Resting-state Neural Activity Research Articles

Resting state neurophysiology of agonist–antagonist myoneural interface in persons with transtibial amputation

The agonist–antagonist myoneural interface (AMI) is an amputation surgery that preserves sensorimotor signaling mechanisms of the central-peripheral nervous systems. Our first neuroimaging study investigating AMI subjects conducted by Srinivasan et al. (2020) focused on task-based neural signatures, and showed evidence of proprioceptive feedback to the central nervous system. The study of resting state neural activity helps non-invasively characterize the neural patterns that prime task response. In this study on resting state functional magnetic resonance imaging in AMI subjects, we compared functional connectivity in patients with transtibial AMI (n = 12) and traditional (n = 7) amputations (TA). To test our hypothesis that we would find significant neurophysiological differences between AMI and TA subjects, we performed a whole-brain exploratory analysis to identify a seed region; namely, we conducted ANOVA, followed by t-test statistics to locate a seed in the salience network. Then, we implemented a seed-based connectivity analysis to gather cluster-level inferences contrasting our subject groups. We show evidence supporting our hypothesis that the AMI surgery induces functional network reorganization resulting in a neural configuration that significantly differs from the neural configuration after TA surgery. AMI subjects show significantly less coupling with regions functionally dedicated to selecting where to focus attention when it comes to salient stimuli. Our findings provide researchers and clinicians with a critical mechanistic understanding of the effect of AMI amputation on brain networks at rest, which has promising implications for improved neurorehabilitation and prosthetic control.

Investigating the impact of rumination and adverse childhood experiences on resting-state neural activity and connectivity in depression

BackgroundBoth ruminative thought processes and adverse childhood experiences (ACEs) are well-established risk factors for the emergence and maintenance of depression. However, the neurobiological mechanisms underlying these associations remain poorly understood. MethodsWe examined resting-state functional magnetic resonance imaging data (3 T Tim Trio MR scanner; Siemens, Erlangen) of 44 individuals diagnosed with an acute depressive episode. Specifically, we focused on investigating functional brain activity and connectivity within and between three large-scale neural networks associated with processes affected in depression: the default mode network (DMN), the salience network (SN), and the central executive network (CEN). Correlational and regression-based analyses were performed. ResultsOur regions of interest analyses revealed that region-specific spontaneous neural activity in the anterior DMN was associated with self-reported trait rumination, specifically, the pregenual anterior cingulate cortex (pgACC). Furthermore, using a liberal statistical threshold, we found that spontaneous neural activity of the ventromedial prefrontal cortex and the pgACC were associated with depression symptom severity. Neither spontaneous neural activity in the SN and CEN nor functional connectivity within and across the investigated networks was associated with depression severity or rumination. Furthermore, there was no association between ACEs and brain activity and connectivity. LimitationsLack of a formal control group or low-risk group for comparison. ConclusionsOverall, our results indicate network-specific changes in spontaneous brain activity, that are linked to both depression severity and rumination. Findings underscore the crucial role of the pgACC in depression and contribute to a dimensional and symptom-based understanding of depression-related network imbalances.

Connectivity-based Meta-Bands: A new approach for automatic frequency band identification in connectivity analyses

The majority of electroencephalographic (EEG) and magnetoencephalographic (MEG) studies filter and analyse neural signals in specific frequency ranges, known as “canonical” frequency bands. However, this segmentation, is not exempt from limitations, mainly due to the lack of adaptation to the neural idiosyncrasies of each individual. In this study, we introduce a new data-driven method to automatically identify frequency ranges based on the topological similarity of the frequency-dependent functional neural network. The resting-state neural activity of 195 cognitively healthy subjects from three different databases (MEG: 123 subjects; EEG1: 27 subjects; EEG2: 45 subjects) was analysed. In a first step, MEG and EEG signals were filtered with a narrow-band filter bank (1 Hz bandwidth) from 1 to 70 Hz with a 0.5 Hz step. Next, the connectivity in each of these filtered signals was estimated using the orthogonalized version of the amplitude envelope correlation to obtain the frequency-dependent functional neural network. Finally, a community detection algorithm was used to identify communities in the frequency domain showing a similar network topology. We have called this approach the “Connectivity-based Meta-Bands” (CMB) algorithm. Additionally, two types of synthetic signals were used to configure the hyper-parameters of the CMB algorithm. We observed that the classical approaches to band segmentation are partially aligned with the underlying network topologies at group level for the MEG signals, but they are missing individual idiosyncrasies that may be biasing previous studies, as revealed by our methodology. On the other hand, the sensitivity of EEG signals to reflect this underlying frequency-dependent network structure is limited, revealing a simpler frequency parcellation, not aligned with that defined by the “canonical” frequency bands. To the best of our knowledge, this is the first study that proposes an unsupervised band segmentation method based on the topological similarity of functional neural network across frequencies. This methodology fully accounts for subject-specific patterns, providing more robust and personalized analyses, and paving the way for new studies focused on exploring the frequency-dependent structure of brain connectivity.

