René S. Kahn

YNICL Journal 2021 Journal Article

Altered effective connectivity within an oculomotor control network in individuals with schizophrenia

• Matthew Lehet
• Ivy F. Tso
• Sebastiaan F.W. Neggers
• Ilse A. Thompson
• Beier Yao
• René S. Kahn
• Katharine N. Thakkar

Rapid inhibition or modification of actions is a crucial cognitive ability, which is impaired in persons with schizophrenia (SZP). Primate neurophysiology studies have identified a network of brain regions that subserves control over gaze. Here, we examine effective connectivity within this oculomotor control network in SZP and healthy controls (HC). During fMRI, participants performed a stop-signal task variant in which they were instructed to saccade to a visual target (no-step trials) unless a second target appeared (redirect trials); on redirect trials, participants were instructed to inhibit the planned saccade and redirect to the new target. We compared functional responses on redirect trials to no-step trials and used dynamic causal modelling (DCM) to examine group differences in network effective connectivity. Behaviorally, SZP were less efficient at inhibiting, which was related to their employment status. Compared to HC, they showed a smaller difference in activity between redirect trials and no-step trials in frontal eye fields (FEF), supplementary eye fields (SEF), inferior frontal cortex (IFC), thalamus, and caudate. DCM analyses revealed widespread group differences in effective connectivity across the task, including different patterns of self-inhibition in many nodes in SZP. Group differences in how effective connectivity was modulated on redirect trials revealed differences between the FEF and SEF, between the SEF and IFC, between the superior colliculus and the thalamus, and self-inhibition within the FEF and caudate. These results provide insight into the neural mechanisms of inefficient inhibitory control in individuals with schizophrenia.

YNICL Journal 2020 Journal Article

Altered thalamocortical structural connectivity in persons with schizophrenia and healthy siblings

• Beier Yao
• Sebastiaan F.W. Neggers
• René S. Kahn
• Katharine N. Thakkar

Schizophrenia has long been framed as a disorder of altered brain connectivity, with dysfunction in thalamocortical circuity potentially playing a key role in the development of the illness phenotype, including psychotic symptomatology and cognitive impairments. There is emerging evidence for functional and structural hypoconnectivity between thalamus and prefrontal cortex in persons with schizophrenia spectrum disorders, as well as hyperconnectivity between thalamus and sensory and motor cortices. However, it is unclear whether thalamocortical dysconnectivity is a general marker of vulnerability to schizophrenia or a specific mechanism of schizophrenia pathophysiology. This study aimed to answer this question by using diffusion-weighted imaging to examine thalamocortical structural connectivity in 22 persons with schizophrenia or schizoaffective disorder (SZ), 20 siblings of individuals with a schizophrenia spectrum disorder (SIB), and 44 healthy controls (HC) of either sex. Probabilistic tractography was used to quantify structural connectivity between thalamus and six cortical regions of interest. Thalamocortical structural connectivity was compared among the three groups using cross-thalamic and voxel-wise approaches. Thalamo-prefrontal structural connectivity was reduced in both SZ and SIB relative to HC, while SZ and SIB did not differ from each other. Thalamo-motor structural connectivity was increased in SZ relative to SIB and HC, while SIB and HC did not differ from each other. Hemispheric differences also emerged in thalamic connectivity with motor, posterior parietal, and temporal cortices across all groups. The results support the hypothesis that altered thalamo-prefrontal structural connectivity is a general marker of vulnerability to schizophrenia, whereas altered connectivity between thalamus and motor cortex is related to illness expression or illness-related secondary factors.

YNIMG Journal 2020 Journal Article

Changes in the intracranial volume from early adulthood to the sixth decade of life: A longitudinal study

• Yaron Caspi
• Rachel M. Brouwer
• Hugo G. Schnack
• Marieke E. van de Nieuwenhuijzen
• Wiepke Cahn
• René S. Kahn
• Wiro J. Niessen
• Aad van der Lugt

