Combining cyproheptadine hydrochloride with targeted muscle activation training to treat upper extremity stroke: a randomized, placebo-controlled trial.

OBJECTIVE: To examine a treatment for upper extremity impairment in stroke survivors that combines administration of cyproheptadine hydrochloride with repetitive practice focused on control of muscle activation patterns. DESIGN: Double-blind, randomized controlled trial. SETTINGS: Laboratory within free-standing rehabilitation hospital. PARTICIPANTS: A total of 94 stroke survivors with severe, chronic hand impairment were randomly assigned to one of four treatment groups. INTERVENTIONS: Participants received either placebo or cyproheptadine hydrochloride in identical pill form. Daily dosage of cyproheptadine/placebo was gradually increased from 8 mg/day to 24 mg/day over three weeks and then maintained over the next 6 weeks while participant completed 18 therapy sessions. Therapy consisted of either: (1) active practice of muscle activation patterns to play "serious" computer games or control a custom hand exoskeleton or (2) passive, cyclical finger stretching imposed by the exoskeleton. MAIN OUTCOME MEASURES: Hand control was evaluated with the primary outcome measure of time to complete the Graded Wolf Motor Function Test (GWMFT) and secondary outcome measures including finger strength and spasticity. RESULTS: Across the 88 participants who completed the study, a repeated measures ANOVA revealed a significant effect of GroupxEvaluation interaction on GWMFT (F=1.996, p=0.026). The three groups receiving cyproheptadine and/or actively practicing muscle activation pattern control exhibited significant reduction in mean time to complete the GWMFT tasks; roughly one-third of these participants experienced at least 10% reduction in completion time. Gains were maintained at the one-month follow-up evaluation. The group receiving placebo and passive stretching did not show improvement. No significant differences among groups were observed in terms of changes in strength or spasticity. CONCLUSIONS: Despite chronic, severe impairment, stroke survivors were able to complete the therapy focused on muscle activations and achieved statistically significant improvement in hand motor control. Cyproheptadine hydrochloride affords a potential complementary treatment modality for stroke survivors with hand impairment.

Is 18F-FDG-PET/CT an Optimal Imaging Modality for Detecting Immune-Related Adverse Events after Immune-Checkpoint Inhibitor Therapy? Pros and Cons.

Immunotherapy with immune checkpoint inhibitors (ICIs) has revolutionized contemporary oncology, presenting efficacy in various solid tumors and lymphomas. However, ICIs may potentially overstimulate the immune system, leading to immune-related adverse events (irAEs). IrAEs may affect multiple organs, such as the colon, stomach, small intestine, kidneys, skin, lungs, joints, liver, lymph nodes, bone marrow, brain, heart, and endocrine glands (e.g., pancreas, thyroid, or adrenal glands), exhibiting autoimmune inflammation. 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) is commonly used in oncology for staging and assessment of therapy responses, but it may also serve as a tool for detecting irAEs. This review aims to present various patterns of metabolic activation associated with irAEs due to ICI treatment, identifiable through 18F-FDG PET/CT. It describes the advantages of early detection of irAEs, but also presents the challenges in differentiating them from tumor progression. It also delves into aspects of molecular response assessment within the context of pseudoprogression and hyperprogression, along with typical imaging findings related to these phenomena. Lastly, it summarizes the role of functional PET imaging in oncological immunotherapy, speculating on its future significance and limitations.

The co-activation patterns of multiple brain regions in Juvenile Myoclonic Epilepsy.

