Biology subjects

Monti, M. M.

Publications and source records attributed to Monti, M. M..

12 recordsLinked to original sources

bioRxiv2026

Mind-manifesting? Examining naturalistic reports from psychedelics, cannabis, meditation, and dreams from the ALTERD mobile application

Altered states of consciousness (ASC) refer to states that differ markedly from normal waking consciousness. ASC may occur spontaneously, such as in dreaming, or through consciousness modifying techniques, from meditation, to cannabis and psychedelics. The etymology behind the term psychedelic, meaning mind-manifesting, is based on the hypothesis that certain substances, including serotonergic hallucinogens, do not merely distort perception, but also afford genuine observation and insight into the nature of mind, a claim that remains empirically contested today. Here, we address this psychedelic hypothesis using 2,242 reports from the Psychedelics, Cannabis, Meditation, and Dreams categories from the ALTERD mobile application. Across categories, we examined semantic similarity, topic structure, visual phenomenology, and alignment with a priori ASC themes. The Psychedelics category was most semantically similar to Dreams, consistent with a hallucinogenic character, yet it also uniquely coupled with Meditation across ASC themes, including Personal Growth, lending support for the psychedelic hypothesis. Cannabis showed the opposite pattern: similar to Meditation semantically, but not aligned on ASC themes such as Personal Growth. Together, these findings indicate that psychedelics induce a dream-like state, yet support a meditation-like trajectory toward personal growth, whereas cannabis may share phenomenological features with meditation, but lacking a transformative therapeutic character.

pharmacology and toxicology↗

bioRxiv2025

Transcranial ultrasonic stimulation of central thalamus reduces arousal in healthy volunteers

We present the first causal evidence in the healthy human brain linking the central thalamus to vigilance and the pulvinar to visuospatial attention using low-intensity transcranial focused ultrasound stimulation (tFUS). In a within-subjects, counterbalanced design, 27 healthy volunteers completed the Psychomotor Vigilance Task (PVT), a vigilance task, and the Egly-Driver Task (EDT), which assesses visuospatial attention, before and after central thalamus, pulvinar, and sham sonication with tFUS. Central thalamic sonication significantly impaired performance on both tasks in a manner consistent with decreases in arousal. Targeting the pulvinar with tFUS resulted in more subtle changes in visuospatial attention. Participants were less reactive to visual stimuli presented in the visual field contralateral to the affected pulvinar. These results demonstrate that tFUS can elicit measurable behavioral changes in healthy volunteers and underscores its potential as a high-resolution tool for non-invasive brain mapping, capable of differentiating functional contributions of thalamic regions only millimeters apart.

neuroscience↗

bioRxiv2024

An AI-Driven Model of Consciousness, Its Disorders, and Their Treatment

Understanding disorders of consciousness (DOC) remains one of the most challenging problems in neuroscience, hindered by the lack of experimental models for probing mechanisms or testing interventions [1]. To address this, we introduce a generative adversarial AI framework [2] that pits deep neural networks--trained to detect consciousness across over 680,000 neuroelectro-physiology samples and validated on 565 patients, healthy volunteers, and animals--against interpretable, machine learning-driven neural field models [3]. This adversarial architecture produces biologically realistic simulations of both conscious and comatose brains that recapitulate empirical neurophysiological features across humans, monkeys, rats, and bats. Without explicit programming, the AI model retrodicts known DOC responses to brain stimulation and generates testable predictions about unconsciousness mechanisms. Two such predictions are validated here: selective disruption of the basal ganglia indirect pathway, supported by diffusion MRI in 51 DOC patients; and increased cortical inhibitory-to-inhibitory synaptic coupling, supported by RNA sequencing from resected brain tissue in six human coma patients and a rat stroke model. The model also identifies high-frequency subthalamic nucleus stimulation as a promising DOC intervention, supported here using electrophysiology data from human patients. This work introduces an AI framework for causal inference and therapeutic discovery in consciousness research and complex systems more broadly.

