporting specific functional networks. We drew on an advanced lesion-analysis and Bayesian statistics approach in 49 right-hemisphere patients (23 with and 26 without limb disownership). Our results reveal that disturbances in the sense of ownership are associated with lesions in the supramarginal gyrus and disconnections of a fronto-insular-parietal network, involving the frontal-insular and frontal inferior longitudinal tracts, confirming previous disconnection hypotheses. Together with previous behavioral and neuroanatomical results, these findings lead us to propose that the sense of body ownership involves the convergence of bottom-up, multisensory integration, and top-down monitoring of sensory salience based on contextual demands.

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Stroke significantly impacts the quality of life. However, the long-term cognitive evolution in stroke is poorly predictable at the individual level. There is an urgent need to better predict long-term symptoms based on acute clinical neuroimaging data. Previous works have demonstrated a strong relationship between the location of white matter disconnections and clinical symptoms. However, rendering the entire space of possible disconnection-deficit associations optimally surveyable will allow for a systematic association between brain disconnections and cognitive-behavioural measures at the individual level. Here we present the most comprehensive framework, a composite morphospace of white matter disconnections (disconnectome) to predict neuropsychological scores 1 year after stroke. Linking the latent disconnectome morphospace to neuropsychological outcomes yields biological insights that are available as the first comprehensive atlas of disconnectome-deficit relations across 86 scores—a Neuropsychological White Matter Atlas. Our novel predictive framework, the Disconnectome Symptoms Discoverer, achieved better predictivity performances than six other models, including functional disconnection, lesion topology and volume modelling. Out-of-sample prediction derived from this atlas presented a mean absolute error below 20% and allowed personalize neuropsychological predictions. Prediction on an external cohort achieved an R2 = 0.201 for semantic fluency. In addition, training and testing were replicated on two external cohorts achieving an R2 = 0.18 for visuospatial performance. This framework is available as an interactive web application (http://disconnectomestudio.bcblab.com) to provide the foundations for a new and practical approach to modelling cognition in stroke. We hope our atlas and web application will help to reduce the burden of cognitive deficits on patients, their families and wider society while also helping to tailor future personalized treatment programmes and discover new targets for treatments. We expect our framework’s range of assessments and predictive power to increase even further through future crowdsourcing.