Altered microstructure integrity of the amygdalain schizophrenia: a bimodal MRI and DWI study

B. Tomasino1, M. Bellani2, C. Perlini2, G. Rambaldelli2, R. Cerini3, M. Isola4, M. Balestrieri5, S. Calı2,

A. Versace2, R. Pozzi Mucelli3, A. Gasparini3, M. Tansella2 and P. Brambilla1,5*

1 Scientific Institute IRCCS ‘E. Medea ’, Udine, Italy2 Department of Public Health and Community Medicine, Section of Psychiatry and Clinical Psychology, Inter-University Centre for Behavioural

Neurosciences, University of Verona, Verona, Italy3 Department of Morphological and Biomedical Sciences, Section of Radiology, G.B. Rossi Hospital, University of Verona, Verona, Italy4 Department of Medical and Morphological Research, Section of Statistics, University of Udine, Udine, Italy5 Inter-University Centre for Behavioural Neurosciences, Department of Pathology and Experimental and Clinical Medicine, Section of Psychiatry,

University of Udine, Udine, Italy

Background. The amygdala plays a central role in the fronto-limbic network involved in the processing of emotions.

Structural and functional abnormalities of the amygdala have recently been found in schizophrenia, although there

are still contradictory results about its reduced or preserved volumes.

Method. In order to address these contradictory findings and to further elucidate the possibly underlying

pathophysiological process of the amygdala, we employed structural magnetic resonance imaging (MRI) and

diffusion weighted imaging (DWI), exploring amygdalar volume and microstructural changes in 69 patients with

schizophrenia and 72 matched healthy subjects, relating these indices to psychopathological measures.

Results. Measuring water diffusivity, the apparent diffusion coefficients (ADCs) for the right amygdala were found

to be significantly greater in patients with schizophrenia compared with healthy controls, with a trend for abnormally

reduced volumes. Also, significant correlations between mood symptoms and amygdalar volumes were found in

schizophrenia.

Conclusions. We therefore provide evidence that schizophrenia is associated with disrupted tissue organization of

the right amygdala, despite partially preserved size, which may ultimately lead to abnormal emotional processing in

schizophrenia. This result confirms the major role of the amygdala in the pathophysiology of schizophrenia and is

discussed with respect to amygdalar structural and functional abnormalities found in patients suffering from this

illness.

Received 8 May 2009 ; Revised 7 January 2010 ; Accepted 30 March 2010 ; First published online 12 May 2010

Key words : Apparent diffusion coefficient, brain, diffusion-weighted magnetic resonance imaging, magnetic resonance

imaging, morphometry, schizophrenia.

Introduction

The impaired ability to process emotion adequately,

such as affectivity, anxiety and fear, is one of the

most severe deficit in patients with schizophrenia

(Addington & Addington, 2000). Research done on

animal models (LeDoux, 1996, 2000 ; Davis & Whalen,

2001) and on humans (LaBar et al. 1995 ; Morris et al.

1998a, b ; Phelps et al. 2000 ; Adolphs et al. 2005)

supports the key role of the amygdala in fronto-limbic

circuitries involved in the modulation of human

emotions (LeDoux, 1998 ; Aggleton, 2000 ; Aggleton &

Young, 2000). Therefore, it is not surprising that dis-

turbances of the amygdala and its connections have

been implicated in the pathophysiology of schizo-

phrenia.

Patients with schizophrenia show functional ab-

normalities of amygdala activity (Kosaka et al. 2002 ;

Taylor et al. 2002; Takahashi et al. 2004 ; Williams et al.

2004 ; Fahim et al. 2005 ; Das et al. 2007) and an altered

functional connectivity in the amygdalar network

underlying fear perception (Keshavan et al. 2005 ; Das

et al. 2007 ; Leitman et al. 2008). Despite growing re-

search efforts, as to morphological changes, there are

still contradictory results about reduced or preserved

amygdalar volumes and structure in schizophrenia

(Altshuler et al. 2000; Niemann et al. 2000; Joyal et al.

* Address for correspondence : P. Brambilla, Dipartimento di

Patologia e Medicina Clinica e Sperimentale, Cattedra di Psichiatria,

AOU, P. le S. Maria della Misericordia 15, 33100 Udine, Italy.

(Email : paolo.brambilla@uniud.it)

Psychological Medicine (2011), 41, 301–311. f Cambridge University Press 2010doi:10.1017/S0033291710000875

ORIGINAL ARTICLE

2003). Indeed, there are some studies showing size

reductions (Nelson et al. 1998 ; Wright et al. 2000 ; Joyal

et al. 2003 ; Exner et al. 2004 ; Niu et al. 2004 ; Kalus et al.

2005 ; Namiki et al. 2007 ; Garcia-Marti et al. 2008) both

in chronic (Breier et al. 1992 ; Shenton et al. 1992 ; Marsh

et al. 1994 ; Anderson et al. 2002) and first-episode

patients (Hirayasu et al. 1998). A trimodal magnetic

resonance (MR) imaging (MRI) study (Kalus et al.

2005) detected a significant reduction of amygdala raw

volumes in 14 patients with schizophrenia, while

amygdala volumes normalized for intracranial volume

(ICV) did not differ between patients and controls.

In the same study, abnormally reduced diffusional

anisotropy and preserved magnetization transfer ratio

of the amygdala were found in individuals with

schizophrenia. On the contrary, other reports showed

no differences in amygdalar volumes between subjects

with schizophrenia and healthy controls (Altshuler

et al. 2000 ; Niemann et al. 2000 ; Staal et al. 2000 ; Levitt

et al. 2001 ; Szeszko et al. 2003; Tanskanen et al. 2005 ;

Velakoulis et al. 2006) and neither did a recent meta-

analysis study (Vita et al. 2006). Furthermore, there

is disagreement between a small number of post-

mortem studies investigating amygdalar volumes and

the number of neurones which did (Bogerts et al. 1985)

or did not (Heckers et al. 1990 ; Pakkenberg, 1990 ;

Chance et al. 2002) find significant differences between

patients with schizophrenia and normal controls.

A review of MRI studies showed that volume re-

duction involving the hippocampus, parahippo-

campal gyrus, or amygdala is reported in 77% of the

30 analysed studies (McCarley et al. 1999). A meta-

analysis revealed that a further source of variability

in results may depend on whether the amygdalar

volumes have been measured alone or in combination

with the hippocampus (Lawrie & Abukmeil, 1998).

In fact, out of 10 studies measuring the combined

amygdala and hippocampus, a 6% of reduction in the

median volume has been found, whereas out of six

studies measuring the amygdala separately the re-

duction was about 10% (Lawrie & Abukmeil, 1998).

Some studies report a decrease of amygdalar volumes

in individuals with schizophrenia bilaterally (Joyal

et al. 2003 ; Niu et al. 2004), in the right hemisphere only

(Pearlson et al. 1997) or in male patients only (Gur et al.

2000).

