Reduced prefrontal oxygenation during object and spatial visual working memory in unpolar and bipolar depression

Psychiatry Research: Neuroimaging 194 (2011) 378–384

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Psychiatry Research: Neuroimaging j o u r n a l h o m e p a g e : w w w. e l s ev i e r. c o m / l o c a t e / p s yc h r e s n s

Reduced prefrontal oxygenation during object and spatial visual working memory in unpolar and bipolar depression Martin Schecklmann a,b,c,⁎, Thomas Dresler b, Stefanie Beck d, Johanna T. Jay e, Richard Febres b, Julia Haeusler c, Tomasz A. Jarczok b, Andreas Reif b, Michael M. Plichta f, Ann-Christine Ehlis b,g, Andreas J. Fallgatter b,g a

University of Regensburg, Department of Psychiatry and Psychotherapy, Regensburg, Germany University of Würzburg, Department of Psychiatry, Psychosomatics and Psychotherapy, Würzburg, Germany c University of Würzburg, Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, Würzburg, Germany d Charité Universitätsmedizin Berlin, Department of Anesthesiology and Operative Intensive Care Medicine, Berlin, Germany e Missionsärztliche Klinik Würzburg, Würzburg, Germany f Central Institute of Mental Health, Mannheim, Germany g University of Tübingen, Department of Psychiatry and Psychotherapy, Tübingen, Germany b

a r t i c l e

i n f o

Article history: Received 1 July 2010 Received in revised form 20 January 2011 Accepted 27 January 2011 Keywords: Functional near-infrared spectroscopy Affective disorders Executive functions

a b s t r a c t Altered prefrontal brain activity (e.g. hypofrontality) during cognitive tasks such as working memory is a core neuroimaging marker in unipolar (UNI) and bipolar (BI) depression. The present study investigated for the first time UNI (n = 16) and BI patients (n = 14) in a working memory task including different processes (storage and matching) and components (object and spatial visual) with functional near-infrared spectroscopy (fNIRS) over the prefrontal cortex. In healthy controls (n = 15) comparable to both patient groups, changes of oxygenated and deoxygenated haemoglobin indicated increased ventro-lateral, dorso-lateral prefrontal and superior frontal cortex activity for object and spatial visual working memory storage as compared to the control condition. In contrast, both patient groups showed diminished brain activity in all working memory conditions. Results revealed unspecific deficits that did not allow the differentiation between unipolar and bipolar depression in dependence of working memory processes or components. However, fNIRS can be considered as a valid, easy manageable, low cost and rapid tool for measuring (diminished) prefrontal cortex functions. © 2011 Elsevier Ireland Ltd. All rights reserved.

1. Introduction Depression is characterized by isolated or recurrent phases of depressive symptoms (unipolar depression or recurrent depression) that may alternate with phases of manic or hypomanic symptoms (bipolar depression or bipolar affective disorder). Besides the clinical symptomatology, affective disorders have been associated with deficits in prefrontal cognitive or executive functions (Mansell et al., 2005; Vasic et al., 2007) such as working memory (Henseler and Gruber, 2007; Walter et al., 2007). It has not yet been understood whether cerebral “hypofrontality” is a causal factor or constitutes an epiphenomenon of depressive symptoms (Harvey et al., 2005). The concept of cerebral hypofrontality in depression or affective disorders has been confirmed by a large number of imaging studies; however, the contradictory finding of increased prefrontal activity has also been reported (for an overview, see Vasic et al., 2007; Walter et al., ⁎ Corresponding author at: University of Regensburg, Department of Psychiatry, Psychosomatics and Psychotherapy, Universitätsstraße 84, 93053 Regensburg, Germany. Tel.: +49 941 941 2054; fax: +49 941 941 2025. E-mail address: [email protected] (M. Schecklmann). 0925-4927/$ – see front matter © 2011 Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.pscychresns.2011.01.016

2007). Moreover, the question of which hemisphere might be specifically affected by cerebral hypofrontality has not yet been sufficiently explored. Findings do not always confirm the hypothesis of diminished left-hemispheric activity (Pascual-Leone et al., 1996). Methods to detect hypofrontality are imaging techniques such as functional magnetic resonance imaging (fMRI) or positron emission tomography (PET). The disadvantages of these two methods are their high costs, poor availability during daily clinical routine, and the usage of radiolabeled tracers for PET. Functional near-infrared spectroscopy (fNIRS) is an optical imaging technique that overcomes these drawbacks (Obrig et al., 2000; Fallgatter et al., 2004). It is a handy and economic method requiring low preparation time and allowing measurement in a natural upright sitting position. It can be used as a bed-side instrument and is well tolerated by psychiatric patients. fNIRS is an optical approach to measure blood flow changes comparable to the measurement of blood oxygenation level dependent (BOLD) signal in fMRI studies. Nearinfrared light has the capacity to pass skin, skull, and brain tissue and is mainly absorbed by oxygenated (O2Hb) and deoxygenated hemoglobin (HHb). According to the principle of neurovascular coupling, increases of O2Hb and decreases of HHb are indicators for brain activity (Fox and Raichle, 1986; Obrig et al., 2000; Heeger and Ress, 2002).

