Mapping hypofrontality during letter fluency task in schizophrenia: A multi-channel near-infrared spectroscopy study

Schizophrenia Research 136 (2012) 63–69

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Mapping hypofrontality during letter fluency task in schizophrenia: A multi-channel near-infrared spectroscopy study Shinji Shimodera a, Yutaka Imai b, Naoto Kamimura a, Ippei Morokuma a, Hirokazu Fujita a, Shimpei Inoue a, Toshi A. Furukawa c,⁎ a

Department of Neuropsychiatry, Kochi Medical School, Kohasu, Okoh-cho, Nankoku-shi, Kochi 783-8505, Japan Brain Function Group, Marketing Department, Medical Systems Division, Shimadzu Corporation, Nishinokyo Kuwahara-cho 1, Nakagyo-ku, Kyoto 604-8511, Japan Department of Health Promotion and Human Behavior, Kyoto University Graduate School of Medical Sciences/School of Public Health, Yoshida Konoe-cho, Sakyo-ku, Kyoto 606-8501, Japan

b c

a r t i c l e

i n f o

Article history: Received 3 May 2011 Received in revised form 23 January 2012 Accepted 29 January 2012 Available online 12 February 2012 Keywords: Schizophrenia Near-infrared spectroscopy Letter fluency test Hypofrontality

a b s t r a c t Cognitive impairment and associated frontal lobe dysfunction characterize schizophrenia. The letter fluency test (LFT) has been used as one of the most sensitive measures of the cognitive dysfunction, but the nature and topography of the hypofrontality have yet to be fully elucidated. In this study we used multi-channel near-infrared spectroscopy (NIRS), a recently developed noninvasive functional imaging technique, to measure changes in the concentration of oxygenated hemoglobin in the prefrontal cortices of 31 schizophrenia patients and 26 age- and sex-matched healthy controls during performance of the LFT. The results demonstrated reduced prefrontal cortex activation during the LFT among the schizophrenia patients in comparison with the healthy controls, even after controlling for medication. The hypofrontality was most salient in the prefrontal ventrolateral subregion bilaterally. The reduced activity appeared to be due not only to the lesser magnitude but also to the lesser fluctuation of the changes in oxygenated hemoglobin concentration. The hypofrontality appeared to be independent of the patients' symptomatological manifestations. We concluded that measuring NIRS during performance of the LFT can detect prefrontal lobe dysfunction of schizophrenia patients and may provide a new tool to monitor their treatment and course. © 2012 Elsevier B.V. All rights reserved.

1. Introduction Schizophrenia is characterized by a broad range of cognitive impairments including abnormalities of memory, attention, and executive functions (Flashman and Green, 2004). There is an accumulating body of research showing that such cognitive dysfunction is an important predictor of the social and functional outcomes of schizophrenia patients independently of their symptomatological manifestations (Green et al., 2004). These cognitive dysfunctions are related to dysfunctions of several areas of the brain, most notably the prefrontal cortex. Recent advances in neuroscience have been revealing even finer segregation of functions within the prefrontal cortex (Fletcher and Henson, 2001; Ramnani and Owen, 2004; Petrides, 2005). Fletcher and Henson (2001), for example, attributed updating/maintenance of information, selection/manipulation/monitoring of that information, and selection of processes/subgoals to the ventrolateral, dorsolateral, and frontopolar regions of the prefrontal cortex, respectively.

⁎ Corresponding author. Tel.: + 81 75 753 9491; fax: + 81 75 753 4641. E-mail address: [email protected] (T.A. Furukawa). 0920-9964/$ – see front matter © 2012 Elsevier B.V. All rights reserved. doi:10.1016/j.schres.2012.01.039

