Investigating the neurobiology of schizophrenia and other major psychiatric disorders with Transcranial Magnetic Stimulation

SCHRES-07285; No of Pages 9 Schizophrenia Research xxx (2017) xxx–xxx

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Investigating the neurobiology of schizophrenia and other major psychiatric disorders with Transcranial Magnetic Stimulation Rachel E. Kaskie, Fabio Ferrarelli ⁎ Department of Psychiatry, University of Pittsburgh, USA

a r t i c l e

i n f o

Article history: Received 26 December 2016 Received in revised form 24 April 2017 Accepted 26 April 2017 Available online xxxx Keywords: Transcranial Magnetic Stimulation Motor-evoked potentials EEG Cortical neurophysiological properties Schizophrenia Major psychiatric disorders

a b s t r a c t Characterizing the neurobiology of schizophrenia and other major psychiatric disorders is one of the main challenges of the current research in psychiatry. The availability of Transcranial Magnetic Stimulation (TMS) allows to directly probe virtually any cortical areas, thus providing a unique way to assess the neurophysiological properties of cortical neurons. This article presents a review of studies employing TMS in combination with Motor Evoked Potentials (TMS/MEPs) and high density Electroencephalogram (TMS/hd-EEG) in schizophrenia and other major psychiatric disorders. Studies were identified by conducting a PubMed search using the following search item: “transcranial magnetic stimulation and (Schizophrenia or OCD or MDD or ADHD)”. Studies that utilized TMS/MEP and/or TMS/hd-EEG measures to characterize cortical excitability, inhibition, oscillatory activity, and/or connectivity in psychiatric patients were selected. Across disorders, patients displayed a pattern of reduced cortical inhibition, and to a lesser extent increased excitability, in the motor cortex, which was most consistently established in Schizophrenia. Furthermore, psychiatric patients showed abnormalities in a number of TMS-evoked EEG oscillations, which was most prominent in the prefrontal cortex of Schizophrenia relative to healthy comparison subjects. Overall, results from this review point to significant impairments in cortical excitability, inhibition, and oscillatory activity, especially in frontal areas, in several major psychiatric disorders. Building on these findings, future studies employing TMS-based experimental paradigms may help elucidating the neurobiology of these psychiatric disorders, and may assess the contribution of TMS-related measures in monitoring and possibly maximizing the effectiveness of treatment interventions in psychiatric populations. © 2017 Elsevier B.V. All rights reserved.

1. Introduction Transcranial magnetic stimulation (TMS) is a non-invasive brain stimulation technique that alters directly the membrane potential of cortical neurons. TMS was introduced a little over three decades ago (Barker et al., 1985), and single pulse TMS has been initially employed to test the functional integrity of human cortico-spinal pathways in humans. Specifically, TMS can induce motor evoked potentials (MEPs) in peripheral muscles, and MEPs amplitude, which depends on cortical, spinal, and peripheral neurons, is a straightforward measure of corticospinal excitability. Over the years, various TMS/MEPs paradigms have been developed to assess more specifically excitatory and inhibitory neurons within the motor cortex (Hallett, 2007; Rossini et al., 2015). Nonetheless, all these paradigms relied on modulating MEPs amplitude, thus providing only an indirect assessment of cortical neuronal activity. Furthermore, areas outside of the motor cortex could not be investigated with TMS, due to the lack of measurable outputs. ⁎ Corresponding author at: Department of Psychiatry, University of Pittsburgh, 3501 Forbes Avenue, Pittsburgh, PA 15213, USA. E-mail address: [email protected] (F. Ferrarelli).

High-density electroencephalography (hd-EEG) provides a large number of electrodes–anywhere from 64 to 256 channels–to record the brain's electrical activity. As with conventional EEG, hd-EEG records with high temporal resolution, and the increased number of channels also improves spatial resolution. Such a dense array of electrodes allows detecting local, developmental and/or learning related changes in EEG activity with greater accuracy (Lustenberger and Huber, 2012), and the recent availability of source modeling analyses has enabled the identification of the cortical sources underlying scalp-recorded hd-EEG signals (Lucka et al., 2012). Building on these premises, TMS in combination with hd-EEG has been increasingly utilized to investigate the functional properties of neuronal populations in various cortical areas. For example, some studies have employed TMS excitatory and inhibitory paradigms on the motor cortex (M1) of healthy subjects to induce comparable changes in TMS-evoked EEG and MEP amplitude, thus revealing the cortical nature and the neuronal groups underlying such changes (Ferreri et al., 2011; Ferreri et al., 2012). It has also been shown that the amplitude of TMS-evoked EEG components of M1 can be modulated by peripheral stimuli, and that a similar modulation can be obtained in the Prefrontal cortex (PFC), an area that play a critical role in a number of psychiatric

http://dx.doi.org/10.1016/j.schres.2017.04.045 0920-9964/© 2017 Elsevier B.V. All rights reserved.

Please cite this article as: Kaskie, R.E., Ferrarelli, F., Investigating the neurobiology of schizophrenia and other major psychiatric disorders with Transcranial Magnetic Stimulation, Schizophr. Res. (2017), http://dx.doi.org/10.1016/j.schres.2017.04.045

