Geometric constraints on human brain function.

The anatomy of the brain necessarily constrains its function, but precisely how remains unclear. The classical and dominant paradigm in neuroscience is that neuronal dynamics are driven by interactions between discrete, functionally specialized cell populations connected by a complex array of axonal fibres1-3. However, predictions from neural field theory, an established mathematical framework for modelling large-scale brain activity4-6, suggest that the geometry of the brain may represent a more fundamental constraint on dynamics than complex interregional connectivity7,8. Here, we confirm these theoretical predictions by analysing human magnetic resonance imaging data acquired under spontaneous and diverse task-evoked conditions. Specifically, we show that cortical and subcortical activity can be parsimoniously understood as resulting from excitations of fundamental, resonant modes of the brain's geometry (that is, its shape) rather than from modes of complex interregional connectivity, as classically assumed. We then use these geometric modes to show that task-evoked activations across over 10,000 brain maps are not confined to focal areas, as widely believed, but instead excite brain-wide modes with wavelengths spanning over 60 mm. Finally, we confirm predictions that the close link between geometry and function is explained by a dominant role for wave-like activity, showing that wave dynamics can reproduce numerous canonical spatiotemporal properties of spontaneous and evoked recordings. Our findings challenge prevailing views and identify a previously underappreciated role of geometry in shaping function, as predicted by a unifying and physically principled model of brain-wide dynamics.

Markers of positive affect and brain state synchrony discriminate melancholic from non-melancholic depression using naturalistic stimuli.

Melancholia has been proposed as a qualitatively distinct depressive subtype associated with a characteristic symptom profile (psychomotor retardation, profound anhedonia) and a better response to biological therapies. Existing work has suggested that individuals with melancholia are blunted in their display of positive emotions and differ in their neural response to emotionally evocative stimuli. Here, we unify these brain and behavioural findings amongst a carefully phenotyped group of seventy depressed participants, drawn from an established Australian database (the Australian Genetics of Depression Study) and further enriched for melancholia (high ratings of psychomotor retardation and anhedonia). Melancholic (n = 30) or non-melancholic status (n = 40) was defined using a semi-structured interview (the Sydney Melancholia Prototype Index). Complex facial expressions were captured whilst participants watched a movie clip of a comedian and classified using a machine learning algorithm. Subsequently, the dynamics of sequential changes in brain activity were modelled during the viewing of an emotionally evocative movie in the MRI scanner. We found a quantitative reduction in positive facial expressivity amongst participants with melancholia, combined with differences in the synchronous expression of brain states during positive epochs of the movie. In non-melancholic depression, the display of positive affect was inversely related to the activity of cerebellar regions implicated in the processing of affect. However, this relationship was reduced in those with a melancholic phenotype. Our multimodal findings show differences in evaluative and motoric domains between melancholic and non-melancholic depression through engagement in ecologically valid tasks that evoke positive emotion. These findings provide new markers to stratify depression and an opportunity to support the development of targeted interventions.

Critical-like Brain Dynamics in a Continuum from Second- to First-Order Phase Transition.

The classic brain criticality hypothesis postulates that the brain benefits from operating near a continuous second-order phase transition. Slow feedback regulation of neuronal activity could, however, lead to a discontinuous first-order transition and thereby bistable activity. Observations of bistability in awake brain activity have nonetheless remained scarce and its functional significance unclear. Moreover, there is no empirical evidence to support the hypothesis that the human brain could flexibly operate near either a first- or second-order phase transition despite such a continuum being common in models. Here, using computational modeling, we found bistable synchronization dynamics to emerge through elevated positive feedback and occur exclusively in a regimen of critical-like dynamics. We then assessed bistability in vivo with resting-state MEG in healthy adults (7 females, 11 males) and stereo-electroencephalography in epilepsy patients (28 females, 36 males). This analysis revealed that a large fraction of the neocortices exhibited varying degrees of bistability in neuronal oscillations from 3 to 200 Hz. In line with our modeling results, the neuronal bistability was positively correlated with classic assessment of brain criticality across narrow-band frequencies. Excessive bistability was predictive of epileptic pathophysiology in the patients, whereas moderate bistability was positively correlated with task performance in the healthy subjects. These empirical findings thus reveal the human brain as a one-of-a-kind complex system that exhibits critical-like dynamics in a continuum between continuous and discontinuous phase transitions.SIGNIFICANCE STATEMENT In the model, while synchrony per se was controlled by connectivity, increasing positive local feedback led to gradually emerging bistable synchrony with scale-free dynamics, suggesting a continuum between second- and first-order phase transitions in synchrony dynamics inside a critical-like regimen. In resting-state MEG and SEEG, bistability of ongoing neuronal oscillations was pervasive across brain areas and frequency bands and was observed only with concurring critical-like dynamics as the modeling predicted. As evidence for functional relevance, moderate bistability was positively correlated with executive functioning in the healthy subjects, and excessive bistability was associated with epileptic pathophysiology. These findings show that critical-like neuronal dynamics in vivo involves both continuous and discontinuous phase transitions in a frequency-, neuroanatomy-, and state-dependent manner.

