Spectral signatures of neurodegenerative diseases: how to decipher them?

Cross-Frequency Coupling as a Biomarker for Early Stroke Recovery

BACKGROUND

The application of neuroimaging-based biomarkers in stroke has enriched our understanding of post-stroke recovery mechanisms, including alterations in functional connectivity based on synchronous oscillatory activity across various cortical regions. Phase-amplitude coupling, a type of cross-frequency coupling, may provide additional mechanistic insight.

OBJECTIVE

To determine how the phase of prefrontal cortex delta (1-3 Hz) oscillatory activity mediates the amplitude of motor cortex beta (13-20 Hz) oscillations in individual's early post-stroke.

METHODS

Participants admitted to an inpatient rehabilitation facility completed resting and task-based EEG recordings and motor assessments around the time of admission and discharge along with structural neuroimaging. Unimpaired controls completed EEG procedures during a single visit. Mixed-effects linear models were performed to assess within- and between-group differences in delta-beta prefrontomotor coupling. Associations between coupling and motor status and injury were also determined.

RESULTS

Thirty individuals with stroke and 17 unimpaired controls participated. Coupling was greater during task versus rest conditions for all participants. Though coupling during affected extremity task performance decreased during hospitalization, coupling remained elevated at discharge compared to controls. Greater baseline coupling was associated with better motor status at admission and discharge and positively related to motor recovery. Coupling demonstrated both positive and negative associations with injury involving measures of lesion volume and overlap injury to anterior thalamic radiation, respectively.

CONCLUSIONS

This work highlights the utility of prefrontomotor cross-frequency coupling as a potential motor status and recovery biomarker in stroke. The frequency- and region-specific neurocircuitry featured in this work may also facilitate novel treatment strategies in stroke.

Functional connectivity drives stroke recovery: shifting the paradigm from correlation to causation

Stroke is a leading cause of disability, with deficits encompassing multiple functional domains. The heterogeneity underlying stroke poses significant challenges in the prediction of post-stroke recovery, prompting the development of neuroimaging-based biomarkers. Structural neuroimaging measurements, particularly those reflecting corticospinal tract injury, are well-documented in the literature as potential biomarker candidates of post-stroke motor recovery. Consistent with the view of stroke as a 'circuitopathy', functional neuroimaging measures probing functional connectivity may also prove informative in post-stroke recovery. An important step in the development of biomarkers based on functional neural network connectivity is the establishment of causality between connectivity and post-stroke recovery. Current evidence predominantly involves statistical correlations between connectivity measures and post-stroke behavioral status, either cross-sectionally or serially over time. However, the advancement of functional connectivity application in stroke depends on devising experiments that infer causality. In 1965, Sir Austin Bradford Hill introduced nine viewpoints to consider when determining the causality of an association: [1] Strength, [2] Consistency [3] Specificity, [4] Temporality, [5] Biological gradient, [6] Plausibility, [7] Coherence, [8] Experiment, and [9] Analogy. Collectively referred to as the Bradford Hill Criteria, these points have been widely adopted in epidemiology. In this review, we assert the value of implementing Bradford Hill's framework to stroke rehabilitation and neuroimaging. We focus on the role of neural network connectivity measurements acquired from task-oriented and resting-state functional magnetic resonance imaging, electroencephalography, magnetoencephalography, and functional near-infrared spectroscopy in describing and predicting post-stroke behavioral status and recovery. We also identify research opportunities within each Bradford Hill tenet to shift the experimental paradigm from correlation to causation.

Coherent neural oscillations inform early stroke motor recovery

Neural oscillations may contain important information pertaining to stroke rehabilitation. This study examined the predictive performance of electroencephalography‐derived neural oscillations following stroke using a data‐driven approach. Individuals with stroke admitted to an inpatient rehabilitation facility completed a resting‐state electroencephalography recording and structural neuroimaging around the time of admission and motor testing at admission and discharge. Using a lasso regression model with cross‐validation, we determined the extent of motor recovery (admission to discharge change in Functional Independence Measurement motor subscale score) prediction from electroencephalography, baseline motor status, and corticospinal tract injury. In 27 participants, coherence in a 1–30 Hz band between leads overlying ipsilesional primary motor cortex and 16 leads over bilateral hemispheres predicted 61.8% of the variance in motor recovery. High beta (20–30 Hz) and alpha (8–12 Hz) frequencies contributed most to the model demonstrating both positive and negative associations with motor recovery, including high beta leads in supplementary motor areas and ipsilesional ventral premotor and parietal regions and alpha leads overlying contralesional temporal–parietal and ipsilesional parietal regions. Electroencephalography power, baseline motor status, and corticospinal tract injury did not significantly predict motor recovery during hospitalization (R² = 0–6.2%). Findings underscore the relevance of oscillatory synchronization in early stroke rehabilitation while highlighting contributions from beta and alpha frequency bands and frontal, parietal, and temporal–parietal regions overlooked by traditional hypothesis‐driven prediction models.

