Allostasis as a core feature of hierarchical gradients in the human brain

Synaptic signaling modeled by functional connectivity predicts metabolic demands of the human brain

PURPOSE

The human brain is characterized by interacting large-scale functional networks fueled by glucose metabolism. Since former studies could not sufficiently clarify how these functional connections shape glucose metabolism, we aimed to provide a neurophysiologically-based approach.

METHODS

51 healthy volunteers underwent simultaneous PET/MRI to obtain BOLD functional connectivity and [18F]FDG glucose metabolism. These multimodal imaging proxies of fMRI and PET were combined in a whole-brain extension of metabolic connectivity mapping. Specifically, functional connectivity of all brain regions were used as input to explain glucose metabolism of a given target region. This enabled the modeling of postsynaptic energy demands by incoming signals from distinct brain regions.

RESULTS

Functional connectivity input explained a substantial part of metabolic demands but with pronounced regional variations (34 - 76%). During cognitive task performance this multimodal association revealed a shift to higher network integration compared to resting state. In healthy aging, a dedifferentiation (decreased segregated/modular structure of the brain) of brain networks during rest was observed. Furthermore, by including data from mRNA maps, [11C]UCB-J synaptic density and aerobic glycolysis (oxygen-to-glucose index from PET data), we show that whole-brain functional input reflects non-oxidative, on-demand metabolism of synaptic signaling. The metabolically-derived directionality of functional inputs further marked them as top-down predictions. In addition, the approach uncovered formerly hidden networks with superior efficiency through metabolically informed network partitioning.

CONCLUSIONS

Applying multimodal imaging, we decipher a crucial part of the metabolic and neurophysiological basis of functional connections in the brain as interregional on-demand synaptic signaling fueled by anaerobic metabolism. The observed task- and age-related effects indicate promising future applications to characterize human brain function and clinical alterations.

The model of the brain as a complex system: Interactions of physical, neural and mental states with neurocognitive functions

The isolated approaching of physical, neural and mental states and the binary classification into stable traits and fluctuating states previously lead to a limited understanding concerning underlying processes and possibilities to explain, measure and regulate neural and mental performance along with the interaction of mental states and neurocognitive traits. In this article these states are integrated by i) differentiating the model of the brain as a complex, self-organizing system, ii) showing possibilities to measure this model, iii) offering a classification of mental states and iv) presenting a holistic operationalization of state regulations and trait trainings to enhance neural and mental high-performance on a macro- and micro scale. This model integrates current findings from the theory of constructed emotions, the theory of thousand brains and complex systems theory and yields several testable hypotheses to provide an integrated reference frame for future research and applied target points to regulate and enhance performance.

The fear-avoidance model as an embodied prediction of threat

The fear-avoidance model is a well-established framework in the understanding of persistent pain. It proposes a dichotomous path: either the context is interpreted as safe; there is no fear reaction and, therefore, the individual engages in active (positive) coping; or the context is interpreted as threatening, leading to a self-reinforcing vicious circle of fear and (negative) avoidance. We propose an embodied interpretation of this phenomenon employing the joint framework of predictive coding and active inference. The key idea is that multisensory integration of exteroceptive, proprioceptive, and interoceptive sensory inputs can lead to dysfunctional experiences of threat in nonthreatening situations. Threat inference can promote fear responses, maladaptive strategies (i.e., avoidance) and self-provides evidence for threat in associated or future contexts, or both. Under this treatment, the prediction of nonrealized threat becomes self-evidencing and context-invariant, and hence self-perpetuating. Safety cues are unable to attenuate the interpretation of the negative context as the dominant inference of the context is threatful and gains more precision and becomes resistant over time. Our model provides an explanation for the emergence of a dysfunctional fear response in the clinical setting despite apparent safety based on modern concepts from theoretical (computational) neuroscience.

Ghrelin is associated with an elevated mood after an overnight fast in depression

BACKGROUND

Major depressive disorder (MDD) comprises subtypes with distinct symptom profiles. For example, patients with melancholic and atypical MDD differ in the direction of appetite and body weight changes as well as mood reactivity. Despite reported links to altered energy metabolism, the role of circulating neuropeptides from the gut in modulating such symptoms remains largely elusive.

