Activations in gray and white matter are modulated by uni-manual responses during within and inter-hemispheric transfer: effects of response hand and right-handedness.

Because the visual cortices are contra-laterally organized, inter-hemispheric transfer tasks have been used to behaviorally probe how information briefly presented to one hemisphere of the visual cortex is integrated with responses resulting from the ipsi- or contra-lateral motor cortex. By forcing rapid information exchange across diverse regions, these tasks robustly activate not only gray matter regions, but also white matter tracts. It is likely that the response hand itself (dominant or non-dominant) modulates gray and white matter activations during within and inter-hemispheric transfer. Yet the role of uni-manual responses and/or right hand dominance in modulating brain activations during such basic tasks is unclear. Here we investigated how uni-manual responses with either hand modulated activations during a basic visuo-motor task (the established Poffenberger paradigm) alternating between inter- and within-hemispheric transfer conditions. In a large sample of strongly right-handed adults (n = 49), we used a factorial combination of transfer condition [Inter vs. Within] and response hand [Dominant(Right) vs. Non-Dominant (Left)] to discover fMRI-based activations in gray matter, and in narrowly defined white matter tracts. These tracts were identified using a priori probabilistic white matter atlases. Uni-manual responses with the right hand strongly modulated activations in gray matter, and notably in white matter. Furthermore, when responding with the left hand, activations during inter-hemispheric transfer were strongly predicted by the degree of right-hand dominance, with increased right-handedness predicting decreased fMRI activation. Finally, increasing age within the middle-aged sample was associated with a decrease in activations. These results provide novel evidence of complex relationships between uni-manual responses in right-handed subjects, and activations during within- and inter-hemispheric transfer suggest that the organization of the motor system exerts sophisticated functional effects. Moreover, our evidence of activation in white matter tracts is consistent with prior studies, confirming fMRI-detectable white matter activations which are systematically modulated by experimental condition.

Erratum to: Activations in gray and white matter are modulated by uni-manual responses during within and inter-hemispheric transfer: effects of response hand and right-handedness.

The original version of this article unfortunately contained a mistake. The family name of Paolo Brambilla was incorrectly spelled as Bambilla.

Classification of first-episode psychosis in a large cohort of patients using support vector machine and multiple kernel learning techniques.

First episode psychosis (FEP) patients are of particular interest for neuroimaging investigations because of the absence of confounding effects due to medications and chronicity. Nonetheless, imaging data are prone to heterogeneity because for example of age, gender or parameter setting differences. With this work, we wanted to take into account possible nuisance effects of age and gender differences across dataset, not correcting the data as a pre-processing step, but including the effect of nuisance covariates in the classification phase. To this aim, we developed a method which, based on multiple kernel learning (MKL), exploits the effect of these confounding variables with a subject-depending kernel weighting procedure. We applied this method to a dataset of cortical thickness obtained from structural magnetic resonance images (MRI) of 127 FEP patients and 127 healthy controls, who underwent either a 3Tesla (T) or a 1.5T MRI acquisition. We obtained good accuracies, notably better than those obtained with standard SVM or MKL methods, up to more than 80% for frontal and temporal areas. To our best knowledge, this is the largest classification study in FEP population, showing that fronto-temporal cortical thickness can be used as a potential marker to classify patients with psychosis.

Chronological age and its impact on associative learning proficiency and brain structure in middle adulthood.

INTRODUCTION: The rate of biological change in middle-adulthood is relatively under-studied. Here, we used behavioral testing in conjunction with structural magnetic resonance imaging to examine the effects of chronological age on associative learning proficiency and on brain regions that previous functional MRI studies have closely related to the domain of associative learning. METHODS: Participants (n=66) completed a previously established associative learning paradigm, and consented to be scanned using structural magnetic resonance imaging. Age-related effects were investigated both across sub-groups in the sample (younger vs. older) and across the entire sample (using regression approaches). RESULTS: Chronological age had substantial effects on learning proficiency (independent of IQ and Education Level), with older adults showing a decrement compared to younger adults. In addition, decreases in estimated gray matter volume were observed in multiple brain regions including the hippocampus and the dorsal prefrontal cortex, both of which are strongly implicated in associative learning. CONCLUSION: The results suggest that middle adulthood may be a more dynamic period of life-span change than previously believed. The conjunctive application of narrowly focused tasks, with conjointly acquired structural MRI data may allow us to enrich the search for, and the interpretation of, age-related changes in cross-sectional samples.