Based on the discrepancies of volumetric studies,

neuroimaging techniques that can provide infor-

mation about amygdalar microstructure organization

in schizophrenia would be of benefit. In the present

study, we further investigated amygdalar size and

cytoarchitectural integrity in a larger sample with re-

spect to the above-mentioned studies by combin-

ing structural MRI and diffusion weighted imaging

(DWI) techniques. In particular, MR design including

high-resolution volumetry and diffusion imaging

might provide a new strategy for the detection of

subtle structural alterations that cannot be visualized

by conventional volumetric imaging. Indeed, DWI

examines molecular water mobility within the local

tissue environment, providing important information

on tissue microstructural integrity. The diffusion of

water in the brain is characterized by its apparent

diffusion coefficient (ADC), which represents the

mean diffusivity of water along all directions (Taylor

et al. 2004). Thus, ADC gives potential information

about the size, orientation and tortuosity of both intra-

and extracellular spaces, providing evidence of dis-

ruption when increased (Rovaris et al. 2002). ADC has

also been used to explore regional grey matter micro-

structure, being higher in the case of potential neuron

density alterations or volume deficit (Sykova, 2004 ;

Ardekani et al. 2005 ; Ray et al. 2006).

Given that the deficit of processing emotion appro-

priately is a core symptom of schizophrenia and based

on previous literature showing a key role of the

amygdala in modulating human emotions, we ex-

pected that patients suffering from schizophrenia

would have an abnormally increased water diffusivity

of the amygdala compared with normal controls

resulting in greater ADCs, potentially without any

apparent gross abnormalities. In addition, the corre-

lations between clinical variables and amygdala

microstructure coherence were explored to investigate

whether the presence of abnormal water diffusivity

is also associated with particular psychopathological

dimensions, such as depression.

Method

Subjects

A total of 69 patients with schizophrenia according to

DSM-IV criteria [aged 40.46 (S.D.=12.06) years, 46

males] and 72 healthy control subjects [aged 40.13

(S.D.=11.09) years, 37 males] were studied (Table 1).

Patients were recruited from the geographically

defined catchment area of South Verona (i.e. 100 000

inhabitants) and were being treated by the South

Verona Community-based Mental Health Service

and by other clinics reporting to the South Verona

Psychiatric Care Register (Amaddeo et al. 2009 ;

Amaddeo & Tansella, 2009). Diagnoses for schizo-

phrenia were obtained using the Item Group Checklist

of the Schedule for Clinical Assessment in Neuro-

psychiatry (IGC-SCAN) (WHO, 1992) and confirmed

by the clinical consensus of two staff psychiatrists. The

IGC-SCAN was performed by two trained research

clinical psychologists with extensive experience in

the procedure. In fact, they administered at least

302 B. Tomasino et al.

10 IGC-SCANs with a senior investigator trained in

SCAN, after having conducted several IGC-SCANs.

Moreover, the psychopathological item groups com-

pleted by the two raters were compared, in order to

discuss any major symptom discrepancies. We also

ensured the reliability of the IGC-SCAN diagnoses

by holding regular consensus meetings with the psy-

chiatrists treating the patients and a senior investi-

gator. It is worth noting that the Italian version of the

SCAN was edited by our group (WHO, 1996) and that

our investigators attended specific training courses

held by official trainers in order to learn how to

administer the IGC-SCAN. Subsequently, diagnoses

for schizophrenia were corroborated by the clinical

consensus of two staff psychiatrists, according to the

DSM-IV criteria. Patients with co-morbid psychiatric

disorders, alcohol or substance abuse within the

6 months preceding the study, history of traumatic

head injury with loss of consciousness, epilepsy or

other neurological diseases were excluded. All but

one patient was receiving antipsychotic medications

at the time of scanning. Specifically, 25 were on typical

antipsychotic drugs (18 on haloperidol, four on flu-

phenazine, three on zuclopenthixol) and 43 on atypical

antipsychotic medication (23 olanzapine, 10 clozapine,

seven risperidone, three quetiapine). Of these subjects,

four were taking another antipsychotic at the time

of imaging (two clotiapine, one thioridazine, one

quetiapine). The mean chlorpromazine-equivalent

dose was 221.5 mg (see Table 1). Patients’ clinical in-

formation was retrieved from psychiatric interviews,

the attending psychiatrist and medical charts. Clinical

symptoms were characterized using the Brief Psy-

chiatric Rating Scale (BPRS, 24-item version; Ventura

et al. 2000), which was administered by two trained

research clinical psychologists. The reliability for the

BPRS was established and monitored utilizing pro-

cedures similar to the IGC-SCAN.

Healthy control subjects had no DSM-IV Axis I dis-

orders, as determined by a brief modified version of

the Structured Clinical Interview for DSM-IV, non-

patient version (SCID-NP), no history of psychiatric

disorders among first-degree relatives, no history of

alcohol or substance abuse and no current major

medical illness. Typical control subjects were hospital

or university staff volunteers or subjects undergoing

MR scans for dizziness without evidence of central

nervous system abnormalities on the scan, as de-

termined by the neuroradiologist (R.C.). Dizziness was

due to benign paroxysmal positional vertigo or to non-

toxic labyrinthitis. Control individuals were scanned

only after a full medical history had been taken,

general neurological, otoscopic, and physical exam-

inations carried out, and the patient had completely

Table 1. Sociodemographic and clinical variables for healthy controls and patients with schizophrenia

Healthy

controls (n=72)

Schizophrenia

patients (n=69) Statistics p

Age, years 40.13 (11.09) 40.46 (12.06) t=0.17 0.86

Gender (n) x2=3.40 0.07

Males 37 46

Females 35 23

Caucasian race (n) 72 69

Educational level, years 12.40 (4.19) 9.48 (3.31) t=x4.59 <0.01

Employment status (n) x2=16.27 <0.01

Employed 60 45

Unemployed 0 14

Student/housewife/retired 12 10

Age at onset (years) 26.61 (9.53)

Duration of illness (years) 14.11 (11.04)

Number of hospitalizations 4.30 (8.08)

Lifetime antipsychotic treatment (years) 12.06 (10.75)

BPRS depression–anxiety 12.65 (5.85)

BPRS negative symptoms 11.83 (5.27)

BPRS positive symptoms 11.58 (7.18)

BPRS manic excitement/disorganization 13.62 (7.44)

Mean CPZeq dose (mg) 221.5

BPRS, Brief Psychiatric Rating Scale ; CPZeq, chlorpromazine equivalent dose.

Values are given as mean and standard deviation or number of participants.

Amygdala microstructure in schizophrenia 303

recovered from the dizziness. In addition, none of

the control subjects was on medication at the time of

participation in the study, including drugs for nausea

or vertigo.

All participants gave signed informed consent, after

having understood all issues involved in participation

in the research, which was approved by the Bio-

medical Ethics Committee of the Azienda Ospedaliera

of Verona.

