anterior cingulate dysfunction during choice anticipation in schizophrenia

www.elsevier.com/locate/psychresns

Psychiatry Research: Neuroim

Anterior cingulate dysfunction during choice

anticipation in schizophrenia

Javier Quintanaa,b,*, Tiffany Wongb, Elena Ortiz-Portillob,

Stephen R. Mardera,b, John C. Mazziottac

aGreater Los Angeles VA Health Care System and VA VISN22 Mental Illness, Research, Education and Clinical Center (MIRECC),

11301 Wilshire Blvd, Los Angeles, CA 90073, USAbUCLA Department of Psychiatry and Biobehavioral Sciences, 760 Westwood Blvd., Los Angeles, CA 90024-1759, USA

cUCLA Departments of Neurology, Radiology, Pharmacology, and Brain Mapping Center, 660 South Charles Young Drive, Los Angeles, CA

90095, USA

Received 25 August 2003; received in revised form 19 March 2004; accepted 12 June 2004

Abstract

The anterior cingulate cortex (ACGC) participates in selective attention, working memory (WM), anticipation, and

behavioral monitoring. Subjects with schizophrenia exhibit deficits in these mechanisms during selective attention and WM

tasks. However, ACGC dysfunctions have not been specifically investigated during behavioral anticipation, whose deficits may

relate to salient schizophrenic features such as foresight abnormalities and impaired social functioning and behavior. We thus

studied ACGC function in relation to two aspects of WM, remembering information and anticipating responses, in control and

schizophrenic subjects. We measured brain activation in eight subjects with schizophrenia and eight healthy volunteers using

functional magnetic resonance imaging. All subjects performed stimulus–response delay tasks with color dots or facial

expression diagrams as cues and either 50% or 100% response predictability, which emphasized demands on remembering the

cues or anticipating the response for correct performance, respectively. We found a double dissociation of ACGC activation

between subject groups and task type. In controls, the ACGC became intensely activated during response anticipation (more

extensively and bilaterally when the cues were colors than when they were facial diagrams) but remained at resting activity

levels during remembering. In schizophrenic patients, significant ACGC activation was seen only when remembering a percept

(more extensively and bilaterally when it was a facial diagram than when it was a color) but not when anticipating a response.

These results reveal an ACGC dysfunction during choice anticipation in schizophrenia and suggest that it might underlie the

foresight deficits seen in schizophrenic patients.

Published by Elsevier Ireland Ltd.

Keywords: Cognitive deficits; Decision making; Social functioning; Foresight; fMRI; Working memory

0925-4927/$ - s

doi:10.1016/j.ps

* Correspon

Sciences, 760 W

E-mail addr

aging 132 (2004) 117–130

ee front matter. Published by Elsevier Ireland Ltd.

cychresns.2004.06.005

ding author. UCLA Neuropsychiatric Institute and Hospital, Room C8-222, Department of Psychiatry and Biobehavioral

estwood Plaza, Los Angeles, CA 90024-1759, USA. Tel.: +1 310 478 3711x41009; fax: +1 310 268 4056.

ess: [email protected] (J. Quintana).

J. Quintana et al. / Psychiatry Research: Neuroimaging 132 (2004) 117–130118

1. Introduction

Patients with schizophrenia exhibit deficits in a

variety of cognitive mechanisms including early

sensory processing, perception of social and emo-

tional cues, attention, working memory (WM), behav-

ioral planning, decision making, and other executive

functions (reviewed in Jeste et al., 1996). Some of

these deficits may be related to the patients’ poor

social functioning and adaptation, a hallmark of

schizophrenia (Penn et al., 1998). Numerous neuro-

imaging studies in subjects with the condition have

reported neural dysfunctions (e.g., increased or

decreased blood flow or neuronal activity in specific

areas or systems or abnormal activation patterns in

distributed neural systems) related to some of those

cognitive abnormalities. The dysfunctions affect the

prefrontal cortex in its dorsolateral (DPFC) and

inferior aspects (IFC), the orbitofrontal cortex

(OFC), the parietal (PPC) and temporal cortices, the

motor and premotor systems, and the anterior cingu-

late cortex (ACGC; Berman et al., 1986; DeLisi et al.,

1989; Friston et al., 1992; Blackwood et al., 1994;

Schroeder et al., 1994; Quintana et al., 2001,

2003a,b). However, these reports do not yet offer a

complete and cohesive picture—in neuroanatomical

or neural systems terms—of brain dysfunctions that

may account for the overall neurocognitive and social

functioning deficits of patients with schizophrenia.

For example, the neural correlates of some cognitive

deficits, such as behavioral anticipation, have not been

specifically addressed, data regarding the role of

particular brain areas appear incomplete, and little is

known about whether the various deficits observed in

schizophrenia are the result of a common or a separate

set of brain function abnormalities.