Normal brain-aging occurs at all structural levels. Excessive pathophysiological changes in the brain, beyond the normal one, are implicated in the etiology of brain disorders such as severe forms of the schizophrenia spectrum and dementia. To account for brain-aging in health and disease, it is critical to study the age-dependent trajectories of brain biomarkers at various levels and among different age groups. The intracranial volume (ICV) is a key biological marker, and changes in the ICV during the lifespan can teach us about the biology of development, aging, and gene X environment interactions. However, whether ICV changes with age in adulthood is not resolved. Applying a semi-automatic in-house-built algorithm for ICV extraction on T1w MR brain scans in the Dutch longitudinal cohort (GROUP), we measured ICV changes. Individuals between the ages of 16 and 55 years were scanned up to three consecutive times with 3.32±0.32 years between consecutive scans (N = 482, 359, 302). Using the extracted ICVs, we calculated ICV longitudinal aging-trajectories based on three analysis methods; direct calculation of ICV differences between the first and the last scan, fitting all ICV measurements of individuals to a straight line, and applying a global linear mixed model fitting. We report statistically significant increase in the ICV in adulthood until the fourth decade of life (average change +0.03%/y, or about 0.5 ml/y, at age 20), and decrease in the ICV afterward (-0.09%/y, or about -1.2 ml/y, at age 55). To account for previous cross-sectional reports of ICV changes, we analyzed the same data using a cross-sectional approach. Our cross-sectional analysis detected ICV changes consistent with the previously reported cross-sectional effect. However, the reported amount of cross-sectional changes within this age range was significantly larger than the longitudinal changes. We attribute the cross-sectional results to a generational effect. In conclusion, the human intracranial volume does not stay constant during adulthood but instead shows a small increase during young adulthood and a decrease thereafter from the fourth decade of life. The age-related changes in the longitudinalmeasure are smaller than those reported using cross-sectional approaches and unlikely to affect structural brain imaging studies correcting for intracranial volume considerably. As to the possible mechanisms involved, this awaits further study, although thickening of the meninges and skull bones have been proposed, as well as a smaller amount of brain fluids addition above the overall loss of brain tissue.

YNIMG Journal 2020 Journal Article

Neuroharmony: A new tool for harmonizing volumetric MRI data from unseen scanners

• Rafael Garcia-Dias
• Cristina Scarpazza
• Lea Baecker
• Sandra Vieira
• Walter H.L. Pinaya
• Aiden Corvin
• Alberto Redolfi
• Barnaby Nelson

YNICL Journal 2019 Journal Article

Interhemispheric connectivity and hemispheric specialization in schizophrenia patients and their unaffected siblings

• Xiao Chang
• Guusje Collin
• René C.W. Mandl
• Wiepke Cahn
• René S. Kahn

Hemispheric integration and specialization are two prominent organizational principles for macroscopic brain function. Impairments of interhemispheric cooperation have been reported in schizophrenia patients, but whether such abnormalities should be attributed to effects of illness or familial risk remains inconclusive. Moreover, it is unclear how abnormalities in interhemispheric connectivity impact hemispheric specialization. To address these questions, we performed magnetic resonance imaging (MRI) in a large cohort of 253 participants, including 84 schizophrenia patients, 106 of their unaffected siblings and 63 healthy controls. Interhemispheric connectivity and hemispheric specialization were calculated from resting-state functional connectivity, and compared across groups. Results showed that schizophrenia patients exhibit lower interhemispheric connectivity as compared to controls and siblings. In addition, patients showed higher levels of hemispheric specialization as compared to siblings. Level of interhemispheric connectivity and hemispheric specialization correlated with duration of illness in patients. No significant alterations were identified in siblings relative to controls on both measurements. Furthermore, alterations in interhemispheric connectivity correlated with changes in hemispheric specialization in patients relative to controls and siblings. Taken together, these results suggest that lower interhemispheric connectivity and associated abnormalities in hemispheric specialization are features of established illness, rather than an expression of preexistent familial risk for schizophrenia.

YNIMG Journal 2017 Journal Article

Multi-center MRI prediction models: Predicting sex and illness course in first episode psychosis patients

• Mireille Nieuwenhuis
• Hugo G. Schnack
• Neeltje E. van Haren
• Julia Lappin
• Craig Morgan
• Antje A. Reinders
• Diana Gutierrez-Tordesillas
• Roberto Roiz-Santiañez

