Recovery of neural dynamics criticality in personalized whole-brain models of stroke

Rocha, Rodrigo P.; Koçillari, Loren; Suweis, Samir; Grazia, Michele De Filippo De; Schotten, Michel Thiebaut de; Zorzi, Marco; Corbetta, Maurizio

doi:10.1038/s41467-022-30892-6

Cited by 31 publications

(46 citation statements)

References 124 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Broadly speaking, these works have used distance from the critical point, variously assessed by the branching ratio, the quality of the power laws/avalanche shape collapse, the extent of multifractality, or the degree to which the exponent relation is satisfied as the relevant variables. For example, this approach has been taken with respect to sleep and sleep deprivation (Meisel et al, 2013 ; Priesemann et al, 2014 ), epilepsy (Meisel et al, 2012 , 2015 ; Arviv et al, 2016 ; Hagemann et al, 2021 ), hypoxia (Roberts et al, 2014 ), stroke (Rocha et al, 2022 ), schizophrenia (Alamian et al, 2022 ), and Alzheimer's disease (Jiang et al, 2018 ), to name a few. For overviews, see Massobrio et al ( 2015 ), Zimmern ( 2020 ), and Fekete et al ( 2021 ).…”

Section: Discussionmentioning

confidence: 99%

Quasicriticality explains variability of human neural dynamics across life span

Fosque

Alipour

Zare³

et al. 2022

Front. Comput. Neurosci.

View full text Add to dashboard Cite

Aging impacts the brain's structural and functional organization and over time leads to various disorders, such as Alzheimer's disease and cognitive impairment. The process also impacts sensory function, bringing about a general slowing in various perceptual and cognitive functions. Here, we analyze the Cambridge Centre for Ageing and Neuroscience (Cam-CAN) resting-state magnetoencephalography (MEG) dataset—the largest aging cohort available—in light of the quasicriticality framework, a novel organizing principle for brain functionality which relates information processing and scaling properties of brain activity to brain connectivity and stimulus. Examination of the data using this framework reveals interesting correlations with age and gender of test subjects. Using simulated data as verification, our results suggest a link between changes to brain connectivity due to aging and increased dynamical fluctuations of neuronal firing rates. Our findings suggest a platform to develop biomarkers of neurological health.

show abstract

Section: Discussionmentioning

confidence: 99%

Quasicriticality explains variability of human neural dynamics across life span

Fosque

Alipour

Zare³

et al. 2022

Front. Comput. Neurosci.

View full text Add to dashboard Cite

show abstract

“…Alternatively, they can be related to reactive changes associated with recovery but that do not directly cause it. To better address these aspects, our analyses are not limited to the lesion or specific areas and/or tracts, but rather focus on connectomics which provide rich information in the understanding of stroke-induced deficits, recovery process and prediction [e.g., ( 41 , 83 – 85 ). Thus, the proposed multi-modal approach will allow to better capture brain reorganization features related to the stroke.…”

Section: Challenges and Limitationsmentioning

confidence: 99%

Toward individualized medicine in stroke—The TiMeS project: Protocol of longitudinal, multi-modal, multi-domain study in stroke

et al. 2022

View full text Add to dashboard Cite

Despite recent improvements, complete motor recovery occurs in <15% of stroke patients. To improve the therapeutic outcomes, there is a strong need to tailor treatments to each individual patient. However, there is a lack of knowledge concerning the precise neuronal mechanisms underlying the degree and course of motor recovery and its individual differences, especially in the view of brain network properties despite the fact that it became more and more clear that stroke is a network disorder. The TiMeS project is a longitudinal exploratory study aiming at characterizing stroke phenotypes of a large, representative stroke cohort through an extensive, multi-modal and multi-domain evaluation. The ultimate goal of the study is to identify prognostic biomarkers allowing to predict the individual degree and course of motor recovery and its underlying neuronal mechanisms paving the way for novel interventions and treatment stratification for the individual patients. A total of up to 100 patients will be assessed at 4 timepoints over the first year after the stroke: during the first (T1) and third (T2) week, then three (T3) and twelve (T4) months after stroke onset. To assess underlying mechanisms of recovery with a focus on network analyses and brain connectivity, we will apply synergistic state-of-the-art systems neuroscience methods including functional, diffusion, and structural magnetic resonance imaging (MRI), and electrophysiological evaluation based on transcranial magnetic stimulation (TMS) coupled with electroencephalography (EEG) and electromyography (EMG). In addition, an extensive, multi-domain neuropsychological evaluation will be performed at each timepoint, covering all sensorimotor and cognitive domains. This project will significantly add to the understanding of underlying mechanisms of motor recovery with a strong focus on the interactions between the motor and other cognitive domains and multimodal network analyses. The population-based, multi-dimensional dataset will serve as a basis to develop biomarkers to predict outcome and promote personalized stratification toward individually tailored treatment concepts using neuro-technologies, thus paving the way toward personalized precision medicine approaches in stroke rehabilitation.

show abstract

“…CET predicts that ADHD can occur when the random neural event initiated by the NFVM and transmitted by the ARAS up to the thalamocortical systems cannot be normally modulated by these parts of the NCC. Whatever the neurophysiological reasons of it may be, there is evidence that critical phenomena are involved in ADHD (e.g., Zimmern, 2020;Heiney et al, 2021;Rocha et al, 2022).…”

Section: Mental Force In Critical Brain Dynamicsmentioning

confidence: 99%

From the origins to the stream of consciousness and its neural correlates

Yurchenko

2022

Front. Integr. Neurosci.

View full text Add to dashboard Cite

There are now dozens of very different theories of consciousness, each somehow contributing to our understanding of its nature. The science of consciousness needs therefore not new theories but a general framework integrating insights from those, yet not making it a still-born “Frankenstein” theory. First, the framework must operate explicitly on the stream of consciousness, not on its static description. Second, this dynamical account must also be put on the evolutionary timeline to explain the origins of consciousness. The Cognitive Evolution Theory (CET), outlined here, proposes such a framework. This starts with the assumption that brains have primarily evolved as volitional subsystems of organisms, inherited from primitive (fast and random) reflexes of simplest neural networks, only then resembling error-minimizing prediction machines. CET adopts the tools of critical dynamics to account for metastability, scale-free avalanches, and self-organization which are all intrinsic to brain dynamics. This formalizes the stream of consciousness as a discrete (transitive, irreflexive) chain of momentary states derived from critical brain dynamics at points of phase transitions and mapped then onto a state space as neural correlates of a particular conscious state. The continuous/discrete dichotomy appears naturally between the brain dynamics at the causal level and conscious states at the phenomenal level, each volitionally triggered from arousal centers of the brainstem and cognitively modulated by thalamocortical systems. Their objective observables can be entropy-based complexity measures, reflecting the transient level or quantity of consciousness at that moment.

show abstract

Recovery of neural dynamics criticality in personalized whole-brain models of stroke

Cited by 31 publications

References 124 publications

Quasicriticality explains variability of human neural dynamics across life span

Quasicriticality explains variability of human neural dynamics across life span

Toward individualized medicine in stroke—The TiMeS project: Protocol of longitudinal, multi-modal, multi-domain study in stroke

From the origins to the stream of consciousness and its neural correlates

Contact Info

Product

Resources

About