Addiction related alteration in resting-state brain connectivity
Ning Ma a ,Ying Liu b ,Nan Li a ,Chang-Xin Wang b ,Hao Zhang d ,Xiao-Feng Jiang c ,Hu-Sheng Xu a ,Xian-Ming Fu c ,⁎,1,Xiaoping Hu e ,⁎,1,Da-Ren Zhang a ,⁎,1
a
Division of Bio-X Interdisciplinary Sciences at the Hefei National Laboratory for Physical Sciences at Microscale and Department of Neurobiology &Biophysics,School of Life Sciences at University of Science &Technology of China,Hefei,Anhui,230027,China b
Department of MRI at Anhui Provincial Hospital,Hefei,Anhui,230001,China c
Department of Neurosurgery at Anhui Provincial Hospital and Anhui Provincial Institute of Stereotactic Neurosurgery,Hefei,Anhui,230001,China d
Anhui Detoxi fication and Rehabilitation Center,Hefei,Anhui,230601,China e
The Wallace H.Coulter Department of Biomedical Engineering,Georgia Institute of Technology/Emory University,Atlanta,GA 30322,USA
a b s t r a c t
a r t i c l e i n f o Article history:
Received 22June 2009Revid 5August 2009Accepted 13August 2009
Available online 22August 2009
It is widely accepted that addictive drug u is related to abnormal functional organization in the ur's brain.The prent study aimed to identify this type of abnormality within the brain networks implicated in addiction by resting-state functional connectivity measured with functional magnetic resonance imaging (fMRI).With fMRI data acquired during resting state from 14chronic heroin urs (12of whom were being treated with methadone)and 13non-addicted controls,we investigated the addiction related alteration in functional connectivity between the regions in the circuits implicated in addiction with ed-bad correlation analysis.Compared with controls,chronic heroin urs showed incread functional connectivity between nucleus accumbens and ventral/rostral anterior cingulate cortex (ACC),between nucleus accumbens and orbital frontal cortex (OFC),and between amygdala and OFC and reduced functional connectivity between prefrontal cortex and OFC and between prefrontal cortex and ACC.The obrvations of altered resting-state functional connectivity sugges
ted abnormal functional organization in the addicted brain and may provide additional evidence supporting the theory of addiction that emphasizes enhanced salience value of a drug and its related cues but weakened cognitive control in the addictive state.
©2009Elvier Inc.All rights rerved.
Introduction
Drug addiction is a major health problem in modern society.It is characterized by the failure to resist one's impuls to obtain and take certain types of addictive drugs despite rious negative con-quences (Volkow and Li,2004).Chronic addictive drug u is often related to abnormal functional organization in the brain,which leads to habitually hypernsitivity to the drug and drug-related cues and ensures their compulsive patterns of drug-eking behavior (Kalivas and Volkow,2005).
Resting-state functional connectivity is assd by the correlation of spontaneous fluctuations of blood oxygen level-dependent (BOLD)signals in different regions of the “resting ”brain and is thought to provide a measure of its functional organization (Fox and Raichle,2007).Studies have outlined a number of resting-state networks
corresponding to critical brain functional organizations including movement,vision,audition,language,episodic memory,executive function,and salience detection (Fox and Raichle,2007).During the acquisition of resting-state functional magnetic resonance imaging (fMRI)data,participants are asked to rest quietly instead of performing tasks,making it potentially more readily applicable than functional activation MRI in clinical ttings.A number of groups have begun to study the resting-state connectivity in a variety of neuropsychiatric disorders such as Alzheimer's dia,depression,and schizophrenia (Greicius,2008;Liu et al.,2007;Wang et al.,2007;Zhou et al.,2008).
According to models of addiction,the main brain regions underlying addiction make up a network of,at a minimum,four interdependent and overlapping circuits (Baler and Volkow,2006):(i)reward,involving the nucleus accumbens and ventral pallidum;(ii)memory and learning,including the amygdala and hippocampus;(iii)cognitive control,located in the prefrontal cortex and dorsal anterior cingulate cortex;and (iv)motivation and/or drive and salience evaluation,located in the orbital frontal cortex.In addition,amygdala and ventral/rostral anterior cingulate cortex (including subgenual area),regions that are associated with craving and emotional regulation,are also likely to affect the reactivity of the above circuits and parts of this network (Bechara,2005;Bush et al.,
干白葡萄酒和干红葡萄酒的区别
NeuroImage 49(2010)738–744
⁎Corresponding authors.D.-R.Zhang is to be contacted at Division of Bio-X Interdisciplinary Sciences at Hefei National Laboratory for Physical Sciences at Microscale and Department of Neurobiology &Biophysics,School of Life Sciences,University of Science &Technology of China,Hefei,Anhui,230027,China.Fax:+865513601443.