Juvenile myoclonic epilepsy (JME) as an idiopathic generalized epilepsy has been studied by many advanced neuroimaging techniques to elucidate its neuroanatomical basis and pathophysiological mechanisms. In this paper, we used co-activation patterns (CAPs) to explore the differences of dynamic brain activity changes in resting state between JME patients and healthy controls. 27 cases JME patients and 27 cases healthy of fMRI data were collected. The structural image data of the subjects were analyzed by voxel-based morphological analysis, and the regions with gray matter volume atrophy and high voxel were selected as the regions of interest. Further, the mean disease duration was used as boundary to divide the patients' data into the below-average time and the above-average time groups, which were defined as patient disease duration groups. And these data were used to construct CAPs and to compare changes in brain dynamics. It was found that the number of patterns occurrences and the possibility of switching between patterns were smaller than those in the healthy control, which indicated patients with damage to brain regions. For the patient time control group, the number of patterns occurrences and the possibility of switching between patterns were similar, while there was linear regression between the three values and disease duration. Collectively, this study provides important evidence for revealing the key brain regions of JME by studying the transformation between CAPs. Future studies could investigate the effects of receiving treatment on patient dynamic brain activity.

Early altered directionality of resting brain network state transitions in the TgF344-AD rat model of Alzheimer's disease.

Introduction: Alzheimer's disease (AD) is a progressive neurodegenerative disease resulting in memory loss and cognitive decline. Synaptic dysfunction is an early hallmark of the disease whose effects on whole-brain functional architecture can be identified using resting-state functional MRI (rsfMRI). Insights into mechanisms of early, whole-brain network alterations can help our understanding of the functional impact of AD's pathophysiology. Methods: Here, we obtained rsfMRI data in the TgF344-AD rat model at the pre- and early-plaque stages. This model recapitulates the major pathological and behavioral hallmarks of AD. We used co-activation pattern (CAP) analysis to investigate if and how the dynamic organization of intrinsic brain functional networks states, undetectable by earlier methods, is altered at these early stages. Results: We identified and characterized six intrinsic brain states as CAPs, their spatial and temporal features, and the transitions between the different states. At the pre-plaque stage, the TgF344-AD rats showed reduced co-activation of hub regions in the CAPs corresponding to the default mode-like and lateral cortical network. Default mode-like network activity segregated into two distinct brain states, with one state characterized by high co-activation of the basal forebrain. This basal forebrain co-activation was reduced in TgF344-AD animals mainly at the pre-plaque stage. Brain state transition probabilities were altered at the pre-plaque stage between states involving the default mode-like network, lateral cortical network, and basal forebrain regions. Additionally, while the directionality preference in the network-state transitions observed in the wild-type animals at the pre-plaque stage had diminished at the early-plaque stage, TgF344-AD animals continued to show directionality preference at both stages. Discussion: Our study enhances the understanding of intrinsic brain state dynamics and how they are impacted at the early stages of AD, providing a nuanced characterization of the early, functional impact of the disease's neurodegenerative process.

Thalamic contributions to psychosis susceptibility: Evidence from co-activation patterns accounting for intra-seed spatial variability (µCAPs).

The temporal variability of the thalamus in functional networks may provide valuable insights into the pathophysiology of schizophrenia. To address the complexity of the role of the thalamic nuclei in psychosis, we introduced micro-co-activation patterns (µCAPs) and employed this method on the human genetic model of schizophrenia 22q11.2 deletion syndrome (22q11.2DS). Participants underwent resting-state functional MRI and a data-driven iterative process resulting in the identification of six whole-brain µCAPs with specific activity patterns within the thalamus. Unlike conventional methods, µCAPs extract dynamic spatial patterns that reveal partially overlapping and non-mutually exclusive functional subparts. Thus, the µCAPs method detects finer foci of activity within the initial seed region, retaining valuable and clinically relevant temporal and spatial information. We found that a µCAP showing co-activation of the mediodorsal thalamus with brain-wide cortical regions was expressed significantly less frequently in patients with 22q11.2DS, and its occurrence negatively correlated with the severity of positive psychotic symptoms. Additionally, activity within the auditory-visual cortex and their respective geniculate nuclei was expressed in two different µCAPs. One of these auditory-visual µCAPs co-activated with salience areas, while the other co-activated with the default mode network (DMN). A significant shift of occurrence from the salience+visuo-auditory-thalamus to the DMN + visuo-auditory-thalamus µCAP was observed in patients with 22q11.2DS. Thus, our findings support existing research on the gatekeeping role of the thalamus for sensory information in the pathophysiology of psychosis and revisit the evidence of geniculate nuclei hyperconnectivity with the audio-visual cortex in 22q11.2DS in the context of dynamic functional connectivity, seen here as the specific hyper-occurrence of these circuits with the task-negative brain networks.