M. Schecklmann et al. / Psychiatry Research: Neuroimaging 194 (2011) 378–384

One central function of the prefrontal cortex is working memory (WM). According to the theoretical concept of Baddeley (2001, 2003), working memory consists of manipulation, maintenance, and storage (WM processes) of different types of material (WM components such as verbal, object, or spatial visual stimuli). The literature indicates subdivisions of the prefrontal cortex that represent neural correlates of WM processes and material (Baddeley, 2003; Wager and Smith, 2003; Postle, 2006). There is evidence for altered WM functions in unipolar (UNI) and bipolar depression (BI); however, it is an open question whether there are differences between UNI and BI and whether differences depend on the investigated WM process or material. Thus, the aim of our study was to investigate differences in prefrontal oxygenation as elicited by fNIRS between UNI and BI patients and comparable healthy controls using a working memory task that requires both storage and matching, and comprises object (OWM) and spatial visual working memory (SWM) components.

2. Methods 2.1. Subjects We included a total of 45 individuals in our analyses (sample characteristics in Table 1): 16 in-patients with recurrent depression (UNI; DSM-IV (Diagnostic and Statistical Manual of Mental Disorders, American Psychiatric Association) code 296.3), 14 in-patients with bipolar affective disorder during a (mixed) depressive episode with depressive symptoms as the main symptoms (BI: DSM-IV code 296.4, 296.5, and 296.6), and 15 healthy controls (HC). Eight patients (UNI: 5, BI: 3) were a priori excluded from group analyses due to difficulties in understanding the task (too many errors during the control condition (N25% errors) or abortion of the task). Patients were diagnosed by experienced psychiatrists according to ICD-10 criteria (International Classification of Diseases, World Health Organisation) during in-patient treatment. Two BI patients suffered from co-morbid alcohol dependence, one UNI patient from pain disorder and obsessive–compulsive disorder, and one UNI patient from mixed personality disorder. Some subjects reported diseases of the thyroid gland (HC: 2; UNI: 3; BI: 3), cardiovascular system (HC: 1; UNI: 1; BI: 2), immune deficiency (UNI: 1), and diabetes (BI: 1), and took appropriate medication. Psychotropic medication and descriptive data are presented in Table 1. Exclusion criteria for the controls were psychiatric diseases, past or current participation in a psychological or psychiatric therapy, intake of psychotropic medication, neurological illness or severe somatic illness. Psychiatric diseases were excluded in controls by questionnaire and interview according to the SCID-I (Wittchen et al., 1997) regarding past and current psychopathological symptoms. Groups were comparable for age, intelligence, education, gender, handedness, and smoking

