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Menon, D. K.

Publications and source records attributed to Menon, D. K..

11 recordsLinked to original sources

Diminished functional gradient of the precuneus during altered states of consciousness

The relationship between the default mode network (DMN) and task-positive networks, such as the frontoparietal control network (FPCN), is a prominent feature of functional connectivity (FC) in the human brain. This relationship is primarily anticorrelated at rest in healthy brains and is disrupted in altered states of consciousness. Although the DMN and FPCN seem to perform distinct and even opposing roles, they are anatomically adjacent and exhibit ambiguous boundaries. To test the hypothesis that the DMN-FPCN distinction manifests probabilistically rather than having absolute anatomical boundaries, we examined the differences in FC along the dorsal-ventral (d-v) axis in the posterior precuneus (PCu), which serves a convergence zone between the DMN and FPCN. Our findings indicate that the connectivity differences along this axis are continuous as characterized by linear slopes. Notably, these linear relationships (i.e., functional gradients of the precuneus/FGp) are present only within the territories of the DMN and FPCN, respectively associating with positive and negative slopes. Furthermore, the gradient is functionally relevant, as its spatial configurations change in specific ways in altered states of consciousness (ASC): the magnitude of FGp is similarly impaired across different types of ASC, while the spatial entropy of FGp differs between psychedelic and sedative states. These results suggest that the DMN and FPCN, while appearing distinct, may originate from a single, integrated mechanism. Significance StatementThis research provides new insights into the brains functional organization underlying human conscious states by examining the relationship between two large-scale networks: the default mode network (DMN) and the frontoparietal control network (FPCN). These networks, which are attuned to handle internal and external information respectively, are often viewed as oppositional. However, our findings indicate they form an integrated system with continuous connectivity. We identified the posterior precuneus as a key convergence point, revealing a gradient of connectivity between the two networks. This gradient flattens during altered states of consciousness induced by psychedelics or sedatives, showing a loss of functional differentiation between the DMN and FPCN.

neuroscience↗

A thalamic perspective of (un)consciousness in pharmacological and pathological states in humans

Currently, there is substantial ongoing discussion around the functional role of the thalamus in consciousness. What is missing in the literature, however, is a systematic investigation of the relevance of specific thalamic nuclei in pharmacologically and pathologically altered states of consciousness in humans. Using functional neuroimaging in both healthy anaesthetised volunteers and patients with disorders of consciousness (DOC), we sought to identify which specific thalamic subregions in both cohorts may be differentially significant for loss of consciousness. Our findings revealed that the pulvinar (Pu) and ventral-latero-ventral (VLV) nuclei, in anaesthesia, and the VLV, in DOC, had distinct functional connectivity patterns related to the default mode and somatomotor networks. Remarkably, among all nuclei, the Pu was found to have the strongest functional connectivity change with anaesthetic-induced loss of consciousness, while in DOC patients, we found the VLV revealed the strongest connectivity change in comparison with healthy controls. Furthermore, we provide evidence that this neural connectivity biomarker in patients also mirrors the changes observed at the behavioural level, which could have clinical implications for targeted deep brain stimulation in therapy for DOC.

neuroscience↗

FlowAtlas.jl: an interactive tool bridging FlowJo with computational tools in Julia

As the dimensionality, throughput, and complexity of cytometry data increases, so does the demand for user-friendly, interactive analysis tools that leverage high-performance machine learning frameworks. Here we introduce FlowAtlas.jl: an interactive web application that bridges the user-friendly environment of FlowJo and computational tools in Julia developed by the scientific machine learning community. We demonstrate the capabilities of FlowAtlas using a novel human multi-tissue, multi-donor immune cell dataset, highlighting key immunological findings.

bioinformatics↗

Accelerated Aging after Traumatic Brain Injury: an ENIGMA Multi-Cohort Mega-Analysis

ObjectiveThe long-term consequences of traumatic brain injury (TBI) on brain structure remain uncertain. In light of current evidence that even a single significant brain injury event increases the risk of dementia, brain-age estimation could provide a novel and efficient indexing of the long-term consequences of TBI. Brain-age procedures use predictive modeling to calculate brain-age scores for an individual using MRI data. Complicated mild, moderate and severe TBI (cmsTBI) is associated with a higher predicted (brain) age difference (PAD), but the progression of PAD over time remains unclear. Here we sought to examine whether PAD increases as a function of time since injury (TSI). MethodsAs part of the ENIGMA Adult Moderate and Severe (AMS)-TBI working group, we examine the largest TBI sample to date (n=343), along with controls, for a total sample size of 540, to reproduce and extend prior findings in the study of TBI brain age. T1w-MRI data were aggregated across 7 cohorts and brain age was established using a similar brain age algorithm to prior work in TBI. ResultsFindings show that PAD widens with longer TSI, and there was evidence for differences between sexes in PAD, with men showing more advanced brain age. We did not find evidence supporting a link between PAD and cognitive performance. InterpretationThis work provides evidence that changes in brain structure after cmsTBI are dynamic, with an initial period of change, followed by relative stability, eventually leading to further changes in the decades after a single cmsTBI.

