Cognitive deficits affect over 70% of stroke survivors, yet the mechanisms by which multiple small ischemic events contribute to cognitive decline remain poorly understood. In this study, we employed chronic two-photon calcium imaging to longitudinally track the fate of individual neurons in the hippocampus of mice navigating a virtual reality environment, both before and after inducing brain-wide microstrokes. Our findings reveal that, under normal conditions, hippocampal neurons exhibit varying degrees of stability in their spatial memory coding. However, microstrokes disrupted this functional network architecture, leading to cognitive impairments. Notably, the preservation of stable coding place cells, along with the stability, precision, and persistence of the hippocampal network, was strongly predictive of cognitive outcomes. Mice with more synchronously active place cells near important locations demonstrated recovery from cognitive impairment. This study uncovers critical cellular responses and network alterations following brain injury, providing a foundation for novel therapeutic strategies preventing cognitive decline.

Alzheimer's disease (AD) and vascular dementia (VaD) together contribute to almost 90 % of all dementia cases leading to major health challenges of our time with a substantial global socioeconomic burden. While in AD, the improved understanding of Amyloid beta (Aß) mismetabolism and tau hyperphosphorylation as pathophysiological hallmarks has led to significant clinical breakthroughs, similar advances in VaD are lacking. After comparing the clinical presentation, including risk factors, disease patterns, course of diseases and further diagnostic parameters for both forms of dementia, we highlight the importance of shared pathomechanisms found in AD and VaD: Endothelial damage, blood brain barrier (BBB) breakdown and hypoperfusion inducing oxidative stress and inflammation and thus trophic uncoupling in the neurovascular unit. A dysfunctional endothelium and BBB lead to the accumulation of neurotoxic molecules and Aß through impaired clearance, which in turn leads to neurodegeneration. In this context we discuss possible neuropathological parameters, which might serve as biomarkers and thus improve diagnostic accuracy or reveal targets for novel therapeutic strategies for both forms of dementia.

Summarize preclinical data on Anti-Nogo-A antibodies, NgR1 decoy receptor and antagonists of Nogo/NgR1 signaling in stroke recovery and to examine whether results favor additional clinical studies in stroke.

Antibody delivery to the CNS remains a huge hurdle for the clinical application of antibodies targeting a CNS antigen. The blood-brain barrier and blood-CSF barrier restrict access of therapeutic antibodies to their CNS targets in a major way. The very high amounts of therapeutic antibodies that are administered systemically in recent clinical trials to reach CNS targets are barely viable cost-wise for broad, routine applications. Though global CNS delivery of antibodies can be achieved by intrathecal application, these procedures are invasive. A non-invasive method to bring antibodies into the CNS reliably and reproducibly remains an important unmet need in neurology. In the present study, we show that intranasal application of a mouse monoclonal antibody against the neurite growth-inhibiting and plasticity-restricting membrane protein Nogo-A leads to a rapid transfer of significant amounts of antibody to the brain and spinal cord in intact adult rats. Daily intranasal application for 2 wk of anti-Nogo-A antibody enhanced growth and compensatory sprouting of corticofugal projections and functional recovery in rats after large unilateral cortical strokes. These findings are a starting point for clinical translation for a less invasive route of application of therapeutic antibodies to CNS targets for many neurological indications.

Object recognition tests are widely used in neuroscience to assess memory function in rodents. Despite the experimental simplicity of the task, the interpretation of behavioural features that are counted as object exploration can be complicated. Thus, object exploration is often analysed by manual scoring, which is time-consuming and variable across researchers. Current software using tracking points often lacks precision in capturing complex ethological behaviour. Switching or losing tracking points can bias outcome measures. To overcome these limitations we developed “EXPLORE”, a simple, ready-to use and open source pipeline. EXPLORE consists of a convolutional neural network trained in a supervised manner, that extracts features from images and classifies behaviour of rodents near a presented object. EXPLORE achieves human-level accuracy in identifying and scoring exploration behaviour and outperforms commercial software with higher precision, higher versatility and lower time investment, in particular in complex situations. By labeling the respective training data set, users decide by themselves, which types of animal interactions on objects are in- or excluded, ensuring a precise analysis of exploration behaviour. A set of graphical user interfaces (GUIs) provides a beginning-to-end analysis of object recognition tests, accelerating a fast and reproducible data analysis without the need of expertise in programming or deep learning.