Abnormal supplementary motor areas are associated with idiopathic and acquired blepharospasm.

Blepharospasm is a common form of focal dystonia characterized by excessive and involuntary spasms of the orbicularis oculi. In addition to idiopathic blepharospasm, lesions in various brain regions can also cause acquired blepharospasm. Whether these two types of blepharospasm share a common brain network remains largely unknown. Herein, we performed lesion coactivation network mapping, based on meta-analytic connectivity modeling, to test whether lesions causing blepharospasm could be mapped to a common coactivation brain network. We then tested the abnormality of the network in patients with idiopathic blepharospasm (n = 42) compared with healthy controls (n = 44). We identified 21 cases of lesion-induced blepharospasms through a systematic literature search. Although these lesions were heterogeneous, they were part of a co-activated brain network that mainly included the bilateral supplementary motor areas. Coactivation of these regions defines a single brain network that encompasses or is adjacent to most heterogeneous lesions causing blepharospasm. Moreover, the bilateral supplementary motor area is primarily associated with action execution, visual motion, and imagination, and participates in finger tapping and saccades. They also reported decreased functional connectivity with the left posterior cingulate cortex in patients with idiopathic blepharospasm. These results demonstrate a common convergent abnormality of the supplementary motor area across idiopathic and acquired blepharospasms, providing additional evidence that the supplementary motor area is an important brain region that is pathologically impaired in patients with blepharospasm.

Unlocking the neural mechanisms of consumer loan evaluations: an fNIRS and ML-based consumer neuroscience study.

Introduction: This study conducts a comprehensive exploration of the neurocognitive processes underlying consumer credit decision-making using cutting-edge techniques from neuroscience and machine learning (ML). Employing functional Near-Infrared Spectroscopy (fNIRS), the research examines the hemodynamic responses of participants while evaluating diverse credit offers. Methods: The experimental phase of this study investigates the hemodynamic responses collected from 39 healthy participants with respect to different loan offers. This study integrates fNIRS data with advanced ML algorithms, specifically Extreme Gradient Boosting, CatBoost, Extra Tree Classifier, and Light Gradient Boosted Machine, to predict participants' credit decisions based on prefrontal cortex (PFC) activation patterns. Results: Findings reveal distinctive PFC regions correlating with credit behaviors, including the dorsolateral prefrontal cortex (dlPFC) associated with strategic decision-making, the orbitofrontal cortex (OFC) linked to emotional valuations, and the ventromedial prefrontal cortex (vmPFC) reflecting brand integration and reward processing. Notably, the right dorsomedial prefrontal cortex (dmPFC) and the right vmPFC contribute to positive credit preferences. Discussion: This interdisciplinary approach bridges neuroscience, machine learning and finance, offering unprecedented insights into the neural mechanisms guiding financial choices regarding different loan offers. The study's predictive model holds promise for refining financial services and illuminating human financial behavior within the burgeoning field of neurofinance. The work exemplifies the potential of interdisciplinary research to enhance our understanding of human financial decision-making.

Effects of wrist posture and stabilization on precision grip force production and muscle activation patterns.