Past, Present, and Future of Non-invasive Brain Stimulation Approaches to Treat Cognitive Impairment in Neurodegenerative Diseases: Time for a Comprehensive Critical Review

Low birth rates and increasing life expectancy experienced by developed societies have placed an unprecedented pressure on governments and the health system to deal effectively with the human, social and financial burden associated to aging-related diseases. At present, ∼24 million people worldwide suffer from cognitive neurodegenerative diseases, a prevalence that doubles every five years. Pharmacological therapies and cognitive training/rehabilitation have generated temporary hope and, occasionally, proof of mild relief. Nonetheless, these approaches are yet to demonstrate a meaningful therapeutic impact and changes in prognosis. We here review evidence gathered for nearly a decade on non-invasive brain stimulation (NIBS), a less known therapeutic strategy aiming to limit cognitive decline associated with neurodegenerative conditions. Transcranial Magnetic Stimulation and Transcranial Direct Current Stimulation, two of the most popular NIBS technologies, use electrical fields generated non-invasively in the brain to long-lastingly enhance the excitability/activity of key brain regions contributing to relevant cognitive processes. The current comprehensive critical review presents proof-of-concept evidence and meaningful cognitive outcomes of NIBS in eight of the most prevalent neurodegenerative pathologies affecting cognition: Alzheimer's Disease, Parkinson's Disease, Dementia with Lewy Bodies, Primary Progressive Aphasias (PPA), behavioral variant of Frontotemporal Dementia, Corticobasal Syndrome, Progressive Supranuclear Palsy, and Posterior Cortical Atrophy. We analyzed a total of 70 internationally published studies: 33 focusing on Alzheimer's disease, 19 on PPA and 18 on the remaining neurodegenerative pathologies. The therapeutic benefit and clinical significance of NIBS remains inconclusive, in particular given the lack of a sufficient number of double-blind placebo-controlled randomized clinical trials using multiday stimulation regimes, the heterogeneity of the protocols, and adequate behavioral and neuroimaging response biomarkers, able to show lasting effects and an impact on prognosis. The field remains promising but, to make further progress, research efforts need to take in account the latest evidence of the anatomical and neurophysiological features underlying cognitive deficits in these patient populations. Moreover, as the development of in vivo biomarkers are ongoing, allowing for an early diagnosis of these neuro-cognitive conditions, one could consider a scenario in which NIBS treatment will be personalized and made part of a cognitive rehabilitation program, or useful as a potential adjunct to drug therapies since the earliest stages of suh diseases. Research should also integrate novel knowledge on the mechanisms and constraints guiding the impact of electrical and magnetic fields on cerebral tissues and brain activity, and incorporate the principles of information-based neurostimulation.

Fine particulate matter is a potential determinant of Alzheimer's disease: A systemic review and meta-analysis

Air pollution is a modifiable and preventable factor, and it is a possible risk factor for dementia. However, evidence from epidemiological studies is still limited. We conducted a systematic review and meta-analysis to summarize the epidemiological evidence for long-term effects of particulate matter with an aerodynamic diameter ≤2.5 μm (PM_2.5) on dementia/Alzheimer's disease (AD). Our inclusion criteria for eligible studies were: longitudinal cohort study design, no overlap in study population, age of study subject ≥50 years, detailed description of exposure assessment for PM_2.5, outdoor assessment of exposure to PM_2.5, usage of a clear definition of dementia/AD, and accessibility of sufficient information for meta-analysis. Six databases were searched for eligible studies. The random-effect model was used to synthesize the associations between PM_2.5 and dementia. After exclusion of all irrelevant studies, we analyzed the results of four cohort studies conducted in Canada, Taiwan, the UK, and the US during 2015-2018 among more than 12 million elderly subjects aged ≥50 years (N = 12,119,853). Our meta-analysis reveals that exposure to a 10 μg/m³ increase in PM_2.5 was significantly and positively associated with dementia (pooled HR = 3.26, 95% CI: 1.20, 5.31). In subgroup analyses, exposure to a 10 μg/m³ increase in PM_2.5 was found to be positively associated with AD (pooled HR = 4.82, 95% CI: 2.28, 7.36). Analysis of current epidemiological research on PM_2.5 and dementia confirmed that exposure to PM_2.5 was positively associated with a higher risk for dementia. However, it is to be noted that the included studies mainly relied on claim-based diagnosis and showed large differences in methods of exposure assessment, hence further epidemiological studies with well validated outcomes and with standardized exposure assessment models are required to ascertain the relationship between PM_2.5 and dementia/AD.