Mode-based morphometry: A multiscale approach to mapping human neuroanatomy.

Voxel-based morphometry (VBM) and surface-based morphometry (SBM) are two widely used neuroimaging techniques for investigating brain anatomy. These techniques rely on statistical inferences at individual points (voxels or vertices), clusters of points, or a priori regions-of-interest. They are powerful tools for describing brain anatomy, but offer little insights into the generative processes that shape a particular set of findings. Moreover, they are restricted to a single spatial resolution scale, precluding the opportunity to distinguish anatomical variations that are expressed across multiple scales. Drawing on concepts from classical physics, here we develop an approach, called mode-based morphometry (MBM), that can describe any empirical map of anatomical variations in terms of the fundamental, resonant modes-eigenmodes-of brain anatomy, each tied to a specific spatial scale. Hence, MBM naturally yields a multiscale characterization of the empirical map, affording new opportunities for investigating the spatial frequency content of neuroanatomical variability. Using simulated and empirical data, we show that the validity and reliability of MBM are either comparable or superior to classical vertex-based SBM for capturing differences in cortical thickness maps between two experimental groups. Our approach thus offers a robust, accurate, and informative method for characterizing empirical maps of neuroanatomical variability that can be directly linked to a generative physical process.

Cross-sectional associations between 24-hour time-use composition, grey matter volume and cognitive function in healthy older adults.

BACKGROUND: Increasing physical activity (PA) is an effective strategy to slow reductions in cortical volume and maintain cognitive function in older adulthood. However, PA does not exist in isolation, but coexists with sleep and sedentary behaviour to make up the 24-hour day. We investigated how the balance of all three behaviours (24-hour time-use composition) is associated with grey matter volume in healthy older adults, and whether grey matter volume influences the relationship between 24-hour time-use composition and cognitive function. METHODS: This cross-sectional study included 378 older adults (65.6 ± 3.0 years old, 123 male) from the ACTIVate study across two Australian sites (Adelaide and Newcastle). Time-use composition was captured using 7-day accelerometry, and T1-weighted magnetic resonance imaging was used to measure grey matter volume both globally and across regions of interest (ROI: frontal lobe, temporal lobe, hippocampi, and lateral ventricles). Pairwise correlations were used to explore univariate associations between time-use variables, grey matter volumes and cognitive outcomes. Compositional data analysis linear regression models were used to quantify associations between ROI volumes and time-use composition, and explore potential associations between the interaction between ROI volumes and time-use composition with cognitive outcomes. RESULTS: After adjusting for covariates (age, sex, education), there were no significant associations between time-use composition and any volumetric outcomes. There were significant interactions between time-use composition and frontal lobe volume for long-term memory (p = 0.018) and executive function (p = 0.018), and between time-use composition and total grey matter volume for executive function (p = 0.028). Spending more time in moderate-vigorous PA was associated with better long-term memory scores, but only for those with smaller frontal lobe volume (below the sample mean). Conversely, spending more time in sleep and less time in sedentary behaviour was associated with better executive function in those with smaller total grey matter volume. CONCLUSIONS: Although 24-hour time use was not associated with total or regional grey matter independently, total grey matter and frontal lobe grey matter volume moderated the relationship between time-use composition and several cognitive outcomes. Future studies should investigate these relationships longitudinally to assess whether changes in time-use composition correspond to changes in grey matter volume and cognition.

Mechanisms of imbalanced frontostriatal functional connectivity in obsessive-compulsive disorder.

