FUNCTIONAL NEURORADIOLOGY

Assessment of abstract reasoning abilities in alcohol-dependentsubjects: an fMRI study

Deepika Bagga & Namita Singh & Sadhana Singh &

Shilpi Modi & Pawan Kumar & D. Bhattacharya &

Mohan L. Garg & Subash Khushu

Received: 28 June 2013 /Accepted: 29 August 2013 /Published online: 13 November 2013# Springer-Verlag Berlin Heidelberg 2013

AbstractIntroduction Chronic alcohol abuse has been traditionallyassociated with impaired cognitive abilities. The deficits aremost evident in higher order cognitive functions, such asabstract reasoning, problem solving and visuospatial process-ing. The present study sought to increase current understand-ing of the neuropsychological basis of poor abstract reasoningabilities in alcohol-dependent subjects using functional mag-netic resonance imaging (fMRI).Methods An abstract reasoning task-based fMRI study wascarried out on alcohol-dependent subjects (n =18) and healthycontrols (n =18) to examine neural activation pattern. Thestudy was carried out using a 3-T whole-body magnetic reso-nance scanner. Preprocessing and post processing wasperformed using SPM 8 software.Results Behavioral data indicated that alcohol-dependent sub-jects took more time than controls for performing the task butthere was no significant difference in their response accuracy.Analysis of the fMRI data indicated that for solving abstractreasoning-based problems, alcohol-dependent subjectsshowed enhanced right frontoparietal neural activation

involving inferior frontal gyrus, post central gyrus, superiorparietal lobule, and occipito-temporal gyrus.Conclusions The extensive activation observed in alcoholdependents as compared to controls suggests that alcoholdependents recruit additional brain areas to meet the behav-ioral demands for equivalent task performance. The results areconsistent with previous fMRI studies suggesting decreasedneural efficiency of relevant brain networks or compensatorymechanisms for the execution of task for showing an equiva-lent performance.

Keywords Alcoholism . fMRI . Abstract reasoning . Brain .

Functional

Introduction

Brain damage is a common and potentially severe conse-quence of long-term, heavy alcohol consumption. There isconsiderable evidence that prolonged, excessive alcohol con-sumption results in neuropsychological deficits [1, 2]. Inparticular, abstract reasoning, visuospatial, and problem solv-ing abilities seem to be frequently impaired after years ofheavy alcohol consumption [3]. These are the cognitive oper-ations linked to the frontal and the parietal cortex that guidecomplex behavior over time through planning, decision-making, and response control. Structural studies have showndiffuse bilateral cortical atrophy in alcohol-dependent subjectswith the frontoparietal areas and cerebellum showing theearliest and most extensive shrinkage [4–6]. Thus, these stud-ies add to the evidence that impairment in these cognitivefunctions is a characteristic sequela of chronic heavy drinking.Several studies of alcoholism have reported significant corre-lations between intellectual impairment and cerebral atrophy[7, 8]. Also, another study by Rogers et al. have shown that

D. Bagga :N. Singh : S. Singh : S. Modi : P. Kumar : S. KhushuNMR Research Centre, Institute of Nuclear Medicine and AlliedSciences (INMAS), Timarpur,Delhi, India

D. BhattacharyaDepartment of Psychiatry, Base Hospital, Delhi Cantt, India

M. L. GargDepartment of Biophysics, Panjab University, Chandigarh, India

S. Khushu (*)NMR Research Centre, INMAS, DRDO, Lucknow Road Timarpur,Delhi, Indiae-mail: skhushu@inmas.drdo.in

Neuroradiology (2014) 56:69–77DOI 10.1007/s00234-013-1281-3

impairments in motor functioning in alcoholics is attributed todiminished connectivity in fronto-cerebellar circuits [6].