E-mail address: (X.-M.Fu),edu (X.Hu),drzhang@ustc.edu (D.-R.Zhang).1
Equally contributed to this
work.1053-8119/$–e front matter ©2009Elvier Inc.All rights rerved.doi:
10.uroimage.2009.08.037
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2000;Volkow et al.,2005).The regions are modulated by dopamine and interconnected mostly through glutamatergic and GABA-ergic projections.The interactions between the regions are integrated to generate the behavioral output toward a reinforcing stimulus (O'Doherty,2004),such that addictive drugs intenly activate the reward and motivation circuits,usurp systems underlying reward-related learning and memory,and hijack cognitive control resources (Baler and Volkow,2006;Bechara,2005;Everitt and Robbins,2005; Garavan and Hester,2007;Goldstein and Volkow,2002).As a result, under addiction,the saliency value of a drug and its related cues are enhan
ced,while the inhibitory control is weakened,tting up the stage for an unrestrained cycle which leads to compulsive drug-eking without regard to its negative conquences.
The neurobiological foundation of the models is mainly bad on the results of functional activation studies in human addicts and the obrvation that exposure to addictive drugs produces persistent structural and functional changes on cells within this network (Garavan et al.,2000;Goldstein et al.,2007;Kalivas and O'Brien, 2008;Tomasi et al.,2007;Yang et al.,2009).To date,the resting-state functional connectivity within the key regions of drug addiction has not been extensively studied in human addicts.Therefore,in this study,we investigated whether there is any addiction related alteration in resting-state functional connectivity in this network with fMRI data acquired during resting state from chronic heroin urs and non-addicted controls.
Methods and materials
Participants
Twenty-ven right-handed male volunteers,including14chronic heroin urs(HU,heroin using(from the time of their initial heroin u until the time of scanning)for7.11±2.82years,range from2to 10years)and13non-addicted controls(CN),participated in this study.All HU were recruited from Anhui
Detoxification and Rehabilitation Center(Hefei,Anhui province,China),sought medical help on their own initiative and had a DSM-IV diagnosis of heroin dependence or abu,and urine tests positive for heroin before enrolling in the treatment program.According to an interview conducted by a clinical psychologist,all of the patients had never ud any other types of illicit drugs,were free of illness that required hospitalization or regular monitoring,and were deemed to be stable and able to participate in the experiment.Before the fMRI scanning,except2of HU who were current heroin urs and not under any treatment,the HU were under a methadone treatment and had no illicit drug u during the treatment as confirmed by their caretakers.Among the12HU under the treatment,9were in the detoxification pha(entering the program within1week before the scanning,mean=2.1days,SD=1.8),while the remaining3were in a relatively stable maintenance pha(one had been in the program for 2months and the other two for6months).All methadone-treated participants were under daily methadone administrations and their last methadone us were at least12hours before the scanning.
