Resting-State Brain Variability in Youth With Attention-Deficit/Hyperactivity Disorder.

In this study, we sought to determine the nature of the abnormality in resting-state default mode network (DMN) activation and explore its correlation with functional connectivity in attention-deficit/hyperactivity disorder (ADHD). We obtained resting-state functional magnetic resonance images of youth with ADHD and typically developing counterparts from the publicly available ADHD-200 database. We used data from Peking University (232 scans) and New York University (172 scans); the scan repetition time was 2 s for both data collection sites. We applied generalized estimating equations to estimate the variability of the averaged blood-oxygen-level-dependent (BOLD) time series extracted from the DMN at rest. We performed network-based statistics to determine the association between the observed differences in BOLD signal variability and altered functional connectivity. We analyzed data from 105 youth with ADHD (age: mean 12.17, standard deviation 2.31, median 12.25; 15.2% female, 84.8% male) and 140 typically developing youth (age: mean 11.99, standard deviation 2.28, median 11.85; 47.1% female, 52.9% male), who aged 7-17 years. The imaging data were cross-sectionally collected for each participant at one time point. We observed a greater number of significant BOLD signal changes and higher-order polynomial significant associations in youth with ADHD. Moreover, there were significant between-group differences in BOLD signal change after the first 140 s, which coincided with decreased resting-state functional connectivity within the DMN in youth with ADHD. Increased variability of neural signaling was intermittently observed in the brains of youth with ADHD at rest, thereby indicating their default mode state was more unstable than that of typically developing youth.

Frequency-specific alternations in the moment-to-moment BOLD signals variability in schizophrenia.

Variability of neuronal activity is considered as the fundamental mechanism for the flexible and optimal brain function. Moreover, different frequency neuro signal is related to specific function. While little is currently known regarding changes in spontaneous BOLD variability of schizophrenia. The current study used resting-state fMRI data from 53 chronic schizophrenic subjects and 67 healthy subjects to investigate this issue. The data-driven method was used to measure the BOLD variability (MSSD: mean square successive difference) in two different frequency bands respectively (slow-5: 0.01-0.027 Hz; slow-4:0.027-0.073 Hz). Schizophrenic subjects exhibited decreased BOLD variability in thalamus region, sensorimotor and visual networks, and increased BOLD variability in salience network compared to matched healthy controls. Moreover, the interaction effects between frequency and group were observed in thalamus and right dorsolateral prefrontal cortex (DLPFC). These findings identified that altered BOLD variability is frequency dependent in schizophrenia. Importantly, the severity of patients' negative symptom was related to the increased BOLD variability of DLPFC within slow-4 frequency band, highlighting the evidence that abnormal BOLD variability of frontal cortex is likely to have effects on the pathophysiology of negative symptom in schizophrenia.

BOLD signal variability and complexity in children and adolescents with and without autism spectrum disorder.

Variability of neural signaling is an important index of healthy brain functioning, as is signal complexity, which relates to information processing capacity. Alterations in variability and complexity may underlie certain brain dysfunctions. Here, resting-state fMRI was used to examine variability and complexity in children and adolescents with and without autism spectrum disorder (ASD). Variability was measured using the mean square successive difference (MSSD) of the time series, and complexity was assessed using sample entropy. A categorical approach was implemented to determine if the brain measures differed between diagnostic groups (ASD and controls). A dimensional approach was used to examine the continuum of relationships between each brain measure and behavioral severity, age, IQ, and the global efficiency (GE) of each participant's structural connectome, which reflects the structural capacity for information processing. Using the categorical approach, no significant group differences were found for neither MSSD nor entropy. The dimensional approach revealed significant positive correlations between each brain measure, GE, and age. Negative correlations were observed between each brain measure and the severity of ASD behaviors across all participants. These results reveal the nature of variability and complexity of BOLD signals in children and adolescents with and without ASD.

Dynamics of the heart rate variability and oxygen saturation response to acute normobaric hypoxia within the first 10 min of exposure.