Managing Cancer and Living Meaningfully (CALM) alleviates chemotherapy related cognitive impairment (CRCI) in breast cancer survivors: A pilot study based on resting-state fMRI.

Chemotherapy related cognitive impairment (CRCI) is a type of memory and cognitive impairment induced by chemotherapy and has become a growing clinical problem. Breast cancer survivors (BCs) refer to patients from the moment of breast cancer diagnosis to the end of their lives. Managing Cancer and Living Meaningfully (CALM) is a convenient and easy-to-apply psychological intervention that has been proven to improve quality of life and alleviate CRCI in BCs. However, the underlying neurobiological mechanisms remain unclear. Resting-state functional magnetic resonance imaging (rs-fMRI) has become an effective method for understanding the neurobiological mechanisms of brain networks in CRCI. The fractional amplitude of low-frequency fluctuations (fALFF) and ALFF have often been used in analyzing the power and intensity of spontaneous regional resting state neural activity. The recruited BCs were randomly divided into the CALM group and the care as usual (CAU) group. All BCs were evaluated by the Functional Assessment of Cancer Therapy Cognitive Function (FACT-Cog) before and after CALM or CAU. The rs-fMRI imaging was acquired before and after CALM intervention in CALM group BCs. The BCs were defined as before CALM intervention (BCI) group and after CALM intervention (ACI) group. There were 32 BCs in CALM group and 35 BCs in CAU group completed the overall study. There were significant differences between the BCI group and the ACI group in the FACT-Cog-PCI scores. Compared with the BCI group, the ACI group showed lower fALFF signal in the left medial frontal gyrus and right sub-gyral and higher fALFF in the left occipital_sup and middle occipital gyrus. There was a significant positive correlation between hippocampal ALFF value and FACT-Cog-PCI scores. CALM intervention may have an effective function in alleviating CRCI of BCs. The altered local synchronization and regional brain activity may be correlated with the improved cognitive function of BCs who received the CALM intervention. The ALFF value of hippocampus seems to be an important factor in reflect cognitive function in BCs with CRCI and the neural network mechanism of CALM intervention deserves further exploration to promote its application.

Sleep quality differentially modulates neural oscillations and proteinopathy in Alzheimer's disease.

Alterations in resting-state neural activity have been reported in people with sleep disruptions and in patients with Alzheimer's disease, but the direct impact of sleep quality on Alzheimer's disease-related neurophysiological aberrations is unclear. We collected cross-sectional resting-state magnetoencephalography and extensive neuropsychological and clinical data from 38 biomarker-confirmed patients on the Alzheimer's disease spectrum and 20 cognitively normal older control participants. Sleep efficiency was quantified using the Pittsburgh Sleep Quality Index. Neural activity in the delta frequency range was differentially affected by poor sleep in patients on the Alzheimer's disease spectrum. Such neural changes were related to processing speed abilities and regional amyloid accumulation, and these associations were mediated and moderated, respectively, by sleep quality. Together, our results point to a mechanistic role for sleep disturbances in the widely reported neurophysiological aberrations seen in patients on the Alzheimer's disease spectrum, with implications for basic research and clinical intervention. National Institutes of Health, USA.

Altered brain activity in patients with end-stage renal disease: A meta-analysis of resting-state functional imaging.