The control(CN)participants were recruited through adverti-ments and compensated for their time,and none of them reported a history of head injury,psychiatric disorders,or substance dependence (other than cigarette smoking).Only male participants were lected as gender effect w
as not a focus of this study.Both cohorts of HU and CN were current tobacco urs.The HU and CN were matched in age (HU,30.1±5.3years,range from22to39years;CN,29.8±7.2years, range from20to39years;t(25)=0.093,ns)and years of education (HU,9.71±2.7,range from5to14;CN,10.8±1.6,range from8to13; t(25)=−1.296,ns).After complete description of the study to the participants,written informed connt was obtained from them for their involvement in this study in accordance with the review board of University of Science&Technology of China.Imaging
Scanning and image preprocessing
All imaging data were obtained on the3T Siemens Magnetom Trio scanner(Siemens Medical Solutions,Erlangen,Germany)in the Anhui Provincial Hospital.A circularly polarized head coil was ud, with foam padding to restrict head motion.Functional images were acquired with a T2⁎-weighted echo-planar imaging quence (TE=30ms,TR=2s,FOV=24cm,matrix=64×64)with22 axial slices(slice gap=0.4mm,voxel size=3.75×3.75×4mm3), covering the parietal lobe,the occipital lobe,and a large portion of the frontal lobe and the temporal lobe(the slices were approxi-mately along the AC-PC line and covered about−30to60in the IS direction).Resting-state fMRI data were acquired with one run of 6minutes(180images per slice).Corresponding high-resolution T1-weighted spin-echo(for anatomical overlay)images and three-dimensional gradient-echo(for stereotaxic transfo
rmation)images were also collected.Before entering the scanner,all participants were told to clo their eyes,remain still and relaxed,and stay awake during the scanning.After the resting-state scanning,veral functional activation runs were acquired with cognitive tasks(data to appear elwhere).All participants could respond to the tasks immediately after the resting-state scanning suggesting that they may not be asleep during the resting state.Before and after the scanning,according to the reports of a clinical psychologist,all the heroin urs were ensured to be at a stable state and not intoxicated during the scanning.
The imaging data were mainly procesd with Analysis of Functional Neuroimages(AFNI)(Cox,1996).For each participant, thefirst four time points were discarded to account for the approach to steady state in the BOLD signal.The raw data were corrected for temporal shifts between slices,corrected for head motion,spatially smoothed with a Gaussian kernel(full width at half maximum=4mm)and temporally normalized(for each voxel,the signal of each image was divided by the temporally averaged signal). We scanned a total of17HU and16CN participants and discarded the data of participants who head moved more than1.0mm in any dimension through the resting-state run.Data of14HU and13CN participants met the movement criterion and appeared in this study. To further reduce the effect of motion and obtain low-frequency fluctuation,we regresd the motion
data out of the time ries and then preformed band-pass temporalfiltering(0.01–0.08Hz)on the residual signals(Auer,2008;Birn et al.,2006).The
preprocesd
Fig. 1.Seed regions of interest.NAc=nucleus accumbens;Amy=amygdale; OFC=orbital frontal cortex;ACC=anterior cingulate cortex.
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N.Ma et al./NeuroImage49(2010)738–744
time ries were ud in the subquent ed-bad regions of interest(ROIs)correlation analysis.
Generation of ed regions of interest
Ten brain regions,five in each hemisphere,were lected as ed regions of interest(ed ROIs)in this study(Fig.1,Table1).The ROIs were bilateral nucleus accumbens(NAc),amygdala(Amy), dorsal anterior cingulate cortex(Brodmann area(BA)24/32),and orbital frontal cortex(OFC,including the lateral areas,BA11/47,and the medial areas,BA11/12).The regions were defined for each participant anatomically as follows.First,a t of masks corresponding to the regions listed above were defined in a standardized coordinate system of Talairach atlas(Talairach et al.,1992)and cortical structures of a standardized brain.Subquently,the masks were transformed, according to the spatial transformation between the anatomic data and the Talairach space,onto to the image space of each participant and were modified according to individual brain's cortical structures by referencing to the anatomic boundaries in the high-resolution three-dimensional structural images.
Calculation of functional connectivity
For each participant,correlation map was calculated respectively for each ed ROI by a voxel-wi multiple-regression.Regressors included the template time cour extracted by averaging time cours of all the voxels in the ed ROI under consideration,as well as the average time cour in white matter and the average time cour in cerebrospinalfluid(as nuisance signals).The masks of white matter were determined from each participant's high-resolution structural image using FAST gmentation program of fMRIb software library(FSL)(ac.uk).The resulting white matter gmentations were then thresholded to ensure80% tissue type probability.The cerebrospinalfluid mask was manually drawn according to the anatomic boundaries of the high-resolution three-dimensional structural images of each participant.The nuisance signals were ud to account forfluctuations unlikely to be relevant to neuronal activities(Birn et al.,2006;Di Martino et al., 2008;Fox et al.,2005).The resultant t-score maps of the ed ROIs were then converted to z-score maps hereafter referred to as “correlation maps.”
