The Power of Smiling: The Adult Brain Networks Underlying Learned Infant Emotionality

Mothers and fathers show different neural synchrony with their children during shared experiences

Parent-child shared experiences has an important influence on social development in children although contributions of mothers and fathers may differ. Neural synchronicity occurs between mothers and fathers and their children during social interactions but it is unclear whether they differ in this respect. We used data from simultaneous fNIRS hyperscanning in mothers (n = 33) and fathers (n = 29) and their children (3-4 years) to determine different patterns and strengths of neural synchronization in the frontal cortex during co-viewing of videos or free-play. Mothers showed greater synchrony with child than fathers during passive viewing of videos and the synchronization was positively associated with video complexity and negatively associated with parental stress. During play interactions, mothers showed more controlling behaviors over their child and greater evidence for joint gaze and joint imitation play with child whereas fathers spent more time gazing at other things. In addition, different aspects of child communication promoted neural synchrony between mothers and fathers and child during active play interactions. Overall, our findings indicate greater neural and behavioral synchrony between mothers than fathers and young children during passive or active shared experiences, although for both it was weakened by parental distress and child difficulty.

Intrinsic neural timescales relate to the dynamics of infraslow neural waves

The human brain is a highly dynamic organ that operates across a variety of timescales, the intrinsic neural timescales (INT). In addition to the INT, the neural waves featured by its phase-related processes including their cycles with peak/trough and rise/fall play a key role in shaping the brain's neural activity. However, the relationship between the brain's ongoing wave dynamics and INT remains yet unclear. In this study, we utilized functional magnetic resonance imaging (fMRI) rest and task data from the Human Connectome Project (HCP) to investigate the relationship of infraslow wave dynamics [as measured in terms of speed by changes in its peak frequency (PF)] with INT. Our findings reveal that: (i) the speed of phase dynamics (PF) is associated with distinct parts of the ongoing phase cycles, namely higher PF in peak/trough and lower PF in rise/fall; (ii) there exists a negative correlation between phase dynamics (PF) and INT such that slower PF relates to longer INT; (iii) exposure to a movie alters both PF and INT across the different phase cycles, yet their negative correlation remains intact. Collectively, our results demonstrate that INT relates to infraslow phase dynamics during both rest and task states.

Maternal prenatal distress exposure negatively associates with the stability of neonatal frontoparietal network

Maternal prenatal distress (PD), frequently defined as in utero prenatal stress exposure (PSE) to the developing fetus, influences the developing brain and numerous associations between PSE and brain structure have been described both in neonates and in older children. Previous studies addressing PSE-linked alterations in neonates' brain activity have focused on connectivity analyses from predefined seed regions, but the effects of PSE at the level of distributed functional networks remains unclear. In this study, we investigated the impact of prenatal distress on the spatial and temporal properties of functional networks detected in functional MRI data from 20 naturally sleeping, term-born (age 25.85 ± 7.72 days, 11 males), healthy neonates. First, we performed group level independent component analysis (GICA) to evaluate an association between PD and the identified functional networks. Second, we searched for an association with PD at the level of the stability of functional networks over time using leading eigenvector dynamics analysis (LEiDA). No statistically significant associations were detected at the spatial level for the GICA-derived networks. However, at the dynamic level, LEiDA revealed that maternal PD negatively associated with the stability of a frontoparietal network. These results imply that maternal PD may influence the stability of frontoparietal connections in neonatal brain network dynamics and adds to the cumulating evidence that frontal areas are especially sensitive to PSE. We advocate for early preventive intervention strategies regarding pregnant mothers. Nevertheless, future research venues are required to assess optimal intervention timing and methods for maximum benefit.