Previous studies have revealed abnormal resting-state brain activity in patients with end-stage renal disease (ESRD); however, the results are inconsistent. Thus, we conducted a coordinate-based meta-analysis of whole-brain resting-state functional neuroimaging studies in ESRD to identify the most consistent neural activity alterations in ESRD patients and explore their relation to serological indicators. A comprehensive literature search strategy was applied to select pertinent studies up to December 2022 in PubMed, Web of Science, and Embase databases. Voxel-wise meta-analysis was conducted via the latest meta-analytic algorithm, seed-based d mapping with permutation of subject images software. Meta-regression analyses were also conducted to explore the potential effect of clinical variables on resting-state neural activity. Eleven studies comprising 304 patients with ESRD and 296 healthy controls (HCs) were included. Compared with HCs, ESRD patients showed decreased brain activity in the default mode network (DMN) regions, including the bilateral anterior cingulate cortex/medial prefrontal cortex, bilateral midcingulate cortex/posterior cingulate cortex, bilateral precuneus, and right angular gyrus. The neural activities in the bilateral midcingulate cortex, bilateral midcingulate cortex/posterior cingulate cortex, and right angular gyrus were significantly associated with serological indexes including hemoglobin, urea, and creatinine levels. The present study provides a quantitative overview of brain activity alterations in patients with ESRD, and the results confirm the essential role of the DMN in ESRD patients, which may be the potential neural basis of their cognitive deficits. Additionally, some serological indicators may be used as predictive markers for progressive impairment of brain function.

Functional connectivity between pre-supplementary motor area and inferior parietal lobule associated with impaired motor response inhibition in first-degree relatives of patients with obsessive-compulsive disorder.

Previous studies have suggested that specific fronto-striatal circuits are associated with impaired motor response inhibition in patients with obsessive-compulsive disorder (OCD) and their relatives. However, no study has investigated the underlying resting-state network associated with motor response inhibition in the unaffected first-degree relatives of patients with OCD. We measured motor response inhibition using stop-signal task, and obtained resting-state fMRI in 23 first-degree relatives and 52 healthy control participants. We explored the group differences in the functional network from seed regions-of-interest (ROIs) associated with motor response inhibition abilities. We used the inferior frontal gyrus (IFG) and pre-supplementary motor area (pre-SMA) as seed-ROIs. A significant group difference was observed in functional connectivity between the pre-SMA and inferior parietal lobule. In the relative group, reduced functional connectivity between these areas was associated with a longer stop-signal reaction time. Additionally, relatives showed significantly greater functional connectivity between the IFG and SMA, precentral, and postcentral areas. Our results could provide new insights into the resting-state neural activity of the pre-SMA underlying impaired motor response inhibition of unaffected first-degree relatives. In addition, our results suggested that relatives have an altered connectivity of the sensorimotor region, similar to that of patients with OCD shown in previous literature.

Changes in Resting-State Neural Activity and Nerve Fibres in Ischaemic Stroke Patients with Hemiplegia.

Many neuroimaging studies have reported that stroke induces abnormal brain activity. However, little is known about resting-state networks (RSNs) and the corresponding white matter changes in stroke patients with hemiplegia. Here, we utilized functional magnetic resonance imaging (fMRI) to measure neural activity and related fibre tracts in 14 ischaemic stroke patients with hemiplegia and 12 healthy controls. Fractional amplitude of low-frequency fluctuations (fALFF) calculation and correlation analyses were used to assess the relationship between regional neural activity and movement scores. Tractography was performed using diffusion tensor imaging (DTI) data to analyse the fibres passing through the regions of interest. Compared with controls, stroke patients showed abnormal functional connectivity (FC) between some brain regions in the RSNs. The fALFF was increased in the contralesional parietal lobe, with the regional fALFF being correlated with behavioural scores in stroke patients. Additionally, the passage of fibres across regions with reduced FC in the RSNs was increased in stroke patients. This study suggests that structural remodelling of functionally relevant white matter tracts is probably an adaptive response that compensates for injury to the brain.

The association of rumination and adverse childhood experiences with resting-state neural activity, connectivity, and neurotransmitter concentrations in depression

The association of rumination and adverse childhood experiences with resting-state neural activity, connectivity, and neurotransmitter concentrations in depression

Changes of Resting-State Neural Activity and Nerve Fibers in Ischemic Stroke Patients with Hemiplegia

Changes of Resting-State Neural Activity and Nerve Fibers in Ischemic Stroke Patients with Hemiplegia

Global Fractional Anisotropy: Effect on Resting-state Neural Activity and Brain Networking in Healthy Participants

