DIALOG: Understanding Disorganisation: A Language-focused Global Initiative in Psychosis

Trial statusNot yet recruiting
Trial phaseNot listed
Trial typeObservational
Biological sexAll
Age18-65
SponsorDouglas Mental Health University Institute

About this trial

Disorganized speech, language and communication, also called 'formal thought disorder,' is a key part of severe mental illnesses like psychosis and mood disorders. When someone's communication is disorganized, it makes social interactions difficult, increases stigma and affect educational and employment opportunities. However, we do not know much about why this happens. This project, called DIALOG, aims to understand the brain's role in disorganization by studying everyday language use instead of traditional clinical ratings. The study will look at how our brain creates predictions during interactions and how these processes break down in psychosis. This international project also includes experts with personal experience of mental illness. The study will look at speech, thinking patterns, symptoms, and brain waves. The goal of the study is to see if brain waves are disrupted in psychosis, especially in language-related problems. Speech tasks, like describing pictures, talking about a significant event, and telling a story are administered. These tasks will be audio-recorded for analysis. Non-invasive brain imaging technologies such as Magnetoencephalography (MEG) and Magnetic Resonance Imaging (MRI) are utilized. MRI creates images of the brain's structure, while MEG records magnetic activity from neurons, shown as brain waves. The MRI machine uses a large magnet to create images, and MEG captures small magnetic field changes from brain activity. Participants will also undergo clinical and neurocognitive assessments. The study will combine Large Language Models (LLM) applied to speech recordings with large scale participant data from neuroimaging tools (MRI/MEG). The goal of DIALOG is to pioneer a computationally informed, molecular-to systems-level account of disorganisation, identifying the precise mechanisms that can be targeted with novel treatments. This project aims to gather speech and neuroimaging data from Montreal \[100 healthy volunteers and 50 patients with psychosis\], Groningen \[17 synaptic density PET scans\], Cardiff \[600 participants\] and Marburg \[1600 participants\] with schizophrenia, schizoaffective disorder or mood disorders and user acceptability data at Pavia and Melbourne.

Eligibility criteria

This trial accepts healthy volunteers

Qualifiers

None

Disqualifiers

None

Trial population

From the Greater Montreal Area, participants will be recruited from inpatient/outpatient and community service caseloads held by consultant psychiatrists working at hospital clinics in CIUSSS de l'ouest-de-L'île-de-Montréal. Specifically, involving Douglas Mental Health University Institute: l'Étape Outpatient Clinic, Assertive Community Treatment Clinics, Intensive Psychosocial Rehab Clinic, Aire Ouvert and from Department of Psychiatry clinics at Lakeshore Hospital, St. Mary's Hospital and from the McGill University Health Centre (MUHC). Healthy Control participants will be recruited using research study posters placed on bulletin boards and using online study advertisements.

Trial design

Design model

Case-control

Time perspective

Other

Treatments tested in this trial

Not listed

Trial groups

150 Participants
are grouped into 2 trial groups
Group A: Patients
Group B: Healthy controls

Trial outcomes

Primary outcomes

1

Lexical Predictability measured from speech transcripts

Lexical probabilities of each word along with surprisal, entropy/perplexity values based on the preceding context will be derived using locally implemented Language Models (Neural Networks) applied to recorded speech data. This is a numerical value derived from model-based estimates of word probability.

Time frame
baseline, 1 year
2

Effective connectivity within the language network (functional MRI)

Based on resting functional magnetic resonance imaging, language network dysconnectivity (specifically, the synaptic gain index for regional nodes within the connected network, a ratio without any specific unit) will be estimated. This is a numerical value derived from time series data.

Time frame
baseline, 1 year
3

Beta-oscillatory power during sentence processing in MEG

Magnetoencephalography recordings will be analysed along with time stamps from word stimuli to identify a specific frequency band (beta) and its power based on time-frequency transformations.

Time frame
baseline

Secondary outcomes

Other outcomes

1

Structural connectivity using diffusion tensor imaging

Using Diffusion Tensor Imaging indices of connectivity within and between language network and other large-scale brain networks will be derived and related to measures of disorganization

Time frame
baseline
2

Functional Connectivity using Magnetoencephalography

Using magnetoencephalography indices of connectivity within and between language network and other large-scale brain networks will be derived and related to measures of disorganization

Time frame
baseline
3

Functional Connectivity using resting state functional MRI

Using resting state functional MRI, indices of connectivity within and between language network and other large-scale brain networks will be derived and related to measures of disorganization

Time frame
baseline

Sponsors and contacts

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