The diagnosis of obsessive-compulsive disorder (OCD) has been linked with changes in frontostriatal resting-state connectivity. However, replication of prior findings is lacking, and the mechanistic understanding of these effects is incomplete. To confirm and advance knowledge on changes in frontostriatal functional connectivity in OCD, participants with OCD and matched healthy controls underwent resting-state functional, structural and diffusion neuroimaging. Functional connectivity changes in frontostriatal systems were here replicated in individuals with OCD (n = 52) compared with controls (n = 45). OCD participants showed greater functional connectivity (t = 4.3, PFWE = 0.01) between the nucleus accumbens (NAcc) and the orbitofrontal cortex (OFC) but lower functional connectivity between the dorsal putamen and lateral prefrontal cortex (t = 3.8, PFWE = 0.04) relative to controls. Computational modelling suggests that NAcc-OFC connectivity changes reflect an increased influence of NAcc over OFC activity and reduced OFC influence over NAcc activity (posterior probability, Pp > 0.66). Conversely, dorsal putamen showed reduced modulation over lateral prefrontal cortex activity (Pp > 0.90). These functional deregulations emerged on top of a generally intact anatomical substrate. We provide out-of-sample replication of opposite changes in ventro-anterior and dorso-posterior frontostriatal connectivity in OCD and advance the understanding of the neural underpinnings of these functional perturbations. These findings inform the development of targeted therapies normalizing frontostriatal dynamics in OCD.

Functional re-organization of hippocampal-cortical gradients during naturalistic memory processes.

The functional organization of the hippocampus mirrors that of the cortex, changing smoothly along connectivity gradients and abruptly at inter-areal boundaries. Hippocampal-dependent cognitive processes require flexible integration of these hippocampal gradients into functionally related cortical networks. To understand the cognitive relevance of this functional embedding, we acquired fMRI data while participants viewed brief news clips, either containing or lacking recently familiarized cues. Participants were 188 healthy mid-life adults and 31 adults with mild cognitive impairment (MCI) or Alzheimer's disease (AD). We employed a recently developed technique - connectivity gradientography - to study gradually changing patterns of voxel to whole brain functional connectivity and their sudden transitions. We observed that functional connectivity gradients of the anterior hippocampus map onto connectivity gradients across the default mode network during these naturalistic stimuli. The presence of familiar cues in the news clips accentuates a stepwise transition across the boundary from the anterior to the posterior hippocampus. This functional transition is shifted in the posterior direction in the left hippocampus of individuals with MCI or AD. These findings shed new light on the functional integration of hippocampal connectivity gradients into large-scale cortical networks, how these adapt with memory context and how these change in the presence of neurodegenerative disease.

Revisiting deficits in threat and safety appraisal in obsessive-compulsive disorder.

Current behavioural treatment of obsessive-compulsive disorder (OCD) is informed by fear conditioning and involves iteratively re-evaluating previously threatening stimuli as safe. However, there is limited research investigating the neurobiological response to conditioning and reversal of threatening stimuli in individuals with OCD. A clinical sample of individuals with OCD (N = 45) and matched healthy controls (N = 45) underwent functional magnetic resonance imaging. While in the scanner, participants completed a well-validated fear reversal task and a resting-state scan. We found no evidence for group differences in task-evoked brain activation or functional connectivity in OCD. Multivariate analyses encompassing all participants in the clinical and control groups suggested that subjective appraisal of threatening and safe stimuli were associated with a larger difference in brain activity than the contribution of OCD symptoms. In particular, we observed a brain-behaviour continuum whereby heightened affective appraisal was related to increased bilateral insula activation during the task (r = 0.39, pFWE = .001). These findings suggest that changes in conditioned threat-related processes may not be a core neurobiological feature of OCD and encourage further research on the role of subjective experience in fear conditioning.

Impact of In Utero Exposure to Antiepileptic Drugs on Neonatal Brain Function.

In utero brain development underpins brain health across the lifespan but is vulnerable to physiological and pharmacological perturbation. Here, we show that antiepileptic medication during pregnancy impacts on cortical activity during neonatal sleep, a potent indicator of newborn brain health. These effects are evident in frequency-specific functional brain networks and carry prognostic information for later neurodevelopment. Notably, such effects differ between different antiepileptic drugs that suggest neurodevelopmental adversity from exposure to antiepileptic drugs and not maternal epilepsy per se. This work provides translatable bedside metrics of brain health that are sensitive to the effects of antiepileptic drugs on postnatal neurodevelopment and carry direct prognostic value.

The Effect of Genetic Predisposition to Alzheimer's Disease and Related Traits on Recruitment Bias in a Study of Cognitive Aging.