MRI acquisition

MRI scans were acquired with a 1.5T Siemens

Magnetom SymphonyMaestro Class, SyngoMR 2002B

(Siemans, USA). A standard head coil was used for

radio frequency transmission and reception of the

MR signal and restraining foam pads were utilized for

minimizing head motion. T1-weighted images were

first obtained to verify each subject’s head position and

image quality [TR=450 ms, echo time (TE)=14 ms,

flip angle=90x, field of view (FOV)=230r230, 18 slices,

slice thickness=5 mm, matrix size=384r512,

NEX=2]. PD/T2-weighted images were then acquired

(TR=2500 ms, TE=24/121 ms, flip angle=180x,

FOV=230r230, 20 slices, slice thickness=5 mm,

matrix size=410r512, NEX=2), according to an axial

plane parallel to the anterior-posterior commissures

(AC-PC), to exclude focal lesions. Subsequently, a

coronal three-dimensional magnetization-prepared

rapid gradient-echo (MP-RAGE) sequence was ac-

quired (TR=2060 ms, TE=3.9 ms, flip angle=15x,

FOV=176r235, slice thickness=1.25 mm, matrix

size=270r512, TI=1100) to obtain 144 images

covering the entire brain. Diffusion weighted echo-

planar images (EPIs) in the axial plane parallel to

the AC-PC line (TR=3200 ms, TE=94 ms, FOV=230r230, 20 slices, slice thickness=5 mmwith 1.5 mm

gap, matrix size=128r128, echo-train length=5;

these parameters were the same for b=0, b=1000, and

the ADC maps). Specifically, three gradients were

acquired in three orthogonal directions.

MRI data processing and analysis

Anatomical image analysis

Anatomical imaging data were transferred to a per-

sonal computer workstation and analysed using

the BRAINS2 software developed at the University

of Iowa (http://www.psychiatry.uiowa.edu/mhcrc/

IPLpages/BRAINS.htm). The amygdala was traced on

the T1-weighted (MP-RAGE sequence) images in the

coronal plane according to prior methods from our

group (Brambilla et al. 2003). All measurements were

done by a well-trained rater, who was blinded to

subject’s identity and achieved an inter-rater reliability

(IRR) of r=0.98 for the right amygdala raw volumes,

and r=0.91 for the left amygdala raw volumes, estab-

lished by blindly tracing 10 randomly selected scans

and calculated by intra-class correlation coefficient

(ICC). The volumes (ml) were obtained by summing

the volumes of all relevant slices and were expressed

in cm3. ICV was traced in the coronal place along the

border of the brain and included the cerebrospinal

fluid (CSF), dura mater, sinus, optic chiasma, brain-

stem, cerebral and cerebellar matter. The inferior

border did not extend below the base of the cerebel-

lum. ICV measurements were obtained by a well-

trained rater who achieved an IRR of 0.97 measured by

ICCs and established by blindly tracing 10 randomly

selected scans.

Diffusion image analysis

Images were displayed on a commercial Siemens

workstation for the post-processing analyses, includ-

ing the calculation of ADC values. ADC maps were

obtained from the diffusion images with b=1000, ac-

cording to the following equation:xbADC=ln [A(b)/

A(0)], where A(b) is the measured echo magnitude, b is

the measure of diffusion weighting and A(0) is the

echo magnitude without diffusion gradient applied

(Basser & Jones, 2002). The resulting ADC was ex-

pressed in units of 10x5 mm2/s. Circular regions of

interest (ROI) standardised at five pixels (corres-

ponding to an area of 0.16 cm2 and including five

pixels in total) were placed on both right and left

amygdala grey matter on the non-diffusion weighted

(b=0) EPIs. One axial slice below the mesencephalon

was chosen and adjacent slices were checked to ensure

that partial volume effects from CSF were minimized.

Then, the ROIs were automatically transferred to the

corresponding maps to obtain the ADC of water

molecules. Two raters achieved high reliability estab-

lished by tracing eight training scans, as defined by

ICCs over 0.80 calculated by taking into consideration

the mean ADC values. Then, the same rater, blind

to study hypotheses, group assignment, and socio-

demographic/clinical data, measured all scans.

Statistical analyses

SPSS for Windows software, version 17 (SPSS Inc.,

USA), was used to perform all statistical analyses, and

the two-tailed statistical significance level was set at

p<0.05. First, we compared demographic variables

using Student’s t test and Pearson’s x2, as appropriate.

A general linear model (GLM) for repeated measures

(hemisphere as repeated-measures factor) was used to

compare the volumes of amygdala between patients

304 B. Tomasino et al.

with schizophrenia and healthy control subjects with

age, gender and ICV as covariates. The same statistical

method (GLM for repeated measures, hemisphere as

repeated-measures factor) with the covariates age and

gender was performed to compare ADCs of amygdala

between the two groups. The assumption that the

vector of the measures followed a multivariate normal

distribution (Shapiro–Wilk test) and the variance–

covariance matrices were circular in form (Mauchly’s

test) were verified. Univariate GLM was performed to

compare the volumes and the ADCs of left and right

amygdala between patients with schizophrenia and

healthy control participants. The effect size, which is

the difference in the observed means divided by the

pooled standard deviation of the samples, was calcu-

lated for both volumes and ADCmeasurements. Effect

sizes are generally considered small if 0.2, medium if

0.5, and large if 0.8 (Cohen, 1988). Pearson’s corre-

lation and Spearman’s correlation analyses were used

to explore possible association between age and clini-

cal variables, respectively, and amygdalar volumes

and ADC measures. In this case the Bonferroni cor-

rection was used for multiple comparisons consider-

ing three clusters of correlations : chronological age,

clinical variables and scale measures.

Results

Volume and ADC measures

Left and right amygdala volumes did not signifi-

cantly differ between patients with schizophrenia

and healthy individuals [GLM for repeated measures,

hemisphere as repeated-measures factor and age,

gender and ICV as covariates : F(1, 136)=3.22, p=0.07,

observed power=0.43] (Fig. 1b). No interaction be-

tween group and hemisphere was found [F(1, 136)=0.47, p=0.49]. The left amygdala volumes did not

significantly differ between patients with schizo-

phrenia and healthy individuals [univariate GLM, age,

gender and ICV as covariates : F(1, 136)=2.2, p=0.13],

whereas a trend, which did not reach statistical

significance, was observed for the right amygdala

volumes, being smaller in patients in respect to con-

trol subjects [univariate GLM, age, gender and ICV as

covariates : F(1, 136)=3.56, p=0.06] (Table 2).

In regard to ADCs, patients with schizophrenia

had significantly greater ADC values compared with

healthy individuals [GLM for repeated measures,

hemisphere as repeated-measures factor and age and

gender as covariates : F(1, 137)=4.90, p=0.028, ob-

served power=0.59] (Fig. 1a). No interaction between

group and hemisphere was shown [F(1, 137)=0.63,

p=0.43]. Compared with the control group, patients

with schizophrenia had significantly greater values

for the right amygdala [univariate GLM, age and

gender as covariates : F(1, 137)=5.3, p=0.02], whereas

no significant differences were found for the left

amygdala [univariate GLM, age and gender as

covariates : F(1, 137)=2.23, p=0.13) (Table 2). Even

when educational level and occupation were con-

sidered as covariates the ADC values for the right

amygdala remained significantly reduced in patients

suffering from schizophrenia in comparison with

healthy controls (GLM for repeated measures,

p<0.05). Also, no significant differences were found

between the two control subgroups (GLM for repeated

measures, age and gender as covariates, p>0.05).