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R.E. Kaskie, F. Ferrarelli / Schizophrenia Research xxx (2017) xxx–xxx

disorders(Daskalakis et al., 2008b). TMS/hd-EEG can be utilized to assess the oscillatory properties of cortical areas, with TMS evoking alpha oscillations (8–12 Hz) in the occipital cortex, beta oscillations (13–20 Hz) in the parietal cortex and fast beta/gamma oscillations (21–40 Hz) in the frontal cortex (Rosanova et al., 2009), and this variability across brain regions has been confirmed for other TMS-EEG metrics in healthy individuals (Casula et al., 2014; Farzan et al., 2009; Kahkonen et al., 2004). Furthermore, TMS-evoked EEG responses allow assessing with unique spatiotemporal precision connectivity between cortical areas across different behavioral states, including several conditions characterized by loss of consciousness (Ferrarelli et al., 2010; Massimini et al., 2005; Massimini et al., 2010), thus providing the possibility to investigate differences in communication patterns between the healthy and diseased brain. It is therefore not surprising that an increasing number of TMS/hd-EEG studies have been recently conducted in major psychiatric disorders. In this article, we will first review studies employing TMS/MEPs and TMS/hd-EEGs to investigate the motor cortex of psychiatric patients and control subjects. We will then present TMS/hd-EEG studies showing abnormalities in the neurophysiological properties, including oscillatory activity and connectivity, of other cortical areas, including PFC, in psychiatric populations, and especially Schizophrenia. Finally, we will discuss future directions for the TMS/hd-EEG technique, which include characterizing the longitudinal effects of major psychiatric disorders on TMS-evoked responses as well as utilizing TMS-related measures to monitor the efficacy of treatment interventions in psychiatric patients. 2. Materials and methods The systematic literature research for this article was conducted via the internet databases PubMed and MEDLINE (1990–2016), using the following search items: “Transcranial magnetic stimulation and (Schizophrenia or OCD or MDD or ADHD)”. This search offered a total of 713 publications. Since the present review focused primarily on the role of TMS in identifying neurophysiological abnormalities in major psychiatric disorders, publications concerning the treatment of psychiatric disorders were excluded, including those involving repetitive TMS paradigms. We then reviewed the titles and abstracts of the remaining studies and selected those that utilized TMS/MEP and/or TMS/hd-EEG measures to characterize cortical excitability, inhibition, oscillatory activity, and/or connectivity in psychiatric patients. Next, we read through the full text of the articles to evaluate relevant data. This led to an additional 21 publications, which were not identified with the initial search. Only studies published in English, which clearly described in the method section clinical characteristics of participants and the TMS-based experimental design were included. Studies were then divided in those focusing on the motor cortex, and those involving also other cortical areas. This choice was based on three main reasons. First, to emphasize the initial and original contribution of TMS/MEPs studies in characterizing motor cortex dysfunctions in psychiatric patients relative to healthy controls. Second, to highlight the importance of collecting both TMS/MEP and TMS/hd-EEG measures in the same study participants to better characterize the neuronal mechanisms of motor neurophysiological impairments in psychiatric patients. Third, to underlie the unique potential of TMS-related EEG measures in identifying electrophysiological abnormalities beyond the motor cortex, including brain regions such as PFC, which is known to play a critical role in major psychiatric disorders like Schizophrenia. To improve readability for those less familiar with TMS-related measures, we briefly described those measures and cite the most pertinent articles, where these measures were first or best characterized. Finally, some studies that have started using TMS-related measures to characterize the effectiveness of pharmacological and nonpharmacological treatment intervention in psychiatric populations were quoted in the future direction section of this article as preliminary, corroborating evidence.

3. Results 3.1. TMS-related findings in the motor cortex of psychiatric and healthy populations 3.1.1. Motor cortical excitability 3.1.1.1. TMS/MEP findings. Numerous studies have investigated excitability of the motor cortex in psychiatric populations, including Schizophrenia, major depression (MDD), obsessive compulsive disorder (OCD), and attention-deficit hyperactivity disorder (ADHD). Resting motor threshold (rMT), which is the intensity required to induce a ≥ 50 μV MEP in 5 of 10 trials, and MEP amplitude were initially the most commonly reported measures. However, since MEPs are affected by the excitability of cortical, spinal as well as peripheral neurons, additional TMS paradigms have been developed to specifically assess cortical excitability within the motor cortex (Hallett, 2007), including intracortical facilitation (ICF) (Nakamura et al., 1997) and I-wave facilitation (Ziemann et al., 1998). ICF is measured by comparing a supra-threshold test stimulus (TS) with a subthreshold conditioning stimulus (CS) delivered at 10– 15-ms intervals, whereas I-wave facilitation involves a subthreshold CS following a TS at specific intervals of 1.3, 2.5, and 4.5 ms. In a recent meta-analysis rMT did not differ between patients with Schizophrenia (SCZ, N = 500) and healthy subjects (HC, N = 617) across 21 studies (Radhu et al., 2013), although one study not included in the meta-analysis found an elevated rMT in SCZ (N = 22) relative to HC (N = 22) (Hasan et al., 2011). Similarly, MEP amplitude did not differ between SCZ and HC across eight studies (Table 1). Furthermore, no differences were found in ICF in individuals at risk of schizophrenia (Hasan et al., 2012), first-episode (Eichhammer et al., 2004; Wobrock et al., 2009; Wobrock et al., 2008), and both medicated and unmedicated chronic SCZ (Daskalakis et al., 2002; Daskalakis et al., 2008a; Fitzgerald et al., 2002a, 2002b; Hasan et al., 2011; Liu et al., 2009; Pascual-Leone et al., 2002) relative to HC, whereas I-wave facilitation was increased in both medicated (N = 9) and unmedicated (N = 9) SCZ compared with HC (N = 9), although data are from a single study on a small group of patients (Fitzgerald et al., 2003). In a meta-analysis of excitability measures in patients with MDD and healthy controls, no group differences were found in rMT (MDD: N = 176; healthy controls: N = 188) or ICF (MDD: N = 115; healthy controls: N = 130) (Radhu et al., 2013). While only three of these studies measured MEP amplitude, no differences were found between MDD (N = 34) and HC (N = 37) (Radhu et al., 2013) (Table 1). In OCD, two studies investigated motor cortical excitability and found that these patients (N = 50) did not differ from HC (N = 45) in rMT values, whereas they had higher ICF (Greenberg et al., 2000; Richter et al., 2012). Similarly, MEP amplitude was not different between the two groups (Richter et al., 2012). Alterations in rMT, MEP amplitude, and IFC have been inconsistently found in children with ADHD relative to HC, with the majority of studies reporting negative findings (Buchmann et al., 2003; Garvey et al., 2005; Gilbert et al., 2011; Gilbert et al., 2007; Hoegl et al., 2012; Wu et al., 2012). Similarly, in adults with ADHD, no changes in rMT have been reported (Hasan et al., 2013; Hoeppner et al., 2008a; Hoeppner et al., 2008b; Richter et al., 2007; Schneider et al., 2007), and enhanced ICF was found only in one study (Hasan et al., 2013). 3.1.1.2. TMS/EEG findings. Only a handful of studies have examined cortical excitability in healthy and psychiatric patients using TMS/hd-EEGs (Table 2). Casarotto et al. investigated the effects of ECT on eight patients with severe, treatment resistant MDD and found an increase in cortical excitability, measured by the subtended area encompassing the early consecutive positive and negative EEG waves triggered by TMS, in sensorimotor areas compared to baseline recordings, which was significant in every patient (Casarotto et al., 2013). Furthermore, Ferrarelli et al. reported decreased frontal cortical excitability, assessed

