Publications by authors named "Morten L Kringelbach"

Article Synopsis
  • A topological principle suggests that the physical structure of the brain (its anatomy) significantly influences its functional dynamics.
  • Researchers found that while local connectivity patterns can explain much of brain function, they overlook the essential role of rare long-range cortical connections, which enhance information processing.
  • By incorporating both local connections and these rare long-range connections into a combined model (EDR+LR), they showed that this approach more effectively captures the complexities of brain activity compared to traditional geometric representations.
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Different whole-brain computational models have been recently developed to investigate hypotheses related to brain mechanisms. Among these, the Dynamic Mean Field (DMF) model is particularly attractive, combining a biophysically realistic model that is scaled up via a mean-field approach and multimodal imaging data. However, an important barrier to the widespread usage of the DMF model is that current implementations are computationally expensive, supporting only simulations on brain parcellations that consider less than 100 brain regions.

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Turbulence is a universal principle for fast energy and information transfer. Moving beyond the turbulence of fluid dynamics, turbulence has recently been demonstrated in brain dynamics. Importantly, turbulence can be expressed as the rich variability across spacetime of the local levels of synchronisation of coupled brain signals.

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Healthy brain function depends on balancing stable integration between brain areas for effective coordinated functioning, with coexisting segregation that allows subsystems to express their functional specialization. Metastability, a concept from the dynamical systems literature, has been proposed as a key signature that characterizes this balance. Building on this principle, the neuroscience literature has leveraged the phenomenon of metastability to investigate various aspects of brain function in health and disease.

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Article Synopsis
  • Serotonergic psychedelics, like LSD and psilocybin, alter consciousness and may help treat mental health issues, but how they work is still not entirely clear.
  • The study reviews subjective experiences, neuroimaging, and molecular actions, indicating LSD leads to more intense visionary experiences compared to psilocybin and alters brain connectivity patterns.
  • Findings suggest a complex relationship between different psychedelics' effects and highlight the need for standardized research methods to better understand these substances and their therapeutic potential.*
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Adaptive cognition relies on cooperation across anatomically distributed brain circuits. However, specialised neural systems are also in constant competition for limited processing resources. How does the brain's network architecture enable it to balance these cooperative and competitive tendencies? Here we use computational whole-brain modelling to examine the dynamical and computational relevance of cooperative and competitive interactions in the mammalian connectome.

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The structure of a complex network plays a crucial role in determining its dynamical properties. In this paper , we show that the the degree to which a network is directed and hierarchically organized is closely associated with the degree to which its dynamics break detailed balance and produce entropy. We consider a range of dynamical processes and show how different directed network features affect their entropy production rate.

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The brain is a complex non-equilibrium system capable of expressing many different dynamics as well as the transitions between them. We hypothesized that the level of non-equilibrium can serve as a signature of a given brain state, which was quantified using the arrow of time (the level of irreversibility). Using this thermodynamic framework, the irreversibility of emergent cortical activity was quantified from local field potential recordings in male Lister-hooded rats at different anesthesia levels and during the sleep-wake cycle.

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Depression is a multifactorial clinical syndrome with a low pharmacological treatment response rate. Therefore, identifying predictors of treatment response capable of providing the basis for future developments of individualized therapies is crucial. Here, we applied model-free and model-based measures of whole-brain turbulent dynamics in resting-state functional magnetic resonance imaging (fMRI) in healthy controls and unmedicated depressed patients.

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Aging is often associated with decline in brain processing power and neural predictive capabilities. To challenge this notion, we used magnetoencephalography (MEG) and magnetic resonance imaging (MRI) to record the whole-brain activity of 39 older adults (over 60 years old) and 37 young adults (aged 18-25 years) during recognition of previously memorised and varied musical sequences. Results reveal that when recognising memorised sequences, the brain of older compared to young adults reshapes its functional organisation.

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Article Synopsis
  • Music is analyzed as a non-verbal language that helps researchers understand how the brain processes complex sounds over time.
  • A study using magnetoencephalography with 70 participants found that recognizing familiar musical sequences activates a broad network in the brain, including areas like the auditory cortex and hippocampus.
  • The research highlights that while the auditory cortex reacts quickly to initial sounds, areas associated with higher cognitive functions show increasing activity as individuals recognize familiar music compared to novel sequences.
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Exploring the intricate relationship between brain's structure and function, and how this affects subjective experience is a fundamental pursuit in neuroscience. Psychedelic substances offer a unique insight into the influences of specific neurotransmitter systems on perception, cognition and consciousness. Specifically, their impact on brain function propagates across the structural connectome - a network of white matter pathways linking different regions.