Structural Magnetic Resonance Imaging (MRI) studies have attempted to use brain measures obtained at the first-episode of psychosis to predict subsequent outcome, with inconsistent results. Thus, there is a real need to validate the utility of brain measures in the prediction of outcome using large datasets, from independent samples, obtained with different protocols and from different MRI scanners. This study had three main aims: 1) to investigate whether structural MRI data from multiple centers can be combined to create a machine-learning model able to predict a strong biological variable like sex; 2) to replicate our previous finding that an MRI scan obtained at first episode significantly predicts subsequent illness course in other independent datasets; and finally, 3) to test whether these datasets can be combined to generate multicenter models with better accuracy in the prediction of illness course. The multi-center sample included brain structural MRI scans from 256 males and 133 females patients with first episode psychosis, acquired in five centers: University Medical Center Utrecht (The Netherlands) (n=67); Institute of Psychiatry, Psychology and Neuroscience, London (United Kingdom) (n=97); University of São Paulo (Brazil) (n=64); University of Cantabria, Santander (Spain) (n=107); and University of Melbourne (Australia) (n=54). All images were acquired on 1. 5-Tesla scanners and all centers provided information on illness course during a follow-up period ranging 3 to 7years. We only included in the analyses of outcome prediction patients for whom illness course was categorized as either “continuous” (n=94) or “remitting” (n=118). Using structural brain scans from all centers, sex was predicted with significant accuracy (89%; p<0. 001). In the single- or multi-center models, illness course could not be predicted with significant accuracy. However, when reducing heterogeneity by restricting the analyses to male patients only, classification accuracy improved in some samples. This study provides proof of concept that combining multi-center MRI data to create a well performing classification model is possible. However, to create complex multi-center models that perform accurately, each center should contribute a sample either large or homogeneous enough to first allow accurate classification within the single-center.

YNIMG Journal 2017 Journal Article

Using neuroimaging to help predict the onset of psychosis

• George Gifford
• Nicolas Crossley
• Paolo Fusar-Poli
• Hugo G. Schnack
• René S. Kahn
• Nikolaos Koutsouleris
• Tyrone D. Cannon
• Philip McGuire

The aim of this review is to assess the potential for neuroimaging measures to facilitate prediction of the onset of psychosis. Research in this field has mainly involved people at ‘ultra-high risk’ (UHR) of psychosis, who have a very high risk of developing a psychotic disorder within a few years of presentation to mental health services. The review details the key findings and developments in this area to date and examines the methodological and logistical challenges associated with making predictions in an individual subject in a clinical setting.

YNICL Journal 2016 Journal Article

Brain development in adolescents at ultra-high risk for psychosis: Longitudinal changes related to resilience

• Sanne de Wit
• Lara M. Wierenga
• Bob Oranje
• Tim B. Ziermans
• Patricia F. Schothorst
• Herman van Engeland
• René S. Kahn
• Sarah Durston

BACKGROUND: The main focus of studies of individuals at ultra-high risk for psychosis (UHR) has been on identifying brain changes in those individuals who will develop psychosis. However, longitudinal studies have shown that up to half of UHR individuals are resilient, with symptomatic remission and good functioning at follow-up. Yet little is known about brain development in resilient individuals. Therefore, the aim of this study was to investigate differences in brain development between resilient and non-resilient individuals. METHODS: A six-year longitudinal structural MRI study was performed with up to three scans per individual. The final sample consisted of 48 UHR individuals and 48 typically developing controls with a total of 225 MRI-scans, aged 12-20 years at the time of the first MRI-scan and matched for age, gender and number of follow-up scans. At six-year follow-up, 35 UHR individuals were divided in resilient (good functional outcome) and non-resilient (poor functional outcome) subgroups, defined by the modified Global Assessment of Functioning. The main outcome measures were developmental changes in MR-based measures of cortical and subcortical anatomy. RESULTS: We found widespread differences in volume of frontal, temporal and parietal cortex between resilient and non-resilient individuals. These were already present at baseline and remained stable over development (12-24 years). Furthermore, there were differences in the development of cortical surface area in frontal regions including cingulate gyrus. CONCLUSIONS: Developmental differences may reflect compensatory neural mechanisms, where better functioning in resilient individuals leads to less tissue loss over development.