Verbal fluency tests, especially the letter fluency test (LFT), have been used widely as a neuropsychological activation task and been found to be one of the most sensitive measures of the underlying frontal lobe dysfunction in schizophrenia (Ehlis et al., 2007; Ikezawa et al., 2009). Functional magnetic resonance imaging (fMRI) studies have revealed prefrontal involvement during verbal fluency tasks (Gaillard et al., 2000). Near-infrared spectroscopy (NIRS) is a recently emerging functional neuroimaging technique. It is based on the principle that nearinfrared light penetrates biological tissues and is mainly absorbed by oxygenated and deoxygenated hemoglobin (oxy-Hb and deoxy-Hb). Because oxy-Hb and deoxy-Hb have different light absorption spectra, measuring the reflected near-infrared light on the scalp can detect changes in their concentrations. NIRS has several advantages over existing imaging techniques, including PET, SPECT, and fMRI, because of its noninvasiveness, ease of administration and tolerance for small movements, and inexpensiveness. It provides excellent time resolution and moderate spatial resolution. Several studies in which NIRS has been used have also found reduced prefrontal cortex activation during various cognitive tasks, including the LFT, in schizophrenia (Suto et al., 2004; Ehlis et al., 2007; Takizawa et al., 2008; Ikezawa et al., 2009). However, the nature and topography of the hypofrontality have not been fully investigated.

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The present study used multi-channel NIRS to map prefrontal cortical activity during LFT and applied new analytical methods to elucidate the characteristics of such hypoactivity. 2. Methods 2.1. Subjects The subjects were recruited from among outpatients and inpatients in the Department of Psychiatry, Kochi Medical School, between March and October 2010. The inclusion criteria were: 1) Diagnosis of schizophrenia according to DSM-IV-TR by the treating psychiatrist 2) Age 18–80 years. The exclusion criteria were: 1) Cognitive impairment severe enough to interfere with administration of the LFT 2) Comorbid mental disorder, such as anxiety disorder or personality disorder, diagnosed by the treating psychiatrist. Whenever dementia was suspected clinically, the patient was screened for dementia by means of the Mini-Mental Status Examination, and if the patient's score was 23 or below, the patient was excluded. Patients suspected of having an organic disease were examined by head magnetic resonance imaging (MRI), and those diagnosed with an organic disease based on the results of the MRI were excluded. The treating psychiatrists had been in charge of the patients for 48 months on average (range: 3 to 201). The control subjects were recruited from among hospital staff members and their acquaintances. The psychopathology of the schizophrenia patients was assessed by means of the Positive and Negative Syndrome Scale (PANSS) (Kay et al., 1987). Handedness was determined according to the Edinburgh Inventory (Oldfield, 1971). The protocol for this study had been approved by the Ethics Committee of Kochi Medical School. 2.2. Procedure The subject sat on a comfortable chair in front of the operator, who explained the procedures of the cognitive task and NIRS measurements. After ascertaining that the subject was ready, the operator put the NIRS holder and probes on the subject's head. The operator then instructed the subject to rest for 30 s, and at the end of the 30-second rest period the operator asked the subject to recall and say as many words starting with /ka/ as possible during the next 30 s, then as many words starting with /no/ as possible during the subsequent 30 s. After these two consecutive 30-second cognitive activation tasks, the subject was instructed to rest for 70 s. The smallest phonetic unit in the Japanese language is a vowel or a consonant-vowel pair, because all consonants are immediately followed by a vowel in Japanese. We chose words starting with /ka/ and /no/, because the former has the largest number of words in Japanese dictionaries whereas the latter has the least number of words. The length of time allocated to each sound was more prolonged than in some previous studies in order to allow a detailed examination of the time course of the cerebral activation. The average number of words generated in the Japanese LFT among the healthy controls was 16.5 (Kameyama et al., 2006), 16.8 (Suto et al., 2004) and 17.3 (Takizawa et al., 2008) in several studies that allocated 20 s each to three sounds of /a/, /ka/ and /sa/. As we used only two sounds and one of them has the least number of words starting with that sound, the expected number of words generated in our LFT could be fewer.

