Early functional connectivity alterations in contralesional motor networks influence outcome after severe stroke: a preliminary analysis

Connectivity studies have significantly extended the knowledge on motor network alterations after stroke. Compared to interhemispheric or ipsilesional networks, changes in the contralesional hemisphere are poorly understood. Data obtained in the acute stage after stroke and in severely impaired patients are remarkably limited. This exploratory, preliminary study aimed to investigate early functional connectivity changes of the contralesional parieto-frontal motor network and their relevance for the functional outcome after severe motor stroke. Resting-state functional imaging data were acquired in 19 patients within the first 2 weeks after severe stroke. Nineteen healthy participants served as a control group. Functional connectivity was calculated from five key motor areas of the parieto-frontal network on the contralesional hemisphere as seed regions and compared between the groups. Connections exhibiting stroke-related alterations were correlated with clinical follow-up data obtained after 3-6 months. The main finding was an increase in coupling strength between the contralesional supplementary motor area and the sensorimotor cortex. This increase was linked to persistent clinical deficits at follow-up. Thus, an upregulation in contralesional motor network connectivity might be an early pattern in severely impaired stroke patients. It might carry relevant information regarding the outcome which adds to the current concepts of brain network alterations and recovery processes after severe stroke.

Cortical thickness of contralesional cortices positively relates to future outcome after severe stroke

Imaging studies have evidenced that contralesional cortices are involved in recovery after motor stroke. Cortical thickness (CT) analysis has proven its potential to capture the changes of cortical anatomy, which have been related to recovery and treatment gains under therapy. An open question is whether CT obtained in the acute phase after stroke might inform correlational models to explain outcome variability. Data of 38 severely impaired (median NIH Stroke Scale 9, interquartile range: 6-13) acute stroke patients of 2 independent cohorts were reanalyzed. Structural imaging data were processed via the FreeSurfer pipeline to quantify regional CT of the contralesional hemisphere. Ordinal logistic regression models were fit to relate CT to modified Rankin Scale as an established measure of global disability after 3-6 months, adjusted for the initial deficit, lesion volume, and age. The data show that CT of contralesional cortices, such as the precentral gyrus, the superior frontal sulcus, and temporal and cingulate cortices, positively relates to the outcome after stroke. This work shows that the baseline cortical anatomy of selected contralesional cortices can explain the outcome variability after severe stroke, which further contributes to the concept of structural brain reserve with respect to contralesional cortices to promote recovery.

Structural cerebellar reserve positively influences outcome after severe stroke

The concept of brain reserve capacity positively influencing the process of recovery after stroke has been continuously developed in recent years. Global measures of brain health have been linked with a favourable outcome. Numerous studies have evidenced that the cerebellum is involved in recovery after stroke. However, it remains an open question whether characteristics of cerebellar anatomy, quantified directly after stroke, might have an impact on subsequent outcome after stroke. Thirty-nine first-ever ischaemic non-cerebellar stroke patients underwent MRI brain imaging early after stroke and longitudinal clinical follow-up. Structural images were used for volumetric analyses of distinct cerebellar regions. Ordinal logistic regression analyses were conducted to associate cerebellar volumes with functional outcome 3-6 months after stroke, operationalized by the modified Rankin Scale. Larger volumes of cerebellar lobules IV, VI, and VIIIB were positively correlated with favourable outcome, independent of the severity of initial impairment, age, and lesion volume (P < 0.01). The total cerebellar volume did not exhibit a significant structure-outcome association. The present study reveals that pre-stroke anatomy of distinct cerebellar lobules involved in motor and cognitive functioning might be linked to outcome after acute non-cerebellar stroke, thereby promoting the emerging concepts of structural brain reserve for recovery processes after stroke.