Depression recurrence is accompanied by longer periods in default mode and more frequent attentional and reward processing dynamic brain-states during resting-state activity

Recurrence in major depressive disorder (MDD) is common, but neurobiological models capturing vulnerability for recurrences are scarce. Disturbances in multiple resting-state networks have been linked to MDD, but most approaches focus on stable (vs. dynamic) network characteristics. We investigated how the brain's dynamical repertoire changes after patients transition from remission to recurrence of a new depressive episode. Sixty two drug-free, MDD-patients with ≥2 episodes underwent a baseline resting-state fMRI scan when in remission. Over 30-months follow-up, 11 patients with a recurrence and 17 matched-remitted MDD-patients without a recurrence underwent a second fMRI scan. Recurrent patterns of functional connectivity were characterized by applying Leading Eigenvector Dynamics Analysis (LEiDA). Differences between baseline and follow-up were identified for the 11 non-remitted patients, while data from the 17 matched-remitted patients was used as a validation dataset. After the transition into a depressive state, basal ganglia-anterior cingulate cortex (ACC) and visuo-attentional networks were detected significantly more often, whereas default mode network activity was found to have a longer duration. Additionally, the fMRI signal in the basal ganglia-ACC areas underlying the reward network, were significantly less synchronized with the rest of the brain after recurrence (compared to a state of remission). No significant changes were observed in the matched-remitted patients who were scanned twice while in remission. These findings characterize changes that may be associated with the transition from remission to recurrence and provide initial evidence of altered dynamical exploration of the brain's repertoire of functional networks when a recurrent depressive episode occurs.

Unraveling dyadic psycho-physiology of social presence between strangers during an audio drama - a signal-analysis approach

A mere co-presence of an unfamiliar person may modulate an individual's attentive engagement with specific events or situations to a significant degree. To understand better how such social presence affects experiences, we recorded a set of parallel multimodal facial and psychophysiological data with subjects (N = 36) who listened to dramatic audio scenes alone or when facing an unfamiliar person. Both a selection of 6 s affective sound clips (IADS-2) followed by a 27 min soundtrack extracted from a Finnish episode film depicted familiar and often intense social situations familiar from the everyday world. Considering the systemic complexity of both the chosen naturalistic stimuli and expected variations in the experimental social situation, we applied a novel combination of signal analysis methods using inter-subject correlation (ISC) analysis, Representational Similarity Analysis (RSA) and Recurrence Quantification Analysis (RQA) followed by gradient boosting classification. We report our findings concerning three facial signals, gaze, eyebrow and smile that can be linked to socially motivated facial movements. We found that ISC values of pairs, whether calculated on true pairs or any two individuals who had a partner, were lower than the group with single individuals. Thus, audio stimuli induced more unique responses in those subjects who were listening to it in the presence of another person, while individual listeners tended to yield a more uniform response as it was driven by dramatized audio stimulus alone. Furthermore, our classifiers models trained using recurrence properties of gaze, eyebrows and smile signals demonstrated distinctive differences in the recurrence dynamics of signals from paired subjects and revealed the impact of individual differences on the latter. We showed that the presence of an unfamiliar co-listener that modifies social dynamics of dyadic listening tasks can be detected reliably from visible facial modalities. By applying our analysis framework to a broader range of psycho-physiological data, together with annotations of the content, and subjective reports of participants, we expected more detailed dyadic dependencies to be revealed. Our work contributes towards modeling and predicting human social behaviors to specific types of audio-visually mediated, virtual, and live social situations.

Development of negative and positive emotionality in irritable and nonirritable neonates

OBJECTIVE

The current study compares the development of negative and positive emotionality of irritable and nonirritable neonates.

BACKGROUND

Research indicates that the first few months of life are marked by decreases in negative emotionality and increases in positive emotionality.

METHODS

The Neonatal Behavioural Assessment Scale (NBAS) was administered twice to 111 neonates at 3 and 4 weeks of age to select a sample of irritable neonates and a comparison group of nonirritable neonates. Mothers completed assessments of negative and positive emotionality at 1, 2, 4, and 9 months of age.

RESULTS

Both irritable and nonirritable neonates demonstrate a significant decrease in frustration and a significant increase in positive emotionality from 2 to 4 months of age. Irritable neonates also demonstrate a significant decrease in negative emotionality from 4 to 9 months of age. Both irritable and nonirritable neonates demonstrate considerable stability in negative and positive emotionality.