Previous neuropsychological studies indicate that alcohol-dependent subjects do show deficits in crystallized intelligencebut these deficits are more subtle than are the deficits exhibitedon fluid intelligence. The crystallized intelligence is dependenton acquired knowledge as it relies on accessing information fromlong-term memory whereas fluid intelligence is independent ofacquired knowledge and is based on the capacity to think logi-cally in novel situations. Abstract reasoning has been consideredto be an important domain for assessment of fluid intelligence[9]. Impairments in fluid intelligence skills of visuospatial pro-cessing and abstract reasoning appear to reflect impairments inhigher cognitive functions of perceptual analysis and synthesis[10]. Various functional connectivity studies have also highlight-ed the importance of frontoparietal control system in executivefunctioning [11]. The latter is also known as a task-positivesystem and is activated by a variety of demanding cognitivetasks like reasoning, attention, and decision-making [12]. Studieshave also shown the role of frontal cortex in abstract reasoning.The connectivity of frontoparietal regions, as suggested by arecent study [13], further strengthens the involvement offrontoparietal cortex in abstract reasoning. Additionally, studieshave also shown the importance of cortico-striato-thalamic cir-cuits in cognitive processes of goal directed behavior and exec-utive functioning. This circuit consists of looped neural pathwaysthat connect the thalamus and striatum regions to the cerebralcortex, and connect the cerebral cortex back to these areas. Thelatter has been shown to be impaired in alcoholism [14]. Thefrontoparietal system in alcoholics might compensate for theimpaired cortico-striato-thalamic circuits to support abstract rea-soning abilities.

Despite the fact that alcohol affects the abstract reasoningabilities to such a great extent, to date, little research has beendone to assess the functional correlates associated with deficitsin abstract reasoning abilities observed in alcohol dependents.The goal of our study was to investigate the functional corre-lates of impaired abstract reasoning abilities in alcohol-dependent subjects. As abstract reasoning is a complex taskthat requires numerous cognitive operations such as workingmemory, attention, visuospatial processing, inhibitory control,decision-making, and abstraction, a matching baseline wasdesigned to require similar processing in terms of visualencoding, decision process, and motor response execution,without the need for reasoning.

Based on previous neuropsychological and functionalmagnetic resonance imaging (fMRI) studies, we hypothesizedthat alcohol-dependent subjects will show an enhanced acti-vation bilaterally in frontal and frontoparietal brain areas. Therationale behind choosing a nonverbal abstract reasoning taskwas that these tasks are considered less biased than language-based problems because of the use of symbols and picturesinstead of concrete examples. To the best of our knowledge,

this is the first abstract reasoning-based fMRI study inalcohol-dependent subjects.

Methods

Subjects

The study included 18 alcohol-dependent subjects and 18healthy individuals (DSM IV criteria). All study participantswere men, between 30 and 50 years of age, and non-smokers.Alcohol-dependent subjects were recruited from a local hospi-tal. The control subjects were recruited from the local commu-nity (see Table 1). As per DSM IV basic criteria, for alcoholabuse or alcohol dependence, impairments in physical, social,legal or any other area of role performance by an individual isrequired. Hence, recruitment of healthy individuals from com-munity excluded individuals with alcohol dependence. Fivecontrol subjects out of 18 controls were occasional drinkers(20 g of pure ethanol/month). All subjects were also evaluatedusing the Alcohol Use Disorders Identification Test (AUDIT)[15]. AUDIT is a very reliable and simple screening tool whichis sensitive to early detection of risky and high risk (or hazard-ous and harmful) drinking. All the subjects were right handedas assessed by Edinburgh Inventory [16]. Imaging studies werecarried out at our institute.

The inclusion criterion for alcohol-dependent patients wasdetoxification for at least 2 weeks and abstinence as assessed bynormal levels of gamma glutamyl transferase (GGT) (Table 1).GGT test is widely used as amarker for alcohol intake. Elevatedlevels of GGT indicate excessive alcohol consumption. As ourstudy subjects were recruited after detoxification of 2 weeks,they were not on any psychotropics at the time of fMRI. Theexclusion criteria included (1) signs or symptoms of malnutri-tion, (2) signs of liver dysfunction: aspartate aminotransferase/alanine aminotransferase ratio greater than 2 [17].

All the alcoholic patients were clinically normal with nopast history of psychiatric disorders. The clinical assessmentincluded detailed medical history, neurological, and neuropsy-chological examinations, and laboratory tests (routine hema-tology and biochemistry screen, thyroid function tests).