Data regarding ACGC function in schizophrenia

appear particularly fragmented and inconsistent,

sometimes even contradictory, and their interpreta-

tion is further complicated by the multiplicity of

putative ACGC cognitive roles in the healthy human

brain. The ACGC (agranular region including the

proisocortical area 24 and the paralimbic area 32 of

Brodmann; see Paus, 2001) is involved in WM,

decision making, monitoring or evaluating decision-

making performance, and in facilitating the assign-

ment of attentional and motivational resources as

needed for those cognitive processes (Carter et al.,

1999). It has also been suggested that the ACGC in

general is involved in resolving prior inhibition (Ruff

et al., 2001) and in cognitive performance monitor-

ing (Nordahl et al., 2001), that its more rostral (or

baffectiveQ) portion is more specifically involved in

the affective and motivational components of error

monitoring, and that its more caudal (or bcognitiveQ)portion is involved in response conflict detection and

internal monitoring (Bush et al., 2000; Kiehl et al.,

2000; Braver et al., 2001; Menon et al., 2001; Van

Veer and Carter, 2002; Laurens et al., 2003) as well

as in anticipation and planning of responses based on

information held online (Petit et al., 1998). The

activation of the ACGC correlates with high

response predictability and concurrent low error rates

during two-choice prediction tasks (Paulus et al.,

2002). Lesions of the ACGC in humans result

mainly in deficits of intention and self-initiated

responses, and less prominently in focused and

sustained attention, or in akinetic–mutism (Cohen

et al., 1999). From the published evidence, it appears

that the ACGC contributes to those aspects of WM

and decision making that have to do mainly with the

on-going control of performance and with the

planning, selection, and execution of correct

responses, and less with the perceptual aspects of

such performance.

Impairments in cognition and behavior in schizo-

phrenia seem to involve some of the neural mecha-

nisms supported by the ACGC. Structural

abnormalities of the ACGC such as loss of neurons

have been described in schizophrenia (Deicken et al.,

1997). Its most anterior portion is reduced in size

(Goldstein et al., 1999; Sigmundsson et al., 2001), and

its normal lateralization reversed (Albanese et al.,

1995) in a number of schizophrenic patients. In

addition, the reduction in size of the ACGC has been

associated with negative symptoms (Sigmundsson et

al., 2001) and deficits in executive function (Szeszko

et al., 2000). Decreases in the number of Layer II

cortical cells (Benes et al., 1997; Benes, 1998, 1999)

and abnormal levels of dopamine (Dolan et al., 1995;

Wyatt et al., 1995) in the ACGC have also been

reported. Recent evidence indicates that ACGC

function may also be abnormal in schizophrenia

(reviewed in Tamminga et al., 2000). Decreased

activation in the ACGC of schizophrenic patients

has been found in relation to response conflict (Carter

J. Quintana et al. / Psychiatry Research: Neuroimaging 132 (2004) 117–130 119

et al., 1997), error detection (Carter et al., 2001; Alain

et al., 2002), and error monitoring (Nordahl et al.,

2001; Laurens et al., 2003). As mentioned before, the

distinction might be related to which area of the

ACGC is considered. The exact nature of the

behavioral and error-monitoring deficit in schizophre-

nia has not been completely elucidated, but it appears

that response conflict might be an underlying factor in

the attentional deficit seen in schizophrenic patients

(Yucel et al., 2002b). An overall decrease in ACGC

metabolic rate has been found in schizophrenia

(Haznedar et al., 1997); alternatively, higher relative

regional cerebral blood flow in ACGC has been

observed when patients go off medications (Miller et

al., 1997) and in neuroleptic-naRve, symptomatic

young schizophrenic patients (Kishimoto et al.,

1998). Increased ACGC activity has been associated

with the disorganization syndrome of schizophrenia

(Liddle et al., 1992), whereas decreased activity has

been associated with both the deficit and nondeficit

clinical subtypes of the condition (Tamminga et al.,

1992). Age has been shown to be negatively

correlated with ACGC metabolism in both schizo-

phrenic patients and healthy controls (Buchsbaum and

Hazlett, 1997; Schultz et al., 2002). It has been

proposed that morphological factors such as the

presence or absence of a paracingulate gyrus in

schizophrenic patients might account for some of

the variability among different studies (Yucel et al.,

2002a). Functional ACGC abnormalities have also

been reported in schizophrenic patients during per-

formance of tasks that demand behavioral monitoring,

execution, and planning—all cognitive mechanisms

related to anticipation.

