Andre F Marquand
Biographic Data
| ID | 1841305 |
|---|---|
| NAME | Andre F Marquand |
| GIVEN NAMES | Andre F |
| FAMILY NAME | Marquand |
| SIGNATURE | MARQUAND A F |
| AFFILIATIONS | Radboud University Nijmegen |
| ORCID | 0000-0001-5903-203X |
| VERIFIED | Yes |
| TOTAL WORKS | 5 |
| TOTAL CITATIONS | 2 |
| AUTHOR COUNT | 5 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2016 |
| LATEST PUBLICATION YEAR | 2023 |
| H-INDEX | 1 |
Prediction of transition to psychosis from an at-risk mental state using structural neuroimaging, genetic, and environmental data
Results showed that none of the modalities alone, i.e., neuroimaging, genetic or environmental data, could predict psychosis from an ARMS statistically better than chance and, as such, no multimodal classification model was trained/tested. These results suggest that the value of structural MRI data and genome-wide genotypes in predicting psychosis from an ARMS, which has been fostered by previous evidence, should be reconsidered
Global urbanicity is associated with brain and behaviour in young people
Urbanicity is a growing environmental challenge for mental health. Here, we investigate correlations of urbanicity with brain structure and function, neuropsychology and mental illness symptoms in young people from China and Europe (total n = 3,867). We developed a remote-sensing satellite measure (UrbanSat) to quantify population density at any point on Earth. UrbanSat estimates of urbanicity were correlated with brain volume, cortical surface a…
Identification of neurobehavioural symptom groups based on shared brain mechanisms
Functional corticostriatal connection topographies predict goal-directed behaviour in humans
Identifying Individuals at High Risk of Psychosis: Predictive Utility of Support Vector Machine using Structural and Functional MRI Data
The identification of individuals at high risk of developing psychosis is entirely based on clinical assessment, associated with limited predictive potential. There is, therefore, increasing interest in the development of biological markers that could be used in clinical practice for this purpose. We studied 25 individuals with an at-risk mental state for psychosis and 25 healthy controls using structural MRI, and functional MRI in conjunction wi…
Global urbanicity is associated with brain and behaviour in young people
Urbanicity is a growing environmental challenge for mental health. Here, we investigate correlations of urbanicity with brain structure and function, neuropsychology and mental illness symptoms in young people from China and Europe (total n = 3,867). We developed a remote-sensing satellite measure (UrbanSat) to quantify population density at any point on Earth. UrbanSat estimates of urbanicity were correlated with brain volume, cortical surface a…
Functional corticostriatal connection topographies predict goal-directed behaviour in humans
Identifying Individuals at High Risk of Psychosis: Predictive Utility of Support Vector Machine using Structural and Functional MRI Data
The identification of individuals at high risk of developing psychosis is entirely based on clinical assessment, associated with limited predictive potential. There is, therefore, increasing interest in the development of biological markers that could be used in clinical practice for this purpose. We studied 25 individuals with an at-risk mental state for psychosis and 25 healthy controls using structural MRI, and functional MRI in conjunction wi…
Functional corticostriatal connection topographies predict goal-directed behaviour in humans
Identification of neurobehavioural symptom groups based on shared brain mechanisms
Global urbanicity is associated with brain and behaviour in young people
Urbanicity is a growing environmental challenge for mental health. Here, we investigate correlations of urbanicity with brain structure and function, neuropsychology and mental illness symptoms in young people from China and Europe (total n = 3,867). We developed a remote-sensing satellite measure (UrbanSat) to quantify population density at any point on Earth. UrbanSat estimates of urbanicity were correlated with brain volume, cortical surface a…
Prediction of transition to psychosis from an at-risk mental state using structural neuroimaging, genetic, and environmental data
Results showed that none of the modalities alone, i.e., neuroimaging, genetic or environmental data, could predict psychosis from an ARMS statistically better than chance and, as such, no multimodal classification model was trained/tested. These results suggest that the value of structural MRI data and genome-wide genotypes in predicting psychosis from an ARMS, which has been fostered by previous evidence, should be reconsidered
Psychology (5 works) · Functional Brain Connectivity Studies (4 works) · Psychiatry (4 works) · Computer Science (3 works) · Advanced Neuroimaging Techniques and Applications (2 works) · Artificial Intelligence (2 works) · Brain Structure and Function (2 works) · Clinical Psychology (2 works) · Medicine (2 works) · Mental Health Research Topics (2 works)