CONCLUSION

Implications of these results for parent education and early intervention are discussed.

Gender differences in brain response to infant emotional faces

Infant emotional stimuli can preferentially engage adults' attention and provide valuable information essential for successful interaction between adults and infants. Exploring the neural processes of recognizing infant stimuli promotes better understandings of the mother-infant attachment mechanisms. Here, combining task-functional magnetic resonance imaging (Task-fMRI) and resting-state fMRI (rs-fMRI), we investigated the effects of infants' faces on the brain activity of adults. Two groups including 26 women and 25 men were recruited to participate in the current study. During the task-fMRI, subjects were exposed to images of infant emotional faces (including happy, neutral, and sad) randomly. We found that the brains of women and men reacted differently to infants' faces, and these differential areas are in facial processing, attention, and empathetic networks. The rs-fMRI further showed that the connectivity of the default-mode network-related regions increased in women than in men. Additionally, brain activations in regions related to emotional networks were associated with the empathetic abilities of women. These differences in women might facilitate them to more effective and quick adjustments in behaviors and emotions during the nurturing infant period. The findings provide special implications and insights for understanding the neural processing of reacting to infant cues in adults.

Driving brain state transitions in major depressive disorder through external stimulation

Major depressive disorder (MDD) as a dysfunction of neural circuits and brain networks has been established in modern neuroimaging sciences. However, the brain state transitions between MDD and health through external stimulation remain unclear, which limits translation to clinical contexts and demonstrable clinical utility. We propose a framework of the large-scale whole-brain network model for MDD linking the underlying anatomical connectivity with functional dynamics obtained from diffusion tensor imaging (DTI) and functional magnetic resonance imaging (fMRI). Then, we further explored the optimal brain regions to promote the transition of brain states between MDD and health through external stimulation of the model. Based on the whole-brain model successfully fitting the brain state space in MDD and the health, we demonstrated that the transition from MDD to health is achieved by the excitatory activation of the limbic system and from health to MDD by the inhibitory stimulation of the reward circuit. Our finding provides novel biophysical evidence for the neural mechanism of MDD and its recovery and allows the discovery of new stimulation targets for MDD recovery.

Psilocybin modulation of time-varying functional connectivity is associated with plasma psilocin and subjective effects

BACKGROUND

Psilocin, the neuroactive metabolite of psilocybin, is a serotonergic psychedelic that induces an acute altered state of consciousness, evokes lasting changes in mood and personality in healthy individuals, and has potential as an antidepressant treatment. Examining the acute effects of psilocin on resting-state time-varying functional connectivity implicates network-level connectivity motifs that may underlie acute and lasting behavioral and clinical effects.

AIM

Evaluate the association between resting-state time-varying functional connectivity (tvFC) characteristics and plasma psilocin level (PPL) and subjective drug intensity (SDI) before and right after intake of a psychedelic dose of psilocybin in healthy humans.

METHODS

Fifteen healthy individuals completed the study. Before and at multiple time points after psilocybin intake, we acquired 10-minute resting-state blood-oxygen-level-dependent functional magnetic resonance imaging scans. Leading Eigenvector Dynamics Analysis (LEiDA) and diametrical clustering were applied to estimate discrete, sequentially active brain states. We evaluated associations between the fractional occurrence of brain states during a scan session and PPL and SDI using linear mixed-effects models. We examined associations between brain state dwell time and PPL and SDI using frailty Cox proportional hazards survival analysis.

RESULTS

Fractional occurrences for two brain states characterized by lateral frontoparietal and medial fronto-parietal-cingulate coherence were statistically significantly negatively associated with PPL and SDI. Dwell time for these brain states was negatively associated with SDI and, to a lesser extent, PPL. Conversely, fractional occurrence and dwell time of a fully connected brain state partly associated with motion was positively associated with PPL and SDI.

