Similarities in the pattern of regional brain dysfunction in negative schizophrenia and unipolar...

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Rug. Nem-Psychopharmacol. & Bol. Psychid. 2001, Vol. 25, pp. 993-1009

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SIMILARITIES IN THE PATTERN OF REGIONAL BRAIN DYSFUNCTION IN NEGATIVE SCHIZOPHRENLA AND

UNIPOLAR DEPRESSION: A SINGLE PROTON EMISSION-COMPUTED TOMOGRAPHY AND AUDITORY EVOKED POTENTIALS SSTUDY

VESNA MEDVED’, RATKO PETROVIC’, VELIMIR ISGUM3, LAJOS SZIROVICZA4 and LJUBOMIR HOTUJAC’

‘Psychiatric Clinic, *Nuclear Medicine Clinic and 3Neurological Clinic, University Clinical Hospital Centre Rebro, 41nstitute for Anthropological Research, Zagreb, CROATIA

(Final form, April 2001)

Abstract

Vesna Medved, Ratko PetroviC, Velimir ISgum, Lajos Szirovicza and Ljubomir Hotujac: Similarities in the Pattern of Regional Brain Dysfunction in Negative Schizophrenia and Unipolar Depression: A Single Photon Emission-Computed Tomography and Auditory Evoked Potentials Study. Prog. Neuro- Psychophurmacol. & Biol. Psychiut. 2001,2& pp. 993-1009.82001 Elsevier Scimce Inc.

1. Negative schizophrenic and unipolar depressive patients were clinically assessed. In addition to this SANS and HRSD tests were administered.

2. SPECT and AEP measurements were provided. SPECT resulted in quantified brain blood perfusion, by means of average “count/pixel” values in the brain regions of interest, AEPs resulted in stored multichannel signal waveforms.

3. Statistical analyses of blood perfusion measurement data revealed an overall similarity between these two disorders in the majority of brain regions. An exception to this are the regions: inferior temporalis, inferior occipitalis, hippocampus and the anterior basal ganglia. Both diagnostic groups manifested hypofrontality. In general, hypoperfusion of the left hemisphere was found, albeit displaying different patterns in the two groups investigated.

4. AEP latencies were prolonged and found to be similar in both diagnostic groups, whilst AEP amplitudes were smaller in schizophrenics compared to depressives.

Kevwords: auditory evoked potentials (AEPs), biological psychiatry, depression, frontal brain regions, schizophrenia, single photon emission-computed tomography (SPECT)

Abbreviations: auditory evoked potentials (AEP), computer tomography (CT), Hamilton rating scale for depression (HRSD), orbitomeatal line (OM), positron emission tomography (PET), regional cerebral

993

994 V. Medved et al.

blood flow (rCBF), region of interest (ROB, single photon emission-computed tomography (SPECT), scale for the assessment of negative symptoms (SANS).

Introduction

The clinical overlap between symptoms of negative schizophrenia and symptoms of unipolar

depression is an established fact. Reports indicate the existence of a partial similarity between the

following common symptoms: loss of energy and willpower, anchedonia, associality (Whiteford et al.

1987), nivelation of affect (Boeringa and Castellani 1982), loss of motivation, physical anergy, loss of

recreational interests, diminished sexual interest, inability to develop intimate relations, as well as to keep

previously developed relations with friends and peers (Kitamura and Suga, 1991). This raises the

question of a possible similarity of patterns in the brain dysfunction of these two psychiatric disorders.

Regional deficit of functional (neural) activity has already been investigated by measuring the regional

cerebral blood flow using 99mTc-HMPA0 single photon emission-computed tomography - (SPECT) and

auditory evoked potentials (AEP) - P300, which reflect the metabolic and electrophysiolgical status of the

living human brain, SPECT and PET methods applied to schizophrenic and depressive patients have

resulted in a number of different findings. In schizophrenics, the general trend accentuates frontal

hypometabolism (Chua and McKemra 1995, Andreasen et al. 1997, Spence et al. 1998) and a strong

association between negative symptoms and hypofrontality has been reported (Ebmeier et al. 1993,

Molina et all. 1997) whereas functional brain studies of affective disorders rarely postulate

hypofrontality (Vasile et al. 1996, Ogura et al. 1998, Galynker et al. 1998). Furthermore, findings

considered robust for schizophrenia include a decrease in P300 amplitude (Salisbury et al. 1998) and an

increase in P300 latency (Coburn et al. 1998). Papers reporting a decrease in P300 amplitude in

depressive disorders lead to the conclusion (Diner et al. 1985) that the P300 amplitude is influenced, not

only by cognitive, but also by emotional factors. Apart from this, prolonged latency is also usually found

in depressives (Vandoolaeghe et al. 1998).

