Anna K. Bonkhoff

Bio: Anna K. Bonkhoff is an academic researcher from Harvard University. The author has contributed to research in topics: Medicine & Stroke (engine). The author has an hindex of 5, co-authored 26 publications receiving 77 citations. Previous affiliations of Anna K. Bonkhoff include Forschungszentrum Jülich & UCL Institute of Neurology.

Acute ischaemic stroke alters the brain's preference for distinct dynamic connectivity states.

Abstract: Acute ischaemic stroke disturbs healthy brain organization, prompting subsequent plasticity and reorganization to compensate for the loss of specialized neural tissue and function. Static resting state functional MRI studies have already furthered our understanding of cerebral reorganization by estimating stroke-induced changes in network connectivity aggregated over the duration of several minutes. In this study, we used dynamic resting state functional MRI analyses to increase temporal resolution to seconds and explore transient configurations of motor network connectivity in acute stroke. To this end, we collected resting state functional MRI data of 31 patients with acute ischaemic stroke and 17 age-matched healthy control subjects. Stroke patients presented with moderate to severe hand motor deficits. By estimating dynamic functional connectivity within a sliding window framework, we identified three distinct connectivity configurations of motor-related networks. Motor networks were organized into three regional domains, i.e. a cortical, subcortical and cerebellar domain. The dynamic connectivity patterns of stroke patients diverged from those of healthy controls depending on the severity of the initial motor impairment. Moderately affected patients (n = 18) spent significantly more time in a weakly connected configuration that was characterized by low levels of connectivity, both locally as well as between distant regions. In contrast, severely affected patients (n = 13) showed a significant preference for transitions into a spatially segregated connectivity configuration. This configuration featured particularly high levels of local connectivity within the three regional domains as well as anti-correlated connectivity between distant networks across domains. A third connectivity configuration represented an intermediate connectivity pattern compared to the preceding two, and predominantly encompassed decreased interhemispheric connectivity between cortical motor networks independent of individual deficit severity. Alterations within this third configuration thus closely resembled previously reported ones originating from static resting state functional MRI studies post-stroke. In summary, acute ischaemic stroke not only prompted changes in connectivity between distinct networks, but it also caused characteristic changes in temporal properties of large-scale network interactions depending on the severity of the individual deficit. These findings offer new vistas on the dynamic neural mechanisms underlying acute neurological symptoms, cortical reorganization and treatment effects in stroke patients.

Female Stroke: Sex Differences in Acute Treatment and Early Outcomes of Acute Ischemic Stroke.

Abstract: Background and purpose Men and women are differently affected by acute ischemic stroke (AIS) in many aspects. Prior studies on sex disparities were limited by moderate sample sizes, varying years of data acquisition, and inconsistent inclusions of covariates leading to controversial findings. We aimed to analyze sex differences in AIS severity, treatments, and early outcome and to systematically evaluate the effect of important covariates in a large German stroke registry. Methods Analyses were based on the Stroke Registry of Northwestern Germany from 2000 to 2018. We focused on admission-stroke severity and disability, acute recanalization treatment, and early stroke outcomes. Potential sex divergences were investigated via odds ratio (OR) using logistic regression models. Covariates were introduced in 3 steps: (1) base models (age and admission year), (2) partially adjusted models (additionally corrected for acute stroke severity and recanalization treatment), (3) fully adjusted models (additionally adjusted for onset-to-admission time interval, prestroke functional status, comorbidities, and stroke cause). Models were separately fitted for the periods 2000 to 2009 and 2010 to 2018. Results Data from 761 106 patients with AIS were included. In fully adjusted models, there were no sex differences with respect to treatment with intravenous thrombolysis (2000-2009: OR, 0.99 [95% CI, 0.94-1.03]; 2010-2018: OR, 1.0 [0.98-1.02]), but women were more likely to receive intraarterial therapy (2010-2018: OR, 1.12 [1.08-1.15]). Despite higher disability on admission (2000-2009: OR, 1.10 [1.07-1.13]; 2010-2018: OR, 1.09 [1.07-1.10]), female patients were more likely to be discharged with a favorable functional outcome (2003-2009: OR, 1.05 [1.02-1.09]; 2010-2018: OR, 1.05 [1.04-1.07]) and experienced lower in-hospital mortality (2000-2009: OR, 0.92 [0.86-0.97]; 2010-2018: OR, 0.91 [0.88-0.93]). Conclusions Female patients with AIS have a higher chance of receiving intraarterial treatment that cannot be explained by clinical characteristics, such as age, premorbid disability, stroke severity, or cause. Women have a more favorable in-hospital recovery than men because their higher disability upon admission was followed by a lower in-hospital mortality and a higher likelihood of favorable functional outcome at discharge after adjustment for covariates.

Outcome after acute ischemic stroke is linked to sex-specific lesion patterns.