All subjects underwent a thorough medical, psychiatric,and neurological examination by a senior psychiatrist. Exclu-sion criteria for all subjects included any kind of neurologicalsymptoms (cerebellar, sensory, or motor dysfunctions), histo-ry of psychiatric disorder (other than alcohol dependence forpatients), medical conditions that may alter cerebral function(i.e., cardiovascular, endocrinological, autoimmune, or onco-logical diseases), and brain trauma (seizures, degenerativedisease, previous head injury with loss of consciousness). Inaddition to these examinations, the presence of visible abnor-malities on T2 images (assessed by a radiologist), pacemaker,bypass surgery or metallic implants that would preclude MRI

70 Neuroradiology (2014) 56:69–77

scan or substance abuse (other than alcohol and tobacco)resulted to the exclusion of the subject.

Therefore, the set of exclusion criteria led up to selectalcohol-dependent patients without apparent neurologicalconditions. The local ethics committee approved the studyand written informed consent was obtained from all partici-pants after the procedures had been fully explained.

Abstract reasoning task

The abstract reasoning task was divided into two conditions:reasoning condition (R) and control condition (C). Each con-dition consisted of two phases: stimulus and response. Sub-jects were presented with the stimulus phase for 4 s, immedi-ately followed by the response phase for 3.5 s. During thestimulus phase, subjects saw three pictures simultaneously inone row across the top of the screen. During the responsephase, subjects saw two possible answer choices presentedsimultaneously in one row across the bottom of the screen. Toselect an answer, all subjects responded with a response grip ineach of their hands. They pressed the button on the left toselect the answer on the left, and the button on the right toselect the answer on the right. During the trials, the phrase

“NEXT?” appeared at the top of the screen for the duration ofthe trial. During R trials, subjects saw three sequential stimulipresented in one row at the top of the screen. During C trials,subjects saw the same stimuli in all three positions of the toprow. Subjects looked at the three stimuli and determined whatthe fourth pictures in the sequence would be (Fig. 1). Duringthe response period, the top row disappeared, and subjects sawtwo possible answer choices on the bottom of the screen. Thestimuli in the R condition consisted of line drawings of shapessuch as circles, squares, and triangles. Sequences weredesigned such that they changed along only one dimension:number, position, shading, or size [18, 19]. Trials weredesigned such that there were an equal number of trial typesthat varied across each of the four dimensions. The answersfor the R trials consisted of the correct response, and a foil thatwas either a picture in the presented sequence, or a variationalong another dimension. C stimuli were created by randomlyselecting one of the stimuli from the R sequences. As with theR trials, the answers for the C trials consisted of the correctresponse and a foil [19].

The control task was designed to require similar processingin terms of visual encoding, decision process, and motorresponse execution, without the need for reasoning.

All subjects were first introduced to the tasks and responsedevice in out-of-magnet training that included introductionand instruction slides as well as sample trials of Reasoningand Control trials on a laptop to make sure that they under-stood the task. Training was geared at thoroughly familiariz-ing participants with the modes of stimulus presentation, taskrequirements, and response options.

Scanning protocol

The participants were scanned inside a 3-T whole-body MRIsystem (Magnetom Skyra, Siemens, Germany) equipped with acircularly polarized 20 channel matrix head and neck coil and45 mT/m actively shielded gradient system. Subjects lay in thesupine position with their heads supported and immobilizedwithin the head coil using foam-pads (vendor provided), tominimize head movement and gradient noise. Thirty-six axialslices parallel to the bicommissural plane through thefrontoparietal cortex covering the whole brain volume usinggradient echo-based interleaved EPI sequence (matrix=64×64,field of view=210 mm, TE=36 ms, TR=3 s, flip angle=90°,slice thickness=3 mm, voxel size=3.28×3.28×3 mm3) wereobtained. For anatomical reference, a T1-weighted 3D gradientecho sequence (MPRAGE: Magnetization Prepared Rapid Ac-quisition Gradient Echo, 160 sagittal slices, slice thickness=1 mm, field of view=256 mm, TR=1900 ms, TE=2.07 ms)image data set was acquired coplanar with the functional scan, toallow for spatial registration of each subject’s data into a standardcoordinate space.