Most of the power for generating forces in the fingers arises from muscles located in the forearm. This configuration maximizes finger joint range of motion while minimizing finger mass and inertia. The resulting multiarticular arrangement of the tendons, however, complicates independent control of the wrist and the digits. Actuating the wrist impacts sensorimotor control of the fingers and vice versa. The goal of this study was to systematically investigate interactions between isometric wrist and digit control. Specifically, we examined how the need to maintain a specified wrist posture influences precision grip. Fifteen healthy adults produced maximum precision grip force at 11 different wrist flexion/extension angles, with the arm supported, under two conditions: 1) the participant maintained the desired wrist angle while performing the precision grip and 2) a robot maintained the specified wrist angle. Wrist flexion/extension posture significantly impacted maximum precision grip force (P < 0.001), with the greatest grip force achieved when the wrist was extended 30° from neutral. External wrist stabilization by the robot led to a 20% increase in precision grip force across wrist postures. Increased force was accompanied by increased muscle activation but with an activation pattern similar to the one used when the participant had to stabilize their wrist. Thus, simultaneous wrist and finger requirements impacted performance of an isometric finger task. External wrist stabilization can promote increased precision grip force resulting from increased muscle activation. These findings have potential clinical significance for individuals with neurologically driven finger weakness, such as stroke survivors.NEW & NOTEWORTHY We explored the interdependence between wrist and fingers by assessing the influence of wrist posture and external stabilization on precision grip force generation. We found that maximum precision grip force occurred at an extended wrist posture and was 20% greater when the wrist was Externally Stabilized. The latter resulted from amplification of muscle activation patterns from the Self-Stabilized condition rather than adoption of new patterns exploiting external wrist stabilization.

High-density and high coverage composite mapping of repetitive atrial activation patterns.

BACKGROUND: Repetitive atrial activation patterns (RAAPs) during atrial fibrillation (AF) may be associated with localized mechanisms that maintain AF. Current electro-anatomical mapping systems are unsuitable for analyzing RAAPs due to the trade-off between spatial coverage and electrode density in clinical catheters. This work proposes a technique to overcome this trade-off by constructing composite maps from spatially overlapping sequential recordings. METHODS: High-density epicardial contact mapping was performed during open-chest surgery in goats (n=16, left and right atria) with 3 or 22 weeks of sustained AF (249-electrode array, electrode distance 2.4 mm). A dataset mimicking sequential recordings was generated by segmenting the grid into four spatially overlapping regions (each region 6.5 cm2, 48±10% overlap) without temporal overlap. RAAPs were detected in each region using recurrence plots of activation times. RAAPs in two different regions were joined in case of RAAP cross-recurrence between overlapping electrodes. We quantified the reconstruction success rate and quality of the composite maps. RESULTS: Of 1021 RAAPs found in the full mapping array (32±13 per recording), 328 spatiotemporally stable RAAPs were analyzed. 247 composite maps were generated (75% success) with a quality of 0.86±0.21 (Pearson correlation). Success was significantly affected by the RAAP area. Quality was weakly correlated with the number of repetitions of RAAPs (r=0.13, p<0.05) and not affected by the atrial side (left or right) or AF duration (3 or 22 weeks of AF). CONCLUSIONS: Constructing composite maps by combining spatially overlapping sequential recordings is feasible. Interpretation of these maps can play a central role in ablation planning.

Variation of body weight supported treadmill training parameters during a single session can modulate muscle activity patterns in post-stroke gait.

Evidence supporting the benefits of locomotor training (LT) to improve walking ability following stroke are inconclusive and could likely be improved with a better understanding of the effects of individual parameters i.e., body weight support (BWS), speed, and therapist assistance and their interactions with walking ability and specific impairments. We evaluated changes in muscle activity of thirty-seven individuals with chronic stroke (> 6 months), in response to a single session of LT at their self-selected or fastest-comfortable speed (FS) with three levels of BWS (0%, 15%, and 30%), and at FS with 30% BWS and seven different combinations of therapist assistance at the paretic foot, non-paretic foot, and trunk. Altered Muscle Activation Pattern (AMAP), a previously developed tool in our lab was used to evaluate the effects of LT parameter variation on eight lower-extremity muscle patterns in individuals with stroke. Repeated-measures mixed-model ANOVA was used to determine the effects of speed, BWS, and their interaction on AMAP scores. The Wilcoxon-signed rank test was used to determine the effects of therapist-assisted conditions on AMAP scores. Increased BWS mostly improved lower-extremity muscle activity patterns, but increased speed resulted in worse plantar flexor activity. Abnormal early plantar flexor activity during stance decreased with assistance at trunk and both feet, exaggerated plantar flexor activity during late swing decreased with assistance to the non-paretic foot or trunk, and diminished gluteus medius activity during stance increased with assistance to paretic foot and/or trunk. Therefore, different sets of training parameters have different immediate effects on activation patterns of each muscle and gait subphases.