METHODS

We collected data from 103 participants, including 52 patients with MDD and 51 healthy control participants (HCP). After an overnight fast, we measured plasma levels of (acyl and des-acyl) ghrelin and participants reported their current metabolic and mood states using visual analog scales (VAS). Furthermore, they completed symptom-related questionnaires (i.e., STAI-T).

RESULTS

Patients with atypical versus melancholic MDD reported less negative affect (p = 0.025). Higher levels of acyl ghrelin (corrected for BMI) were associated with improved mood (p = 0.012), specifically in patients with MDD. These associations of ghrelin were not mood-item specific and exceeded correlations with trait markers of negative affectivity. In contrast to associations with mood state, higher levels of ghrelin were not associated with increased hunger per se or changes in appetite in patients with MDD.

LIMITATIONS

The study is limited by the cross-sectional design without an intervention.

CONCLUSIONS

Our results reveal potentially mood-enhancing effects of ghrelin in fasting individuals that exceed associations with metabolic state ratings. These associations with circulating neuropeptides might help explain anti-depressive effects of fasting interventions and could complement conventional treatments in patients with melancholic MDD.

Default mode network tau predicts future clinical decline in atypical early Alzheimer's disease

Identifying individuals with early stage Alzheimer's disease (AD) at greater risk of steeper clinical decline would allow professionals and loved ones to make better-informed medical, support, and life planning decisions. Despite accumulating evidence on the clinical prognostic value of tau PET in typical late-onset amnestic AD, its utility in predicting clinical decline in individuals with atypical forms of AD remains unclear. In this study, we examined the relationship between baseline tau PET signal and the rate of subsequent clinical decline in a sample of 48 A+/T+/N+ patients with mild cognitive impairment or mild dementia due to AD with atypical clinical phenotypes (Posterior Cortical Atrophy, logopenic variant Primary Progressive Aphasia, and amnestic syndrome with multi-domain impairment and age of onset < 65 years). All patients underwent structural magnetic resonance imaging (MRI), tau (18F-Flortaucipir) PET, and amyloid (either 18F-Florbetaben or 11C-Pittsburgh Compound B) PET scans at baseline. Each patient's longitudinal clinical decline was assessed by calculating the annualized change in the Clinical Dementia Rating Sum-of-Boxes (CDR-SB) scores from baseline to follow-up (mean time interval = 14.55 ± 3.97 months). Our sample of early atypical AD patients showed an increase in CDR-SB by 1.18 ± 1.25 points per year: t(47) = 6.56, p < .001, d = 0.95. These AD patients showed prominent baseline tau burden in posterior cortical regions including the major nodes of the default mode network, including the angular gyrus, posterior cingulate cortex/precuneus, and lateral temporal cortex. Greater baseline tau in the broader default mode network predicted faster clinical decline. Tau in the default mode network was the strongest predictor of clinical decline, outperforming baseline clinical impairment, tau in other functional networks, and the magnitude of cortical atrophy and amyloid burden in the default mode network. Overall, these findings point to the contribution of baseline tau burden within the default mode network of the cerebral cortex to predicting the magnitude of clinical decline in a sample of atypical early AD patients one year later. This simple measure based on a tau PET scan could aid the development of a personalized prognostic, monitoring, and treatment plan tailored to each individual patient, which would help clinicians not only predict the natural evolution of the disease but also estimate the effect of disease-modifying therapies on slowing subsequent clinical decline given the patient's tau burden while still early in the disease course.

The subcortical default mode network and Alzheimer's disease: a systematic review and meta-analysis

The default mode network is a central cortical brain network suggested to play a major role in several disorders and to be particularly vulnerable to the neuropathological hallmarks of Alzheimer's disease. Subcortical involvement in the default mode network and its alteration in Alzheimer's disease remains largely unknown. We performed a systematic review, meta-analysis and empirical validation of the subcortical default mode network in healthy adults, combined with a systematic review, meta-analysis and network analysis of the involvement of subcortical default mode areas in Alzheimer's disease. Our results show that, besides the well-known cortical default mode network brain regions, the default mode network consistently includes subcortical regions, namely the thalamus, lobule and vermis IX and right Crus I/II of the cerebellum and the amygdala. Network analysis also suggests the involvement of the caudate nucleus. In Alzheimer's disease, we observed a left-lateralized cluster of decrease in functional connectivity which covered the medial temporal lobe and amygdala and showed overlap with the default mode network in a portion covering parts of the left anterior hippocampus and left amygdala. We also found an increase in functional connectivity in the right anterior insula. These results confirm the consistency of subcortical contributions to the default mode network in healthy adults and highlight the relevance of the subcortical default mode network alteration in Alzheimer's disease.