YNIMG Journal 2016 Journal Article

Topology of genetic associations between regional gray matter volume and intellectual ability: Evidence for a high capacity network

• Marc M. Bohlken
• Rachel M. Brouwer
• René C.W. Mandl
• Anna M. Hedman
• Martijn P. van den Heuvel
• Neeltje E.M. van Haren
• René S. Kahn
• Hilleke E. Hulshoff Pol

Intelligence is associated with a network of distributed gray matter areas including the frontal and parietal higher association cortices and primary processing areas of the temporal and occipital lobes. Efficient information transfer between gray matter regions implicated in intelligence is thought to be critical for this trait to emerge. Genetic factors implicated in intelligence and gray matter may promote a high capacity for information transfer. Whether these genetic factors act globally or on local gray matter areas separately is not known. Brain maps of phenotypic and genetic associations between gray matter volume and intelligence were made using structural equation modeling of 3T MRI T1-weighted scans acquired in 167 adult twins of the newly acquired U-TWIN cohort. Subsequently, structural connectivity analyses (DTI) were performed to test the hypothesis that gray matter regions associated with intellectual ability form a densely connected core. Gray matter regions associated with intellectual ability were situated in the right prefrontal, bilateral temporal, bilateral parietal, right occipital and subcortical regions. Regions implicated in intelligence had high structural connectivity density compared to 10, 000 reference networks (p=0. 031). The genetic association with intelligence was for 39% explained by a genetic source unique to these regions (independent of total brain volume), this source specifically implicated the right supramarginal gyrus. Using a twin design, we show that intelligence is genetically represented in a spatially distributed and densely connected network of gray matter regions providing a high capacity infrastructure. Although genes for intelligence have overlap with those for total brain volume, we present evidence that there are genes for intelligence that act specifically on the subset of brain areas that form an efficient brain network.

YNIMG Journal 2014 Journal Article

Can structural MRI aid in clinical classification? A machine learning study in two independent samples of patients with schizophrenia, bipolar disorder and healthy subjects

• Hugo G. Schnack
• Mireille Nieuwenhuis
• Neeltje E.M. van Haren
• Lucija Abramovic
• Thomas W. Scheewe
• Rachel M. Brouwer
• Hilleke E. Hulshoff Pol
• René S. Kahn

Although structural magnetic resonance imaging (MRI) has revealed partly non-overlapping brain abnormalities in schizophrenia and bipolar disorder, it is unknown whether structural MRI scans can be used to separate individuals with schizophrenia from those with bipolar disorder. An algorithm capable of discriminating between these two disorders could become a diagnostic aid for psychiatrists. Here, we scanned 66 schizophrenia patients, 66 patients with bipolar disorder and 66 healthy subjects on a 1. 5T MRI scanner. Three support vector machines were trained to separate patients with schizophrenia from healthy subjects, patients with schizophrenia from those with bipolar disorder, and patients with bipolar disorder from healthy subjects, respectively, based on their gray matter density images. The predictive power of the models was tested using cross-validation and in an independent validation set of 46 schizophrenia patients, 47 patients with bipolar disorder and 43 healthy subjects scanned on a 3T MRI scanner. Schizophrenia patients could be separated from healthy subjects with an average accuracy of 90%. Additionally, schizophrenia patients and patients with bipolar disorder could be distinguished with an average accuracy of 88%. The model delineating bipolar patients from healthy subjects was less accurate, correctly classifying 67% of the healthy subjects and only 53% of the patients with bipolar disorder. In the latter group, lithium and antipsychotics use had no influence on the classification results. Application of the 1. 5T models on the 3T validation set yielded average classification accuracies of 76% (healthy vs schizophrenia), 66% (bipolar vs schizophrenia) and 61% (healthy vs bipolar). In conclusion, the accurate separation of schizophrenia from bipolar patients on the basis of structural MRI scans, as demonstrated here, could be of added value in the differential diagnosis of these two disorders. The results also suggest that gray matter pathology in schizophrenia and bipolar disorder differs to such an extent that they can be reliably differentiated using machine learning paradigms.

YNIMG Journal 2014 Journal Article

Functional differences in emotion processing during adolescence and early adulthood

• Matthijs Vink
• Jolanda M. Derks
• Janna Marie Hoogendam
• Manon Hillegers
• René S. Kahn

Adolescence is a transitional period between childhood and adulthood and is characterized by emotional instability. Underlying this behavior may be an imbalance between the limbic subcortical areas and the prefrontal cortex. Here, we investigated differences in these regions during adolescence and young adulthood. Fifty subjects aged 10 to 24 viewed and rated neutral, negative, and positive pictures (IAPS: International Affective Picture System), while being scanned with functional MRI. Only those trials in which there was a match between the subject's response and the IAPS rating were included in the analyses. Task performance (matching accuracy, reaction times) did not differ across age. Activity in the amygdala and hippocampus decreased with age when processing emotional salient stimuli versus neutral stimuli. In contrast, activation in the ventrolateral prefrontal cortex increased with age. Importantly, we show for the first time that these age-related changes are paralleled by an increase in functional coupling of the amygdala and hippocampus with the orbitofrontal cortex and ventrolateral prefrontal cortex. These findings are in line with the general notion that brain development from childhood to adulthood is characterized by a gradual increase in frontal control over subcortical regions. Understanding these developmental changes is important as these may underlie typical adolescent behavior.

