Hyper-resting brain entropy within chronic smokers and its moderation by Sex

Repetitive transcranial magnetic stimulation reshaped the dynamic reconfiguration of the executive and reward networks in individuals with tobacco use disorder

BACKGROUND

Studies have demonstrated the potential of repetitive transcranial magnetic stimulation (rTMS) to decrease smoking cravings in individuals with tobacco use disorder (TUD). However, the neural features underlying the effects of rTMS treatment, especially the dynamic attributes of brain networks associated with the treatment, remain unclear.

METHODS

Using dynamic functional connectivity analysis, this study first explored the differences in dynamic functional network features between 60 subjects with TUD and 64 nonsmoking healthy controls (HCs). Then, the left dorsolateral prefrontal cortex (DLPFC) was targeted for a five-day course of rTMS treatment in the 60 subjects with TUD (active rTMS in 42 subjects and sham treatment in 18 subjects). We explored the effect of rTMS on the dynamic network features associated with rTMS by comparing the actively treated group and the sham group.

RESULTS

Compared to nonsmokers, TUD subjects exhibited an increased integration coefficient between the frontoparietal network (FPN) and the basal ganglia network (BGN) and a reduced integration coefficient between the medial frontal network (MFN) and the FPN. Analysis of variance revealed that rTMS treatment reduced the integration coefficient between the FPN and BGN and improved the recruitment coefficient of the FPN.

LIMITATIONS

This study involved a limited sample of young male smokers, and the findings may not generalize to older smokers or female smokers with an extensive history of smoking.

CONCLUSION

rTMS treatment of the left DLPFC exhibited significant effectiveness in restructuring the neural circuits associated with TUD while significantly mitigating smoking cravings.

Altered Structural Connectivity and Functional Brain Dynamics in Individuals With Heavy Alcohol Use Elucidated via Network Control Theory

BACKGROUND

Heavy alcohol use and its associated conditions, such as alcohol use disorder, impact millions of individuals worldwide. While our understanding of the neurobiological correlates of alcohol use has evolved substantially, we still lack models that incorporate whole-brain neuroanatomical, functional, and pharmacological information under one framework.

METHODS

Here, we utilized diffusion and functional magnetic resonance imaging to investigate alterations to brain dynamics in 130 individuals with a high amount of current alcohol use. We compared these alcohol-using individuals to 308 individuals with minimal use of any substances.

RESULTS

We found that individuals with heavy alcohol use had less dynamic and complex brain activity, and through leveraging network control theory, had increased control energy to complete transitions between activation states. Furthermore, using separately acquired positron emission tomography data, we deployed an in silico evaluation demonstrating that decreased D2 receptor levels, as found previously in individuals with alcohol use disorder, may relate to our observed findings.

CONCLUSIONS

This work demonstrates that whole-brain, multimodal imaging information can be combined under a network control framework to identify and evaluate neurobiological correlates and mechanisms of heavy alcohol use.

Age-dependent functional development pattern in neonatal brain: An fMRI-based brain entropy study

The relationship between brain entropy (BEN) and early brain development has been established through animal studies. However, it remains unclear whether the BEN can be used to identify age-dependent functional changes in human neonatal brains and the genetic underpinning of the new neuroimaging marker remains to be elucidated. In this study, we analyzed resting-state fMRI data from the Developing Human Connectome Project, including 280 infants who were scanned at 37.5-43.5 weeks postmenstrual age. The BEN maps were calculated for each subject, and a voxel-wise analysis was conducted using a general linear model to examine the effects of age, sex, and preterm birth on BEN. Additionally, we evaluated the correlation between regional BEN and gene expression levels. Our results demonstrated that the BEN in the sensorimotor-auditory and association cortices, along the 'S-A' axis, was significantly positively correlated with postnatal age (PNA), and negatively correlated with gestational age (GA), respectively. Meanwhile, the BEN in the right rolandic operculum correlated significantly with both GA and PNA. Preterm-born infants exhibited increased BEN values in widespread cortical areas, particularly in the visual-motor cortex, when compared to term-born infants. Moreover, we identified five BEN-related genes (DNAJC12, FIG4, STX12, CETN2, and IRF2BP2), which were involved in protein folding, synaptic vesicle transportation and cell division. These findings suggest that the fMRI-based BEN can serve as an indicator of age-dependent brain functional development in human neonates, which may be influenced by specific genes.