It has also been suggested that factors such as

subject group composition and/or experimental

design—especially differences between activation

tasks used in various functional neuroimaging stud-

ies—may account for some of the variability in results

or discrepancies in the literature. Studies where

minimal and controlled variations of a basic task

design call for different behavioral or cognitive

strategies may offer clarifying advantages. For exam-

ple, during performance of simple visuomotor WM

tasks, the level of predictability of correct choices may

dictate alternative or preferred strategies—such as

remembering the cue or anticipating the response—

that have been shown to be supported by separate

components of WM in a DPFC–PPC network in

monkeys (Quintana and Fuster, 1992, 1999). Using an

experimental task design that incorporates different

cue types and strengths of contingency between these

cues and response choices, we have recently shown

functional balance shifts between PFC and PPC that

reflect the brain’s adjustment to task demands through

the appropriate use of specialized resources (i.e.,

different cognitive strategies; Quintana et al., 2003a).

These results provide evidence of primary PFC brain

deficits and secondary PPC compensations occurring

in schizophrenia during perception–action behavior, as

well as a possible explanation for inconsistencies

found among previous studies, with respect to DPFC

functional states in schizophrenic patients. Together

with the DPFC and the PPC, the ACGC is an important

component of the distributed neural network that

supports perception–action integration, and related

ACGC data would thus be important for a better

understanding of the operational condition of such a

network in schizophrenia. In this report, we present

data that further characterize ACGC dysfunctions in

schizophrenia, particularly in relation to aspects of

decision making such as anticipation and foresight

whose abnormalities may be at the root of social

function deficits in schizophrenic patients.

This study was thus designed to identify and

characterize differences in ACGC function between

normal controls and schizophrenic patients during

performance of visuomotor stimulus–response delay

tasks that, by testing different levels of response

predictability, emphasize mnemonic or anticipatory

aspects of WM during decision making. Previous

single-unit recording studies in awake, behaving

monkeys demonstrated that the tasks used in this study

can unequivocally elicit separate, distinct neuronal

activities related to remembering and anticipating

during WM (Quintana and Fuster, 1992, 1999). One

objective of this study was to elucidate if functional

abnormalities in the ACGC in schizophrenia occur in

situations where the predictability of correct response

might call for anticipatory decision-making strategies.

Deficits in anticipation and foresight are common in

schizophrenia and likely instrumental in the social

dysfunction associated with the condition. A second,

related objective was to characterize ACGC function in

schizophrenia during retention of a percept in WM.

Deficits in retentive aspects of WM have been


repeatedly described in schizophrenia and have been

linked to functional abnormalities of the DPFC, which

is heavily and reciprocally connected to the ACGC

(Petrides and Pandya, 1984; Goldman-Rakic, 1988;

Brothers, 1995; Paus, 2001).

2. Methods

We recruited eight volunteers (six males, two

females, mean age: 29.25F5.13) and eight schizo-

phrenic patients (six males, two females, mean age:

35.22F10.69), all right-handed. The schizophrenic

patients (mean education level: 12.88F1.46 years;

and average length of illness: 8.5 years) were

diagnosed according to DSM-IV criteria (American

Psychiatric Association, 1994) by two independent,

board-certified psychiatrists. They were all stable

outpatients maintained on standard doses of atypical

antipsychotics (olanzapine 10–20 mg/day or risper-

idone 2–6 mg/day) without anticholinergic medica-

tions. The control subjects had an average educational

level of 16.75F2.96 years and no personal or family

history of neurological or psychiatric disorders. All

subjects gave written consent to participation under

protocols approved at the West Los Angeles VA

Health Care Center and the UCLA School of

Medicine, following a detailed explanation of the

nature and possible consequences of the study.

For functional MRI data acquisition, subjects from

both groups lay on the scanner bed while being

presented with four consecutive block-design para-

digms counterbalanced for order across subjects. Each

paradigm consisted of three resting blocks of approx-

imately 24 s each (during which the subjects saw a

black visual field) interleaved with two activation

blocks of approximately 70 s (during which the

subjects performed a series of stimulus–response

visuomotor tasks). Each activation block consisted

of a series of six trials (see Fig. 1A, diagram) of a

visuomotor delay task that included a cue–delay–

choice sequence. The cue for each trial was presented

for 0.5 s at the center of the screen on a black

background. We used two sets of cues for the trials:

(a) a colored circle (green, red, blue, or yellow) or

(b) a line drawing of a face (depicting a happy or a

sad expression).

After a 7-s delay (black screen), a choice was

presented between two colored circles or two face

diagrams displayed side-by-side on a black back-

ground for up to 2.5 s. The subjects were asked to

select between the right or left item by pressing, using

minimal movement of two fingers of their dominant

(right) hand, the right or left button of a magnetic-

compatible mouse device, respectively. Once a choice

was made according to the task contingencies

explained below, the choice stimuli disappeared and

the screen remained black for the rest of the 2.5-s

period, right after which the cue for the next trial

appeared. Of the total duration of each block of six

trials (approximately 70 s), 3.5 s (5% of total)

corresponded to cue presentations, 42 s (60% of total)

to delay periods, 7–10 s (10–15% of total) to choice

execution, and 14–17 s (20–25% of total) to intertrial

periods. This time distribution was designed to

maximize the weight of delay activity in our imaging

data.