YNICL Journal 2014 Journal Article

GABA and glutamate in schizophrenia: A 7 T 1H-MRS study

• Anouk Marsman
• René C.W. Mandl
• Dennis W.J. Klomp
• Marc M. Bohlken
• Vincent O. Boer
• Anna Andreychenko
• Wiepke Cahn
• René S. Kahn

Schizophrenia is characterized by loss of brain volume, which may represent an ongoing pathophysiological process. This loss of brain volume may be explained by reduced neuropil rather than neuronal loss, suggesting abnormal synaptic plasticity and cortical microcircuitry. A possible mechanism is hypofunction of the NMDA-type of glutamate receptor, which reduces the excitation of inhibitory GABAergic interneurons, resulting in a disinhibition of glutamatergic pyramidal neurons. Disinhibition of pyramidal cells may result in excessive stimulation by glutamate, which in turn could cause neuronal damage or death through excitotoxicity. In this study, GABA/creatine ratios, and glutamate, NAA, creatine and choline concentrations in the prefrontal and parieto-occipital cortices were measured in 17 patients with schizophrenia and 23 healthy controls using proton magnetic resonance spectroscopy at an ultra-high magnetic field strength of 7 T. Significantly lower GABA/Cr ratios were found in patients with schizophrenia in the prefrontal cortex as compared to healthy controls, with GABA/Cr ratios inversely correlated with cognitive functioning in the patients. No significant change in the GABA/Cr ratio was found between patients and controls in the parieto-occipital cortex, nor were levels of glutamate, NAA, creatine, and choline differed in patients and controls in the prefrontal and parieto-occipital cortices. Our findings support a mechanism involving altered GABA levels distinguished from glutamate levels in the medial prefrontal cortex in schizophrenia, particularly in high functioning patients. A (compensatory) role for GABA through altered inhibitory neurotransmission in the prefrontal cortex may be ongoing in (higher functioning) patients with schizophrenia.

YNIMG Journal 2014 Journal Article

Multi-site study of additive genetic effects on fractional anisotropy of cerebral white matter: Comparing meta and megaanalytical approaches for data pooling

• Peter Kochunov
• Neda Jahanshad
• Emma Sprooten
• Thomas E. Nichols
• René C. Mandl
• Laura Almasy
• Tom Booth
• Rachel M. Brouwer

Combining datasets across independent studies can boost statistical power by increasing the numbers of observations and can achieve more accurate estimates of effect sizes. This is especially important for genetic studies where a large number of observations are required to obtain sufficient power to detect and replicate genetic effects. There is a need to develop and evaluate methods for joint-analytical analyses of rich datasets collected in imaging genetics studies. The ENIGMA-DTI consortium is developing and evaluating approaches for obtaining pooled estimates of heritability through meta-and mega-genetic analytical approaches, to estimate the general additive genetic contributions to the intersubject variance in fractional anisotropy (FA) measured from diffusion tensor imaging (DTI). We used the ENIGMA-DTI data harmonization protocol for uniform processing of DTI data from multiple sites. We evaluated this protocol in five family-based cohorts providing data from a total of 2248 children and adults (ages: 9–85) collected with various imaging protocols. We used the imaging genetics analysis tool, SOLAR-Eclipse, to combine twin and family data from Dutch, Australian and Mexican-American cohorts into one large “mega-family”. We showed that heritability estimates may vary from one cohort to another. We used two meta-analytical (the sample-size and standard-error weighted) approaches and a mega-genetic analysis to calculate heritability estimates across-population. We performed leave-one-out analysis of the joint estimates of heritability, removing a different cohort each time to understand the estimate variability. Overall, meta- and mega-genetic analyses of heritability produced robust estimates of heritability.