Group analys
Group analys were performed for the correlation maps of each ed ROI.First,the maps were transformed to the Talairach space (re-sampled voxel size:3×3×3mm3)according to the spatial transformation between the anatomic data and the Talairach space. Second,using AFNI,voxel-wi o
ne-sample t-tests and two-sample t-tests were calculated to compare the ed-bad functional connec-tivity within and between the two groups.For the one-sample t-tests, the correlation maps for each participant in the group(HU or CN, respectively)was entered into the analysis and the z-scores at each
Table1
Seed regions of interest(ROIs).
ROI Hemisphere Size(mm3)Coordinates b
NAc Left333−10.5,7.5,−7.9
Right33511.6,7.3,−6.9
Amy Left1149−22.9,−4.8,−14.9
Right114723.6,−4.8,−14.9
Dorsal ACC Left7887−6.0,15.4,32.7
24/32a Right7995 6.0,15.2,32.6
Lateral OFC Left13,725−26.3,39.3,−5.5
11/47Right12,97226.3,39.4,−5.6
Medial OFC Left3636−6.0,36.9,−12.3
11/12Right3529 6.0,37.0,−12.3
a Brodmann area.
b Coordinates refer to the center of the ROI,in Talairach space(left to right,posterior
to anterior,inferior to superior).
Table2
Significant clusters in the two-sample t-tests comparing functional connectivity in heroin urs(HU)versus controls(CN).
Seed ROI Cluster anatomical locations
(Brodmann Area)Cluster size
(mm3)
Primary peak
location a
HU CN
n=14n=13
Mean b Mean
HU N CN
Left NAc Left ventral ACC/medial OFC(24/32)459−7.5,34.5,−0.5 5.875 1.079 Right NAc Left ventral/rostral ACC(24/32)405−7.5,37.5,−0.5 3.2560.082 Right Amy Left lateral OFC(47)189−28.5,22.5,−9.5 2.8540.081 Left lateral OFC Right medial OFC(10/12)18910.5,55.5,−0.5 5.174 1.034 Left medial OFC Right medial OFC(10/12)48613.5,55.5,−0.5 5.1270.540
新好莱坞电影
HU b CN
Left NAc Left precuneus(7)189−22.5,−79.5,41.5−0.700 1.938 Left dorsal ACC Left ventral/rostral ACC(24/32)297−10.5,37.5,2.5 2.039 6.217 Left dorsolateral PFC(8/9)297−28.5,31.5,41.5 2.068 5.588 Left lateral OFC Medial PFC(8/9/32)2079 4.5,22.5,41.50.319 3.528 Left IFG(45)729−43.5,31.5,−0.5 1.077 5.007
Right dorsolateral PFC(9)43246.5,16.5,32.5−0.126 2.088
Left insula(13)297−37.5,13.5,14.50.146 2.857
Left dorsolateral PFC(8/9)270−40.5,7.5,35.50.351 4.050
Left dorsolateral PFC(9)243−49.5,13.5,29.50.551 3.456
Left lateral OFC(10)189−28.5,43.5,8.5−0.099 3.418 Right lateral OFC Left lateral OFC/IFG(47/45)2943−43.5,28.5,2.5−0.450 2.576 Medial PFC(8/9/32)1620−1.5,16.5,47.50.102 3.481
五年级上册数学书答案Left dorsolateral PFC(8/9)1026−37.5,1.5,38.5−0.750 2.551
Right dorsolateral PFC(8/9)99946.5,13.5,38.50.848 3.597
Right IPL(39/40)40549.5,−61.5,41.5 1.172 3.570
Right anterior PFC(10)18937.5,52.5,11.5 1.949 5.066
Right IPL(39/40)18952.5,−58.5,35.5 1.369 4.444 Left medial OFC Left IFG(45)270−37.5,31.5,−0.5−0.477 2.734
NAc=nucleus accumbens;Amy=amygdale;OFC=orbital frontal cortex;ACC=anterior cingulate cortex;PFC=prefrontal cortex;IFG=inferior frontal gyrus;IPL=inferior parietal lobule.
a Coordinates in Talairach space(left to right,posterior to anterior,inferior to superior).
b Within-group averaged z-scores(from correlation maps of each participant)of all voxels in clusters.
