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Modulation of brain activity with transcranial direct current stimulation: Targeting regions implicated in impaired illness awareness in schizophrenia

Published online by Cambridge University Press:  01 January 2020

Julia Kim ,
Eric Plitman ,
Shinichiro Nakajima ,
Youssef Alshehri ,
Yusuke Iwata ,
Jun Ku Chung ,
Fernando Caravaggio ,
Mahesh Menon ,
Daniel M. Blumberger  and
Bruce G. Pollock
...Show all authors
Julia Kim
Affiliation:
aMultimodal Imaging Group, Research Imaging Centre, Centre for Addiction and Mental Health, (CAMH), University of Toronto, Toronto, Ontario, Canada bInstitute of Medical Science, University of Toronto, Toronto, Ontario, Canada
Eric Plitman
Affiliation:
cCerebral Imaging Centre, Douglas Mental Health University Institute, McGill University, Montreal, Quebec, Canada dDepartment of Psychiatry, McGill University, Montreal, Quebec, Canada
Shinichiro Nakajima
Affiliation:
aMultimodal Imaging Group, Research Imaging Centre, Centre for Addiction and Mental Health, (CAMH), University of Toronto, Toronto, Ontario, Canada eDepartment of Psychiatry, University of Toronto, Toronto, Ontario, Canada fGeriatric Mental Health Division, CAMH, University of Toronto, Toronto, Ontario, Canada gDepartment of Neuropsychiatry, Keio University, Tokyo, Japan
Youssef Alshehri
Affiliation:
fGeriatric Mental Health Division, CAMH, University of Toronto, Toronto, Ontario, Canada hCampbell Family Mental Health Research Institute, CAMH, University of Toronto, Toronto, Ontario, Canada
Yusuke Iwata
Affiliation:
aMultimodal Imaging Group, Research Imaging Centre, Centre for Addiction and Mental Health, (CAMH), University of Toronto, Toronto, Ontario, Canada eDepartment of Psychiatry, University of Toronto, Toronto, Ontario, Canada
Jun Ku Chung
Affiliation:
aMultimodal Imaging Group, Research Imaging Centre, Centre for Addiction and Mental Health, (CAMH), University of Toronto, Toronto, Ontario, Canada bInstitute of Medical Science, University of Toronto, Toronto, Ontario, Canada
Fernando Caravaggio
Affiliation:
aMultimodal Imaging Group, Research Imaging Centre, Centre for Addiction and Mental Health, (CAMH), University of Toronto, Toronto, Ontario, Canada eDepartment of Psychiatry, University of Toronto, Toronto, Ontario, Canada
Mahesh Menon
Affiliation:
iUniversity of British Columbia, Vancouver, Canada
Daniel M. Blumberger
Affiliation:
bInstitute of Medical Science, University of Toronto, Toronto, Ontario, Canada eDepartment of Psychiatry, University of Toronto, Toronto, Ontario, Canada fGeriatric Mental Health Division, CAMH, University of Toronto, Toronto, Ontario, Canada hCampbell Family Mental Health Research Institute, CAMH, University of Toronto, Toronto, Ontario, Canada
Bruce G. Pollock
Affiliation:
bInstitute of Medical Science, University of Toronto, Toronto, Ontario, Canada eDepartment of Psychiatry, University of Toronto, Toronto, Ontario, Canada fGeriatric Mental Health Division, CAMH, University of Toronto, Toronto, Ontario, Canada gDepartment of Neuropsychiatry, Keio University, Tokyo, Japan
Gary Remington
Affiliation:
bInstitute of Medical Science, University of Toronto, Toronto, Ontario, Canada eDepartment of Psychiatry, University of Toronto, Toronto, Ontario, Canada fGeriatric Mental Health Division, CAMH, University of Toronto, Toronto, Ontario, Canada hCampbell Family Mental Health Research Institute, CAMH, University of Toronto, Toronto, Ontario, Canada jSchizophrenia Division, CAMH, Toronto, Ontario, Canada
Vincenzo De Luca
Affiliation:
bInstitute of Medical Science, University of Toronto, Toronto, Ontario, Canada eDepartment of Psychiatry, University of Toronto, Toronto, Ontario, Canada fGeriatric Mental Health Division, CAMH, University of Toronto, Toronto, Ontario, Canada hCampbell Family Mental Health Research Institute, CAMH, University of Toronto, Toronto, Ontario, Canada
Ariel Graff-Guerrero
Affiliation:
aMultimodal Imaging Group, Research Imaging Centre, Centre for Addiction and Mental Health, (CAMH), University of Toronto, Toronto, Ontario, Canada bInstitute of Medical Science, University of Toronto, Toronto, Ontario, Canada eDepartment of Psychiatry, University of Toronto, Toronto, Ontario, Canada fGeriatric Mental Health Division, CAMH, University of Toronto, Toronto, Ontario, Canada hCampbell Family Mental Health Research Institute, CAMH, University of Toronto, Toronto, Ontario, Canada
Philip Gerretsen*
Affiliation:
aMultimodal Imaging Group, Research Imaging Centre, Centre for Addiction and Mental Health, (CAMH), University of Toronto, Toronto, Ontario, Canada bInstitute of Medical Science, University of Toronto, Toronto, Ontario, Canada eDepartment of Psychiatry, University of Toronto, Toronto, Ontario, Canada fGeriatric Mental Health Division, CAMH, University of Toronto, Toronto, Ontario, Canada hCampbell Family Mental Health Research Institute, CAMH, University of Toronto, Toronto, Ontario, Canada
*
*Corresponding author at: Centre for Addiction and Mental Health, 80 Workman Way, 6th Floor, Toronto, ON, M6J1H4, Canada. Email addresses: philgerretsen@yahoo.com, philip.gerretsen@camh.ca(P. Gerretsen).

Abstract

Background.

Impaired illness awareness or insight into illness (IIA) is a common feature of schizophrenia that contributes to medication nonadherence and poor clinical outcomes. Neuroimaging studies suggest IIA may arise from interhemispheric imbalance in frontoparietal regions, particularly in the posterior parietal area (PPA) and the dorsolateral prefrontal cortex (dlPFC). In this pilot study, we examined the effects of transcranial direct current stimulation (tDCS) on brain regions implicated in IIA.

Methods.

Eleven patients with schizophrenia with IIA (≥3 PANSS G12) and 10 healthy controls were included. A crossover design was employed where all participants received single-session bi-frontal, bi-parietal, and sham stimulation in random order. For each condition, we measured (i) blood oxygen level-dependent (BOLD) response to an illness awareness task pre- and post-stimulation, (ii) regional cerebral blood-flow (rCBF) prior to and during stimulation, and (iii) changes in illness awareness.

Results.

At baseline, patients with schizophrenia showed higher BOLD-response to an illness awareness task in the left-PPA compared to healthy controls. Bi-parietal stimulation reduced the interhemispheric imbalance in the PPA compared to sham stimulation. Relatedly, bi-parietal stimulation increased rCBF beneath the anode (21% increase in the right-PPA), but not beneath the cathode (5.6% increase in the left-PPA). Bi-frontal stimulation did not induce changes in rCBF. We found no changes in illness awareness.

Conclusion.

Although single-session tDCS did not improve illness awareness, this pilot study provides mechanistic justification for future investigations to determine if multi-session bi-parietal tDCS can induce sustained changes in brain activity in the PPA in association with improved illness awareness.