YNIMG Journal 2013 Journal Article

Heritability of subcortical brain measures: A perspective for future genome-wide association studies

• Anouk den Braber
• Marc M. Bohlken
• Rachel M. Brouwer
• Dennis van 't Ent
• Ryota Kanai
• René S. Kahn
• Eco J.C. de Geus
• Hilleke E. Hulshoff Pol

Several large imaging-genetics consortia aim to identify genetic variants influencing subcortical brain volumes. We investigated the extent to which genetic variation accounts for the variation in subcortical volumes, including thalamus, amygdala, putamen, caudate nucleus, globus pallidus and nucleus accumbens and obtained the stability of these brain volumes over a five-year period. The heritability estimates for all subcortical regions were high, with the highest heritability estimates observed for the thalamus (. 80) and caudate nucleus (. 88) and lowest for the left nucleus accumbens (. 44). Five-year stability was substantial and higher for larger [e. g. , thalamus (. 88), putamen (. 86), caudate nucleus (. 87)] compared to smaller [nucleus accumbens (. 45)] subcortical structures. These results provide additional evidence that subcortical structures are promising starting points for identifying genetic variants that influence brain structure.

YNIMG Journal 2012 Journal Article

Classification of schizophrenia patients and healthy controls from structural MRI scans in two large independent samples

• Mireille Nieuwenhuis
• Neeltje E.M. van Haren
• Hilleke E. Hulshoff Pol
• Wiepke Cahn
• René S. Kahn
• Hugo G. Schnack

The purpose of this study is to create a model that can classify schizophrenia patients and healthy controls based on whole brain gray matter densities (voxel-based morphometry, VBM) from structural magnetic resonance imaging (MRI) scans. In addition, we investigated the stability of the accuracy of the models, when built with different sample sizes. Using a support vector machine, we built a model from 239 subjects (128 patients and 111 healthy controls) and classified 71. 4% correct (leave-one-out). We replicated and validated this result by testing the unaltered model on a completely independent sample of 277 subjects (155 patients and 122 healthy controls), scanned with a different scanner. The classification rate of the validation sample was 70. 4%. The model's discriminative pattern showed, amongst other differences, gray matter density decreases in frontal and superior temporal lobes and hippocampus in schizophrenia patients with respect to healthy controls and increases in gray matter density in basal ganglia and left occipital lobe and. Larger training samples gave more reliable models: Models based on sample sizes smaller than N=130 should be considered unstable and can even score below chance.

YNIMG Journal 2010 Journal Article

Heritability of DTI and MTR in nine-year-old children

• Rachel M. Brouwer
• René C.W. Mandl
• Jiska S. Peper
• G. Caroline M. van Baal
• René S. Kahn
• Dorret I. Boomsma
• Hilleke E. Hulshoff Pol

Overall brain size is strikingly heritable throughout life. The influence of genes on variation in focal gray and white matter density is less pronounced and may vary with age. This paper describes the relative influences of genes and environment on variation in white matter microstructure, measured along fiber tracts with diffusion tensor imaging and magnetization transfer imaging, in a sample of 185 nine-year old children from monozygotic and dizygotic twin pairs. Fractional anisotropy, a measure of microstructural directionality, was not significantly influenced by genetic factors. In contrast, studying longitudinal and radial diffusivity separately, we found significant genetic effects for both radial and longitudinal diffusivity in the genu and splenium of the corpus callosum and the right superior longitudinal fasciculus. Moreover, genetic factors influencing the magnetization transfer ratio (MTR), putatively representing myelination, were most pronounced in the splenium of the corpus callosum and the superior longitudinal fasciculi, located posterior in the brain. The differences in the extent to which genetic and environmental factors influence the various diffusion parameters and MTR, suggest that different physiological mechanisms (either genetic or environmental) underlie these traits at nine years of age.

YNIMG Journal 2010 Journal Article

Microglia activation in schizophrenia

• Thalia F. van der Doef
• Matthijs G. Bossong
• Ronald Boellaard
• Maqsood Yaqub
• Reina Kloet
• Alie Schuitemaker
• Neeltje van Haren
• Albert D. Windhorst

YNIMG Journal 2008 Journal Article

Evidence of altered cortical and amygdala activation during social decision-making in schizophrenia

• Daan Baas
• André Aleman
• Matthijs Vink
• Nick F. Ramsey
• Edward H.F. de Haan
• René S. Kahn

Impaired social cognition is a frequently observed and disabling characteristic of schizophrenia. An important aspect of social cognition involves making social decisions about others. The present study investigates whether brain activity related to social decision-making differs between patients with schizophrenia and healthy controls. Twelve patients with schizophrenia and 21 control subjects participated in the study. Behavioral performance and brain activity were assessed during a task that involved judging the trustworthiness of faces. We performed region-of-interest-based analyses, which revealed that patients with schizophrenia display specific increases and reductions in activation of the medial orbitofrontal cortex, amygdala and the right insula during social decision-making, areas that play key roles in the network that underlies social decisions. These findings suggest that the impairments in social cognition that are often observed in schizophrenia are, at least in part, related to altered brain activity in these areas.