Abstract: Acute ischemic stroke affects men and women differently. In particular, women are often reported to experience higher acute stroke severity than men. We derived a low-dimensional representation of anatomical stroke lesions and designed a Bayesian hierarchical modeling framework tailored to estimate possible sex differences in lesion patterns linked to acute stroke severity (National Institute of Health Stroke Scale). This framework was developed in 555 patients (38% female). Findings were validated in an independent cohort (n = 503, 41% female). Here, we show brain lesions in regions subserving motor and language functions help explain stroke severity in both men and women, however more widespread lesion patterns are relevant in female patients. Higher stroke severity in women, but not men, is associated with left hemisphere lesions in the vicinity of the posterior circulation. Our results suggest there are sex-specific functional cerebral asymmetries that may be important for future investigations of sex-stratified approaches to management of acute ischemic stroke.

3D-StyleGAN: A Style-Based Generative Adversarial Network for Generative Modeling of Three-Dimensional Medical Images

Abstract: Image synthesis via Generative Adversarial Networks (GANs) of three-dimensional (3D) medical images has great potential that can be extended to many medical applications, such as, image enhancement and disease progression modeling. Current GAN technologies for 3D medical image synthesis must be significantly improved to be suitable for real-world medical problems. In this paper, we extend the state-of-the-art StyleGAN2 model, which natively works with two-dimensional images, to enable 3D image synthesis. In addition to the image synthesis, we investigate the behavior and interpretability of the 3D-StyleGAN via style vectors inherited form the original StyleGAN2 that are highly suitable for medical applications: (i) the latent space projection and reconstruction of unseen real images, and (ii) style mixing. The model can be applied to any 3D volumetric images. We demonstrate the 3D-StyleGAN’s performance and feasibility with \(\sim \)12,000 three-dimensional full brain MR T1 images. Furthermore, we explore different configurations of hyperparameters to investigate potential improvement of the image synthesis with larger networks. The codes and pre-trained networks are available online: https://github.com/sh4174/3DStyleGAN.

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

Abstract: 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.

Trends in cognitive sciences

Abstract: Preface The Effects of Acute, Chronic & Withdrawal from Chronic Ethanol on Emotional Learning Enhanced Odorant Preference Associative Learning in C. Elegans with Protein Kinase C-Interactive Protein (PKCI)/Hint1 Mutation Brain Derives Neurotrophic Factor (BDNF) & Adult Neurogenesis Neural Mechanisms for Expertise in Mental Imagery Language Processing Across Modalities: Insights from Bimodal Bilingualism Exploiting the Relationship of Natural Language & Computer Science: A Novel Theoretical Approach to Fairness Zero Power & Selflessness: What Meditation & Conscious Perception Have in Common Early Memories of Children & Adults: Implications for Infantile Amnesia APOE ? 4 Allele & Alheimer's Disease: Perspectives on AD Pathogenesis & Therapy The "Egocentric" Americans? Long-Term Memory for Public Events in Five Countries Ecological Validity & the Study of Procedural & Episodic Memory Function in Songbirds Need Dendritic Spines? There's an APP for That Cholesterol & Neuronal Susceptibility to Beta-Amyloid Toxicity Index.

Recovery from stroke: current concepts and future perspectives

Abstract: 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.

Post-Stroke Cognitive Impairment and Dementia

Abstract: Poststroke cognitive impairment and dementia (PSCID) is a major source of morbidity and mortality after stroke worldwide. PSCID occurs as a consequence of ischemic stroke, intracerebral hemorrhage, or subarachnoid hemorrhage. Cognitive impairment and dementia manifesting after a clinical stroke is categorized as vascular even in people with comorbid neurodegenerative pathology, which is common in elderly individuals and can contribute to the clinical expression of PSCID. Manifestations of cerebral small vessel disease, such as covert brain infarcts, white matter lesions, microbleeds, and cortical microinfarcts, are also common in patients with stroke and likewise contribute to cognitive outcomes. Although studies of PSCID historically varied in the approach to timing and methods of diagnosis, most of them demonstrate that older age, lower educational status, socioeconomic disparities, premorbid cognitive or functional decline, life-course exposure to vascular risk factors, and a history of prior stroke increase risk of PSCID. Stroke characteristics, in particular stroke severity, lesion volume, lesion location, multiplicity and recurrence, also influence PSCID risk. Understanding the complex interaction between an acute stroke event and preexisting brain pathology remains a priority and will be critical for developing strategies for personalized prediction, prevention, targeted interventions, and rehabilitation. Current challenges in the field relate to a lack of harmonization of definition and classification of PSCID, timing of diagnosis, approaches to neurocognitive assessment, and duration of follow-up after stroke. However, evolving knowledge on pathophysiology, neuroimaging, and biomarkers offers potential for clinical applications and may inform clinical trials. Preventing stroke and PSCID remains a cornerstone of any strategy to achieve optimal brain health. We summarize recent developments in the field and discuss future directions closing with a call for action to systematically include cognitive outcome assessment into any clinical studies of poststroke outcome.

The Impact of Sex and Gender on Stroke

Abstract: Women face a disproportionate burden of stroke mortality and disability. Biologic sex and sociocultural gender both contribute to differences in stroke risk factors, assessment, treatment, and outcomes. There are substantial differences in the strength of association of stroke risk factors, as well as female-specific risk factors. Moreover, there are differences in presentation, response to treatment, and stroke outcomes in women. This review outlines current knowledge of impact of sex and gender on stroke, as well as delineates research gaps and areas for future inquiry.