Weakened effective connectivity between salience network and default mode network during resting state in adolescent depression

Adolescent major depressive disorder (MDD) is associated with altered resting-state connectivity between the default mode network (DMN) and the salience network (SN), which are involved in self-referential processing and detecting and filtering salient stimuli, respectively. Using spectral dynamical causal modelling, we investigated the effective connectivity and input sensitivity between key nodes of these networks in 30 adolescents with MDD and 32 healthy controls while undergoing resting-state fMRI. We found that the DMN received weaker inhibition from the SN and that the medial prefrontal cortex and the anterior cingulate cortex showed reduced self-inhibition in MDD, making them more prone to external influences. Moreover, we found that selective serotonin reuptake inhibitor (SSRI) intake was associated with decreased and increased self-inhibition of the SN and DMN, respectively, in patients. Our findings suggest that adolescent MDD is characterized by a hierarchical imbalance between the DMN and the SN, which could affect the integration of emotional and self-related information. We propose that SSRIs may help restore network function by modulating excitatory/inhibitory balance in the DMN and the SN. Our study highlights the potential of prefrontal-amygdala interactions as a biomarker and a therapeutic target for adolescent depression.

Arousal coherence, uncertainty, and well-being: an active inference account

Here we build on recent findings which show that greater alignment between our subjective experiences (how we feel) and physiological states (measurable changes in our body) plays a pivotal role in the overall psychological well-being. Specifically, we propose that the alignment or 'coherence' between affective arousal (e.g. how excited we 'feel') and autonomic arousal (e.g. heart rate or pupil dilation) may be key for maintaining up-to-date uncertainty representations in dynamic environments. Drawing on recent advances in interoceptive and affective inference, we also propose that arousal coherence reflects interoceptive integration, facilitates adaptive belief updating, and impacts our capacity to adapt to changes in uncertainty, with downstream consequences to well-being. We also highlight the role of meta-awareness of arousal, a third level of inference, which may permit conscious awareness, learning about, and intentional regulation of lower-order sources of arousal. Practices emphasizing meta-awareness of arousal (like meditation) may therefore elicit some of their known benefits via improved arousal coherence. We suggest that arousal coherence is also likely to be associated with markers of adaptive functioning (like emotional awareness and self-regulatory capacities) and discuss mind-body practices that may increase coherence.

The neurobiology of interoception and affect

Scholars have argued for centuries that affective states involve interoception, or representations of the state of the body. Yet, we lack a mechanistic understanding of how signals from the body are transduced, transmitted, compressed, and integrated by the brains of humans to produce affective states. We suggest that to understand how the body contributes to affect, we first need to understand information flow through the nervous system's interoceptive pathways. We outline such a model and discuss how unique anatomical and physiological aspects of interoceptive pathways may give rise to the qualities of affective experiences in general and valence and arousal in particular. We conclude by considering implications and future directions for research on interoception, affect, emotions, and human mental experiences.

Transcutaneous auricular vagus nerve stimulation modulates the processing of interoceptive prediction error signals and their role in allostatic regulation

It has recently been suggested that predictive processing principles may apply to interoception, defined as the processing of hormonal, autonomic, visceral, and immunological signals. In the current study, we aimed at providing empirical evidence for the role of cardiac interoceptive prediction errors signals on allostatic adjustments, using transcutaneous auricular vagus nerve stimulation (taVNS) as a tool to modulate the processing of interoceptive afferents. In a within-subject design, participants performed a cardiac-related interoceptive task (heartbeat counting task) under taVNS and sham stimulation, spaced 1-week apart. We observed that taVNS, in contrast to sham stimulation, facilitated the maintenance of interoceptive accuracy levels over time (from the initial, stimulation-free, baseline block to subsequent stimulation blocks), suggesting that vagus nerve stimulation may have helped to maintain engagement to cardiac afferent signals. During the interoceptive task, taVNS compared to sham, produced higher heart-evoked potentials (HEP) amplitudes, a potential readout measure of cardiac-related prediction error processing. Further analyses revealed that the positive relation between interoceptive accuracy and allostatic adjustments-as measured by heart rate variability (HRV)-was mediated by HEP amplitudes. Providing initial support for predictive processing accounts of interoception, our results suggest that the stimulation of the vagus nerve may increase the precision with which interoceptive signals are processed, favoring their influence on allostatic adjustments.