The calculated effect sizes in our present study were

medium to small for both volumes and ADC values

(Table 2).

Age and clinical variables

No correlation was found between age and amygdala

volumes either in the control group (left side : r=0.08,

95

90

85

80

75

AD

Cs

(mm

2 /s)

Left amygdala Right amygdala

2.0

1.5

1.0

0.5

0

Vol

ume

(cm

2 )

Left amygdala Right amygdala

(a) (b)

Fig. 1. Apparent diffusion coefficients (ADCs) (a) and volumes (b) of amygdala in patients with schizophrenia ( ) and normal

controls (%). Mean ADCs (mm2/s) and mean volumes (cm2) of the left and right amygdala are shown, with vertical bars

representing standard deviations.

Amygdala microstructure in schizophrenia 305

p=0.50 ; right side : r=0.05, p=0.66) or in the schizo-

phrenia group (left side : r=0.11, p=0.34 ; right side :

r=x0.004, p=0.96). Age was significantly correlated

with right amygdala ADC measures in the control

group (r=x0.27, p=0.019), but not in the schizo-

phrenia group (r=x0.19, p=0.11), although it did not

survive the Bonferroni correction (p>0.05). No sig-

nificant associations were found between age and left

amygdala ADCs in both controls (r=x0.14, p=0.22)

and patients (r=0.03, p=0.80).

No significant associations were found between

clinical features (age at illness onset, length of illness,

number of hospitalizations, antipsychotic lifetime

medication, chlorpromazine-equivalent dose) and any

of the anatomical or ADC measures (Spearman corre-

lation coefficients, p>0.05, after Bonferroni cor-

rection).

BPRS scores for depression–anxiety were sig-

nificantly directly correlated with both right and

left amygdalar volumes (r=0.45, p=0.0002 ; r=0.41,

p=0.001, respectively), even after Bonferroni correc-

tion (p=0.0008, p=0.004, respectively). Furthermore,

significant direct correlations were found between

BPRS scores for positive and mania/disorganization

symptoms and left amygdalar volumes (r=0.34,

p=0.008 ; r=0.33, p=0.009, respectively), even after

Bonferroni correction (p=0.032, p=0.036, respect-

ively).

Discussion

This MRI study showed that the ADCs for the right

amygdala were significantly greater in patients with

schizophrenia compared with healthy controls, with a

trend for significantly decreased volumes. By contrast,

left amygdalar size and ADC measures did not sig-

nificantly differ between groups. In this study we

combined the analyses of both amygdalar volumes

and microstructural organization in schizophrenia,

reporting a dissociation between altered integrity

of the right amygdala, as shown by increased ADC

values, and partially preserved volumes.

Microstructural integrity measures versus

volumetric imaging

Our results show that schizophrenia is associated

with an abnormally increased water diffusivity in the

right amygdala, suggesting that changes of amygdalar

tissue composition in schizophrenia may not necess-

arily affect the structural gross volume and should be

investigated at a cytoarchitectural level. DWI provides

evidence of tissue disruption even when conventional

volumetric quantification fails to detect size differ-

ences between patients and controls (DeLisi et al.

2006), being a complementary neuroimaging strategy

to structural imaging. In our study ROIs were placed

in the grey matter of the amygdala, being consistent

with the finding showing grey matter alterations in

schizophrenia (Wright et al. 1999 ; Steen et al. 2006).

ADC has been used by previous DWI studies to ex-

plore grey matter deficits, such as in patients with

traumatic brain injury (Hou et al. 2007 ; Galloway et al.

2008), obsessive–compulsive disorder (Nakamae et al.

2008) or schizophrenia (Shin et al. 2006). Furthermore,

it has been shown by MR spectroscopy (MRS) in-

vestigations that in healthy subjects N-acetyl aspartate

(NAA), a marker of neuronal integrity/functioning,

negatively correlates with ADC (Irwan et al. 2005).

Therefore, increased right amygdalar ADCs reported

in our study are consistent with reduced NAA in the

same region shown in MRS reports (Nasrallah et al.

1994).

Increased ADC values may probably reflect dis-

ruption of the composition of the extracellular inter-

neuronal space, which may cause an alteration in the

Table 2. Left and right amygdalar volumes and ADCs in healthy controls and patients with schizophreniaa

Healthy controls

(n=72)

Patients with

schizophrenia (n=69)

Statistics

F p Effect size

Left amygdala volume (cm3) 1.45 (0.28) 1.38 (0.29) 2.23 0.13 0.24

Right amygdala volume (cm3) 1.53 (0.29) 1.45 (0.31) 3.56 0.06 0.27

Left amygdala ADC (mm2/s) 81.54 (8.21) 83.37 (7.42) 2.23 0.13 0.23

Right amygdala ADC (mm2/s) 81.16 (6.73) 83.97 (9.24) 5.32 0.02 0.34

ADC, Apparent diffusion coefficient ; GLM, general linear model.

Values are given as mean (standard deviation).a GLM for repeated measures was performed to compare volumes (with age, gender and intracranial volume as covariates :

F=3.22, p=0.07) and ADC values (with age and gender as covariates : F=4.90, p=0.028) between patients with schizophrenia

and normal controls. In the Table the statistics of the univariate GLM are reported.

306 B. Tomasino et al.

neuronal and glial cross-talk mediated by neuro-

transmitters. Abnormalities of neurotransmission sys-

tems, such as dopamine, glutamate or c-amino butyric

acid, have strongly been suggested as the core of the

pathophysiology of schizophrenia. A model based on

the glutamate neurotransmitter hypothesis (Aleman &

Kahn, 2005) could explain amygdalar volume re-

ductions in patients with schizophrenia. Prolonged

hyperactivation of the amygdala during psychotic

states could lead to excessive glutamatergic activity

and excitotoxicity, resulting in amygdalar lesions and

long-term hypofunctioning (Hulshoff Pol et al. 2001).

However, what exactly an ADC increase is caused

by is still a matter of investigation, being both intra-

cellular and extracellular space sources of ADC. This

is indeed an average of water molecule diffusivity

within a selected ROI. Volume fraction alterations

of extracellular/intracellular spaces and changes of

neuronal cytoskeleton may therefore increase ADC

measurements (Sykova, 2004). In this perspective, our

findings may also suggest a reduced dendritic arbor-

ization, which has consistently been found in chronic

schizophrenia (Sweet et al. 2009). ADC may also be

used as a potential marker for alterations in neuron

density or for cortical volume deficit (Sykova, 2004 ;

Ardekani et al. 2005). In this regard, elevation of the

sulcal and ventricular CSF volume accompanies cor-

tical brain atrophy (Narr et al. 2003 ; Davis et al. 2004)

and results in a higher ADC. Therefore, increases

in ADC level may suggest replacement of brain

parenchyma by CSF, or volume loss. However, our

results partially match this view, because a disrupted

tissue organization of the right amygdala was found,

despite its partially preserved size. Moreover, a post-

mortem examination on amygdalar neuron number by

Pakkenberg (1990) showed no significant alteration in

subjects with schizophrenia, although only the baso-

lateral nucleus was included and not the whole region.