Altered Resting-State Brain Entropy in Cerebral Small Vessel Disease Patients with Cognitive Impairment

Objective: Cerebral small vessel disease (CSVD) is a primary vascular disease of cognitive impairment. Previous studies have predominantly focused on brain linear features. However, the nonlinear measure, brain entropy (BEN), has not been elaborated. Thus, this study aims to investigate if BEN abnormalities could manifest in CSVD patients with cognitive impairment. Methods: Thirty-four CSVD patients with cognitive impairment and 37 healthy controls (HCs) were recruited. Analysis of gray matter approximate entropy (ApEn) and sample entropy (SampEn) which are two indices of BEN was calculated. To explore whether BEN can provide unique information, we further performed brain linear methods, namely, amplitude of low frequency fluctuation (ALFF) and regional homogeneity (ReHo), to observe their differences. The ratios of BEN/ALFF and BEN/ReHo which represent the coupling of nonlinear and linear features were introduced. Correlation analysis was conducted between imaging indices and cognition. Subsequently, the linear support vector machine (SVM) was used to assess their discriminative ability. Results: CSVD patients exhibited lower ApEn and SamEn values in sensorimotor areas, which were correlated with worse memory and executive function. In addition, the results of BEN showed little overlap with ALFF and ReHo in brain regions. Correlation analysis also revealed a relationship between the two ratios and cognition. SVM analysis using BEN and its ratios as features achieved an accuracy of 74.64% (sensitivity: 86.49%, specificity: 61.76%, and AUC: 0.82439). Conclusion: Our study reveals that the reduction of sensorimotor system complexity is correlated with cognition. BEN exhibits distinctive characteristics in brain activity. Combining BEN and the ratios can be new biomarkers to diagnose CSVD with cognitive impairment.

Divergent association between pain intensity and resting-state fMRI-based brain entropy in different age groups

Pain is a multidimensional subjective experience sustained by multiple brain regions involved in different aspects of pain experience. We used brain entropy (BEN) estimated from resting-state fMRI (rsfMRI) data to investigate the neural correlates of pain experience. BEN was estimated from rs-fMRI data provided by two datasets with different age range: the Human Connectome Project-Young Adult (HCP-YA) and the Human Connectome project-Aging (HCP-A) datasets. Retrospective assessment of experienced pain intensity was retrieved from both datasets. No main effect of pain intensity was observed. The interaction between pain and age, however, was related to increased BEN in several pain-related brain regions, reflecting greater variability of spontaneous brain activity. Dividing the sample into a young adult group (YG) and a middle age-aging group (MAG) resulted in two divergent patterns of pain-BEN association: In the YG, pain intensity was related to reduced BEN in brain regions involved in the sensory processing of pain; in the MAG, pain was associated with increased BEN in areas related to both sensory and cognitive aspects of pain experience.

Task-induced changes in brain entropy

Entropy indicates irregularity of a dynamic system, with higher entropy indicating higher irregularity and more transit states. In the human brain, regional brain entropy (BEN) has been increasingly assessed using resting state fMRI (rs-fMRI), while changes of regional BEN during task-based fMRI have been scarcely studied. The purpose of this study is to characterize task-induced regional BEN alterations using the large Human Connectome Project (HCP) data. To control the potential modulation by the block design, BEN of task-fMRI was calculated from the fMRI images acquired during the task conditions only (task BEN) and then compared to BEN of rs-fMRI (resting BEN). Moreover, BEN was separately calculated from the control blocks of the task-fMRI runs (control BEN) and compared to task BEN. Finally, control BEN was compared to resting BEN to test for residual task effects in the control condition. With respect to resting state, task performance unanimously induced BEN reduction in the peripheral cortical area and BEN increase in the centric part of the sensorimotor and perception networks. Control compared to resting BEN showed similar entropy alterations, suggesting large residual task effects. Task compared to control BEN was characterized by reduced entropy in occipital, orbitofrontal, and parietal regions.

Common hyper-entropy patterns identified in nicotine smoking, marijuana use, and alcohol use based on uni-drug dependence cohorts

Substance use disorders present similar behaviors and psychopathologies related to impaired decision making/inhibition control and information processing, suggesting common alterations in frontal and limbic brain areas. To test this hypothesis, we identified three uni-substance use cohorts with dependence to only one type of substance from the Human Connectome Project: marijuana dependence, nicotine dependence, and alcohol dependence. Fifty-nine marijuana uses, 34 nicotine smokers, 35 alcohol drinkers, and their age and sex-matched non-substance use controls were identified. We used brain entropy mapping to probe brain alterations in substance use disorders. Compared to non-substance use individuals, all three substance use disorder cohorts had increased brain entropy. Marijuana dependence and nicotine dependence showed overlapped hyper-brain entropy in bilateral dorso-lateral prefrontal cortex, anterior cingulate cortex, and right insula. Hyper-brain entropy in marijuana dependence and alcohol dependence overlap in left insula, left doso-lateral prefrontal cortex, and posterior cingulate. Hyper-brain entropy in nicotine dependence and alcohol dependence overlap only in left dorso-lateral prefrontal cortex. Hyper-brain entropy in those areas was correlated with increased impulsivity or reduced inhibition control in substance use disorder but not in controls. Drug dependence is associated with hyper-brain entropy in the prefrontal cortex and the meso-limbic system, independent of a specific addictive drug. Brain entropy in this circuit provides a sensitive marker to detect brain and behavioral alterations in substance user disorders.