Common brain activation and connectivity patterns supporting the generation of creative uses and creative metaphors.

Recent studies and reviews suggest that creative thinking is at least partly a domain-general cognitive ability, dependent on consistent patterns of brain activity including co-activation of the executive control and default mode networks. However, the degree to which the generation of ideas in different creative tasks relies on common brain activity remains unknown. In this fMRI study, participants were asked to generate creative ideas in both a uses generation task and a metaphor production task. Whole-brain analysis showed that generation of creative uses (relative to conventional uses) activated the bilateral inferior frontal gyrus (IFG), medial prefrontal cortex, left supplementary motor area, left angular gyrus (AG), left thalamus, and bilateral cerebellum posterior lobe. The generation of creative metaphors (relative to conventional metaphors) activated dorsal medial prefrontal cortex (dmPFC) and left AG. Importantly, regions active in both creative use and creative metaphor generation included the dmPFC and left AG. Psycho-physiological interactions analysis showed that the left AG was positively connected to the right precentral gyrus, and the dmPFC to the left IFG in both creative tasks. Our findings provide evidence that the generation of creative ideas relies on a core creative network related to remote semantic association-making and conceptual integration, offering new insight into the domain-general mechanisms underlying creative thinking.

Investigating the role of Prefrontal Neurons in cognitive tasks through Fiber Photometry and Adapted Barnes Maze Protocols

The medial prefrontal cortex (mPFC) is essential in the execution of cognitive tasks, however very little is known on how these neurons are modulated during specific tasks and which subtype of neurons are responsible for so. Therego, with the intention of addressing this issue, we recorded mPFC gabaergic and glutamatergic activation patterns through fiber photometry (FIP) in mice, while simultaneously performing the Barnes Maze (BM) cognitive task (4 day behavioral trial). In addition, an altered structural and procedural protocol for BM was validated in this study due to necessary modifications allowing FIP and BM to happen simultaneously. A successful protocol validation was followed by our preliminary results, which showed that both glutamatergic and gabaergic neurons presented significant change in activation intensity and number of events in specific contexts throughout the task days. In addition, when stratified and crossed with BM performance parameters, such as latency to complete tasks and adopted strategy, glutamatergic and gabaergic neurons presented a significant decline in both activation patterns and number of activation events throughout the days. This data suggest not only an important role of glutamatergic and gabaergic mPFC neurons in learning, memory and decision making, but also that activation patterns of each of these groups may serve as markers for cognitive progression and/or dysfunction. KEY-WORDS: Memory, Learning, Decision Making, Medial Prefrontal Cortex (mPFC), Fiber Photometry (FIP), Barnes Maze (BM), Glutamatergic, Gabaergic, Neuronal Activity, Neuronal Activation Patterns, Neuronal Dynamics.

O córtex pré-frontal medial (mPFC) é essencial na execução de tarefas cognitivas, no entanto, pouco se sabe sobre como esses neurônios são modulados durante tarefas específicas e qual subtipo de neurônios é responsável por isso. Portanto, com a intenção de abordar essa questão, registramos os padrões de ativação de neurônios gabaérgicos e glutamatérgicos do mPFC por meio de fotometria de fibra (FIP) em camundongos, enquanto realizávamos simultaneamente a tarefa cognitiva do Labirinto de Barnes (BM) (ensaio comportamental de 4 dias). Além disso, um protocolo estrutural e procedimental alterado para o BM foi validado neste estudo devido a modificações necessárias que permitiram a realização simultânea de FIP e BM. Uma validação bem-sucedida do protocolo foi seguida pelos nossos resultados preliminares, que mostraram que tanto os neurônios glutamatérgicos quanto os gabaérgicos apresentaram mudanças significativas na intensidade de ativação e no número de eventos em contextos específicos ao longo dos dias da tarefa. Além disso, quando estratificados e cruzados com parâmetros de desempenho do BM, como latência para completar as tarefas e estratégia adotada, os neurônios glutamatérgicos e gabaérgicos apresentaram uma diminuição significativa nos padrões de ativação e no número de eventos de ativação ao longo dos dias. Esses dados sugerem não apenas um papel importante dos neurônios glutamatérgicos e gabaérgicos do mPFC na aprendizagem, memória e tomada de decisões, mas também que os padrões de ativação de cada um desses grupos podem servir como marcadores de progressão e/ou disfunção cognitiva. PALAVRAS-CHAVE: Memória, Aprendizagem, Tomada de Decisões, Córtex Pré-Frontal Medial (mPFC), Fotometria de Fibra (FIP), Labirinto de Barnes (BM), Glutamatérgico, Gabaérgico, Atividade Neuronal, Padrões de Ativação Neuronal, Dinâmica Neuronal.