Please cite this article as: Kaskie, R.E., Ferrarelli, F., Investigating the neurobiology of schizophrenia and other major psychiatric disorders with Transcranial Magnetic Stimulation, Schizophr. Res. (2017), http://dx.doi.org/10.1016/j.schres.2017.04.045

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Table 1 TMS/MEP findings in SCZ and other psychiatric disorders. Diagnosis/measure Number Increase of studies (N) Schizophrenia Resting motor threshold

Decrease

No change

N = 20 (Bajbouj et al., 2004; Boroojerdi et al., 1999; Daskalakis et al., 2008aAB; Fitzgerald et al., 2002a; Fitzgerald et al., 2002b; Fitzgerald et al., 2003; Herbsman et al., 2009; Hoy et al., 2007; Liu et al., 2009; Oxley et al., 2004; Reid et al., 2002; Wobrock et al., 2009; Wobrock et al., 2008), (Daskalakis et al., 2002)A, (Fitzgerald et al., 2002b)A, (Pascual-Leone et al., 2002)B, (Fitzgerald et al., 2004)B; (Puri et al., 1996); (Mehta et al., 2014)AB; (Strube et al., 2014) N=8 (Chroni et al., 2002; Daskalakis et al., 2008a, b; Enticott et al., 2008; Fitzgerald et al., 2002b; Fitzgerald et al., 2004; Oxley et al., 2004; Soubasi et al., 2010); (Mehta et al., 2014) N = 13 (Daskalakis et al., 2002; Daskalakis et al., 2008a, b; Eichhammer et al., 2004; Fitzgerald et al., 2002b; Fitzgerald et al., 2004; Hasan et al., 2011; Hasan et al., 2012; Liu et al., 2009; Wobrock et al., 2009; Wobrock et al., 2008), (Pascual-Leone et al., 2002)B; (Strube et al., 2014) N=4 (Hasan et al., 2011; Herbsman et al., 2009), (Daskalakis et al., 2008a, b)B; (Ahlgren-Rimpilainen et al., 2013)A

N = 25

N=4 (Fitzgerald et al., 2004; Hasan et al., 2011; Pascual-Leone et al., 2002; Soubasi et al., 2010)A

N=4 (Abarbanel et al., 1996; Chroni et al., 2002; Eichhammer et al., 2004), (Daskalakis et al., 2002)B

Motor evoked potential

N=8

N=1 (Reid et al., 2002)

N=0

Intracortical facilitation

N = 12

N=1 (Pascual-Leone et al., 2002)A

N=0

Cortical silent period

N = 14

N=4 (Fitzgerald et al., 2002b; Fitzgerald et al., 2004), (Daskalakis et al., 2002)B

Short-interval cortical inhibition

N = 14

N=8 (Bajbouj et al., 2006; Hasan et al., 2012; Liu et al., 2009; Soubasi et al., 2010; Wobrock et al., 2009), (Daskalakis et al., 2002)A, (Daskalakis et al., 2008a, b)A; (Strube et al., 2014) N=0

Depression Resting motor threshold

N = 10 (Fitzgerald et al., 2002b; Hasan et al., 2011; Hasan et al., 2012; Liu et al., 2009; Oxley et al., 2004; Wobrock et al., 2008), (Daskalakis et al., 2002)B, (Pascual-Leone et al., 2002)A; (Mehta et al., 2014)B; (Strube et al., 2014)

N=7 (Daskalakis et al., 2008a, b; Eichhammer et al., 2004; Fitzgerald et al., 2002b; Pascual-Leone et al., 2002; Wobrock et al., 2009), (Daskalakis et al., 2002)A, (Pascual-Leone et al., 2002)B; (Mehta et al., 2014)A N=7 (Abarbanel et al., 1996; Bajbouj et al., 2006; Chroni et al., 2002; Grunhaus et al., 2003; Levinson et al., 2010; Maeda et al., 2000; Reid et al., 2002) N=3 (Chroni et al., 2002; Reid et al., 2002; Shajahan et al., 1999) N=2 (Bajbouj et al., 2006; Levinson et al., 2010) N=0

N=8

N=1 (Lefaucheur et al., 2008)

N=0

Motor evoked potential

N=3

N=0

N=0

Intracortical facilitation Cortical silent period

N=3

N=0

N=4

N=1 (Steele et al., 2000)

Short-interval cortical inhibition OCD Resting motor threshold Motor evoked potential Intracortical facilitation Cortical silent period Short-interval cortical inhibition ADHD - children Resting motor threshold