740N.Ma et al./NeuroImage49(2010)738–744
voxel were averaged across all participants in the group and compared to zero.Clusters with z -scores signi ficantly larger than zero were determined by combining individual voxel threshold of p b 0.005with a spatial cluster (cluster size from 29to 48voxels among eds and groups)which yielded a fal-positive level of 0.05over the entire volume according to Monte Carlo simulations conducted with AFNI.For the two-sample t-tests,the correlation maps from both groups were entered into the analysis and the z -scores at each voxel were averaged within each group and then compared between groups.For each ed,the two-sample t-test was restricted to voxels within the mask de fined by a logic ‘or ’between the two group maps of each ed resulting from the one-sample t-tests described above.Clusters with z -scores signi ficantly differed between two groups were determined by combining individual voxel threshold of p b 0.005with a spatial cluster size (cluster size from 5to 12voxels among eds)which yielded a fal-positive level of 0.05for voxels in the masks according to Monte Carlo simulations conducted with AFNI.Results
The results are shown in Table 2and Fig.2.Compared to controls,heroin urs showed signi ficantly (p b 0.05,corrected)stronger functional connectivity between NAc and ventral/rostral ACC,between NAc and medial OFC,between amygdala and lateral OFC,between lateral OFC and medial OFC,and within medial OFC.On the other hand,compared to controls,heroin urs exhibited signi ficantly weak
滨州旅游景点er functional connectivity between lateral OFC and medial,dorsolateral PFC,within lateral OFC,between dorsal ACC and dorsolateral prefrontal cortex (PFC),between dorsal ACC and ventral/rostral ACC,and between OFC and some frontal and parietal regions.Discussion
Addiction related alteration in functional connectivity within the key regions implicated in addiction is demonstrated with resting-state fMRI data acquired from chronic heroin urs and non-addicted controls.Compared with controls,chronic heroin urs showed incread functional connectivity between nucleus accumbens (NAc)and ventral/rostral anterior cingulate cortex (ACC),between NAc and orbital frontal cortex (OFC),and between amygdala and OFC;
but reduced functional connectivity between PFC and ACC and between PFC and OFC (Fig.3).
The BOLD signal has been con firmed to indirectly re flect neural activity,and the low-frequency fluctuations in the resting state,although not conclusively proven,have been attributed to neural spontaneous activity (Fox and Raichle,2007).Recent studies using diffusion tensor imaging (Greicius et al.,2009)and task-bad meta-analys (Toro et al.,2008)suggest that resting-state functional connectivity re flects structural connectivity and that networks identi fied in the resting-state mimic tho identi fiable with a lot of task paradigms.Meanwhile,resting-state functional connectivity was fo
und among some brain regions implicated in addiction in recent studies in normal participants (Di Martino et al.,2008;Margulies et al.,2007;Roy et al.,2009).As dysfunctions in the regions were robustly proven in drug addiction (with human and animal models)(Kalivas and O'Brien,2008;Volkow et al.,2007),we suggest that the altered functional connectivity found in HU in the prent study may be a neurobiological indicator of addiction related abnormal func-tional organization in neural networks related to reward,craving and motivation processing which leads to addiction related compulsive drug-eking behaviors.
梦晓Nucleus accumbens plays a central role in reward processing (Baler and Volkow,2006;Knutson and Wimmer,2007).It is widely accepted that the initial reinforcing effects of most drugs of abu rely heavily upon the induction of large and rapid increas in the level of dopamine in the NAc,which can render the drugs as highly salient,drive motivation,and produce compulsive behaviors (Nestler,2005;Volkow et al.,2007).Ventral/rostral ACC is the affective subdivision of the ACC and is primarily involved in asssing the salience of emotional and motivational information and regulating emotional respons (Allman et al.,2001;Bush et al.,2000).This subdivision has extensive connections with other limbic areas including the striatum and amygdala (Kalivas and McFarland,2003).In drug addicts,incread activity in ventral/rostral ACC was found to be associated
with their subjective experience of drug craving (Diekhof et al.,2008;Volkow et al.,2005).The OFC is a major area of motivation,drive,and salience evaluation,which is impaired in drug addicts and plays an important role in the output of compulsive drug-eking behaviors (Volkow and Fowler,2000).In the prent study,signi ficant resting-state functional connectivity was found between NAc and ventral/rostral ACC and between NAc and medial OFC,consistent with the results of a recent study on the functional connectivity of striatum (Di Martino et al.,2008).Amygdala is thought to primarily contribute to the acquisition,consolidation,and expression of learning of the drug-related cues that drive relap to drug-eking behaviors (Hyman et al.,2006;Robbins et al.,2008).This area is also important for craving processing,robustly activated under drug-related cues (Diekhof et al.,2008)(even for the unen ones (Childress et al.,2008;Zhang et al.,2009)),involved in signaling pleasure of immediate prospects which are related to impulsive behaviors (Bechara,2005)and was found to exhibit robust resting-state functional connectivity with affective brain areas including OFC (Roy et al.,2009).Our finding of higher functional connectivity between NAc and ventral ACC,between NAc and OFC,and between amygdala and OFC in HU may be relevant to previous studies that have demonstrated the involvement of the areas in the pathology of addiction (Bolla et al.,2004;Goldstein and Volkow,2002)and may underlie addiction related strong craving respons and motivation for drugs in addicts.