In this study we examine the relationship between regional cerebral blood flow and P300 in patients

with negative schizophrenia and unipolar depression. The aim was to research the topography of

metabolic and electrophysiological dysfunctions, and their possible similarities, in view of the two

psychiatric disorders above.

SPECT and AEPs in negative schizophrenia and unipolar depression

Methods

Patient Ponulation

995

Subjects for the study were recruited at the Psychiatric Clinic, University Hospital Centre Rebro,

Zagreb, Croatia. All subjects met the DSM-III-R criteria for schizophrenia or depression (American

Psychiatric Association, 1987). Psychopathological data were obtained by the first co-author of this paper

during a semi-structured interview using SANS (Andreasen 1983) and Hamilton rating scales (Hamilton

1960). The study encompassed 20 female patients diagnosed with negative schizophrenia (mean age 32.1,

ranging from 24 to 40), and 13 with unipolar depression (mean age 47.8, ranging from 33 to 55). The

mean educational level was 12 years for schizophrenics and 10 for depressives. The mean duration of

illness was 7 years for schizophrenics and 8 years for depressives. The subjects manifested current

psychopathology and were not regarded as being in remission. All schizophrenic subjects were receiving

treatment consisting of typical antipsychotics (mean chlorpromazine - equivalent dose = 959.37 mg/day).

Depressives were undergoing treatment consisting of tricyclic or tetracyclic antidepressives and

anxiolytics. Patients had not previously received atypical neuroleptic or electroconvulsive therapy. All

patients were righthanded. According to the set criteria, those over 55 years of age, those taking drugs

that might induce EEG-changes, and those with a history of neurological illnesses, alcoholism or

dependencies were excluded from the study. All subjects featured an average IQ and readily consented in

writing to participate once the aims and procedures of this study had been explained to them.

Study Design

The study was carried out during a period subsequent to one to two weeks of stay in the hospital, once

the patient’s state had stabilized. Each participant was subjected to the two assessment methods

mentioned above. The findings for five (AEPs) and four (SPECTs) for different schizophrenic, and two

depressive patients were excluded from the study due to technical problems. Rating scales and AEP

recordings were made for each patient on the same day; SPECT was administered a day later.

Assessment Instruments

The SPECT procedure was carried out in a darkened sound-proof room. Image acquisition began 15

min after an i.v. radiotracer injection of 15 mCi (550 Mbq) of Tc99m-HMPA0. Measurements were made


using the double-headed rotating scintillation gamma camera Siemens ZLC 37, and lasted for 20 minutes.

Brain slices, 4.6 mm apart, parallel to the orbitomeatal line (OM), were recorded. Recording was done in

120 projections (60 from each camera head) at 3 distances. Data obtained were stored in an ADAC 33000

computer which provided visualization of perfusion records and numerical processing of digitized data.

Quantification was performed in the following manner, and included four slices chosen for numerical

processing. The first slice was 2.5 cm above the OM line, with ROB for the inferior temporalis (IT) and

the hippocampus (HI). The second slice was 5 cm above the OM line with ROIs for the gyms frontalis

superior (SF3), the gyms frontalis inferior (IF), the superior temporalis (ST), the inferior occipitalis (IO),

the anterior basal ganglia (BG) and the thalamus (TH). The third slice was 7.5 cm above the OM line

with ROIs for the gyms frontalis superior (SF2), the gyms frontalis medialis (MF), the central region

(C2), the inferior parietalis (IP) and the superior occipitalis (SO). The fourth slice was 9 cm above the

OM line with ROIs for the gyms frontalis superior (SFI), the central region (Cl) and the superior

parietalis (SP) (32 regions in all).