Table 1 Characteristics of study groups

Characteristics Alcohol-dependentsubjects (n =18)

Healthysubjects(n=18)

Laboratorynorms

Age(years) 36.5±5 35.2±3.7

Body mass index (kg/m2) 24.5±4.1 24.6±3.5

Education (years) 10±1.89 10±1.85

AUDIT 30.2±4.6 2±1.3b,c

Alcohol consumptiona 153.3±19.2

Duration of dependence(years)

4.43±1.3

Abstinence (weeks) 17.47±4.39

Age (years) at first drinking 23.7±3.1

Age (years) at the onset ofdependence

33.2±6.2

Biological variables:

g-Glutamyl-transferase 51.3±2.1 ≤53Alanine aminotransferase(U/l)

26.4±14.1 ≤38

Aspartateaminotransferase (U/l)

27.3±16.1 ≤40

Aspartateaminotransferase/alanineaminotransferase

1.03±0.27 ≤2

a Consumption was defined as grams of pure alcohol per day during3 months preceding detoxificationb p value (≤0.05) for between-group comparisons performed using two-sample t testc Average score of five control subjects who were occasional drinkers

Neuroradiology (2014) 56:69–77 71

fMRI Protocol

Block paradigm (BABABABABABAB) with alternating sixphases of activation (A) and baseline (B) was chosen. 190sequential image volumes (belonging to six alternating cy-cles+one baseline for eliminating T1 saturation effects andacclimatization of the patient to the gradient noise) were taken.The baseline (30 s) and the experimental task (60 s) blocksconsisted of four and eight stimuli each. The total fMRIacquisition time was 9 min and 34 s including the activation(6 min) and baseline phases (3.5 min) along with an introduc-tory screen (4 s) at the beginning of task.

Stimuli were presented using fMRI hardware fromNordicNeuroLab and the subject’s response was monitored withthe help of Nordic response device system (NordicNeuroLab(http://www.nordicneurolab.com/Productsand Solutions/NordicfMRI solution/index.aspx)). Timing of stimuli presentation wassynchronized with the scanner image volume acquisition rate.Response times (RT) and response accuracies (RA) wererecorded and stored on a PC outside the magnetic resonancescanner room, for off-line statistical analysis.

Data analysis

At first, fMRI data were transformed into NIFTI format. fMRIimage data were processed with Statistical Parametric Mapping(SPM8, Wellcome Department of Cognitive Neurology, Lon-don, UK, http://www.fil.ion.ucl.ac.uk/spm) software packageimplemented in MATLAB R2008a (Version 7.6.0, Mathworks, Sherbon, MA). The first ten brain volumes (onebaseline) of each fMRI data set were discarded to remove theinitial transit signal fluctuations and subsequent images were re-aligned within the session to remove any minor movements.Translational or rotational movement of ±1.5 mm was notconsidered for analysis. The T1-weighted high-resolution ana-tomical images were co-registered with fMRI images and spa-tially normalized according to the Montreal Neurological Insti-tute (MNI) brain template. The time-course images were nor-malized using the same normalization parameters and thensmoothed with a 6×6×6 mm3 (full width at half maximum)Gaussian smoothing kernel. The EPI-images were high-passfiltered (128 s) to remove artifacts due to cardio respiratoryand other cyclical influences. A statistic parametric map

Fig. 1 Experimental task. For all stimuli, subjects saw an instructionalcue word and three pictures at the top of the screen. After 4 s, the top rowdisappeared, and two answer choices appeared at the bottom of the

screen. For both reasoning (R) and control (C) trials, the word “NEXT?”cued participants to determine the next picture in the sequence

72 Neuroradiology (2014) 56:69–77

(SPM) was generated for each subject under each condition byfitting the stimulation paradigm to the functional data, con-volved with a hemodynamic response function. Condition-specific effects at each voxel were estimated using the generallinear model [20]. Individual first-level contrast images weregenerated for the abstract reasoning task versus baseline contrast(FWE-corrected, p<0.05). One-sample t test in both the groupswas performed to generate an average activation map using thecontrast images from the single-subject analyses. For thebetween-group analyses, two-sample t test was performed.Since age, duration of alcohol dependence, and response timemight influence the BOLD activation pattern in the two groups;they were added as covariates of no interest in the two-sample ttest. The resulting statistical mapwas set at a combined thresholdof p<0.001 for each voxel and a minimum cluster size>80voxels for one-sample t test and >10 voxels for two-sample ttest, which resulted in a corrected threshold of p<0.05 as deter-mined by AlphaSim in RESTsoftware (www.restfmri.net), as nocluster survived on applying FWE correction in controls. Thisapproach of combining voxel probability threshold with anonarbitrary minimum cluster size threshold protects againstfalse positives (Type 1 error) based on the assumption thatmeaningful activation in fMRI is spatially clustered [21]. For agiven voxel-level threshold, the required minimum cluster sizefor both within and between-group analysis was determined byAlphaSim via Monte Carlo simulation.