2.3. NIRS measurements In this study, 42 channels of the 52-multi-channel NIRS machine (OMM-3000/16, Shimadzu Corporation) were placed on the forehead of each subject in a reticular pattern. The bottom row of channels was set along the Fp1–Fp2 line as defined in the International 10–20 system of electroencephalography. Each channel consists of a source probe and detector probe, which are placed 30 mm apart. Three wave lengths, i.e., 780 nm, 805 nm, and 830 nm, are used to measure changes in the concentration of oxyHb and deoxy-Hb according to the Beer–Lambert law. The source probe emits light sequentially in order to avoid cross-talk noise. Sampling time is adjusted to 0.22 s, which is sufficiently fast to measure changes. Each channel is supposed to measure the changes at the midpoint between the two probes at 20 to 30 mm deep under the scalp. See Fig. 1. The time course of hemoglobin concentration changes was acquired at each channel during the LFT. The data contained some artifacts caused by the scalp muscle activities. The channel records containing artifacts were identified and removed in the course of the analyses by an independent engineer who was unaware of the diagnosis and the cognitive task performance of the subject. The baseline was drawn between two points, one of which was the average of the activity during the 10 s before the start of the task, and the other of which was the average of the activity during the last 10 s of the final 70-second rest period. Cf. Fig. 2A. We calculated six indexes in order to capture the characteristics of the time course of changes in oxy-Hb concentration, which had been smoothed by moving averages. In order to effectively decrease the noise caused by heart movements, electrical fluctuations, etc., the number of averaged data recruited was set at 10, and the duration of the moving average was set at 2.2 s. The area under the curve (AUC) was calculated through the 60 s of the task period after the baseline shift, which set the end point of the curve at zero (Fig. 2A). The time when the accumulated data reached half the AUC was also calculated and is referred to here as the weighted center (WC). (Takizawa et al., 2008) We also obtained the initial upward gradient (referred to here as UP) and the terminal downward gradient (DOWN). UP and DOWN are the gradients of the lines connecting the minimum and maximum points in the original curve before the baseline shift within the 10-second period after the start of task and after the end of the task, respectively (Fig. 2B). In order to quantify the degree of fluctuation of the curve, we submitted 256 adjacent

8

7 6

5 14 13

34

33 32

31 39

25

24

23

22

30

17

16

15

41

42

40

Fig. 1. Projection of the probes and the channels onto the brain surface, using MRI data and a 3D position detector. Red: source; blue: detector; yellow, channel.

S. Shimodera et al. / Schizophrenia Research 136 (2012) 63–69

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A. Example of baseline shift of the curve. The 120s point is set equal to zero.

Hb concentration [cM·mm]

task period

rest period task end point

task start point 0s

120s

60s

B. The scheme for UP and DOWN parameters. UP is the gradient of the line connecting the minimum point and the maximum point within the initial 10 seconds of the task period, and DOWN is the corresponding line in the initial 10 seconds after the end of the task period, in the original curve before the baseline shift.

Hb concentration [cM·mm] UP(gradient)

DOWN(gradient)

maximum point minimum point

task start 0s

task end 60s

10s

70s

C. DC correlates with the area under the original curve before the baseline shift for the first 56.2 seconds. AC increases when the curve shows large up and down fluctuations.

Hb concentration [cM·mm]

Fluctuation

256 sample points

task start 0s

56.2s

task end 60s

Fig. 2. Time course of oxy-Hb concentrations and NIRS indexes. A. Example of baseline shift of the curve. The 120 s point is set equal to zero. B. The scheme for UP and DOWN parameters. UP is the gradient of the line connecting the minimum point and the maximum point within the initial 10 s of the task period, and DOWN is the corresponding line in the initial 10 s after the end of the task period, in the original curve before the baseline shift. C. DC correlates with the area under the original curve before the baseline shift for the first 56.2 s. AC increases when the curve shows large up and down fluctuations.