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(Table 1). Both patient groups (T = 5.637; df = 25; P b 0.001; BI: T = 5.883; df= 22; P b 0.001) had higher depression scores than healthy controls, whereas there was no difference between UNI and BI (T = 0.537; df= 19; P = 0.598) as assessed by the Beck Depression Inventory-II (BDI–II; Kuehner et al., 2007). The study was approved by the Ethics Committee of the University of Wuerzburg and all procedures involved were in accordance with the fifth revision of the Declaration of Helsinki. All participants gave written informed consent after comprehensive explanation of the procedures. 2.2. Working memory task The working memory task (Fig. 1) was based on a study by Courtney et al. (1996). A stimulus consisted of 24 gray, irregularly ordered squares on a black background. One of these squares showed parts of a face in frontal view. Facial stimuli were taken from the “Karolinska Directed Emotional Faces” (Lundqvist et al., 1998) and depicted only eyes, nose, and mouth (no ears and hair). Each trial consisted of an instruction screen, followed by three consecutive stimuli that had to be memorized (storage), thereafter a black screen, followed by another stimulus that had to be compared with the three previous stimuli (matching), and finally another black screen. There were three task conditions, OWM, SWM, and a control condition (CON) indicated by the instruction “same face?”, “same place?”, and “left or right?”, respectively. For CON, blurry faces were shown instead of regular face stimuli (Gaussian blur filter, Adobe Photoshop 7.0, Adobe Systems GmbH, Germany, Munich). For OWM, subjects were instructed to compare the face of the matching condition with the three faces of the storage condition; for SWM, subjects had to compare the location of the presented faces while ignoring their identity; for CON, subjects were simply asked whether the fourth stimulus appeared on the left or right side of the screen. Subjects were requested to answer by pressing the left (“yes”/“left side”) or right arrow button (“no”/“right side”) of a standard keyboard during the 2 s of the presentation of the match stimulus. Each condition comprised 30 trials that required subjects to press the left buttons and right buttons 15 times each. Conditions and face stimuli were presented in pseudo-randomized order. The fNIRS measurement took about 15 min. Prior to the measurement, subjects were instructed and trained in practice trials. They were instructed to sit in a relaxed position and to avoid any major body movements during the initial baseline phase (10 s) and the whole experiment. Dependent behavioural variables were the number of correct responses and mean reaction time for correct responses for each condition. 2.3. Measurement and analysis of fNIRS signals For the fNIRS measurement we used a continuous wave multichannel system (ETG-4000 Optical Topography System; Hitachi Medical Co., Japan, Tokyo) working with two different wavelengths

Table 1 Sample characteristics of included subjects (n=45) and a priori excluded patients (n=8) (mean ± standard deviation (number of subjects)).

Age (years) Intelligence (IQ) Graduation (no A-/A-levels) Gender (female/male) Handedness (right/left/ambidext) Nicotine use (non-smoker/smoker) Depression score (BDI–II) Antidepressive medication Antipsychotic medication Mood stabilizing agents Benzodiazepine use

Healthy controls (n = 15)

Unipolar depression (n = 16)

Bipolar depression (n = 14)

Statistical parameters

Patients drop-outs (n = 8)

40.9 ± 8.0 111.1 ± 8.2 (n = 15) 11/4 8/7 14/0/1

43.4 ± 9.8 112.3 ± 18.9 (n = 15) 8/8 7/9 12/2/2

40.8 ± 10.2 111.2 ± 10.8 (n = 13) 10/4 11/3 13/0/1

F = 0.370; df = 2,42; P = 0.693 T = 0.172; df = 82; P = 0.864 χ² = 2.272; df = 2; P = 0.321 χ² = 3.893; df = 2; P = 0.143 χ² = 3.962; df = 4; P = 0.411

49.5 ± 9.1 107.7 ± 16.9 (n = 7) 6/1 (n = 7) 4/4 8/0/0

9/6

8/8

7/7

χ² = 0.402; df = 2; P = 0.818

4/3 (n = 7)

4.1 ± 3.0 (n = 15) 0 out of 15 0 out of 15 0 out of 15 0 out of 15

18.2 ± 9.2 (n = 12) 15 out of 16 9 out of 16 1 out of 16 9 out of 16

20.4 ± 10.2 (n = 9) 13 out of 14 7 out of 14 7 out of 14 8 out of 14

F = 17.681; df = 2,33; P b 0.001

25.8 ± 8.4 (n = 5)