YNIMG Journal 2008 Journal Article

Within-subject variation in BOLD-fMRI signal changes across repeated measurements: Quantification and implications for sample size

• Bram B. Zandbelt
• Thomas E. Gladwin
• Mathijs Raemaekers
• Mariët van Buuren
• Sebastiaan F. Neggers
• René S. Kahn
• Nick F. Ramsey
• Matthijs Vink

Functional magnetic resonance imaging (fMRI) can be used to detect experimental effects on brain activity across measurements. The success of such studies depends on the size of the experimental effect, the reliability of the measurements, and the number of subjects. Here, we report on the stability of fMRI measurements and provide sample size estimations needed for repeated measurement studies. Stability was quantified in terms of the within-subject standard deviation (σ w ) of BOLD signal changes across measurements. In contrast to correlation measures of stability, this statistic does not depend on the between-subjects variance in the sampled group. Sample sizes required for repeated measurements of the same subjects were calculated using this σ w. Ten healthy subjects performed a motor task on three occasions, separated by one week, while being scanned. In order to exclude training effects on fMRI stability, all subjects were trained extensively on the task. Task performance, spatial activation pattern, and group-wise BOLD signal changes were highly stable over sessions. In contrast, we found substantial fluctuations (up to half the size of the group mean activation level) in individual activation levels, both in ROIs and in voxels. Given this large degree of instability over sessions, and the fact that the amount of within-subject variation plays a crucial role in determining the success of an fMRI study with repeated measurements, improving stability is essential. In order to guide future studies, sample sizes are provided for a range of experimental effects and levels of stability. Obtaining estimates of these latter two variables is essential for selecting an appropriate number of subjects.

YNIMG Journal 2006 Journal Article

Gray and white matter density changes in monozygotic and same-sex dizygotic twins discordant for schizophrenia using voxel-based morphometry

• Hilleke E. Hulshoff Pol
• Hugo G. Schnack
• René C.W. Mandl
• Rachel G.H. Brans
• Neeltje E.M. van Haren
• Wim F.C. Baaré
• Clarine J. van Oel
• D. Louis Collins

Global gray matter brain tissue volume decreases in schizophrenia have been associated to disease-related (possibly nongenetic) factors. Global white matter brain tissue volume decreases were related to genetic risk factors for the disease. However, which focal gray and white matter brain regions best reflect the genetic and environmental risk factors in the brains of patients with schizophrenia remains unresolved. 1. 5-T MRI brain scans of 11 monozygotic and 11 same-sex dizygotic twin-pairs discordant for schizophrenia were compared to 11 monozygotic and 11 same-sex dizygotic healthy control twin-pairs using voxel-based morphometry. Linear regression analysis was done in each voxel for the average and difference in gray and white matter density separately, in each twin-pair, with group (discordant, healthy) and zygosity (monozygotic, dizygotic) as between subject variables, and age, sex and handedness as covariates. The t-maps (critical threshold value ∣t∣ > 6. 0, P < 0. 05) revealed a focal decrease in gray matter density accompanied by a focal increase in white matter density in the left medial orbitofrontal gyrus and a focal decrease in white matter density in the left sensory motor gyrus in twin-pairs discordant for schizophrenia as compared to healthy twin-pairs. Focal changes in left medial (orbito)frontal and left sensory motor gyri may reflect the increased genetic risk to develop schizophrenia. Focal changes in the left anterior hemisphere may therefore be particularly relevant as endophenotype in genetic studies of schizophrenia.