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sample points on the curve (corresponding to 56.2 s of the 60-second task) to Fast Fourier transformation and obtained the absolute amplitude frequency spectrum (frequency bin zero to frequency bin 127. Frequency of bin 1 = 1/56.2 Hz [0.018 Hz] and frequency bin 127 = 127/56.2 Hz [2.26 Hz]. Sampling time was 0.22 s.) (Fig. 2C). The alternate current component (AC) was the sum of the absolute amplitudes of frequency bins 1 to 10 (0.018 to 0.18 Hz), and the direct current component (DC) was the amplitude of frequency bin zero. AC reflects the degree of fluctuation of the curve, while DC shows the average amplitude of the curve. 2.4. Analyses First, we compared the schizophrenia patients and the control subjects at each of the 42 channels in terms of the six indexes. Because we were making 42 comparisons for each index, we set the level of statistical significance at 0.05/42 = 0.001 and the level of statistical trend at 0.10/42 = 0.002. Since we were interested in the possible presence of left/right asymmetry, we excluded the left-handed subjects from this analysis. In order to adjust for the effects of performance (i.e. the possibility that subjects had less activation simply because they were producing less words), the analyses were repeated by controlling for LFT results. To assess the effect of the patients' medication, we also repeated the analyses while controlling for treatment with antipsychotic drugs and anxiolytic drugs. Second, we averaged these indexes across all the channels and calculated the Pearson correlation coefficients between the six indexes to see their interrelationships. Third, we investigated whether schizophrenia psychopathology was correlated with any of the six NIRS indexes by calculating Pearson coefficients for the correlations between the subscale and total scores on the PANSS and the averaged indexes. 3. Results 3.1. Participants Table 1 shows the demographic and clinical characteristics of the schizophrenia patients and the controls. There were no statistically significant differences between the patients and the controls in terms of age or sex. Two persons in each group were left-handed. The patient group was being treated with an average daily dose of 350 mg of an antipsychotic drug as chlorpromazine equivalents and an average daily dose of 9.8 mg of an anxiolytic drug as diazepam equivalents. Eleven patients were also being treated with an antidepressant, three with lithium and one with valproate. The schizophrenia patients were able to generate far fewer words than the controls during the LFT (9.0 words vs 14.0 words, p b 0.001).

The LFT performance was correlated with brain activation as the correlations between LFT results and the grand averaged AUC, DOWN, DC and AC were statistically significant with 0.36 (p = 0.006), −0.37 (p = 0.005), 0.31 (p = 0.02) and 0.27 (p = 0.04) respectively.

3.2. Mapping hypofrontality during the letter fluency task in schizophrenia We compared the values of the six indexes recorded from each of the 42 channels and mapped them according to the spatial distribution of the relevant channels. No channels showed a statistically significant difference between the groups in WC or DOWN, and the results are not shown (Fig. 3). The number of channels that showed a statistically significant difference between the patients and the controls decreased when controlled for the LFT results or for the medications, but the foci of hypofunction were basically concordant with the unadjusted analyses. Thus, the topography of the hypofrontality centered around two symmetric foci: one was the areas around channel 28 on the right hemisphere, and the other was the areas around channel 32 on the left hemisphere.

3.3. Characteristics of the NIRS indexes Table 2 shows the grand averaged, trans-prefrontal values of AUC, WC, UP, DOWN, AC and DC of the schizophrenia patients and the healthy controls. The results of the statistical analysis of these overall measures of prefrontal cortex activity showed highly significant differences in AUC, UP, DOWN, AC, and DC between the schizophrenia patient group and the healthy control group. These differences were not due to differences in LFT performance, because statistical significance persisted after controlling for the number of words produced. Controlling for the medication did not change the overall findings either. The interrelationships between the six NIRS indexes were examined by calculating their correlation coefficients (Table 3). AUC appeared to be the most representative index, while WC and DOWN appeared to be relatively unrelated to the other indexes. DC and AC were closely correlated, but the former contributed to both AUC and UP, while the latter correlated with AUC alone.

3.4. Correlations with psychopathology We examined the correlations between the index values and schizophrenia psychopathology as measured with the PANSS (Table 4). None of the Pearson correlation coefficients between the indexes and scale scores was statistically significant at the conventional p value of 0.05.

Table 1 Demographic and clinical characteristics of the participants.

