Connectome-based Brain Marker Moderates the Relationship between Childhood Adversity and Transdiagnostic Psychopathology during Early Adolescence.

Importance: Identifying brain-based markers of resiliency that reliably predict who is and is not at elevated risk for developing psychopathology among children who experience adverse childhood experiences (ACEs) is important for improving our mechanistic understanding of these etiological links between child adversity and psychopathology and guiding precision medicine and prevention efforts for reducing psychiatric impact of ACEs. Objective: To examine associations between ACEs and transdiagnostic psychopathology during the transition from preadolescence to early adolescence and test whether these associations are moderated by a hypothesized resilience factor, a previously identified connectome variate (CV) that is associated with higher cognitive function and lower psychopathology. Design Setting and Participants: This study was conducted in a longitudinal design based on multicenter data from a community cohort of U.S. youth aged of 9-11 at baseline, who participated in the Adolescent Brain Cognitive Development (ABCD) study (N=7,382 at baseline and 6,813 at 2-year follow-up). Linear regression models and moderation analyses were used to characterize concurrent and prospective associations between lifetime ACEs and number of DSM-5 psychiatric disorders (indexing transdiagnostic psychopathology) and to determine if individual variations in these associations were moderated by the CV derived from resting-state fMRI at baseline. Main Outcomes and Measures: Cumulative number of current DSM-5 psychiatric disorders assessed using the computerized self-admin version Kiddie Schedule for Affective Disorders and Schizophrenia (KSADS-5) and lifetime ACEs assessed from child and parent reports at baseline (9-10 years) and 2-year-follow-up (11-12 years). Results: ACE total scores correlated positively with the cumulative number of current DSM-5 psychiatric disorders at both baseline (r =.258, p < .001) and 2-year follow-up (r =.257, p < .001). The baseline CV score moderated the ACE-disorder associations at baseline (B = -0.021, p < .001) and at 2-year follow-up (B = -0.018, p = .008), as well as the association between the changes in ACE and in the number of disorders from baseline to year 2 (B = -0.012, p = .045). Post-hoc analyses further showed that the moderation effect of CV on ACE-psychopathology associations was specific to the threat-related ACEs and to female youth. Conclusions and Relevance: These findings provide preliminary evidence for a connectome-based resiliency marker and suggest that functional connectivity strength in a broad system including frontal-parietal cortices and subcortical nuclei relevant to cognitive control may protect preadolescents who have experienced lifetime ACEs--especially females and those experiencing threat-related ACEs--from developing transdiagnostic psychopathology.

The resting-state brain activity signatures for addictive disorders.

BACKGROUND: Addiction is a chronic and relapsing brain disorder. Despite numerous neuroimaging and neurophysiological studies on individuals with substance use disorder (SUD) or behavioral addiction (BEA), currently a clear neural activity signature for the addicted brain is lacking. METHODS: We first performed systemic coordinate-based meta-analysis and partial least-squares regression to identify shared or distinct brain regions across multiple addictive disorders, with abnormal resting-state activity in SUD and BEA based on 46 studies (55 contrasts), including regional homogeneity (ReHo) and low-frequency fluctuation amplitude (ALFF) or fractional ALFF. We then combined Neurosynth, postmortem gene expression, and receptor/transporter distribution data to uncover the potential molecular mechanisms underlying these neural activity signatures. FINDINGS: The overall comparison between addiction cohorts and healthy subjects indicated significantly increased ReHo and ALFF in the right striatum (putamen) and bilateral supplementary motor area, as well as decreased ReHo and ALFF in the bilateral anterior cingulate cortex and ventral medial prefrontal cortex, in the addiction group. On the other hand, neural activity in cingulate cortex, ventral medial prefrontal cortex, and orbitofrontal cortex differed between SUD and BEA subjects. Using molecular analyses, the altered resting activity recapitulated the spatial distribution of dopaminergic, GABAergic, and acetylcholine system in SUD, while this also includes the serotonergic system in BEA. CONCLUSIONS: These results indicate both common and distinctive neural substrates underlying SUD and BEA, which validates and supports targeted neuromodulation against addiction. FUNDING: This work was supported by the National Natural Science Foundation of China and Intramural Research Program of the National Institute on Drug Abuse, National Institutes of Health.

The Association between Default-mode Network Functional Connectivity and Childhood Trauma on the Symptom Load in Male Adults with Methamphetamine Use Disorder.