The use of dynamic susceptibility contrast (DSC) MRI to automatically classify patients with first episode psychosis.

Hemodynamic changes in the brain have been reported in major psychosis in respect to healthy controls, and could unveil the basis of structural brain modifications happening in patients. The study of first episode psychosis is of particular interest because the confounding role of chronicity and medication can be excluded. The aim of this work is to automatically discriminate first episode psychosis patients and normal controls on the basis of brain perfusion employing a support vector machine (SVM) classifier. 35 normal controls and 35 first episode psychosis underwent dynamic susceptibility contrast magnetic resonance imaging, and cerebral blood flow and volume, along with mean transit time were obtained. We investigated their behavior in the whole brain and in selected regions of interest, in particular the left and right frontal, parietal, temporal and occipital lobes, insula, caudate and cerebellum. The distribution of values of perfusion indexes were used as features in a support vector machine classifier. Mean values of blood flow and volume were slightly lower in patients, and the difference reached statistical significance in the right caudate, left and right frontal lobes, and in left cerebellum. Linear SVM reached an accuracy of 83% in the classification of patients and normal controls, with the highest accuracy associated with the right frontal lobe and left parietal lobe. In conclusion, we found evidence that brain perfusion could be used as a potential marker to classify patients with psychosis, who show reduced blood flow and volume in respect to normal controls.

Classification of first-episode psychosis: a multi-modal multi-feature approach integrating structural and diffusion imaging.

Currently, most of the classification studies of psychosis focused on chronic patients and employed single machine learning approaches. To overcome these limitations, we here compare, to our best knowledge for the first time, different classification methods of first-episode psychosis (FEP) using multi-modal imaging data exploited on several cortical and subcortical structures and white matter fiber bundles. 23 FEP patients and 23 age-, gender-, and race-matched healthy participants were included in the study. An innovative multivariate approach based on multiple kernel learning (MKL) methods was implemented on structural MRI and diffusion tensor imaging. MKL provides the best classification performances in comparison with the more widely used support vector machine, enabling the definition of a reliable automatic decisional system based on the integration of multi-modal imaging information. Our results show a discrimination accuracy greater than 90 % between healthy subjects and patients with FEP. Regions with an accuracy greater than 70 % on different imaging sources and measures were middle and superior frontal gyrus, parahippocampal gyrus, uncinate fascicles, and cingulum. This study shows that multivariate machine learning approaches integrating multi-modal and multisource imaging data can classify FEP patients with high accuracy. Interestingly, specific grey matter structures and white matter bundles reach high classification reliability when using different imaging modalities and indices, potentially outlining a prefronto-limbic network impaired in FEP with particular regard to the right hemisphere.

Psychopathological and personality traits underlie decision making in recent onset medication naïve anorexia nervosa: a pilot study.

The Iowa Gambling Task (IGT) analyzes the ability of participants to sacrifice immediate rewards in view of a long term gain. Anorexia Nervosa (AN) in addition to weight loss and body image disturbances is also characterized by the tendency to make decisions that may result in long-term negative outcomes. Studies that analyzed IGT performance in patients with AN were not consistent with each other. Fifteen adolescents with AN and 15 matched controls carried out IGT after being clinically and neuropsychologically evaluated. An interesting generalized estimating equation approach showed that four independent clinical variables, and not the group, explained IGT performances, such as blocks repetition, anxiety, psychogenic eating disorders and self transcendence. The impairment of decision making is not related to the diagnosis of AN, but it is driven by high levels of anxiety and self transcendence. Instead, some psychogenic eating disorders traits, related to illness severity, positively affected IGT performance in the whole sample. IGT impairment in AN found by prior studies could be related to these clinical features which are not always taken into account.