BackgroundAttention-deficit/hyperactivity disorder (ADHD) is a chronic neuropsychiatric disorder, that typically manifests itself during childhood and persists in a majority of the affected individuals into adulthood, negatively affecting physical and mental health. Previous studies have shown detrimental effects of the COVID-19 pandemic on mental health in individuals with ADHD. Thus, telemedicine could be a useful tool for optimizing treatment-outcomes in adult ADHD by improving treatment adherence and persistence. However, data on telemedical treatment outcomes in adult patients with ADHD is scarce.MethodsWe report here the sub-cohort analysis of a naturalistic cohort of adult patients (N = 254) recruited between April 2020–April 2021, comparing the effects of telemedical treatment on participants either clinically diagnosed with depression (N = 54) or ADHD (N = 67). Participants were asked to fill out the WHO-5 repetitively during >12 weeks of telemedical treatment. Furthermore scores of WHO-5, SCL-90R and BDI-II, psychopathology, psychosocial functioning, sociodemographic data, medical records and a feedback survey were analyzed for both groups and compared. Participants with ADHD were further stratified according to the development of well-being during the study period in order to identify factors associated with a satisfactory treatment outcome.ResultsParticipants with depression reported a significant improvement of well-being during the course of the study, while no such effect could be seen in participants with ADHD on a group level. Despite the good outcome, participants with depression were more severely affected at baseline, with significantly worse psychopathology and a more precarious labor and financial situation. A detailed analysis of ADHD participants without clinical improvement revealed significantly higher BDI-II scores than for ADHD participants with a satisfactory outcome (p = 0.03, Mann–Whitney-U-Test), suggesting successful treatment was hampered by the combination of ADHD and depressive symptoms. Furthermore, female sex among ADHD patients was correlated with an unfavorable treatment outcome during the course of the study (p = 0.001, Spearman correlation) as well as living with children (p = 0.02, Spearman correlation).ConclusionBesides screening for depressive symptoms before telemedical treatment, future research should address the specific needs of female ADHD patients as these patients may be at a particularly high risk of being overburdened with family work.

The brain elicits a remarkable capacity to respond to and recover from focal injury such as a stroke on 18 different spatial scales. Neuroimaging studies in stroke patients and rodent models show local and 19 global reorganization of functional brain circuits, including shifts in representation of function. In 20 tandem with these systems-level changes, advances in high-resolution imaging have revealed a 21 plethora of local changes up to the sub-cellular and molecular level. Recent progress in neurophotonics 22 has opened up tremendous opportunities for investigating and manipulating brain circuitry in vivo.

BackgroundDuring the COVID-19 pandemic telemedicine became essential in maintaining diagnostic procedures and treatment in psychiatry. However, it is still an open question if telemedicine is a feasible treatment option for all groups of psychiatric patients alike. This prospective monocentric observational trial was conducted to assess the general applicability of telemedical treatment in a naturalistic psychiatric outpatient cohort and to identify groups of disorders and clusters of psychopathology that respond particularly well to telemedical treatment considering sociodemographic characteristics and patients' perspectives.MethodsPatients were recruited April 2020–April 2021 and asked to fill out the WHO-5 and the SCL-90R at baseline, after 4–6 and 8–12 weeks and a feedback-survey. Additionally, medical records, psychopathology, psychosocial functioning, and socio-demographic data were analyzed. Primary outcomes were well-being, psychopathology and functioning during treatment. Secondly, diagnostic groups and psychopathology linked to a superior treatment-response were determined with respect to patients' subjective experiences.ResultsOut of 1.385 patients, 254—mostly with hyperkinetic (35.3%) and depressive disorders (24.6%)—took part. Well-being and SCL-90R total scores improved substantially (both p < 0.001). CGI and GAF scores were worse in depressed subjects (both p < 0.05). Improvement was mainly seen in depressed patients; chronic disorders experienced a decline in well-being. Sociodemographic characteristics could not explain this difference. Particularly female (r = 0.413) patients found telepsychiatry equivalent to conventional treatment. The more virtual sessions participants attended the more likely they were to find telepsychiatry equal to conventional treatment (r = 0.231).ConclusionTelemedicine is an effective treatment for patients with depression under naturalistic conditions. Telemedical consultations are a simple and reliable way of monitoring symptom severity and directing treatment choices during the treatment of depressive disorders. Patients with depression benefited more from telemedical treatment compared to participants with chronic non-episodic psychiatric disorders. Future research needs to concentrate on improving telemedical treatment options suited for the latter conditions. Psychiatric telemedicine yielded overall high degrees of satisfaction among users.