Keywords

Transcranial direct current stimulationIllness awarenessInsightSchizophreniaFunctional MRIArterial spin labellingRegional cerebral blood flow
Type
Original article
Information
European Psychiatry , Volume 61 , September 2019 , pp. 63 - 71
Copyright
Copyright © 2019 European Psychiatric Association

1. Introduction

Impaired illness awareness or insight into illness (IIA) – having partial or complete lack of conscious awareness of one’s illness, its symptoms, and the need for treatment – is a common feature of schizophrenia [Reference David1, Reference Lincoln, Lullmann and Rief2]. IIA is of high clinical relevance as it contributes to antipsychotic medication nonadherence and poor treatment outcomes [Reference Czobor, Van Dorn, Citrome, Kahn, Fleischhacker and Volavka3, Reference Lysaker, Pattison, Leonhardt, Phelps and Vohs4].

IIA is prototypically associated with right hemisphere brain damage secondary to stroke, but it is also encountered in other neuropsychiatric conditions [Reference Orfei5]. IIA is proposed to arise from interhemispheric imbalance, primarily in frontoparietal regions [Reference Gerretsen, Menon, Chakravarty, Lerch, Mamo and Remington6, Reference Gerretsen, Chakravarty, Mamo, Menon, Pollock and Rajji7]. This imbalance may result from right hemisphere damage in “structural”, lesion-based disorders (e.g., right hemisphere stroke, neurodegeneration) [Reference Mendez8, Reference Schmitz9] or left hemisphere overactivity in “functional” disorders, such as schizophrenia [Reference Cooke, Peters, Kuipers and Kumari10, Reference Shad11].

Support for the interhemispheric imbalance model in patients with schizophrenia comes from functional neuroimaging studies that found increased blood oxygen level-dependent (BOLD) response to an illness awareness task in the left posterior parietal area (PPA) [Reference Gerretsen, Menon, Chakravarty, Lerch, Mamo and Remington6], and increased default-network connectivity with the left-PPA in patients with IIA [Reference Gerretsen, Menon, Mamo, Fervaha, Remington and Pollock12]. Although findings from structural neuroimaging studies are mixed, right hemisphere deficits in patients with IIA have been reported [13–Reference Shad, Muddasani and Keshavan15], including our own study that found reduced right dorsolateral prefrontal cortex (dlPFC) and PPA volumes relative to the left hemisphere [Reference Gerretsen, Chakravarty, Mamo, Menon, Pollock and Rajji7].

Frontoparietal regions contributing to interhemispheric imbalance provide suitable neural targets for non-invasive brain stimulation, such as transcranial direct-current stimulation (tDCS). tDCS applies a weak electric current through anodal and cathodal electrodes placed on the scalp, which have been proposed to increase and decrease cortical excitability, respectively [Reference Nitsche and Paulus16]. Recent studies suggest tDCS may be an efficacious treatment for schizophrenia [17–Reference Aleman, Agrawal, Morgan and David19], including studies that showed improvements in illness awareness [20–Reference Chang, Tzeng, Chao, Yeh and Chang22].

A number of neuroimaging studies in healthy participants examined the effects of tDCS on regional cerebral blood flow (rCBF), a surrogate marker of neural activity [Reference Uludag, Dubowitz, Yoder, Restom, Liu and Buxton23]. Zheng et al. (2011) showed anodal stimulation to the right motor cortex increased rCBF beneath the electrode, whereas cathodal stimulation over the contralateral supraorbital region caused a slight increase in rCBF that decreased after tDCS cessation [Reference Zheng, Alsop and Schlaug24]. Stagg et al. (2013) showed that anodal stimulation of the left dlPFC increased rCBF in this region compared to cathodal stimulation of the same area [Reference Stagg, Lin, Mezue, Segerdahl, Kong and Xie25]. Whether similar changes occur in patients with schizophrenia, and the clinical implications of such alterations, remain unclear.

In this pilot study, we investigated the effects of single-session tDCS on the frontoparietal regions associated with IIA by measuring BOLD-response to an illness awareness task and changes in rCBF. We used two electrode placements, i.e., bi-parietal and bi-frontal tDCS to target the PPA and the dlPFC, respectively. We hypothesized that single-session tDCS would:

  1. (i) Increase BOLD-response in the right-PPA and/or decrease BOLD-response in the left-PPA to an illness awareness task to restore the interhemispheric balance. Our hypothesis was specific to the PPA based on the consistency of this region in relation to IIA in our prior functional neuroimaging studies [Reference Gerretsen, Menon, Chakravarty, Lerch, Mamo and Remington6, Reference Gerretsen, Menon, Mamo, Fervaha, Remington and Pollock12].

  2. (ii) Increase rCBF beneath the anode, but not cathode, during bi-parietal and bi-frontal stimulation.

  3. (iii) Transiently improve illness awareness in patients with schizophrenia.

2. Methods

2.1 Study design

A crossover design was employed where all participants received each of the three conditions separated by at least one week: bi-parietal, bi-frontal, and sham stimulation. The order of stimulation was randomized via a computer-generated list and counterbalanced. During each visit, participants received the following: (i) task-based fMRIs pre- and post-tDCS; (ii) bi-parietal, bi-frontal, or sham stimulation; and (iii) serial arterial spin labeling (ASL) scans prior to and during stimulation to measure rCBF (Fig. 1). Both raters and participants were blind to the stimulation condition. After each stimulation, participants were asked to guess which stimulation condition they received. Randomized allocation concealment and blinding were maintained until all participants completed the study.

Fig. 1. Participants were randomly assigned to receive each of the three single-session tDCS conditions in the scanner: bi-parietal, bi-frontal, and sham stimulation. The order of stimulation was randomized and counterbalanced. During each condition, participants received the following: (i) illness awareness task-based fMRIs pre- and post-tDCS; (ii) bi-parietal, bi-frontal, or sham stimulation; and (iii) serial arterial spin labeling (ASL) sequences prior to and during stimulation. For the bi-parietal condition, the anode and cathode were placed over P4 and P3, respectively. For the bi-frontal condition, the anode and cathode were placed over F4 and F3, respectively. For the sham condition, the electrodes were placed at the site of active treatment (half of the participants P3 and P4 and the other half F3 and F4).

2.2 Participant criteria

Twelve patients with schizophrenia and 11 healthy control participants (HC) were recruited from the Centre for Addiction & Mental Health (CAMH). The study was approved by the Research Ethics Board and was conducted between 2013 and 2016. Capacity to consent to participate in the study was confirmed with the MacArthur Test of Competence [Reference Appelbaum and Grisso26]. Inclusion criteria for patients were: Inpatients or outpatients ≥18 years of age; DSM-IV diagnosis of schizophrenia or schizoaffective disorder; and IIA (≥3 on PANSS G12). Exclusion criteria included: Serious, unstable medical illness, or concomitant medical or neurological illness; acute suicidal or homicidal ideation; formal thought disorder rating >2 on the Scale for the Assessment of Positive Symptoms (SAPS); DSM-IV substance dependence (except caffeine and nicotine) within the past month; pregnant; positive urine drug screen; taking antiepileptics; contraindications to MRI; and a score <32 on the Wide Range Achievement Test-III (WRAT-III) [Reference Wilkinson27].

Inclusion and exclusion criteria for HCs were the same as patients, with the exception of the following requirements for inclusion: No current or past psychiatric disorder; and no first-degree relatives with a primary psychotic disorder.