N=3

N=0

N=1 (Lefaucheur et al., 2008) N=3 (Bajbouj et al., 2006; Lefaucheur et al., 2008; Levinson et al., 2010) N=3 (Bajbouj et al., 2006; Lefaucheur et al., 2008), (Levinson et al., 2010)C

N=2

N=0

N=1

N=0

N=2 N=2

N=1 (Richter et al., 2012) N=0

N=3

N=0

N=1 (Richter et al., 2012) N=2 (Greenberg et al., 2000; Greenberg et al., 1998)

N=5

N=0

N=0

N=4

N=0

N=0

Motor evoked

N=1 (Greenberg et al., 2000) N=0 N=0

N=1 (Levinson et al., 2010)

N=1 (Richter et al., 2012) N=1 (Richter et al., 2012) N=1 (Greenberg et al., 2000) N=1 (Greenberg et al., 2000) N=1 (Richter et al., 2012)

N=5 (Buchmann et al., 2003; Garvey et al., 2005; Gilbert et al., 2011; Hoegl et al., 2012; Wu et al., 2012) N=4 (continued on next page)

Please cite this article as: Kaskie, R.E., Ferrarelli, F., Investigating the neurobiology of schizophrenia and other major psychiatric disorders with Transcranial Magnetic Stimulation, Schizophr. Res. (2017), http://dx.doi.org/10.1016/j.schres.2017.04.045

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Table 1 (continued) Diagnosis/measure Number Increase of studies (N)

Decrease

No change

potential

A

Intracortical facilitation Cortical silent period

N=2 N=3

N=1 (Wu et al., 2012) N=0

Short-interval cortical inhibition ADHD - adults Resting motor threshold

N=3

N=0

N=2 (Gilbert et al., 2011; Hoegl et al., 2012; Wu et al., 2012)

N=5

N=0

N=0

Motor evoked potential

N=5

N=0

N=0

Intracortical facilitation

N=4

N=1 (Hasan et al., 2013)

N=0

Cortical silent period Short-interval cortical inhibition

N=2

N=1 (Hasan et al., 2013) N=0

N=0

N=4

N=0 N=0

N=2 (Richter et al., 2007; Schneider et al., 2007)

(Buchmann et al., 2003; Garvey et al., 2005; Hoegl et al., 2012; Wu et al., 2012) N=1 (Gilbert et al., 2011) N=3 (Buchmann et al., 2003; Gilbert et al., 2011; Wu et al., 2012) N=0

N=5 (Hasan et al., 2013; Hoeppner et al., 2008a; Hoeppner et al., 2008b; Richter et al., 2007; Schneider et al., 2007) N=5 (Hasan et al., 2013; Hoeppner et al., 2008a; Hoeppner et al., 2008b; Richter et al., 2007; Schneider et al., 2007) N=3 (Hoeppner et al., 2008a; Richter et al., 2007; Schneider et al., 2007) N=1 (Hoeppner et al., 2008b) N=2 (Hasan et al., 2013; Hoeppner et al., 2008a)

= medicated; B = unmedicated; C = treatment-resistant.

as a reduction in event-related spectral perturbation (ERSP), combined with a reduction in beta-range oscillatory activity in the motor cortex of SCZ compared to HC (Ferrarelli et al., 2012). 3.1.2. Motor cortical inhibition 3.1.2.1. TMS/MEP findings. Several TMS paradigms investigate cortical inhibition, including short-interval cortical inhibition (SICI) (Kujirai et al., 1993), long-interval cortical inhibition (LICI) (Valls-Sole et al., 1992), and cortical silent period (CSP) (Cantello et al., 1992), in healthy subjects and psychiatric patients. SICI consists of applying a sub-threshold conditioning stimulus before a supra-threshold test stimulus at short inter-stimulus intervals (1–6 ms), which results in inhibition of MEP amplitude up to 90% of the baseline response. LICI implicates delivering a supra-threshold conditioning stimulus followed by a supra-threshold test stimulus at long inter-stimulus intervals (60–150 ms), resulting in inhibition of the MEP, whereas CSP refers to an interruption of voluntary muscle contraction by TMS, and it is measured from the MEP onset to the return of EMG activity. SICI was also found to be decreased in a large group of SCZ (N = 335) compared to HC (N = 440), a finding based on 12 studies, whereas there was no difference in CSP between groups across eleven studies, though the results were highly variable (reviewed in (Radhu et al., 2013), see also Table 1). A reduction in cortico-spinal inhibition, reflected by shorted MEP latencies, was also found in an initial study in nine, medication-free SCZ patients (Puri et al., 1996), whereas in another TMS study a larger group (N = 33) of antipsychotic-naive SCZ patients showed deficient motor facilitation of the first dorsal interosseous muscle during action observation relative to rest state, a proxy measure of mirror neuron activity that may underlie social cognition deficits in SCZ(Mehta et al., 2014). Long-term antipsychotic treatment does not appear to change the latency and duration of MEPS but leads to multiple CSP, thus suggesting a deficit in inhibitory motor cortical regulation (Ahlgren-Rimpilainen et al., 2013), whereas deficits in SICI and CSP

were found in both early course and chronic SCZ relative to HC (Strube et al., 2014), thus suggesting that these impairments in motor cortical inhibitory mechanisms are already present at illness onset. SICI and CSP were also significantly reduced in MMD (N = 115) compared HC (N = 130) across three studies (Bajbouj et al., 2006; Lefaucheur et al., 2008; Levinson et al., 2010), though another study found that depressed patients had an increased CSP in comparison to healthy subjects(Steele et al., 2000). Similarly, both SICI and CSP were significantly reduced in OCD patients (N = 62) compared to healthy controls (N = 57), as reported by three (Greenberg et al., 2000; Greenberg et al., 1998; Richter et al., 2012) and two (Greenberg et al., 2000; Richter et al., 2012) studies respectively, although data are from a relatively small sample size (Table 1). Only one study investigated LICI in SCZ, and found no difference when compared to HC (Fitzgerald et al., 2003). Reduced SICI in both child and adult patients suffering from ADHD has been reported in most (Gilbert et al., 2011; Hoegl et al., 2012; Richter et al., 2007; Schneider et al., 2007; Wu et al., 2012), although not all (Hasan et al., 2013; Hoeppner et al., 2008a), TMS studies. Only three studies measured CSP between child ADHD and HC and found no difference (Buchmann et al., 2003; Gilbert et al., 2011; Wu et al., 2012), whereas two studies of CSP in adult ADHD yielded inconclusive evidence (Hasan et al., 2013; Hoeppner et al., 2008b), Table 1.

