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Fong WJ, Tan HM, Garg R, Teh AL, Pan H, Gupta V, Krishna B, Chen ZH, Purwanto NY, Yap F, Tan KH, Chan KYJ, Chan SY, Goh N, Rane N, Tan ESE, Jiang Y, Han M, Meaney M, Wang D, Keppo J, Tan GCY. Comparing feature selection and machine learning approaches for predicting CYP2D6 methylation from genetic variation. Front Neuroinform 2024; 17:1244336. [PMID: 38449836 PMCID: PMC10915285 DOI: 10.3389/fninf.2023.1244336] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2023] [Accepted: 10/18/2023] [Indexed: 03/08/2024] Open
Abstract
Introduction Pharmacogenetics currently supports clinical decision-making on the basis of a limited number of variants in a few genes and may benefit paediatric prescribing where there is a need for more precise dosing. Integrating genomic information such as methylation into pharmacogenetic models holds the potential to improve their accuracy and consequently prescribing decisions. Cytochrome P450 2D6 (CYP2D6) is a highly polymorphic gene conventionally associated with the metabolism of commonly used drugs and endogenous substrates. We thus sought to predict epigenetic loci from single nucleotide polymorphisms (SNPs) related to CYP2D6 in children from the GUSTO cohort. Methods Buffy coat DNA methylation was quantified using the Illumina Infinium Methylation EPIC beadchip. CpG sites associated with CYP2D6 were used as outcome variables in Linear Regression, Elastic Net and XGBoost models. We compared feature selection of SNPs from GWAS mQTLs, GTEx eQTLs and SNPs within 2 MB of the CYP2D6 gene and the impact of adding demographic data. The samples were split into training (75%) sets and test (25%) sets for validation. In Elastic Net model and XGBoost models, optimal hyperparameter search was done using 10-fold cross validation. Root Mean Square Error and R-squared values were obtained to investigate each models' performance. When GWAS was performed to determine SNPs associated with CpG sites, a total of 15 SNPs were identified where several SNPs appeared to influence multiple CpG sites. Results Overall, Elastic Net models of genetic features appeared to perform marginally better than heritability estimates and substantially better than Linear Regression and XGBoost models. The addition of nongenetic features appeared to improve performance for some but not all feature sets and probes. The best feature set and Machine Learning (ML) approach differed substantially between CpG sites and a number of top variables were identified for each model. Discussion The development of SNP-based prediction models for CYP2D6 CpG methylation in Singaporean children of varying ethnicities in this study has clinical application. With further validation, they may add to the set of tools available to improve precision medicine and pharmacogenetics-based dosing.
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Affiliation(s)
- Wei Jing Fong
- Computational Biology, National University of Singapore, Singapore, Singapore
| | - Hong Ming Tan
- Computational Biology, National University of Singapore, Singapore, Singapore
| | - Rishabh Garg
- Computational Biology, National University of Singapore, Singapore, Singapore
| | - Ai Ling Teh
- Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (A*STAR), Singapore, Singapore
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), Singapore, Singapore
| | - Hong Pan
- Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (A*STAR), Singapore, Singapore
| | - Varsha Gupta
- Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (A*STAR), Singapore, Singapore
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), Singapore, Singapore
| | - Bernadus Krishna
- Computational Biology, National University of Singapore, Singapore, Singapore
| | - Zou Hui Chen
- Computational Biology, National University of Singapore, Singapore, Singapore
| | | | - Fabian Yap
- KK Women's and Children's Hospital, Singapore, Singapore
| | - Kok Hian Tan
- KK Women's and Children's Hospital, Singapore, Singapore
- Duke NUS Medical School, Singapore, Singapore
| | - Kok Yen Jerry Chan
- KK Women's and Children's Hospital, Singapore, Singapore
