Poster No:
638
Submission Type:
Abstract Submission
Authors:
Nadja Zimmermann1,2,3, Miriam Stüble1,3, Arndt-Lukas Klaassen1, Chantal Michel1, Michael Kaess1,4, Jochen Kindler1, Yosuke Morishima2
Institutions:
1University Hospital of Child and Adolescent Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland, 2Translational Research Center, University Hospital of Psychiatry, University of Bern, Bern, Switzerland, 3Graduate School for Health Sciences, University of Bern, Bern, Switzerland, 4Department of Child and Adolescent Psychiatry, Center for Psychosocial Medicine, University Hospital Heidelberg, Heidelberg, Germany
First Author:
Nadja Zimmermann
University Hospital of Child and Adolescent Psychiatry and Psychotherapy, University of Bern|Translational Research Center, University Hospital of Psychiatry, University of Bern|Graduate School for Health Sciences, University of Bern
Bern, Switzerland|Bern, Switzerland|Bern, Switzerland
Co-Author(s):
Miriam Stüble
University Hospital of Child and Adolescent Psychiatry and Psychotherapy, University of Bern|Graduate School for Health Sciences, University of Bern
Bern, Switzerland|Bern, Switzerland
Arndt-Lukas Klaassen
University Hospital of Child and Adolescent Psychiatry and Psychotherapy, University of Bern
Bern, Switzerland
Chantal Michel
University Hospital of Child and Adolescent Psychiatry and Psychotherapy, University of Bern
Bern, Switzerland
Michael Kaess
University Hospital of Child and Adolescent Psychiatry and Psychotherapy, University of Bern|Department of Child and Adolescent Psychiatry, Center for Psychosocial Medicine, University Hospital Heidelberg
Bern, Switzerland|Heidelberg, Germany
Jochen Kindler
University Hospital of Child and Adolescent Psychiatry and Psychotherapy, University of Bern
Bern, Switzerland
Yosuke Morishima
Translational Research Center, University Hospital of Psychiatry, University of Bern
Bern, Switzerland
Introduction:
A clinical high-risk (CHR) state for psychosis describes a possibly prepsychotic state, marked by prodromal symptoms such as impairment of cognition, affect, and social behaviour (Fusar-Poli, 2013). Such a state usually precedes the onset of Schizophrenia and other psychotic disorders by several years, but only a fraction of patients classified as CHR convert to a first episode psychosis (De Pablo, 2021).
Dysconnection of brain networks has been recognized to lie at the base of psychotic disorders, causing a failure of functional integration on a synaptic level as well as in long-range connectivity. This could be a possible cause for psychotic symptoms as well as cognitive deficits observed in psychotic disorders (Stephan, 2009). Dysconnectivity in psychotic spectrum disorders has been predominantly observed in prefrontal areas, which is already evident in the CHR state (Pettersson-Yeo, 2011) but possibly to a lesser degree (Crossley, 2009).
The concurrent use of transcranial magnetic stimulation (TMS) and electroencephalography (EEG) provides opportunities to measure the temporal order of activations of connected cortical areas and their causal interactions in regards to excitatory or inhibitory functioning (Hallett, 2017). While there is evidence of abnormal signal propagation (Frantseva, 2014) and abnormal synchronized neural oscillations (Ferrarelli, 2008) in schizophrenic patients measured by TMS-EEG, there is a lack of studies investigating these parameters in a CHR population. Therefore, in the current study, we utilized TMS-EEG to study abnormal neural oscillations in CHR.
Methods:
Patients and healthy controls (HC) completed a psychopathological and neuropsychological assessment as well as an MRI and TMS-EEG session. In the individual structural MRIs, the left dorsolateral prefrontal cortex (lDLPFC) and left posterior parietal cortex (lPPC) were marked and subsequently used with a neuronavigational device to mark stimulation target sites on the EEG cap. At each site, single-pulse TMS was applied at both sub- and suprathreshold intensities of the individual motor threshold and TMS-evoked activity was measured simultaneously with a 64 channel EEG. The acquired EEG data was pre-processed in MATLAB, using the EEGLAB and tmseeg toolbox and subsequently analysed with custom scripts. Time-frequency information was extracted by performing Morlet-Wavelet convolution.