The global fractional anisotropy (gFA) is a structural marker of white matter myelination and integrity. Previous studies already evidenced that aging-related reduced integrity of specific white matter tracts is associated with decreased functional connectivity in several hubs. However, the correlations between gFA and functional brain connectivity remain unknown. In this cross-sectional study, we analyzed structural and functional MR datasets of 79 healthy participants from the Leipzig Study for Mind–Body–Emotion Interactions. DTI model-based method was used to quantify gFA values. We tested associations between gFA, age, and gender. The fractional amplitude of low-frequency fluctuations (fALFF) and ROI-to-ROI connectivity were analyzed in a regression model for evaluating the effects of gFA on brain activity and networking, respectively. A negative correlation was found between gFA and age (ρ = −0.343; p = 0.002). No statistically significant correlation as found between gFA and gender (p = 0.229). Higher values of gFA were associated with increased brain regional activity, including areas of the default mode network. There was a higher degree of correlation between some regions, particularly those that conform to the limbic system. Our study demonstrates that gFA influences regional neural activity and brain networking on resting, particularly the limbic system.

Resting-state aperiodic neural dynamics predict individual differences in visuomotor performance and learning.

An emerging body of work has demonstrated that resting-state non-oscillatory, or aperiodic, 1/f neural activity is a functional and behaviorally relevant marker of cognitive function capacity. In the motor domain, previous work has only applied 1/f analyses to investigations of motor coordination and performance measures. The value of aperiodic resting-state neural dynamics as a marker of individual visuomotor performance capacity remains unknown. Accordingly, the aim of this work was to investigate if individual 1/f intercept and slope parameters of aperiodic resting-state neural activity predict reaction time and perceptual sensitivity in an immersive virtual reality marksmanship task. The marksmanship task required speeded selection of target stimuli and avoidance of selecting non-target stimuli. Motor and perceptual demands were incrementally increased across task blocks and participants performed the task across three training sessions spanning one week. When motor demands were high, steeper individual 1/f slope predicted shorter reaction time. This relationship did not change with practice. Increased 1/f intercept and a steeper 1/f slope were associated with higher perceptual sensitivity, measured as d'. However, this association was only observed under the highest levels of perceptual demand and only in the initial exposure to these conditions. Individuals with a lower 1/f intercept and a shallower 1/f slope demonstrated the greatest gains in perceptual sensitivity from task practice. These findings demonstrate that individual differences in motor and perceptual performance can be accounted for with resting-state aperiodic neural dynamics. The 1/f aperiodic parameters are most informative in predicting visuomotor performance under complex and demanding task conditions. In addition to predicting capacity for high visuomotor performance with a novel task, 1/f aperiodic parameters might also be useful in predicting which individuals might derive the most improvements from practice.

The interplay of resting and inhibitory control-related theta-band activity depends on age.

Resting‐state neural activity plays an important role for cognitive control processes. Regarding response inhibition processes, an important facet of cognitive control, especially theta‐band activity has been the focus of research. Theoretical considerations suggest that the interrelation of resting and task‐related theta activity is subject to maturational effects. To investigate whether the relationship between resting theta activity and task‐related theta activity during a response inhibition task changes even in young age, we tested N = 166 healthy participants between 8 and 30 years of age. We found significant correlations between resting and inhibitory control‐related theta activity as well as behavioral inhibition performance. Importantly, these correlations were moderated by age. The moderation analysis revealed that higher resting theta activity was associated with stronger inhibition‐related theta activity in individuals above the age of ~10.7 years. The EEG beamforming analysis showed that this activity is associated with superior frontal region function (BA6). The correlation between resting and superior frontal response inhibition‐related theta activity became stronger with increasing age. A similar pattern was found for response inhibition performance, albeit only evident from the age of ~19.5 years. The results suggest that with increasing age, resting theta activity becomes increasingly important for processing the alarm/surprise signals in superior frontal brain regions during inhibitory control. Possible causes for these developmental changes are discussed.