The anatomical representation of the clusters was related tocytoarchitechtonic maps as implemented in SPM AnatomyToolbox [22]. The toolbox provides a routine, standardizedapplication of probabilistic cytoarchitectonic maps as an ana-tomical reference for functional activations. It includes thefunctionality for the construction of summary maps combiningprobability of several cortical areas by finding the most proba-ble assignment of each activated voxel to one of these areas.

BOLD contrast estimates were also extracted from the 8 mmROIs defined on the regions showing group differences in two-sample t test using MarsBaR toolbox of SPM (http://marsbar.sourceforge.net/).

Results

Drinking history variables for the alcohol-dependent subjectsare presented in Table 1. The alcohol-dependent and controlgroups were similar with respect to mean age, years of edu-cation, and body mass index.

Behavioral performance

During the active phase (abstract reasoning trials), there was nodifferencewith respect to accuracy (two-sample t test, p ≤0.12)between alcohol-dependent subjects (percentage accuracy:mean=63.52, SD=3.37; total no. of responses: mean=41.23,

SD=1.42; no of correct responses: mean=30.28, SD=1.31)and controls (percentage accuracy: mean=64.91 %, SD=2.12;total no. of responses: mean=42.13, SD=3.22; no of correctresponses: mean=31.65, SD=1.34). However, there was asignificant difference in the response times (two-sample t test,p ≤0.01) of the two groups. Control subjects (mean=5260 ms,SD=73.34) performed significantly faster than alcohol-dependent subjects (mean=6110 ms, SD=73.33).

fMRI

Within-group analysis

The alcohol-dependent subjects showed activation in right in-ferior frontal gyrus (IFG), right middle frontal gyrus (MFG),right occipito-temporal gyrus (OTG), inferior parietal lobule(IPL) bilaterally, right superior parietal lobule (SPL) and leftcaudate nucleus (Fig. 2, see Table 2 for coordinates). Thecontrol subjects showed activation in IFG bilaterally, rightOTG, IPL, bilaterally and left insula (Fig. 3, see Table 3 forcoordinates).

Between-group analysis

Control>alcohol dependents When subtracting the alcoholgroup from the control group, there remained no significantareas showing greater activation.

Fig. 2 3D-rendered whole brain activation map for alcohol-dependentsubjects. Activation maps are displayed at a threshold of t>10, p <0.001for magnitude, p <0.05, AlphaSim-corrected

Neuroradiology (2014) 56:69–77 73

Alcohol dependents>controls The alcohol-dependent subjectsshowed an enhanced activation in Right inferior frontal gyrus(RIFG) at (45, 29, −8), right occipito-temporal gyrus (ROTG)at (39, −58, −2), right postcentral gyrus (RPG) at (54, −13, 31)and right superior parietal lobule (RSPL) at (18, −55, 67), ascompared to control subjects (see Fig. 4, Table 4 for details).

ROI analysis

The contrast estimates of BOLD response as obtained usingMarsBaR toolbox in the regions obtained in two-sample t testwere significantly higher in alcohol-dependent subjects ascompared to controls (see Fig. 5 for details).

Discussion

The present study was designed to look for the neural recruit-ment pattern attributed to impaired abstract reasoning abilities

Table 2 Regions of significant activity observed in alcohol-dependentsubjects during the abstract reasoning task

Area MNI coordinates (x , y, z) Activation size (voxels) t value

RMFG 30 −2 57 188 30.14

Left CN −18 −22 22 157 30.94

RIPL 51 −37 55 125 30.58

RSPL −42 1 39 134 16.05

RIFG 45 17 37 105 21.63

LIPL −30 −58 49 98 18.06

ROTG 30 −42 −7 91 16.12

Peaks of activation at p value≤0. 001 (uncorrected) threshold. AlphaSim-corrected (parameters: p value≤0.05, voxels=80)MNI Montreal Neurological Institute, MFG middle frontal gyrus, CNcaudate nucleus, IPL inferior parietal lobule, SPL superior parietal lobule,IFG inferior frontal gyrus, IOG inferior occipital gyrus, R right, L left