Although the heart rate variability (HRV) response to hypoxia has been studied, little is known about the dynamics of HRV after hypoxia exposure. The purpose of this study was to assess the HRV and oxygen saturation (SpO2 ) responses to normobaric hypoxia (FiO2  = 9·6%) comparing 1 min segments to baseline (normoxia). Electrocardiogram and SpO2 were recorded during a 10-min hypoxia exposure in 29 healthy male subjects aged 26·0 ± 4·9 years. Baseline HRV values were obtained from a 5-min recording period prior to hypoxia. The hypoxia period was split into 10 non-overlapping 1-min segments and time domain HRV indexes (RMSSD and SDNN) were calculated for each segment. Differences (Δ) from baseline values were calculated and transformed using natural logarithm (Ln). This study revealed that the decrease in ΔSpO2 became significant (P<0·001) in the first minute of hypoxia, the decrease in ΔLn RMSSD became significant (P = 0·002) in the second minute, and the decrease in ΔLn SDNN became significant (P = 0·001) in the third minute. Between the second and fifth minute of hypoxia, ΔSpO2 correlated with ΔLn RMSSD (r = 0·57, P<0·001) and ΔLn SDNN (r = 0·44, P<0·001). Five min after the onset of hypoxia, ΔSpO2 was significantly (P = 0·002) decreased but changes in ΔLn RMSSD (P = 0·344) and ΔLn SDNN (P = 0·558) were not significant. In conclusion, the decrease in HRV was proportional to desaturation but only during the first 5 min of hypoxia.

Moment-to-Moment BOLD Signal Variability Reflects Regional Changes in Neural Flexibility across the Lifespan.

Variability of neuronal responses is thought to underlie flexible and optimal brain function. Because previous work investigating BOLD signal variability has been conducted within task-based fMRI contexts on adults and older individuals, very little is currently known regarding regional changes in spontaneous BOLD signal variability in the human brain across the lifespan. The current study used resting-state fMRI data from a large sample of male and female human participants covering a wide age range (6-85 years) across two different fMRI acquisition parameters (TR = 0.645 and 1.4 s). Variability in brain regions including a key node of the salience network (anterior insula) increased linearly across the lifespan across datasets. In contrast, variability in most other large-scale networks decreased linearly over the lifespan. These results demonstrate unique lifespan trajectories of BOLD variability related to specific regions of the brain and add to a growing literature demonstrating the importance of identifying normative trajectories of functional brain maturation.SIGNIFICANCE STATEMENT Although brain signal variability has traditionally been considered a source of unwanted noise, recent work demonstrates that variability in brain signals during task performance is related to brain maturation in old age as well as individual differences in behavioral performance. The current results demonstrate that intrinsic fluctuations in resting-state variability exhibit unique maturation trajectories in specific brain regions and systems, particularly those supporting salience detection. These results have implications for investigations of brain development and aging, as well as interpretations of brain function underlying behavioral changes across the lifespan.

The multiscale entropy: Guidelines for use and interpretation in brain signal analysis.

BACKGROUND: Multiscale entropy (MSE) estimates the predictability of a signal over multiple temporal scales. It has been recently applied to study brain signal variability, notably during aging. The grounds of its application and interpretation remain unclear and subject to debate. METHOD: We used both simulated and experimental data to provide an intuitive explanation of MSE and to explore how it relates to the frequency content of the signal, depending on the amount of (non)linearity and stochasticity in the underlying dynamics. RESULTS: The scaling and peak-structure of MSE curves relate to the scaling and peaks of the power spectrum in the presence of linear autocorrelations. MSE also captures nonlinear autocorrelations and their interactions with stochastic dynamical components. The previously reported crossing of young and old adults' MSE curves for EEG data appears to be mainly due to linear stochastic processes, and relates to young adults' EEG dynamics exhibiting a slower time constant. COMPARISON WITH EXISTING METHODS: We make the relationship between MSE curve and power spectrum as well as with a linear autocorrelation measure, namely multiscale root-mean-square-successive-difference, more explicit. MSE allows gaining insight into the time-structure of brain activity fluctuations. Its combined use with other metrics could prevent any misleading interpretations with regard to underlying stochastic processes. CONCLUSIONS: Although not straightforward, when applied to brain signals, the features of MSE curves can be linked to their power content and provide information about both linear and nonlinear autocorrelations that are present therein.