CONCLUSION

Our findings suggest that the acute perceptual psychedelic effects induced by psilocybin may stem from drug-level associated decreases in the occurrence and duration of lateral and medial frontoparietal connectivity motifs. We apply and argue for a modified approach to modeling eigenvectors produced by LEiDA that more fully acknowledges their underlying structure. Together these findings contribute to a more comprehensive neurobiological framework underlying acute effects of serotonergic psychedelics.

Test-retest reliability of time-varying patterns of brain activity across single band and multiband resting-state functional magnetic resonance imaging in healthy older adults

Leading Eigenvector Dynamics Analysis (LEiDA) is an analytic approach that characterizes brain activity recorded with functional Magnetic Resonance Imaging (fMRI) as a succession of discrete phase-locking patterns, or states, that consistently recur over time across all participants. LEiDA allows for the extraction of three state-related measures which have previously been key to gaining a better understanding of brain dynamics in both healthy and clinical populations: the probability of occurrence of a given state, its lifetime and the probability of switching from one state to another. The degree to which test-retest reliability of the LEiDA measures may be affected by increasing MRI multiband (MB) factors in comparison with single band sequences is yet to be established. In this study, 24 healthy older adults were scanned over three sessions, on weeks 0, 1, and 4. On each visit, they underwent a conventional single band resting-state fMRI (rs-fMRI) scan and three different MB rs-fMRI scans, with MB factors of 4, with and without in-plane acceleration, and 6 without in-plane acceleration. We found test-retest reliability scores to be significantly higher with MB factor 4 with and without in-plane acceleration for most cortical networks. These findings will inform the choice of acquisition parameters for future studies and clinical trials.

The naturalistic approach to laughter in humans and other animals: towards a unified theory

This opinion piece aims to tackle the biological, psychological, neural and cultural underpinnings of laughter from a naturalistic and evolutionary perspective. A naturalistic account of laughter requires the revaluation of two dogmas of a longstanding philosophical tradition, that is, the quintessential link between laughter and humour, and the uniquely human nature of this behaviour. In the spirit of Provine's and Panksepp's seminal studies, who firstly argued against the anti-naturalistic dogmas, here we review compelling evidence that (i) laughter is first and foremost a social behaviour aimed at regulating social relationships, easing social tensions and establishing social bonds, and that (ii) homologue and homoplasic behaviours of laughter exist in primates and rodents, who also share with humans the same underpinning neural circuitry. We make a case for the hypothesis that the contagiousness of laughter and its pervasive social infectiousness in everyday social interactions is mediated by a specific mirror mechanism. Finally, we argue that a naturalistic account of laughter should not be intended as an outright rejection of classic theories; rather, in the last part of the piece we argue that our perspective is potentially able to integrate previous viewpoints-including classic philosophical theories-ultimately providing a unified evolutionary explanation of laughter. This article is part of the theme issue 'Cracking the laugh code: laughter through the lens of biology, psychology and neuroscience'.

The web of laughter: frontal and limbic projections of the anterior cingulate cortex revealed by cortico-cortical evoked potential from sites eliciting laughter

According to an evolutionist approach, laughter is a multifaceted behaviour affecting social, emotional, motor and speech functions. Albeit previous studies have suggested that high-frequency electrical stimulation (HF-ES) of the pregenual anterior cingulate cortex (pACC) may induce bursts of laughter-suggesting a crucial contribution of this region to the cortical control of this behaviour-the complex nature of laughter implies that outward connections from the pACC may reach and affect a complex network of frontal and limbic regions. Here, we studied the effective connectivity of the pACC by analysing the cortico-cortical evoked potentials elicited by single-pulse electrical stimulation of pACC sites whose HF-ES elicited laughter in 12 patients. Once these regions were identified, we studied their clinical response to HF-ES, to reveal the specific functional target of pACC representation of laughter. Results reveal that the neural representation of laughter in the pACC interacts with several frontal and limbic regions, including cingulate, orbitofrontal, medial prefrontal and anterior insular regions-involved in interoception, emotion, social reward and motor behaviour. These results offer neuroscientific support to the evolutionist approach to laughter, providing a possible mechanistic explanation of the interplay between this behaviour and emotion regulation, speech production and social interactions. This article is part of the theme issue 'Cracking the laugh code: laughter through the lens of biology, psychology and neuroscience'.