neuroscience↗

bioRxiv2024

The subcortical basis of subjective sleep quality

Study objectivesTo assess the association between self-reported measures of sleep quality and cortical and subcortical local morphometry. MethodsSleep quality, operationalized with the Pittsburgh Sleep Quality Index (PSQI), and neuroanatomical data from the full release of the young adult Human Connectome Project dataset were analyzed (N=1,112; 46% female; mean age: 28.8 years old). Local cortical and subcortical morphometry was measured with subject-specific segmentations resulting in voxelwise gray matter difference (i.e., voxel based morephometry) measurements for cortex and local shape measurements for subcortical regions. Associations between the total score of PSQI, two statistical groupings of its subcomponents (obtained with a principal component analysis), and their interaction with demographic (i.e., sex, age, handedness, years of education) and biometric (i.e., BMI) variables were assessed using a general linear model and a nonparametric permutation approach. ResultsSleep quality-related variance was significantly associated with subcortical morphometry, particularly in the bilateral caudate, putamen, and left pallidum, where smaller shape measures correlated with worse sleep quality. Notably, these associations were independent of demographic and biometric factors. In contrast, cortical morphometry, along with additional subcortical sites, showed no direct associations with sleep quality but demonstrated interactions with demographic and biometric variables. ConclusionsThis study reveals a specific link between self-reported sleep quality and subcortical morphometry, particularly within the striatum and pallidum, reinforcing the role of these regions in sleep regulation. These findings underscore the importance of considering subcortical morphology in sleep research and highlight potential neuromodulatory targets for sleep-related interventions. Statement of SignificanceThis study provides evidence for the role of subcortical structures in sleep regulation, demonstrating that poorer self-reported sleep quality is associated with reduced shape measures in the bilateral caudate, putamen, and left pallidum. These associations were independent of demographic and biometric factors, distinguishing subcortical morphometry as a unique correlate of sleep quality. In contrast, cortical morphology exhibited no direct relationship with sleep quality but showed interactions with factors such as sex, BMI, and age, highlighting the complexity of brain-sleep relationships. These findings contribute to a growing body of literature emphasizing the basal ganglias role in non-motor functions, including sleep regulation, and suggest potential neuromodulatory targets for sleep-related interventions, such as transcranial focused ultrasound or deep brain stimulation.

neuroscience↗

bioRxiv2023

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↗

bioRxiv2021

Evaluating denoising strategies in resting-state fMRI in traumatic brain injury (EpiBioS4Rx)

ObjectiveResting-state functional MRI is increasingly used in the clinical setting and is now included in some diagnostic guidelines for severe brain injury patients. However, to ensure high-quality data, one should mitigate fMRI-related noise typical of this population. Therefore, we aimed to evaluate the ability of different preprocessing strategies to mitigate noise-related signal (i.e., in-scanner movement and physiological noise) in functional connectivity of traumatic brain injury patients. MethodsWe applied nine commonly used denoising strategies, combined into 17 pipelines, to 88 traumatic brain injury patients from the Epilepsy Bioinformatics Study for Anti-epileptogenic Therapy clinical trial (EpiBioS4Rx). Pipelines were evaluated by three quality control metrics across three exclusion regimes based on the participants head movement profile. ResultsWhile no pipeline eliminated noise effects on functional connectivity, some pipelines exhibited relatively high effectiveness depending on the exclusion regime. Once high-motion participants were excluded, the choice of denoising pipeline becomes secondary - although this strategy leads to substantial data loss. Pipelines combining spike regression with physiological regressors were the best performers, whereas pipelines that used automated data driven methods performed comparatively worse. ConclusionIn this study, we report the first large-scale evaluation of denoising pipelines aimed at reducing noise-related functional connectivity in a clinical population known to be highly susceptible to in-scanner motion and significant anatomical abnormalities. If resting-state functional magnetic resonance is to be a successful clinical technique, it is crucial that procedures mitigating the effect of noise be systematically evaluated in the most challenging populations, such as traumatic brain injury datasets.