3.1.2.2. TMS/EEG findings. It has been recently shown that LICI can be assessed through EEG in the motor cortex of healthy individuals (Fitzgerald et al., 2008). Specifically, a reduction of TMS-evoked activity at C3, the electrode that overlies the hand motor area, was selected and LICI was calculated as the area under the rectified unconditioned (single) and conditioned (paired) TMS-evoked waveforms between 50 and 150 ms post stimulus. A significant inhibition in the conditioned LICI was found, which was correlated with the level of MEP suppression (Farzan et al., 2010b).

Please cite this article as: Kaskie, R.E., Ferrarelli, F., Investigating the neurobiology of schizophrenia and other major psychiatric disorders with Transcranial Magnetic Stimulation, Schizophr. Res. (2017), http://dx.doi.org/10.1016/j.schres.2017.04.045

R.E. Kaskie, F. Ferrarelli / Schizophrenia Research xxx (2017) xxx–xxx Table 2 TMS/hd-EEG findings in SCZ and other major psychiatric disorders. Diagnosis

Target area

TMS/hd-EEG findings

MDD Canali et al. (2014)

Prefrontal cortex

Casarotto et al. (2013)

Prefrontal cortex

Sun et al. (2016)

Left DLPFC left motor cortex

Single pulse TMS after treatment with light therapy and sleep deprivation resulted in increased amplitude and slope of TMS-evoked EEG oscillations. In 8 treatment resistant MDD patients, larger TMS-evoked EEG oscillations were found after ECT treatment compared to baseline measurements. In treatment resistant MDD patients, LICI and N100 in the DLPF (but not motor cortex) predicted remission of suicide ideation after treatment with magnetic seizure therapy.

ADHD Helfrich et al. (2012)

D'Agati et al. (2014)

Schizophrenia Levit-Binnun et al. (2010) Ferrarelli et al. (2012)

Primary motor cortex

Primary motor cortex DLPFC

Primary motor cortex Primary motor cortex Parietal cortex prefrontal cortex

Frantseva et al. (2014)

Primary motor cortex

Ferrarelli et al. (2008)

Premotor cortex

Canali et al. (2015)

Premotor cortex

Farzan et al. (2010a)

Primary motor cortex prefrontal cortex Prefrontal cortex

Radhu et al. (2015)

A decrease in TMS-evoked N100 oscillatory component was observed after 1 Hz rTMS in patients with ADHD. Change in amplitude of N100 was correlated with change in MEP amplitude, though this correlation was also found during sham stimulation. In children with ADHD, N100 did not differ from controls at rest. ADHD patients showed smaller increase in N100 amplitude and reduced reaction time variability during no-go trials of a go/no-go task. Amplitude of early TMS-evoked EEG oscillations is decreased in schizophrenia patients compared to healthy controls. Amplitude of early TMS-evoked EEG oscillations in motor cortex is decreased in schizophrenia patients compared to healthy controls. Controls showed an increase in oscillatory activity from parietal to prefrontal cortex (low beta to gamma frequency, respectively), while schizophrenia patients did not show this posterior-to-anterior increase in frequency. No difference in early TMS-evoked EEG oscillations, but later (400–700 ms) oscillations were increased in schizophrenia patients relative to healthy controls. Schizophrenia patients showed a decrease in early TMS-evoked EEG oscillations compared to healthy controls; a specific decrease in gamma power was also found. Patients with MDD, BPAD, and schizophrenia all show decrease in TMS-evoked beta/gamma oscillations in premotor cortex. Schizophrenia patients show a specific deficit in PFC when compared to BPAD patients.

Schizophrenia patients show a specific deficit in PFC when compared to OCD patients.

Farzan et al. recently examined the effects of LICI on cortical oscillations in SCZ, bipolar disorder, and HC in motor cortex and reported no differences across the three groups (Farzan et al., 2010a). A reduction in the suppression of mu, an 8–13 Hz EEG rhythm thought to be generated by mirror neurons, was observed during TMS/EEG recordings of motor cortex in bipolar patients compared to HC, thus suggesting a potential mirror system deficit in these patients(Andrews et al., 2016). However, this reduction was not correlated with decreased performance in social cognitive tasks or with altered TMS motor resonance, another putative measure of mirror system activity. In another study performing both TMS/EEG and TMS/MEP recordings, it was found that SCZ showed no difference in rMT as well as in the TMS-evoked initial EEG response compared to HC, whereas SCZ had higher late, gammarange oscillations in centro-parietal and temporal regions bilaterally (Frantseva et al., 2014).