neuroscience↗

Mapping Pharmacologically-induced Functional Reorganisation onto the Brain's Neurotransmitter Landscape

To understand how pharmacological interventions can exert their powerful effects on brain function, we need to understand how they engage the brains rich neurotransmitter landscape. Here, we bridge microscale molecular chemoarchitecture and pharmacologically-induced macroscale functional reorganisation, by relating the regional distribution of 19 neurotransmitter receptors and transporters obtained from Positron Emission Tomography, and the regional changes in functional MRI connectivity induced by 10 different mind-altering drugs: propofol, sevoflurane, ketamine, LSD, psilocybin, DMT, ayahuasca, MDMA, modafinil, and methylphenidate. Our results reveal that psychoactive drugs exert their effects on brain function by engaging multiple neurotransmitter systems. The effects of both anaesthetics and psychedelics on brain function are organised along hierarchical gradients of brain structure and function. Finally, we show that regional co-susceptibility to pharmacological interventions recapitulates co-susceptibility to disorder-induced structural alterations. Collectively, these results highlight rich statistical patterns relating molecular chemoarchitecture and drug-induced reorganisation of the brains functional architecture.

neuroscience↗

Paths to Oblivion: Common Neural Mechanisms of Anaesthesia and Disorders of Consciousness

The human brain generates a rich repertoire of spatiotemporal dynamics during normal wakefulness, supporting a wide variety of conscious experiences and cognitive functions. However, neural dynamics are reconfigured, in comparable ways, when consciousness is lost either due to anaesthesia or disorders of consciousness (DOC). Here, leveraging a neurobiologically realistic whole-brain computational model informed by functional MRI, diffusion MRI, and PET, we sought to identify the neurobiological mechanisms that explain the common reconfiguration of neural dynamics observed both for transient pharmacological intervention and chronic neuroanatomical injury. Our results show that, by incorporating local inhibitory action through a PET-based GABA receptor density map, our model can reproduce the brain dynamics of subjects undergoing propofol anaesthesia, and that this effect depends specifically on the spatial distribution of GABA receptors across cortical regions. Additionally, using a structural connectome obtained from DOC patients, we demonstrate how the dynamics that characterise loss of consciousness can emerge from changes in neuroanatomical connectivity. Crucially, we find that each of these two interventions generalises across datasets: a model with increased GABA-mediated inhibition can reproduce the dynamics of DOC patients brains, and a model with a DOC connectome is also compatible with brain dynamics observed during propofol anaesthesia. These results demonstrate how increased inhibition and connectome randomisation represent different neurobiological paths towards the characteristic dynamics of the unconscious brain. Overall, the present findings begin to disentangle the neurobiological mechanisms by which highly dissimilar perturbations of the brains neurodynamics can lead to unconsciousness.

neuroscience↗

A Synergistic Workspace for Human Consciousness Revealed by Integrated Information Decomposition

A central goal of neuroscience is to understand how the brain orchestrates information from multiple input streams into a unified conscious experience. Here, we address two fundamental questions: how is the human information-processing architecture functionally organised, and how does its organisation support consciousness? We combine network science and a rigorous information-theoretic notion of synergy to delineate a "synergistic global workspace", comprising gateway regions that gather synergistic information from specialised modules across the brain. This information is then integrated within the workspace and widely distributed via broadcaster regions. Through functional MRI analysis, we show that gateway regions of the synergistic workspace correspond to the brains default mode network, whereas broadcasters coincide with the executive control network. Demonstrating the empirical relevance of our proposed architecture for neural information processing, we show that loss of consciousness due to general anaesthesia or disorders of consciousness corresponds to a diminished ability of the synergistic workspace to integrate information, which is restored upon recovery. Thus, loss of consciousness coincides with a breakdown of information integration within the synergistic workspace of the human brain. This work contributes to conceptual and empirical reconciliation between two prominent scientific theories of consciousness, the Global Neuronal Workspace and Integrated Information Theory. Taken together, this work provides a new perspective on the role of prominent resting-state networks within the human information-processing architecture, while also advancing our understanding of how the human brain supports consciousness through the synergistic integration of information.

