Reduced emergent character of neural dynamics in patients with a disrupted connectome.

High-level brain functions are widely believed to emerge from the orchestrated activity of multiple neural systems. However, lacking a formal definition and practical quantification of emergence for experimental data, neuroscientists have been unable to empirically test this long-standing conjecture. Here we investigate this fundamental question by leveraging a recently proposed framework known as "Integrated Information Decomposition," which establishes a principled information-theoretic approach to operationalise and quantify emergence in dynamical systems - including the human brain. By analysing functional MRI data, our results show that the emergent and hierarchical character of neural dynamics is significantly diminished in chronically unresponsive patients suffering from severe brain injury. At a functional level, we demonstrate that emergence capacity is positively correlated with the extent of hierarchical organisation in brain activity. Furthermore, by combining computational approaches from network control theory and whole-brain biophysical modelling, we show that the reduced capacity for emergent and hierarchical dynamics in severely brain-injured patients can be mechanistically explained by disruptions in the patients' structural connectome. Overall, our results suggest that chronic unresponsiveness resulting from severe brain injury may be related to structural impairment of the fundamental neural infrastructures required for brain dynamics to support emergence.

Distributed harmonic patterns of structure-function dependence orchestrate human consciousness.

A central question in neuroscience is how consciousness arises from the dynamic interplay of brain structure and function. Here we decompose functional MRI signals from pathological and pharmacologically-induced perturbations of consciousness into distributed patterns of structure-function dependence across scales: the harmonic modes of the human structural connectome. We show that structure-function coupling is a generalisable indicator of consciousness that is under bi-directional neuromodulatory control. We find increased structure-function coupling across scales during loss of consciousness, whether due to anaesthesia or brain injury, capable of discriminating between behaviourally indistinguishable sub-categories of brain-injured patients, tracking the presence of covert consciousness. The opposite harmonic signature characterises the altered state induced by LSD or ketamine, reflecting psychedelic-induced decoupling of brain function from structure and correlating with physiological and subjective scores. Overall, connectome harmonic decomposition reveals how neuromodulation and the network architecture of the human connectome jointly shape consciousness and distributed functional activation across scales.

Whole-brain modelling identifies distinct but convergent paths to unconsciousness in anaesthesia and disorders of consciousness.

The human brain entertains rich spatiotemporal dynamics, which are drastically reconfigured when consciousness is lost due to anaesthesia or disorders of consciousness (DOC). Here, we sought to identify the neurobiological mechanisms that explain how transient pharmacological intervention and chronic neuroanatomical injury can lead to common reconfigurations of neural activity. We developed and systematically perturbed a neurobiologically realistic model of whole-brain haemodynamic signals. By incorporating PET data about the cortical distribution of GABA receptors, our computational model reveals a key role of spatially-specific local inhibition for reproducing the functional MRI activity observed during anaesthesia with the GABA-ergic agent propofol. Additionally, incorporating diffusion MRI data obtained from DOC patients reveals that the dynamics that characterise loss of consciousness can also emerge from randomised neuroanatomical connectivity. Our results generalise between anaesthesia and DOC datasets, demonstrating how increased inhibition and connectome perturbation represent distinct neurobiological paths towards the characteristic activity of the unconscious brain.

Preserved fractal character of structural brain networks is associated with covert consciousness after severe brain injury.

Self-similarity is ubiquitous throughout natural phenomena, including the human brain. Recent evidence indicates that fractal dimension of functional brain networks, a measure of self-similarity, is diminished in patients diagnosed with disorders of consciousness arising from severe brain injury. Here, we set out to investigate whether loss of self-similarity is observed in the structural connectome of patients with disorders of consciousness. Using diffusion MRI tractography from N = 11 patients in a minimally conscious state (MCS), N = 10 patients diagnosed with unresponsive wakefulness syndrome (UWS), and N = 20 healthy controls, we show that fractal dimension of structural brain networks is diminished in DOC patients. Remarkably, we also show that fractal dimension of structural brain networks is preserved in patients who exhibit evidence of covert consciousness by performing mental imagery tasks during functional MRI scanning. These results demonstrate that differences in fractal dimension of structural brain networks are quantitatively associated with chronic loss of consciousness induced by severe brain injury, highlighting the close connection between structural organisation of the human brain and its ability to support cognitive function.

Dopaminergic brainstem disconnection is common to pharmacological and pathological consciousness perturbation.