Neurostructural abnormalities associated with axes of emotion dysregulation in generalized anxiety.

BACKGROUND: Despite the high prevalence of generalized anxiety disorder (GAD) and its negative impact on society, its neurobiology remains obscure. This study characterizes the neurostructural abnormalities associated with key symptoms of GAD, focusing on indicators of impaired emotion regulation (excessive worry, poor concentration, low mindfulness, and physiological arousal). METHODS: These domains were assessed in 19 (16 women) GAD patients and 19 healthy controls matched for age and gender, using questionnaires and a low demand behavioral task performed before and after an induction of perseverative cognition (i.e. worry and rumination). Continuous pulse oximetry was used to measure autonomic physiology (heart rate variability; HRV). Observed cognitive and physiological changes in response to the induction provided quantifiable data on emotional regulatory capacity. Participants underwent structural magnetic resonance imaging; voxel-based morphometry was used to quantify the relationship between gray matter volume and psychological and physiological measures. RESULTS: Overall, GAD patients had lower gray matter volume than controls within supramarginal, precentral, and postcentral gyrus bilaterally. Across the GAD group, increased right amygdala volume was associated with prolonged reaction times on the tracking task (indicating increased attentional impairment following the induction) and lower scores on the 'Act with awareness' subscale of the Five Facets Mindfulness Questionnaire. Moreover in GAD, medial frontal cortical gray matter volume correlated positively with the 'Non-react mindfulness' facet. Lastly, smaller volumes of bilateral insula, bilateral opercular cortex, right supramarginal and precentral gyri, anterior cingulate and paracingulate cortex predicted the magnitude of autonomic change following the induction (i.e. a greater decrease in HRV). CONCLUSIONS: Results distinguish neural structures associated with impaired capacity for cognitive, attentional and physiological disengagement from worry, suggesting that aberrant competition between these levels of emotional regulation is intrinsic to symptom expression in GAD.

Munc18-1 haploinsufficiency results in enhanced anxiety-like behavior as determined by heart rate responses in mice.

Heterozygous (HZ) missense mutations in the gene encoding syntaxin binding protein 1 (Stxbp1 or Munc18-1), a presynaptic protein essential for neurotransmitter release, causes early infantile epileptic encephalopathy, abnormal brain structure and mental retardation in humans. Here we investigated whether the mouse model mimics symptoms of the human phenotype. The effects of the deletion of munc18-1 were studied in HZ and wild-type (WT) mice based on heart rate (HR) and its variability (HRV) as independent measures to expand previous behavioral results of enhanced anxiety and impaired emotional learning suggesting mild cognitive impairments. HR responses were assessed during novelty exposure, during the expression and extinction of conditioned tone-dependent fear and during the diurnal phase. Novelty exposure yielded no differences in activity patterns between the two genotypes, while maximum HR differed significantly (WT: 770 bpm; HZ: 790 bpm). Retention tests after both auditory delay and trace fear conditioning showed a delayed extinction of the conditioned HR response in HZ mice compared to WT mice. Since the HR versus HRV correlation and HR dynamics assessed by nonlinear methods revealed similar function in HZ and WT mice, the higher HR responses of munc18-1 HZ mice to different emotional challenges cannot be attributed to differences in autonomic nervous system function. Thus, in contrast to the adverse consequences of deletion of a single allele of munc18-1 in humans, C57BL/6J mice show enhanced anxiety responses based on HR adjustments that extend previous results on the behavioral level without support of cognitive impairment, epileptic seizures and autonomic dysregulation.