A systematic review of sex/gender differences in the multi-dimensional neurobiological mechanisms in addiction and their relevance to impulsivity

Purpose of Review

Addiction may be characterized along three functional domains: Approach Behavior, Executive Function, and Negative Emotionality. Constructs underlying impulsivity thought to be relevant in addiction map on to these three functional domains. The purpose of the present review was to evaluate the extant research regarding sex/gender differences in the multi-dimensional domains of addiction using human neuroimaging and discuss their relevance to impulsivity.

Recent Findings

Few papers over the past two decades have used human neuroimaging to test sex/gender differences in addiction. There is therefore a significant gap in the literature regarding sex/gender differences in the neurobiological mechanisms driving the multi-dimensionality of addiction and their implications to impulsivity.

Summary

Of the 34 reviewed papers, the orbitofrontal cortex/ventromedial prefrontal cortex (OFC/vmPFC) was the most frequently reported brain region to evidence a sex/gender difference during fMRI tasks probing Approach Behavior and Negative Emotionality. This finding suggests potential sex/gender-specific patterns of subjective valuation in substance misuse, driven by OFC/vmPFC dysregulation.

Altered structural connectivity and functional brain dynamics in individuals with heavy alcohol use

Heavy alcohol use and its associated conditions, such as alcohol use disorder (AUD), impact millions of individuals worldwide. While our understanding of the neurobiological correlates of AUD has evolved substantially, we still lack models incorporating whole-brain neuroanatomical, functional, and pharmacological information under one framework. Here, we utilize diffusion and functional magnetic resonance imaging to investigate alterations to brain dynamics in N = 130 individuals with a high amount of current alcohol use. We compared these alcohol using individuals to N = 308 individuals with minimal use of any substances. We find that individuals with heavy alcohol use had less dynamic and complex brain activity, and through leveraging network control theory, had increased control energy to complete transitions between activation states. Further, using separately acquired positron emission tomography (PET) data, we deploy an in silico evaluation demonstrating that decreased D2 receptor levels, as found previously in individuals with AUD, may relate to our observed findings. This work demonstrates that whole-brain, multimodal imaging information can be combined under a network control framework to identify and evaluate neurobiological correlates and mechanisms of AUD.

Unraveling Neural Complexity: Exploring Brain Entropy to Yield Mechanistic Insight in Neuromodulation Therapies for Tobacco Use Disorder

Neuromodulation therapies, such as repetitive transcranial magnetic stimulation (rTMS), have shown promise as treatments for tobacco use disorder (TUD). However, the underlying mechanisms of these therapies remain unclear, which may hamper optimization and personalization efforts. In this study, we investigated alteration of brain entropy as a potential mechanism underlying the neural effects of noninvasive brain stimulation by rTMS in people with TUD. We employed sample entropy (SampEn) to quantify the complexity and predictability of brain activity measured using resting-state fMRI data. Our study design included a randomized single-blind study with 42 participants who underwent 2 data collection sessions. During each session, participants received high-frequency (10Hz) stimulation to the dorsolateral prefrontal cortex (dlPFC) or a control region (visual cortex), and resting-state fMRI scans were acquired before and after rTMS. Our findings revealed that individuals who smoke exhibited higher baseline SampEn throughout the brain as compared to previously-published SampEn measurements in control participants. Furthermore, high-frequency rTMS to the dlPFC but not the control region reduced SampEn in the insula and dlPFC, regions implicated in TUD, and also reduced self-reported cigarette craving. These results suggest that brain entropy may serve as a potential biomarker for effects of rTMS, and provide insight into the neural mechanisms underlying rTMS effects on smoking cessation. Our study contributes to the growing understanding of brain-based interventions for TUD by highlighting the relevance of brain entropy in characterizing neural activity patterns associated with smoking. The observed reductions in entropy following dlPFC-targeted rTMS suggest a potential mechanism for the therapeutic effects of this intervention. These findings support the use of neuroimaging techniques to investigate the use of neuromodulation therapies for TUD.