PFC,which is believed to be responsible for restraining craving and cognitive control,was found to be impaired in drug abu or relap (Goldstein et al.,2004;Yang et al.,2009).Dorsal ACC is in responsible for inhibition controlling and con flict monitoring (Bush et al.,2000).Resting-state functional connectivity was found between the regions in a previous study (Margulies et al.,2007),implicating the dorsal –caudal ACC-bad frontoparietal attention networks.In the prent study,heroin urs showed reduced functional
connectivity
Fig. 3.Schematic diagram showing signi ficant functional connectivity differences between chronic heroin urs (HU)and controls.Red line/word:Enhanced in HU.Blue line/word:Reduced in HU.The colors of backgrounds,as ud in a review article (Baler and Volkow,2006),indicate different roles of the regions in drug addiction:red=reward;purple=memory and learning;green=cognitive control;yellow=motivation,craving,and behavior guidance.NAc=nucleus accumbens;Amy=amygdale;OFC=orbital frontal cortex,med =medial,lat=lateral;PFC=prefrontal cortex;dACC=dorsal anterior cingulate cortex;vACC=ventral/rostral anterior cingulate cortex.Inspired from Baler and Volkow (2006).
742N.Ma et al./NeuroImage 49(2010)738–744
within the circuit of cognitive control(between dorsal ACC and PFC) and between the circuits of cognitive control and motivation (between PFC and OFC,between dorsal ACC and ventral/rostral ACC).The obrvations,which are consistent with the results of a recent diffusion tensor imaging study reporting reduced white matter integrity in heroin urs in the frontal and cingulate areas(Liu et al., 2008),suggested diminished cognitive control function and weak-ened cognitive control upon cra
ving and motivation in heroin urs. Taken together,the abnormality of functional connectivity in heroin urs obrved here supports the theories of addiction positing that the drug craving and motivation are enhanced in the addicted state, whereas the strength of cognitive control is weakened(Baler and Volkow,2006;Bechara,2005;Everitt and Robbins,2005;Garavan and Hester,2007;Goldstein and Volkow,2002).
The OFC is a functionally heterogeneous region that involved in complex adaptive behaviors:the medial part of OFC appears to be involved in ongoing monitoring of the reward value of reinforcers, while the lateral part is involved in both evaluating the punishment value of reinforcers and behavioral guidance functions which may lead to a change in current behavior(Elliott et al.,2009;Kringelbach, 2005;Kringelbach and Rolls,2004;Murray et al.,2007;O'Doherty et al.,2001;O'Doherty,2007).In the prent study,we respectively analyzed the functional connectivity of the two sub-regions of OFC. We found heroin urs exhibited enhanced functional connectivity between medial OFC and NAc and within medial OFC,which may correspond to their stronger salience value of drugs.The lateral OFC of heroin urs showed stronger functional connectivity to amygdala and to medial OFC but weaker connectivity to PFC and to lateral OFC. In previous studies,the dysfunction of lateral OFC found in drug addicts was thought to be implicated in the core
characteristics of drug addiction,such as failure to properly inhibit excessive drug consumption and develop aversive/withdrawal reactions to poten-tially dangerous situations(Goldstein et al.,2001,2005;Volkow et al., 2003).Our obrvations may suggest that,in drug addicts,there may be abnormally excessive influences of drug and drug cues-induced craving to the behavioral guidance function,while the ability of behavior changing according to cognitive control and the function of evaluating punishment value of reinforcers(such as negative conquences of drug taking)may be impaired.As drug addiction is characterized by the failure to resist one's impuls to obtain and take addictive drugs despite rious negative conquences(Volkow and Li,2004),our functional connectivityfindings may provide a neurobiological explanation for this phenomenon.