Clinical research into consciousness has long focused on cortical macroscopic networks and their disruption in pathological or pharmacological consciousness perturbation. Despite demonstrating diagnostic utility in disorders of consciousness (DoC) and monitoring anesthetic depth, these cortico-centric approaches have been unable to characterize which neurochemical systems may underpin consciousness alterations. Instead, preclinical experiments have long implicated the dopaminergic ventral tegmental area (VTA) in the brainstem. Despite dopaminergic agonist efficacy in DoC patients equally pointing to dopamine, the VTA has not been studied in human perturbed consciousness. To bridge this translational gap between preclinical subcortical and clinical cortico-centric perspectives, we assessed functional connectivity changes of a histologically characterized VTA using functional MRI recordings of pharmacologically (propofol sedation) and pathologically perturbed consciousness (DoC patients). Both cohorts demonstrated VTA disconnection from the precuneus and posterior cingulate (PCu/PCC), a main default mode network node widely implicated in consciousness. Strikingly, the stronger VTA-PCu/PCC connectivity was, the more the PCu/PCC functional connectome resembled its awake configuration, suggesting a possible neuromodulatory relationship. VTA-PCu/PCC connectivity increased toward healthy control levels only in DoC patients who behaviorally improved at follow-up assessment. To test whether VTA-PCu/PCC connectivity can be affected by a dopaminergic agonist, we demonstrated in a separate set of traumatic brain injury patients without DoC that methylphenidate significantly increased this connectivity. Together, our results characterize an in vivo dopaminergic connectivity deficit common to reversible and chronic consciousness perturbation. This noninvasive assessment of the dopaminergic system bridges preclinical and clinical work, associating dopaminergic VTA function with macroscopic network alterations, thereby elucidating a critical aspect of brainstem-cortical interplay for consciousness.

Propofol sedation-induced alterations in brain connectivity reflect parvalbumin interneurone distribution in human cerebral cortex.

BACKGROUND: Propofol, a commonly used intravenous anaesthetic, binds to type A gamma aminobutyric acid (GABA) receptors in mammalian brain. Previous work on its anaesthetic action has characterised either the biochemistry underlying propofol binding or the associated changes in brain network dynamics during sedation. Despite these advances, no study has focused on understanding how propofol action at the cellular level results in changes in brain network connectivity. METHODS: We used human whole-brain microarray data to generate distribution maps for genes that mark the primary GABAergic cortical interneurone subtypes (somatostatin, parvalbumin [PV], and 5-hydroxytryptamine 3A. Next, 25 healthy participants underwent propofol-induced sedation during resting state functional MRI scanning. We used partial least squares analysis to identify the brain regions in which connectivity patterns were most impacted by propofol sedation. We then correlated these multimodal cortical patterns to determine if a specific interneurone subtype was disproportionately expressed in brain regions in which connectivity patterns were altered during sedation. RESULTS: Brain networks that were significantly altered by propofol sedation had a high density of PV-expressing GABAergic interneurones. Brain networks that anticorrelated during normal wakefulness, namely the default mode network and attentional and frontoparietal control networks, increased in correlation during sedation. CONCLUSIONS: PV-expressing interneurones are highly expressed in brain regions with altered connectivity profiles during propofol-induced sedation. This study also demonstrates the utility of leveraging multiple datasets to address multiscale neurobiological problems.

Structural optimality and neurogenetic expression mediate functional dynamics in the human brain.

The human brain exhibits a rich functional repertoire in terms of complex functional connectivity patterns during rest and tasks. However, how this is developed upon a fixed structural anatomy remains poorly understood. Here we investigated the hypothesis that resting state functional connectivity and the manner in which it changes during tasks related to a set of underlying structural connections that promote optimal communication in the brain. We used a game-theoretic model to identify such optimal connections in the structural connectome of 50 healthy individuals and subsequently used the optimal structural connections to predict resting-state functional connectivity with high accuracy. In contrast, we found that nonoptimal connections accurately predicted functional connectivity during a working memory task. We further found that this balance between optimal and nonoptimal connections between brain regions was associated with a specific gene expression linked to neurotransmission. This multimodal evidence shows for the first time that structure-function relationships in the human brain are related to how brain networks navigate information along different white matter connections as well as the brain's underlying genetic profile.

Consciousness-specific dynamic interactions of brain integration and functional diversity.