Paradoxical Reasoning: An fMRI Study.

Paradoxes are a special form of reasoning leading to absurd inferences in contrast to logical reasoning that is used to reach valid conclusions. A functional MRI (fMRI) study was conducted to investigate the neural substrates of paradoxical and deductive reasoning. Twenty-four healthy participants were scanned using fMRI, while they engaged in reasoning tasks based on arguments, which were either Zeno's like paradoxes (paradoxical reasoning) or Aristotelian arguments (deductive reasoning). Clusters of significant activation for paradoxical reasoning were located in bilateral inferior frontal and middle temporal gyrus. Clusters of significant activation for deductive reasoning were located in bilateral superior and inferior parietal lobe, precuneus, and inferior frontal gyrus. These results confirmed that different brain activation patterns are engaged for paradoxical vs. deductive reasoning providing a basis for future studies on human physiological as well as pathological reasoning.

Comparison of Resting-State Functional MRI Methods for Characterizing Brain Dynamics.

Resting-state functional MRI (fMRI) exhibits time-varying patterns of functional connectivity. Several different analysis approaches have been developed for examining these resting-state dynamics including sliding window connectivity (SWC), phase synchrony (PS), co-activation pattern (CAP), and quasi-periodic patterns (QPP). Each of these approaches can be used to generate patterns of activity or inter-areal coordination which vary across time. The individual frames can then be clustered to produce temporal groupings commonly referred to as "brain states." Several recent publications have investigated brain state alterations in clinical populations, typically using a single method for quantifying frame-wise functional connectivity. This study directly compares the results of k-means clustering in conjunction with three of these resting-state dynamics methods (SWC, CAP, and PS) and quantifies the brain state dynamics across several metrics using high resolution data from the human connectome project. Additionally, these three dynamics methods are compared by examining how the brain state characterizations vary during the repeated sequences of brain states identified by a fourth dynamic analysis method, QPP. The results indicate that the SWC, PS, and CAP methods differ in the clusters and trajectories they produce. A clear illustration of these differences is given by how each one results in a very different clustering profile for the 24s sequences explicitly identified by the QPP algorithm. PS clustering is sensitive to QPPs with the mid-point of most QPP sequences grouped into the same single cluster. CAPs are also highly sensitive to QPPs, separating each phase of the QPP sequences into different sets of clusters. SWC (60s window) is less sensitive to QPPs. While the QPPs are slightly more likely to occur during specific SWC clusters, the SWC clustering does not vary during the 24s QPP sequences, the goal of this work is to improve both the practical and theoretical understanding of different resting-state dynamics methods, thereby enabling investigators to better conceptualize and implement these tools for characterizing functional brain networks.

Moving beyond the 'CAP' of the Iceberg: Intrinsic connectivity networks in fMRI are continuously engaging and overlapping.