The recruitment of participants for research studies may be subject to bias. The Prospective Imaging Study of Ageing (PISA) aims to characterize the phenotype and natural history of healthy adult Australians at high future risk of Alzheimer's disease (AD). Participants approached to take part in PISA were selected from existing cohort studies with available genomewide genetic data for both successfully and unsuccessfully recruited participants, allowing us to investigate the genetic contribution to voluntary recruitment, including the genetic predisposition to AD. We use a polygenic risk score (PRS) approach to test to what extent the genetic risk for AD, and related risk factors predict participation in PISA. We did not identify a significant association of genetic risk for AD with study participation, but we did identify significant associations with PRS for key causal risk factors for AD, IQ, household income and years of education. We also found that older and female participants were more likely to take part in the study. Our findings highlight the importance of considering bias in key risk factors for AD in the recruitment of individuals for cohort studies.

Revisiting the effectiveness of repetitive transcranial magnetic stimulation treatment in depression, again.

Following on from the publication of the Royal Australian and New Zealand Journal of Psychiatry Mood Disorder Clinical Practice Guidelines (2020) and criticisms of how these aberrantly addressed repetitive transcranial magnetic stimulation treatment of depression, questions have continued to be raised in the journal about this treatment by a small group of authors, whose views we contend do not reflect the broad acceptance of this treatment nationally and internationally. In fact, the evidence supporting the use of repetitive transcranial magnetic stimulation treatment in depression is unambiguous and substantial, consisting of an extensive series of clinical trials supported by multiple meta-analyses, network meta-analysis and umbrella reviews. Importantly, the use of repetitive transcranial magnetic stimulation treatment in depression has also been subject to a series of health economic analyses. These indicate that repetitive transcranial magnetic stimulation is a cost-effective therapy and have been used in some jurisdictions, including Australia, in support of public funding. An argument has been made that offering repetitive transcranial magnetic stimulation treatment may delay potentially effective pharmacotherapy. In fact, there is considerably greater danger of the opposite happening. Repetitive transcranial magnetic stimulation is as, if not more effective, than antidepressant medication after two unsuccessful medication trials and should be a consideration for all patients under these circumstances where available. There is no meaningful ongoing debate about the use of repetitive transcranial magnetic stimulation treatment in depression - it is a safe, effective and cost-effective treatment.

The structural connectivity of subthalamic deep brain stimulation correlates with impulsivity in Parkinson's disease.

Subthalamic deep brain stimulation (STN-DBS) for Parkinson's disease treats motor symptoms and improves quality of life, but can be complicated by adverse neuropsychiatric side-effects, including impulsivity. Several clinically important questions remain unclear: can 'at-risk' patients be identified prior to DBS; do neuropsychiatric symptoms relate to the distribution of the stimulation field; and which brain networks are responsible for the evolution of these symptoms? Using a comprehensive neuropsychiatric battery and a virtual casino to assess impulsive behaviour in a naturalistic fashion, 55 patients with Parkinson's disease (19 females, mean age 62, mean Hoehn and Yahr stage 2.6) were assessed prior to STN-DBS and 3 months postoperatively. Reward evaluation and response inhibition networks were reconstructed with probabilistic tractography using the participant-specific subthalamic volume of activated tissue as a seed. We found that greater connectivity of the stimulation site with these frontostriatal networks was related to greater postoperative impulsiveness and disinhibition as assessed by the neuropsychiatric instruments. Larger bet sizes in the virtual casino postoperatively were associated with greater connectivity of the stimulation site with right and left orbitofrontal cortex, right ventromedial prefrontal cortex and left ventral striatum. For all assessments, the baseline connectivity of reward evaluation and response inhibition networks prior to STN-DBS was not associated with postoperative impulsivity; rather, these relationships were only observed when the stimulation field was incorporated. This suggests that the site and distribution of stimulation is a more important determinant of postoperative neuropsychiatric outcomes than preoperative brain structure and that stimulation acts to mediate impulsivity through differential recruitment of frontostriatal networks. Notably, a distinction could be made amongst participants with clinically-significant, harmful changes in mood and behaviour attributable to DBS, based upon an analysis of connectivity and its relationship with gambling behaviour. Additional analyses suggested that this distinction may be mediated by the differential involvement of fibres connecting ventromedial subthalamic nucleus and orbitofrontal cortex. These findings identify a mechanistic substrate of neuropsychiatric impairment after STN-DBS and suggest that tractography could be used to predict the incidence of adverse neuropsychiatric effects. Clinically, these results highlight the importance of accurate electrode placement and careful stimulation titration in the prevention of neuropsychiatric side-effects after STN-DBS.

Prediction-error signals to violated expectations about person identity and head orientation are doubly-dissociated across dorsal and ventral visual stream regions.