BACKGROUND:The COVID-19 pandemic and governmental lockdown measures disproportionally impact older adults. This study presents the results from a psychiatric helpline for older adults in Mannheim, Germany, during the lockdown, set up to provide information and psychosocial support. We aim to elucidate the needs of older adults, their reported changes, and the psychological impact during the initial stages of the health crisis.METHODS:A total of 55 older adults called the psychiatric helpline between April and June 2020. Information on demographics, medical and psychiatric history. as well as changes in daily life due to the pandemic was collected anonymously. Mental health status was assessed using the 7-Item Hamilton Depression Rating Scale (HAMD-7) and the Hamilton Anxiety Rating Scale (HAM-A).RESULTS:Most callers were women, older adults (M = 74.69 years), single, and retired. In total, 69% of callers reported new or an increase in psychiatric symptoms, with anxiety and depressive symptoms being the most common ones. Age was significantly negatively correlated to higher levels of anxiety and depression symptoms. Individuals with a previous diagnosis of a psychiatric disease reported significantly higher levels of depressive and anxiety symptoms than those without a diagnosis.CONCLUSION:In older adults, the perceived psychological impact of the COVID-19 crisis appears to ameliorate with age. Individuals with a history of psychiatric disease are most vulnerable to negative mental health outcomes. Rapid response in the form of a geriatric helpline is a useful initiative to support the psychosocial needs of older adults during a health crisis.

Post-stroke Epilepsy (PSE) is one of the most common forms of acquired epilepsy, especially in the elderly population. As people get increasingly older, the number of stroke patients is expected to rise and concomitantly the number of people with PSE. Although many patients are affected by post-ischemic epileptogenesis, not much is known about the underlying pathomechanisms resulting in the development of chronic seizures. A common hypothesis is that persistent neuroinflammation and glial scar formation cause aberrant neuronal firing. Here, we summarize the clinical features of PSE and describe in detail the inflammatory changes after an ischemic stroke as well as the chronic changes reported in epilepsy. Moreover, we discuss alterations and disturbances in blood-brain-barrier leakage, astrogliosis, and extracellular matrix changes in both, stroke and epilepsy. In the end, we provide an overview of commonalities of inflammatory reactions and cellular processes in the post-ischemic environment and epileptic brain and discuss how these research questions should be addressed in the future.

Motor behaviour analysis is essential to biomedical research and clinical diagnostics as it provides a non-invasive strategy for identifying motor impairment and its change caused by interventions. State-of-the-art instrumented movement analysis is time- and cost-intensive, since it requires placing physical or virtual markers. Besides the effort required for marking keypoints or annotations necessary for training or finetuning a detector, users need to know the interesting behaviour beforehand to provide meaningful keypoints. We introduce unsupervised behaviour analysis and magnification (uBAM), an automatic deep learning algorithm for analysing behaviour by discovering and magnifying deviations. A central aspect is unsupervised learning of posture and behaviour representations to enable an objective comparison of movement. Besides discovering and quantifying deviations in behaviour, we also propose a generative model for visually magnifying subtle behaviour differences directly in a video without requiring a detour via keypoints or annotations. Essential for this magnification of deviations even across different individuals is a disentangling of appearance and behaviour. Evaluations on rodents and human patients with neurological diseases demonstrate the wide applicability of our approach. Moreover, combining optogenetic stimulation with our unsupervised behaviour analysis shows its suitability as a non-invasive diagnostic tool correlating function to brain plasticity.

Neuronal networks of the mammalian motor cortex (M1) are important for dexterous control of limb joints. Yet it remains unclear how encoding of joint movement in M1 depends on varying environmental contexts. Using calcium imaging we measured neuronal activity in layer 2/3 of the M1 forelimb region while mice grasped regularly or irregularly spaced ladder rungs during locomotion. We found that population coding of forelimb joint movements is sparse and varies according to the flexibility demanded from individual joints in the regular and irregular context, even for equivalent grasping actions across conditions. This context-dependence of M1 encoding emerged during task learning, fostering higher precision of grasping actions, but broke apart upon silencing of projections from secondary motor cortex (M2). These findings suggest that M1 exploits information from M2 to adapt encoding of joint movements to the flexibility demands of distinct familiar contexts, thereby increasing the accuracy of motor output.