Resting-state functional magnetic resonance imaging is currently the mainstay of functional neuroimaging and has allowed researchers to identify intrinsic connectivity networks (aka functional networks) at different spatial scales. However, little is known about the temporal profiles of these networks and whether it is best to model them as continuous phenomena in both space and time or, rather, as a set of temporally discrete events. Both categories have been supported by series of studies with promising findings. However, a critical question is whether focusing only on time points presumed to contain isolated neural events and disregarding the rest of the data is missing important information, potentially leading to misleading conclusions. In this work, we argue that brain networks identified within the spontaneous blood oxygenation level-dependent (BOLD) signal are not limited to temporally sparse burst moments and that these event present time points (EPTs) contain valuable but incomplete information about the underlying functional patterns. We focus on the default mode and show evidence that is consistent with its continuous presence in the BOLD signal, including during the event absent time points (EATs), i.e., time points that exhibit minimum activity and are the least likely to contain an event. Moreover, our findings suggest that EPTs may not contain all the available information about their corresponding networks. We observe distinct default mode connectivity patterns obtained from all time points (AllTPs), EPTs, and EATs. We show evidence of robust relationships with schizophrenia symptoms that are both common and unique to each of the sets of time points (AllTPs, EPTs, EATs), likely related to transient patterns of connectivity. Together, these findings indicate the importance of leveraging the full temporal data in functional studies, including those using event-detection approaches.

Normalizing the brain connectome for communication through synchronization.

Networks in neuroscience determine how brain function unfolds, and their perturbations lead to psychiatric disorders and brain disease. Brain networks are characterized by their connectomes, which comprise the totality of all connections, and are commonly described by graph theory. This approach is deeply rooted in a particle view of information processing, based on the quantification of informational bits such as firing rates. Oscillations and brain rhythms demand, however, a wave perspective of information processing based on synchronization. We extend traditional graph theory to a dual, particle-wave, perspective, integrate time delays due to finite transmission speeds, and derive a normalization of the connectome. When applied to the database of the Human Connectome Project, it explains the emergence of frequency-specific network cores including the visual and default mode networks. These findings are robust across human subjects (N = 100) and are a fundamental network property within the wave picture. The normalized connectome comprises the particle view in the limit of infinite transmission speeds and opens the applicability of graph theory to a wide range of novel network phenomena, including physiological and pathological brain rhythms. These two perspectives are orthogonal, but not incommensurable, when understood within the novel, here-proposed, generalized framework of structural connectivity.

Altered anterior default mode network dynamics in progressive multiple sclerosis.

BACKGROUND: Modifications in brain function remain relatively unexplored in progressive multiple sclerosis (PMS), despite their potential to provide new insights into the pathophysiology of the disease at this stage. OBJECTIVES: To characterize the dynamics of functional networks at rest in patients with PMS, and the relation with clinical disability. METHODS: Thirty-two patients with PMS underwent clinical and cognitive assessment. The dynamic properties of functional networks, retrieved from transient brain activity, were obtained from patients and 25 healthy controls (HCs). Sixteen HCs and 19 patients underwent a 1-year follow-up (FU) clinical and imaging assessment. Differences in the dynamic metrics between groups, their longitudinal changes, and the correlation with clinical disability were explored. RESULTS: PMS patients, compared to HCs, showed a reduced dynamic functional activation of the anterior default mode network (aDMN) and a decrease in its opposite-signed co-activation with the executive control network (ECN), at baseline and FU. Processing speed and visuo-spatial memory negatively correlated to aDMN dynamic activity. The anti-couplings between aDMN and auditory/sensory-motor network, temporal-pole/amygdala, or salience networks were differently associated with separate cognitive domains. CONCLUSION: Patients with PMS presented an altered aDMN functional recruitment and anti-correlation with ECN. The aDMN dynamic functional activity and interaction with other networks explained cognitive disability.

Muscle activation patterns and muscle synergies reflect different modes of coordination during upper extremity movement.