neuroscience↗

bioRxiv2021

Consciousness is supported by near-critical cortical electrodynamics

Mounting evidence suggests that during conscious states, the electrodynamics of the cortex are poised near a critical point or phase transition, and that this near-critical behavior supports the vast flow of information through cortical networks during conscious states. Here, for the first time, we empirically identify the specific critical point near which conscious cortical dynamics operate as the edge-of-chaos critical point, or the boundary between periodicity/stability and chaos/instability. We do so by applying the recently developed modified 0-1 chaos test to electrocorticography (ECoG) and magne-toencephalography (MEG) recordings from the cortices of humans and macaques across normal waking, generalized seizure, GABAergic anesthesia, and psychedelic states. Our evidence suggests that cortical information processing is disrupted during unconscious states because of a transition of cortical dynamics away from this critical point; conversely, we show that psychedelics may increase the information-richness of cortical activity by tuning cortical electrodynamics closer to this critical point. Finally, we analyze clinical electroencephalography (EEG) recordings from patients with disorders of consciousness (DOC), and show that assessing the proximity of cortical electrodynamics to the edge-of-chaos critical point may be clinically useful as a new biomarker of consciousness. Significance StatementWhat changes in the brain when we lose consciousness? One possibility is that the loss of consciousness corresponds to a transition of the brains electric activity away from edge-of-chaos criticality, or the knifes edge in between stability and chaos. Recent mathematical developments have produced novel tools for testing this hypothesis, which we apply for the first time to cortical recordings from diverse brain states. We show that the electric activity of the cortex is indeed poised near the boundary between stability and chaos during conscious states and transitions away from this boundary during unconsciousness, and that this transition disrupts cortical information processing.

neuroscience↗

bioRxiv2020

Real Time and Delayed Effects of Subcortical Low Intensity Focused Ultrasound

Deep brain nuclei are integral components of large-scale circuits mediating important cognitive and sensorimotor functions. However, because they fall outside the domain of conventional non-invasive neuromodulatory techniques, their study has been primarily based on neuropsychological models, limiting the ability to fully characterize their role and to develop interventions in cases where they are damaged. To address this gap, we used the emerging technology of non-invasive low-intensity focused ultrasound (LIFU) to directly modulate left lateralized basal ganglia structures in healthy volunteers. During sonication, we observed local and distal decreases in blood oxygenation level dependent (BOLD) signal in the targeted left globus pallidus (GP) and in large-scale cortical networks. We also observed a generalized decrease in relative perfusion throughout the cerebrum following sonication. These results show, for the first time using functional MRI data, the ability to modulate deep-brain nuclei using LIFU while measuring its local and global consequences, opening the door for future applications of subcortical LIFU.

neuroscience↗

bioRxiv2019

Emergence of consciousness and complexity amidst diffuse delta rhythms: the paradox of Angelman syndrome

Numerous theories link consciousness to informationally rich, complex neural dynamics. This idea is challenged by the observation that children with Angelman syndrome (AS), while fully conscious, display a hypersynchronous electroencephalogram (EEG) phenotype typical of information-poor dynamics associated with unconsciousness. If informational complexity theories are correct, then sufficiently complex dynamics must still exist during wakefulness and exceed that observed in sleep despite pathological delta (1 - 4 Hz) rhythms in children with AS. As characterized by multiscale metrics, EEGs from 35 children with AS feature significantly greater complexity during wakefulness compared with sleep, even when comparing the most pathological segments of wakeful EEG to the segments of sleep EEG least likely to contain conscious experiences, and when factoring out delta power differences across states. These findings support theories linking consciousness with complexity and warn against reverse inferring an absence of consciousness solely on the basis of clinical readings of EEG.

neuroscience↗

bioRxiv2019

EEG power spectra and subcortical pathology in chronic disorders of consciousness