neuroscience↗

A synergistic core for human brain evolution and cognition

A fundamental question in neuroscience is how brain organisation gives rise to humans unique cognitive abilities. Although complex cognition is widely assumed to rely on frontal and parietal brain regions, the underlying mechanisms remain elusive: current approaches are unable to disentangle different forms of information processing in the brain. Here, we introduce a powerful framework to identify synergistic and redundant contributions to neural information processing and cognition. Leveraging multimodal data including functional MRI, PET, cytoarchitectonics and genetics, we reveal that synergistic interactions are the fundamental drivers of complex human cognition. Whereas redundant information dominates sensorimotor areas, synergistic activity is closely associated with the brains prefrontal-parietal and default networks; furthermore, meta-analytic results demonstrate a close relationship between high-level cognitive tasks and synergistic information. From an evolutionary perspective, the human brain exhibits higher prevalence of synergistic information than non-human primates. At the macroscale, we demonstrate that high-synergy regions underwent the highest degree of evolutionary cortical expansion. At the microscale, human-accelerated genes promote synergistic interactions by enhancing synaptic transmission. These convergent results provide critical insights that synergistic neural interactions underlie the evolution and functioning of humans sophisticated cognitive abilities, and demonstrate the power of our widely applicable information decomposition framework.

neuroscience↗

A Precuneal Causal Loop Mediates External and Internal Information Integration in the Human Brain

AO_SCPLOWBSTRACTC_SCPLOWHuman brains interpret external stimuli based on internal representations. One untested hypothesis is that the default-mode network (DMN) while responsible for internally oriented cognition can also encode externally oriented information. The unique neuroanatomical and functional fingerprint of the posterior part of the DMN supports a prominent role for the precuneus in this process. By utilising imaging data during two tasks from 100 participants, we found that the precuneus is functionally divided into dorsal and ventral subdivisions, each one differentially connecting to internally and externally oriented networks. The strength and direction of their connectivity is modulated by task difficulty in a manner dictated by the balance of internal versus external cognitive demands. Our study provides evidence that the medial posterior part of the DMN may drive interactions between large-scale networks, potentially allowing access to stored representations for moment to moment interpretation of an ever-changing environment.

neuroscience↗

Connectome Harmonic Decomposition of Human Brain Dynamics Reveals a Landscape of Consciousness

AbstractA central question in neuroscience is how consciousness arises from the dynamic interplay of brain structure and function. Departing from the predominant location- centric view in neuroimaging, here we provide an alternative perspective on the neural signatures of human consciousness: one that is intrinsically centered on how the distributed network architecture of the human structural connectome shapes functional activation across scales. We decompose cortical dynamics of resting-state functional MRI into fundamental distributed patterns of structure- function association: the harmonic modes of the human structural connectome. We contrast wakefulness with a wide spectrum of states of consciousness, spanning chronic disorders of consciousness but also pharmacological perturbations of consciousness induced with the anaesthetic propofol and the psychoactive drugs ketamine and LSD. Decomposing this wide spectrum of states of consciousness in terms of "connectome harmonics" reveals a generalisable structure-function signature of loss of consciousness, whether due to anaesthesia or brain injury. A mirror-reverse of this harmonic signature characterises the altered state induced by LSD or ketamine, reflecting psychedelic-induced decoupling of brain function from structure. The topology and neuroanatomy of the human connectome are crucial for shaping the repertoire of connectome harmonics into a fine-tuned indicator of consciousness, correlating with physiological and subjective scores across datasets and capable of discriminating between behaviourally indistinguishable sub-categories of brain-injured patients, tracking the presence of covert consciousness. Overall, connectome harmonic decomposition identifies meaningful relationships between neurobiology, brain function, and conscious experience.

neuroscience↗

Human labor pain is influenced by the voltage-gated potassium channel KV6.4 subunit

AO_SCPLOWBSTRACTC_SCPLOWWe sought genetic effects on labour pain by studying healthy women who did not request analgesia during their first delivery. Extensive sensory and psychometric testing were normal in these women, except for significantly higher cuff-pressure pain. We found an excess of heterozygotes carrying the rare allele of SNP rs140124801 in KCNG4. The rare variant KV6.4-Met419 exerts a dominant negative effect and cannot modulate the voltage-dependence of KV2.1 inactivation because it fails to traffic to the plasma membrane. In vivo, we observed Kcng4 (KV6.4) expression in 40% of retrograde labelled mouse uterine sensory neurones, all of which expressed KV2.1, and over 90% expressed nociceptor genes Trpv1 and Scn10a. In neurones overexpressing KV6.4-Met419, the voltage-dependence of inactivation for KV2.1 is more depolarised compared to neurones overexpressing KV6.4. Finally, KV6.4-Met419 overexpressing neurones have a higher action potential threshold. We conclude KV6.4 can influence human labour pain by modulating the excitability of uterine nociceptors.

neuroscience↗