Objective: : The relationship between adverse childhood experiences and methamphetamine use disorder (MUD) has been shown in previous studies; nevertheless, the underlying neural mechanisms remain elusive. Childhood trauma is associated with aberrant functional connectivity (FC) within the default-mode network (DMN). Furthermore, within the DMN, FC may contribute to impaired self-awareness in addiction, while cross-network FC is critical for relapse. We aimed to investigate whether childhood trauma was associated with DMN-related resting-state FC among healthy controls and patients with MUD and to examine whether DMN-related FC affected the effect of childhood trauma on the symptom load of MUD diagnosis. Methods: : Twenty-seven male patients with MUD and 27 male healthy controls were enrolled and completed the Childhood Trauma Questionnaire. DMN-related resting-state FC was examined using functional magnetic resonance imaging. Results: : There were 47.1% healthy controls and 66.7% MUD patients in this study with adverse childhood experiences. Negative correlations between adverse childhood experiences and within-DMN FC were observed in both healthy controls and MUD patients, while within-DMN FC was significantly altered in MUD patients. The detrimental effects of adverse childhood experiences on MUD patients may be attenuated through DMN-executive control networks (ECN) FC. Conclusion: : Adverse childhood experiences were negatively associated with within-DMN FC in MUD patients and healthy controls. However, DMN-ECN FC may attenuate the effects of childhood trauma on symptoms load of MUD.

Brain Functional Connectome Defines a Transdiagnostic Dimension Shared by Cognitive Function and Psychopathology in Preadolescents.

BACKGROUND: Cognitive function and general psychopathology are two important classes of human behavior dimensions that are individually related to mental disorders across diagnostic categories. However, whether these two transdiagnostic dimensions are linked to common or distinct brain networks that convey resilience or risk for the development of psychiatric disorders remains unclear. METHODS: The current study is a longitudinal investigation with 11,875 youths from the Adolescent Brain Cognitive Development (ABCD) Study at ages 9 to 10 years at the onset of the study. A machine learning approach based on canonical correlation analysis was used to identify latent dimensional associations of the resting-state functional connectome with multidomain behavioral assessments including cognitive functions and psychopathological measures. For the latent resting-state functional connectivity factor showing a robust behavioral association, its ability to predict psychiatric disorders was assessed using 2-year follow-up data, and its genetic association was evaluated using twin data from the same cohort. RESULTS: A latent functional connectome pattern was identified that showed a strong and generalizable association with the multidomain behavioral assessments (5-fold cross-validation: ρ = 0.68-0.73 for the training set [n = 5096]; ρ = 0.56-0.58 for the test set [n = 1476]). This functional connectome pattern was highly heritable (h2 = 74.42%, 95% CI: 56.76%-85.42%), exhibited a dose-response relationship with the cumulative number of psychiatric disorders assessed concurrently and at 2 years post-magnetic resonance imaging scan, and predicted the transition of diagnosis across disorders over the 2-year follow-up period. CONCLUSIONS: These findings provide preliminary evidence for a transdiagnostic connectome-based measure that underlies individual differences in the development of psychiatric disorders during early adolescence.

Disrupted Dynamic Interactions Between Large-Scale Brain Networks in Cocaine Users Are Associated With Dependence Severity.

BACKGROUND: Substance use disorder is conceptualized as a neuropsychiatric disease with multifaceted phenotypic manifestations including disrupted interactions between brain networks. While the current understanding of brain network interactions is mostly based on static functional connectivity, accumulating evidence suggests that temporal dynamics of these network interactions may better reflect brain function and disease-related dysfunction. We thus investigated brain dynamics in cocaine use disorder and assessed their relationship with cocaine dependence severity. METHODS: Using a time frame analytical approach on resting-state functional magnetic resonance imaging data of 54 cocaine users and 54 age- and sex-matched healthy control participants, we identified temporally recurring brain network configuration patterns, termed brain states. With Menon's triple network model as a guide, we characterized these state dynamics by quantifying their occurrence rate and transition probability. Group differences in the state dynamics and their association with cocaine dependence were assessed. RESULTS: Three recurrent brain states with spatial patterns resembling the default mode, salience, and executive control networks were identified. Compared with healthy control subjects, cocaine users showed a higher default mode state occurrence rate and higher probability of transitioning from the salience state to the default mode state, with the former being attributed to the latter. A composite state transition probability negatively correlated with cocaine dependence severity. CONCLUSIONS: Our results provide novel evidence supporting the triple network model. While confirming hyperactivity of default mode network in cocaine users, our findings indicate the failure of salience network in toggling between default mode and executive control networks in cocaine use disorder.