YNIMG Journal 2005 Journal Article

Perceptual bias following visual target selection

• Matthijs Vink
• René S. Kahn
• Mathijs Raemaekers
• Nick F. Ramsey

Attending to a relevant item in a visual display is thought to require not only selective attention to this item, but also active inhibition of surrounding distractor items. As a consequence of this spatial inhibition, selection of a relevant item in a previous distractor location is slowed (i. e. , the spatial inhibition effect). The goal of this study is to identify brain regions that are involved in this spatial inhibition effect using functional magnetic resonance imaging (fMRI). Subjects had to select a target from a display which also included a distractor, while that target was presented in either a new location (control) or in a location previously occupied by a distractor (spatial inhibition). A region of interest analysis revealed decreased activation in the superior parietal lobe (SPL), but increased activation in the motor areas (supplementary motor area, putamen) when the target was presented in a previously inhibited compared to a new location. We take these results to suggest that presenting a target in a previously inhibited location negatively biases the selection of that target in favor of an accompanying distractor. This may result in an initially more efficient selection process, resulting in lower activation in the SPL. Counteracting this perceptual bias possibly requires additional motor activation. This study provides evidence for the notion that to make selection more efficient, prior information concerning an item is used. When this prior information conflicts with the current stimulus demands, compensatory motor actions are taken to correct this perceptual bias.

YNIMG Journal 2004 Journal Article

Focal white matter density changes in schizophrenia: reduced inter-hemispheric connectivity

• Hilleke E. Hulshoff Pol
• Hugo G. Schnack
• René C.W. Mandl
• W. Cahn
• D.Louis Collins
• Alan C. Evans
• René S. Kahn

Gray matter changes have been demonstrated in several regions in schizophrenia. Particularly, the frontal and temporal cortices and amygdala-hippocampal region have been found decreased in volume and density in magnetic resonance imaging (MRI) studies. These abnormalities may reflect an aberrant neuronal network in schizophrenia, suggesting that white matter fibers connecting these regions may also be affected. However, it is unclear if particular white matter areas are (progressively) affected in schizophrenia and if these are related to the gray matter changes. Focal white matter changes in schizophrenia were studied in whole brain magnetic resonance images acquired from 159 patients with schizophrenia or schizophreniform disorder and 158 healthy comparison subjects using voxel-based morphometry. White matter density changes in the patients with schizophrenia were correlated to gray matter density changes and to illness severity. In the patients with schizophrenia, significant decreases in white matter density were found in the genu and truncus of the corpus callosum in the left and right hemisphere, in the right anterior internal capsule and in the right anterior commissure. No interactions between diagnosis and age were found. Increased illness severity was correlated with low density of the corpus callosum and anterior commissure. Decreased corpus callosum density correlated with decreased density of thalamus, lateral inferior frontal and insular gray matter in patients and controls and with decreased density of medial orbitofrontal and superior temporal gyri in patients. Decreased internal capsule and anterior commissure density correlated with increased caudate, and globus pallidus density in patients and controls. These findings suggest aberrant inter-hemispheric connectivity of anterior cortical and sub-cortical brain regions in schizophrenia, reflecting decreased hemispheric specialisation in schizophrenia.

YNIMG Journal 2000 Journal Article

Specific versus Nonspecific Brain Activity in a Parametric N-Back Task

• Johan Martijn Jansma
• Nick F. Ramsey
• Richard Coppola
• René S. Kahn

In this study functional magnetic resonance imaging (fMRI) was used to examine cerebral activity patterns in relation to increasing mental load of a working memory task. Aim of the experiment was to distinguish nonspecific task-related processes from specific workload processes analytically. Twelve healthy volunteers engaged in a spatial n-back task with four levels. FMRI data were acquired with the 3D-PRESTO pulse sequence. Analysis entailed a two-step multiple regression algorithm, which was specifically designed to measure and separate load-sensitive and load-insensitive activity simultaneously, while preserving the original high spatial resolution of the fMRI signal. Load-sensitive and load-insensitive activity was found in both dorsolateral-prefrontal and parietal cortex, predominantly bilaterally, and in the anterior cingulate. As expected, the left primary sensorimotor cortex showed predominantly load-insensitive activity. Load-sensitive activity reflects specific working memory functions, such as temporary retention and manipulation of information, while load-insensitive activity reflects supportive functions, such as visual orientation, perception, encoding, and response selection and execution. Good performance was correlated with a large area of load-sensitive activity in anterior cingulate, and with a small area of load-insensitive activity in the right parietal cortex. The findings indicate that nonspecific and specific working memory processes colocalize and are represented in multiple frontal and parietal regions. Implication of this analytical strategy for application in research on psychiatric disorders is discussed.