Fig. 3 3D-rendered whole brain activation map for control subjects.Significant clusters are superimposed on the anatomical render (SPM8).Activation maps are displayed at a threshold of t >10, p <0.001 formagnitude, p<0.05, AlphaSim-corrected

Table 3 Regions of significant activity observed in control subjectsduring the abstract reasoning task

Area MNI coordinates (x , y, z) Activation size (voxels) t value

ROTG −33 −85 −8 195 26.88

RIFG 45 26 28 178 13.34

LIFG −45 −29 28 108 11.86

RIPL 18 −70 49 104 8.93

LIPL −39 −68 −6 99 12.34

LI −36 −68 −6 82 10.21

Peaks of activation at p value≤0.001 (uncorrected) threshold. AlphaSim-corrected (parameters: p value≤0.05, voxels=80)MNI Montreal Neurological Institute, IPL inferior parietal lobule, IFGinferior frontal gyrus, IOG inferior occipital gyrus, I insula, R right; L left

Fig. 4 3D-rendered whole brain activation map for regions thatresponded more strongly in alcoholics as compared to controls. Activa-tion maps are displayed at a threshold of t >5, p <0.001 for magnitude, p<0.05, AlphaSim-corrected

74 Neuroradiology (2014) 56:69–77

in alcohol-dependent subjects. Behavioral results in our sub-ject group showed that there were no significant differences inthe response accuracy but response times were significantlydifferent, with alcohol-dependent subjects taking more timethan control subjects for performing the task. As abstractreasoning task required the coordination of multiple subgoals,increased response times of alcohol-dependent subjects duringthe task could be interpreted as reflecting increased demandson sub goal coordination. To ensure that activation differenceswere not due to longer response times, the latter was taken ascovariate of no interest in two-sample t test. Even so, the samepattern of results emerged.

The frontoparietal network responsible for abstract reason-ing is common to both groups. Alcohol-dependent subjectscompared with control subjects showed increased activationin inferior frontal gyrus, occipito-temporal gyrus, postcentralgyrus and superior parietal lobule in the right hemisphere. Thelarger extension of the frontoparietal network activations

observed in alcohol-dependent subjects support the Parieto-Frontal Integration Theory (P-FIT) of intelligence [23].

SPL and postcentral gyrus (PG) activation has been reportedin previous abstract reasoning studies [19, 24, 25, 28]. Theseactivations have been hypothesized to reflect the manipulation ofspatial information [19, 24, 28], relational complexity or visualinspection and attention. These areas are found to be a part of anetwork that supports reasoning abilities [18]. The greater task-related activity in right SPL and right PG in alcohol-dependentsubjects may indicate greater effort to sustain their attentiondemands related to visuospatial manipulation processes and rea-soning complexity.

The regions involved in making a decision and respondingto a problem are the inferior and medial frontal gyrus which areknown to support unique functions that contribute to successfulabstract reasoning. The IFG is the executive center of mainte-nance and information processing with internal representationsduring working memory, and a key brain region supportingreasoning and novel problem solving [19, 24, 26]. IFG has beendemonstrated to be involved in response inhibition [27]. Thegreater activation of IFG observed in alcohol-dependent sub-jects may represent their difficulty in processing information,creation of a strategy or planning required to solve the reason-ing problems.

The lateral OTG store representations of visual informationand are associated with spatial stimuli and visual perceptionand processing [24, 28]. The greater activation of OTG inalcohol-dependent subjects reflects the increased need forvisual processing for equivalent task performance.

On direct comparison between the two groups, despiteequal task performance, we observed a more extensivelydistributed pattern of right frontoparietal activation inalcohol-dependent subjects. This extensive activation sug-gests that alcohol-dependent subjects had to recruit additional

Table 4 Results for the whole brain analysis for alcohol dependents>controls contrast

Statistical values MNI coordinates and anatomical location

Cluster size t value x y z Hemisphere Structure BA

42 6.11 45 29 −8 R IFG 45

21 5.53 39 −58 −2 R OTG 19

15 4.78 54 −13 31 R PG 3b

14 6.04 18 −55 67 R SPL 7A

Peaks of activation at p value≤0.001 (uncorrected) threshold. AlphaSim-corrected (parameters: p value≤0.05, voxels=10)MNI Montreal Neurological Institute, SPL superior parietal lobule, IFGinferior frontal gyrus, IOG inferior occipital gyrus, PG postcentral gyrus

Fig. 5 BOLD contrast estimateson the regions showing groupdifferences in two-sample t test

Neuroradiology (2014) 56:69–77 75

brain areas to meet the behavioral demands for equivalent taskperformance. Previous studies have also shown increasedBOLD response in prenatally exposed alcohol dependentsfor performing spatial working memory task as compared tocontrols reflecting greater recruitment of neural resources tocompensate for poorer neurocognitive abilities [29, 30].