Transcutaneous Auricular Vagus Nerve Stimulation to Improve Emotional State

Emotional experiences are a part of our lives. The maladaptive functioning of an individual's emotional field can lead to emotional disturbances of various kinds, such as anxiety and depression. Currently, there is an increasing prevalence of emotional disorders that cause great human suffering and high socioeconomic costs. Emotional processing has a biological basis. The major neuroscientific theories of emotion are based on biological functioning, and all of them take into account the anatomy and function of the tenth cranial nerve: the vagus nerve. The vagus nerve connects the subdiaphragmatic and supradiaphragmatic areas and modulates emotional processing as the basis of interoceptive functioning. Auricular vagus nerve stimulation is a new and innovative neuromodulation technique based on the function of the vagus nerve. Several interventions have shown that this new neurostimulation technique is a very promising resource for treating emotional disorders. In this paper, we summarise three neuroscientific theories of emotion, explain what transcutaneous auricular nerve stimulation is, and present arguments for its use and continued research.

Exploration versus exploitation decisions in the human brain: A systematic review of functional neuroimaging and neuropsychological studies

Thoughts and actions are often driven by a decision to either explore new avenues with unknown outcomes, or to exploit known options with predictable outcomes. Yet, the neural mechanisms underlying this exploration-exploitation trade-off in humans remain poorly understood. This is attributable to variability in the operationalization of exploration and exploitation as psychological constructs, as well as the heterogeneity of experimental protocols and paradigms used to study these choice behaviours. To address this gap, here we present a comprehensive review of the literature to investigate the neural basis of explore-exploit decision-making in humans. We first conducted a systematic review of functional magnetic resonance imaging (fMRI) studies of exploration-versus exploitation-based decision-making in healthy adult humans during foraging, reinforcement learning, and information search. Eleven fMRI studies met inclusion criterion for this review. Adopting a network neuroscience framework, synthesis of the findings across these studies revealed that exploration-based choice was associated with the engagement of attentional, control, and salience networks. In contrast, exploitation-based choice was associated with engagement of default network brain regions. We interpret these results in the context of a network architecture that supports the flexible switching between externally and internally directed cognitive processes, necessary for adaptive, goal-directed behaviour. To further investigate potential neural mechanisms underlying the exploration-exploitation trade-off we next surveyed studies involving neurodevelopmental, neuropsychological, and neuropsychiatric disorders, as well as lifespan development, and neurodegenerative diseases. We observed striking differences in patterns of explore-exploit decision-making across these populations, again suggesting that these two decision-making modes are supported by independent neural circuits. Taken together, our review highlights the need for precision-mapping of the neural circuitry and behavioural correlates associated with exploration and exploitation in humans. Characterizing exploration versus exploitation decision-making biases may offer a novel, trans-diagnostic approach to assessment, surveillance, and intervention for cognitive decline and dysfunction in normal development and clinical populations.

Emotion regulation from an action-control perspective

Despite increasing interest in emotional processes in cognitive science, theories on emotion regulation have remained rather isolated, predominantly focused on cognitive regulation strategies such as reappraisal. However, recent neurocognitive evidence suggests that early emotion regulation may involve sensorimotor control in addition to other emotion-regulation processes. We propose an action-oriented view of emotion regulation, in which feedforward predictions develop from action-selection mechanisms. Those can account for acute emotional-action control as well as more abstract instances of emotion regulation such as cognitive reappraisal. We argue the latter occurs in absence of overt motor output, yet in the presence of full-blown autonomic, visceral, and subjective changes. This provides an integrated framework with testable neuro-computational predictions and concrete starting points for intervention to improve emotion control in affective disorders.