- Duke NUS Medical School, Singapore, Singapore
| | - Shiao-Yng Chan
- Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (A*STAR), Singapore, Singapore
- National University Hospital, Singapore, Singapore
| | | | - Nikita Rane
- Institute of Mental Health,Singapore, Singapore
| | | | | | - Mei Han
- Computational Biology, National University of Singapore, Singapore, Singapore
| | - Michael Meaney
- Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (A*STAR), Singapore, Singapore
| | - Dennis Wang
- Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (A*STAR), Singapore, Singapore
- National Heart and Lung Institute, Imperial College London, London, United Kingdom
| | - Jussi Keppo
- Computational Biology, National University of Singapore, Singapore, Singapore
| | - Geoffrey Chern-Yee Tan
- Computational Biology, National University of Singapore, Singapore, Singapore
- Institute of Mental Health,Singapore, Singapore
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Tan GCY, Wang Z, Tan ESE, Ong RJM, Ooi PE, Lee D, Rane N, Tey SYX, Chua SY, Goh N, Lam GW, Chakraborty A, Yew AKL, Ong SK, Kee JL, Lim XY, Hashim N, Lu SH, Meany M, Tolomeo S, Lee CA, Tan HM, Keppo J. Transdiagnostic clustering of self-schema from self-referential judgements identifies subtypes of healthy personality and depression. Front Neuroinform 2024; 17:1244347. [PMID: 38274390 PMCID: PMC10808829 DOI: 10.3389/fninf.2023.1244347] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2023] [Accepted: 11/06/2023] [Indexed: 01/27/2024] Open
Abstract
Introduction The heterogeneity of depressive and anxiety disorders complicates clinical management as it may account for differences in trajectory and treatment response. Self-schemas, which can be determined by Self-Referential Judgements (SRJs), are heterogeneous yet stable. SRJs have been used to characterize personality in the general population and shown to be prognostic in depressive and anxiety disorders. Methods In this study, we used SRJs from a Self-Referential Encoding Task (SRET) to identify clusters from a clinical sample of 119 patients recruited from the Institute of Mental Health presenting with depressive or anxiety symptoms and a non-clinical sample of 115 healthy adults. The generated clusters were examined in terms of most endorsed words, cross-sample correspondence, association with depressive symptoms and the Depressive Experiences Questionnaire and diagnostic category. Results We identify a 5-cluster solution in each sample and a 7-cluster solution in the combined sample. When perturbed, metrics such as optimum cluster number, criterion value, likelihood, DBI and CHI remained stable and cluster centers appeared stable when using BIC or ICL as criteria. Top endorsed words in clusters were meaningful across theoretical frameworks from personality, psychodynamic concepts of relatedness and self-definition, and valence in self-referential processing. The clinical clusters were labeled "Neurotic" (C1), "Extraverted" (C2), "Anxious to please" (C3), "Self-critical" (C4), "Conscientious" (C5). The non-clinical clusters were labeled "Self-confident" (N1), "Low endorsement" (N2), "Non-neurotic" (N3), "Neurotic" (N4), "High endorsement" (N5). The combined clusters were labeled "Self-confident" (NC1), "Externalising" (NC2), "Neurotic" (NC3), "Secure" (NC4), "Low endorsement" (NC5), "High endorsement" (NC6), "Self-critical" (NC7). Cluster differences were observed in endorsement of positive and negative words, latency biases, recall biases, depressive symptoms, frequency of depressive disorders and self-criticism. Discussion Overall, clusters endorsing more negative words tended to endorse fewer positive words, showed more negative biases in reaction time and negative recall bias, reported more severe depressive symptoms and a higher frequency of depressive disorders and more self-criticism in the clinical population. SRJ-based clustering represents a novel transdiagnostic framework for subgrouping patients with depressive and anxiety symptoms that may support the future translation of the science of self-referential processing, personality and psychodynamic concepts of self-definition to clinical applications.