Intracranial arachnoid cysts are usually benign congenital findings of neuroimaging modalities, sometimes however, leading to focal neurological and psychiatric comorbidities. Whether primarily clinically silent cysts may become causally involved in cognitive decline in old age is neither well examined nor understood. A 66-year old caucasian man presenting with a giant left-hemispheric frontotemporal cyst without progression of size, presented with slowly progressive cognitive decline. Neuropsychological assessment revealed an amnestic mild cognitive impairment (MCI) without further neurological or psychiatric symptoms. The patient showed mild medio-temporal lobe atrophy on structural MRI. Diffusion tensor and functional magnetic resonance imaging depicted a rather sustained function of the strongly suppressed left hemisphere. Amyloid-PET imaging was positive for increased amyloid burden and he was homozygous for the APOEε3-gene. A diagnosis of MCI due to Alzheimer’s disease was given and a co-morbidity with a silent arachnoid cyst was assumed. To investigate, if a potentially reduced CSF flow due to the giant arachnoid cyst contributed to the early manifestation of AD, we reviewed 15 case series of subjects with frontotemporal arachnoid cysts and cognitive decline. However, no increased manifestation of neurodegenerative disorders was reported. With this case report, we illustrate the necessity of a systematic work-up for neurodegenerative disorders in patients with arachnoid cysts and emerging cognitive decline. We finally propose a modus operandi for the stratification and management of patients with arachnoid cysts potentially susceptive for cognitive dysfunction.

Current experimental stroke research faces the same challenge as neuroscience: to transform correlative findings in causative ones. Research of recent years has shown the tremendous potential of the central nervous system to react to noxious stimuli such as a stroke: Increased plastic changes leading to reorganization in form of neuronal rewiring, neurogenesis, and synaptogenesis, accompanied by transcriptional and translational turnover in the affected cells, have been described both clinically and in experimental stroke research. However, only minor attempts have been made to connect distinct plastic remodeling processes as causative features for specific behavioral phenotypes. Here, we review current state-of the art techniques for the examination of cortical reorganization and for the manipulation of neuronal circuits as well as techniques which combine anatomical changes with molecular profiling. We provide the principles of the techniques together with studies in experimental stroke research which have already applied the described methodology. The tools discussed are useful to close the loop from our understanding of stroke pathology to the behavioral outcome and may allow discovering new targets for therapeutic approaches. The here presented methods open up new possibilities to assess the efficiency of rehabilitative strategies by understanding their external influence for intrinsic repair mechanisms on a neurobiological basis.

Skilled upper limb function heavily depends on the corticospinal tract. After bilateral lesions to this tract, motor control is disrupted but can be partially substituted by other motor systems to allow functional recovery. However, the remaining roles of motor cortex and especially of axotomized corticospinal neurons (CSNs) are not well understood. Using the single pellet retrieval task in adult rats, we induced significant recovery of skilled reaching after bilateral pyramidotomy by rehabilitative reaching training, and show that reach-related motor cortex activity, recorded in layer V, topographically reappeared shortly after axotomy. Using a chemogenetic neuronal silencing technique, we found that axotomized CSNs retained a crucial role for the recovered pellet retrieval success. The axotomized CSNs sprouted extensively in the red nucleus supplying new innervation to its magnocellular and parvocellular parts. Specific silencing of the rubrospinal tract (RST) also strongly abolished the recovered pellet retrieval success, suggesting a role of this cervically projecting nucleus in relaying cortical motor control. In summary, our results show that after bilateral corticospinal axotomy, motor cortex still actively engages in forelimb motor control and axotomized CSNs are crucially involved in the recovered reaching movement, potentially by relaying motor control via the RST.

The majority of stroke patients develop post-stroke fatigue, a symptom which impairs motivation and diminishes the success of rehabilitative interventions. We show that large cortical strokes acutely reduce activity levels in rats for 1-2 weeks as a physiological response paralleled by signs of systemic inflammation. Rats were exposed early (1-2 weeks) or late (3-4 weeks after stroke) to an individually monitored enriched environment to stimulate self-controlled high-intensity sensorimotor training. A group of animals received Anti-Nogo antibodies for the first two weeks after stroke, a neuronal growth promoting immunotherapy already in clinical trials. Early exposure to the enriched environment resulted in poor outcome: Training intensity was correlated to enhanced systemic inflammation and functional impairment. In contrast, animals starting intense sensorimotor training two weeks after stroke preceded by the immunotherapy revealed better recovery with functional outcome positively correlated to the training intensity and the extent of re-innervation of the stroke denervated cervical hemi-cord. Our results suggest stroke-induced fatigue as a biological purposeful reaction of the organism during neuronal remodeling, enabling new circuit formation which will then be stabilized or pruned in the subsequent rehabilitative training phase. However, intense training too early may lead to wrong connections and is thus less effective.