Of the included participants, one schizophrenia and one HC participant dropped out after receiving sham stimulation due to withdrawal of consent because the MRI sessions were described as too long. For task-based fMRI analyses, post-tDCS data for one schizophrenia participant was excluded due to excess head movement. For rCBF, two schizophrenia and three HC participants were missing rCBF data for bi-frontal stimulation. These participants received stimulation outside the scanner because the MR-compatible electrode wires were damaged by the user. Lastly, some participants were missing data from the last 5-min rCBF interval. This occurred for one schizophrenia participant during bi-parietal and sham stimulation, and three schizophrenia participants during bi-frontal stimulation.

2.3 Study measures

Illness awareness was measured with the VAGUS self-report (VAGUS-SR) and clinician-rated versions (VAGUS-CR) [Reference Gerretsen, Remington, Borlido, Quilty, Hassan and Polsinelli28], and fMRI paradigm scores (higher percentage of items answered correctly represents greater illness awareness). Symptom severity was assessed with the SAPS and the Scale for the Assessment of Negative Symptoms (SANS) [Reference Andreasen29]. The Beck Cognitive Insight Scale (BCIS), composed of the self-reflectiveness and self-certainty subscales, was used to measure cognitive insight [Reference Beck30]. A composite-index score is derived from subtracting the self-certainty from the self-reflectiveness subscale score [Reference Beck30]. The WRAT-III reading subtest was used to measure premorbid IQ [Reference Wilkinson27]. The Edinburgh Handedness Inventory was used to measure laterality [Reference Oldfield31]. Chlorpromazine antipsychotic dose equivalents (CPZ equivalence) were calculated using a previously reported method [Reference Atkins, Burgess, Bottomley and Riccio32, Reference Woods33]. Self-reported smoking status was also collected.

2.4 Statistical analyses

Statistical analyses were carried out using SPSS Statistics v23.0 (IBM Corporation). Independent samples t-tests were used to examine group differences in demographic and clinical characteristics between schizophrenia and HC participants. Linear mixed effects model analyses were performed to examine differences in VAGUS (-SR and -CR), BCIS composite and subscale, and SAPS scores pre- and post-tDCS. A threshold of p<0.008 (i.e., 0.05/6) was used. Linear mixed effects modeling was preferred as it has the capacity to handle missing data by using maximum likelihood estimation (See Supplemental Material 1A). Subsequent exploratory paired t-tests were performed to examine differences in pre- and post-tDCS scores for each stimulation condition.

2.5 tDCS parameters

tDCS was performed using the programmable DC-Stimulator Plus (NeuroConn, GmbH). MR-compatible rubber electrodes (7 × 5 cm) were placed with the long-edge in the anterior-posterior direction using conduction paste and secured with a rubber strap around the head. For the bi-parietal condition, the anode and cathode were placed over P4 and P3, respectively. For the bi-frontal condition, the anode and cathode were placed over F4 and F3, respectively [Reference Klem, Luders, Jasper and Elger34]. For the active conditions, a 2 mA constant current was applied for 20-min. For the sham condition, the electrodes were placed at the site of active stimulation (half of the participants at P3/P4 and the other half at F3/F4), and a 1 mA current was applied for 15 s with a fade in-and-out of 15 s. SimNIBS 2.1.2 (http://simnibs.de/) was used for electric field modeling of bi-parietal and bi-frontal tDCS (Supplemental Material 2 and 3) [Reference Thielscher, Antunes and Saturnino35].

2.6 Illness awareness task

Each participant completed a task in the scanner designed to confront participants with their beliefs about their illness. The same paradigm was employed in a prior study by our group [Reference Gerretsen, Menon, Chakravarty, Lerch, Mamo and Remington6]. The task consisted of a bank of “yes/agree” or “no/disagree” items derived from four categories: general illness awareness, symptom awareness, awareness of the need for treatment, and illness-independent/control. For symptom awareness, the statements were tailored to each participant’s experience. The statements for other categories were common across all participants. The paradigm for HCs was similar consisting of stimuli derived from the same four categories.

Each participant was outfitted with an MR-compatible button-box. An adjustable mirror located above the participant's eyes was used to view the stimuli projected onto a screen placed at the head of the bed. Stimuli were presented using E-Prime software (Psychology Software Tools, Pittsburgh, PA). Each statement was presented for 4 s with an interstimulus interval of 2 s. Participants could respond up to 5 s following the presentation of each stimulus (Supplemental Material 4).

2.7 MRI data acquisition

MRI scans were performed on a Discovery MR750 3.0 T GE scanner (Milwaukee, WI, USA). See Supplemental Material 5A for detailed acquisition parameters.

Using T1-weighted images, cerebrospinal fluid (CSF) to total brain volume (TBV) ratio was calculated as a global measure of cerebral atrophy (Supplemental Material 5B).

2.8 Task-based fMRI analyses

2.8.1 Task-based fMRI: preprocessing

Similar to the analysis performed in our original study to identify the neural correlates of IIA [Reference Gerretsen, Menon, Chakravarty, Lerch, Mamo and Remington6], first-level contrasts were created using random-effect analyses between total illness awareness (i.e., general illness awareness, symptom awareness, and awareness of the need for treatment combined) and illness-independent/control stimuli, and also between each illness awareness category and illness-independent/control stimuli. These contrast images were then used for second-level analyses. See Supplemental Material 6 for a detailed description.

2.8.2 Task-based fMRI: whole brain analyses

Two sample t-tests were used to investigate differences in BOLD-response between schizophrenia and HCs pre- and post-tDCS. As the left-PPA was our a priori region of interest (ROI), our statistical analyses were confined to the PPA (10 mm sphere around the peak -46,-70,+36) [Reference Gerretsen, Menon, Mamo, Fervaha, Remington and Pollock12]. The cluster was reported as significant if the peak survived a threshold of family-wise error (FWE) p<0.05 within this region.

2.8.3 Task-based fMRI: ROI analyses

ROI analyses were performed using the same a priori ROI for the whole brain analysis (10 mm sphere around the peak -/+46,−70,+36) was defined using the Talairach Daemon atlas with WFU-Pickatlas software [36–Reference Maldjian, Laurienti, Kraft and Burdette38]. The mean BOLD-response in each hemisphere was extracted using the REX toolbox (http://web.mit.edu/swg/software.htm).

Linear mixed effects models were used to examine the difference in baseline interhemispheric imbalance between patients with schizophrenia and HCs (i.e., left minus right BOLD-response in the PPA using baseline scans from all visits), as well as the change in interhemispheric imbalance with bi-parietal compared to sham tDCS (See Supplemental Material 1B).

For exploratory purposes, we examined the correlation between left minus right BOLD-response in the PPA and the VAGUS scores. We did not expect to observe any associations due to the limited range in illness awareness scores as all patients included had moderate-to-severe illness awareness impairment.

2.9 Regional CBF analyses

2.9.1 Regional CBF: preprocessing

See Supplemental Material 6 for a detailed description.

2.9.2 Regional CBF: whole brain analyses

Two sample t-tests were performed to examine changes in rCBF following 20-min (or if missing, 15-min) of bi-parietal, bi-frontal, and sham stimulation compared to baseline. A cluster was reported as significant if the peak survived a threshold of FWE p<0.05 [Reference Friston, Holmes, Poline, Price and Frith39].