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The N100, the negative peak around 100 ms of the TMS-evoked EEG response in the motor cortex, is another measure of cortical inhibition. In a recent study, the N100 of the motor cortex fail to predict remission of suicidal ideation in treatment-resistant MDD after magnetic seizure treatment (Sun et al., 2016). The N100 was also investigated both at rest and during a go/no-go task in ADHD and HC (Table 2). While it did not differ between these two groups at rest, children with ADHD showed a smaller increase in N100 amplitude, combined with reduced reaction time variability, during the no-go trials, thus suggesting deficits in inhibitory cortical circuits (D'Agati et al., 2014). 3.2. TMS-related findings in non-motor cortical areas of psychiatric and healthy populations 3.2.1. Cortical inhibition Recent, elegant work has shown that LICI can be measured with TMS/ hd-EEG in PFC in HC (Daskalakis et al., 2008b). Additional experiments by Fitzgerald et al. reported prefrontal LICI is maximal between 50 and 250 ms in PFC, whereas in the parietal area it peaks from 50 to 175 ms (Fitzgerald et al., 2009). While this paradigm has yet to be applied to SCZ, a recent study found that LICI in PFC, but not in the motor cortex, predicted remission of suicidal ideation in MDD patients undergoing magnetic seizure treatment (Sun et al., 2016). Furthermore, Farzan et al. reported that SCZ had significant deficits in inhibition of fast, gammarange oscillations in the DLPFC compared to both healthy and psychiatric controls (Farzan et al., 2010a). Importantly, the authors utilized the modulation of gamma oscillations as an index of cortical inhibition, rather than assessing the ability per se of DLPFC to generate these oscillations. 3.2.2. Cortical excitability TMS-evoked EEG responses provide a measure of the excitability of underlying neuronal populations, which can be characterized both in the time and the frequency domain. For example, Canali et al. recorded EEG responses to TMS of PFC in depressed inpatients with bipolar affective disorder (BPAD) before and after treatment with sleep deprivation and light therapy and found an increase in the amplitude and slope of TMS-evoked EEG oscillations in these patients following treatment interventions (Canali et al., 2014). The same authors also reported that higher values at baseline differentiated responders from non-responders following treatment (Canali et al., 2014). A single blind, sham-controlled study in twenty-five ADHD children reported a decrease in TMS-evoked N100 oscillatory component after 1 Hz rTMS compared to baseline and sham recordings (Helfrich et al., 2012). Amplitude changes in N100 and MEPs correlated significantly, thus suggesting an increase in cortical excitability, although this correlation was also observed for the sham stimulation and possible relationships between variation in N100 amplitude and clinical symptoms of ADHD were not assessed. 3.2.3. Cortical oscillatory activity Several studies have investigated TMS-evoked EEG oscillations over different cortical regions in SCZ. Over the motor cortex, two different studies reported that SCZ had reduced amplitude of TMS-evoked early (≤ 300 ms) oscillations relative to HC (Ferrarelli et al., 2012; Levit-Binnun et al., 2010). By contrast, another study employing TMS on the motor cortex found no differences in the initial TMS-evoked EEG response, whereas oscillations at longer time intervals (400– 700 ms) appear to be increased in SCZ (Frantseva et al., 2014). Our group also assessed the oscillatory activity of the premotor cortex in SCZ and found a reduction in the early TMS-evoked EEG oscillations (Ferrarelli et al., 2008). A time-frequency analysis revealed a specific decrease in premotor gamma-range power and synchronization in these patients. In a follow-up study, we investigated the oscillatory activity of four cortical areas, parietal, motor, premotor, and prefrontal cortices in SCZ and HC. We found that HC had a progressive increase in the frequency of their main oscillatory activity, or natural frequency, from the

Please cite this article as: Kaskie, R.E., Ferrarelli, F., Investigating the neurobiology of schizophrenia and other major psychiatric disorders with Transcranial Magnetic Stimulation, Schizophr. Res. (2017), http://dx.doi.org/10.1016/j.schres.2017.04.045

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parietal (low beta) to the prefrontal (gamma range) cortex (Ferrarelli et al., 2012). By contrast, SCZ patients failed to show this posterior-anterior frequency increase, to the extent that their PFC natural frequency was slower than in any HC. The PFC natural frequency also correlated with symptom severity and reaction time on the Penn Word Recognition Test, thus suggesting that this defect in prefrontal gamma oscillations may underlie some of the clinical features commonly observed in SCZ. Importantly, a recent TMS/hd-EEG study MDD, BPAD, and SCZ showed a similar decrease in TMS-evoked beta/gamma-range oscillations in the premotor cortex of these patients relative to HC (Canali et al., 2015). While these findings seem to point to common neurobiological impairments in major neuropsychiatric disorders, it should be noticed that PFC was not assessed in that study. In contrast, a specific deficit in the PFC of SCZ relative to BPAD (Farzan et al., 2010a) and OCD (Radhu et al., 2015) patients has been recently shown by two elegant TMS/ hd-EEG studies, which is consistent with the unique implication of PFC in the neurobiology of SCZ. 3.2.4. Cortical connectivity TMS-evoked cortical activity propagates both ipsilaterally and contralaterally, and an effective communication within and across hemispheres is thought to be critically implicated in the development and maintenance of functional specialization in different cortical areas (Gazzaniga, 2000). Disruptions in cortical connectivity have been implicated in a variety of psychiatric disorders, including autism (Frith, 2001) and SCZ (Bastos-Leite et al., 2015), thus suggesting that the combination of TMS with EEG may provide unique insight into cortical connectivity abnormalities in these psychiatric disorders. Consistent with this assumption, we found that in SCZ the evoked cortical response after TMS of the premotor cortex hardly propagated beyond the stimulation site, whereas in HC it involved both contro-lateral premotor and bilateral sensorimotor areas (Ferrarelli et al., 2008). Furthermore, Frantseva et al. reported an abnormal propagation of gamma oscillations after TMS of the motor cortex, which was related with positive symptom severity, whereas negative symptom severity was related with aberrant delta and theta propagations (Frantseva et al., 2014). Altogether, despite these promising results, TMS/hd-EEG has been scantily utilized to investigate brain connectivity abnormalities in psychiatric patients. 4. Discussion The results presented in the review show that TMS has been extensively utilized to characterize the neurophysiological properties of the motor cortex in healthy subjects and psychiatric patients. Furthermore, the combination of TMS with hd-EEG has enabled characterizing the excitability, inhibitory properties, oscillatory activity, and connectivity of several cortical areas, including PFC, which are critically implicated in the neurobiology of major psychiatric disorders, and especially SCZ. In what follows, we will briefly discuss the neurochemical basis of the TMS/TMS-EEG findings, and will highlight some limitations, together with several exciting future contributions that the TMS/EEG technique may provide to the research in psychiatry (Fig. 2). 4.1. Neurochemical basis of TMS/hd-EEG findings The TMS/hd-EEG findings in psychiatric disorders presented in this review suggest underlying neurochemical dysfunctions that affect central cortical inhibitory mechanisms, and particularly abnormalities in the GABAergic neurotransmission. In SCZ, prior computational work has demonstrated that a reduction of GABAergic inhibition in prefrontal circuits increases vulnerability to psychosis (Tanaka, 2008), a prediction confirmed by several post-mortem studies (Lewis, 2014) as well as by a recent PET paradigm (Frankle et al., 2015) showing marked impairments in GABA neurotransmission in SCZ. Furthermore, an in silico study employing a biophysically realistic computational model of cortical circuits demonstrated that reduced GABA activity leads to a slowing of fast