Functional connectivity gradients of the cingulate cortex

Heterogeneity of the cingulate cortex is evident in multiple dimensions including anatomy, function, connectivity, and involvement in networks and diseases. Using the recently developed functional connectivity gradient approach and resting-state functional MRI data, we found three functional connectivity gradients that captured distinct dimensions of cingulate hierarchical organization. The principal gradient exhibited a radiating organization with transitions from the middle toward both anterior and posterior parts of the cingulate cortex and was related to canonical functional networks and corresponding behavioral domains. The second gradient showed an anterior-posterior axis across the cingulate cortex and had prominent geometric distance dependence. The third gradient displayed a marked differentiation of subgenual and caudal middle with other parts of the cingulate cortex and was associated with cortical morphology. Aside from providing an updated framework for understanding the multifaceted nature of cingulate heterogeneity, the observed hierarchical organization of the cingulate cortex may constitute a novel research agenda with potential applications in basic and clinical neuroscience.

Embodied cognitive morphogenesis as a route to intelligent systems

The embryological view of development is that coordinated gene expression, cellular physics and migration provides the basis for phenotypic complexity. This stands in contrast with the prevailing view of embodied cognition, which claims that informational feedback between organisms and their environment is key to the emergence of intelligent behaviours. We aim to unite these two perspectives as embodied cognitive morphogenesis, in which morphogenetic symmetry breaking produces specialized organismal subsystems which serve as a substrate for the emergence of autonomous behaviours. As embodied cognitive morphogenesis produces fluctuating phenotypic asymmetry and the emergence of information processing subsystems, we observe three distinct properties: acquisition, generativity and transformation. Using a generic organismal agent, such properties are captured through models such as tensegrity networks, differentiation trees and embodied hypernetworks, providing a means to identify the context of various symmetry-breaking events in developmental time. Related concepts that help us define this phenotype further include concepts such as modularity, homeostasis and 4E (embodied, enactive, embedded and extended) cognition. We conclude by considering these autonomous developmental systems as a process called connectogenesis, connecting various parts of the emerged phenotype into an approach useful for the analysis of organisms and the design of bioinspired computational agents.

Correspondence of functional connectivity gradients across human isocortex, cerebellum, and hippocampus

Gradient mapping is an important technique to summarize high dimensional biological features as low dimensional manifold representations in exploring brain structure-function relationships at various levels of the cerebral cortex. While recent studies have characterized the major gradients of functional connectivity in several brain structures using this technique, very few have systematically examined the correspondence of such gradients across structures under a common systems-level framework. Using resting-state functional magnetic resonance imaging, here we show that the organizing principles of the isocortex, and those of the cerebellum and hippocampus in relation to the isocortex, can be described using two common functional gradients. We suggest that the similarity in functional connectivity gradients across these structures can be meaningfully interpreted within a common computational framework based on the principles of predictive processing. The present results, and the specific hypotheses that they suggest, represent an important step toward an integrative account of brain function.

Improving the study of brain-behavior relationships by revisiting basic assumptions

Neuroimaging research has been at the forefront of concerns regarding the failure of experimental findings to replicate. In the study of brain-behavior relationships, past failures to find replicable and robust effects have been attributed to methodological shortcomings. Methodological rigor is important, but there are other overlooked possibilities: most published studies share three foundational assumptions, often implicitly, that may be faulty. In this paper, we consider the empirical evidence from human brain imaging and the study of non-human animals that calls each foundational assumption into question. We then consider the opportunities for a robust science of brain-behavior relationships that await if scientists ground their research efforts in revised assumptions supported by current empirical evidence.

Respiration-entrained brain oscillations in healthy fMRI participants with high anxiety

Brain-body interactions can be studied by using directed coupling measurements of fMRI oscillations in the low (0.1-0.2 Hz) and high frequency bands (HF; 0.2-0.4 Hz). Recently, a preponderance of oscillations in the information flow between the brainstem and the prefrontal cortex at around 0.15/0.16 Hz was shown. The goal of this study was to investigate the information flow between BOLD-, respiratory-, and heart beat-to-beat interval (RRI) signals in the HF band in healthy subjects with high anxiety during fMRI examinations. A multivariate autoregressive model was concurrently applied to the BOLD signals from the middle frontal gyrus (MFG), precentral gyrus and the brainstem, as well as to respiratory and RRI signals. Causal coupling between all signals was determined using the Directed Transfer Function (DTF). We found a salience of fast respiratory waves with a period of 3.1 s (corresponding to ~ 0.32 Hz) and a highly significant (p < 0.001) top-down information-flow from BOLD oscillations in the MFG to the brainstem. Additionally, there was a significant (p < 0.01) information flow from RRI to respiratory oscillations. We speculate that brain oscillations around 0.32 Hz, triggered by nasal breathing, are projected downwards to the brainstem. Particularly interesting is the driving force of cardiac to respiratory waves with a ratio of 1:1 or 1:2. These results support the binary hierarchy model with preferred respiratory frequencies at 0.32 Hz and 0.16 Hz.