2.9.3 Regional CBF: ROI analyses

We extracted rCBF from the PPA (10 mm sphere around the peak -/+46,−70,+36) [Reference Gerretsen, Menon, Mamo, Fervaha, Remington and Pollock12] and the dlPFC (10 mm sphere around the peak -/+27,+49,+24) [Reference Gerretsen, Chakravarty, Mamo, Menon, Pollock and Rajji7] using the REX toolbox. Linear mixed effects models were used to measure rCBF differences from baseline between conditions. rCBF was defined as mL of blood per 100 mg of tissue per min (mL/100 mg/min). The significance level was established at p<0.025 (i.e., 0.05/2). Linear contrasts were used to explore rCBF differences between baseline and each 5-min interval (See Supplemental Material 1C). Regression analyses were performed to explore the effects of clinical characteristics, including CSF-to-TBV ratio and CPZ equivalence, on the changes in rCBF following 20-min (or if missing, 15-min) of tDCS.

3. Results

3.1 Participant characteristics

Table 1 presents participant demographic and clinical characteristics. Compared to HCs, patients with schizophrenia had fewer years of education (t(21)=3.02, p=0.007) and higher CSF-to-TBV ratios (t(21)=-2.55, p=0.019). The fMRI task condition response times for symptom awareness and symptom awareness minus illness-independent/control items were significantly longer in the schizophrenia compared to HCs. Supplemental Material 7 includes a list of antipsychotic and concomitant medications.

Table 1 Participant demographic and clinical characteristics at baseline.

SCZ, schizophrenia spectrum disorder; HC, healthy control; IQ, Intelligence Quotient; EHI, Edinburgh Handedness Inventory; CSF, cerebrospinal fluid; TBV, total brain volume; CPZ, chlorpromazine; SAPS, Scale for the Assessment of Positive Symptoms; SANS, Scale for the Assessment of Negative Symptoms; PANSS G12, Positive and Negative Syndrome Scale Insight and Judgement Item; BCIS, Beck's Cognitive Insight Scale.

1. One participant was taking more than one antipsychotic medication.

* p≤0.05.

3.2 Clinical effects

Linear mixed effects model analyses showed a main effect of time (i.e., pre- and post-tDCS) on BCIS-composite (F=15.41, p<0.001), self-reflective (F=11.45, p=0.002), and self-certainty scores (F=8.44, p=0.006). Subsequent exploratory paired t-tests showed differences in BCIS composite scores with bi-frontal (t(10)=-2.8, p=0.019) and sham stimulation (t(11)=-2.51, p=0.029), and self-certainty scores with bi-frontal stimulation (t(10)=3.01, p=0.013). There were no differences in the VAGUS or SAPS scores (Supplemental Material 8). Participants’ guess as to which stimulation condition they received did not differ between conditions. The mean percentage of participants guessing they received active stimulation for the bi-frontal, bi-parietal, and sham conditions was 61%, 75%, and 65%, respectively.

3.3 Task-based fMRI results

3.3.1 Task-based fMRI: whole brain analyses

At baseline, a whole brain analysis comparing the schizophrenia and HC groups using the contrast total illness awareness > illness independent/control stimuli revealed a peak BOLD-response in the left-PPA (-44,-62,+40) (t=3.34, p=0.025, FWE corr.) (Fig. 2A). Post-tDCS, there were no suprathreshold clusters between the groups. Supplemental Material 9 shows the results from other contrasts.

Fig. 2. (A) BOLD-response in the left posterior parietal area (PPA) for the contrast total illness awareness > illness-independent/control stimuli in the schizophrenia compared to the healthy control group. A low threshold of p < 0.01 was used to reveal all brain activity (peak voxel -44, -60, 40). (B) BOLD-response for the contrast total illness awareness > illness-independent/control stimuli in patients with IIA compared to patients with intact illness awareness. Reproduced from our previous study [6]. Regional cerebral blood flow beneath the anode with 20-min of (C) bi-parietal, (D) bi-frontal, (E) and sham tDCS compared to baseline. A low threshold of p<0.05 was used to reveal all regions affected.

3.3.2 Task-based fMRI: ROI analyses

At baseline, linear mixed effect model analysis showed a significant difference in the left minus right PPA BOLD-response (for the contrast total illness awareness > illness-independent/control stimuli) in patients with schizophrenia compared to HCs (F=6.07, p=0.022), suggesting that patients with impaired illness awareness have higher interhemispheric imbalance in the PPA (schizophrenia, left vs. right t(35)=4.26, p<0.001; HC, t(29)=0.05, p=0.959).

Linear mixed effect model analysis showed a significant interaction effect of group (i.e., schizophrenia and HCs), stimulation (sham and bi-parietal tDCS), and time (pre and post-tDCS) (F=6.32, p=0.016). Bi-parietal compared to sham tDCS reduced the interhemispheric imbalance in patients with schizophrenia (F=4.42, p=0.046), but not in HCs (F=2.40, p=0.137). Supplemental Material 10 shows the exploratory results from other contrasts.

Interhemispheric imbalance was correlated with one of the subdomains of the VAGUS, specifically the negative consequences domain (r(12)=-0.632, p=0.028), but not with the VAGUS average (r(12)=-0.247, p=0.438) or other domain scores (illness awareness, r(12)=-0.220, p=0.492; symptom attribution, r(12)=0.345, p=0.272; and need for treatment domain, r(12)=-0.233, p=0.466). Following bi-parietal tDCS, we found no significant correlations between interhemispheric imbalance and VAGUS average or subdomain scores.

3.4 Regional CBF results

3.4.1 Regional CBF: whole brain analyses

Whole brain analyses comparing rCBF at 20-min of bi-parietal, bi-frontal, and sham stimulation to baseline in both the schizophrenia and HC groups revealed no peak activation that survived FWE corr. Fig. 2C-E show the areas of activation with bi-parietal, bi-frontal, and sham stimulation in all participants using a liberal threshold of p<0.05, uncorr. Supplemental Material 11 and Supplemental Material 12 show areas of activation for each of the conditions for the HC and schizophrenia groups, respectively.

3.4.2 Regional CBF: ROI analyses

3.4.2.1 Baseline rCBF

At baseline, HCs had higher rCBF in the PPA (t(21)=2.61, p=0.016) and the dlPFC (t(21)=3.15, p=0.005) compared to the schizophrenia group. Exploratory analyses showed an association between baseline rCBF and CSF-to-TBV ratio in the PPA (F(1,22)=8.46, p=0.008) (Supplemental Material 13) and the dlPFC (F(1,22)=16.81, p=0.001) suggesting cerebral atrophy was related to lower rCBF. There was no association between CPZ equivalence and baseline rCBF.

3.4.2.2 Changes in rCBF with bi-parietal tDCS

There was a significant main effect of group on rCBF beneath the anode (F=8.11, p=0.009), where HCs had higher overall rCBF. There was a significant main effect of stimulation (F=9.05, p=0.007), time (F=5.37, p<0.001), and an interaction effect of stimulation by time (F=3.20, p=0.015). Exploratory analyses showed increased rCBF at 5-min (t=2.52, p=0.013), 10-min (t=3.14, p=0.002), 15-min (t=2.82, p=0.005), and 20-min (t=2.29, p=0.023) of bi-parietal compared to sham stimulation. This corresponded to a 21.0% increase in rCBF in the right-PPA with 20-min of bi-parietal stimulation compared to baseline (Fig. 3).