A core issue in motor control is how the central nervous system generates and selects the muscle activation patterns necessary to achieve a variety of behaviors and movements. Extensive studies have verified that it is the foundation to induce a complex movement by the modular combinations of several muscles with a synergetic relationship. However, a few studies focus on the synergetic similarity and dissimilarity among different types of movements, especially for the upper extremity movements. In this study, we introduced the non-negative matrix factorization (NMF) method to explore the muscle activation patterns and synergy structure under 6 types of movements, involving the hand open (HO), hand close (HC), wrist flexion (WF), wrist extension (WE), supination (SU), and pronation (PR). For this, we enrolled 10 healthy subjects to record the electromyography signal for NMF calculation. The results showed a highly modular similarity of the muscle synergy among subjects under the same movement. Furthermore, Spearman's correlation analysis indicated significant similarities among HO-WE, HO-SU, and WE-SU (p < 0.001). Additionally, we also found shared synergy and special synergy in activation patterns among different movements. This study confirmed the theory of modular structure in the central nervous system, which yields a stable synergetic pattern under the same movement. Our findings on muscle synergy will be of great significance to motor control and even to clinical assessment techniques.

The characteristics of cortical activation when hemiplegic stroke survivors walk assisted by functional electrical stimulation / 中华物理医学与康复杂志

Objective:To explore the characteristics of cortical activation during the stimulation-assisted walking of hemiplegic stroke survivors using functional near-infrared spectroscopy (fNIRS).Methods:Eight stroke survivors with right hemiplegia (average age 44.4±7.2 years) in a self-controlled study each walked at 2km/h on a treadmill, alone and assisted by functional electronic stimulation (FES). Real-time near-infrared spectroscopic images were recorded. The Matlab NIRS-SPM toolkit was employed to calculate the changes in oxyhemoglobin concentration in different cortical regions. A general linear model was evaluated which integrated the task effects, and version 20.0 of the SPSS statistical software was used to perform single sample or paired sample t-tests of the beta values so as to produce activation hot maps of the significant differences.Results:During unassisted walking channels 8, 10, 11, 13-20, 23-28, 30 and 32-37 were significantly activated. During FES-assisted walking it was the same channels plus channels 9 and 22, 31. The results suggest that in walking the cortical regions activated are mainly located in M1 of the unaffected hemisphere, supplemented by M1 and SMA, PMC and S1 in the affected hemisphere. There were significant differences in the activation of channels 9, 24, 27, 32, 33 between the two walking tasks. FES-assistance enhances S1 activation on the unaffected side, as well as the SMA and PMC of the affected side more significantly.Conclusions:Bilateral asymmetrical activation is found mostly in M1 during walking with or without FES assistance. FES assistance significantly strengthens the compensatory activation of the PMC and SMA of the affected hemisphere while walking for those with hemiplegia.

Trunk Muscle Activation Patterns During Standing Turns in Patients With Stroke: An Electromyographic Analysis.

Recent evidence indicates that turning difficulty may correlate with trunk control; however, surface electromyography has not been used to explore trunk muscle activity during turning after stroke. This study investigated trunk muscle activation patterns during standing turns in healthy controls (HCs) and patients with stroke with turning difficulty (TD) and no TD (NTD). The participants with stroke were divided into two groups according to the 180° turning duration and number of steps to determine the presence of TD. The activation patterns of the bilateral external oblique and erector spinae muscles of all the participants were recorded during 90° standing turns. A total of 14 HCs, 14 patients with TD, and 14 patients with NTD were recruited. The duration and number of steps in the turning of the TD group were greater than those of the HCs, independent of the turning direction. However, the NTD group had a significantly longer turning duration than did the HC group only toward the paretic side. Their performance was similar when turning toward the non-paretic side; this result is consistent with electromyographic findings. Both TD and NTD groups demonstrated increased amplitudes of trunk muscles compared with the HC groups. Their trunk muscles failed to maintain consistent amplitudes during the entire movement of standing turns in the direction that they required more time or steps to turn toward (i.e., turning in either direction for the TD group and turning toward the paretic side for the NTD group). Patients with stroke had augmented activation of trunk muscles during turning. When patients with TD turned toward either direction and when patients with NTD turned toward the paretic side, the flexible adaptations and selective actions of trunk muscles observed in the HCs were absent. Such distinct activation patterns during turning may contribute to poor turning performance and elevate the risk of falling. Our findings provide insights into the contribution and importance of trunk muscles during turning and the association with TD after stroke. These findings may help guide the development of more effective rehabilitation therapies that target specific muscles for those with TD.