Predictive coding theories of perception highlight the importance of constantly updated internal models of the world to predict future sensory inputs. Importantly, such theories suggest that prediction-error signalling should be specific to the violation of predictions concerning distinct attributes of the same stimulus. To interrogate this as yet untested prediction, we focused on two different aspects of face perception (identity and orientation) and investigated whether cortical regions which process particular stimulus attributes also signal prediction violations with respect to those same stimulus attributes. We employed a paradigm using sequential trajectories of images to create perceptual expectations about face orientation and identity, and then parametrically violated each attribute. Using MEG data, we identified double dissociations of expectancy violations in the dorsal and ventral visual streams, such that the right fusiform gyrus showed greater prediction-error signals to identity violations than to orientation violations, whereas the left angular gyrus showed the converse pattern of results. Our results suggest that perceptual prediction-error signalling is directly linked to regions associated with the processing of different stimulus properties.

Subthalamic deep brain stimulation identifies frontal networks supporting initiation, inhibition and strategy use in Parkinson's disease.

Initiation and inhibition are executive functions whose disruption in Parkinson's disease impacts substantially on everyday activities. Management of Parkinson's disease with subthalamic deep brain stimulation (DBS) modifies initiation and inhibition, with prior work suggesting that these effects may be mediated via the connectivity of the subthalamic nucleus (STN) with the frontal cortex. Here, we employed high-resolution structural neuroimaging to investigate the variability in initiation, inhibition and strategy use in a cohort of twenty-five (ten females, mean age 62.5, mean Hoehn and Yahr stage 2.5) participants undertaking subthalamic DBS for Parkinson's disease. Neuropsychological assessment of initiation and inhibition was performed preoperatively and at six months postoperatively. We first reconstructed the preoperative connectivity of the STN with a frontal network of anterior and superior medial cortical regions. We then modelled the postoperative site of subthalamic stimulation and reconstructed the connectivity of the stimulation field within this same network. We found that, at both pre- and postoperative intervals, inter-individual variability in inhibition and initiation were strongly associated with structural network connectivity. Measures of subcortical atrophy and local stimulation effects did not play a significant role. Preoperatively, we replicated prior work, including a role for the right inferior frontal gyrus in inhibition and strategy use, as well as the left inferior frontal gyrus in tasks requiring selection under conditions of maintained inhibition. Postoperatively, greater connectivity of the stimulation field with right anterior cortical regions was associated with greater rule violations and suppression errors, supporting prior work implicating right-hemispheric STN stimulation in disinhibition. Our findings suggest that, in Parkinson's disease, connectivity of the frontal cortex with the STN is an important mediator of individual variability in initiation and inhibition,. Personalised information on brain network architecture could guide individualised brain circuit manipulation to minimise neuropsychological disruption after STN-DBS.

Manipulating the structure of natural scenes using wavelets to study the functional architecture of perceptual hierarchies in the brain.

Functional neuroimaging experiments that employ naturalistic stimuli (natural scenes, films, spoken narratives) provide insights into cognitive function "in the wild". Natural stimuli typically possess crowded, spectrally dense, dynamic, and multimodal properties within a rich multiscale structure. However, when using natural stimuli, various challenges exist for creating parametric manipulations with tight experimental control. Here, we revisit the typical spectral composition and statistical dependences of natural scenes, which distinguish them from abstract stimuli. We then demonstrate how to selectively degrade subtle statistical dependences within specific spatial scales using the wavelet transform. Such manipulations leave basic features of the stimuli, such as luminance and contrast, intact. Using functional neuroimaging of human participants viewing degraded natural images, we demonstrate that cortical responses at different levels of the visual hierarchy are differentially sensitive to subtle statistical dependences in natural images. This demonstration supports the notion that perceptual systems in the brain are optimally tuned to the complex statistical properties of the natural world. The code to undertake these stimulus manipulations, and their natural extension to dynamic natural scenes (films), is freely available.

Dose-dependent modulation of the visually evoked N1/N170 by perceptual surprise: a clear demonstration of prediction-error signalling.