OUP accepted manuscript

Analyses of alterations of brain networks have gained an increasing interest in stroke rehabilitation research. Compared with functional networks derived from resting-state analyses, there is limited knowledge of how structural network topology might undergo changes after stroke and, more importantly, if structural network information obtained early after stroke could enhance recovery models to infer later outcomes. The present work re-analysed cross-sectional structural imaging data, obtained within the first 2 weeks, of 45 acute stroke patients (22 females, 24 right-sided strokes, age 68 ± 13 years). Whole-brain tractography was performed to reconstruct structural connectomes and graph-theoretical analyses were employed to quantify global network organization with a focus on parameters of network integration and modular processing. Graph measures were compared between stroke patients and 34 healthy controls (15 females, aged 69 ± 10 years) and they were integrated with four clinical scores of the late subacute stage, covering neurological symptom burden (National Institutes of Health Stroke Scale), global disability (modified Rankin Scale), activity-related disability (Barthel Index) and motor functions (Upper-Extremity Score of the Fugl-Meyer Assessment). The analyses were employed across the complete cohort and, based on clustering analysis, separately within subgroups stratified in mild to moderate (n = 21) and severe (n = 24) initial deficits. The main findings were (i) a significant reduction of network’s global efficiency, specifically in patients with severe deficits compared with controls (P = 0.010) and (ii) a significant negative correlation of network efficiency with the extent of persistent functional deficits at follow-up after 3–6 months (P ≤ 0.032). Specifically, regression models revealed that this measure was capable to increase the explained variance in future deficits by 18% for the modified Rankin Scale, up to 24% for National Institutes of Health Stroke Scale, and 16% for Barthel Index when compared with models including the initial deficits and the lesion volume. Patients with mild to moderate deficits did not exhibit a similar impact of network efficiency on outcome inference. Clustering coefficient and modularity, measures of segregation and modular processing, did not exhibit comparable structure–outcome relationships, neither in severely nor in mildly affected patients. This study provides empirical evidence that structural network efficiency as a graph-theoretical marker of large-scale network topology, quantified early after stroke, relates to recovery. Notably, this contribution was only evident in severely but not mildly affected stroke patients. This suggests that the initial clinical deficit might shape the dependency of recovery on global network topology after stroke.

Predictive Value of Upper Extremity Outcome Measures After Stroke-A Systematic Review and Metaregression Analysis

A better understanding of motor recovery after stroke requires large-scale, longitudinal trials applying suitable assessments. Currently, there is an abundance of upper limb assessments used to quantify recovery. How well various assessments can describe upper limb function change over 1 year remains uncertain. A uniform and feasible standard would be beneficial to increase future studies' comparability on stroke recovery. This review describes which assessments are common in large-scale, longitudinal stroke trials and how these quantify the change in upper limb function from stroke onset up to 1 year. A systematic search for well-powered stroke studies identified upper limb assessments classifying motor recovery during the initial year after a stroke. A metaregression investigated the association between assessments and motor recovery within 1 year after stroke. Scores from nine common assessments and 4,433 patients were combined and transformed into a standardized recovery score. A mixed-effects model on recovery scores over time confirmed significant differences between assessments (P < 0.001), with improvement following the weeks after stroke present when measuring recovery using the Action Research Arm Test (β = 0.013), Box and Block test (β = 0.011), Fugl–Meyer Assessment (β = 0.007), or grip force test (β = 0.023). A last-observation-carried-forward analysis also highlighted the peg test (β = 0.017) and Rivermead Assessment (β = 0.011) as additional, valuable long-term outcome measures. Recovery patterns and, thus, trial outcomes are dependent on the assessment implemented. Future research should include multiple common assessments and continue data collection for a full year after stroke to facilitate the consensus process on assessments measuring upper limb recovery.