The correct response for each trial was determined

according to the following contingency rules (see Fig.

1B): A red or green cue, or a smiling or sad face,

preceded a choice between red and green color circles

or between smiling and sad faces, respectively,

presented side-by-side in random position. The sub-

jects were instructed to choose the response stim-

ulus—right or left—that matched the cue presented 7

s before. Thus, in this case, the predictability of the

correct response side was 50% (chance level).

Alternatively, a blue or a yellow cue preceded a

choice between two side-by-side white circles. And a

smiling or a sad face, whose nose pointed at the right

or left of the subject’s visual field, preceded a smiling

and a sad face (also presented side-by-side, the one on

the left with its nose pointing to the left of the subject,

the one on the right with its nose pointing to the right).

The subjects had been instructed before the scanning

session that after a blue color, the correct response

was always the left white circle and that after a yellow

color, the right white circle. They had also been

instructed that the direction where the nose of the face

cue was pointing always determined the correct

response between the two face choices, left or right.

Hence, the predictability of correct response was

100%, although the subjects could not execute a

response until the two choices appeared following the

cue. Depending on the degree of contingency between

Fig. 1. (A) Example of time course of average changes in signal intensity over an entire scanning run in ACGC, area 24, of controls during

anticipatory task performance with color stimuli. Observe the prominent, protracted signal-intensity increases during the activation periods of

the run. The middle section of the figure shows a diagram of the temporal events of an experimental run, indicating the duration of resting (24 s)

and activation periods (69 s), as well as the temporal structure and epochs of each of the six trials composing an activation period. A1, A2

indicate activation period numbers 1 and 2 (see Section 2 for details). The bottom graph shows the time course of averaged changes in signal

intensity during periods of activation (average of two activation periods of a run for a specific task and area). Observe that the relative increases

in signal intensity coincide with the delay periods of the six trials (light gray bands). (B) Diagrams of the two tasks—remembering and

anticipating—with both color and facial diagram stimuli (see Section 2). A double arrow between the two choices in the case of the

brememberingQ task indicates the random presentation (i.e., right or left) of the correct response in that task. A small bcQ under one of the choicesfor each diagram indicates the correct response according to task contingencies.



cue and response choice (i.e., location of the correct

choice indicated by the cue with certainty or with a

probability of only 50%), therefore, the subjects faced

two situations operationally:

(a) know the answer and wait to respond—thus

being able to anticipate the correct choice—or

(b) don’t know the answer and wait to decide—thus

being forced to remember or retain the cue.

The two activation blocks of an experimental run

contained only trials with the same stimulus cue

category (color or face) and the same type of task

demand (anticipating or remembering) or level of

predictability (certain or uncertain correct choice side)

(i.e., each run presented only either color cues

allowing anticipation such as yellow or blue, color

cues necessitating remembering such as red or green,

smiling or sad faces, or faces with right- and left-

pointing noses). Other than this restriction, the

selection of cue (between yellow and blue, red and

green, smiling and sad face, face with right- and left-

pointing nose) and of correct choice position (right or

left) was random for each trial. Overall, for the

purpose of this study, each subject underwent four 12-

trial runs—one for each combination of task con-

tingency and stimulus types, counterbalanced in order

across subjects—for a total of 48 trials, with an equal

total number of trials of each of the two-task and two-

stimulus modalities.

The presentation of stimuli was controlled by a

microcomputer and delivered to subjects through a

magnet-compatible goggle system. Correct perform-

ance levels and reaction times were also recorded by

the microcomputer. Concurrent imaging was per-

formed using a GE 3T scanner with an echo-planar

imaging upgrade. First, we acquired echo-planar high-

resolution structural images covering the entire brain

volume (TR/TE/flip angle/thickness=4000 ms/54 ms/

908/1.2 mm). Then, we acquired gradient echo func-

tional images covering 14 slices (4-mm thick, 1-mm

gap) beginning near the middle of the temporal lobes

and moving upward (TR/TE/flip angle=2000 ms/45

ms/798). Images for each subject were pre-processed

using AIR (Woods et al., 1998) rendering a final in-

plane resolution of 2�2 mm. They were first

realigned to correct for head motion, then normalized

into a standard stereotaxic space and smoothed with a

Gaussian filter, set at 6-mm full-width at half-

maximum, to minimize noise and residual differences

in gyral anatomy. With respect to subjects’ movement

during the imaging procedures, our data showed only

nonsignificant progressive drifts unrelated to task

periods or behavioral events and well within the

range of motion correction provided by the AIR

algorithms (Woods et al., 1998).