Low frequency repetitive transcranial magnetic stimulation to the right dorsolateral prefrontal cortex engages thalamus, striatum, and the default mode network.

The positive treatment outcomes of low frequency (LF) repetitive transcranial magnetic stimulation (rTMS) when applied over the right dorsolateral prefrontal cortex (DLPFC) in treatment-refractory depression has been verified. However, the mechanism of action behind these results have not been well-explored. In this work we used simultaneous functional magnetic resonance imaging (fMRI) during TMS to explore the effect of LF rTMS on brain activity when applied to the right [RDLPFC1 (MNI: 50, 30, 36)] and left DLPFC sites [LDLPFC1 (MNI: -50, 30, 36), LDLPFC2 (MNI: -41, 16, 54)]. Seventeen healthy adult volunteers participated in this study. To identify brain areas affected by rTMS, an independent component analysis and a general linear model were used. Our results showed an important laterality effect when contrasting rTMS over the left and right sites. Specifically, LF rTMS increased brain activity at the striatum, thalamus, and areas of the default mode network when applied to the right, but not to the contralateral left DLPFC. In contrast, no site differences were observed when evaluating the effect of LF rTMS over the two left sites. These findings demonstrate that LF rTMS to the right DLPFC was able to stimulate the cortico-striato-thalamo-cortical pathway, which is dysregulated in patients with major depressive disorder; therefore, possibly providing some neurobiological justification for the successful outcomes found thus far for LF rTMS in the treatment of depression.

High-Frequency Transcranial Magnetic Stimulation Combined With Functional Magnetic Resonance Imaging Reveals Distinct Activation Patterns Associated With Different Dorsolateral Prefrontal Cortex Stimulation Sites.

OBJECTIVES: Transcranial magnetic stimulation (TMS) has been extensively used for the treatment of depression, obsessive-compulsive disorder, and certain neurologic disorders. Despite having promising treatment efficacy, the fundamental neural mechanisms of TMS remain understudied. MATERIALS AND METHODS: In this study, 15 healthy adult participants received simultaneous TMS and functional magnetic resonance imaging to map the modulatory effect of TMS when it was applied over three different sites in the dorsolateral prefrontal cortex. Independent component analysis (ICA) was used to identify the networks affected by TMS when applied over the different sites. The standard general linear model (GLM) analysis was used for comparison. RESULTS: ICA showed that TMS affected the stimulation sites as well as remote brain areas, some areas/networks common across all TMS sites, and other areas/networks specific to each TMS site. In particular, TMS site and laterality differences were observed at the left executive control network. In addition, laterality differences also were observed at the dorsal anterior cingulate cortex and dorsolateral/dorsomedial prefrontal cortex. In contrast with the ICA findings, the GLM-based results mainly showed activation of auditory cortices regardless of the TMS sites. CONCLUSIONS: Our findings support the notion that TMS could act through a top-down mechanism, indirectly modulating deep subcortical nodes by directly stimulating cortical regions. CLINICAL TRIAL REGISTRATION: The Clinicaltrials.gov registration number for the study is NCT03394066.

Cox Regression Based Modeling of Functional Connectivity and Treatment Outcome for Relapse Prediction and Disease Subtyping in Substance Use Disorder.

Functional magnetic resonance imaging (fMRI) has become one of the most widely used noninvasive neuroimaging technique in research of cognitive neurosciences and of neural mechanisms of neuropsychiatric/neurological diseases. A primary goal of fMRI-based neuroimaging studies is to identify biomarkers for brain-behavior relationship and ultimately perform individualized treatment outcome prognosis. However, the concern of inadequate validation and the nature of small sample sizes are associated with fMRI-based neuroimaging studies, both of which hinder the translation from scientific findings to clinical practice. Therefore, the current paper presents a modeling approach to predict time-dependent prognosis with fMRI-based brain metrics and follow-up data. This prediction modeling is a combination of seed-based functional connectivity and voxel-wise Cox regression analysis with built-in nested cross-validation, which has been demonstrated to be able to provide robust and unbiased model performance estimates. Demonstrated with a cohort of treatment-seeking cocaine users from psychosocial treatment programs with 6-month follow-up, our proposed modeling method is capable of identifying brain regions and related functional circuits that are predictive of certain follow-up behavior, which could provide mechanistic understanding of neuropsychiatric/neurological disease and clearly shows neuromodulation implications and can be used for individualized prognosis and treatment protocol design.