Distinct SAP102 and PSD-95 nano-organization defines multiple types of synaptic scaffold protein domains at single synapses

The MAGUK family of scaffold proteins plays a central role in maintaining and modulating synaptic signaling, providing a framework to retain and position receptors, signaling molecules, and other synaptic components. Of these scaffold proteins, SAP102 and PSD-95 are essential for synaptic function at distinct developmental timepoints and perform overlapping as well as unique roles. While their similar structures allow for common binding partners, SAP102 is expressed earlier in synapse development and is required for synaptogenesis, whereas PSD-95 expression peaks later in development and is associated with synapse maturation. PSD-95 and other key synaptic proteins organize into subsynaptic nanodomains that have a significant impact on synaptic transmission, but the nanoscale organization of SAP102 is unknown. How SAP102 is organized within the synapse, and how it relates spatially to PSD-95 on a nanometer scale, could impact how SAP102 clusters synaptic proteins and underlie its ability to perform its unique functions. Here we used DNA-PAINT super-resolution microscopy to measure SAP102 nano-organization and its spatial relationship to PSD-95 at individual synapses. We found that like PSD-95, SAP102 accumulates in high-density subsynaptic nanoclusters. However, SAP102 nanoclusters were smaller and denser than PSD-95 nanoclusters across development. Additionally, only a subset of SAP102 nanoclusters co-organized with PSD-95, revealing that within individual synapses there are nanodomains that contain either one or both proteins. This organization into both shared and distinct subsynaptic nanodomains may underlie the ability of SAP102 and PSD-95 to perform both common and unique synaptic functions.

Task-induced changes in brain entropy

Entropy indicates irregularity of a dynamic system with higher entropy indicating higher irregularity and more transit states. In the human brain, regional entropy has been increasingly assessed using resting state fMRI. Response of regional entropy to task has been scarcely studied. The purpose of this study is to characterize task-induced regional brain entropy (BEN) alterations using the large Human Connectome Project (HCP) data. To control the potential modulation by the block-design, BEN of task-fMRI was calculated from the fMRI images acquired during the task conditions only and then compared to BEN of rsfMRI. Compared to resting state, task-performance unanimously induced BEN reduction in the peripheral cortical area including both the task activated regions and task non-specific regions such as the task negative area and BEN increase in the centric part of the sensorimotor and perception networks. Task control condition showed large residual task effects. After controlling the task non-specific effects using the control BEN vs task BEN comparison, regional BEN showed task specific effects in target regions.

Lower resting brain entropy is associated with stronger task activation and deactivation

Brain entropy (BEN) calculated from resting state fMRI has been the subject of increasing research interest in recent years. Previous studies have shown the correlations between rest BEN and neurocognition and task performance, but how this relates to task-evoked brain activations and deactivations remains unknown. The purpose of this study is to address this open question using large data (n = 862). Voxel wise correlations were calculated between rest BEN and task activations/deactivations of five different tasks. For most of the assessed tasks, lower rest BEN was found to be associated with stronger activations (negative correlations) and stronger deactivations (positive correlations) only in brain regions activated or deactivated by the tasks. Higher workload evoked spatially more extended negative correlations between rest BEN and task activations. These results not only confirm that resting brain activity can predict brain activity during task performance but also for the first time show that resting brain activity may facilitate both task activations and deactivations. In addition, the results provide a clue to understanding the individual differences of task performance and brain activations.

Brain Entropy is Associated with Divergent Thinking

Creativity is the ability to generate original and useful products, and it is considered central to the progression of human civilization. As a noninherited emerging process, creativity may stem from temporally dynamic brain activity, which, however, has not been well studied. The purpose of this study was to measure brain dynamics using entropy and to examine the associations between brain entropy (BEN) and divergent thinking in a large healthy sample. The results showed that divergent thinking was consistently positively correlated with regional BEN in the left dorsal anterior cingulate cortex/pre-supplementary motor area and left dorsolateral prefrontal cortex, suggesting that creativity is closely related to the functional dynamics of the control networks involved in cognitive flexibility and inhibitory control. Importantly, our main results were cross-validated in two independent cohorts from two different cultures. Additionally, three dimensions of divergent thinking (fluency, flexibility, and originality) were positively correlated with regional BEN in the left inferior frontal gyrus and left middle temporal gyrus, suggesting that more highly creative individuals possess more flexible semantic associative networks. Taken together, our findings provide the first evidence of the associations of regional BEN with individual variations in divergent thinking and show that BEN is sensitive to detecting variations in important cognitive abilities in healthy subjects.

The neurocognitive correlates of brain entropy estimated by resting state fMRI

Resting state brain activity consumes most of brain energy, likely creating and maintaining a reserve of general brain functionality. The latent reserve if it exists may be reflected by the profound long-range fluctuations of resting brain activity. The long-range temporal coherence (LRTC) can be characterized by resting state fMRI (rsfMRI)-based brain entropy (BEN) mapping. While BEN mapping results have shown sensitivity to neuromodulations or disease conditions, the underlying neuromechanisms especially the associations of BEN or LRTC to neurocognition still remain unclear. To address this standing question and to test a novel hypothesis that resting BEN reflects a latent functional reserve through the link to general functionality, we mapped resting BEN of 862 young adults and comprehensively examined its associations to neurocognitions using data from the Human Connectome Project (HCP). Our results unanimously highlighted two brain circuits: the default mode network (DMN) and executive control network (ECN) through their negative associations of BEN to general functionality, which is independent of age and sex. While BEN in DMN/ECN increases with age, it decreases with education years. These results demonstrated the neurocognitive correlates of resting BEN in DMN/ECN and suggest resting BEN in DMN/ECN as a potential proxy of the latent functional reserve that facilitates general brain functionality and may be enhanced by education.

