Excitatory-Inhibitory Homeostasis and Diaschisis: Tying the Local and Global Scales in the Post-stroke Cortex

Parvalbumin interneurons regulate rehabilitation-induced functional recovery after stroke and identify a rehabilitation drug

Motor disability is a critical impairment in stroke patients. Rehabilitation has a limited effect on recovery; but there is no medical therapy for post-stroke recovery. The biological mechanisms of rehabilitation in the brain remain unknown. Here, using a photothrombotic stroke model in male mice, we demonstrate that rehabilitation after stroke selectively enhances synapse formation in presynaptic parvalbumin interneurons and postsynaptic neurons in the rostral forelimb motor area with axonal projections to the caudal forelimb motor area where stroke was induced (stroke-projecting neuron). Rehabilitation improves motor performance and neuronal functional connectivity, while inhibition of stroke-projecting neurons diminishes motor recovery. Stroke-projecting neurons show decreased dendritic spine density, reduced external synaptic inputs, and a lower proportion of parvalbumin synapse in the total GABAergic input. Parvalbumin interneurons regulate neuronal functional connectivity, and their activation during training is necessary for recovery. Furthermore, gamma oscillation, a parvalbumin-regulated rhythm, is increased with rehabilitation-induced recovery in animals after stroke and stroke patients. Pharmacological enhancement of parvalbumin interneuron function improves motor recovery after stroke, reproducing rehabilitation recovery. These findings identify brain circuits that mediate rehabilitation-recovery and the possibility for rational selection of pharmacological agents to deliver the first molecular-rehabilitation therapeutic.

Role of homeostatic plasticity in critical brain dynamics following focal stroke lesions

Can focal brain lesions, such as those caused by stroke, disrupt critical brain dynamics? What biological mechanisms drive its recovery? In a recent study, we showed that focal lesions generate a sub-critical state that recovers over time in parallel with behavior (Rocha et al., Nat. Commun. 13, 2022). The loss of criticality in a cohort of stroke patients was associated with structural brain disconnections, while its recovery was accompanied by the re-modeling of specific white-matter tracts. These results were challenged by Janarek et al. (Sci. Rep. 13, 2023), who proposed an alternative interpretation for the anomalous monotonic decaying of the second cluster size, which is the neural signature originally used to infer loss of criticality. The present study tackles this controversy and provides evidence that the theoretical framework proposed by Janarek et al. cannot explain the anomalous cluster dynamics observed in our patients. Notably, this invalidates the claim that the brain maintains its critical dynamics regardless of the lesion severity. In addition, we explore biological mechanisms beyond white-matter remodeling that may facilitate the recovery of criticality over time. We considered two distinct scenarios: one where we suppress homeostatic plasticity, and another where we increase the excitability of brain regions. We find that suppressing homeostatic plasticity - specifically, the inhibition-excitation balance - disfavors the emergence of criticality. Conversely, increasing brain excitability can help to restore criticality when the latter is disrupted. Our results suggest that normalizing the excitation-inhibition balance is crucial for supporting recovery of critical brain dynamics.

Deep brain stimulation combined with morroniside promotes neural plasticity and motor functional recovery after ischemic stroke

Background and Objective

Until now, there has been an unmet need for treatments promoting chronic-phase post-stroke functional recovery. We previously found that morroniside promoted endogenous neurogenesis in ischemic stroke, but its therapeutic window was limited to the first 48 h. Here, we aimed to explore whether deep brain stimulation (DBS) combined with morroniside could enhance neurogenesis in rats subjected to focal ischemic stroke and contributes to functional recovery.

Methods

Beginning 2 weeks after the endothelin-1-induced stroke, rats were administered DBS of lateral cerebellar nucleus consecutively for 14 days, followed by morroniside for 7 consecutive days post-stimulation. Behavioral tests were used for assessing motor function. Local field potentials were recorded to evaluate neuronal excitability. Nissl staining was used to assess infarct volume. Immunofluorescence staining and Western blotting were carried out to uncover the stroke recovery mechanisms of DBS combined with morroniside treatment.

Results

The results showed that this combined treatment improved behavioral outcomes, enhanced cortical local field potentials, and diminished infarct volumes at 35 days post-stroke. Moreover, it notably amplified neurogenic responses post-stroke, evidenced by the proliferation of BrdU/SOX2 and BrdU/DCX in the subventricular zone, and their subsequent differentiation into BrdU/NeuN and BrdU/VgulT1 in the ischemic penumbra. Moreover, the combined treatment also elevated the amount of BrdU/Olig2 and the level of axonal sprouting-related proteins in the perilesional cortex.

Conclusion

Our results demonstrated that the combined treatment extended the neurorestorative efficacy of morroniside, reduced infarct size, enhanced neuronal excitability and accelerated sensorimotor function recovery. This therapeutic approach may emerge as a potential clinical intervention for chronic ischemic stroke.

Two-photon optogenetics-based assessment of neuronal connectivity in healthy and chronic hypoperfusion mice

Significance

Two-photon optogenetics and simultaneous calcium imaging can be used to visualize the response of surrounding neurons with respect to the activity of an optically stimulated target neuron, providing a direct method to assess neuronal connectivity.