Right amygdala abnormalities may be involved

in the altered emotional processing in schizophrenia,

as supported by the correlations with affective symp-

toms. Our results are in line with the view propos-

ing that the right hemisphere hypersensitivity to

emotional material may play a crucial role for the

functional basis of schizophrenia (Oepen et al. 1987 ;

Kosaka et al. 2002 ; Exner et al. 2004). It should also be

noted that clinical variables (i.e. age at onset, length

of illness, number of hospitalizations) as well as anti-

psychotic treatment and dose did not apparently affect

amygdalar measurements. In this regard, there are

conflicting findings between studies reporting that

psychotropic medications might affect amygdala

size (Tebartz van Elst et al. 2004) and those suggesting

little influence of neuroleptics (Schneider et al. 1998 ;

Whittaker et al. 2001; Kosaka et al. 2002). Clearly,

studying unmedicated first-episode patients with

schizophrenia will provide a further opportunity

to assess whether microstructural abnormalities are

present prior to the administration of neuroleptic

treatment.

Correlation with psychopathological measures

Interestingly, significant direct correlations were

found between depression–anxiety, mania and posi-

tive symptoms and amygdalar volumes. Psycho-

pathology was measured by the BPRS, which was

divided into subscales in accordance with a prior

validated method (Ruggeri et al. 2005). Positive corre-

lations between amygdalar size and depression

severity have previously been reported in other dis-

eases, such as borderline personality disorder

(Zetzsche et al. 2006) and autism (Juranek et al. 2006). It

is of interest that amygdala dysfunction is implicated

in the development of depressive disorders (Drevets,

1998, 1999) as well as anxiety disorders (Birbaumer

et al. 1998; Garakani et al. 2006 ; Talarovicova et al.

2007). Altered amygdalar activation has been reported

in anxiety-prone subjects who had higher scores on

several measures assessing anxiety proneness (e.g.

neuroticism, trait anxiety and anxiety sensitivity)

(Stein et al. 2007). The association between amygdalar

volume and depressionn–anxiety symptoms suggests

that amygdalar abnormalities may be a predisposing

factor for increased stress sensitivity. Our findings

thus suggest that the amygdala plays a major role in

modulating emotions, including depressive, manic

and anxious symptoms, in schizophrenia and not only

in mood-related disorders. In this regard, it is of

interest to note that a prior diffusion tensor imaging

(DTI) study (Leitman et al. 2007) showed that reduced

fractional anisotropy of the amygdala contributes to

the inability of patients with schizophrenia in de-

coding emotional aspects of speech, which is crucial

for a preserved social communication (Bellani &

Brambilla, 2008 ; Bellani et al. 2009). Therefore,

emotions and anxiety should consistently be taken

into consideration by future imaging studies in

schizophrenia, which may potentially guide further

efforts towards developing treatment interventions for

alleviating affective symptoms.

Limitations of the study

First, in our study, although we recruited a large

number of patients, accurately matching them to con-

trol individuals in order to not increase variability,

we did not involve first-episode patients, our sample

being composed primarily by chronic treated patients.

Therefore, we cannot establish whether the amygdala

Amygdala microstructure in schizophrenia 307

disruption is present early in the course of the illness,

or whether it develops over time as a result of the

illness course or of psychotropic treatment. Second,

part of our control group was selected from individ-

uals undergoing MR scanning for dizziness, which

may represent a methodological limitation. However,

they were fully recovered at the time of imaging and

had no evidence of central nervous system abnor-

malities on the scan; auditory evoked potentials were

not investigated in these subjects. Future studies in-

volving larger samples of high-risk and first-episode

patients, as well as long-term follow-up studies, will

be needed to characterize whether abnormalities in

amygdala structure precede the appearance of symp-

toms, or appear afterwards, as a result of illness

course. Third, the diffusion images were not acquired

during cardiac gated imaging and the diffusion tensor

sequence (DTI) was not collected. However, both DWI

and DTI provide information on subtle tissue organ-

ization even when conventional structural MRI fails

to detect gross anatomical abnormalities (Basser &

Jones, 2002 ; Taylor et al. 2004). In this regard, our

DWI protocol, being relatively short, has the potential

to be added to any conventional volumetric scan,

representing a clinical and scientific advantage for the

evaluation of brain microstructure organization in

schizophrenia in the real world of psychiatric practice.

Conclusions

In conclusion, this study provides evidence of dis-

rupted amygdala cytoarchitecture in the right side, in

the presence of minimally preserved volumes, in a

large sample of patients with schizophrenia represen-

tative of those living in the geographically defined

catchment area of South Verona, Italy (i.e. 100 000 in-

habitants). Such abnormalities may result from a re-

duced microstructural integrity of this area or may

reflect a reduced dendritic arborization, ultimately

leading to abnormal emotional processing in schizo-

phrenia. This study thus confirms the role of the

amygdala in the pathophysiology of schizophrenia,

which may be related to microscopic alterations de-

tectable by the DWI technique added to any conven-

tional scan session.

Acknowledgements

This work was partly supported by grants from the

American Psychiatric Institute for Research and

Education (APIRE Young Minds in Psychiatry

Award), the Italian Ministry for Education, University

and Research (PRIN no. 2005068874), the Veneto

StartCup 2007 to P.B. and by a grant from Regione

Veneto, Italy (159/03, DGRV no. 4087).

Declaration of Interest

None.

References

Addington J, Addington D (2000). Neurocognitive and

social functioning in schizophrenia : a 2.5 year follow-up

study. Schizophrenia Research 44, 47–56.

Adolphs R, Gosselin F, Buchanan TW, Tranel D, Schyns P,

Damasio AR (2005). A mechanism for impaired fear

recognition after amygdala damage. Nature 433, 68–72.

Aggleton JP (2000). The Amygdala : A Functional Analysis.

Oxford University Press : Oxford.

Aggleton JP, Young AW (2000). The enigma of the

amygdala : on its contribution to human emotion.

In Cognitive Neuroscience of Emotion (ed. R. D. Lane,

L. Nadel, G. L. Ahern, J. J. B. Allen, A. W. Kaszniak,

S. Z. Rapcsak and G. E. Schwartz), pp. 106–128. Oxford

University Press : New York.

Aleman A, Kahn RS (2005). Strange feelings : do amygdala

abnormalities dysregulate the emotional brain in

schizophrenia? Progress in Neurobiology 77, 283–298.

Altshuler LL, Bartzokis G, Grieder T, Curran J,

Jimenez T, Leight K, Wilkins J, Gerner R, Mintz J (2000).

An MRI study of temporal lobe structures in men with

bipolar disorder or schizophrenia. Biological Psychiatry 48,

147–162.

Amaddeo F, Burti L, Ruggeri M, Tansella M (2009). Long-

term monitoring and evaluation of a new system of

community-based psychiatric care. Integrating research,

teaching and practice at the University of Verona. Annali

dell’Istituto Superiore di Sanita 45, 43–53.

Amaddeo F, Tansella M (2009). Information systems for

mental health. Epidemiologia e Psichiatria Sociale 18, 1–4.