Acute Alcohol Intake Produces Widespread Decreases in Cortical Resting Signal Variability in Healthy Social Drinkers

BACKGROUND

Acute alcohol intoxication has wide-ranging neurobehavioral effects on psychomotor, attentional, inhibitory, and memory-related cognitive processes. These effects are mirrored in disruption of neural metabolism, functional activation, and functional network coherence. Metrics of intraregional neural dynamics such as regional signal variability (RSV) and brain entropy (BEN) may capture unique aspects of neural functional capacity in healthy and clinical populations; however, alcohol's influence on these metrics is unclear. The present study aimed to elucidate the influence of acute alcohol intoxication on RSV and to clarify these effects with subsequent BEN analyses.

METHODS

26 healthy adults between 25 and 45 years of age (65.4% women) participated in 2 counterbalanced sessions. In one, participants consumed a beverage containing alcohol sufficient to produce a breath alcohol concentration of 0.08 g/dl. In the other, they consumed a placebo beverage. Approximately 35 minutes after beverage consumption, participants completed a 9-minute resting-state fMRI scan. Whole-brain, voxel-wise standard deviation was used to assess RSV, which was compared between sessions. Within clusters displaying alterations in RSV, sample entropy was calculated to assess BEN.

RESULTS

Compared to the placebo, alcohol intake resulted in widespread reductions in RSV in the bilateral middle frontal, right inferior frontal, right superior frontal, bilateral posterior cingulate, bilateral middle temporal, right supramarginal gyri, and bilateral inferior parietal lobule. Within these clusters, significant reductions in BEN were found in the bilateral middle frontal and right superior frontal gyri. No effects were noted in subcortical or cerebellar areas.

CONCLUSIONS

Findings indicate that alcohol intake produces diffuse reductions in RSV among structures associated with attentional processes. Within these structures, signal complexity was also reduced in a subset of frontal regions. Neurobehavioral effects of acute alcohol consumption may be partially driven by disruption of intraregional neural dynamics among regions involved in higher-order cognitive and attentional processes.

Associations of brain entropy (BEN) to cerebral blood flow and fractional amplitude of low-frequency fluctuations in the resting brain

Entropy is a fundamental trait of human brain. Using fMRI-based brain entropy (BEN) mapping, interesting findings have been increasingly revealed in normal brain and neuropsychiatric disorders. As BEN is still relatively new, an often-raised question is how much new information can this measure tell about the brain compared to other more established brain activity measures. The study aimed to address that question by examining the relationship between BEN and cerebral blood flow (CBF) and the fractional amplitude of low-frequency fluctuations (fALFF), two widely used resting state brain state measures. fMRI data acquired from a large cohort of normal subjects were used to calculate the three metrics; inter-modality associations were assessed at each voxel through the Pearson correlation analysis. A moderate to high positive BEN-CBF and BEN-fALFF correlations were found in orbito-frontal cortex (OFC) and posterior inferior temporal cortex (ITC); Strong negative BEN-fALFF correlations were found in visual cortex (VC), anterior ITC, striatum, motor network, precuneus, and lateral parietal cortex. Positive CBF-fALFF correlations were found in medial OFC (MOFC), medial prefrontal cortex (MPFC), left angular gyrus, and left precuneus. Significant gender effects were observed for all three metrics and their correlations. Our data clearly demonstrated that BEN provides unique information that cannot be revealed by CBF and fALFF.

Altered Brain Entropy as a predictor of antidepressant response in major depressive disorder

OBJECTIVE

To explore the alterations and value of brain entropy (BEN) in major depressive disorder (MDD).

METHODS

85 MDD patients and 45 matched normal controls were recruited. MDD was diagnosed based on Diagnostic and Statistical Manual of Mental Disorders, 4th ed (DSM-IV). Symptoms of depression were assessed using the Hamilton depression scale-24 (HAMD-24) at baseline and follow-up (after 8-week treatment). All subjects underwent functional magnetic resonance imaging (fMRI) scans at baseline, and 30 MDD patients completed scans at 8th week. Whole brain BEN maps at each session was calculated using the BEN mapping toolbox.