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(695 ± 20 and 830 ± 20 nm) and a time resolution of 10 Hz to measure relative changes of absorbed near-infrared light. These changes are transformed into concentration changes of O2Hb and HHb as indicators for brain activity by means of a modified Beer–Lambert law (Obrig and Villringer, 2003). The unit is mmol*mm, i.e. changes of chromophore concentration depend on the path length of the nearinfrared light. We used one probe-set (plastic panel) of optodes consisting of 17 light emitters and 16 detectors with an inter-optode distance of 3 cm. A measuring point of activation (channel) was defined as the region between one emitter and one detector resulting in 52 channels to cover an area of 30 * 6 cm2 on the scalp. The panel was fastened to the head by elastic straps. The probe-set was placed on the head with regard to the relevant standard positions of the international 10–20 system for EEG electrode placement (Jasper, 1958; Okamoto et al., 2004). The middle inferior optode was placed over Fpz, and the inferior row of optodes was oriented towards T3 and T4, respectively (Fig. 2). Before statistical analysis of the functional data, the high frequency portion of the signal was removed by calculating a moving average with a time window of 5 s, before a high pass filter with nine discrete cosine basis functions was applied. We used the general linear model approach according to fMRI and fNIRS literature (Friston et al., 1995; Schroeter et al., 2004a; Plichta et al., 2007a) with a gamma function with two parameters serving as the model for the hemodynamic response function (HRF). For O2Hb and HHb, we used a peak time of 6 s according to the findings by Schroeter et al. (2004b) in an event-related Stroop task. The beginning of each stimulus was modelled as a delta stick function and folded with the HRF resulting in six predictor variables (memorize and match for the three conditions). Betas were estimated by the method of least squares indicating the amplitude of brain activation. For mapping of channels on certain brain areas in regard to region of interest (ROI) analyses, we referred to Suda et al. (2009), who used the same fNIRS equipment and the same (orientation of the) probe-set as in our study. We defined ROIs for the left and right hemisphere covering mirror-inverted areas. Based on the literature (Courtney et al., 1996; Haxby et al., 2000; Baddeley, 2003; VentreDominey et al., 2005), we defined the ventro-lateral prefrontal cortex (VLPFC; Brodmann Area (BA) 44/45; face working memory), dorsolateral prefrontal cortex (DLPFC; BA 9/10/46; central executive), and posterior superior frontal cortex (superior frontal sulcus, SFS; BA 6/8; spatial working memory) as relevant ROIs (left VLPFC: channels 39, 40, 49, 50; right VLPFC: 34, 35, 45, 46; left DLPFC: 7, 8, 17, 18, 19, 28, 29; right DLPFC: 3, 4, 13, 14, 15, 24, 25; left SFS: 9, 10, 20, 21; right SFS: 1, 2, 11, 12).

Fig. 1. Trial flow chart of the working memory task.

2.4. Data analyses For statistical analyses of behavioural and brain activation data, we used a 3 × 3 analysis of variance (ANOVA) with the within-subject factor “task condition” (OWM, SWM, and CON) and the between-subject factor “group” (controls and UNI and BI patients), as well as corresponding post hoc t-tests alpha = 0.05; uncorrected; corrected for inequality of variances by Levene's test – noticeable by degrees of freedom with decimal places); for fNIRS data, the factor “hemisphere” (left and right side) was additionally included. We abstained from evaluation of the relationship between behavioural/imaging data and subject/clinical characteristics as the three samples were too small to allow statistically meaningful conclusions based on correlation analyses. All analyses were conducted with MatLab 6.5 (The MathWorks, Inc., USA) and SPSS 15.0 (SPSS Inc., USA). 3. Results 3.1. Performance (Fig. 3) For behavioral data, 3×3 ANOVAs indicated significant main effects of task condition for the number of correct answers (F=57.035; df=2,84; Pb 0.001) and reaction times (F=280.936; df=2,84; Pb 0.001) showing a parametric modulation with CON as easiest, SWM as more difficult, and OWM as most difficult (OWM N SWM: TN 3.308; Pb 0.006; SWMN CON: TN 8.017; Pb 0.001; OWMN CON: TN 9.809; Pb 0.001; for all groups). For reaction time, we furthermore found a condition×group interaction effect with a statistical trend (F=2.463; df=4,84; P=0.051). Post hoc tests indicated slower reaction times for BI patients during SWM (T=2.007; df=25.547; P=0.055) and CON (T=2.596; df=25.965; P=0.015) compared to HC. 3.2. Brain activity (Figs. 2 and 3) For fNIRS data, we focussed on the analyses of the storage component as the descriptive inspection of the matching condition did not indicate task-specific activation, i.e. higher activation for both WM conditions in contrast to CON. For the ANOVAs, we found no effects of side interacting with group, and therefore abstained from presentation of any side effects (Figs. 2 and 3). For VLPFC and O2Hb, we found a significant condition by group interaction effect (F = 3.027; df = 4,84; P = 0.032). For controls, OWM (T = 2.224; df = 14; P = 0.043) and SWM (T = 2.624; df = 14; P = 0.020) were associated with higher O2Hb increases than CON showing no difference between WM conditions. For both patient groups, no O2Hb differences between task conditions were found. Controls had significantly higher O2Hb increases in contrast to BI patients in the working memory conditions (OWM: T = 2.827; df = 17.447; P = 0.011; VWM: T = 2.487; df = 16.037; P = 0.024). For HHb in VLPFC, we only found a main effect of group, but no effect of condition. We therefore omitted to show a more detailed description as no task-relevant activation was observed. For DLPFC and O2Hb, we found significant main effects of condition (F = 7.278; df = 2,84; P = 0.001) and group (F = 8.821; df = 2,42; P b 0.001) and a significant interaction effect of condition by group (F = 4.630; df= 4,84; P = 0.002). For HC, OWM (T = 2.480; df= 14; P = 0.026) and SWM (T = 4.458; df = 14; P = 0.001) were associated with higher O2Hb increases than CON showing no difference between WM conditions. For both patient groups, no significant O2Hb differences between task conditions were found. Controls had significantly higher O2Hb increases compared to both patient groups in all task conditions except for CON, which yielded no significant difference between controls and UNI (statistical trend; T N 1.949; P b 0.069). For HHb in DLPFC, we found a significant main effect of condition (F = 5.659; df = 2,84; P = 0.005) and a condition by group interaction effect (F = 5.558; df = 4,84; P b 0.001). For controls, OWM (T = 3.842;