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The human brain is a complex system, whose activity exhibits flexible and continuous reorganization across space and time. The decomposition of whole-brain recordings into harmonic modes has revealed a repertoire of gradient-like activity patterns associated with distinct brain functions. However, the way these activity patterns are expressed over time with their changes in various brain states remains unclear.

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Linguistic research showed that the depth of syntactic embedding is reflected in brain theta power. Here, we test whether this also extends to non-linguistic stimuli, specifically music. We used a hierarchical model of musical syntax to continuously quantify two types of expert-annotated harmonic dependencies throughout a piece of Western classical music: prolongation and preparation.

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A fundamental challenge in neuroscience is accurately defining brain states and predicting how and where to perturb the brain to force a transition. Here, we investigated resting-state fMRI data of patients suffering from disorders of consciousness (DoC) after coma (minimally conscious and unresponsive wakefulness states) and healthy controls. We applied model-free and model-based approaches to help elucidate the underlying brain mechanisms of patients with DoC.

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To not only survive, but also thrive, the brain must efficiently orchestrate distributed computation across space and time. This requires hierarchical organisation facilitating fast information transfer and processing at the lowest possible metabolic cost. Quantifying brain hierarchy is difficult but can be estimated from the asymmetry of information flow.

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"Supporting human flourishing" is a goal of governments and societies, yet the construct may appear hard to define. We discuss the emerging science of pleasure and flourishing, insights into the brain mechanisms of meaning making and thriving, and the potential for interdisciplinary studies to advance this promising scientific field.

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Article Synopsis
  • - Traumatic Brain Injury (TBI) leads to ongoing cognitive issues and affects both caregivers and healthcare systems; current severity assessments are often inadequate in predicting long-term outcomes.
  • - This review discusses innovative modeling approaches for analyzing TBI, including model-free and model-based methods, to discover new neuroimaging biomarkers and understand recovery processes in moderate-severe TBI patients over one year.
  • - The authors suggest that integrating whole-brain computational models with genomic data could enhance insights into TBI recovery and assist in identifying effective deep brain stimulation targets for improved outcomes.
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It has been previously shown that traumatic brain injury (TBI) is associated with reductions in metastability in large-scale networks in resting-state fMRI (rsfMRI). However, little is known about how TBI affects the local level of synchronization and how this evolves during the recovery trajectory. Here, we applied a novel turbulent dynamics framework to investigate whole-brain dynamics using an rsfMRI dataset from a cohort of moderate to severe TBI patients and healthy controls (HCs).

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Psilocybin therapy for depression has started to show promise, yet the underlying causal mechanisms are not currently known. Here, we leveraged the differential outcome in responders and non-responders to psilocybin (10 and 25 mg, 7 days apart) therapy for depression-to gain new insights into regions and networks implicated in the restoration of healthy brain dynamics. We used large-scale brain modelling to fit the spatiotemporal brain dynamics at rest in both responders and non-responders before treatment.

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Adolescence is a timed process with an onset, tempo, and duration. Nevertheless, the temporal dimension, especially the pace of maturation, remains an insufficiently studied aspect of developmental progression. The primary objective is to estimate the precise influence of pubertal maturational tempo on the configuration of associative brain regions.

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Despite significant improvements in our understanding of brain diseases, many barriers remain. Cognitive neuroscience faces four major challenges: complex structure-function associations; disease phenotype heterogeneity; the lack of transdiagnostic models; and oversimplified cognitive approaches restricted to the laboratory. Here, we propose a synergetics framework that can help to perform the necessary dimensionality reduction of complex interactions between the brain, body, and environment.

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The brain is a nonequilibrium system whose dynamics change in different brain states, such as wakefulness and deep sleep. Thermodynamics provides the tools for revealing these nonequilibrium dynamics. We used violations of the fluctuation-dissipation theorem to describe the hierarchy of nonequilibrium dynamics associated with different brain states.

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Recent findings have shown that psychedelics reliably enhance brain entropy (understood as neural signal diversity), and this effect has been associated with both acute and long-term psychological outcomes, such as personality changes. These findings are particularly intriguing, given that a decrease of brain entropy is a robust indicator of loss of consciousness (e.g.

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