Prominent theories of consciousness emphasise different aspects of neurobiology, such as the integration and diversity of information processing within the brain. Here, we combine graph theory and dynamic functional connectivity to compare resting-state functional MRI data from awake volunteers, propofol-anaesthetised volunteers, and patients with disorders of consciousness, in order to identify consciousness-specific patterns of brain function. We demonstrate that cortical networks are especially affected by loss of consciousness during temporal states of high integration, exhibiting reduced functional diversity and compromised informational capacity, whereas thalamo-cortical functional disconnections emerge during states of higher segregation. Spatially, posterior regions of the brain's default mode network exhibit reductions in both functional diversity and integration with the rest of the brain during unconsciousness. These results show that human consciousness relies on spatio-temporal interactions between brain integration and functional diversity, whose breakdown may represent a generalisable biomarker of loss of consciousness, with potential relevance for clinical practice.

Spectral Diversity in Default Mode Network Connectivity Reflects Behavioral State.

Default mode network (DMN) functional connectivity is thought to occur primarily in low frequencies (<0.1 Hz), resulting in most studies removing high frequencies during data preprocessing. In contrast, subtractive task analyses include high frequencies, as these are thought to be task relevant. An emerging line of research explores resting fMRI data at higher-frequency bands, examining the possibility that functional connectivity is a multiband phenomenon. Furthermore, recent studies suggest DMN involvement in cognitive processing; however, without a systematic investigation of DMN connectivity during tasks, its functional contribution to cognition cannot be fully understood. We bridged these concurrent lines of research by examining the contribution of high frequencies in the relationship between DMN and dorsal attention network at rest and during task execution. Our findings revealed that the inclusion of high frequencies alters between network connectivity, resulting in reduced anticorrelation and increased positive connectivity between DMN and dorsal attention network. Critically, increased positive connectivity was observed only during tasks, suggesting an important role for high-frequency fluctuations in functional integration. Moreover, within-DMN connectivity during task execution correlated with RT only when high frequencies were included. These results show that DMN does not simply deactivate during task execution and suggest active recruitment while performing cognitively demanding paradigms.

Identifying Rodent Resting-State Brain Networks with Independent Component Analysis.

Rodent models have opened the door to a better understanding of the neurobiology of brain disorders and increased our ability to evaluate novel treatments. Resting-state functional magnetic resonance imaging (rs-fMRI) allows for in vivo exploration of large-scale brain networks with high spatial resolution. Its application in rodents affords researchers a powerful translational tool to directly assess/explore the effects of various pharmacological, lesion, and/or disease states on known neural circuits within highly controlled settings. Integration of animal and human research at the molecular-, systems-, and behavioral-levels using diverse neuroimaging techniques empowers more robust interrogations of abnormal/ pathological processes, critical for evolving our understanding of neuroscience. We present a comprehensive protocol to evaluate resting-state brain networks using Independent Component Analysis (ICA) in rodent model. Specifically, we begin with a brief review of the physiological basis for rs-fMRI technique and overview of rs-fMRI studies in rodents to date, following which we provide a robust step-by-step approach for rs-fMRI investigation including data collection, computational preprocessing, and brain network analysis. Pipelines are interwoven with underlying theory behind each step and summarized methodological considerations, such as alternative methods available and current consensus in the literature for optimal results. The presented protocol is designed in such a way that investigators without previous knowledge in the field can implement the analysis and obtain viable results that reliably detect significant differences in functional connectivity between experimental groups. Our goal is to empower researchers to implement rs-fMRI in their respective fields by incorporating technical considerations to date into a workable methodological framework.

Probing Intrinsic Resting-State Networks in the Infant Rat Brain.

Resting-state functional magnetic resonance imaging (rs-fMRI) measures spontaneous fluctuations in blood oxygenation level-dependent (BOLD) signal in the absence of external stimuli. It has become a powerful tool for mapping large-scale brain networks in humans and animal models. Several rs-fMRI studies have been conducted in anesthetized and awake adult rats, reporting consistent patterns of brain activity at the systems level. However, the evolution to adult patterns of resting-state activity has not yet been evaluated and quantified in the developing rat brain. In this study, we hypothesized that large-scale intrinsic networks would be easily detectable but not fully established as specific patterns of activity in lightly anesthetized 2-week-old rats (N = 11). Independent component analysis (ICA) identified 8 networks in 2-week-old-rats. These included Default mode, Sensory (Exteroceptive), Salience (Interoceptive), Basal Ganglia-Thalamic-Hippocampal, Basal Ganglia, Autonomic, Cerebellar, as well as Thalamic-Brainstem networks. Many of these networks consisted of more than one component, possibly indicative of immature, underdeveloped networks at this early time point. Except for the Autonomic network, infant rat networks showed reduced connectivity with subcortical structures in comparison to previously published adult networks. Reported slow fluctuations in the BOLD signal that correspond to functionally relevant resting-state networks in 2-week-old rats can serve as an important tool for future studies of brain development in the settings of different pharmacological applications or disease.