Behavior analysis provides a crucial non-invasive and easily accessible diagnostic tool for biomedical research. A detailed analysis of posture changes during skilled motor tasks can reveal distinct functional deficits and their restoration during recovery. Our specific scenario is based on a neuroscientific study of rodents recovering from a large sensorimotor cortex stroke and skilled forelimb grasping is being recorded. Given large amounts of unlabeled videos that are recorded during such long-term studies, we seek an approach that captures fine-grained details of posture and its change during rehabilitation without costly manual supervision. Therefore, we utilize self-supervision to automatically learn accurate posture and behavior representations for analyzing motor function. Learning our model depends on the following fundamental elements: (i) limb detection based on a fully convolutional network is initialized solely using motion information, (ii) a novel self-supervised training of LSTMs using only temporal permutation yields a detailed representation of behavior, and (iii) back-propagation of this sequence representation also improves the description of individual postures. We establish a novel test dataset with expert annotations for evaluation of fine-grained behavior analysis. Moreover, we demonstrate the generality of our approach by successfully applying it to self-supervised learning of human posture on two standard benchmark datasets.

Current neuromodulatory strategies to enhance motor recovery after stroke often target large brain areas non-specifically and without sufficient understanding of their interaction with internal repair mechanisms. Here we developed a novel therapeutic approach by specifically activating corticospinal circuitry using optogenetics after large strokes in rats. Similar to a neuronal growth-promoting immunotherapy, optogenetic stimulation together with intense, scheduled rehabilitation leads to the restoration of lost movement patterns rather than induced compensatory actions, as revealed by a computer vision-based automatic behavior analysis. Optogenetically activated corticospinal neurons promote axonal sprouting from the intact to the denervated cervical hemi-cord. Conversely, optogenetically silencing subsets of corticospinal neurons in recovered animals, results in mistargeting of the restored grasping function, thus identifying the reestablishment of specific and anatomically localized cortical microcircuits. These results provide a conceptual framework to improve established clinical techniques such as transcranial magnetic or transcranial direct current stimulation in stroke patients.

Stroke is a major cause of adult disability and rehabilitative training is the prevailing approach to enhance motor recovery. However, the way rehabilitation helps to restore lost motor functions by continuous reshaping of kinematics is still an open research question. We follow the established setup of a rat model before/after stroke in the motor cortex to analyze the subtle changes in hand motor function solely based on video. Since nuances of paw articulation are crucial, mere tracking and trajectory analysis is insufficient. Thus, we propose an automatic spatiotemporal parsing of grasping kinematics based on a max-projection of randomized exemplar classifiers. A large ensemble of these discriminative predictors of hand posture is automatically learned and yields a measure of grasping similarity. This non-parametric distributed representation effectively captures the nuances of hand posture and its deformation over time. A max-margin projection then not only quantifies functional deficiencies, but also back-projects them accurately to specific defects in the grasping sequence to provide neuroscience with a better understanding of the precise effects of rehabilitation. Moreover, evaluation shows that our fully automatic approach is reliable and more efficient than the prevalent manual analysis of the day.

After stroke the central nervous system reveals a spectrum of intrinsic capacities to react as a highly dynamic system which can change the properties of its circuits, form new contacts, erase others, and remap related cortical and spinal cord regions. This plasticity can lead to a surprising degree of spontaneous recovery. It includes the activation of neuronal molecular mechanisms of growth and of extrinsic growth promoting factors and guidance signals in the tissue. Rehabilitative training and pharmacological interventions may modify and boost these neuronal processes, but almost nothing is known on the optimal timing of the different processes and therapeutic interventions and on their detailed interactions. Finding optimal rehabilitation paradigms requires an optimal orchestration of the internal processes of re-organization and the therapeutic interventions in accordance with defined plastic time windows. In this review we summarize the mechanisms of spontaneous plasticity after stroke and experimental interventions to enhance growth and plasticity, with an emphasis on anti-Nogo-A immunotherapy. We highlight critical time windows of growth and of rehabilitative training and consider different approaches of combinatorial rehabilitative schedules. Finally, we discuss potential future strategies for designing repair and rehabilitation paradigms by introducing a “3 step model”: determination of the metabolic and plastic status of the brain, pharmacological enhancement of its plastic mechanisms, and stabilization of newly formed functional connections by rehabilitative training.