Consistency of local activation parameters at sensor- and source-level in neural signals

Objective. Although magnetoencephalography and electroencephalography (M/EEG) signals at sensor level are robust and reliable, they suffer from different degrees of distortion due to changes in brain tissue conductivities, known as field spread and volume conduction effects. To estimate original neural generators from M/EEG activity acquired at sensor level, diverse source localisation algorithms have been proposed; however, they are not exempt from limitations and usually involve time-consuming procedures. Connectivity and network-based M/EEG analyses have been found to be affected by field spread and volume conduction effects; nevertheless, the influence of the aforementioned effects on widely used local activation parameters has not been assessed yet. The goal of this study is to evaluate the consistency of various local activation parameters when they are computed at sensor- and source-level. Approach. Six spectral (relative power, median frequency, and individual alpha frequency) and non-linear parameters (Lempel-Ziv complexity, sample entropy, and central tendency measure) are computed from M/EEG signals at sensor- and source-level using four source inversion methods: weighted minimum norm estimate (wMNE), standardised low-resolution brain electromagnetic tomography (sLORETA), linear constrained minimum variance (LCMV), and dynamical statistical parametric mapping (dSPM). Main results. Our results show that the spectral and non-linear parameters yield similar results at sensor- and source-level, showing high correlation values between them for all the source inversion methods evaluated and both modalities of signal, EEG and MEG. Furthermore, the correlation values remain high when performing coarse-grained spatial analyses. Significance. To the best of our knowledge, this is the first study analysing how field spread and volume conduction effects impact on local activation parameters computed from resting-state neural activity. Our findings evidence that local activation parameters are robust against field spread and volume conduction effects and provide equivalent information at sensor- and source-level even when performing regional analyses.

Reduced Resting State Neural Activity in the Right Orbital Part of Middle Frontal Gyrus in Anxious Depression.

BackgroundAnxious depression (AD), which is generally recognized as a common clinical subtype of major depressive disorder (MDD), holds distinctive features compared with unanxious depression (UAD). However, the neural mechanism of AD still remains unrevealed. To give insight to it, we compared resting-state functional magnetic resonance amplitude of low-frequency fluctuation (ALFF) and functional connectivity (FC) between AD and UAD patients.MethodThe data were collected from 60 AD patients, 38 UAD patients, and 60 matched healthy controls. The ALFF and seed-based FC were examined. Pearson correlations were computed between ALFF/FC and clinical measures.ResultsIn Comparison with the UAD group, the ALFF value of the right orbital part of middle frontal gyrus (RO-MFG) decreased in AD group. Specifically, the ALFF values of the RO-MFG were negatively correlated with retardation factor scores in AD group (r = -0.376, p = 0.003).ConclusionsAD patients exhibited disturbed intrinsic brain function compared with UAD patients. The decreased activity of the RO-MFG is indicative of the alterations involved in the neural basis of AD.

Density center-based fast clustering of widefield fluorescence imaging of cortical mesoscale functional connectivity and relation to structural connectivity.

.Spontaneous resting-state neural activity or hemodynamics has been used to reveal functional connectivity in the brain. However, most of the commonly used clustering algorithms for functional parcellation are time-consuming, especially for high-resolution imaging data. We propose a density center-based fast clustering (DCBFC) method that can rapidly perform the functional parcellation of isocortex. DCBFC was validated using both simulation data and the spontaneous calcium signals from widefield fluorescence imaging of excitatory neuron-expressing transgenic mice (Vglut2-GCaMP6s). Compared to commonly used clustering methods such as k-means, hierarchical, and spectral, DCBFC showed a higher adjusted Rand index when the signal-to-noise ratio was greater than for simulated data and higher silhouette coefficient for in vivo mouse data. The resting-state functional connectivity (RSFC) patterns obtained by DCBFC were compared with the anatomic axonal projection density (PDs) maps derived from the voxel-scale model. The results showed a high spatial correlation between RSFC patterns and PDs.

You do not have to act to be impulsive: Brain resting-state activity predicts performance and impulsivity on the Balloon Analogue Risk Task

ObjectiveImpulsivity is a key, trait-like feature of the decision-making process. As personality traits are stable over time, we hypothesized that resting-state (RS) neural activity would predict individual impulsivity. MethodsThirty-five healthy individuals underwent fMRI scan during RS and subsequently performed the Balloon Analogue Risk Task (BART). In BART, impulsivity was inversely correlated to monetary earnings. A group-level whole-brain regression assessed the relationship between earnings at BART and RS evaluated by the Hurst Exponent, regional homogeneity; low frequency oscillation (LFO), (including the Amplitude of Low Frequency Fluctuations – ALFF– and the fractional Amplitude of Low Frequency Fluctuations –fALFF) and the Default Mode Network (DMN) functional connectivity. ResultsALFF significantly correlates with total earnings in the ventral part of the ACC/MPFC (FWE corrected p < 0.05 (uncorrected p value <0.0005; cluster size: ≥10 voxels), while H significantly correlates with total earnings in the anterior insula and the part opercularis of the inferior frontal gyrus. ConclusionsThese results suggest that impulsivity and ability to change strategies according to external cues are trait characteristics shaped in the RS’s functional architecture that can be detected also when individuals are not engaged in decision-making tasks.