During the process of image quantification, the number of pixels in each ROI was counted, so that

“count/pixel” for a particular region were chosen as raw measurement variables. (These quantities are, in

fact, average values of perfusion measures for corresponding ROIs). Since it was not possible to

determine the dosage of radioactivity entering brain cells, measurement on an absolute scale was not

possible. “Count/pixel” as raw measurement data were suitable for some quantitative comparisons, for

instance, when evaluating brain hemispheric symmetry. In some other quantitative analyses, the mode for

normalization of raw measurement data applied is as follows. The values for particular regions were

divided by the average value for the corresponding hemisphere, at a certain slice level. Values normalized

in this manner (amounting to approximately 1) made it possible to draw inter-subject comparisons

between measurement results. Further, values normalized in this way also made it possible to draw

comparisons between particular regions in the sense frontal-occipital for each patient.

Scalp EEGs were recorded using Ag-AgCl electrodes placed at: FPZ, FPl, FP2, F7, F3, FZ, F4, F8,

T3, C3, CZ, C4, T4, T5, P3, PZ, P4, T6, 01, OZ and 02 locations, according to the International lo/20

system (Brain Atlas 2.30 System by Bio-Logic Systems Corp.). AEPs were obtained using an oddball

task. Stimuli consisted of a 1 -kHz tone-burst (frequent, nontarget stimulus) and a 2-kHz tone-burst (rare,

target stimulus). Stimuli were presented binaurally in random order at 70 dB. The stimulus plateau was

90 ms, with rise and fall times of 10 ms. Patients were instructed to count the number of rare tones and to

report their count for each trial. Analysis time was 512 ms. AEPs were averaged separately for rare and

frequent stimuli. Multichannel AEP curves thus obtained, expressed in pV, were stored in computer

memory for further processing.

SPECT and AEPs in negative schizophrenia and unipolar depression 997

Data Analysis

Due to the complex and multivariable nature of the interrelationships between measurement variables,

several signal processing methods, and a battery of parametric and non-parametric statistical testing

methods were applied in their comprehensive analysis (Medved 1995). The choice of a certain method of

analysis followed only after testing the character of probability distribution of the corresponding

measurement variable, so that one among parametric (normal distribution) or non-parametric

(distribution deviating from normal) methods were able to be used. In all analyses, 0.05 has been used as

the significance level criterion.

Global scores of rating scales applied were compared using the Student-t test, provided the same

global scores had been previously tested for normality using the Smimov-Kolmogorov test.

To provide quantitative insight into the possible differences between the measured values of rCBF

between the two diagnostic groups, a univariant analysis of variance with discriminating procedure was

provided for each identified cerebral region. Normalised perfusion values for regions were used as

variables, as explained previously (Assessment Instruments). In order to evaluate differences in rCBF

between corresponding regions in two diagnostic groups, a Student-t test was used to determine the

significance of differences in the arithmetic means of two independent samples, provided that

homogeneity of variance has been established previously. The differentiation in perfusion between brain

hemispheres was determined based on raw measurement values (“count/pixel”) - as explained in the

Assessment Instruments section - by direct comparison of perfusion values of corresponding left-right

brain regions. In the statistical comparison of mean perfusion values of particular left-right regions the

significance t-test for differences in paired samples was used, with an 0.05 level of significance.

Comparisons were done separately for subsample shizophrenia (SCH) (N=l5) and subsample depression

(DEP) (N=ll).

Multichannel AEP signals in each individual recording were processed by calculating the mean square

waveform. This in turn served as the basis for finding the latency value for each particular record, which

was done in an interval ranging from 250 to 512 ms (Regan 1987) using the software algorithm. Further,

at each particular electrode position, average waveforms for SCH and DEP groups were calculated (so-

called grand-average waveforms).


Results

The average total score on SANS for the group of schizophrenic patients was 87.43, and 54.54 for the

group of depressive patients. The average total score on the Hamilton scale for the group of schizophrenic

patients was 27.93, and 26.81 for depressives. It was determined that there were no significant deviations

form normality. The difference in the total score on SANS between groups was highly significant

statistically (p < O.OOl), whereas the difference in the Hamilton score was not (p > 0.05). This confirms

that SANS generally allows for good discriminability for the two diseases concerned, unlike the Hamilton

scale.