The preserved performance during the abstract reasoning taskis most striking when considering that the alcohol-dependentsubjects were impaired in the related neuropsychological tests.As suggested by Spadoni et al. [30], the enhanced activations inthe alcohol-dependent subjects could reflect inefficient process-ing of the brain or a compensatory mechanism for altered brainanatomy generally observed in alcohol dependents such that alarge number of neurons have to be activated in order to meet theabstract reasoning task demands. All these findings support theidea that alcoholic subjects set up compensatory mechanisms toexecute the reasoning task. Functional connectivity analysisusing dynamic causal modeling (DCM) on the existing datamight shed further light on the differences in the involved neuralmechanisms for task performance among the two groups.

A possible limitation of the study was that the interpretationswere drawn from a sample of men. As alcohol-related neuropsy-chological deficits and brain alterations are gender dependent, thequestions raised in this study still remain for alcoholic women.

Conclusions

In sum, we found that alcohol-dependent subjects showed en-hanced neural activation as compared to controls whileperforming an abstract reasoning task despite similar behavioralperformance. Patterns of brain activation between the alcoholicsand controls are consistent either with a set up of compensatorymechanisms, particularly by non usual activations in thefrontoparietal circuit or it could be due to a decreased efficiencyof relevant brain networks, at neural and/or cognitive levels.

Acknowledgments The authors are grateful for the financial supportfrom DRDO under project INM-311 (4.1), Ministry of Defense andCouncil of Scientific and Industrial Research (CSIR), India.

Conflict of interest We declare that we have no conflict of interest.

References

1. Oscar-BermanM,Marinkovic K (2003)Alcoholism and the brain: anoverview. Alcohol Res Health 27:125–133

2. Fitzpatrick LE, JacksonM (2008) The relationship between alcoholiccerebellar degeneration and cognitive and emotional functioning.Neurosci Biobehav rev 32:466–485

3. Ratti MT, Bo P, Giardini A, Soragna D (2002) Chronic alcoholismand the frontal lobe: which executive functions are impaired? ActaNeurol Scand 105:276–281

4. Moselhy HF, Georgiou G, Kahn A (2001) Frontal lobe changes inalcoholism: a review of the literature. Alcohol Alcohol 36:357–368

5. Pfefferbaum A, Sullivan EV, Mathalon DH, Shear PK, RosenbloomMJ, Lim KO (1995) Longitudinal changes in magnetic resonanceimaging brain volumes in abstinent and relapsed alcoholics. AlcoholClin Exp Res 19:1177–1191

6. Rogers BP, Parks MH, Nickel MK, Katwal SB, Martin PR (2012)Reduced fronto-cerebellar functional connectivity in chronic alcohol-ic patients. Alcohol Clin Exp Res 36:294–301

7. Cala LA, Jones B, Mastaglia FL, Wiley B (1978) Brain atrophy andintellectual impairment in heavy drinkers: a clinical, psychometricand computerized tomography study. Aust NZ J Med 8:147–153

8. Chanraud S, ReynaudM,WessaM, Penttila J, Kostogianni N, CachiaA, Artiges E, Delain F, Perrin M, Aubin HJ, Cointepas Y, Martelli C,Martinot JL (2009) Diffusion tensor tractography in mesencephalicbundles: relation to mental flexibility in detoxified alcohol-dependentsubjects. Neuropsychopharmacol 34:1223–1232

9. Krawczyk DC, McClelland MM, Donovan CM, Tillman GD,Maguire MJ (2010) An fMRI investigation of cognitive stages inreasoning by analogy. Brain Res 1342:63–73

10. Tarter RE (1975) Psychological deficit in chronic alcoholics: a re-view. Int J Addict 10:327–368

11. Vincent JL, Kahn I, Snyder AZ, Raichle ME, Buckner RL (2008)Evidence for a frontoparietal control system revealed by intrinsicfunctional connectivity. J Neurophysiol 100:3228–3242