Aim

We aim to develop a two-photon optogenetics-based method for evaluating neuronal connectivity, compare it to the existing indirect resting-state synchrony method, and investigate the application of the method to brain pathophysiology.

Approach

C1V1-mScarlet was introduced into GCaMP6s-expressing transgenic mice with an adeno-associated virus. Optical stimulation of a single target neuron and simultaneous calcium imaging of the target and surrounding cells were performed. Neuronal connectivity was evaluated from the correlation between the fluorescence intensity of the target and surrounding cells.

Results

The neuronal connectivity in the living brain was evaluated using two-photon optogenetics. However, resting-state synchrony was not always consistent with two-photon optogenetics-based connectivity. Comparison with neuronal synchrony measured during sensory stimulation suggested that the disagreement was due to external sensory input. Two-photon optogenetics-based connectivity significantly decreased in the common carotid artery occlusion model, whereas there was no significant change in the control group.

Conclusions

We successfully developed a direct method to evaluate neuronal connectivity in the living brain using two-photon optogenetics. The technique was successful in detecting connectivity impairment in hypoperfusion model mice.

Disentangling neuroplasticity mechanisms in post-stroke language recovery

A major objective in post-stroke aphasia research is to gain a deeper understanding of neuroplastic mechanisms that drive language recovery, with the ultimate goal of enhancing treatment outcomes. Subsequent to recent advances in neuroimaging techniques, we now have the ability to examine more closely how neural activity patterns change after a stroke. However, the way these neural activity changes relate to language impairments and language recovery is still debated. The aim of this review is to provide a theoretical framework to better investigate and interpret neuroplasticity mechanisms underlying language recovery in post-stroke aphasia. We detail two sets of neuroplasticity mechanisms observed at the synaptic level that may explain functional neuroimaging findings in post-stroke aphasia recovery at the network level: feedback-based homeostatic plasticity and associative Hebbian plasticity. In conjunction with these plasticity mechanisms, higher-order cognitive control processes dynamically modulate neural activity in other regions to meet communication demands, despite reduced neural resources. This work provides a network-level neurobiological framework for understanding neural changes observed in post-stroke aphasia and can be used to define guidelines for personalized treatment development.

Redefining stroke rehabilitation: Mobilizing the embodied goal-oriented brain

Advancements in stroke rehabilitation remain limited and call for a reorientation. Based on recent results, this study proposes a network-centric perspective on stroke, positing that it not only causes localized deficits but also affects the brain's intricate network of networks, transiting it into a pathological state. Translating these system-level insights into interventions requires brain theory, and the Distributed Adaptive Control (DAC) theory offers such a framework. When applied in the rehabilitation gaming system, these principles demonstrate superior results over conventional methods. This impact stems from activating extensive brain networks, particularly the executive control network, focused motor learning, and maintaining excitatory-inhibitory balance, which is essential for neural repair and functional reorganization. The analysis stresses uniting preclinical and clinical research and placing the architecture of the embodied volitional brain at the centre of rehabilitation approaches.

Patient-specific modeling for guided rehabilitation of stroke patients: the BrainX3 use-case

BrainX3 is an interactive neuroinformatics platform that has been thoughtfully designed to support neuroscientists and clinicians with the visualization, analysis, and simulation of human neuroimaging, electrophysiological data, and brain models. The platform is intended to facilitate research and clinical use cases, with a focus on personalized medicine diagnostics, prognostics, and intervention decisions. BrainX3 is designed to provide an intuitive user experience and is equipped to handle different data types and 3D visualizations. To enhance patient-based analysis, and in keeping with the principles of personalized medicine, we propose a framework that can assist clinicians in identifying lesions and making patient-specific intervention decisions. To this end, we are developing an AI-based model for lesion identification, along with a mapping of tract information. By leveraging the patient's lesion information, we can gain valuable insights into the structural damage caused by the lesion. Furthermore, constraining whole-brain models with patient-specific disconnection masks can allow for the detection of mesoscale excitatory-inhibitory imbalances that cause disruptions in macroscale network properties. Finally, such information has the potential to guide neuromodulation approaches, assisting in the choice of candidate targets for stimulation techniques such as Transcranial Ultrasound Stimulation (TUS), which modulate E-I balance, potentiating cortical reorganization and the restoration of the dynamics and functionality disrupted due to the lesion.