Association of Regional Cortical Network Atrophy With Progression to Dementia in Patients With Primary Progressive Aphasia

BACKGROUND AND OBJECTIVES

Patients with primary progressive aphasia (PPA) have gradually progressive language deficits during the initial phase of the illness. As the underlying neurodegenerative disease progresses, patients with PPA start losing independent functioning due to the development of nonlanguage cognitive or behavioral symptoms. The timeline of this progression from the mild cognitive impairment stage to the dementia stage of PPA is variable across patients. In this study, in a sample of patients with PPA, we measured the magnitude of cortical atrophy within functional networks believed to subserve diverse cognitive and affective functions. The objective of the study was to evaluate the utility of this measure as a predictor of time to subsequent progression to dementia in PPA.

METHODS

Patients with PPA with largely independent daily function were recruited through the Massachusetts General Hospital Frontotemporal Disorders Unit. All patients underwent an MRI scan at baseline. Cortical atrophy was then estimated relative to a group of amyloid-negative cognitively normal control participants. For each patient, we measured the time between the baseline visit and the subsequent visit at which dementia progression was documented or last observation. Simple and multivariable Cox regression models were used to examine the relationship between cortical atrophy and the likelihood of progression to dementia.

RESULTS

Forty-nine patients with PPA (mean age = 66.39 ± 8.36 years, 59.2% females) and 25 controls (mean age = 67.43 ± 4.84 years, 48% females) were included in the data analysis. Greater baseline atrophy in not only the left language network (hazard ratio = 1.47, 95% CI = 1.17-1.84) but also in the frontoparietal control (1.75, 1.25-2.44), salience (1.63, 1.25-2.13), default mode (1.55, 1.19-2.01), and ventral frontotemporal (1.41, 1.16-1.71) networks was associated with a higher risk of progression to dementia. A multivariable model identified contributions of the left frontoparietal control (1.94, 1.09-3.48) and ventral frontotemporal (1.61, 1.09-2.39) networks in predicting dementia progression, with no additional variance explained by the language network (0.75, 0.43-1.31).

DISCUSSION

These results suggest that baseline atrophy in cortical networks subserving nonlanguage cognitive and affective functions is an important predictor of progression to dementia in PPA. This measure should be included in precision medicine models of prognosis in PPA.

Nine insights from internet engineering that help us understand brain network communication

Philosophers have long recognized the value of metaphor as a tool that opens new avenues of investigation. By seeing brains as having the goal of representation, the computer metaphor in its various guises has helped systems neuroscience approach a wide array of neuronal behaviors at small and large scales. Here I advocate a complementary metaphor, the internet. Adopting this metaphor shifts our focus from computing to communication, and from seeing neuronal signals as localized representational elements to seeing neuronal signals as traveling messages. In doing so, we can take advantage of a comparison with the internet's robust and efficient routing strategies to understand how the brain might meet the challenges of network communication. I lay out nine engineering strategies that help the internet solve routing challenges similar to those faced by brain networks. The internet metaphor helps us by reframing neuronal activity across the brain as, in part, a manifestation of routing, which may, in different parts of the system, resemble the internet more, less, or not at all. I describe suggestive evidence consistent with the brain's use of internet-like routing strategies and conclude that, even if empirical data do not directly implicate internet-like routing, the metaphor is valuable as a reference point for those investigating the difficult problem of network communication in the brain and in particular the problem of routing.

The role of the salience network in cognitive and affective deficits

Analysis and interpretation of studies on cognitive and affective dysregulation often draw upon the network paradigm, especially the Triple Network Model, which consists of the default mode network (DMN), the frontoparietal network (FPN), and the salience network (SN). DMN activity is primarily dominant during cognitive leisure and self-monitoring processes. The FPN peaks during task involvement and cognitive exertion. Meanwhile, the SN serves as a dynamic "switch" between the DMN and FPN, in line with salience and cognitive demand. In the cognitive and affective domains, dysfunctions involving SN activity are connected to a broad spectrum of deficits and maladaptive behavioral patterns in a variety of clinical disorders, such as depression, insomnia, narcissism, PTSD (in the case of SN hyperactivity), chronic pain, and anxiety, high degrees of neuroticism, schizophrenia, epilepsy, autism, and neurodegenerative illnesses, bipolar disorder (in the case of SN hypoactivity). We discuss behavioral and neurological data from various research domains and present an integrated perspective indicating that these conditions can be associated with a widespread disruption in predictive coding at multiple hierarchical levels. We delineate the fundamental ideas of the brain network paradigm and contrast them with the conventional modular method in the first section of this article. Following this, we outline the interaction model of the key functional brain networks and highlight recent studies coupling SN-related dysfunctions with cognitive and affective impairments.