ObjectiveTo determine (i) the association between long-term impairment of consciousness after severe brain injury, spontaneous brain oscillations, and underlying subcortical damage, and (ii) whether such data can be used to aid patient diagnosis, a process known to be susceptible to high error rates. MethodsCross-sectional observational sample of 116 patients with a disorder of consciousness secondary to brain injury, collected prospectively at a tertiary center between 2011 and 2013. Multimodal analyses relating clinical measures of impairment, electroencephalographic measures of spontaneous brain activity, and magnetic resonance imaging data of subcortical atrophy were conducted in 2018. ResultsIn the final analyzed sample of 61 patients, systematic associations were found between electroencephalographic power spectra and subcortical damage. Specifically, the ratio of beta-to-delta relative power was negatively associated with greater atrophy in regions of the bilateral thalamus and globus pallidus (both left > right) previously shown to be preferentially atrophied in chronic disorders of consciousness. Power spectrum total density was also negatively associated with widespread atrophy in regions of the left globus pallidus, right caudate, and in brainstem. Furthermore, we showed that the combination of demographics, encephalographic, and imaging data in an analytic framework can be employed to aid behavioral diagnosis. ConclusionsThese results ground, for the first time, electroencephalographic presentation detected with routine clinical techniques in the underlying brain pathology of disorders of consciousness and demonstrate how multimodal combination of clinical, electroencephalographic, and imaging data can be employed in potentially mitigating the high rates of misdiagnosis typical of this patient cohort. Search termsdisorders of consciousness, subcortical pathology, EEG, MRI.

neuroscience↗

bioRxiv2019

The thalamic basis of outcome and cognitive impairment in traumatic brain injury

ObjectiveTo understand how, biologically, the acute event of traumatic brain injury gives rise to a long-term disease, we address the relationship between evolving cortical and subcortical brain damage and measures of functional outcome and cognitive functioning at six months post-injury.\n\nMethodsLongitudinal analysis of clinical and MRI data collected, in a tertiary neurointensive care setting, in a continuous sample of 157 patients surviving moderate to severe traumatic brain injury between 2000 and 2018. For each patient we collected T1- and T2-weighted MRI data, acutely and at a six-months follow-up, as well as acute measures of injury severity (Glasgow Coma Scale) and follow-up measures of functional impairment (Glasgow Outcome Scale extended), and, in a subset of patients, neuropsychological measures of attention, executive functions, and episodic memory.\n\nResultsIn the final cohort of 113 subcortical and 92 cortical datasets that survived (blind) quality control, extensive atrophy was observed over the first six months post-injury across the brain. Nonetheless, only atrophy within subcortical regions, particularly in left thalamus, were associated with functional outcome and neuropsychological measures of attention, executive functions, and episodic memory. Furthermore, when brought together in an analytical model, longitudinal brain measurements could distinguish good versus bad outcome with 90% accuracy, whereas acute brain and clinical measurements alone could only achieve 20% accuracy.\n\nInterpretationDespite great injury heterogeneity, secondary thalamic pathology is a measurable minimum common denominator mechanism directly relating biology to clinical measures of outcome and cognitive functioning, potentially linking the acute \"event\" and the long(er)-term \"disease\" of TBI.

neuroscience↗

bioRxiv2017

The language of music: Common neural codes for structured sequences in music and natural language

The ability to process structured sequences is a central feature of natural language but also characterizes many other domains of human cognition. In this fMRI study, we measured brain metabolic response in musicians as they generated structured and non-structured sequences in language and music. We employed a univariate and multivariate cross-classification approach to provide evidence that a common neural code underlies the production of structured sequences across the two domains. Crucially, the common substrate includes Brocas area, a region well known for processing structured sequences in language. These findings have several implications. First, they directly support the hypothesis that language and music share syntactic integration mechanisms. Second, they show that Brocas area is capable of operating supramodally across these two domains. Finally, these results dismiss the recent hypothesis that domain general processes or proximal neural substrates explain the previously observed \"overlap\" between neuroimaging activations across the two domains.

neuroscience↗