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Fig. 2. Probe-set arrangement and brain activation. Top: Orientation of optodes (red = emitters; blue = detectors) and channels (numbers) over an exemplary head and brain. Bottom: T-maps of brain activation as elicited by t-tests against zero (OWM: object visual working memory; SWM: spatial visual working memory; CON: control task).

df= 14; P = 0.002) and SWM (T = 3.026; df = 14; P = 0.009) were associated with higher HHb decreases than CON showing no difference between WM conditions. For both patient groups, no HHb differences between task conditions could be detected. For OWM, controls (T = 2.425; df= 19.153; P = 0.025) and BI (T = 2.670; df= 23.786; P = 0.013) had higher HHb decreases than UNI, and for CON, BI had higher HHb decreases than UNI (T = 2.402; df = 20.904; P = 0.026). In SFS – in posterior superior prefrontal cortex/sulcus – we found significant main effects of condition (F = 6.688; df = 2,84; P = 0.002) and group (F = 8.171; df = 2,42; P = 0.001) for concentration changes of O2Hb, as well as a significant interaction effect condition by group (F = 2.862; df = 4,84; P = 0.036). For controls, SWM was associated with higher O2Hb increases than OWM (T = 2.477; df = 14; P = 0.027) and CON (T = 3.726; df = 14; P = 0.002). For both patient groups, no significant O2Hb differences between task conditions could be detected. Controls had higher O2Hb increases in contrast to both patient groups for all task conditions (T N 2.132; P b 0.046). For HHb in SFS, we only found a main effect of group, but no effect of condition. We therefore do not present a more detailed description as no taskrelevant activation was observed. 4. Discussion To our knowledge, we investigated for the first time patients with unipolar and bipolar depression by performing an fNIRS paradigm using a working memory (WM) task that requires storage and

matching and comprises object (OWM) and spatial visual working memory (SWM) components. For the matching condition we could not detect task-related brain activity, i.e. higher concentration changes during the WM conditions in contrast to the control condition. For the storage condition we found the expected task-related increases of O2Hb for the control group, i.e. higher increases during the working memory conditions compared to the control condition. We previously applied this task in children (8–15 years), where brain activation during the matching component, but not during the storage component was observed (Schecklmann et al., 2010). These findings indicate that a missing matching effect is not due to methodical limitations (short and constant black screen interval between the storage and matching phase), but can probably be attributed to maturational or age effects of brain physiology or cognitive strategies. For the storage condition in posterior superior frontal cortex, SWM was associated with higher O2Hb changes in contrast to OWM and CON. Superior parts of the prefrontal cortex are considered to be related to SWM rather than OWM (Courtney et al., 1996; Baddeley, 2003). For dorso-lateral and ventro-lateral prefrontal cortex, controls showed higher O2Hb changes during both WM conditions in contrast to CON without difference between OWM and SWM. As the dorsolateral prefrontal cortex is considered to be the anatomical correlate of the central executive (Baddeley, 2003), we did not expect differences between the two WM conditions in this ROI. For the ventro-lateral prefrontal cortex or the inferior frontal cortex (part of the ventral “what” visual processing pathway; Courtney et al., 1996), we

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Fig. 3. Performance data and mean beta weights in regions of interest for oxygenated (O2Hb) and deoxygenated haemoglobin (HHb) and for superior frontal sulcus (SFS), dorso-lateral prefrontal cortex (DLPFC), and ventro-lateral prefrontal cortex (VLPFC) according to analyses of variance (left and right side were averaged due to missing side by group interactions). Error bars indicate standard errors.