Performance and imaging data were analyzed

using, respectively, SPSS software (SPSS, Chicago,

Illinois) and SPM99 (Friston et al., 1994). We used

multiple and logistic regression models for the

analyses of response time and correctness data,

respectively. A group analysis of the AIR-processed

images was completed using a general linear model

with a delayed box–car reference function (Friston et

al., 1994). We first used a fixed-effects model

comparing signal intensity between activation and

resting periods for each group and each performance

situation (i.e., performance under each task–stimulus

combination), using explicit definitions of baseline

periods and appropriate masking contrasts. We also

pooled together data related to mnemonic or antici-

patory WM performance, respectively (i.e., independ-

ently of stimulus type, colors or face diagrams),

within each group of subjects, and conducted a fixed-

effects model analysis followed by conjunction

analyses contrasting activation versus resting periods

(SPM99) to characterize the cohesiveness of activa-

tion patterns at the group level and guard against

false-positive results. Differences in activation pat-

terns during mnemonic and anticipatory WM per-

formance within each subject group were statistically

analyzed using a random effects model followed by a

two-tailed t-test contrasting the two conditions

(SPM99). We also used a random effects model

followed by a two-tailed t-test to identify statistically

significant differences in activation patterns between

patients and controls for each particular task perform-

ance modality (i.e., remembering or anticipating).

3. Results

We did not detect statistically significant differ-

ences in performance levels—reaction time or correct

response levels—between the two groups of subjects

(F=3.38, P=0.066), although a nonsignificant trend


towards longer overall reaction time was observed

among patients. As described elsewhere (Quintana et

al., 2003a), the error level was equally distributed

between tasks, and the reaction times were shorter by a

similar nonsignificant magnitude during the anticipa-

tory than during the mnemonic task in both groups. We

identified discrete, highly significant ACGC activa-

tions related to task performance in controls and in

schizophrenic patients (Fig. 2, Table 1). The activation

pattern in relation to mnemonic or anticipatory task

demands was strikingly different, almost reciprocal,

between the two groups. Healthy controls showed no

significant ACGC activation during information reten-

tion (Table 1). Conversely, the patients showed

significant ACGC activation (bilateral Brodmann’s

area 24 and left Brodmann’s area 32 when the task

used face diagram cues; only left Brodmann’s area 32

when it used color cues) while remembering informa-

tion (Fig. 2, Table 1). When the subjects could

anticipate a correct response based on the initial

Fig. 2. Sections of brain templates showing results of group analyses of pre

data. Talairach coordinates, voxel-based statistical significance, and extens

activations of the Brodmann’s areas indicated. Data represent averages of al

two rows, activations during mnemonic working memory. Lower two rows

R=right, L=left, BL=bilateral.

information, we found significant ACGC (left area

32 for face diagram cues, right area 32 and bilateral

area 24 for color cues) in the group of healthy

volunteers, but no significant ACGC activation in

schizophrenic patients (Fig. 2, Table 1). Conjunction

analyses, which require each and every subject of a

group to exhibit activity in the area studied and thus

guard against false-positive results, revealed the same

double dissociation between task types and subject

groups; we found significant activation of area 32 only

during anticipatory WM in the control group and only

during mnemonic WM in the group of schizophrenic

patients (Table 2). Direct statistical comparisons of

activations between groups for each particular task

type (i.e., mnemonic WM and anticipatory WM)

confirmed these differences (patientsNcontrols,

t=3.15, Pb0.002, and t=2.73, Pb0.005 during mne-

monic WM for left and right ACGC, respectively;

controlsNpatients, t=3.44, Pb0.001 for right ACGC

during anticipatory WM; Table 2). Within-group direct

processed (realigned, normalized, and smoothed; see text for details)

ion of clusters are described in Table 1. A red ring circles significant

l trial series for all subjects from each group and for each task. Upper

, activations during anticipatory working memory. Yellow lettering:

Table 1

Anterior cingulate cortex (ACGC) activations in control subjects and schizophrenic patients: fixed effect analyses

Controls Patients

Anatomical

area

Brodmann’s

area

Talairach

coordinates

(x, y, z)

Voxel-level

corrected

P-score

{Z-score in

brackets}

Cluster

extent

(number

of voxels)

Talairach

coordinates

(x, y, z)

Voxel-level

corrected

P-score

{Z-score in

brackets}

Cluster

extent

(number

of voxels)

Logical

(color dots)

REM. Left

anterior

cingulate

32 – – – (�2, 32, 20) 0.000

{6.08}

18

ANT. Right

anterior

cingulate

32 (2, 22, 30) 0.000

{5.74}

32 – – –

Bilateral

anterior

cingulate

24 (0, 2, 46) 0.000

{7.69}

269 – – –

Emotional

(face diagrams)