SPECT Results

Table 1 shows the overall results of determined significances of differences in rCBF measured values

between the two diagnostic groups and includes the values of particular arithmetic means.

This shows that 8 out of 32 brain regions differ significantly, whilst the remaining 24 do not. Regions that

displayed a significant difference in perfusion between the SCH and DEP groups are:

- the IT and IO regions, which displayed a significantly lower perfusion in SCH in relation to DEP

bilaterally,

- the HI region, which displayed a significantly higher perfusion in SCH in relation to DEP bilaterally,

- the right BG region which displayed a significantly higher perfusion in SCH in relation to DEP,

whilst at the left side the difference being in the same sense, albeit not significant (p=O.O6),

- the right ST region which displayed a significantly lower perfusion in SCH in relation to DEP.

Distributions of normalised rCBF values in particular brain regions for each diagnostic category are

graphically presented in Fig. 1 (taken as an example), which serves to illustrate data in Table 1.

In Table 1, the SF2 and SF3 values for both left and right show that hypofrontality is present in both

disorders.

Table 2 shows the results of differentiation in perfusion between brain hemispheres in SCH and DEP

groups, respectively. Arithmetic mean values are included.

A significant asymmetry appeared in a large number of regions. The perfusion values for the left side

are regularly lower than those for the right side. This indicates a global hypoperfusion of the left

hemisphere.

SPECT and AEPs in negative schizophrenia and unipolar depression

Table 1

Differentiation in Cerebral Blood Perfusion in Particular Regions Between Schizophrenia (SCH) and Depression (DEP) Groups

Region

Right Hemisphere

SCH DEP pa

Left Hemisphere

SCH DEP pa

Gyrus frontalis superior (SFl) Gyrus frontalis superior (SF2) Gyrus frontalis superior (SF3) Gyrus frontalis medialis (MF) Gyrus frontalis inferior (IF) Central region (C 1) Central region (C2) Superior parietalis (SP) Inferior parietalis (IP) Superior temporalis (ST) Inferior temporalis (IT) Superior occipitalis (SO) Inferior occipitalis (IO)

Anterior basal ganglia (BG) Thalamus (TH) Hippocampus (HI)

0.9956 0.9604 0.338 0.9818 0.9656 0.711 1.0471 0.9814 0.111 1.0037 1.0058 0.948 1.0078 1.0125 0.873 1.0276 1.0840 0.056 1.0205 1.0147 0.826 0.9768 0.9556 0.458 0.9889 0.9798 0.798 1.0078 < 1.0615 0.024b 0.9976 < 1.0593 0.014b 1.0051 1.0341 0.349 0.9523 < 1.0520 0.001 b

1.0488 > 0.9619 0.015b

0.9362 0.9307 0.925 1.0024 > 0.9407 0.014b

1.0225 0.9779 0.274 1.0115 1.0197 0.865 1.0547 0.9895 0.085 1.0074 0.9887 0.510 0.9846 1.0499 0.135 1.0299 1.0402 0.755 0.9958 0.9984 0.915 0.9476 0.9819 0.375 0.9386 0.9571 0.567 0.9855 1.0467 0.054 0.9780 < 1.0448 0.018b 1.0467 1.0361 0.830 0.9625 < 1.0698 0.009b 1.0638 0.9143 0.006b 0.9488 0.9298 0.743 1.0220 > 0.9552 0.018b

a p denotes the degree of significance of differences; b denotes that p < 0.05

AEP Results

AEP measurement results encompassed a total of 16 SCH and 11 DEP patients. Latency values for

particular individual recordings are presented in Table 3 for the SCH group and in Table 4 for the DEP

group, respectively, together with corresponding group mean values and ranges.

In both groups the dispersion of P300 latency values is considerably high. While latencies in

depressives are longer, the between-group difference is statistically insignificant (~~0.05). The biological

increase in latency with age further supports this conclusion.