12. Fox MD, Snyder AZ, Vincent JL, Corbetta M, Van Essen DC,Raichle ME (2005) The human brain is intrinsically organized intodynamic, anticorrelated functional networks. Proc Natl Acad Sci U SA 102:9673–9678

13. Schmahmann JD, Pandya DN (2007) The complex history of thefronto-occipital fasciculus. J Hist Neurosci 16:362–377

14. Jamadar S, DeVito EE, Jiantonio RE, Meda SA, Stevens MC,Potenza MN, Krystal JH, Pearlson GD (2012) Memantine, anNMDA receptor antagonist, differentially influences Go/No-Go per-formance and fMRI activity in individuals with and without a familyhistory of alcoholism. Psychopharmacology 222:129–140

15. Reinert DF, Allen JP (2002) The Alcohol Use DisordersIdentification Test (AUDIT): a review of recent research. AlcoholClin Exp Res 26:272–279

16. Oldfield RC (1971) The assessment and analysis of handedness: theEdinburgh inventory. Neuropsychologia 9:97–113

17. Cohen JA, Kaplan MM (1979) The SGOT/SGPT ratio—an indicatorof alcoholic liver disease. Dig Dis Sci 24:835–838

18. Melrose RJ, Poulina RM, Sterna CE (2007) An fMRI investi-gation of the role of the basal ganglia in reasoning. Brain res1142:146–158

19. Kroger JK, Sabb FW, Fales CL, Bookheimer SY, Cohen MS,Holyoak KJ (2002) Recruitment of anterior dorsolateral prefrontalcortex in human reasoning: a parametric study of relational complex-ity. Cereb Cortex 12:477–485

20. Friston KJ, Worksley KJ (2005) Analysis of fMRI time seriesrevisited again. Neuroimage 2:173–181

21. Forman SD, Cohen JD, Fitzgerald M, Eddy WF, Mintun MA, NollDC (1995) Improved assessment of significant activation in func-tional magnetic resonance imaging (fMRI): use of a cluster-sizethreshold. Magn Reson Med 33:636–647

22. Eickhoff S, Stephan KE, Mohlberg H, Grefkes C, Fink GR,Amunts K, Zilles K (2005) A new SPM toolbox for combin-ing probabilistic cytoarchitectonic maps and functional imag-ing data. NeuroImage 25:1325–1335

23. Jung RE, Haier RJ (2007) The parieto-frontal intergration theory (P-FIT)of intelligence: converging neuroimaging evidence. Behav brain sci 30:135–154

24. Lee KH, Choi YY, Gray JR, Cho SH, Chae JH, Lee S, Kim K (2006)Neural correlates of superior intelligence: stronger recruitment ofposterior parietal cortex. Neuroimage 29:578–586

76 Neuroradiology (2014) 56:69–77

25. Watson CE, Chatterjee A (2012) A bilateral frontoparietal networkunderlies visuospatial analogical reasoning. NeuroImage 59:2831–2838

26. Perfetti B, Saggino A, Ferreti A, Caulo M, Romani GL, Onofrj M(2009) Differential patterns of cortical activation as a function of fluidreasoning complexity. Hum Brain Mapp 30:497–510

27. Liddle PF, Kiehl KA, Smith AM (2001) Event related fMRI study ofresponse inhibition. Hum brain mapp 12:100–109

28. Prabhakaran V, Smith JA, Desmond JE, Glover GH, Gabrieli JD(1997) Neural substrates of fluid reasoning: an fMRI study of

neocortical activation during performance of the Raven’sProgressive Matrices Test. Cogn Psychol 33:43–63

29. Pfefferbaum A, Desmond JE, Galloway C, Menon V, GloverGH, Sullivan EV (2001) Reorganization of frontal systemsused by alcoholics for spatial working memory: an fMRI study.Neuroimage 14:7–20

30. Spadoni AD, Bazinet AD, Fryer SL, Tapert SF, Mattson SN,Riley EP (2005) BOLD response during spatial working mem-ory in youth with heavy prenatal alcohol exposure. AlcoholClin Exp Res 33:2067–2076

Neuroradiology (2014) 56:69–77 77