RESULTS

The 8-week antidepressant treatment improved symptoms for all MDD patients. As compared to normal controls, MDD showed reduced BEN in medial orbitofrontal cortex (MOFC)/subgenual cingulate cortex (sgACC), but increased BEN in motor cortex (MC). In MDD patients, higher baseline BEN in MOFC/sgACC and lower baseline BEN in temporal cortex (TC) were associated with higher baseline HAMD scores; higher baseline BEN in MOFC/sgACC and hippocampus were associated with greater reduction of HAMD scores after 8-week medication; greater reduction of HAMD scores after 8-week medication was correlated with greater BEN reduction in MOFC/sgACC but were correlated with less BEN reduction in MC, TC, fusiform gyrus (FG) and visual cortex (VC).

CONCLUSION

The results highlighted MOFC/sgACC BEN as a potential marker for the prediction of MDD diagnosis and treatment effect. MDD might have increased MOFC/sgACC BEN but reduced BEN in visual and sensory-motor circuits corresponding to the imbalanced emotional and sensory-motor information processing. Reversing this unbalanced BEN would improve disease conditions in MDD.

Resting-state brain entropy in right temporal lobe epilepsy and its relationship with alertness

BACKGROUND

To date, no functional MRI (fMRI) studies have focused on brain entropy in right temporal lobe epilepsy (rTLE) patients. Here, we characterized brain entropy (BEN) alterations in patients with rTLE using resting-state functional MRI(rs-fMRI) and explored the relationship between BEN and alertness.

METHOD

Thirty-one rTLE patients and 33 controls underwent MRI scanning to investigate differences in BEN and resting-state functional connectivity (rs-FC) in regions of interest (ROIs) between patients and controls. Correlation analyses were performed to examine relationships between the BEN of each ROI and alertness reaction times (RTs) in rTLE patients.

RESULTS

Compared with controls, the BEN of rTLE patients was significantly increased in the right middle temporal gyrus, inferior temporal gyrus, and other regions of the left hemisphere and significantly decreased in the right middle frontal gyrus and left supplementary motor area (p < .05). The rs-FCs between the ROIs (at p < .01, with the left superior parietal lobule and right precentral gyrus defined as ROI1 and ROI2, respectively) and the whole brain showed an increasing trend in rTLE patients. In addition, the BEN of ROI2 was associated with the intrinsic alertness and phasic alertness RTs of patients with rTLE.

CONCLUSIONS

Our findings suggest that BEN is altered in patients with rTLE and that decreased BEN in the right precentral gyrus is positively related to intrinsic and phasic alertness; the abnormal FC in the brain regions with altered entropy suggests a reconstruction of brain functional connectivity. These findings suggest that BEN mapping may provide a useful tool for probing brain mechanisms related to TLE.

Reduced brain entropy by repetitive transcranial magnetic stimulation on the left dorsolateral prefrontal cortex in healthy young adults

Entropy indicates system irregularity and the capacity for information processing. Recent research has identified interesting voxel-wise entropy distribution patterns in normal brain and its changes due to aging and brain disorders. A question of great scientific and clinical importance is whether brain entropy (BEN) can be modulated using non-invasive neuromodulations. The purpose of this study was to address this open question using high-frequency repetitive transcranial magnetic stimulation (rTMS). BEN was calculated from resting state fMRI at each voxel acquired before and after applying 20 Hz rTMS or SHAM (control) stimulation. As compared to SHAM, 20 Hz rTMS reduced BEN in medial orbito-frontal cortex and subgenial anterior cingulate cortex (MOFC/sgACC), suggesting a reduced information processing therein, probably as a result of the enhanced top-down regulation by the left DLPFC rTMS. No significant changes were observed to the functional connectivity (FC) between the left DLPFC (the target site) to the rest of the brain, suggesting that rTMS may not affect FC though it might use FC to transfer its effects or the ad hoc information. Our data proved that rTMS can modulate BEN and BEN can be used to monitor rTMS effects.

Sex differences in tobacco smokers: Executive control network and frontostriatal connectivity

BACKGROUND

Women experience greater difficulty quitting smoking than men, which may be explained by sex differences in brain circuitry underlying cognitive control. Prior work has linked reduced interhemispheric executive control network (ECN) coupling with poor executive function, shorter time to relapse, and greater substance use. Lower structural connectivity between a key ECN hub, the dorsolateral prefrontal cortex (DLPFC), and the dorsal striatum (DS) also contributes to less efficient cognitive control recruitment, and reduced intrahemispheric connectivity between these regions has been associated with smoking relapse. Therefore, sex differences were probed by evaluating interhemispheric ECN and intrahemispheric DLPFC-DS connectivity. To assess the potential sex by nicotine interaction, a pilot sample of non-smokers was evaluated following acute nicotine and placebo administration.