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Affiliation(s)
| | | | | | - Rachel Jing Min Ong
- Faculty of Social Sciences, National University of Singapore, Singapore, Singapore
| | - Pei En Ooi
- School of Biological Sciences, National Technological University, Singapore, Singapore
| | - Danan Lee
- Yale-NUS College, Singapore, Singapore
| | - Nikita Rane
- Institute of Mental Health, Singapore, Singapore
| | | | - Si Ying Chua
- Institute of Mental Health, Singapore, Singapore
| | | | | | - Atlanta Chakraborty
- Institute of Operations Research and Analytics, National University of Singapore, Singapore, Singapore
| | - Anthony Khye Loong Yew
- Institute of Operations Research and Analytics, National University of Singapore, Singapore, Singapore
| | | | | | - Xin Ying Lim
- Faculty of Social Sciences, National University of Singapore, Singapore, Singapore
| | - Nawal Hashim
- Institute of Mental Health, Singapore, Singapore
| | | | - Michael Meany
- Singapore Institute for Clinical Sciences, A*STAR, Singapore, Singapore
| | - Serenella Tolomeo
- Institute of High Performance Computing (IHPC), Agency for Science, Technology and Research (A*STAR), Singapore, Singapore
| | | | - Hong Ming Tan
- Institute of Operations Research and Analytics, National University of Singapore, Singapore, Singapore
| | - Jussi Keppo
- Institute of Operations Research and Analytics, National University of Singapore, Singapore, Singapore
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Chang S, Sambasivam R, Seow E, Subramaniam M, Ashok Assudani H, Tan GCY, Lu SH, Vaingankar JA. Positive mental health in psychotherapy: a qualitative study from psychotherapists' perspectives. BMC Psychol 2022; 10:111. [PMID: 35488353 PMCID: PMC9055746 DOI: 10.1186/s40359-022-00816-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2021] [Accepted: 04/15/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND There is growing evidence in the literature on the use of positive mental health (PMH) interventions among clinical samples. This qualitative study aims to explore the definitions of PMH from psychotherapists' perspectives, and to examine views and attitudes related to the construct. METHODS Focus group discussions were conducted with psychotherapists at a tertiary psychiatric institute. Focus group sessions were transcribed verbatim and transcripts were analyzed using an inductive thematic approach. RESULTS Five themes related to psychotherapists' definition of PMH were identified: (1) acceptance; (2) normal functioning and thriving in life; (3) resilience; (4) positive overall evaluation of life; (5) absence of negative emotions and presence of positive emotion states. Themes related to views and attitudes towards PMH were: (1) novel and valuable for psychotherapy; (2) reservations with terminology; (3) factors influencing PMH. CONCLUSION PMH in psychotherapy is a multidimensional concept that means more than symptom management and distress reduction in clients. There is potential value for its application in psychotherapy practice, though some concerns need to be addressed before it can be well integrated.
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Affiliation(s)
- Sherilyn Chang
- Research Division, Institute of Mental Health, Singapore, Singapore
| | | | - Esmond Seow
- Research Division, Institute of Mental Health, Singapore, Singapore
| | | | | | - Geoffrey Chern-Yee Tan
- Department of Mood and Anxiety, Institute of Mental Health, Singapore, Singapore.,Singapore Institute of Clinical Sciences, A*STAR, Singapore, Singapore
| | - Sharon Huixian Lu
- Department of Psychology, Institute of Mental Health, Singapore, Singapore
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Chang S, Sambasivam R, Seow E, Tan GCY, Lu SH, Assudani H, Chong SA, Subramaniam M, Vaingankar JA. "We Are All Trying to Find a Way to Help Ourselves": A Look at Self-Help Strategies Among Psychotherapy Clients. Front Psychol 2021; 12:621085. [PMID: 34690850 PMCID: PMC8529116 DOI: 10.3389/fpsyg.2021.621085] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2020] [Accepted: 09/09/2021] [Indexed: 11/23/2022] Open
Abstract
Objective: This study examined self-help strategies engaged by psychotherapy clients and explored their views on such self-help approach. Methods: Secondary analysis of data from a qualitative research study was conducted. A total of 15 psychotherapy clients were recruited, and data were collected via semi-structured interviews. Thematic analysis of data was conducted using inductive approach to examine the content. Results: Three main themes revolving around self-help strategies were identified: (1) types of self-help strategies, (2) reasons for engaging in self-help activities, and (3) effectiveness of self-help strategies. Conclusion: The self-help approach to manage distress is common among psychotherapy clients. This study provided insights into understanding how and why clients use self-help strategies in their daily lives.