Table 2

Hemispheric (left-right) Differentiation of Cerebral Perfusion for each Region in the Schizophrenia (N=lS) and Depression (N=l 1) Groups

Schizophrenic Depression

Region Right Left pa Right Left pa

Gyrus frontalis superior (SFl) 458.8 467.9 0.188 418.8 397.2 0.129 Gyrus frontalis superior (SF2) 480.2 467.8 0.100 447.6 449.1 0.880 Gyrus frontalis superior (SF3) 525.1 511.1 0.064 457.0 446.1 0.252 Gyrus frontalis medialis (MF) 489.8 > 465.1 0.030b 466.8 > 438.8 0.021b Gyrus frontalis inferior (IF) 505.1 480.7 0.091 471.4 473.0 0.943 Central region (Cl) 478.8 479.3 0.953 469.4 > 420.7 0.003b Central region (C2) 495.1 > 460.3 O.OIOb 470.8 442.0 0.05 1 Superior parietalis (SP) 448.5 434.4 0.131 413.9 397.5 0.172 Inferior parietalis (IP) 477.7 > 430.5 O.OOob 454.6 424.9 0.092 Superior temporalis (ST) 504.0 > 476.8 0.022b 494.2 > 471.4 0.043b Inferior temporalis (IT) 487.9 475.5 0.170 499.3 480.0 0.191 Superior occipitalis (SO) 482.0 > 468.9 0.025b 479.2 458.9 0.071 Inferior occipitalis (IO) 480.2 467.1 0.103 490.4 483.0 0.367 Anterior basal ganglia (BG) 528.2 519.3 0.410 447.4 > 411.8 0.017b Thalamus (TH) 471.4 461.3 0.414 432.2 415.4 0.323 Hippocampus (HI) 484.7 490.5 0.541 441.9 437.6 0.663

a p denotes the degree of significance of differences; b denotes that p < 0.05

When comparing grand-averaged waveforms for each channel between the groups, a systematic

difference was found; in SCH the amplitudes (max. 3 uV, typically 2 uV) were smaller than in DEP.

Figure 2 illustrates grand-average waveform for the FPl electrode position.

Discussion

Methodolonical Consideration

It is widely accepted that schizophrenia is associated with functional and structural brain

abnormalities. There are similar findings for depression however, they are less consistent. In addition to

standard clinical evaluation methods, in our research of schizophrenia and unipolar depression we


applied two kinds of functional brain imaging techniques; data on cerebral blood metabolism was

obtained by applying SPECT, and data on bioelectrical manifestation of brain function by applying AEP.

It is clear that, due to the enormous complexity of CNS, it is not possible to draw direct parallels between

these empirical data spaces. However, presuming that both biological measures manifest local properties

reflected in the topography of the brain, it is acceptable for corresponding features be put into relation. In

view of our results, both clinical entities manifested the following similar features: hypofrontality, a

decrease in perfusion in the hypothalamic region bilaterally, hemispheric asymmetry, an increase in P300

latency and a decrease in P300 amplitude.

1.3

1.2

1.1

1.0

.9

.8 N= 15 15 15 15 11 11 11 11

Schizophrenic Depressive

m XST-R

&j XST-L

H XIT-R

m XIT-L

Fig. 1. Graphical representation of the range of normalized perfusion values in the regions superior and inferior temporalis for each patient group. The median, interquartal range (coloured) and total range are shown. * denotes numbers of patients with extreme values; ’ denotes outliers. XST-R/L denotes arithmetic mean of superior temporalis (right/left) and XIT-R/L denotes arithmetic mean of inferior temporalis (right/let?).


Table 3 Table 4

P300 Latency Values in all Measurement P300 Latency Values in all Measurement Recordings and Corresponding Arithmetic Recordings and Corresponding Arithmetic

Means in the Schizophrenia Group Means in the DepressionGroup

Patient No. T300 lat (ms)

01 344 05 474 06 392 07 414 09 386 14 312 15 304 20 402 22 332 23 442 25 294 26 324 27 334 29 322

30 336 31 282

N=16, ~“355.9, sb=55.8, Min=282, Max=474

a arithmetic mean; b standard deviation

Patient No. Patient No.

02 420 03 466 08 436 10 410 11 494 12 264 13 330 16 350 19 408 28 328 32 330

N=ll, xa=385.1, sb=69.7, Min=264, Max=494

a arithmetic mean; b standard deviation

At the same time, we found differences in brain perfusion in the IT and IO regions, bilaterally, and the

right ST region (lower perfusion in SCH), and in the HI region, bilaterally, and the right BG (lower

perfusion in DEP). Further, grand average AEP-waveform amplitudes were smaller in SCH than in DEP.