METHODS

Thirty-five smokers (19 women) completed one resting state functional magnetic resonance imaging scan. Seventeen non-smokers (8 women) were scanned twice using a repeated measures design where they received 2 and 0 mg nicotine.

RESULTS

In smokers, women had less interhemispheric ECN and DLPFC-DS coupling than men. In non-smokers, there was a drug x sex interaction where women, relative to men, had weaker ECN coupling following nicotine but not placebo administration.

CONCLUSIONS

The current work indicates that nicotine-dependent women, versus men, have weaker connectivity in brain networks critically implicated in cognitive control. How these connectivity differences contribute to the behavioral aspects of smoking requires more testing. However, building on the literature, it is likely these deficits in functional connectivity contribute to the lower abstinence rates noted in women relative to men.

Disrupted Brain Entropy And Functional Connectivity Patterns Of Thalamic Subregions In Major Depressive Disorder

PURPOSE

Entropy analysis of resting-state functional magnetic resonance imaging (R-fMRI) has recently been adopted to characterize brain temporal dynamics in some neuropsychological or psychiatric diseases. Thalamus-related dysfunction might be a potential trait marker of major depressive disorder (MDD), but the abnormal changes in the thalamus based on R-fMRI are still unclear from the perspective of brain temporal dynamics. The aim of this study was to identify local entropy changes and subregional connectivity patterns of the thalamus in MDD patients.

PATIENTS AND METHODS

We measured the sample entropy of the R-fMRI data from 46 MDD patients and 32 matched healthy controls. We employed the Louvain method for the module detection algorithm to automatically identify a functional parcellation of the thalamus and then examined the whole-brain subregional connectivity patterns.

RESULTS

The results indicated that the MDD patients had decreased entropy in the bilateral thalami compared with healthy controls. Increased functional connectivity between the thalamic subregions and the medial part of the superior frontal gyrus (mSFG) was found in MDD patients.

CONCLUSION

This study showed new evidence about sample entropy changes in MDD patients. The functional connectivity alterations that were widely distributed across almost all the thalamic subregions with the mSFG in MDD suggest a general involvement independent of the location and function of the subregions.

Interactions of BDNF Val66Met Polymorphism and Menstrual Pain on Brain Complexity

The irregularity and uncertainty of neurophysiologic signals across different time scales can be regarded as neural complexity, which is related to the adaptability of the nervous system and the information processing between neurons. We recently reported general loss of brain complexity, as measured by multiscale sample entropy (MSE), at pain-related regions in females with primary dysmenorrhea (PDM). However, it is unclear whether this loss of brain complexity is associated with inter-subject genetic variations. Brain-derived neurotrophic factor (BDNF) is a widely expressed neurotrophin in the brain and is crucial to neural plasticity. The BDNF Val66Met single-nucleotide polymorphism (SNP) is associated with mood, stress, and pain conditions. Therefore, we aimed to examine the interactions of BDNF Val66Met polymorphism and long-term menstrual pain experience on brain complexity. We genotyped BDNF Val66Met SNP in 80 PDM females (20 Val/Val, 31 Val/Met, 29 Met/Met) and 76 healthy female controls (25 Val/Val, 36 Val/Met, 15 Met/Met). MSE analysis was applied to neural source activity estimated from resting-state magnetoencephalography (MEG) signals during pain-free state. We found that brain complexity alterations were associated with the interactions of BDNF Val66Met polymorphism and menstrual pain experience. In healthy female controls, Met carriers (Val/Met and Met/Met) demonstrated lower brain complexity than Val/Val homozygotes in extensive brain regions, suggesting a possible protective role of Val/Val homozygosity in brain complexity. However, after experiencing long-term menstrual pain, the complexity differences between different genotypes in healthy controls were greatly diminished in PDM females, especially in the limbic system, including the hippocampus and amygdala. Our results suggest that pain experience preponderantly affects the effect of BDNF Val66Met polymorphism on brain complexity. The results of the present study also highlight the potential utilization of resting-state brain complexity for the development of new therapeutic strategies in patients with chronic pain.

Smoking Cessation With 20 Hz Repetitive Transcranial Magnetic Stimulation (rTMS) Applied to Two Brain Regions: A Pilot Study

Chronic smoking impairs brain functions in the prefrontal cortex and the projecting meso-cortical limbic system. The purpose of this pilot study is to examine whether modulating the frontal brain activity using high-frequency repetitive transcranial magnetic stimulation (rTMS) can improve smoking cessation and to explore the changing pattern of the brain activity after treatment. Fourteen treatment-seeking smokers were offered a program involving 10 days of rTMS treatment with a follow-up for another 25 days. A frequency of 20 Hz rTMS was sequentially applied on the left dorso-lateral prefrontal cortex (DLPFC) and the superior medial frontal cortex (SMFC). The carbon monoxide (CO) level, withdrawal, craving scales, and neuroimaging data were collected. Ten smokers completed the entire treatment program, and 90% of them did not smoke during the 25-day follow-up time. A significant smoking craving reduction and resting brain activity reduction measured by the cerebral blood flow (CBF) and brain entropy (BEN) were observed after 10 days of 20 Hz rTMS treatments compared to the baseline. Although limited by sample size, these pilot findings definitely showed a high potential of multiple-target high-frequency rTMS in smoking cessation and the utility of fMRI for objectively assessing the treatment effects.