The early adolescent brain on music: Analysis of functional dynamics reveals engagement of orbitofrontal cortex reward system

Music listening plays a pivotal role for children and adolescents, yet it remains unclear how music modulates brain activity at the level of functional networks in this young population. Analysing the dynamics of brain networks occurring and dissolving over time in response to music can provide a better understanding of the neural underpinning of music listening. We collected functional magnetic resonance imaging (fMRI) data from 17 preadolescents aged 10-11 years while listening to two similar music pieces separated by periods without music. We subsequently tracked the occurrence of functional brain networks over the recording time using a recent method that detects recurrent patterns of phase-locking in the fMRI signals: the leading eigenvector dynamics analysis (LEiDA). The probabilities of occurrence and switching profiles of different functional networks were compared between periods of music and no music. Our results showed significantly increased occurrence of a specific functional network during the two music pieces compared to no music, involving the medial orbitofrontal and ventromedial prefrontal cortices-a brain subsystem associated to reward processing. Moreover, the higher the musical reward sensitivity of the preadolescents, the more this network was preceded by a pattern involving the insula. Our findings highlight the involvement of a brain subsystem associated with hedonic and emotional processing during music listening in the early adolescent brain. These results offer novel insight into the neural underpinnings of musical reward in early adolescence, improving our understanding of the important role and the potential benefits of music at this delicate age.

Stronger brain activation for own baby but similar activation toward babies of own and different ethnicities in parents living in a multicultural environment

Specific facial features in infants automatically elicit attention, affection, and nurturing behaviour of adults, known as the baby schema effect. There is also an innate tendency to categorize people into in-group and out-group members based on salient features such as ethnicity. Societies are becoming increasingly multi-cultural and multi-ethnic, and there are limited investigations into the underlying neural mechanism of the baby schema effect in a multi-ethnic context. Functional magnetic resonance imaging (fMRI) was used to examine parents' (N = 27) neural responses to (a) non-own ethnic in-group and out-group infants, (b) non-own in-group and own infants, and (c) non-own out-group and own infants. Parents showed similar brain activations, regardless of ethnicity and kinship, in regions associated with attention, reward processing, empathy, memory, goal-directed action planning, and social cognition. The same regions were activated to a higher degree when viewing the parents' own infant. These findings contribute further understanding to the dynamics of baby schema effect in an increasingly interconnected social world.

Effects of visual attention modulation on dynamic functional connectivity during own-face viewing in body dysmorphic disorder

Body dysmorphic disorder (BDD) is characterized by preoccupations with misperceptions of one's physical appearance. Previous neuroimaging studies in BDD have yet to examine dynamic functional connectivity (FC) patterns between brain areas, necessary to capture changes in activity in response to stimuli and task conditions. We used Leading Eigenvector Dynamics Analysis to examine whole-brain dynamic FC from fMRI data during an own-face viewing task in 29 unmedicated adults with BDD with facial concerns and 30 healthy controls. The task involved two parts: (1) unconstrained, naturalistic viewing and (2) holding visual attention in the center of the image, to reduce scanning and fixation on perceived facial flaws. An FC state consisting of bilateral medial orbitofrontal cortex regions occurred significantly less often during the visual attention condition and afterward during the unconstrained face viewing in BDD participants, compared to the first unconstrained face viewing, a pattern that differed from controls. Moreover, the probability of this state during the second unconstrained face viewing was associated with severity of obsessions and compulsions and degree of poor insight in BDD, suggesting its clinical significance. These findings have implications for understanding the pathophysiology of own-face viewing in BDD and how it is affected by modification of viewing patterns, which may have implications for novel perceptual retraining treatment designs.