REM. Left

anterior

cingulate

32 – – – (�2, 14, 34) 0.003

{5.37}

15

Left

anterior

cingulate

24 – – – (�4, 22, 22) 0.000

{6.61}

78

Right

anterior

cingulate

24 – – – (6, 4, 42) 0.005

{5.46}

187

(8, 24, 20) 0.005

{5.28}

6

ANT. Left

Anterior

cingulate

32 (�12, 14, 46) 0.003

{5.43}

7 – – –


statistical comparisons between activations related to

each task type indicated that controls, but not patients,

activated the ACGC to a significantly greater degree

during anticipatory than during mnemonic WM

(t=2.62, Pb0.007 for right ACGC; Table 2). Thus,

we found a double dissociation of ACGC activation

between task types and subject groups. The overall

differences between groups did not change as a

function of the cue content (i.e., colors or facial

diagrams). That is, for any type of information, we

observed ACGC activation in patients only during

remembering and in controls only during anticipating.

Differences in ACGC activation in relationship to cue

content were seen, however, within each group. These

within-group, cue-related differences also showed an

opposite pattern in both groups. In patients, the ACGC

activation observed during information retention was

more extended and bilateral when the information was

of an emotional nature (i.e., facial diagrams) than when

it was based on colors (see Fig. 2, Table 1). In controls,

during response anticipation, we observed more

extended, and bilateral, activation when the cues were

colors than when they were facial diagrams.

4. Discussion

Our results provide evidence of differences in

ACGC activation between normal controls and

schizophrenic patients during performance of deci-

sion-making tasks with variable degrees of contin-

gency between cues and subsequent response choices.

They indicate that in normal controls, the ACGC

participates solely in anticipatory aspects of WM

during decision making. In schizophrenic patients

performing the same tasks, on the other hand, the

ACGC becomes active while remembering informa-

tion, yet it does not significantly engage in active

processing related to prediction, anticipation, or

planning of a response. These differences between

Table 2

Anterior cingulate cortex (ACGC) activations in control subjects and schizophrenic patients

Random effect analysis

Controls Patients

Anatomical

area

Brodmann’s

area

Coordinates

x, y, z

Uncorrected

P value

T score Coordinates

x, y, z

Uncorrected

P value

T score

Anticipating vs.

remembering

Right ACGC 32 14, 10, 34 0.007 2.62 NS

Anticipating and

remembering

Left ACGC 24 NS �2, 4, 44 0.000 4.89

Controls vs. patients Patients vs. controls

Anatomical

area

Brodmann’s

area

Coordinates

x, y, z

Uncorrected

P value

T score Coordinates

x, y, z

Uncorrected

P value

T score

Anticipating Right ACGC 24 4, �8, 32 0.001 3.44 NS

Remembering Left ACGC 24 NS �12, �8, 36 0.002 3.15

Conjunction analysis

Controls Patients

Anatomical

area

Brodmann’s

area

Coordinates

x, y, z

Uncorrected

P value

Z score Coordinates

x, y, z

Uncorrected

P value

Z score

Anticipating Right ACGC 32 2, 16, 32 0.000 4.64 NS

Left ACGC 32 �2, 8, 42 0.000 4.78 NS

Remembering Bilateral ACGC 32 NS 0, 20, 36 0.000 4.39

Random effect and conjunction analyses.


healthy controls and schizophrenic patients are con-

sistently observed across different types of informa-

tion, thus indicating a pervasive deficit of ACGC

functions supporting the temporal planning of goal-

oriented behavior through WM in schizophrenia.

Prediction, anticipation, and planning of responses

are cognitive mechanisms required for and supportive

of foresight aspects of decision making, important in

social functioning and adaptation, and are known to

be deficient in schizophrenia. We did not rate social

function levels in our schizophrenic patients, and

therefore, we cannot elaborate on any possible direct

correlation between brain activity, task performance

and social dysfunction. Furthermore, we chose a

design that facilitated similar performance levels in

both controls and patients so that any activation

differences could be tentatively assigned to primary

deficits or compensatory neuronal processes and not

to deficient participation in the task. The caveat of this

approach, however, is that no direct connection can be

established between daily life deficits and the activa-

tion measured in response to the task paradigm.

Nonetheless, our results suggest that ACGC func-

tional abnormalities in schizophrenia may be at least

involved in deficits of basic cognitive elements that

likely support social function.