Age Sex (male:female) Handedness (right:left) Illness duration (months) Medication

PANSS

LFT

Schizophrenia patients (n = 31)

Healthy controls (n = 26)

Comparison

42.4 (15.7) 12:19 29:2 90.3 (84.9) Antipsychotics (mg chlorpromazine): 350 (349) (range: 0–1700) Anxiolytics (mg diazepam): 9.8 (16.6) (range: 0–73) Positive: 14.8 (5.5) Negative: 21.4 (7.6) General: 34.0 (11.8) Total: 70.2 (22.9) 9.0 (3.7)

41.4 (10.4) 13:13 24:2 – –

p = 0.78 p = 0.56 p = 0.62

PANSS = Positive and Negative Syndrome Scale. LFT = Letter fluency test. The values are means (SD) unless otherwise noted.

–

14.0 (3.6)

p b 0.001

S. Shimodera et al. / Schizophrenia Research 136 (2012) 63–69

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AUC 1 9

2 10

18** 26

3 11

19

20 28*‡

27 35

4 12

36

5 13

21 29

37

6 14

22 30

38

7 15

23

24 32**‡

31 39

8 16

40

17 25

33 41

34 42

UP 2†

1 9

10 18

26

3 11

19

20 28*‡

27 35

4 12

36

5 13

21 29

37

6 14

22 30

38

7 15

23 31

39

8 16

24 32

40

17 25

33 41

34 42

DC 1 9

2 10

18 26

3

19 27

20 28

35*

4 12*

11

36*

5 13

21 29

37

6 14

22 30

38

7 15

23

24 32**†

31 39

8 16

34*

33 41*

40

17 25

42

AC 1 9

2 10

18 26

3 11

19

20 28*

27 35*

4 12

36

21 29

37

5 13

6 14

22 30

38

7 15

23

24 32**

31 39

40

8 16

17 25 34*

33 41*

(Right)

42

(Left)

p<0.002 is indicated in light red and p<0.001 in dark red, when the p values were calculated by unadjusted unpaired t-tests. p<0.002 is indicated by * and p<0.001 by **, when the p values were calculated after controlling for LFT results. p<0.002 is indicated by † and p<0.001 by ‡, when the p values were calculated after controlling for medication. Fig. 3. Mapping hypofrontality.

4. Discussion We used NIRS to measure the frontal cortex activity of 31 schizophrenia patients and 26 healthy controls during the LFT, which is a cognitive activation task known to be sensitive to the frontal lobe dysfunction in schizophrenia. Topographically, the hypofrontality was focused in ventrolateral regions of the prefrontal cortex bilaterally. When the NIRS indexes were averaged across the prefrontal lobes, the values of all but one of the indexes revealed reduced activity in schizophrenia, and the differences persisted after controlling for medication or for task performance. Moreover, the hypofrontality appeared to be unrelated to the schizophrenic psychopathology as measured with the PANSS.

The reduced frontal cortex activity during the LFT in schizophrenia found in this study is consistent with the results of many earlier neuroimaging studies. Of greater interest is the topography of the hypofunction. An fMRI study found statistically significant differences between schizophrenia patients and controls in the activity of the left middle and inferior frontal gyri, left insula, and right inferior frontal gyrus during the LFT (Curtis et al., 1998). One NIRS study found statistically significant differences in the lower prefrontal channels bilaterally (Suto et al., 2004), while another emphasized involvement of the frontopolar region, although it too found significant differences in wider areas, including the middle to lower prefrontal regions bilaterally (Takizawa et al., 2008). A third study found hypoactivation of a larger area of prefrontal cortex (Ehlis et al., 2007). A fourth study, on

Table 2 Comparison of NIRS indexes.

AUC WC UP DOWN DC AC

Schizophrenia patients (n = 31)

Healthy controls (n = 26)

P values for the difference between the two groups

When controlled for antipsychotics and anxiolytics

When controlled for task performance

2.1 (2.1) 35.5 (9.3) 0.0014 (0.0027) 0.0004 (0.0056) 2.4 (2.1) 2.5 (1.5)

5.5 (3.1) 34.1 (5.1) 0.0033 (0.0017) − 0.0028 (0.0019) 5.9 (3.4) 4.3 (2.4)

p b 0.001 p = 0.48 p = 0.004 p = 0.005 p b 0.001 p = 0.002

p = 0.001 p = 0.91 p = 0.07 p = 0.003 p = 0.002 p = 0.03

p = 0.001 p = 0.28 p = 0.03 p = 0.17 p b 0.001 p = 0.009

The values are means (SD) unless otherwise noted.