Long-term behavioral effects in a rat model of prolonged postnatal morphine exposure.

Prolonged morphine treatment in neonatal pediatric populations is associated with a high incidence of opioid tolerance and dependence. Despite the clinical relevance of this problem, our knowledge of long-term consequences is sparse. The main objective of this study was to investigate whether prolonged morphine administration in a neonatal rat is associated with long-term behavioral changes in adulthood. Newborn animals received either morphine (10 mg/kg) or equal volume of saline subcutaneously twice daily for the first 2 weeks of life. Morphine-treated animals underwent 10 days of morphine weaning to reduce the potential for observable physical signs of withdrawal. Animals were subjected to nonstressful testing (locomotor activity recording and a novel-object recognition test) at a young age (Postnatal Days [PDs] 27-31) or later in adulthood (PDs 55-56), as well as stressful testing (calibrated forceps test, hot plate test, and forced swim test) only in adulthood. Analysis revealed that prolonged neonatal morphine exposure resulted in decreased thermal but not mechanical threshold. Importantly, no differences were found for total locomotor activity (proxy of drug reward/reinforcement behavior), individual forced swim test behaviors (proxy of affective processing), or novel-object recognition test. Performance on the novel-object recognition test was compromised in the morphine-treated group at the young age, but the effect disappeared in adulthood. These novel results provide insight into the long-term consequences of opioid treatment during an early developmental period and suggest long-term neuroplastic differences in sensory processing related to thermal stimuli.

Cytotoxicity effects of different surfactant molecules conjugated to carbon nanotubes on human astrocytoma cells.

Phase contrast and epifluorescence microscopy were utilized to monitor morphological changes in human astrocytoma cells during a time-course exposure to single-walled carbon nanotube (SWCNT) conjugates with different surfactants and to investigate sub-cellular distribution of the nanotube conjugates, respectively. Experimental results demonstrate that cytotoxicity of the nanotube/surfactant conjugates is related to the toxicity of surfactant molecules attached on the nanotube surfaces. Both sodium dodecyl sulfate (SDS) and sodium dodecylbenzene sulfonate (SDBS) are toxic to cells. Exposure to CNT/SDS conjugates (0.5 mg/mL) for less than 5 min caused changes in cell morphology resulting in a distinctly spherical shape compared to untreated cells. In contrast, sodium cholate (SC) and CNT/SC did not affect cell morphology, proliferation, or growth. These data indicate that SC is an environmentally friendly surfactant for the purification and dispersion of SWCNTs. Epifluorescence microscopy analysis of CNT/DNA conjugates revealed distribution in the cytoplasm of cells and did not show adverse effects on cell morphology, proliferation, or viability during a 72-h incubation. These observations suggest that the SWCNTs could be used as non-viral vectors for diagnostic and therapeutic molecules across the blood-brain barrier to the brain and the central nervous system.

Cytotoxicity of single-walled carbon nanotubes suspended in various surfactants.

The cytotoxicity of single-walled carbon nanotubes (SWCNTs) suspended in various surfactants was investigated by phase contrast light microscopy characterization in combination with an absorbance spectroscopy cytotoxicity analysis. Our data indicate that individual SWCNTs suspended in the surfactants, sodium dodecyl sulfate (SDS) and sodium dodecylbenzene sulfonate (SDBS), were toxic to 1321N1 human astrocytoma cells due to the toxicity of SDS and SDBS on the nanotube surfaces. This toxicity was observed when cells were exposed to an SDS or SDBS solution having a concentration as low as 0.05 mg ml(-1) for 30 min. The proliferation and viability of the cells were not affected by SWCNTs alone or by conjugates of SWCNTs with various concentrations of sodium cholate (SC) or single-stranded DNA. The cells proliferated similarly to untreated cells when surrounded by SWCNTs as they grow, which indicated that the nanotubes did not affect cells adversely. The cytotoxicity of the nanotube-surfactant conjugates was controlled in these experiments by the toxicity of the surfactants. Consequently, when evaluating a surfactant to be used for the dispersion of nanoscale materials in applications such as nanoscale electronics or non-viral biomolecular transporters, the cytotoxicity needs to be evaluated. The methodology proposed in this study can be used to investigate the cytotoxicity of other nanoscale materials suspended in a variety of surfactants.