Prediction-error checking processes play a key role in predictive coding models of perception. However, neural indices of such processes have yet to be unambiguously demonstrated. To date, experimental paradigms aiming to study such phenomena have relied upon the relative frequency of stimulus repeats and/or 'unexpected' events that are physically different from 'expected' events. These features of experimental design leave open alternative explanations for the observed effects. A definitive demonstration requires that presumed prediction error-related responses should show contextual dependency (rather than simply effects of frequency or repetition) and should not be attributable to low-level stimulus differences. Most importantly, prediction-error signals should show dose dependency with respect to the degree to which expectations are violated. Here, we exploit a novel experimental paradigm specifically designed to address these issues, using it to interrogate early latency event-related potentials (ERPs) to contextually expected and unexpected visual stimuli. In two electroencephalography (EEG) experiments, we demonstrate that an N1/N170 evoked potential is robustly modulated by unexpected perceptual events ('perceptual surprise') and shows dose-dependent sensitivity with respect to both the influence of prior information and the extent to which expectations are violated. This advances our understanding of perceptual predictions in the visual domain by clearly identifying these evoked potentials as an index of visual surprise.

The connectomics of brain disorders.

Pathological perturbations of the brain are rarely confined to a single locus; instead, they often spread via axonal pathways to influence other regions. Patterns of such disease propagation are constrained by the extraordinarily complex, yet highly organized, topology of the underlying neural architecture; the so-called connectome. Thus, network organization fundamentally influences brain disease, and a connectomic approach grounded in network science is integral to understanding neuropathology. Here, we consider how brain-network topology shapes neural responses to damage, highlighting key maladaptive processes (such as diaschisis, transneuronal degeneration and dedifferentiation), and the resources (including degeneracy and reserve) and processes (such as compensation) that enable adaptation. We then show how knowledge of network topology allows us not only to describe pathological processes but also to generate predictive models of the spread and functional consequences of brain disease.

Correction: Connectomics of bipolar disorder: a critical review, and evidence for dynamic instabilities within interoceptive networks.

This Article was originally published under Nature Research's License to Publish, but has now been made available under a [CC BY 4.0] license. The PDF and HTML versions of the Article have been modified accordingly.

Connectomics of bipolar disorder: a critical review, and evidence for dynamic instabilities within interoceptive networks.

The notion that specific cognitive and emotional processes arise from functionally distinct brain regions has lately shifted toward a connectivity-based approach that emphasizes the role of network-mediated integration across regions. The clinical neurosciences have likewise shifted from a predominantly lesion-based approach to a connectomic paradigm-framing disorders as diverse as stroke, schizophrenia (SCZ), and dementia as "dysconnection syndromes". Here we position bipolar disorder (BD) within this paradigm. We first summarise the disruptions in structural, functional and effective connectivity that have been documented in BD. Not surprisingly, these disturbances show a preferential impact on circuits that support emotional processes, cognitive control and executive functions. Those at high risk (HR) for BD also show patterns of connectivity that differ from both matched control populations and those with BD, and which may thus speak to neurobiological markers of both risk and resilience. We highlight research fields that aim to link brain network disturbances to the phenotype of BD, including the study of large-scale brain dynamics, the principles of network stability and control, and the study of interoception (the perception of physiological states). Together, these findings suggest that the affective dysregulation of BD arises from dynamic instabilities in interoceptive circuits which subsequently impact on fear circuitry and cognitive control systems. We describe the resulting disturbance as a "psychosis of interoception".

Transitions in information processing dynamics at the whole-brain network level are driven by alterations in neural gain.

A key component of the flexibility and complexity of the brain is its ability to dynamically adapt its functional network structure between integrated and segregated brain states depending on the demands of different cognitive tasks. Integrated states are prevalent when performing tasks of high complexity, such as maintaining items in working memory, consistent with models of a global workspace architecture. Recent work has suggested that the balance between integration and segregation is under the control of ascending neuromodulatory systems, such as the noradrenergic system, via changes in neural gain (in terms of the amplification and non-linearity in stimulus-response transfer function of brain regions). In a previous large-scale nonlinear oscillator model of neuronal network dynamics, we showed that manipulating neural gain parameters led to a 'critical' transition in phase synchrony that was associated with a shift from segregated to integrated topology, thus confirming our original prediction. In this study, we advance these results by demonstrating that the gain-mediated phase transition is characterized by a shift in the underlying dynamics of neural information processing. Specifically, the dynamics of the subcritical (segregated) regime are dominated by information storage, whereas the supercritical (integrated) regime is associated with increased information transfer (measured via transfer entropy). Operating near to the critical regime with respect to modulating neural gain parameters would thus appear to provide computational advantages, offering flexibility in the information processing that can be performed with only subtle changes in gain control. Our results thus link studies of whole-brain network topology and the ascending arousal system with information processing dynamics, and suggest that the constraints imposed by the ascending arousal system constrain low-dimensional modes of information processing within the brain.