Anderson JE, Wible CG, McCarley RW, Jakab M, Kasai K,

Shenton ME (2002). An MRI study of temporal lobe

abnormalities and negative symptoms in chronic

schizophrenia. Schizophrenia Research 58, 123–134.

Ardekani BA, Bappal A, D’Angelo D, Ashtari M, Lencz T,

Szeszko PR, Butler PD, Javitt DC, Lim KO, Hrabe J,

Nierenberg J, Branch CA, Hoptman MJ (2005). Brain

morphometry using diffusion-weighted magnetic

resonance imaging : application to schizophrenia.

Neuroreport 16, 1455–1459.

Basser PJ, Jones DK (2002). Diffusion-tensor MRI : theory,

experimental design and data analysis – a technical review.

NMR in Biomedicine 15, 456–467.

Bellani M, Brambilla P (2008). Social cognition,

schizophrenia and brain imaging. Epidemiologia e Psichiatria

Sociale 17, 117–119.

Bellani M, Marzi CA, Brambilla P (2009). Interhemispheric

communication in schizophrenia. Epidemiologia e Psichiatria

Sociale 18, 104–106.

Birbaumer N, Grodd W, Diedrich O, Klose U, Erb M,

Lotze M, Schneider F, Weiss U, Flor H (1998). fMRI

reveals amygdala activation to human faces in social

phobics. Neuroreport 9, 1223–1226.

Bogerts B, Meertz E, Schonfeldt-Bausch R (1985). Basal

ganglia and limbic system pathology in schizophrenia.

308 B. Tomasino et al.

A morphometric study of brain volume and shrinkage.

Archives of General Psychiatry 42, 784–791.

Brambilla P, Harenski K, Nicoletti M, Sassi RB,

Mallinger AG, Frank E, Kupfer DJ, Keshavan MS,

Soares JC (2003). MRI investigation of temporal lobe

structures in bipolar patients. Journal of Psychiatry Research

37, 287–295.

Breier A, Buchanan RW, Elkashef A, Munson RC,

Kirkpatrick B, Gellad F (1992). Brain morphology and

schizophrenia. A magnetic resonance imaging study of

limbic, prefrontal cortex, and caudate structures. Archives

of General Psychiatry 49, 921–926.

Chance SA, Esiri MM, Crow TJ (2002). Amygdala volume

in schizophrenia : post-mortem study and review of

magnetic resonance imaging findings. British Journal of

Psychiatry 180, 331–338.

Cohen J (1988). Statistical Power Analysis for the Behavioral

Sciences. Lawrence Erlbaum Associates : Hillsdale, NJ.

Das P, Kemp AH, Flynn G, Harris AW, Liddell BJ,

Whitford TJ, Peduto A, Gordon E, Williams LM (2007).

Functional disconnections in the direct and indirect

amygdala pathways for fear processing in schizophrenia.

Schizophrenia Research 90, 284–294.

Davis KA, Kwon A, Cardenas VA, Deicken RF (2004).

Decreased cortical gray and cerebral white matter in male

patients with familial bipolar I disorder. Journal of Affective

Disorders 82, 475–485.

Davis M, Whalen PJ (2001). The amygdala : vigilance and

emotion. Molecular Psychiatry 6, 13–34.

DeLisi LE, Szulc KU, Bertisch H, Majcher M, Brown K,

Bappal A, Branch CA, Ardekani BA (2006). Early

detection of schizophrenia by diffusion weighted imaging.

Psychiatry Research 148, 61–66.

Drevets WC (1998). Functional neuroimaging studies of

depression : the anatomy of melancholia. Annual Review of

Medicine 49, 341–361.

Drevets WC (1999). Prefrontal cortical–amygdalar

metabolism in major depression. In Annals of the

New York Academy of Sciences : Advancing from the

Ventral Striatum to the Extended Amygdala, vol. 877

(ed. J. F. McGinty), pp. 614–637. New York Academy of

Sciences : New York.

Exner C, Boucsein K, Degner D, Irle E, Weniger G (2004).

Impaired emotional learning and reduced amygdala size in

schizophrenia : a 3-month follow-up. Schizophrenia Research

71, 493–503.

Fahim C, Stip E, Mancini-Marie A, Mensour B, Boulay LJ,

Leroux JM, Beaudoin G, Bourgouin P, Beauregard M

(2005). Brain activity during emotionally negative

pictures in schizophrenia with and without flat affect : an

fMRI study. Psychiatry Research 140, 1–15.

Galloway NR, Tong KA, Ashwal S, Oyoyo U, Obenaus A

(2008). Imaging improves outcome prediction in pediatric

traumatic brain injury. Journal of Neurotrauma 25,

1153–1162.

Garakani A, Mathew SJ, Charney DS (2006). Neurobiology

of anxiety disorders and implications for treatment. Mount

Sinai Journal of Medicine 73, 941–949.

Garcia-Marti G, Aguilar EJ, Lull JJ, Marti-Bonmati L,

Escarti MJ, Manjon JV, Moratal D, Robles M, Sanjuan J

(2008). Schizophrenia with auditory hallucinations : a

voxel-based morphometry study. Progress in

Neuro-Psychopharmacology, Biological Psychiatry 32, 72–80.

Gur RE, Turetsky BI, Cowell PE, Finkelman C, Maany V,

Grossman RI, Arnold SE, Bilker WB, Gur RC (2000).

Temporolimbic volume reductions in schizophrenia.

Archives of General Psychiatry 57, 769–775.

Heckers S, Heinsen H, Heinsen YC, Beckmann H (1990).

Limbic structures and lateral ventricle in schizophrenia.

A quantitative postmortem study. Archives of General

Psychiatry 47, 1016–1022.

Hirayasu Y, Shenton ME, Salisbury DF, Dickey CC,

Fischer IA, Mazzoni P, Kisler T, Arakaki H, Kwon JS,

Anderson JE, Yurgelun-Todd D, Tohen M, McCarley RW

(1998). Lower left temporal lobe MRI volumes in patients

with first-episode schizophrenia compared with

psychotic patients with first-episode affective disorder

and normal subjects. American Journal of Psychiatry 155,

1384–1391.

Hou DJ, Tong KA, Ashwal S, Oyoyo U, Joo E, Shutter L,

Obenaus A (2007). Diffusion-weighted magnetic resonance

imaging improves outcome prediction in adult traumatic

brain injury. Journal of Neurotrauma 24, 1558–1569.

Hulshoff Pol HE, Schnack HG, Mandl RC, van Haren NE,

Koning H, Collins DL, Evans AC, Kahn RS (2001). Focal

gray matter density changes in schizophrenia. Archives of

General Psychiatry 58, 1118–1125.

Irwan R, Sijens PE, Potze JH, Oudkerk M (2005).

Correlation of proton MR spectroscopy and diffusion

tensor imaging. Magnetic Resonance Imaging 23, 851–858.