Occupational functional plasticity revealed by brain entropy: A resting-state fMRI study of seafarers

Recently, functional magnetic resonance imaging (fMRI) has been increasingly used to assess brain function. Brain entropy is an effective model for evaluating the alteration of brain complexity. Specifically, the sample entropy (SampEn) provides a feasible solution for revealing the brain's complexity. Occupation is one key factor affecting the brain's activity, but the neuropsychological mechanisms are still unclear. Thus, in this article, based on fMRI and a brain entropy model, we explored the functional complexity changes engendered by occupation factors, taking the seafarer as an example. The whole-brain entropy values of two groups (i.e., the seafarers and the nonseafarers) were first calculated by SampEn and followed by a two-sample t test with AlphaSim correction (p < .05). We found that the entropy of the orbital-frontal gyrus (OFG) and superior temporal gyrus (STG) in the seafarers was significantly higher than that of the nonseafarers. In addition, the entropy of the cerebellum in the seafarers was lower than that of the nonseafarers. We conclude that (1) the lower entropy in the cerebellum implies that the seafarers' cerebellum activity had strong regularity and consistency, suggesting that the seafarer's cerebellum was possibly more specialized by the long-term career training; (2) the higher entropy in the OFG and STG possibly demonstrated that the seafarers had a relatively decreased capability for emotion control and auditory information processing. The above results imply that the seafarer occupation indeed impacted the brain's complexity, and also provided new neuropsychological evidence of functional plasticity related to one's career.

Caffeine Caused a Widespread Increase of Resting Brain Entropy

Entropy is an important trait of brain function and high entropy indicates high information processing capacity. We recently demonstrated that brain entropy (BEN) is stable across time and differs between controls and patients with various brain disorders. The purpose of this study was to examine whether BEN is sensitive to pharmaceutical modulations with caffeine. Both cerebral blood flow (CBF) and resting fMRI were collected from sixty caffeine-naïve healthy subjects before and after taking a 200 mg caffeine pill. Our data showed that caffeine reduced CBF in the whole brain but increased BEN across the cerebral cortex with the highest increase in lateral prefrontal cortex, the default mode network (DMN), visual cortex, and motor network, consistent with the beneficial effects of caffeine (such as vigilance and attention) on these areas. BEN increase was correlated to CBF reduction only in several regions (-0.5 < r < -0.4), indicating a neuronal nature for most of the observed BEN alterations. In summary, we showed the first evidence of BEN alterations due to caffeine ingestion, suggesting BEN as a biomarker sensitive to pharmaceutical brain function modulations.

A hypo-status in drug-dependent brain revealed by multi-modal MRI

Drug addiction is a chronic brain disorder with no proven effective cure. Assessing both structural and functional brain alterations by using multi-modal, rather than purely unimodal imaging techniques, may provide a more comprehensive understanding of the brain mechanisms underlying addiction, which in turn may facilitate future treatment strategies. However, this type of research remains scarce in the literature. We acquired multi-modal magnetic resonance imaging from 20 cocaine-addicted individuals and 19 age-matched controls. Compared with controls, cocaine addicts showed a multi-modal hypo-status with (1) decreased brain tissue volume in the medial and lateral orbitofrontal cortex (OFC); (2) hypo-perfusion in the prefrontal cortex, anterior cingulate cortex, insula, right temporal cortex and dorsolateral prefrontal cortex and (3) reduced irregularity of resting state activity in the OFC and limbic areas, as well as the cingulate, visual and parietal cortices. In the cocaine-addicted brain, larger tissue volume in the medial OFC, anterior cingulate cortex and ventral striatum and smaller insular tissue volume were associated with higher cocaine dependence levels. Decreased perfusion in the amygdala and insula was also correlated with higher cocaine dependence levels. Tissue volume, perfusion, and brain entropy in the insula and prefrontal cortex, all showed a trend of negative correlation with drug craving scores. The three modalities showed voxel-wise correlation in various brain regions, and combining them improved patient versus control brain classification accuracy. These results, for the first time, demonstrate a comprehensive cocaine-dependence and craving-related hypo-status regarding the tissue volume, perfusion and resting brain irregularity in the cocaine-addicted brain.