The major points discusd above are mainly bad onfindings of altered resting connectivity in addicts compared with non-addicted controls.However,as the roles of resting-state functional connectivity in the circuits implicated in addiction,such as tho related reward and craving,remains to be elucidated and due to the lack of behavior tasks in the prent study,to what extent the prentfindings are related to the abnormal brain function in drug addicts is still an open question.Thus,future studies focud on the implications of resting-state functional connectivity in brain circuits of reward,craving,and cognitive control,especially in tho of drug addicts,are needed to provide a more specific and definitive interpretation of the results in the prent study.
As most chronic heroin urs in our study were under methadone treatment,what effects of methadone would have on the functional connectivity is an interesting question.Known as a drug that prolongs opioid dependence,methadone has similar effects as addictive drugs to some extent(Connock et al.,2007).For example,studies have found that methadone can prime heroin cue respon and craving (Curran et al.,1999)and enhance brain respon to drug cues (Langleben et al.,2008),which are similar to tho in untreated heroin dependence(Daglish et al.,2003).Thus,we speculate that the alteration of functional connectivity related to methadone might be in the same direction as that related to heroin addiction.However,as the effect of methadone was not sufficiently controlled in the prent study,its effect on functional connectivity needs to be clarified in further studies.Nonetheless,as chronic heroin urs under metha-done treatment are thought to be still at states of addiction(Connock et al.,2007),ourfindings of alteration in brain functional connectivity in HU may be mainly related to their opioid addiction.
A recent study found that the verity of nicotine addiction was negatively correlated with the strength of connectivity between dorsal ACC and striatal circuits(Hong et al.,2009).However,in the prent study,in contrast to controls,we found that the connectivity between ventral ACC and NAc was stronger in heroin ur who reported higher(p b0.001)Fagerström Test for Nicotine Dependence
(FTND)scores,and there was no significant between-group difference on the connectivity between dorsal ACC and NAc.Thus,we propod that the effect of nicotine addiction verity may not be a main effect of alteration on functional connectivity found in our study.Nonethe-less,as our two groups were not well controlled for nicotine addiction verity,this question should be addresd in future studies.
Additional investigations involving larger sample size of and more diver s addictive to other substance and in different genders)are needed for generalizing our results,examining the relationship between behavioral and imaging data,and clarifying the effects of different treatment stages of addiction on functional connectivity.In particular,the prent study did not dissociate the effects of methadone treatment on resting-state functional connec-tivity from tho of heroin addiction,so further studies in this regard are needed;such a study may be of potentially clinical significance. Meanwhile,methods that could address potential noi due to low-frequencyfluctuations from possible thermal noi,scanner instabil-ity,and alias of cardiac and/or respiratory cycling,more advanced analysis,such as independent component analysis(Greicius et al., 2007)and effective connectivity analysis(Fox and Raichle,2007),and combination with diffusion tensor imaging(Greicius et al.,2009)may be ud in further studies.
Taken together,we found enhanced resting-state functional connectivity within the regions related to reward,memory,craving, and motivation but reduced connections within the regions associ-ated with cognitive control and craving and behavioral guidance in addictive drug urs with fMRI.Thefindings suggest an abnormal functional organization in the addictive brain,which may provide additional evidence supporting the theory of addiction(Baler and Volkow,2006;Bechara,2005;Everitt and Robbins,2005;Garavan and Hester,2007;Goldstein and Volkow,2002)that emphasizes enhanced salience value of a drug and its related cues but weakened strength of cognitive control in the addictive state.
队名队呼口号大全
Acknowledgments
We thank two anonymous reviewers and the editor of Neuroimage for their helpful comments and suggestions.This rearch is supported by the National Nature Science Foundation of China (30770713,30870764,and30670683),Ministry of Science and Technology of China(2006CB500705),Academic Exchange Fund of International Medical MR(N7014),and the US National Institutes of Health(RO1EB002009and RO1DA17795).We thank Dr.De-Lin Sun, Xiao-Song He,and Zu-Ji Chen for their advice.
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