Functional connectivity of dorsolateral prefrontal cortex predicts cocaine relapse: implications for neuromodulation treatment.

Relapse is one of the most perplexing problems of addiction. The dorsolateral prefrontal cortex is crucially involved in numerous cognitive and affective processes that are implicated in the phenotypes of both substance use disorders and other neuropsychiatric diseases and has become the principal site to deliver transcranial magnetic stimulation for their treatment. However, the dorsolateral prefrontal cortex is an anatomically large and functionally heterogeneous region, and the specific dorsolateral prefrontal cortex locus and dorsolateral prefrontal cortex-based functional circuits that contribute to drug relapse and/or treatment outcome remain unknown. We systematically investigated the relationship of cocaine relapse with functional circuits from 98 dorsolateral prefrontal cortex regions-of-interest defined by evenly sampling the entire surface of bilateral dorsolateral prefrontal cortex in a cohort of cocaine dependent patients (n = 43, 5 Fr) following a psychosocial treatment intervention. Cox regression models were utilized to predict relapse likelihood based on dorsolateral prefrontal cortex functional connectivity strength. Functional connectivity from only 3 of the 98 dorsolateral prefrontal cortex loci, one in the left and two in the right hemisphere, significantly predicted cocaine relapse with an accuracy of 83.9%, 84.6% and 85.4%, respectively. Combining all three loci significantly improved prediction validity to 87.5%. Protective and risk circuits related to these dorsolateral prefrontal cortex loci were identified that have previously been implicated to support 'bottom up' drive to use drug and 'top down' control over behaviour together with social emotional, learning and memory processing. Three dorsolateral prefrontal cortex-centric circuits were identified that predict relapse to cocaine use with high accuracy. These functionally distinct dorsolateral prefrontal cortex-based circuits provide insights into the multiple roles played by the dorsolateral prefrontal cortex in cognitive and affective functioning that affects treatment outcome. The identified dorsolateral prefrontal cortex loci may serve as potential neuromodulation targets to be tested in subsequent clinical studies for addiction treatment and as clinically relevant biomarkers of its efficacy. Zhai et al. identify three dorsolateral prefrontal cortex (dlPFC)-centric circuits that predict cocaine relapse with high accuracy, providing insights into the multiple roles of the dlPFC in brain functioning that affects treatment outcome and suggesting the dlPFC loci as potential neuromodulation targets for addiction treatment.

Simultaneous Transcranial Magnetic Stimulation and Functional Magnetic Resonance Imaging: Aspects of Technical Implementation.

The simultaneous transcranial magnetic stimulation (TMS) and functional magnetic resonance imaging (fMRI) offers a unique opportunity to non-invasively stimulate brain circuits while simultaneously monitoring changes in brain activity. However, to take advantage of this multimodal technique, some technical issues need to be considered/addressed. In this work, we evaluated technical issues associated with the setup and utilization of this multimodal tool, such as the use of a large single-channel radio frequency (rf) coil, and the artifacts induced by TMS when interleaved with the echo-planar imaging (EPI) sequence. We demonstrated that good image quality can be achieved with this rf coil and that the adoption of axial imaging orientation in conjunction with a safe interval of 100 ms, between the TMS pulse and imaging acquisition, is a suitable combination to eliminate potential image artifacts when using the combined TMS-fMRI technique in 3-T MRI scanners.

Abnormal gray matter volume and resting-state functional connectivity in former heroin-dependent individuals abstinent for multiple years.

Previous studies have suggested that heroin addiction is associated with structural and functional brain abnormalities. However, it is largely unknown whether these characteristics of brain abnormalities would be persistent or restored after long periods of abstinence. Considering the very high rates of relapse, we hypothesized that there may exist some latent neural vulnerabilities in abstinent heroin users. In this study, structural and resting-state functional magnetic resonance imaging data were collected from 30 former heroin-dependent (FHD) subjects who were drug free for more than 3 years and 30 non-addicted control (CN) volunteers. Voxel-based morphometry was used to identify possible gray matter volume differences between the FHD and CN groups. Alterations in resting-state functional connectivity in FHD were examined using brain areas with gray matter deficits as seed regions. Significantly reduced gray matter volume was observed in FHD in an area surrounding the parieto-occipital sulcus, which included the precuneus and cuneus. Functional connectivity analyses revealed that the FHD subjects showed reduced positive correlation within the default mode network and visual network and decreased negative correlation between the default mode network, visual network and task positive network. Moreover, the altered functional connectivity was correlated with self-reported impulsivity scores in the FHD subjects. Our findings suggest that disruption of large-scale brain systems is present in former heroin users even after multi-year abstinence, which could serve as system-level neural underpinnings for behavioral dysfunctions associated with addiction.