From mechanisms to markers: novel noninvasive EEG proxy markers of the neural excitation and inhibition system in humans

Brain function is a product of the balance between excitatory and inhibitory (E/I) brain activity. Variation in the regulation of this activity is thought to give rise to normal variation in human traits, and disruptions are thought to potentially underlie a spectrum of neuropsychiatric conditions (e.g., Autism, Schizophrenia, Downs' Syndrome, intellectual disability). Hypotheses related to E/I dysfunction have the potential to provide cross-diagnostic explanations and to combine genetic and neurological evidence that exists within and between psychiatric conditions. However, the hypothesis has been difficult to test because: (1) it lacks specificity-an E/I dysfunction could pertain to any level in the neural system- neurotransmitters, single neurons/receptors, local networks of neurons, or global brain balance - most researchers do not define the level at which they are examining E/I function; (2) We lack validated methods for assessing E/I function at any of these neural levels in humans. As a result, it has not been possible to reliably or robustly test the E/I hypothesis of psychiatric disorders in a large cohort or longitudinal patient studies. Currently available, in vivo markers of E/I in humans either carry significant risks (e.g., deep brain electrode recordings or using Positron Emission Tomography (PET) with radioactive tracers) and/or are highly restrictive (e.g., limited spatial extent for Transcranial Magnetic Stimulation (TMS) and Magnetic Resonance Spectroscopy (MRS). More recently, a range of novel Electroencephalography (EEG) features has been described, which could serve as proxy markers for E/I at a given level of inference. Thus, in this perspective review, we survey the theories and experimental evidence underlying 6 novel EEG markers and their biological underpinnings at a specific neural level. These cheap-to-record and scalable proxy markers may offer clinical utility for identifying subgroups within and between diagnostic categories, thus directing more tailored sub-grouping and, therefore, treatment strategies. However, we argue that studies in clinical populations are premature. To maximize the potential of prospective EEG markers, we first need to understand the link between underlying E/I mechanisms and measurement techniques.

Cortical connectivity in stroke using signals from resting-state EEG: a review of current literature

INTRODUCTION

Stroke is considered a substantial cause of disability worldwide and many researches are focused on rehabilitative interventions. Functional magnetic resonance imaging studies centered on brain networks after stroke describe affected functional connectivity between areas within the default mode, sensorimotor, visual, fronto-parietal and executive networks. Recent studies renewed the perspective of utilizing electroencephalography to describe markers of cortical activity in stroke and recovery neurophysiological processes.

METHODS

We included in our research studies realized on patients that had an ischemic or hemorrhagic stroke that performed electroencephalography and had an analysis of connectivity indices. Resting-state electroencephalography has the advantage of including patients with any neurological deficit and it is easier to perform than the task-based variant. The changes in resting-state EEG networks after stroke are important to determine a relationship between frequency cortical activity and spatial conformation of a network. From conventional to quantitative EEG analysis in stroke, these techniques are improved with additional brain connectivity tools that lead to a better characterization between injured areas and other intra- and inter-hemispheric areas.

RESULTS

There are studies that underline the disruptions in local networks in a frequency-dependent modality after stroke, while other results are focused on bilateral changes in resting-state cortical networks, independent of the side of the lesions.

CONCLUSIONS

Many studies found alterations in various connectivity measures after stroke with the help of EEG, but the clinical significance of these findings is a field of increasing interest in research area.

Long-interval intracortical inhibition in primary motor cortex related to working memory in middle-aged adults

Introduction

Excitability of the primary motor cortex measured with TMS has been associated with cognitive dysfunctions in patient populations. However, only a few studies have explored this relationship in healthy adults, and even fewer have considered the role of biological sex.

Methods

Ninety-seven healthy middle-aged adults (53 male) completed a TMS protocol and a neuropsychological assessment. Resting Motor Threshold (RMT) and Long-Interval Intracortical Inhibition (LICI) were assessed in the left motor cortex and related to attention, episodic memory, working memory, reasoning, and global cognition composite scores to evaluate the relationship between cortical excitability and cognitive functioning.

Results

In the whole sample, there was a significant association between LICI and cognition; specifically, higher motor inhibition was related to better working memory performance. When the sample was broken down by biological sex, LICI was only associated with working memory, reasoning, and global cognition in men. No associations were found between RMT and cognitive functions.

Conclusion

Greater intracortical inhibition, measured by LICI, could be a possible marker of working memory in healthy middle-aged adults, and biological sex plays a critical role in this association.

Whole-Brain Network Models: From Physics to Bedside

Computational neuroscience has come a long way from its humble origins in the pioneering work of Hodgkin and Huxley. Contemporary computational models of the brain span multiple spatiotemporal scales, from single neuronal compartments to models of social cognition. Each spatial scale comes with its own unique set of promises and challenges. Here, we review models of large-scale neural communication facilitated by white matter tracts, also known as whole-brain models (WBMs). Whole-brain approaches employ inputs from neuroimaging data and insights from graph theory and non-linear systems theory to model brain-wide dynamics. Over the years, WBM models have shown promise in providing predictive insights into various facets of neuropathologies such as Alzheimer's disease, Schizophrenia, Epilepsy, Traumatic brain injury, while also offering mechanistic insights into large-scale cortical communication. First, we briefly trace the history of WBMs, leading up to the state-of-the-art. We discuss various methodological considerations for implementing a whole-brain modeling pipeline, such as choice of node dynamics, model fitting and appropriate parcellations. We then demonstrate the applicability of WBMs toward understanding various neuropathologies. We conclude by discussing ways of augmenting the biological and clinical validity of whole-brain models.