expected – but failed to show – higher O2Hb increases for OWM compared to SWM. Typical findings are increases of brain activation with rising difficulty (Carlson et al., 1998), but some studies also show a decrease of brain activation after a certain difficulty level has been reached (Callicott et al., 1999). Considering the difficulty of OWM (more difficult than SWM), this task condition might have been too demanding for the present control sample, resulting in an equal or diminished O2Hb concentration during OWM in contrast to SWM. For HHb we only found typical task-related brain activation for the dorso-lateral prefrontal cortex ROI. During OWM and SWM, HHb decreases were higher in contrast to CON. Missing effects for the other

ROIs might be due to the lower statistical power of HHb compared to O2Hb (Schecklmann et al., 2008), although it is an open question whether O2Hb or HHb is the more reliable chromophore or the best indicator for brain activity (Schroeter et al., 2004a; Plichta et al., 2006; Schroeter et al., 2006; Hoshi, 2007; Plichta et al., 2007b). However, the descriptive examination of HHb revealed comparable findings, i.e. mirror-inverted activation patterns in comparison to O2Hb without reaching statistical significance. Patients partly showed reduced brain activation also for the control condition. Performance data indicated slowed reaction times of BI patients during the control condition and also during SWM. Additionally, the fact

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that some patients (n=8) were unable to perform the task (too many errors in the control task and comprehension problems) indicates that the chosen paradigm was probably too difficult. Higher numerical values in age, lower intelligence, and higher depression rates in these drop-outs (Table 1) are in line with this assumption. For future studies an easier paradigm should be used to enable most of the patients to manage the task, even with reduced self-confidence and impaired cognitive functions. In summary, controls showed the expected and typical task-related brain activation during the storage condition. Although both patient groups performed equally well and showed the same performance pattern as healthy controls (difficulty: OWM N SWM N CON), UNI and BI patients showed no differences in brain activation between the three WM conditions. Additionally, controls had significantly higher brain activation (mainly indicated by O2Hb) in comparison to both patient groups. This is in line with the hypothesis of cerebral hypofrontality in depression (see Section 1). Our data indicated a hypofrontality unspecific for depression type. There is literature confirming this finding (Sweeney et al., 2000) but also showing distinct profiles in executive functions between UNI and BI (Taylor Tavares et al., 2007). The fMRI literature working explicitly with WM (e.g. n-back tasks) often showed heightened brain activity in UNI (Harvey et al., 2005; Matsuo et al., 2007; Walsh et al., 2007; Walter et al., 2007; Fitzgerald et al., 2008) and BI patients (Adler et al., 2004; Frangou et al., 2008). Reports of decreased BOLD signal are rare (Monks et al., 2004). Increased activity was found in samples corrected for performance differences and for samples in which the performance was comparable to controls. Authors explain these increases in BOLD signal as compensatory activation necessary to obtain comparable performance levels, which therefore supports the hypofrontality hypothesis. There are no other fNIRS studies so far that have investigated WM in depression. Previous fNIRS investigations often used verbal fluency and found reduced brain activity (Herrmann et al., 2004; Matsuo et al., 2004; Kameyama et al., 2006; Pu et al., 2008). Differences between studies regarding the detected activation pattern (hyperactivation vs. hypoactivation) might partly be caused by medication effects, as samples often include patients treated with different kinds of antidepressant medication. Another factor possibly accounting for part of the between-study variance might arise from the specific imaging methods and working memory tasks employed. Such an influence of task design and imaging methods should be examined in future studies. Limitations of the presented study are mainly related to clinical characteristics of the patient samples. It is well known that the hemodynamic response can be influenced by vascular disorders such as cerebral microangiopathy (Schroeter et al., 2005, 2007), certain medication (overview in D'Esposito et al., 2003), or brain atrophy related to psychiatric disease (Schecklmann et al., 2007). We cannot statistically evaluate these issues due to small sample sizes, but the number of somatic disorders was comparable between the control and both patient groups, and medication was comparable between the patient groups (Table 1). Our study in alcohol-dependent patients indicated no negative influence of brain atrophy on fNIRS results (Schecklmann et al., 2007). Additionally, these limitations are shared by all imaging investigations. Another potential limitation is related to possible subtle symptom differences between patient groups, in spite of being diagnosed as depressed at time of measurement. In summary, results revealed unspecific deficits that did not allow for a differentiation between unipolar and bipolar depression in dependence of working memory processes or components. However, we could demonstrate that fNIRS is a valid tool for measuring (diminished) prefrontal cortex functions. Acknowledgements The authors would like to thank Hitachi Medical Corporation for the ETG-4000 equipment. The study was supported by the Deutsche Forschungsgemeinschaft, KFO 125-1 and SFB TRR 58 (C4).

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