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Understanding the topographic organization of the human brain remains a major goal in neuroscience. Brain atlases are fundamental to this goal, yet many contemporary human atlases cover only the cerebral cortex, leaving the subcortex a terra incognita. We revealed the astoundingly complex topographic organization of the human subcortex by disambiguating smooth connectivity gradients from discrete areal boundaries in resting-state fMRI data acquired from more than 1000 healthy adults. This unveiled four hierarchical scales of subcortical organization, recapitulating well-known anatomical nuclei at the coarsest scale and delineating 27 new bilateral regions at the finest. Ultra-high field strength fMRI corroborated and extended this hierarchy, enabling delineation of finer subdivisions of hippocampus and amygdala, while task-evoked fMRI revealed a subtle reorganization of subcortical topography in response to changing cognitive demands. A new subcortical atlas was delineated, personalized to account for individual connectivity differences and utilized to uncover reproducible relationships between subcortical connectivity and individual variation in human behaviors. The new atlas enables holistic connectome mapping and characterization of cortico-subcortical connectivity.

Rapid reconfigurations of brain activity support efficient neuronal communication and flexible behaviour. Suboptimal brain dynamics is associated to impaired adaptability, possibly leading to functional deficiencies. We hypothesize that impaired flexibility in brain activity can lead to motor and cognitive symptoms of Parkinson’s disease (PD). To test this hypothesis, we studied the ‘functional repertoire’—the number of distinct configurations of neural activity—using source-reconstructed magnetoencephalography in PD patients and controls. We found stereotyped brain dynamics and reduced flexibility in PD. The intensity of this reduction was proportional to symptoms severity, which can be explained by beta-band hyper-synchronization. Moreover, the basal ganglia were prominently involved in the abnormal patterns of brain activity. Our findings support the hypotheses that: symptoms in PD relate to impaired brain flexibility, this impairment preferentially involves the basal ganglia, and beta-band hypersynchronization is associated with reduced brain flexibility. These findings highlight the importance of extensive functional repertoires for correct behaviour.

Highlights d Cognitive complexity causes alterations in the lowdimensional whole-brain dynamics d Deviations from the manifold dissociate correct from incorrect performance d Low-dimensional trajectories relate to activity in medial thalamic nuclei

Applying the trained models to predict the chronological age of all participants resulted in personalized organ-specific age gaps.Follow-up phenotype and imaging measurements were available for body (n = 1,220, 837 males; 2.1-5.6 years follow-up) and brain (n = 1,294, 632 males; 2.0-2.7 years follow-up) systems. Chronological age was thus predicted at baseline (t 0 ) and follow-up (t 1 ), yielding two age gaps for each organ per individual (Fig. 2c). This enabled estimation of longitudinal rates of change in body and brain age.

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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.

In this paper, complex dynamical synchronization in a non-linear model of a neural system is studied, and the computational significance of the behaviours is explored. The local neural dynamics is determined by voltage- and ligand-gated ion channels and feedback between densely interconnected excitatory and inhibitory neurons. A mesoscopic array of local networks is modelled by introducing coupling between the local networks via weak excitatory-to-excitatory connectivity. It is shown that with modulation of this long-range synaptic coupling, the system undergoes a transition from independent oscillations to stable chaotic synchronization. Between these states exists a 'weakly' stable state associated with complex, intermittent behaviour in the temporal domain and clusters of synchronous regions in the spatial domain. The paper concludes with a discussion of the putative relevance of such processes in the brain, including the role of neuromodulatory systems and the mechanisms underlying sensory perception, adaptation, computation and complexity.