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Affiliation(s)
- Sherilyn Chang
- Research Division, Institute of Mental Health, Singapore, Singapore
| | | | - Esmond Seow
- Research Division, Institute of Mental Health, Singapore, Singapore
| | | | - Sharon Huixian Lu
- Department of Psychology, Institute of Mental Health, Singapore, Singapore
| | - Hanita Assudani
- Department of Psychology, Institute of Mental Health, Singapore, Singapore
| | - Siow Ann Chong
- Research Division, Institute of Mental Health, Singapore, Singapore
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Gupta B, Chee KS, Neo LQ, Tang C, Hariram J, Tan GCY, Verma S, Basu S, Appan DP, Ting CC, Abdin E, Lee J. Effect of aripiprazole as an adjunct to atypical antipsychotics on weight and metabolic profile: a 12-week open-label trial. Ther Adv Psychopharmacol 2021; 11:20451253211046765. [PMID: 34646440 PMCID: PMC8504280 DOI: 10.1177/20451253211046765] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/22/2021] [Accepted: 08/27/2021] [Indexed: 11/16/2022] Open
Abstract
BACKGROUND Atypical antipsychotics are widely prescribed, yet have been associated with weight gain and metabolic syndrome. AIM To study the effect of adjunct low-dose aripiprazole on weight and metabolic parameters of subjects on atypical antipsychotics (olanzapine, clozapine or risperidone). METHODS The study was carried out as an open-label trial with a fixed dose of 5 mg aripiprazole added to the patient's current antipsychotic for 12 weeks. The primary outcome measure was mean change in weight, while secondary outcome measures included change in waist circumference; fasting blood glucose; HbA1c; triglycerides; total, HDL and LDL cholesterol levels; functioning; and neurocognition. RESULTS For the overall study (n = 55), there was no significant effect of adjunct aripiprazole on the weight of the subjects. However, the clozapine group achieved significant weight loss (p = 0.002) and also had significant improvements in total cholesterol (p < 0.001), HDL (p = 0.016), LDL (p = 0.044) and triglyceride levels (p = 0.038). The olanzapine group had significant improvement in triglycerides (p = 0.001), and other metabolic parameters for this group showed improvement trends, but did not reach statistical significance. The risperidone group did not show any significant improvement in weight or metabolic parameters. CONCLUSIONS The study adds support to the adjunctive use of aripiprazole to clozapine for weight loss and improvement in metabolic profile, and for reduction in cardiometabolic risk for patients on olanzapine. TRIAL REGISTRATION Clinicaltrials.gov identifier: NCT02949752.
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Affiliation(s)
- Bhanu Gupta
- Institute of Mental Health, Singapore 539747
| | | | - Li-Qi Neo
- Institute of Mental Health, Singapore
| | | | | | | | | | | | | | | | | | - Jimmy Lee
- Institute of Mental Health, Singapore
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Tan GCY, Chu C, Lee YT, Tan CCK, Ashburner J, Wood NW, Frackowiak RS. The influence of microsatellite polymorphisms in sex steroid receptor genes ESR1, ESR2 and AR on sex differences in brain structure. Neuroimage 2020; 221:117087. [PMID: 32593802 PMCID: PMC8960998 DOI: 10.1016/j.neuroimage.2020.117087] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2020] [Revised: 05/11/2020] [Accepted: 06/22/2020] [Indexed: 12/04/2022] Open
Abstract
The androgen receptor (AR), oestrogen receptor alpha (ESR1) and oestrogen receptor beta (ESR2) play essential roles in mediating the effect of sex hormones on sex differences in the brain. Using Voxel-based morphometry (VBM) and gene sizing in two independent samples (discovery n = 173, replication = 61), we determine the common and unique influences on brain sex differences in grey (GM) and white matter (WM) volume between repeat lengths (n) of microsatellite polymorphisms AR(CAG)n, ESR1(TA)n and ESR2(CA)n. In the hypothalamus, temporal lobes, anterior cingulate cortex, posterior insula and prefrontal cortex, we find increased GM volume with increasing AR(CAG)n across sexes, decreasing ESR1(TA)n across sexes and decreasing ESR2(CA)n in females. Uniquely, AR(CAG)n was positively associated with dorsolateral prefrontal and orbitofrontal GM volume and the anterior corona radiata, left superior fronto-occipital fasciculus, thalamus and internal capsule WM volume. ESR1(TA)n was negatively associated with the left superior corona radiata, left cingulum and left inferior longitudinal fasciculus WM volume uniquely. ESR2(CA)n was negatively associated with right fusiform and posterior cingulate cortex uniquely. We thus describe the neuroanatomical correlates of three microsatellite polymorphisms of steroid hormone receptors and their relationship to sex differences. Microsatellite polymorphisms in sex hormone receptor genes influence volume in regions of brain sex difference AR(CAG)n repeat length is positively associated with grey and white matter volume across males and females ESR1(TA)n repeat length is negatively associated with grey and white matter volume across males and females ESR2(CA)n repeat length is negatively associated with grey matter volume in females but not in males Repeat length was associated with volume in the hypothalamus, insula, temporal cortices, prefrontal cortices, inferior and superior longitudinal fasciculi in the three genes. These regions were largely replicated in an independent cohort acquired on a separate scanner.