Our findings regarding ACGC activation in normal

controls agree with recent reports (Petit et al., 1998;

Dagher et al., 1999) that suggest the involvement of

the ACGC in planning and anticipation of responses

based on information available online. ACGC activity

has also been associated with resolution of prior

inhibition (Ruff et al., 2001), uncertainty during

guessing (Elliott et al., 1999) and risky choices

(Critchley et al., 2001), and the emotional evaluative

processes of risky choice consequences (Elliott and

Dolan, 1998). Uncertainty during probabilistic pre-

diction, which likely involves learning and memory of

stimulus–response associations, has been associated,

however, with activation of Brodmann’s area 8 (Volz et

al., 2003). High response predictability and concurrent

low error rates, a combination present during our

anticipatory task, have also been linked to increased

cingulate activation during two-choice prediction tasks


(Paulus et al., 2002). Additionally, it has been shown

that the ACGC is involved in emotional information

processing (Davidson et al., 1999; Davidson and

Irwin, 1999; Teasdale et al., 1999; Bush et al., 2000).

Our data from healthy controls agree with these

findings and indicate that, during decision-making

processing requiring anticipatory WM, the ACGC

becomes active independently of whether the informa-

tion is of an emotional or nonemotional nature.

There is strong evidence indicating that the ACGC

contributes to on-going behavior by monitoring errors

during performance (Carter et al., 1998; Botvinick et

al., 1999; Kiehl et al., 2000; Scheffers and Coles,

2000), and by managing the assignment of attentional

resources (Carter et al., 1997; Baars, 1999; Carter et

al., 1999; Cohen et al., 1999; Mesulam, 1999; Peterson

et al., 1999; Davis et al., 2000) to a particular task. In

this and in a previous study (Quintana et al., 2003a),

we intentionally investigated neural mechanisms that

might respectively relate to perceptual and planning

aspects of the perception–action cycle (i.e., remember-

ing the percept and anticipating an appropriate

response action) separately. We thought that such a

strategy might help us to better characterize the neural

correlates of cognitive deficits specific to retentive

WM or to planning or anticipatory executive functions

in schizophrenic patients. Deficits in WM and in

planning and foresight are well known in schizophre-

nia, and they may be related to the social functioning

deficits observed in patients afflicted by the condition.

A division of WM along its mnemonic and planning or

executive aspects has been characterized in normal

controls (Owen et al., 1996a,b; Smith and Jonides,

1998), where both mechanisms are represented in

overlapping but distinct neural networks over the

DLPFC and the IFC. Activations related to sensory

cues, response preparation, and response execution

have been described with different time courses in the

ventral PFC in a study where protracted activation

related to information retention was seen only in dorsal

premotor and parietal cortex (Toni et al., 1999).

Because normal subjects in that study were instructed

to respond with specific finger movements to visual

cues, the lack of response choice demands could

account for the lack of DPFC activation. Notwith-

standing, the mnemonic and anticipatory components

of WM have not been studied in schizophrenic patients

at the ACGC level before, in spite of the evidence

linking WM and ACGC dysfunction to schizophrenia.

Our results provide evidence that ACGC dysfunctions

likely associated with WM, executive planning, and

foresight deficits can be dissociated in schizophrenic

patients. Furthermore, at least within the spatial limits

of cortical resolution that our study permits, our data

suggest that the ACGC dysfunction in schizophrenic

patients impacts cognitive mechanisms important for

decision making, irrespective of the content of the

information being processed.

The double dissociation of ACGC activation

between tasks and subject groups indicates that normal

controls and schizophrenic patients may handle

particular demands of any given task very differently.

During anticipation, the decreased activation observed

in patients relative to controls suggests an inefficient

mechanism for response planning, a WM component

that crucially supports goal-oriented behaviors neces-

sary for adaptive social functioning (Fuster, 1989).

Poor social functioning and adaptation are hallmarks

of schizophrenia. The ACGC activation deficits we

describe here may be a component of the neural

correlates of poor social functioning and adaptation in

schizophrenia. During mnemonic performance, on the

other hand, the patients in our study exhibited

significantly increased activation relative to controls

in the same ACGC areas where an activation deficit

was observed during anticipation. Considering that

both patients and controls in our study performed at

statistically similar levels of accuracy, the mnemonic-

related increased ACGC activation seen in patients

likely indicates a compensatory attempt. Inefficient or

suboptimal function of specific areas of distributed

networks for WM and decision making may result in

either deficit-related hypoactivity or in compensatory

hyperactivity, depending on whether alternative intact

areas of the network are available for and capable of

handling particular task demands, as has been shown at

the DPFC level (Callicott et al., 2000; Quintana et al.,

2003a). In the case of ACGC, our schizophrenic

patients showed hyperactivity during mnemonic WM

and hypoactivity during anticipatory WM, the same

pattern previously observed in the DPFC (Quintana et

al., 2003a) This similarity of ACGC and DPFC

dysfunctions in our schizophrenic subjects is not

surprising considering the close reciprocal connections

between these two areas (Brothers, 1995; Paus, 2001).