Neurocognitive Recovery of Sentence Processing in Aphasia.

Purpose Reorganization of language networks in aphasia takes advantage of the facts that (a) the brain is an organ of plasticity, with neuronal changes occurring throughout the life span, including following brain damage; (b) plasticity is highly experience dependent; and (c) as with any learning system, language reorganization involves a synergistic interplay between organism-intrinsic (i.e., cognitive and brain) and organism-extrinsic (i.e., environmental) variables. A major goal for clinical treatment of aphasia is to be able to prescribe treatment and predict its outcome based on the neurocognitive deficit profiles of individual patients. This review article summarizes the results of research examining the neurocognitive effects of psycholinguistically based treatment (i.e., Treatment of Underlying Forms; Thompson & Shapiro, 2005) for sentence processing impairments in individuals with chronic agrammatic aphasia resulting from stroke and primary progressive aphasia and addresses both behavioral and brain variables related to successful treatment outcomes. The influences of lesion volume and location, perfusion (blood flow), and resting-state neural activity on language recovery are also discussed as related to recovery of agrammatism and other language impairments. Based on these and other data, principles for promoting neuroplasticity of language networks are presented. Conclusions Sentence processing treatment results in improved comprehension and production of complex syntactic structures in chronic agrammatism and generalization to less complex, linguistically related structures in chronic agrammatism. Patients also show treatment-induced shifts toward normal-like online sentence processing routines (based on eye movement data) and changes in neural recruitment patterns (based on functional neuroimaging), with posttreatment activation of regions overlapping with those within sentence processing and dorsal attention networks engaged by neurotypical adults performing the same task. These findings provide compelling evidence that treatment focused on principles of neuroplasticity promotes neurocognitive recovery in chronic agrammatic aphasia. Presentation Videohttps://doi.org/10.23641/asha.10257587.

Behavioral and Electrophysiological Arguments in Favor of a Relationship between Impulsivity, Risk-Taking, and Success on the Iowa Gambling Task.

The aim of the present study was to investigate the relationship between trait impulsivity, risk-taking, and decision-making performance. We recruited 20 healthy participants who performed the Iowa Gambling Task (IGT) and the Balloon Analog Risk Task (BART) to measure decision-making and risk-taking. The impulsivity was measured by the Barratt Impulsiveness Scale. Resting-state neural activity was recorded to explore whether brain oscillatory rhythms provide important information about the dispositional trait of impulsivity. We found a significant correlation between the ability to develop a successful strategy and the propensity to take more risks in the first trials of the BART. Risk-taking was negatively correlated with cognitive impulsivity in participants who were unable to develop a successful strategy. Neither risk-taking nor decision-making was correlated with cortical asymmetry. In a more exploratory approach, the group was sub-divided in function of participants’ performances at the IGT. We found that the group who developed a successful strategy at the IGT was more prone to risk, whereas the group who failed showed a greater cognitive impulsivity. These results emphasize the need for individuals to explore their environment to develop a successful strategy in uncertain situations, which may not be possible without taking risks.

Resting-state neural activity and connectivity associated with subjective happiness

The majority of people throughout the world rate subjective happiness as the top of the important thing in life. A recent structural neuroimaging study exploring neurocognitive mechanisms underlying subjective happiness has suggested that the gray matter volume of the right precuneus is associated with Subjective Happiness Scale (SHS) scores. However, how the neural activity in this region, as well as the neural functional coupling between this and other regions, could be related to SHS scores remains unclear. To investigate these issues, we performed resting-state functional magnetic resonance imaging and analyzed the fractional amplitude of low-frequency fluctuation (fALFF) in participants, whose subjective happiness was evaluated using the SHS. Lower fALFF values in the right precuneus were associated with higher SHS scores. Furthermore, functional connectivity and spectral dynamic causal modeling analyses showed that both functional and effective connectivity of the right precuneus with the right amygdala were positively associated with SHS scores. These findings, together with other evidence on the information-processing functions of these brain regions, suggest the possibility that subjective happiness is associated with a reduction in self-referential mental processes, which are well integrated with emotional processing.