The Influence of Cortico-Cerebellar Structural Connectivity on Cortical Excitability in Chronic Stroke

Brain imaging has recently evidenced that the structural state of distinct reciprocal cortico-cerebellar fiber tracts, the dentato-thalamo-cortical tract (DTCT), and the cortico-ponto-cerebellar tract (CPCeT), significantly influences residual motor output in chronic stroke patients, independent from the level of damage to the corticospinal tract (CST). Whether such structural information might also directly relate to measures of cortical excitability is an open question. Eighteen chronic stroke patients with supratentorial ischemic lesions and 17 healthy controls underwent transcranial magnetic stimulation to assess recruitment curves of motor evoked potentials of both hemispheres. Diffusion-weighted imaging and probabilistic tractography were applied to reconstruct reciprocal cortico-cerebellar motor tracts between the primary motor cortex and the cerebellum. Tract-related microstructure was estimated by means of fractional anisotropy, and linear regression modeling was used to relate it to cortical excitability. The main finding was a significant association between cortical excitability and the structural integrity of the DTCT, the main cerebellar outflow tract, independent from the level of damage to the CST. A comparable relationship was neither detectable for the CPCeT nor for the healthy controls. This finding contributes to a mechanistic understanding of the putative supportive role of the cerebellum for residual motor output by facilitating cortical excitability after stroke.

Early parietofrontal network upregulation relates to future persistent deficits after severe stroke-a prospective cohort study

Recent brain imaging has evidenced that parietofrontal networks show alterations after stroke which also relate to motor recovery processes. There is converging evidence for an upregulation of parietofrontal coupling between parietal brain regions and frontal motor cortices. The majority of studies though have included only moderately to mildly affected patients, particularly in the subacute or chronic stage. Whether these network alterations will also be present in severely affected patients and early after stroke and whether such information can improve correlative models to infer motor recovery remains unclear. In this prospective cohort study, 19 severely affected first-ever stroke patients (mean age 74 years, 12 females) were analysed which underwent resting-state functional MRI and clinical testing during the initial week after the event. Clinical evaluation of neurological and motor impairment as well as global disability was repeated after three and six months. Nineteen healthy participants of similar age and gender were also recruited. MRI data were used to calculate functional connectivity values between the ipsilesional primary motor cortex, the ventral premotor cortex, the supplementary motor area and the anterior and caudal intraparietal sulcus of the ipsilesional hemisphere. Linear regression models were estimated to compare parietofrontal functional connectivity between stroke patients and healthy controls and to relate them to motor recovery. The main finding was a significant increase in ipsilesional parietofrontal coupling between anterior intraparietal sulcus and the primary motor cortex in severely affected stroke patients (P < 0.003). This upregulation significantly contributed to correlative models explaining variability in subsequent neurological and global disability as quantified by National Institute of Health Stroke Scale and modified Rankin Scale, respectively. Patients with increased parietofrontal coupling in the acute stage showed higher levels of persistent deficits in the late subacute stage of recovery (P < 0.05). This study provides novel insights that parietofrontal networks of the ipsilesional hemisphere undergo neuroplastic alteration already very early after severe motor stroke. The association between early parietofrontal upregulation and future levels of persistent functional deficits and dependence from help in daily living might be useful in models to enhance clinical neurorehabilitative decision making.

Can Daytime Napping Assist the Process of Skills Acquisition After Stroke?

Acquisition and reacquisition of skills is a main pillar of functional recovery after stroke. Nighttime sleep has a positive influence on motor learning in healthy individuals, whereas the effect of daytime sleep on neuro-rehabilitative training and relearning of the trained skills is often neglected. The aim of this study was to investigate the relationship between daytime sleep (napping) and the ability to learn a new visuomotor task in chronic stroke patients. The main hypothesis was that sleep enhances motor memory consolidation after training resulting in better motor performance after a period of daytime sleep. Thirty stroke survivors completed the study. They were randomized to one of three different conditions (i) wakeful resting, (ii) short nap (10-20 min), or (iii) long nap (50-80 min). All individuals trained the task with the contralesional, stroke-impaired hand, behavioral evaluation was performed after the break time (wake, nap), and 24 h later. Patients demonstrated a significant task-related behavioral improvement throughout the training. In contrast to the main hypothesis, there was no evidence for sleep-dependent motor consolidation early after the initial, diurnal break, or after an additional full night of sleep. In a secondary analysis, the performance changes of stroke survivors were compared with those of a group of healthy older adults who performed the identical task within the same experimental setup with their non-dominant hand. Performance levels were comparable between both cohorts at all time points. Stroke-related difficulties in motor control did not impact on the degree of performance improvement through training and daytime sleep did not impact on the behavioral gains in the two groups. In summary, the current study indicates that one-time daytime sleep after motor training does not influence behavioral gains.