Results:
The preliminary analyses of TMS-evoked spectral activity included 29 patients and 29 HC. For the HC group, lDLPFC TMS evoked gamma and beta activities at the site of stimulation and theta activity in a more central area. While the general spatiotemporal pattern of TMS-evoked spectral activity of the patient group looked similar to the HC, activity in all frequency bands was reduced compared to the HC.
When stimulating the lPPC, the HC group showed a similar pattern to lDLPFC TMS evoked activity, but evoked theta activity was significantly lower when compared to lDLPFC stimulation. For patients, the asymmetry of theta activity was not present.
Conclusions:
In the current study, we found an asymmetry in TMS-evoked theta activity between lDLPFC and lPPC, consistent with the typical anatomical asymmetry observed between feedforward and feedback networks (Chen, 2009). In contrast, this asymmetry was not present in the patient group. Theta-band oscillatory activity plays a key role in long-range communication between brain networks (Von Stein, 2000) suggesting that TMS-induced theta activity could represent feed-forward and feed-backward propagation. Our results suggest that patients with CHR have an impairment of the backpropagation of long-range transmission within brain networks.
Brain Stimulation:
Non-invasive Magnetic/TMS 2
TMS
Disorders of the Nervous System:
Psychiatric (eg. Depression, Anxiety, Schizophrenia) 1
Modeling and Analysis Methods:
Connectivity (eg. functional, effective, structural)
Novel Imaging Acquisition Methods:
EEG
Keywords:
Cortex
Electroencephaolography (EEG)
Psychiatric Disorders
Schizophrenia
Transcranial Magnetic Stimulation (TMS)
Other - Oscillations
1|2Indicates the priority used for review
Provide references using author date format
Chen, C.C. (2009). ‘Forward and backward connections in the brain: a DCM study of functional asymmetries’, Neuroimage, vol. 45, no. 2, pp. 453-462.
Crossley, N.A. (2009). ‘Superior temporal lobe dysfunction and frontotemporal dysconnectivity in subjects at risk of psychosis and in first‐episode psychosis’, Human brain mapping, vol. 30, no. 12, pp. 4129-4137.
De Pablo, G.S. (2021). ‘Probability of transition to psychosis in individuals at clinical high risk: an updated meta-analysis’, JAMA psychiatry, vol. 78, no. 9, pp. 970-978.
Ferrarelli, F. (2008). ‘Reduced evoked gamma oscillations in the frontal cortex in schizophrenia patients: a TMS/EEG study’, American Journal of Psychiatry, vol. 165, no. 8, pp. 996-1005.
Frantseva, M. (2014). ‘Disrupted cortical conductivity in schizophrenia: TMS–EEG study’, Cerebral Cortex, vol. 24, no. 1, pp. 211-221.
Fusar-Poli, P. (2013). ‘The psychosis high-risk state: a comprehensive state-of-the-art review’, JAMA psychiatry, vol. 70, no. 1, pp.107-120.
Hallett, M. (2017). ‘Contribution of transcranial magnetic stimulation to assessment of brain connectivity and networks’, Clinical Neurophysiology, vol. 128, no. 11, pp. 2125-2139.
Pettersson-Yeo, W. (2011). ‘Dysconnectivity in schizophrenia: where are we now?’, Neuroscience & Biobehavioral Reviews, vol. 35, no. 5, pp. 1110-1124.
Stephan, K.E. (2009). ‘Dysconnection in schizophrenia: from abnormal synaptic plasticity to failures of self-monitoring’, Schizophrenia bulletin, vol. 35, no. 3, pp. 509-527.
Von Stein, A. (2000). ‘Different frequencies for different scales of cortical integration: from local gamma to long range alpha/theta synchronization’, International journal of psychophysiology, vol. 38, no. 3, pp. 301-313.