Fig. 3. Change in regional cerebral blood flow ±1 standard error beneath the cathode (left) and anode (right) at each 5-min interval of bi-parietal compared to sham stimulation. *p<0.05 for subsequent pairwise comparisons. Schizophrenia, schizophrenia spectrum disorder; HC, healthy control.

There was a significant main effect of group on rCBF beneath the cathode (F=1.68, p=0.010) where HCs had higher overall rCBF. No other main or interaction effects survived correction for multiple comparisons. Compared to baseline, there was a 5.6% increase in rCBF in the left-PPA at 20-min.

Exploratory regression analyses showed an association between CPZ equivalence and rCBF change beneath the anode (F(1,10)=7.89, p=0.020) (Fig. 4). Cerebral atrophy and smoking status were not associated with changes in rCBF. Supplemental Material 14 shows the extracted rCBF data.

Fig. 4. Correlation between chlorpromazine equivalent antipsychotic dose and change in regional cerebral blood flow in the right posterior parietal area (PPA) with anodal stimulation in schizophrenia participants.

3.4.2.3 Changes in rCBF with bi-frontal tDCS

There was a significant main effect of group on rCBF beneath the anode (F=6.81, p=0.016) and the cathode (F=9.07, p=0.006) where HCs had higher overall rCBF. There were no other main or interaction effects. Supplemental Material 14 shows the extracted rCBF data.

4. Discussion

This study examined the effects of single-session tDCS on fMRI BOLD-response to an illness awareness task and rCBF. Bi-parietal stimulation significantly reduced the interhemispheric imbalance in the PPA, and relatedly, increased rCBF beneath the anode in the right-PPA. Bi-frontal stimulation did not induce changes in rCBF in the dlPFC. Taken together, the results of this pilot study suggest that single-session bi-parietal tDCS can modulate brain regions implicated in IIA. However, multi-session tDCS may be required to observe clinical effects [Reference Kim, Iwata, Plitman, Caravaggio, Chung and Shah40].

The fMRI illness awareness task employed in this study was designed to assess brain activity at the moment of illness acceptance/denial. In a previous study by our group, the illness awareness task was used to compare patients with impaired versus intact illness awareness. Specifically, we aimed to identify differences in BOLD-response between patients that incorrectly deny having an illness and patients that correctly accept having an illness [Reference Gerretsen, Menon, Chakravarty, Lerch, Mamo and Remington6]. The current study is the first to use the illness awareness task in HCs. We wished to build on our previous work by aiming to identify the differences in BOLD-response between patients that incorrectly deny having an illness and HCs that correctly deny having an illness. The increased BOLD-response in the left-PPA was consistent across both studies (Fig. 2A,B). The consistency of our results between related, but distinct comparison groups support the role of the PPA in IIA in patients with schizophrenia.

The reduction in left-PPA BOLD-response with bi-parietal stimulation suggests that single-session tDCS may transiently resolve the interhemispheric balance associated with IIA. Moreover, this occurred in relation to increased rCBF beneath the anode in the right-PPA (Fig. 2C). However, changes in brain activity with single-session tDCS did not directly correspond with clinical improvements in illness awareness. This is expected as tDCS effects may be delayed and are more likely to be cumulative [Reference Kennedy, Lee and Frangou17, 40–Reference Sampaio-Junior, Tortella, Borrione, Moffa, Machado-Vieira and Cretaz43]. Three recent studies, including two open-labelled [Reference Bose, Shivakumar, Narayanaswamy, Nawani, Subramaniam and Agarwal20, Reference Sreeraj, Dinakaran, Parlikar, Chhabra, Selvaraj and Shivakumar21] and one randomized-sham controlled [Reference Chang, Tzeng, Chao, Yeh and Chang22], showed that multi-session tDCS improves illness awareness in patients with schizophrenia. Bose et al. (2014) and Chang et al. (2018) applied twice-daily tDCS for 5 days with cathodal stimulation to the left temporoparietal junction (i.e., between T3 and P3) and anodal stimulation in the left prefrontal cortex (i.e., between F3 and FP1) [Reference Bose, Shivakumar, Narayanaswamy, Nawani, Subramaniam and Agarwal20, Reference Chang, Tzeng, Chao, Yeh and Chang22]. Sreeraj et al. using high-definition tDCS, a more focal method of electrical stimulation, showed that twice-daily cathodal stimulation to the left temporoparietal junction for 5-days improved illness awareness [Reference Sreeraj, Dinakaran, Parlikar, Chhabra, Selvaraj and Shivakumar21]. Taken together, the results of these studies suggest that multi-session cathodal stimulation of the left parietal area improves illness awareness, possibly by reducing the overactivation in this region. However, it remains unclear if anodal stimulation to the right parietal area provides greater benefit than left parietal cathodal stimulation alone. Further, additional studies are needed to determine the effects of modifications to other tDCS parameters (e.g., intensity, frequency and duration) on tDCS response [Reference Stagg and Nitsche44].

While the results of our study demonstrate that single-session bi-parietal stimulation induces a stable increase in rCBF beneath the anode (Fig. 3), changes in rCBF appeared to be influenced by antipsychotic drug CPZ equivalence. Patients with schizophrenia with higher CPZ equivalence had lower rCBF changes beneath the anode. Interactions between antipsychotic drugs and responses to tDCS in patients with schizophrenia have been reported previously. Agarwal et al. (2016) found that patients taking antipsychotics with lower affinity for dopamine 2 (D2) receptors were more likely to have a favorable response to tDCS in reducing auditory hallucinations Reference Agarwal, Bose, Shivakumar, Narayanaswamy, Chhabra and Kalmady[45]. With our current sample, we are unable to comment on the possible effect of D2 receptor affinity as only 2 of the 12 participants were prescribed high D2 receptor affinity antipsychotic drugs. Notably, 6 of the 12 participants were on clozapine. Further studies are needed to tease out the effect of antipsychotic medications on tDCS response.

Previous investigations have reported on the cognitive benefits of single-session tDCS, particularly in improving working memory and learning in patients with schizophrenia [46–Reference Vercammen, Rushby, Loo, Short, Weickert and Weickert48]. Although we did not observe a main effect of tDCS in improving cognitive insight, post-hoc exploratory analyses showed that bi-frontal stimulation reduced ‘self-certainty’ subscale scores (Supplemental Material 8). This reduction in self-certainty, a core component of cognitive insight as measured with the BCIS, represents a generalized increase in mental flexibility, which according to cognitive insight theorists, may be necessary for improvement in clinical insight [Reference Beck30, Reference van der Meer, Costafreda, Aleman and David49]. However, this finding from our study should be interpreted with caution, especially given we did not observe a change in rCBF in the dlPFC with bi-frontal tDCS. It is possible that our results were underpowered to detect a difference as data from two schizophrenia and three HC participants were missing. Alternatively, methodological (e.g., inaccurate electrode placement) or other patient-specific factors may have hampered the effects of bi-frontal tDCS. Previous studies have shown that the electric fields of frontal tDCS are highly variable due to greater variation in cortical folding patterns in comparison with other brain regions [Reference Laakso, Tanaka, Koyama, De Santis and Hirata50, Reference Tremblay, Lepage, Latulipe-Loiselle, Fregni, Pascual-Leone and Théoret51]. Furthermore, other anatomical differences, such as skull thickness and composition, subcutaneous fat levels, and shunting effects may hamper the effects of tDCS [Reference Opitz, Paulus, Will, Antunes and Thielscher52, Reference Thair, Holloway, Newport and Smith53]. Further studies to assess the distribution of electric fields may be useful to understand, and potentially account for, the inter-subject variability in response to tDCS [54–Reference Woods, Antal, Bikson, Boggio, Brunoni and Celnik56].