The effect of sleep on motor learning in the aging and stroke population - a systematic review

There is extensive evidence for positive effects of sleep on motor learning in young individuals; however, the effects of sleep on motor learning in people with stroke and in healthy older individuals are not well understood. The aim of this systematic review was to quantify the association between sleep and procedural memory performance - a marker for motor learning - in healthy older people and people with stroke. After searches in PubMed, Medline and Embase fourteen studies, including 44 subjects after stroke and 339 healthy older participants were included. Overall, sleep was found to enhance motor performance in people after stroke in comparison to an equivalent time of wakefulness. In addition, although evidence is limited, sleep only enhanced motor performance in people after stroke and not in age-matched healthy older adults. In older adults the effect of a sleep intervention did - in general - not differ from equivalent periods of wakefulness. Tasks with whole hand or whole body movements could show significant changes. The results suggest a delayed retention effect after longer breaks including sleep, hinting towards a changed learning strategy as a result of aging. Current evidence for sleep dependent learning in people after stroke is promising, however sparse.

Motor Performance Is not Enhanced by Daytime Naps in Older Adults

The impact of sleep on motor learning in the aging brain was investigated using an experimental diurnal nap setup. As the brain ages several components of learning as well as motor performance change. In addition, aging is also related to sleep architectural changes. This combination of slowed learning processes and impaired sleep behavior raises the question of whether sleep can enhance learning and specifically performance of procedural tasks in healthy, older adults. Previous research was able to show sleep-dependent consolidation overnight for numerous tasks in young adults. Some of these study findings can also be replicated for older adults. This study aims to clarify whether sleep-dependent consolidation can also be found during shorter periods of diurnal sleep. The impact of midday naps on motor consolidation was analyzed by comparing procedural learning using a sequence and a motor adaptation task, in a crossover fashion in healthy, non-sleep deprived, older adults randomly subjected to wake (45 min), short nap (10–20 min sleep) or long nap (50–70 min sleep) conditions. Older adults exhibited learning gains, these were not found to be sleep-dependent in either task. The results suggest that daytime naps do not have an impact on performance and motor learning in an aging population.

Daytime sleep has no effect on the time course of motor sequence and visuomotor adaptation learning

Sleep has previously been claimed to be essential for the continued learning processes of declarative information as well as procedural learning. This study was conducted to examine the importance of sleep, especially the effects of midday naps, on motor sequence and visuomotor adaptation learning. Thirty-five (27 females) healthy, young adults aged between 18 and 30years of age participated in the current study. Addressing potential differences in explicit sequence and motor adaptation learning participants were asked to learn both, a nine-element explicit sequence and a motor adaptation task, in a crossover fashion on two consecutive days. Both tasks were performed with their non-dominant left hand. Prior to learning, each participant was randomized to one of three interventions; (1) power nap: 10-20min sleep, (2) long nap: 50-80min sleep or (3) a 45-min wake-condition. Performance of the motor learning task took place prior to and after a midday rest period, as well as after a night of sleep. Both sleep conditions were dominated by Stage N2 sleep with embedded sleep spindles, which have been described to be associated with enhancement of motor performance. Significant performance changes were observed in both tasks across all interventions (sleep and wake) confirming that learning took place. In the present setup, the magnitude of motor learning was not sleep-dependent in young adults - no differences between the intervention groups (short nap, long nap, no nap) could be found. The effect of the following night of sleep was not influenced by the previous midday rest or sleep period. This finding may be related to the selectiveness of the human brain enhancing especially memory being thought of as important in the future. Previous findings on motor learning enhancing effects of sleep, especially of daytime sleep, are challenged.