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Table 3 Correlations between NIRS indexes.

AUC WC UP DOWN DC

WC

UP

DOWN

DC

AC

0.39⁎

0.49⁎ 0.07

− 0.32 − 0.24 − 0.32

0.95⁎ 0.32 0.44⁎ − 0.33

0.85⁎ 0.26 0.33 − 0.09 0.88⁎

⁎ indicates p b 0.05/15 = 0.003.

the other hand, found significant differences in both the dorsolateral prefrontal cortex and the dorsal area of the frontopolar cortex bilaterally (Takeshi et al., 2010). The results of our study accord fully with the fMRI study, because we found significant differences in the ventrolateral regions of the prefrontal cortex bilaterally, which correspond to the inferior frontal gyri. The results of our study also corroborate the results of the first two NIRS studies, because we found significant hypofrontality in bilateral lower prefrontal channels, although in our study the involvement of the frontopolar region appeared to be smaller. Despite notable technological advances and the corresponding growth of the literature, the location of the anatomical architecture that subserves executive functions has often been a matter of controversy (Brett et al., 2002). The dorsolateral frontal cortex has been implicated in many cognitive functions, including holding spatial information ‘on-line,’ monitoring and manipulation within working memory, response selection, implementation of strategies to facilitate memory, and the organization of material before encoding. The ventrolateral frontal cortex has been implicated in a similarly wide range of cognitive processes, including the selection, comparison, and judgment of stimuli held in short-term and long-term memory, holding non-spatial information ‘on-line,’ task switching, reversal learning, stimulus selection, and the specification of retrieval cues, while the anterior prefrontal cortex, also known as the frontal pole, has remained largely uncharacterized (Ramnani and Owen, 2004). Fletcher and Henson (2001) summarized the findings as updating/ maintenance of information in the ventrolateral prefrontal cortex, selection/manipulation/monitoring of information in the dorsolateral prefrontal cortex, and selection of processes/subgoals in the anterior prefrontal cortex. When it comes to examining how these executive functions and the anatomical structures underlying them might be impaired in schizophrenia, the picture becomes less straightforward. A recent review has pointed to the quantitative abnormalities in the dorsolateral prefrontal cortex, rostral anterior cingulate, and inferior parietal lobule that underlie the executive dysfunctions in schizophrenia: patients with schizophrenia exhibit relatively inefficient prefrontal activation under low cognitive loads and a decrease in activation when executive demands exceed capacity (Meyer-Lindenberg, 2010). The situation is even more complicated, however, because we now have evidence that compensatory activation occurs in the ventrolateral prefrontal cortex, indicating a system that comes ‘on-line’ as the dorsolateral-prefrontal and anterior cingulate system starts to fail (Tan et al., 2006). In our comparative study using the LFT, the greatest

Table 4 Correlations between the psychopathology of the schizophrenia patients and their NIRS indexes.

AUC WC UP DOWN DC AC

PANSS-Positive

PANSS-Negative

PANSS-General

PANSS-Total

0.05 0.07 − 0.01 − 0.04 − 0.08 0.02

− 0.14 0.24 − 0.10 0.13 − 0.21 − 0.09

− 0.11 0.26 − 0.15 − 0.03 − 0.16 − 0.11

− 0.09 0.23 − 0.11 0.02 − 0.17 − 0.08

No coefficient was statistically significant even at unadjusted p b 0.05.