A possible weakness in the interpretation of our results may be due to the fact that the statistical data

analysed was obtained for multiple brain regions in a limited number of subjects by applying multiple

comparisons.

Brain Blood Perfusion

Although our findings for hypofrontality in unipolar depressive and negative schizophrenic patients is

similar to those in the majority of existing reports, there are reports which postulate the role of other

regions. If it is assumed that hypofrontality in schizophrenia is a convincing hypothesis, smaller regions


of interest inside the frontal cortex itself are postulated, and weak activation of dorsolateral prefrontal

cortex in both the resting state and the state of cognitive activation is found (Buchsbaum et al. 1990).

Hypofrontality is associated with particular psychopathological phenomena, psychomotor poverty for

instance, i.e. it is in correlation with the degree of pronounced negative schizophrenic symptoms

(Medved and Petrovic 1993).

5 _________________________________________________________________ 1 4 _________________________________________~~~,~~“_,~,,,__________________

-

SCH _3__________________________________________________________________

-4 DEP z “e J+ e, % +> “se /Bp -+. -=Lc 23 +& +? -%. $ --?$ ‘ie 46 ?$o %c

Time (ms)

Fig. 2. Grand average AEP curves for the schizophrenic (SCH) group and depressive (DEP) group, at the FPl electrode position.

There are also findings which indicate that hypofrontality is in remission among patients with

schizophrenia with symptomatic improvement; this would indicate that that it is a state and not a trait

factor @pence et al. 1998). Our findings for hypofrontality in schizophrenic patients are not consistent

with the findings by Erkwoh et al. (1999) who found hypofrontality and hypertemporality to be part of the

active phase of schizophrenia. During remission hypofrontality partially disappeared and

hypertemporality disappeared completely. The question most often posed is whether hypofrontality

results from the influence of disease over time or in consequence of medication. In an attempt to find an

answer, the Scottish Schizophrenia Research Group (1998) found that patients displayed hypofrontality


compared to a control group in a first episode of schizophrenia prior to drug treatment. Reduced blood

flow was observed after six months of antipsychotic drug treatment.

Evidence from neuroimaging studies has linked negative symptoms to dysfunctional circuits in the

prefrontal cortex, the limbic system and the basal ganglia (Andreasen et al. 1997, Goff and Evins 1998,

Zakzanis and Heinrichs 1999, Sabri et al. 1997). However, there are studies which do not find

hypofrontality (Widen et al. 1983, Wiesel et al. 1987, Cohen et al. 1989, Szechtman et al. 1988, DeLisi et

al. 1989, Russel et al. 1997). Among subcortical structures, the basal ganglia is the one most often

associated with schizophrenia, like in patients who have never been medicated (Sheppard et al. 1983,

Hawton et al. 1990).

There is less consistency in research results of regional cerebral blood flow in depression. Buchsbaum

et al. (1984) first reported hypofrontality. Both a regional and a global decrease in brain metabolic

activity in depressives are mentioned (Warren et al. 1984). Schroeder et al. (1989) found hypofrontality to

be specific for the diagnostic spectrum which includes schizophrenia, schizoaffective psychosis and

major depression. Unlike schizophrenia, which tends towards chronicity, a bipolar affective disorder is a

state that alternates between disease and health, even in the absence of treatment. Blood flow and

metabolic data demonstrate that major depression is accociated with reversible mood state-dependant

neurophysiological abnormalities (Drevets 1998). Baxter et al. (1985) pose the question whether different

affective states in the same patients also have different metabolic patterns as a consequence. Biver et al.