Editorial: Focus feature on consciousness and cognition

Consciousness and cognition are an increasing focus of theoretical and experimental research in neuroscience, leveraging the methods and tools of brain dynamics and connectivity. This Focus Feature brings together a collection of articles that examine the various roles of brain networks in computational and dynamic models, and in studies of physiological and neuroimaging processes that underpin and enable behavioral and cognitive function.

Affective Enhancement of Episodic Memory Is Associated With Widespread Patterns of Intrinsic Functional Connectivity in the Brain Across the Adult Lifespan

Subjectively arousing experiences tend to be better remembered than neutral ones. While numerous task-related neuroimaging studies have revealed the neural mechanisms associated with this phenomenon, it remains unclear how variability in the extent to which individuals show superior memory for subjectively arousing stimuli is associated with the intrinsic functional organization of their brains. Here, we addressed this issue using functional magnetic resonance imaging data collected at rest from a sample drawn from the Cambridge Centre for Ageing and Neuroscience cohort (N = 269, 18–86 years). Specifically, we performed multi-voxel pattern analysis of intrinsic functional connectivity, an unbiased, data-driven approach to examine whole-brain voxel-wise connectivity patterns. This technique allowed us to reveal the most important features from the high-dimensional, whole-brain connectivity structure without a priori hypotheses about the topography and direction of functional connectivity differences. Behaviorally, both item and associative memory accuracy were enhanced for trials with affectively arousing (positive or negative) stimuli than those with neutral ones. Whole-brain multi-voxel pattern analysis of functional connectivity revealed that the affective enhancement of memory was associated with intrinsic connectivity patterns of spatially distributed brain regions belonging to several functional networks in the cerebral cortex. Post hoc seed-based brain-behavior regression analysis and principal component analysis of the resulting correlation maps showed that these connectivity patterns were in turn primarily characterized by the involvement of heteromodal association and paralimbic (dorsal attention, salience, and default mode) networks of the cerebral cortex as well as select subcortical structures (striatum, thalamus, and cerebellum). Collectively, these findings suggest that the affective enhancement of episodic memory may be characterized as a whole-brain phenomenon, possibly supported by intrinsic functional interactions across several networks and structures in the brain.

A new science of emotion: implications for functional neurological disorder

Functional neurological disorder reflects impairments in brain networks leading to distressing motor, sensory and/or cognitive symptoms that demonstrate positive clinical signs on examination incongruent with other conditions. A central issue in historical and contemporary formulations of functional neurological disorder has been the mechanistic and aetiological role of emotions. However, the debate has mostly omitted fundamental questions about the nature of emotions in the first place. In this perspective article, we first outline a set of relevant working principles of the brain (e.g. allostasis, predictive processing, interoception and affect), followed by a focused review of the theory of constructed emotion to introduce a new understanding of what emotions are. Building on this theoretical framework, we formulate how altered emotion category construction can be an integral component of the pathophysiology of functional neurological disorder and related functional somatic symptoms. In doing so, we address several themes for the functional neurological disorder field including: (i) how energy regulation and the process of emotion category construction relate to symptom generation, including revisiting alexithymia, 'panic attack without panic', dissociation, insecure attachment and the influential role of life experiences; (ii) re-interpret select neurobiological research findings in functional neurological disorder cohorts through the lens of the theory of constructed emotion to illustrate its potential mechanistic relevance; and (iii) discuss therapeutic implications. While we continue to support that functional neurological disorder is mechanistically and aetiologically heterogenous, consideration of how the theory of constructed emotion relates to the generation and maintenance of functional neurological and functional somatic symptoms offers an integrated viewpoint that cuts across neurology, psychiatry, psychology and cognitive-affective neuroscience.