Our pilot study has several limitations. First, our sample size was small, limiting multi-level statistical analyses. Relatedly, due to the loss of ASL data during bi-frontal stimulation, we likely did not have enough statistical power to detect changes in rCBF. Second, it is important to note that “sham” tDCS may have some neuromodulatory activity due to the fade-in and fade-out of the stimulus and possible current leakage from the device [Reference Loo, Husain, McDonald, Aaronson, O’Reardon and Alonzo57]. Third, although participants’ guess as to which stimulation condition they received did not differ between conditions, it is possible that blinding was not maintained given the crossover study design. Third, other factors, such as tobacco and nicotine use, may have influenced the results [Reference Brunelin, Hasan, Haesebaert, Nitsche and Poulet58]. Fourth, there is an unavoidable heterogeneity in our schizophrenia sample that may have influenced our results, including treatment responsiveness and antipsychotic drug regimens. Relatedly, given that some participants were taking concurrent medications, the individual and combined pharmacological effects on rCBF remain unclear and require further investigation [Reference Navarro, Gasto, Lomena, Mateos, Portella and Massana59].

5. Conclusion

Overall, this study showed that single-session bi-parietal tDCS can modulate BOLD-response to an illness awareness task and rCBF in the PPA, a brain region implicated in IIA. This pilot study provides mechanistic justification for future investigations to determine if multi-session bi-parietal tDCS can induce sustained changes in brain activity in the PPA in association with improved illness awareness. Additionally, the effects of tDCS on cognitive insight require further exploration as bi-frontal tDCS may enhance mental flexibility. This has implications for the use of tDCS in combination with psychotherapy (e.g., cognitive behavioral therapy for psychosis) to facilitate patients’ re-evaluation of their anomalous experiences.

Financial support

This work was supported by the Canadian Institute of Health Research (CIHR) (MOP-142493 and 141968 to A.G.G.), the Ontario Mental Health Foundation grant (P.G), and the Canada Foundation for Innovation and Ontario Research Fund (B.P.).

Acknowledgments

We would like to thank Wanna Mar, Ausmeema Hossain, Dr. Nancy Lobaugh, and Anusha Ravichandran for their invaluable assistance.

Appendix A Supplementary data

Supplementary material related to this article can be found, in the online version, at doi:https://doi.org/10.1016/j.eurpsy.2019.06.007.