(1994), however, find that two opposite processes occur in the frontal cortex in unipolar depression at the

same time: an increase in metabolic activity in the lateral and medial area of the basal frontal cortex, and

a reduction of metabolism in the dorsolateral prefrontal cortex. Neuropsychologic research in patients

with frontal lesions, as well as animal studies, indicate that lesions of particular substructures of the

frontal cortex cause a disturbance in various behavioural, cognitive and emotional functions (Mesulam

1986). A lesion of the dorsolateral prefrontal cortex creates a state termed “frontal retardation”, which

includes apathy, a nivelation of affect, loss of interest and apragmatisme. Our findings for bilateral

hypofrontality are consistent with the actual concept (Grasby 1999, Drevets 1998), and partially

consistent with the findings by Kishimoto et al. (1998) who found hypometabolism in the let?

anterolateral prefrontal cortex in patients with unipolar and bipolar depression. In a more elaborate study

by (Galynker et al. 1998), which examined the relations between regional cerebral flow, depressive

symptoms and negative symptoms in patients with major depressive disorder, decreased perfusion in the

left dorsolateral prefrontal cortex was found to be related to negative symptoms, in particular.

The study by Klemm et al. (1996) found left temporal and left frontal hypoperfusion in 17 patients


with schizophrenia and 12 patients with major depression in concordance with our model of limbic and

frontal dysfunction.

In our research in the SCH group, significant asymmetry appeared in regions MF, C2, IP, SO and ST.

The first four regions all belong to the third level, which reflects a significant hypoperfusion of the left

hemisphere exactly at this anatomical location. In the DEP group significant asymmetry was found in

regions MF, Cl, ST and BG, where a different, more “vertically” oriented anatomical pattern of

hypoperfusion of the left hemisphere can be seen.

Furthermore, brain laterality in schizophrenia and depression was demonstrated in our research. In

general, literature implies abnormalities in the activity of the left hemisphere in schizophrenic patients

(Gur and Chin 1999), but the notion of lateralization in connection with depression is uncommon.

In addition to this, our finding of hypoactivity in the hypothalamic region in schizophrenic patients has

confirmed findings by Min et al. (1999) who have shown that a significant correlation exists between

negative symptoms and a decreased level in perfusion in the left thalamic region.

Auditorv Evoked Potentials

From a psychological point of view, prolongation of P300 may be interpreted as a decrease of

cognitive processing speed (Cobum et al. 1998). Prolonged latency may indicate the neurodegenerative

nature of brain processes since it occurs in dementia, but also during normal ageing (O’Donnell et al.

1995). In our research, the AEPs provided subtle differentiation between groups; P300 latencies were

prolonged in both groups examined, consistent with an increase in the P300 latency in schizophrenic and

depressive patients (Weir et al. 1998, Laurent et al. 1999), while schizophrenic patients displayed smaller

amplitudes as reported by Salisbury et al. (1998), and negative symptoms are related to an increase in

latency (Keefe et al. 1991). However, Wagner and colleagues have found that there are no significant

differences in the amplitudes of P300 averaged signals between schizophrenic and depressive subjects

(Wagner et al. 1997). A reduced P300 amplitude coincides with the diagnosis of schizophrenia, however,

severely afIJ.icted patients had smaller P3OOs than those moderately ill. Among moderately ill patients,

P300 was related to symptom withdrawal.

A sophisticated study designed by Shajahan et al. (1997) examined schizophrenic patients while

performing an auditory two-tone oddball discrimination task using SPECT. Patients activated the left

superior temporal gyrus during the task, as well as the right caudate. There was a negative correlation


between the P300 amplitude and perfusion during the activation procedure in both caudate nucleii and in

the left lingual gyrus. No P300 latency correlations were observed and there was no frontal activation

during the task.

In general, reduction in frontal and thalamic rcBF may be more likely in patients with an impoverished

mental status.

Patterns of cerebral dysfunction in schizophrenia and depression topographically show partial

similarity. It may be assumed that lesion patterns have a common topography in part, whereas they do not

necessarily share a common physiology. The nature of physiological dysfunction in schizophrenia and

depression is an interesting question which remains to be answered through the development of

functional brain imaging studies.

Conclusion

In the two disorders the measured brain blood perfusion was found to be similar, with differences

appearing only in certain brain regions. Hypoperfusion of the left hemisphere was found in both groups.

AEPs led to the detection of a general decrease in cognitive process speed in both disorders, through an

increase in latency. AEP amplitudes were found to be smaller in the schizophrenia group than among

depressives. These findings may bear to both clinical and neuro-scientific relevance which will need to be

studied in future.

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