difference between the schizophrenia patients and the healthy controls was observed in the ventrolateral region, possibly because the LFT requires selection, comparison, and judgment of stimuli held in shortterm and long-term memory and holding non-spatial information ‘online.’ The findings in our study also shed some light on the nature of the hypofrontality observed in schizophrenia patients. The most sensitive index for differentiating the schizophrenia patients from the healthy controls appeared to be the AUC of the oxy-Hb concentrations changes. The smaller AUC is reflected in the lower DC component after Fast Fourier transformation. These differences are most likely due to the slower UP gradient at the start of the task and the corresponding slower DOWN gradient after the end of the task period in schizophrenia. A similar pattern has already been described in earlier NIRS studies (Suto et al., 2004; Takizawa et al., 2008). WC, which basically describes where the peak of the curve lies, and which has been found to be significantly shorter in a group of euthymic unipolar depression patients than in a group of bipolar patients and a healthy control group (Shimodera et al., submitted for publication), did not discriminate between the schizophrenia patient group and the control group. In other words, the curve appears to be uniformly lowered and flattened in schizophrenia. Our study also found less fluctuation of the curve, as evidenced by the lower AC in schizophrenia. In other words, not only the absolute magnitude of oxy-Hb concentration increase but also its vicissitude is attenuated in patients with schizophrenia in comparison with healthy controls. Much to our own surprise, we did not find any correlation between the NIRS indexes and schizophrenia symptoms, while the former are clearly reduced during neurocognitive tasks, whose results, in turn, are known to be important predictors of functional outcomes of schizophrenia. NIRS indexes may then represent useful predictors of the functional outcome of schizophrenia patients, independently of their presenting symptoms. This possibility merits further investigation. There are several limitations to our study. First, we did not administer structured diagnostic interviews to confirm the diagnoses of the patients in our cohort. However, their diagnoses had been confirmed by the psychiatrists in charge of their care for an average of about 4 years, and we consider such longitudinal diagnoses to be as valid as, if not more valid than, structured psychiatric interviews lasting a few hours. The second limitation was that we focused on one neuropsychological task, namely the LFT, because it has been found to be one of the most sensitive measures of the underlying frontal lobe dysfunction in schizophrenia (Ehlis et al., 2007; Ikezawa et al., 2009). However, other cognitive tasks, such as the Tower of London, may also be sensitive to schizophrenia psychopathology (Zhu et al., 2010) and may point to hypofunction in different brain regions. Third, there is a study showing that hypofrontality may characterize schizophrenia at rest as well as during activation (Hoshi, 2003). We will therefore have to study hypofrontality in schizophrenia not only across other activation tasks but also in the absence of any activation tasks. Both these 2nd and 3rd points need be examined in future studies. In summary, our study using NIRS to tap prefrontal cortex activation during the performance of the LFT confirmed its hypoactivation in schizophrenia. The results of our study further located the hypofrontality in bilateral ventrolateral regions, which are believed to be responsible for updating/maintenance of information (Fletcher and Henson, 2001). The nature of the hypofrontality appeared to reside not only in its lesser magnitude but also in its lesser variability. Given the simplicity and relative inexpensiveness of NIRS, it may promise to be a valuable tool for monitoring the treatment of schizophrenia patients, possibly independently of and in conjunction with symptomatological monitoring. Role of the funding source This study required no external funding.

S. Shimodera et al. / Schizophrenia Research 136 (2012) 63–69 Contributors SS and YI conceived and designed the study. SS and SI wrote the protocol. SS, YI, NK, IM and HF undertook patient recruitment and experimental measurements. YI and TAF did the statistical analyses. TAF wrote the first draft of the manuscript. All the authors contributed to and have approved the final manuscript. Conflict of interest YI is an employee of Shimadzu Corporation. TAF has received honoraria for speaking at CME meetings sponsored by Astellas, Dai-Nippon Sumitomo, Eli Lilly, GlaxoSmithKline, Janssen, Kyorin, MDS, Meiji, Otsuka, Pfizer, Shionogi and Yoshitomi. He is on advisory board for Sekisui Chemicals and Takeda Science Foundation. He has received royalties from Igaku-Shoin, Seiwa-Shoten, Nihon Bunka Kagaku-sha and American Psychiatric Publication. The Japanese Ministry of Education, Science, and Technology and the Japanese Ministry of Health, Labor and Welfare have funded his research. All the other authors report that they have no conflicts of interest to declare. Acknowledgments Shimadzu Corporation provided the machine, the personnel and the technique to perform NIRS measurements. Shimadzu had no further involvement in the conception, design, conduct, analyses or writing-up of this study.

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