Brain States and Transitions: Insights from Computational Neuroscience

Within the field of computational neuroscience there are great expectations of finding new ways to rebalance the complex dynamic system of the human brain through controlled pharmacological or electromagnetic perturbation. Yet many obstacles remain between the ability to accurately predict how and where best to perturb to force a transition from one brain state to another. The foremost challenge is a commonly agreed definition of a given brain state. Recent progress in computational neuroscience has made it possible to robustly define brain states and force transitions between them. Here, we review the state of the art and propose a framework for determining the functional hierarchical organization describing any given brain state. We describe the latest advances in creating sophisticated whole-brain computational models with interacting neuronal and neurotransmitter systems that can be studied fully in silico to predict and design novel pharmacological and electromagnetic interventions to rebalance them in disease.

The Dynamics of Functional Brain Networks Associated With Depressive Symptoms in a Nonclinical Sample

Brain function depends on the flexible and dynamic coordination of functional subsystems within distributed neural networks operating on multiple scales. Recent progress has been made in the characterization of functional connectivity (FC) at the whole-brain scale from a dynamic, rather than static, perspective, but its validity for cognitive sciences remains under debate. Here, we analyzed brain activity recorded with functional Magnetic Resonance Imaging from 71 healthy participants evaluated for depressive symptoms after a relationship breakup based on the conventional Major Depression Inventory (MDI). We compared both static and dynamic FC patterns between participants reporting high and low depressive symptoms. Between-group differences in static FC were estimated using a standard pipeline for network-based statistic (NBS). Additionally, FC was analyzed from a dynamic perspective by characterizing the occupancy, lifetime, and transition profiles of recurrent FC patterns. Recurrent FC patterns were defined by clustering the BOLD phase-locking patterns obtained using leading eigenvector dynamics analysis (LEiDA). NBS analysis revealed a brain subsystem exhibiting significantly lower within-subsystem correlation values in more depressed participants (high MDI). This subsystem predominantly comprised connections between regions of the default mode network (i.e., precuneus) and regions outside this network. On the other hand, LEiDA results showed that high MDI participants engaged more in a state connecting regions of the default mode, memory retrieval, and frontoparietal network (p-FDR = 0.012); and less in a state connecting mostly the visual and dorsal attention systems (p-FDR = 0.004). Although both our analyses on static and dynamic FC implicate the role of the precuneus in depressive symptoms, only including the temporal evolution of BOLD FC helped to disentangle over time the distinct configurations in which this region plays a role. This finding further indicates that a holistic understanding of brain function can only be gleaned if the temporal dynamics of FC is included.

Ghost Attractors in Spontaneous Brain Activity: Recurrent Excursions Into Functionally-Relevant BOLD Phase-Locking States

Functionally relevant network patterns form transiently in brain activity during rest, where a given subset of brain areas exhibits temporally synchronized BOLD signals. To adequately assess the biophysical mechanisms governing intrinsic brain activity, a detailed characterization of the dynamical features of functional networks is needed from the experimental side to constrain theoretical models. In this work, we use an open-source fMRI dataset from 100 healthy participants from the Human Connectome Project and analyze whole-brain activity using Leading Eigenvector Dynamics Analysis (LEiDA), which serves to characterize brain activity at each time point by its whole-brain BOLD phase-locking pattern. Clustering these BOLD phase-locking patterns into a set of k states, we demonstrate that the cluster centroids closely overlap with reference functional subsystems. Borrowing tools from dynamical systems theory, we characterize spontaneous brain activity in the form of trajectories within the state space, calculating the Fractional Occupancy and the Dwell Times of each state, as well as the Transition Probabilities between states. Finally, we demonstrate that within-subject reliability is maximized when including the high frequency components of the BOLD signal (>0.1 Hz), indicating the existence of individual fingerprints in dynamical patterns evolving at least as fast as the temporal resolution of acquisition (here TR = 0.72 s). Our results reinforce the mechanistic scenario that resting-state networks are the expression of erratic excursions from a baseline synchronous steady state into weakly-stable partially-synchronized states - which we term ghost attractors. To better understand the rules governing the transitions between ghost attractors, we use methods from dynamical systems theory, giving insights into high-order mechanisms underlying brain function.