Uncovering the biological basis of control energy: Structural and metabolic correlates of energy inefficiency in temporal lobe epilepsy.

Network control theory is increasingly used to profile the brain's energy landscape via simulations of neural dynamics. This approach estimates the control energy required to simulate the activation of brain circuits based on structural connectome measured using diffusion magnetic resonance imaging, thereby quantifying those circuits' energetic efficiency. The biological basis of control energy, however, remains unknown, hampering its further application. To fill this gap, investigating temporal lobe epilepsy as a lesion model, we show that patients require higher control energy to activate the limbic network than healthy volunteers, especially ipsilateral to the seizure focus. The energetic imbalance between ipsilateral and contralateral temporolimbic regions is tracked by asymmetric patterns of glucose metabolism measured using positron emission tomography, which, in turn, may be selectively explained by asymmetric gray matter loss as evidenced in the hippocampus. Our investigation provides the first theoretical framework unifying gray matter integrity, metabolism, and energetic generation of neural dynamics.

A practical guide to methodological considerations in the controllability of structural brain networks.

OBJECTIVE: Predicting how the brain can be driven to specific states by means of internal or external control requires a fundamental understanding of the relationship between neural connectivity and activity. Network control theory is a powerful tool from the physical and engineering sciences that can provide insights regarding that relationship; it formalizes the study of how the dynamics of a complex system can arise from its underlying structure of interconnected units. APPROACH: Given the recent use of network control theory in neuroscience, it is now timely to offer a practical guide to methodological considerations in the controllability of structural brain networks. Here we provide a systematic overview of the framework, examine the impact of modeling choices on frequently studied control metrics, and suggest potentially useful theoretical extensions. We ground our discussions, numerical demonstrations, and theoretical advances in a dataset of high-resolution diffusion imaging with 730 diffusion directions acquired over approximately 1 h of scanning from ten healthy young adults. MAIN RESULTS: Following a didactic introduction of the theory, we probe how a selection of modeling choices affects four common statistics: average controllability, modal controllability, minimum control energy, and optimal control energy. Next, we extend the current state-of-the-art in two ways: first, by developing an alternative measure of structural connectivity that accounts for radial propagation of activity through abutting tissue, and second, by defining a complementary metric quantifying the complexity of the energy landscape of a system. We close with specific modeling recommendations and a discussion of methodological constraints. SIGNIFICANCE: Our hope is that this accessible account will inspire the neuroimaging community to more fully exploit the potential of network control theory in tackling pressing questions in cognitive, developmental, and clinical neuroscience.

Brain-based ranking of cognitive domains to predict schizophrenia.

Schizophrenia is a devastating brain disorder that disturbs sensory perception, motor action, and abstract thought. Its clinical phenotype implies dysfunction of various mental domains, which has motivated a series of theories regarding the underlying pathophysiology. Aiming at a predictive benchmark of a catalog of cognitive functions, we developed a data-driven machine-learning strategy and provide a proof of principle in a multisite clinical dataset (n = 324). Existing neuroscientific knowledge on diverse cognitive domains was first condensed into neurotopographical maps. We then examined how the ensuing meta-analytic cognitive priors can distinguish patients and controls using brain morphology and intrinsic functional connectivity. Some affected cognitive domains supported well-studied directions of research on auditory evaluation and social cognition. However, rarely suspected cognitive domains also emerged as disease relevant, including self-oriented processing of bodily sensations in gustation and pain. Such algorithmic charting of the cognitive landscape can be used to make targeted recommendations for future mental health research.

Reduced serotonin receptors and transporters in normal aging adults: a meta-analysis of PET and SPECT imaging studies.

Alterations in serotonin (5-HT) function have been hypothesized to underlie a range of physiological, emotional, and cognitive changes in older age. Here, we conducted a quantitative synthesis and comparison of the effects of age on 5-HT receptors and transporters from cross-sectional positron emission tomography and single-photon emission computed tomography imaging studies. Random-effects meta-analyses of 31 studies including 1087 healthy adults yielded large negative effects of age in 5-HT-2A receptors (largest in global cortex), moderate negative effects of age in 5-HT transporters (largest in thalamus), and small negative effects of age in 5-HT-1A receptors (largest in parietal cortex). Presynaptic 5-HT-1A autoreceptors in raphe/midbrain, however, were preserved across adulthood. Adult age differences were significantly larger in 5-HT-2A receptors compared with 5-HT-1A receptors. A meta-regression showed that 5-HT target, radionuclide, and publication year significantly moderated the age effects. The findings overall identify reduced serotonergic signal transmission in healthy aging. The evidence for the relative preservation of 5-HT-1A compared with 5-HT-2A receptors may partially explain psychological age differences, such as why older adults use more emotion-focused rather than problem-focused coping strategies.

Subjective value representations during effort, probability and time discounting across adulthood.

Every day, humans make countless decisions that require the integration of information about potential benefits (i.e. rewards) with other decision features (i.e. effort required, probability of an outcome or time delays). Here, we examine the overlap and dissociation of behavioral preferences and neural representations of subjective value in the context of three different decision features (physical effort, probability and time delays) in a healthy adult life span sample. While undergoing functional neuroimaging, participants (N = 75) made incentive compatible choices between a smaller monetary reward with lower physical effort, higher probability, or a shorter time delay versus a larger monetary reward with higher physical effort, lower probability, or a longer time delay. Behavioral preferences were estimated from observed choices, and subjective values were computed using individual hyperbolic discount functions. We found that discount rates were uncorrelated across tasks. Despite this apparent behavioral dissociation between preferences, we found overlapping subjective value-related activity in the medial prefrontal cortex across all three tasks. We found no consistent evidence for age differences in either preferences or the neural representations of subjective value across adulthood. These results suggest that while the tolerance of decision features is behaviorally dissociable, subjective value signals share a common representation across adulthood.

Reduced dopamine receptors and transporters but not synthesis capacity in normal aging adults: a meta-analysis.

Many theories of cognitive aging are based on evidence that dopamine (DA) declines with age. Here, we performed a systematic meta-analysis of cross-sectional positron emission tomography and single-photon emission-computed tomography studies on the average effects of age on distinct DA targets (receptors, transporters, or relevant enzymes) in healthy adults (N = 95 studies including 2611 participants). Results revealed significant moderate to large, negative effects of age on DA transporters and receptors. Age had a significantly larger effect on D1- than D2-like receptors. In contrast, there was no significant effect of age on DA synthesis capacity. The average age reductions across the DA system were 3.7%-14.0% per decade. A meta-regression found only DA target as a significant moderator of the age effect. This study precisely quantifies prior claims of reduced DA functionality with age. It also identifies presynaptic mechanisms (spared synthesis capacity and reduced DA transporters) that may partially account for previously unexplained phenomena whereby older adults appear to use dopaminergic resources effectively. Recommendations for future studies including minimum required samples sizes are provided.