Altered superficial amygdala-cortical functional link in resting state after 36 hours of total sleep deprivation.

The superficial amygdala (SFA) is important in human emotion/affective processing via its strong connection with other limbic and cerebral cortex for receptive and expressive emotion processing. Few studies have investigated the functional connectivity changes of the SFA under extreme conditions, such as prolonged sleep loss, although the SFA showed a distinct functional connectivity pattern throughout the brain. In this study, resting-state functional magnetic resonance imaging (rs-fMRI) was employed to investigate the changes of SFA-cortical functional connectivity after 36 hr of total sleep deprivation (TSD). Fourteen healthy male volunteers aged 25.9 ± 2.3 years (range 18-28 years) enrolled in this within-subject crossover study. We found that the right SFA showed increased functional connectivity with the right medial prefrontal cortex (mPFC) and decreased functional connectivity with the right dorsal posterior cingulate cortex (dPCC) in the resting brain after TSD compared with that during rested wakefulness. For the left SFA, decreased connectivity with the right dorsal anterior cingulate cortex (dACC) and right dPCC was found. Further regression analysis indicated that the functional link between mPFC and SFA significantly correlated with the Profile of Mood State scores. Our results suggest that the amygdala cannot be treated as a single unit in human neuroimaging studies and that TSD may alter the functional connectivity pattern of the SFA, which in turn disrupts emotional regulation.

Abnormal resting-state functional connectivity of the nucleus accumbens in multi-year abstinent heroin addicts.

Functional neuroimaging studies suggest that abnormal brain functional connectivity may be the neural underpinning of addiction to illicit drugs and of relapse after successful cessation therapy. Aberrant brain networks have been demonstrated in addicted patients and in newly abstinent addicts. However, it is not known whether abnormal brain connectivity patterns persist after prolonged abstinence. In this cross-sectional study, whole-brain resting-state functional magnetic resonance images (8 min) were collected from 30 heroin-addicted individuals after a long period of abstinence (more than 3 years) and from 30 healthy controls. We first examined the group differences in the resting-state functional connectivity of the nucleus accumbens (NAc), a brain region implicated in relapse-related processes, including craving and reactivity to stress following acute and protracted withdrawal from heroin. We then examined the relation between the duration of abstinence and the altered NAc functional connectivity in the heroin group. We found that, compared with controls, heroin-dependent participants exhibited significantly greater functional connectivity between the right ventromedial prefrontal cortex and the NAc and weaker functional connectivity between the NAc and the left putamen, left precuneus, and supplementary motor area. However, with longer abstinence time, the strength of NAc functional connectivity with the left putamen increased. These results indicate that dysfunction of the NAc functional network is still present in long-term-abstinent heroin-dependent individuals.

Large-Scale Brain Network Coupling Predicts Total Sleep Deprivation Effects on Cognitive Capacity.

Interactions between large-scale brain networks have received most attention in the study of cognitive dysfunction of human brain. In this paper, we aimed to test the hypothesis that the coupling strength of large-scale brain networks will reflect the pressure for sleep and will predict cognitive performance, referred to as sleep pressure index (SPI). Fourteen healthy subjects underwent this within-subject functional magnetic resonance imaging (fMRI) study during rested wakefulness (RW) and after 36 h of total sleep deprivation (TSD). Self-reported scores of sleepiness were higher for TSD than for RW. A subsequent working memory (WM) task showed that WM performance was lower after 36 h of TSD. Moreover, SPI was developed based on the coupling strength of salience network (SN) and default mode network (DMN). Significant increase of SPI was observed after 36 h of TSD, suggesting stronger pressure for sleep. In addition, SPI was significantly correlated with both the visual analogue scale score of sleepiness and the WM performance. These results showed that alterations in SN-DMN coupling might be critical in cognitive alterations that underlie the lapse after TSD. Further studies may validate the SPI as a potential clinical biomarker to assess the impact of sleep deprivation.

Nature of functional links in valuation networks differentiates impulsive behaviors between abstinent heroin-dependent subjects and nondrug-using subjects.