oscillations (Volman et al., 2011) – and two recent TMS/hd-EEG studies reported a marked decrease in frontal fast oscillations in SCZ patients relative to healthy controls (Ferrarelli et al., 2008; Ferrarelli et al., 2012). Thus, by measuring TMS-evoked cortical oscillations, TMS-EEG allows for the assessment of GABAergic dysfunction, which is likely implicated in the pathophysiology of SCZ. In major depressive disorder, a similar GABA defect has been proposed. Specifically, Luscher et al. (2011) have summarized much of the existing evidence suggesting that MDD is accompanied by GABAergic dysfunction, including a reduction in the overall brain concentration of GABA and alterations in the structure of GABA receptors (Luscher et al., 2011). This is supported by findings from TMS studies of motor cortical inhibition, wherein patients with MDD have reduced CSP and SICI relative to healthy controls, reflecting a disruption of inhibitory systems. Deficits in frontal oscillatory and inhibitory activity could also be related to hypofunction of the N-methyl-D-aspartate-receptor (NMDAR). Notably, a blockade of excitatory neurotransmission by NMDAR antagonists can induce psychotic-like experiences in healthy subjects, which closely resemble the positive, negative and cognitive impairments of SCZ (Coyle et al., 2012). Furthermore, deficits in NMDAR neurotransmission determine a decrease in GABAergic interneuron activity and consequent pyramidal cell disinhibition, thus diminishing GABA synthesis and release (Gonzalez-Burgos et al., 2015; Moreau and Kullmann, 2013). A reduction in GABAergic inhibitory neurotransmission will then result in abnormal gamma oscillations in the cortex, thus leading to the deficits observed in SCZ and other major psychiatric disorders (Uhlhaas and Singer, 2015). 4.2. Limitations of current TMS-EEG findings While a detailed discussion of the limitations of TMS-EEG findings goes beyond the scope of the present review, we want to highlight three issues that clearly still need to be addressed. 1) Trans-diagnostic overlapping in the TMS-related neurophysiological deficits in psychiatric patients: abnormalities in measures of cortical inhibition and cortical oscillatory activities, assessed with TMs/MEPs and TMS/hd-EEG, have been consistently reported in SCZ. Some of the same deficits have been also reported in other psychiatric patients, thus suggesting that these measures may lack diagnostic specificity. However, these findings have been reported by different research groups employing different recording systems, different data analyses tools, and different comparison groups. It is therefore important that future studies are conducted utilizing the same experimental design on several psychiatric populations, which would help minimize these confounds while at the same time allowing trans-diagnostic comparisons of TMS-related neurophysiological deficits. 2) Effects of psychotropic medications on TMS/MEP-TMS/EEG measures: most of the currently available TMS studies in psychiatry have been conducted on medicated patients, whereas those who were un-medicated at the time of the assessment were not retested after receiving pharmacological treatment. Future studies are therefore needed to more directly address the effects of medications on TMS-related neurophysiological measures. 3) Limited utilization of TMS outside of the motor cortex: as previously reported, the vast majority TMS measures have been traditionally limited to the motor cortex, which is a significant limitation since non-motor neurophysiological processes are of primary interest. Indeed, other brain areas such as the dorsolateral prefrontal cortex may be more proximal to the pathophysiology of psychiatric disorders, and especially SCZ. Future work is therefore needed to fully establish the potential of TMS-EEG in characterizing the neurobiology of SCZ and related disorders. 4.3. Future applications of TMS-EEG in psychiatry 4.3.1. Characterize the impact of disease-related variables of major psychiatric disorders on TMS-EEG measures 4.3.1.1. Psychiatric diagnoses. One important future application for TMSrelated measures involves their ability to contribute to psychiatric

Please cite this article as: Kaskie, R.E., Ferrarelli, F., Investigating the neurobiology of schizophrenia and other major psychiatric disorders with Transcranial Magnetic Stimulation, Schizophr. Res. (2017), http://dx.doi.org/10.1016/j.schres.2017.04.045

