FRRB Project 2681424 - Assessment of Predictors of Response to Cognitive Training in Patients with First Episode Psychosis

Name and Surname of PI

Bruno Biagianti

Project Acronym


Project ID


Host Institution

Università degli Studi di Milano - Milan

Pathology of Interest


Research Area

Psychiatry and Neuroscience

Project Start Date

1 October 2021

Project End Date

1 October 2022 (anticipated)


€ 171.473,28

Type of Project



Treating cognitive impairments in patients with schizophrenia early in the course of illness is a major goal of 21st century psychiatry. To date, none of the trials of cognitive enhancing medications found significant effects. Recent evidence from three randomized clinical trials shows that a computerized neuroplasticity-based cognitive training program significantly improves in schizophrenia domains of cognition, their neural underpinnings, as well as real-world functioning and quality of life. However, ~40% of the patients do not respond to the treatment. In addition, two studies found improvement on the training exercises but no transfer of these gains to untrained cognitive outcome measures. To date, no studies investigated which neural systems need to be engaged by the training exercises in order to induce cognitive gains. The goal of APReCoT (Assessment of Predictors of Response to Cognitive Training) is to use machine learning and multimodal neuroimaging echniques (fMRI, EEG) to identify baseline predictors of response as well as biomarkers of early neural change. During the fellowship, I will receive advanced training in innovative neuroimaging methods, machine learning, and computational analyses. I will apply these newly acquired competences to a single-arm study that I will conduct in a sample of 50 patients with first episode psychosis who will be asked to complete 20 hours of cognitive training. Multimodal neuroimaging scans and neuropsychological assessments will be administered at 3 time points: at baseline, after 1 hour of training, and immediately after the completion of the intervention. The identification of key neuroimaging indexes that serve as predictors of response and biomarkers will critically inform how to personalize, monitor, predict, and optimize response to cognitive training. If successful, this approach can radically enhance the impact of this innovative treatment on the real-world functioning of individuals with schizophrenia.