References

David, A.S., Insight and psychosis. Br J Psychiatry, 1990; 156: 798–808.CrossRefGoogle ScholarPubMed
Lincoln, T.M., Lullmann, E., Rief, W., Correlates and long-term consequences of poor insight in patients with schizophrenia. A systematic review. Schizophr Bull, 2007; 33: 1324–1342. doi: http://dx.doi.org/10.1093/schbul/sbm002CrossRefGoogle ScholarPubMed
Czobor, P., Van Dorn, R.A., Citrome, L., Kahn, R.S., Fleischhacker, W.W., Volavka, J., Treatment adherence in schizophrenia: a patient-level meta-analysis of combined CATIE and EUFEST studies. Eur Neuropsychopharmacol, 2015; 25: 1158–1166. doi: http://dx.doi.org/10.1016/j.euroneuro.2015.04.003CrossRefGoogle ScholarPubMed
Lysaker, P.H., Pattison, M.L., Leonhardt, B.L., Phelps, S., Vohs, J.L., Insight in schizophrenia spectrum disorders: relationship with behavior, mood and perceived quality of life, underlying causes and emerging treatments. World Psychiatry, 2018; 17: 12–23. doi: http://dx.doi.org/10.1002/wps.20508CrossRefGoogle ScholarPubMed
Orfei, M.D., Unawareness of illness in neuropsychiatric disorders: phenomenological certainty versus etiopathogenic vagueness. Neuroscientist, 2008; 14: 203–222.CrossRefGoogle ScholarPubMed
Gerretsen, P., Menon, M., Chakravarty, M.M., Lerch, J.P., Mamo, D.C., Remington, G., et al. Illness denial in schizophrenia spectrum disorders: a function of left hemisphere dominance. Hum Brain Mapp, 2015; 36: 213–225. doi: http://dx.doi.org/10.1002/hbm.22624CrossRefGoogle ScholarPubMed
Gerretsen, P., Chakravarty, M.M., Mamo, D., Menon, M., Pollock, B.G., Rajji, T.K., et al. Frontotemporoparietal asymmetry and lack of illness awareness in schizophrenia. Hum Brain Mapp, 2013; 34: 1035–1043.CrossRefGoogle Scholar
Mendez, M.F., Loss of insight and functional neuroimaging in frontotemporal dementia. J Neuropsychiatry Clin Neurosci, 2005; 17: 413–416.CrossRefGoogle ScholarPubMed
Schmitz, T.W., Neural correlates of self-evaluative accuracy after traumatic brain injury. Neuropsychologia, 2006; 44: 762–773.CrossRefGoogle ScholarPubMed
Cooke, M.A., Peters, E.R., Kuipers, E., Kumari, V., Disease, deficit or denial? Models of poor insight in psychosis. Acta Psychiatr Scand, 2005; 112: 4–17. doi: 10.1111/j.1600-0447.2005.00537.xCrossRefGoogle ScholarPubMed
Shad, M.U., Neurobiological underpinnings of insight deficits in schizophrenia. Int Rev Psychiatry, 2007; 19: 437–446.CrossRefGoogle Scholar
Gerretsen, P., Menon, M., Mamo, D.C., Fervaha, G., Remington, G., Pollock, B.G., et al. Impaired insight into illness and cognitive insight in schizophrenia spectrum disorders: resting state functional connectivity. Schizophr Res, 2014; 160: 43–50. doi: http://dx.doi.org/10.1016/j.schres.2014.10CrossRefGoogle ScholarPubMed
Emami, S., Guimond, S., Mallar Chakravarty, M., Lepage, M., Cortical thickness and low insight into symptoms in enduring schizophrenia. Schizophr Res, 2016; 170: 66–72.CrossRefGoogle ScholarPubMed
Flashman, L.A., McAllister, T.W., Andreasen, N.C., Saykin, A.J., Smaller brain size associated with unawareness of illness in patients with schizophrenia. Am J Psychiatry, 2000; 157: 1167–1169.CrossRefGoogle ScholarPubMed
Shad, M.U., Muddasani, S., Keshavan, M.S., Prefrontal subregions and dimensions of insight in first-episode schizophrenia — a pilot study. Psychiatry Res Neuroimaging, 2006; 146: 35–42.CrossRefGoogle ScholarPubMed
Nitsche, M.A., Paulus, W., Excitability changes induced in the human motor cortex by weak transcranial direct current stimulation. J Physiology, 2000; 527: 633–639.CrossRefGoogle ScholarPubMed
Kennedy, N.I., Lee, W.H., Frangou, S., Efficacy of non-invasive brain stimulation on the symptom dimensions of schizophrenia: a meta-analysis of randomized controlled trials. Eur Psychiatry, 2018; 49: 69–77. doi: http://dx.doi.org/10.1016/j.eurpsy.2017.12.025CrossRefGoogle ScholarPubMed
Osoegawa, C., Gomes, J.S., Grigolon, R.B., Brietzke, E., Gadelha, A., Lacerda, A.L.T. et al. Non-invasive brain stimulation for negative symptoms in schizophrenia: an updated systematic review and meta-analysis. Schizophr Res, 201810.1016/j.schres.2018.01.010Google Scholar
Aleman, A., Agrawal, N., Morgan, K.D., David, A.S., Insight in psychosis and neuropsychological function: meta-analysis. Br J Psychiatry, 2006; 189: 204–212.CrossRefGoogle ScholarPubMed
Bose, A., Shivakumar, V., Narayanaswamy, J.C., Nawani, H., Subramaniam, A., Agarwal, S.M., et al. Insight facilitation with add-on tDCS in schizophrenia. Schizophr Res, 2014; 156: 63–65. doi: http://dx.doi.org/10.1016/j.schres.2014.03.029CrossRefGoogle Scholar
Sreeraj, V.S., Dinakaran, D., Parlikar, R., Chhabra, H., Selvaraj, S., Shivakumar, V., et al. High-definition transcranial direct current simulation (HD-tDCS) for persistent auditory hallucinations in schizophrenia. Asian J Psychiatr, 2018; 37: 46–50. doi: http://dx.doi.org/10.1016/j.ajp.2018.08.008CrossRefGoogle Scholar
Chang, C.C., Tzeng, N.S., Chao, C.Y., Yeh, C.B., Chang, H.A., The effects of add-on fronto-temporal transcranial direct current stimulation (tDCS) on auditory verbal hallucinations, other psychopathological symptoms and insight in schizophrenia: a randomized, double-blind, sham-controlled trial. Int J Neuropsychopharmacol, 201810.1093/ijnp/pyy074Google Scholar
Uludag, K., Dubowitz, D.J., Yoder, E.J., Restom, K., Liu, T.T., Buxton, R.B., Coupling of cerebral blood flow and oxygen consumption during physiological activation and deactivation measured with fMRI. NeuroImage, 2004; 23: 148–155.CrossRefGoogle ScholarPubMed
Zheng, X., Alsop, D.C., Schlaug, G., Effects of transcranial direct current stimulation (tDCS) on human regional cerebral blood flow. NeuroImage, 2011; 58: 26–33. doi: http://dx.doi.org/10.1016/j.neuroimage.2011.06.018CrossRefGoogle ScholarPubMed
Stagg, C.J., Lin, R.L., Mezue, M., Segerdahl, A., Kong, Y., Xie, J., et al. Widespread modulation of cerebral perfusion induced during and after transcranial direct current stimulation applied to the left dorsolateral prefrontal cortex. J Neurosci, 2013; 33: 11425–11431. doi: 10.1523/jneurosci.3887-12.2013CrossRefGoogle ScholarPubMed
Appelbaum, P.S., Grisso, T., The MacArthur treatment competence study. I: mental illness and competence to consent to treatment. Law Hum Behav, 1995; 19: 105–126.CrossRefGoogle Scholar
Wilkinson, G.S., WRAT-3: Wide range achievement test administration manual, Wilmington, Del: Wide Range, Inc.; 1993.Google Scholar
Gerretsen, P., Remington, G., Borlido, C., Quilty, L., Hassan, S., Polsinelli, G., et al. The VAGUS insight into psychosis scale – self-report and clinician-rated versions. Psychiatry Res, 2014; 220: 1084–1089. doi: http://dx.doi.org/10.1016/j.psychres.2014.08.005CrossRefGoogle ScholarPubMed
Andreasen, N.C., Scale for the assessment of positive symptoms (SAPS), Iowa City: University of Iowa; 1983.Google Scholar
Beck, A., A new instrument for measuring insight: the Beck Cognitive Insight Scale. Schizophr Res, 2004; 68: 319–329.CrossRefGoogle ScholarPubMed
Oldfield, R.C., The assessment and analysis of handedness: the Edinburgh inventory. Neuropsychologia, 1971; 9: 97–113.CrossRefGoogle ScholarPubMed
Atkins, M., Burgess, A., Bottomley, C., Riccio, M., Chlorpromazine equivalents: a consensus of opinion for both clinical and research applications. Psychiatr Bull, 1997; 21: 224CrossRefGoogle Scholar
Woods, S.W., Chlorpromazine equivalent doses for the newer atypical antipsychotics. J Clin Psychiatry, 2003; 64: 663–667.CrossRefGoogle ScholarPubMed
Klem, G.H., Luders, H.O., Jasper, H.H., Elger, C., The ten-twenty electrode system of the International Federation. The International Federation of Clinical Neurophysiology. Electroencephalogr Clin Neurophysiol Suppl, 1999; 52: 3–6.Google ScholarPubMed
Thielscher, A., Antunes, A., Saturnino, G.B., Field modeling for transcranial magnetic stimulation: a useful tool to understand the physiological effects of TMS?. Conf Proc IEEE Eng Med Biol Soc 2015, 2015; 222–225, doi: 10.1109/EMBC.2015.7318340CrossRefGoogle Scholar
Lancaster, J.L., The Talairach daemon, a database server for Talairach atlas labels. NeuroImage, 1997; 5: S633Google Scholar
Lancaster, J.L., Woldorff, M.G., Parsons, L.M., Liotti, M., Freitas, C.S., Rainey, L., et al. Automated Talairach Atlas labels for functional brain mapping. Hum Brain Mapp, 2000; 10: 120–131.3.0.CO;2-8>CrossRefGoogle ScholarPubMed
Maldjian, J.A., Laurienti, P.J., Kraft, R.A., Burdette, J.H., An automated method for neuroanatomic and cytoarchitectonic atlas-based interrogation of fMRI data sets. NeuroImage, 2003; 19: 1233–1239.CrossRefGoogle ScholarPubMed
Friston, K.J., Holmes, A., Poline, J.B., Price, C.J., Frith, C.D., Detecting activations in PET and fMRI: levels of inference and power. NeuroImage, 1996; 4: 223–235. doi: http://dx.doi.org/10.1006/nimg.1996.0074CrossRefGoogle Scholar
Kim, J., Iwata, Y., Plitman, E., Caravaggio, F., Chung, J.K., Shah, P., et al. A meta-analysis of transcranial direct current stimulation for schizophrenia: “Is more better?”. J Psychiatr Res, 2019; 110: 117–126. doi: http://dx.doi.org/10.1016/j.jpsychires.2018.12.009CrossRefGoogle Scholar
Bikson, M., Brunoni, A.R., Charvet, L.E., Clark, V.P., Cohen, L.G., Deng, Z.-D., et al. Rigor and reproducibility in research with transcranial electrical stimulation: an NIMH-sponsored workshop. Brain Stimul, 2018; 11: 465–480. doi: http://dx.doi.org/10.1016/j.brs.2017.12.008CrossRefGoogle ScholarPubMed
Mariano, T.Y., Burgess, F.W., Bowker, M., Kirschner, J., Van’t Wout-Frank, M., Jones, R.N. et al. Transcranial direct current stimulation for affective symptoms and functioning in chronic low back pain: a pilot double-blinded, randomized, placebo-controlled trial. Pain Med, 201810.1093/pm/pny188Google Scholar
Sampaio-Junior, B., Tortella, G., Borrione, L., Moffa, A.H., Machado-Vieira, R., Cretaz, E., et al. Efficacy and safety of transcranial direct current stimulation as an add-on treatment for bipolar depression: a randomized clinical trial. JAMA Psychiatry, 2018; 75: 158–166. doi: http://dx.doi.org/10.1001/jamapsychiatry.2017.4040CrossRefGoogle ScholarPubMed
Stagg, C.J., Nitsche, M.A., Physiological basis of transcranial direct current stimulation. Neuroscientist, 2011; 17: 37–53. doi: 10.1177/1073858410386614CrossRefGoogle ScholarPubMed
Agarwal, S.M., Bose, A., Shivakumar, V., Narayanaswamy, J.C., Chhabra, H., Kalmady, S.V., et al. Impact of antipsychotic medication on transcranial direct current stimulation (tDCS) effects in schizophrenia patients. Psychiatry Res, 2016; 235: 97–103.CrossRefGoogle ScholarPubMed
Hoy, K.E., Arnold, S.L., Emonson, M.R., Daskalakis, Z.J., Fitzgerald, P.B., An investigation into the effects of tDCS dose on cognitive performance over time in patients with schizophrenia. Schizophr Res, 2014; 155: 96–100. doi: http://dx.doi.org/10.1016/j.schres.2014.03.006CrossRefGoogle ScholarPubMed
Papazova, I., Strube, W., Becker, B., Henning, B., Schwippel, T., Fallgatter, A.J. et al. Improving working memory in schizophrenia: effects of 1mA and 2mA transcranial direct current stimulation to the left DLPFC. Schizophr Res, 201810.1016/j.schres.2018.06.032CrossRefGoogle Scholar
Vercammen, A., Rushby, J.A., Loo, C., Short, B., Weickert, C.S., Weickert, T.W., Transcranial direct current stimulation influences probabilistic association learning in schizophrenia. Schizophr Res, 2011; 131: 198–205. doi: http://dx.doi.org/10.1016/j.schres.2011.06.021CrossRefGoogle Scholar
van der Meer, L., Costafreda, S., Aleman, A., David, A.S., Self-reflection and the brain: a theoretical review and meta-analysis of neuroimaging studies with implications for schizophrenia. Neurosci Biobehav Rev, 2010; 34: 935–946. doi: http://dx.doi.org/10.1016/j.neubiorev.2009.12.004CrossRefGoogle Scholar
Laakso, I., Tanaka, S., Koyama, S., De Santis, V., Hirata, A., Inter-subject variability in electric fields of motor cortical tDCS. Brain Stimul, 2015; 8: 906–913. doi: http://dx.doi.org/10.1016/j.brs.2015.05.002CrossRefGoogle ScholarPubMed
Tremblay, S., Lepage, J.-F., Latulipe-Loiselle, A., Fregni, F., Pascual-Leone, A., Théoret, H., The uncertain outcome of prefrontal tDCS. Brain Stimul, 2014; 7: 773–783. doi: http://dx.doi.org/10.1016/j.brs.2014.10.003CrossRefGoogle ScholarPubMed
Opitz, A., Paulus, W., Will, S., Antunes, A., Thielscher, A., Determinants of the electric field during transcranial direct current stimulation. NeuroImage, 2015; 109: 140–150. doi: http://dx.doi.org/10.1016/j.neuroimage.2015.01.033CrossRefGoogle ScholarPubMed
Thair, H., Holloway, A.L., Newport, R., Smith, A.D., Transcranial direct current stimulation (tDCS): a beginner’s guide for design and implementation. Front Neurosci, 2017; 11: 641, doi: 10.3389/fnins.2017.00641CrossRefGoogle ScholarPubMed
Bikson, M., Rahman, A., Datta, A., Computational models of transcranial direct current stimulation. Clin EEG Neurosci, 2012; 43: 176–183. doi: 10.1177/1550059412445138CrossRefGoogle ScholarPubMed
Lee, W.H., Kennedy, N.I., Bikson, M., Frangou, S., A computational assessment of target engagement in the treatment of auditory hallucinations with transcranial direct current stimulation. Front Psychiatry, 2018; 9: 48, doi: 10.3389/fpsyt.2018.00048CrossRefGoogle ScholarPubMed
Woods, A.J., Antal, A., Bikson, M., Boggio, P.S., Brunoni, A.R., Celnik, P., et al. A technical guide to tDCS, and related non-invasive brain stimulation tools. Clin Neurophysiol, 2016; 127: 1031–1048. doi: http://dx.doi.org/10.1016/j.clinph.2015.11.012CrossRefGoogle ScholarPubMed
Loo, C.K., Husain, M.M., McDonald, W.M., Aaronson, S., O’Reardon, J.P., Alonzo, A., et al. International randomized-controlled trial of transcranial Direct Current Stimulation in depression. Brain Stimul, 2018; 11: 125–133. doi: http://dx.doi.org/10.1016/j.brs.2017.10.011CrossRefGoogle ScholarPubMed
Brunelin, J., Hasan, A., Haesebaert, F., Nitsche, M.A., Poulet, E., Nicotine smoking prevents the effects of frontotemporal transcranial direct current stimulation (tDCS) in hallucinating patients with schizophrenia. Brain Stimul, 2015; 8: 1225–1227. doi: http://dx.doi.org/10.1016/j.brs.2015.08.002CrossRefGoogle ScholarPubMed
Navarro, V., Gasto, C., Lomena, F., Mateos, J.J., Portella, M.J., Massana, G., et al. Frontal cerebral perfusion after antidepressant drug treatment versus ECT in elderly patients with major depression: a 12-month follow-up control study. J Clin Psychiatry, 2004; 65: 656–661.CrossRefGoogle ScholarPubMed
Figure 0