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diagnoses. Preliminary evidence suggests that abnormalities in some of these measures may be consistently and specifically assessed in certain psychiatric disorders. For example, Farzan et al. showed that SCZ had significant deficits of cortical inhibition of gamma oscillations in PFC compared to both HC and BPAD patients, whereas no deficits were found in motor cortex (Farzan et al., 2010a). Furthermore, we reported that SCZ had a marked reduction in their main oscillatory activity, or natural frequency, in frontal areas to the extent that the prefrontal natural frequency of these patients was slower than in any HC (Ferrarelli et al., 2012). Although promising, these findings were established in chronic patients. Thus, additional studies involving first-episode patients are needed to establish whether these abnormalities are present at illness onset. It will also be important to collect these TMS/hd-EEG measures in a variety of psychiatric disorders, to assess if they are specific for a patient population. A priority of future research will therefore be to establish the relationship between TMS-related measures and psychiatric diagnoses. 4.3.1.2. Acute vs chronic changes. Along with the diagnosis, another critical variable that characterizes psychiatric disorders is their time course. Recent TMS/hd-EEG work demonstrated a reduction in the oscillatory activity of frontal areas in chronic SCZ, MDD, and BPAD patients relative to HC (Canali et al., 2015; Ferrarelli et al., 2012). Longitudinal studies are however needed to establish when and how these impairments occur along the development of these major psychiatric disorders. This work will help characterize acute vs chronic changes, including the spatial and temporal changes in brain activity during the course of the illness in psychiatric patients. 4.3.1.3. Medication status. The effects of medications on EEG oscillations are still largely unknown. In one of the few studies enrolling both medicated and un-medicated participants, a reduction in EEG gamma oscillatory power was found during cognitive control in first-episode psychotic patients, independent of medication status, relative to healthy controls (Minzenberg et al., 2010). Furthermore, in two recent studies we found no correlation between medication doses and reduced TMSevoked frontal EEG oscillations in psychiatric patients compared to HC (Canali et al., 2015; Ferrarelli et al., 2008; Ferrarelli et al., 2012). We also previously reported that the natural frequencies of non-frontal cortical areas, such as the parietal cortex, were not altered in medicated SCZ, which at least suggest that antipsychotic medications are unlikely to impair the ability to generate neuronal oscillations per se (Ferrarelli et al., 2012). Nonetheless, additional studies are necessary to characterize the role of medication status in TMS-evoked brain activity, including the impact of both acute and chronic medication exposure. Overall, when the relationships between these disease-related variables and TMS-related measures is fully established, we will be able to assess the potential of these measures to serve as biomarkers and/or endophenotypes for some of these psychiatric disorders, including SCZ. 4.3.2. Utilize EEG patterns to maximize efficacy of TMS or other interventions in clinical trials Another potentially interesting application of TMS/hd-EEG involves utilizing the background EEG activity to deliver individual TMS pulses (i.e., interactive stimulation), rather than using invariant stimulus timing parameters. The advantage of this approach was recently demonstrated by a study on forty-two treatment-resistant depressed patients, who received either standard TMS (10 Hz) or interactive TMS over the DLPFC over a randomized, 4 week, double-blind treatment trial(Price et al., 2010). The authors found that the TMS interactive group had greater efficacy than the standard group in both absolute and percentage change in scores on the Hamilton Depression Rating Scale, and the response rate (N 50% reduction) for the interactive technique was also higher (43%, 9/21) compared to the TMS standard technique (22%, 5/23). While additional studies are needed to establish the full benefit of this approach, the use of EEG-based repetitive TMS is

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feasible in psychiatric populations and may yield to higher clinical effect in treatment trials compared to standard TMS treatment paradigms. 4.3.3. Assess with TMS/hd-EEG the effects of pharmacological and nonpharmacological interventions in psychiatric populations TMS-related EEG measures could also be utilized to assess the effects of pharmacological and non-pharmacological interventions in psychiatric populations on cortical excitability, inhibition, and connectivity, and how these changes relate to modifications in the clinical features of these patients. For example, Casarotto et al. reported an increase in frontal cortical excitability, in eight medication-resistant MDD patients after several ECTs treatment, and clinical assessments confirmed the beneficial effects of ECT on depressive symptoms at the group level (Casarotto et al., 2013). A similar relationship between cortical excitability changes and improvements in depressive symptoms was reported by a systematic review in MDD, although these changes were primarily assessed on the motor cortex (Fidalgo et al., 2014). Furthermore, in two recent studies Premoli et al. demonstrated that different pharmacological compounds can selectively modulate the amplitude and latency of several TMS-evoked oscillations, including the N45, the N100, and the P180. These TMS-related measures could not only be useful in assessing both local and network abnormalities in psychiatric patients, but would also establish the effectiveness of pharmacological interventions in ameliorating cortical activity and connectivity dysfunctions in psychiatric populations. 5. Conclusions In sum, in this article we reviewed TMS studies investigating several cortical neurophysiological properties in SCZ and other major psychiatric disorders. A deficit in motor cortical inhibition is a consistently reported finding across several psychiatric groups, whereas abnormalities in cortical oscillatory activity and connectivity are especially prominent in the PFC of SCZ patients. Future work is needed to elucidate the implication of these findings in diagnostic and/or treatment interventions in SCZ and other psychiatric populations. Nonetheless, the direct access provided by TMS to virtually any cortical area combined with the increasing ability of TMS-related paradigms to characterize the spatio-temporal dynamics of cortical neurons may uniquely contribute to further our current understanding of the neurobiology of SCZ and related disorders, thus eventually relieving the suffering of the patients affected by these devastating mental illnesses. Contributors FF designed the study. FF and RK performed the literature search, collected and analyzed the data and constructed, wrote and edited the manuscript. All authors have approved the final manuscript. Role of funding source No funding body agreement. This work was supported by the The Pittsburgh Foundation Emmerling Rising Star Award (FPG00031).

Potentials conflict of interest None. Acknowledgments We would like to thank all patients who agreed to participate to the studies reviewed in the manuscript.

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Please cite this article as: Kaskie, R.E., Ferrarelli, F., Investigating the neurobiology of schizophrenia and other major psychiatric disorders with Transcranial Magnetic Stimulation, Schizophr. Res. (2017), http://dx.doi.org/10.1016/j.schres.2017.04.045