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Affiliation(s)
- Geoffrey Chern-Yee Tan
- Institute of Mental Health, National Healthcare Group, Singapore; Clinical Imaging Research Centre, National University of Singapore, Singapore; Singapore Institute for Clinical Sciences, Agency for Science, Technology and Research (A(∗)STAR), Singapore.
| | - Carlton Chu
- DeepMind Technologies Limited, United Kingdom, UK
| | - Yu Teng Lee
- University of Sydney, Sydney, NSW, Australia
| | | | - John Ashburner
- Wellcome Centre for Human Neuroimaging, University College London (UCL), United Kingdom, UK
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Sebastian CL, Roiser JP, Tan GCY, Viding E, Wood NW, Blakemore SJ. Effects of age and MAOA genotype on the neural processing of social rejection. Genes Brain Behav 2010; 9:628-37. [PMID: 20497231 DOI: 10.1111/j.1601-183x.2010.00596.x] [Citation(s) in RCA: 23] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Adolescents are often sensitive to peer rejection, a factor that might contribute to the risk of affective disorder in this age group. Previous studies suggest a significant overlap among socioaffective brain regions involved in the response to social rejection, regions continuing to develop functionally during adolescence and regions influenced by monoamine oxidase A (MAOA) polymorphism. The current study investigated whether the neural response to social rejection is functionally immature in adolescents compared with adults, and whether these responses are modulated by MAOA genotype. Blood-oxygen-level-dependent response was measured with functional magnetic resonance imaging during a rejection-themed emotional Stroop task in 19 adolescents (aged 14-16) and 16 adults (aged 23-28) genotyped for MAOA polymorphism. Similar numbers of MAOA-L and MAOA-H carriers were recruited to maximize power to detect genotype effects. Main effects of rejection stimuli (relative to neutral and acceptance control stimuli) were seen in predicted socioaffective brain regions. Adolescents did not show the adult pattern of modulation by rejection stimuli in the right ventrolateral prefrontal cortex, suggesting continued functional maturation of this regulatory region during adolescence. Age and genotype interacted in the left amygdala, in which the predicted effect of genotype on responses to rejection stimuli was seen in the adults, but not in the adolescents. The data suggest continued functional development of the circuitry underlying the processing of social rejection between adolescence and adulthood, and show that the effects of MAOA genotype on neural responses may vary with age.
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Affiliation(s)
- C L Sebastian
- Clinical, Educational and Health Psychology, Division of Psychology and Language Sciences, University College London, London, UK.
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Garrido L, Furl N, Draganski B, Weiskopf N, Stevens J, Tan GCY, Driver J, Dolan RJ, Duchaine B. Voxel-based morphometry reveals reduced grey matter volume in the temporal cortex of developmental prosopagnosics. ACTA ACUST UNITED AC 2010; 132:3443-55. [PMID: 19887506 PMCID: PMC2792372 DOI: 10.1093/brain/awp271] [Citation(s) in RCA: 150] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
Individuals with developmental prosopagnosia exhibit severe and lasting difficulties in recognizing faces despite the absence of apparent brain abnormalities. We used voxel-based morphometry to investigate whether developmental prosopagnosics show subtle neuroanatomical differences from controls. An analysis based on segmentation of T1-weighted images from 17 developmental prosopagnosics and 18 matched controls revealed that they had reduced grey matter volume in the right anterior inferior temporal lobe and in the superior temporal sulcus/middle temporal gyrus bilaterally. In addition, a voxel-based morphometry analysis based on the segmentation of magnetization transfer parameter maps showed that developmental prosopagnosics also had reduced grey matter volume in the right middle fusiform gyrus and the inferior temporal gyrus. Multiple regression analyses relating three distinct behavioural component scores, derived from a principal component analysis, to grey matter volume revealed an association between a component related to facial identity and grey matter volume in the left superior temporal sulcus/middle temporal gyrus plus the right middle fusiform gyrus/inferior temporal gyrus. Grey matter volume in the lateral occipital cortex was associated with component scores related to object recognition tasks. Our results demonstrate that developmental prosopagnosics have reduced grey matter volume in several regions known to respond selectively to faces and provide new evidence that integrity of these areas relates to face recognition ability.
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Affiliation(s)
- Lúcia Garrido
- Institute of Cognitive Neuroscience, Alexandra House, 17 Queen Square, London WC1N3AR, UK.
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