Fig. 1. Participants were randomly assigned to receive each of the three single-session tDCS conditions in the scanner: bi-parietal, bi-frontal, and sham stimulation. The order of stimulation was randomized and counterbalanced. During each condition, participants received the following: (i) illness awareness task-based fMRIs pre- and post-tDCS; (ii) bi-parietal, bi-frontal, or sham stimulation; and (iii) serial arterial spin labeling (ASL) sequences prior to and during stimulation. For the bi-parietal condition, the anode and cathode were placed over P4 and P3, respectively. For the bi-frontal condition, the anode and cathode were placed over F4 and F3, respectively. For the sham condition, the electrodes were placed at the site of active treatment (half of the participants P3 and P4 and the other half F3 and F4).

Figure 1

Table 1 Participant demographic and clinical characteristics at baseline.

Figure 2

Fig. 2. (A) BOLD-response in the left posterior parietal area (PPA) for the contrast total illness awareness > illness-independent/control stimuli in the schizophrenia compared to the healthy control group. A low threshold of p < 0.01 was used to reveal all brain activity (peak voxel -44, -60, 40). (B) BOLD-response for the contrast total illness awareness > illness-independent/control stimuli in patients with IIA compared to patients with intact illness awareness. Reproduced from our previous study [6]. Regional cerebral blood flow beneath the anode with 20-min of (C) bi-parietal, (D) bi-frontal, (E) and sham tDCS compared to baseline. A low threshold of p<0.05 was used to reveal all regions affected.

Figure 3

Fig. 3. Change in regional cerebral blood flow ±1 standard error beneath the cathode (left) and anode (right) at each 5-min interval of bi-parietal compared to sham stimulation. *p<0.05 for subsequent pairwise comparisons. Schizophrenia, schizophrenia spectrum disorder; HC, healthy control.

Figure 4

Fig. 4. Correlation between chlorpromazine equivalent antipsychotic dose and change in regional cerebral blood flow in the right posterior parietal area (PPA) with anodal stimulation in schizophrenia participants.

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