Joyal CC, Laakso MP, Tiihonen J, Syvalahti E, Vilkman H,

Laakso A, Alakare B, Rakkolainen V, Salokangas RK,

Hietala J (2003). The amygdala and schizophrenia : a

volumetric magnetic resonance imaging study in first-

episode, neuroleptic-naive patients. Biological Psychiatry

54, 1302–1304.

Juranek J, Filipek PA, Berenji GR, Modahl C, Osann K,

Spence MA (2006). Association between amygdala

volume and anxiety level : magnetic resonance imaging

(MRI) study in autistic children. Journal of Child Neurology

21, 1051–1058.

Kalus P, Slotboom J, Gallinat J, Wiest R, Ozdoba C,

Federspiel A, Strik WK, Buri C, Schroth G, Kiefer C

(2005). The amygdala in schizophrenia : a trimodal

magnetic resonance imaging study. Neuroscience Letters

375, 151–156.

Keshavan MS, Diwadkar VA, Rosenberg DR (2005).

Developmental biomarkers in schizophrenia and other

psychiatric disorders : common origins, different

trajectories ? Epidemiologia e Psichiatria Sociale 14, 188–193.

Kosaka H, Omori M, Murata T, Iidaka T, Yamada H, Okada

T, Takahashi T, Sadato N, Itoh H, Yonekura Y, Wada Y

(2002). Differential amygdala response during facial

recognition in patients with schizophrenia : an fMRI study.

Schizophrenia Research 57, 87–95.

LaBar KS, LeDoux JE, Spencer DD, Phelps EA (1995).

Impaired fear conditioning following unilateral temporal

lobectomy in humans. Journal of Neuroscience 15, 6846–6855.

Lawrie SM, Abukmeil SS (1998). Brain abnormality in

schizophrenia. A systematic and quantitative review of

Amygdala microstructure in schizophrenia 309

volumetric magnetic resonance imaging studies. British

Journal of Psychiatry 172, 110–120.

LeDoux J (1998). Fear and the brain : where have we been,

and where are we going? Biological Psychiatry 44,

1229–1238.

LeDoux JE (1996). The Emotional Brain : The Mysterious

Underpinnings of Emotional Life. Simon and Schuster :

New York.

LeDoux JE (2000). Emotion circuits in the brain. Annual

Review of Neuroscience 23, 155–184.

Leitman DI, Hoptman MJ, Foxe JJ, Saccente E, Wylie GR,

Nierenberg J, Jalbrzikowski M, Lim KO, Javitt DC (2007).

The neural substrates of impaired prosodic detection in

schizophrenia and its sensorial antecedents. American

Journal of Psychiatry 164, 474–482.

Leitman DI, Loughead J, Wolf DH, Ruparel K, Kohler CG,

Elliott MA, Bilker WB, Gur RE, Gur RC (2008). Abnormal

superior temporal connectivity during fear perception in

schizophrenia. Schizophrenia Bulletin 34, 673–678.

Levitt JG, Blanton RE, Caplan R, Asarnow R, Guthrie D,

Toga AW, Capetillo-Cunliffe L, McCracken JT (2001).

Medial temporal lobe in childhood-onset schizophrenia.

Psychiatry Research 108, 17–27.

Marsh L, Suddath RL, Higgins N, Weinberger DR (1994).

Medial temporal-lobe structures in schizophrenia –

relationship of size to duration of illness. Schizophrenia

Research 11, 225–238.

McCarley RW, Wible CG, Frumin M, Hirayasu Y, Levitt JJ,

Fischer IA, Shenton ME (1999). MRI anatomy of

schizophrenia. Biological Psychiatry 45, 1099–1119.

Morris JS, Friston KJ, Buchel C, Frith CD, Young AW,

Calder AJ, Dolan RJ (1998a). A neuromodulatory role for

the human amygdala in processing emotional facial

expressions. Brain 121, 47–57.

Morris JS, Ohman A, Dolan RJ (1998b). Conscious and

unconscious emotional learning in the human amygdala.

Nature 393, 467–470.

Nakamae T, Narumoto J, Shibata K, Matsumoto R,

Kitabayashi Y, Yoshida T, Yamada K, Nishimura T,

Fukui K (2008). Alteration of fractional anisotropy and

apparent diffusion coefficient in obsessive–compulsive

disorder : a diffusion tensor imaging study. Progress in

Neuro-psychopharmacology and Biological Psychiatry 32,

1221–1226.

Namiki C, Hirao K, Yamada M, Hanakawa T, Fukuyama H,

Hayashi T, Murai T (2007). Impaired facial emotion

recognition and reduced amygdalar volume in

schizophrenia. Psychiatry Research 156, 23–32.

Narr KL, Sharma T, Woods RP, Thompson PM, Sowell ER,

Rex D, Kim S, Asuncion D, Jang S, Mazziotta J, Toga AW

(2003). Increases in regional subarachnoid CSF without

apparent cortical gray matter deficits in schizophrenia :

modulating effects of sex and age. American Journal of

Psychiatry 160, 2169–2180.

Nasrallah HA, Skinner TE, Schmalbrock P, Robitaille PM

(1994). Proton magnetic resonance spectroscopy (1H MRS)

of the hippocampal formation in schizophrenia : a pilot

study. British Journal of Psychiatry 165, 481–485.

Nelson MD, Saykin AJ, Flashman LA, Riordan HJ (1998).

Hippocampal volume reduction in schizophrenia as

assessed by magnetic resonance imaging : a meta-analytic

study. Archives of General Psychiatry 55, 433–440.

Niemann K, Hammers A, Coenen VA, Thron A,

Klosterkotter J (2000). Evidence of a smaller left

hippocampus and left temporal horn in both patients with

first episode schizophrenia and normal control subjects.

Psychiatry Research 99, 93–110.

Niu L, Matsui M, Zhou SY, Hagino H, Takahashi T,

Yoneyama E, Kawasaki Y, Suzuki M, Seto H, Ono T,

Kurachi M (2004). Volume reduction of the amygdala in

patients with schizophrenia : a magnetic resonance

imaging study. Psychiatry Research 132, 41–51.

Oepen G, Funfgeld M, Holl T, Zimmermann P, Landis T,

Regard M (1987). Schizophrenia – an emotional

hypersensitivity of the right cerebral hemisphere.

International Journal of Psychophysiology 5, 261–264.

Pakkenberg B (1990). Pronounced reduction of total neuron

number in mediodorsal thalamic nucleus and nucleus

accumbens in schizophrenics. Archives of General Psychiatry

47, 1023–1028.

Pearlson GD, Barta PE, Powers RE, Menon RR, Richards

SS, Aylward EH, Federman EB, Chase GA, Petty RG,

Tien AY (1997). Ziskind-Somerfeld Research Award 1996.

Medial and superior temporal gyral volumes and cerebral

asymmetry in schizophrenia versus bipolar disorder.

Biological Psychiatry 41, 1–14.

Phelps EA, O’Connor KJ, Cunningham WA, Funayama ES,

Gatenby JC, Gore JC, Banaji MR (2000). Performance on

indirect measures of race evaluation predicts amygdala

activation. Journal of Cognitive Neuroscience 12, 729–738.