As we concluded with respect to the DPFC cortex


(Quintana et al., 2003a), the task-dependent activation

pattern seen in the ACGC points to a primary

dysfunction of this area in schizophrenia.

It is unlikely, however, that the ACGC dysfunction

in schizophrenic patients we describe here would be

solely at the basis of social maladaptation in those

patients. The ACGC is reciprocally connected to the

DPFC, the PPC, and other areas of the limbic system

such as the amygdala, the OFC, and the hippocampus

(Brothers, 1995). These connections facilitate the

functional cooperation of several of these areas as

distributed networks supporting complex cognitive

processes. Although important for coordinating

resources and for behavioral monitoring, the ACGC

is just a single component of those functional

networks. It is likely that the activations we report

here are correlated with or even result from activation

in other areas of the distributed networks that handle

decision-making behavior. For example, both PFC

and PPC neurons support response anticipation such

as the one demanded by our task design, but neuronal

activity related to mnemonic WM is only seen in PFC

units (Quintana and Fuster, 1992, 1999). Schizo-

phrenic patients exhibit increased PPC activation

compared with control subjects during performance

of anticipatory tasks (Quintana et al., 2003a). This

PPC hyperactivation has been interpreted as a

compensatory mechanism that explains the decreased

activity in the DPFC during response anticipation

(Quintana et al., 2003a), and it might also be linked to

the ACGC deficit during anticipatory WM reported

here. Conversely, the increased ACGC activity during

mnemonic performance that we report here in

schizophrenic subjects compared with controls, which

also exists at the level of the DPFC (Quintana et al.,

2003a), may indicate a primary deficit in these two

areas in schizophrenia. A DPFC and ACGC primary

deficit in schizophrenia should indeed result in

increased activity in these two areas (as shown here

and in a previous study, Quintana et al., 2003a) as a

result of an increased processing effort during

performance of tasks that cannot be handled effi-

ciently by the PPC, such as retention of information

[PPC inefficiency in these tasks has been shown in

both monkey (Quintana and Fuster, 1992, 1993, 1999)

and human (Quintana et al., 2003a) studies].

We did not detect concurrent sensory activations in

visual cortex during task performance in our study. It

is thus difficult to believe that the ACGC activations

we detected are directly and solely related to sensory

processing. The two tasks our subjects performed

used cues that were almost identical from a sensory

perspective but that differed in their relationships of

contingency with the required responses. Further-

more, the signal differences measured between the

two tasks in controls indicate that the underlying

activations are related to processing of these relation-

ships of contingency (i.e., active or working memory)

as needed for decision making.

The signal changes we measured lasted for the

entire duration of the activation periods of our

experimental runs. In our design, 60% of the activation

periods’ time was spent during the trial delay, 20–25%

on intertrial periods, 10–15% on choice execution, and

only a 5% on cue presentations. We also observed

smaller, superimposed changes in signal intensity that

closely paralleled the succession of trials and the time

course of their epochs (cue, delay, choice, intertrial

interval; see Fig. 1, legend for more details). These

additional signal variations, although indicative of the

different components of the overall processing, only

accounted for a small proportion of the total protracted

signal changes, and did not modify the correlations

between these signal changes and the block compo-

nents of our runs.

In summary, the present study provides evidence

that, much as in the case of the DPFC, both increased

and decreased ACGC activity can be observed in

schizophrenic patients compared with controls during

WM performance, and that the direction of the change

is determined in our case by the predominance of

mnemonic or anticipatory task demands. These

demands, in turn, are the result of one factor—

predictability of response—commonly present in

variable degrees in most decision-making situations

in real life. The parallel dysfunctions of the ACGC

and the DPFC in anticipatory processing may explain

the foresight deficits that schizophrenic patients

present in those situations.

Acknowledgments

We thank Drs. A. Kopelowicz (San Fernando

Mental Health Center, Los Angeles Department of

Mental Health) and Drs. W. Wirshing, D. Ames-


Wirshing, and Dr. Scott Saunders (Schizophrenic

Research Clinic, West Los Angeles VA Health Care

Center) for generously agreeing to the recruitment of

subjects.

This research was supported by a Department of

Veteran Affairs (Office of Research and Development,

Medical Research Service) Advanced Research Sci-

entist Career Development Award, and by a NAR-

SAD Staglin Young Investigator Award to J.Q., as

well as by contributions from the VA’s VISN-22

MIRECC, the Brain Mapping Medical Research

Organization, the Pierson–Lovelace Foundation, the

Ahmanson Foundation, the Tamkim Foundation, the

Jennifer–Jones Simon Foundation, the Capital Group

Companies Charitable Foundation, the Robson Fam-

ily, the Northstar Fund, and a National Center for

Research Resources grant RR12169.

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