Advanced neuroimaging studies have identified brain correlates of pathological impulsivity in a variety of neuropsychiatric disorders. However, whether and how these spatially separate and functionally integrated neural correlates collectively contribute to aberrant impulsive behaviors remains unclear. Building on recent progress in neuroeconomics toward determining a biological account of human behaviors, we employed resting-state functional MRI to characterize the nature of the links between these neural correlates and to investigate their impact on impulsivity. We demonstrated that through functional connectivity with the ventral medial prefrontal cortex, the δ-network (regions of the executive control system, such as the dorsolateral prefrontal cortex) and the ß-network (regions of the reward system involved in the mesocorticolimbic pathway), jointly influence impulsivity measured by the Barratt impulsiveness scale scores. In control nondrug-using subjects, the functional link between the ß- and δ-networks is balanced, and the δ-network competitively controls impulsivity. However, in abstinent heroin-dependent subjects, the link is imbalanced, with stronger ß-network connectivity and weaker δ-network connectivity. The imbalanced link is associated with impulsivity, indicating that the ß- and δ-networks may mutually reinforce each other in abstinent heroin-dependent subjects. These findings of an aberrant link between the ß- and δ-networks in abstinent heroin-dependent subjects may shed light on the mechanism of aberrant behaviors of drug addiction and may serve as an endophenotype to mark individual subjects' self-control capacity.

Altered resting-state amygdala functional connectivity after 36 hours of total sleep deprivation.

OBJECTIVES: Recent neuroimaging studies have identified a potentially critical role of the amygdala in disrupted emotion neurocircuitry in individuals after total sleep deprivation (TSD). However, connectivity between the amygdala and cerebral cortex due to TSD remains to be elucidated. In this study, we used resting-state functional MRI (fMRI) to investigate the functional connectivity changes of the basolateral amygdala (BLA) and centromedial amygdala (CMA) in the brain after 36 h of TSD. MATERIALS AND METHODS: Fourteen healthy adult men aged 25.9 ± 2.3 years (range, 18-28 years) were enrolled in a within-subject crossover study. Using the BLA and CMA as separate seed regions, we examined resting-state functional connectivity with fMRI during rested wakefulness (RW) and after 36 h of TSD. RESULTS: TSD resulted in a significant decrease in the functional connectivity between the BLA and several executive control regions (left dorsolateral prefrontal cortex [DLPFC], right dorsal anterior cingulate cortex [ACC], right inferior frontal gyrus [IFG]). Increased functional connectivity was found between the BLA and areas including the left posterior cingulate cortex/precuneus (PCC/PrCu) and right parahippocampal gyrus. With regard to CMA, increased functional connectivity was observed with the rostral anterior cingulate cortex (rACC) and right precentral gyrus. CONCLUSION: These findings demonstrate that disturbance in amygdala related circuits may contribute to TSD psychophysiology and suggest that functional connectivity studies of the amygdala during the resting state may be used to discern aberrant patterns of coupling within these circuits after TSD.

Altered intrinsic hippocmapus declarative memory network and its association with impulsivity in abstinent heroin dependent subjects.

Converging evidence suggests that addiction can be considered a disease of aberrant learning and memory with impulsive decision-making. In the past decades, numerous studies have demonstrated that drug addiction is involved in multiple memory systems such as classical conditioned drug memory, instrumental learning memory and the habitual learning memory. However, most of these studies have focused on the contributions of non-declarative memory, and declarative memory has largely been neglected in the research of addiction. Based on a recent finding that hippocampus, as a core functioning region of declarative memory, was proved biased the decision-making process based on past experiences by spreading associated reward values throughout memory. Our present study focused on the hippocampus. By utilizing seed-based network analysis on the resting-state functional MRI datasets with the seed hippocampus we tested how the intrinsic hippocampal memory network altered toward drug addiction, and examined how the functional connectivity strength within the altered hippocampal network correlated with behavioral index 'impulsivity'. Our results demonstrated that HD group showed enhanced coherence between hippocampus which represents declarative memory system and non-declarative reward-guided learning memory system, and also showed attenuated intrinsic functional link between hippocampus and top-down control system, compared to the CN group. This alteration was furthered found to have behavioral significance over the behavioral index 'impulsivity' measured with Barratt Impulsiveness Scale (BIS). These results provide insights into the mechanism of declarative memory underlying the impulsive behavior in drug addiction.