A physiological model of dark-adapted and light-adapted photoreceptors of the honeybee

A physiological model of dark-adapted and light-adapted photoreceptors in the honeybee worker (Apis mellifera) has been developed. Almost all of the electrophysiological components of photoreceptors known up to date, e.g. the phototransduction cascade, the ion channels of the membrane, phototransduction gain and optical adaptation mechanisms, are adequately described by simple biophysical and biochemical models. The connections of these components were tried out in synthetic simulations for best fits of simulated to intracellularly recorded membrane potentials. Although the parameters of the best model were determined exclusively for the measured membrane potentials of dark-adapted photoreceptors, the model also accurately describes the light-adapted photoreceptor membrane potentials. Furthermore, the model correctly predicts the time-courses of measured photoreceptor responses with respect to squared-modulated flicker lights up to 200 Hz. This clearly demonstrates that the presented photoreceptor model is indeed a physiologically adequate description of the essential components of the phototransduction and the electrical membrane processes in the photoreceptors of the honeybee worker.

The Bezold-Brücke effect in the color vision system of the honeybee

Evidence is presented that intensity dependent color shifts (Bezold-Brücke effect) occur in the color vision system of the honeybee. The evidence comes from a fit between the choices of monochromatic lights in training experiments (Menzel, R., 1981; Journal of Comparative Physiology A, 141, 389-393) and the choice percentages derived now from recently presented quantitative predictions from the color opponent coding (COC) model for the bee (Backhaus, W., 1991; Vision Research, 31, 1381-1397) for the Bezold-Brücke effect. The only open parameter in the simulations of the training experiments is an experiment type dependent factor describing the weighting of color differences (judgement values) in the choice behavior. The results show (1) that the Bezold-Brücke effect exists in the bee. The results (2) confirm the color opponent coding (COC) model which was developed to describe the physiological components of the color vision system in the bee, (3) the general psychophysical assumptions about the structure of the color space, (4) the color difference formula, and (5) the general psychophysical assumptions about the (triadic) structure of judgements as tested in color similarity experiments.

Color vision in honeybees

Theoretical and experimental investigations of the color vision system in honeybees are reviewed. Grassmann's model and receptor models of color vision are discussed with respect to the problem of color difference. A recent analysis of the bee's color opponent coding system is presented in brief. Predictions for the spectral sensitivity of color opponent coding neurons derived directly from the color opponent coding (COC) model and predictions for the Bezold-Brücke color shift and the spectral discrimination function derived from the model via color difference formula are presented. The predictions are compared with electrophysiological data and with choice proportions of behavioral experiments, respectively.

Color opponent coding in the visual system of the honeybee

A model is presented for the color vision system of the honeybee, which takes the nonlinear phototransduction process in the photoreceptors into account and assumes linear computations of the excitations of the photoreceptors. The model parameters are derived by a least squares fit of the scale values determined by multidimensional scaling analysis of the results of color choice experiments to the excitation values of two hypothetical spectral antagonistic coding cells. The psychophysical scale values are interpreted physiologically. Furthermore, a color difference formula is presented which is based on the color opponent coding (COC) model. The model explains quantitatively (1) the sensitivity of spectral antagonistic neurons measured by Kien and Menzel (1977; Journal of Comparative Physiology, 113, 17-34, 35-53), (2) the color discrimination function measured by von Helversen (1972; Journal of Comparative Physiology, 80, 439-472). The following predictions are derived from the model: (1) excitation/log (I) curves of the spectral antagonistic neurons; and from the model in conjunction with the color difference formula: (2) intensity dependent color shifts (Bezold-Brücke effect); (3) the intensity dependence of wavelength discrimination.