Ray KM, Wang H, Chu Y, Chen YF, Bert A, Hasso AN, Su

MY (2006). Mild cognitive impairment : apparent diffusion

coefficient in regional gray matter and white matter

structures. Radiology 24, 197–205.

Rovaris M, Bozzali M, Iannucci G, Ghezzi A, Caputo D,

Montanari E, Bertolotto A, Bergamaschi R, Capra R,

Mancardi GL, Martinelli V, Comi G, Filippi M (2002).

Assessment of normal-appearing white and gray matter

in patients with primary progressive multiple sclerosis – a

diffusion-tensor magnetic resonance imaging study.

Archives of Neurology 59, 1406–1412.

Ruggeri M, Koeter M, Schene A, Bonetto C,

Vazquez-Barquero JL, Becker T, Knapp M, Knudsen HC,

Tansella M, Thornicroft G (2005). Factor solution of the

BPRS-expanded version in schizophrenic outpatients

living in five European countries. Schizophrenia Research

75, 107–117.

Schneider F, Weiss U, Kessler C, Salloum JB, Posse S,

Grodd W, Muller-Gartner HW (1998). Differential

amygdala activation in schizophrenia during sadness.

Schizophrenia Research 34, 133–142.

Shenton ME, Kikinis R, Jolesz FA, Pollak SD, Lemay M,

Wible CG, Hokama H, Martin J, Metcalf D, Coleman M,

McCarley RW (1992). Abnormalities of the left

temporal-lobe and thought-disorder in schizophrenia – a

quantitative magnetic-resonance-imaging study. New

England Journal of Medicine 327, 604–612.

Shin YW, Kwon JS, Ha TH, Park HJ, Kim DJ, Hong SB,

Moon WJ, Lee JM, Kim IY, Kim SI, Chung EC (2006).

Increased water diffusivity in the frontal and temporal

310 B. Tomasino et al.

cortices of schizophrenic patients. Neuroimage 30,

1285–1291.

Staal WG, Pol HEH, Schnack HG, Hoogendoorn MLC,

Jellema K, Kahn RS (2000). Structural brain abnormalities

in patients with schizophrenia and their healthy siblings.

American Journal of Psychiatry 157, 416–421.

Steen RG, Mull C, McClure R, Hamer RM, Lieberman JA

(2006). Brain volume in first-episode schizophrenia :

systematic review and meta-analysis of magnetic

resonance imaging studies. British Journal of Psychiatry

188, 510–518.

Stein MB, Simmons AN, Feinstein JS, Paulus MP (2007).

Increased amygdala and insula activation during emotion

processing in anxiety-prone subjects. American Journal of

Psychiatry 164, 318–327.

Sweet RA, Henteleff RA, Zhang W, Sampson AR,

Lewis DA (2009). Reduced dendritic spine density in

auditory cortex of subjects with schizophrenia.

Neuropsychopharmacology 34, 374–389.

Sykova E (2004). Diffusion properties of the brain in health

and disease. Neurochemistry International 45, 453–466.

Szeszko PR, Goldberg E, Gunduz-Bruce H, Ashtari M,

Robinson D, Malhotra AK, Lencz T, Bates J, Crandall DT,

Kane JM, Bilder RM (2003). Smaller anterior hippocampal

formation volume in antipsychotic-naive patients with

first-episode schizophrenia. American Journal of Psychiatry

160, 2190–2197.

Takahashi H, Koeda M, Oda K, Matsuda T, Matsushima E,

Matsuura M, Asai K, Okubo Y (2004). An fMRI study of

differential neural response to affective pictures in

schizophrenia. Neuroimage 22, 1247–1254.

Talarovicova A, Krskova L, Kiss A (2007). Some assessments

of the amygdala role in suprahypothalamic

neuroendocrine regulation : a minireview. Endocrine

Regulations 41, 155–162.

Tanskanen P, Veijola JM, Piippo UK, Haapea M,

Miettunen JA, Pyhtinen J, Bullmore ET, Jones PB,

Isohanni MK (2005). Hippocampus and amygdala

volumes in schizophrenia and other psychoses in the

Northern Finland 1966 birth cohort. Schizophrenia Research

75, 283–294.

Taylor SF, Liberzon I, Decker LR, Koeppe RA (2002).

A functional anatomic study of emotion in schizophrenia.

Schizophrenia Research 58, 159–172.

Taylor WD, Hsu E, Krishnan KR, MacFall JR (2004).

Diffusion tensor imaging : background, potential, and

utility in psychiatric research. Biological Psychiatry 55,

201–207.

Tebartz van Elst L, Baumer D, Ebert D, Trimble MR (2004).

Chronic antidopaminergic medication might affect

amygdala structure in patients with schizophrenia.

Pharmacopsychiatry 37, 217–220.

Velakoulis D, Wood SJ, Wong MT, McGorry PD, Yung A,

Phillips L, Smith D, Proffitt T, Desmond P, Pantelis C

(2006). Hippocampal and amygdala volumes according

to psychosis stage and diagnosis : a magnetic resonance

imaging study of chronic schizophrenia, first-episode

psychosis, and ultra-high-risk individuals. Archives of

General Psychiatry 63, 139–149.

Ventura J, Nuechterlein KH, Subotnik KL (2000). Symptom

dimensions in recent-onset schizophrenia and mania : a

principal components analysis of the 24-item Brief

Psychiatric Rating Scale. Psychiatry Research 97, 129–135.

Vita A, De Peri L, Silenzi C, Dieci A (2006). Brain

morphology in first-episode schizophrenia : a meta-

analysis of quantitative magnetic resonance imaging

studies. Schizophrenia Research 82, 75–88.

Whittaker JF, Deakin JF, Tomenson B (2001). Face

processing in schizophrenia : defining the deficit.

Psychological Medicine 31, 499–507.

WHO (1992). Schedules for Clinical Assessment in

Neuropsychiatry. World Health Organization : Geneva.

WHO (1996). Schede di valutazione clinica in

neuropsichiatria. SCAN 2.1 (M. Tansella, M. Nardini,

series editors). Il Pensiero Scientifico Editore : Roma.

Williams LM, Brown KJ, Das P, Boucsein W, Sokolov EN,

Brammer MJ, Olivieri G, Peduto A, Gordon E (2004). The

dynamics of cortico-amygdala and autonomic activity over

the experimental time course of fear perception. Brain

Research. Cognitive Brain Research 21, 114–123.

Wright IC, Ellison ZR, Sharma T, Friston KJ, Murray RM,

McGuire PK (1999). Mapping of grey matter changes in

schizophrenia. Schizophrenia Research 35, 1–14.

Wright IC, Rabe-Hesketh S, Woodruff PW, David AS,

Murray RM, Bullmore ET (2000). Meta-analysis of

regional brain volumes in schizophrenia. American Journal

of Psychiatry 157, 16–25.

Zetzsche T, Frodl T, Preuss UW, Schmitt G, Seifert D,

Leinsinger G, Born C, Reiser M, Moller HJ, Meisenzahl

EM (2006). Amygdala volume and depressive symptoms

in patients with borderline personality disorder. Biological

Psychiatry 60, 302–310.

Amygdala microstructure in schizophrenia 311