Decreased hypothalamus volumes in generalized anxiety disorder but not in panic disorder.

BACKGROUND: The hypothalamus is a brain structure involved in the neuroendocrine aspect of stress and anxiety. Evidence suggests that generalized anxiety disorder (GAD) and panic disorder (PD) might be accompanied by dysfunction of the hypothalamus-pituitary-adrenal axis (HPA), but so far structural alterations were not studied. We investigated hypothalamic volumes in patients with either GAD or PD and in healthy controls. METHODS: Twelve GAD patients, 11 PD patients and 21 healthy controls underwent a 1.5T MRI scan. Hypothalamus volumes were manually traced by a rater blind to subjects' identity. General linear model for repeated measures (GLM-RM) was used to compare groups on hypothalamic volumes, controlling for total intracranial volume, age and sex. RESULTS: The hypothalamus volume was significantly reduced (p=0.04) in GAD patients, with significant reductions in both the left (p=0.02) and right side (p=0.04). Patients with PD did not differ significantly (p=0.73). Anxiety scores were inversely correlated with hypothalamic volumes. LIMITATIONS: The small sample size could reduce the generalizability of the results while the lack of stress hormone measurements renders functional assessment of the hypothalamus-pituitary-adrenal axis not feasible. CONCLUSIONS: The present study showed decreased hypothalamic volumes in GAD patients but not in those with PD. Future longitudinal studies should combine volumetric data with measurements of stress hormones to better elucidate the role of the HPA axis in GAD.

Enlarged hypothalamic volumes in schizophrenia.

Hypothalamic abnormalities in schizophrenia have been associated with endocrine dysfunctions and stress response. The hypothalamus is involved in several pathways found disrupted in schizophrenia (e.g., hypothalamic-pituitary-adrenal axis, HPA axis); however the available results on potential structural hypothalamic alterations are still controversial. The aim of the study was to investigate the volumes of the hypothalamus and the mammillary bodies in patients with schizophrenia and healthy controls. Twenty-six patients with schizophrenia and 26 healthy controls underwent a 3 Tesla magnetic resonance imaging (MRI) scan. Hypothalamus and mammillary bodies were manually traced by a rater who was blind to subjects' identity. The General Linear Model was used in group comparisons of the volumes of the hypothalamus and the mammillary bodies. The hypothalamus and mammillary body volumes were significantly larger in patients with schizophrenia than controls, with significant enlargement of the left hypothalamus and trends for significantly increased right hypothalamus and right mammillary body. The size of the mammillary bodies was inversely correlated with negative symptoms and directly correlated with anxiety. This study showed abnormally increased sizes of the hypothalamus and the mammillary bodies in schizophrenia. Mammillary bodies volumes were associated to negative symptoms and anxiety. Future longitudinal studies on the volumes of the hypothalamus and the mammillary bodies with respect to the levels of related hormones will clarify their role in modulating HPA axis in schizophrenia.

White matter microstructure alterations in bipolar disorder.

Genetic, neuropathological and magnetic resonance imaging findings support the presence of diffuse white matter cytoarchitectural disruption in bipolar disorder. In this study, diffusion-weighted imaging (DWI) was applied to study cortical white matter microstructure organisation in 24 patients with DSM-IV bipolar disorder and 35 matched normal controls. DWI images were obtained using a 1.5 Tesla scanner and apparent diffusion coefficient (ADC) values were determined over regions of interest placed, bilaterally, in the frontal, temporal, parietal, and occipital white matter. Significantly increased ADC values were found in bipolar patients with respect to normal controls in the right temporal lobe, left parietal lobe and bilateral occipital lobes. ADC values did not associate significantly with age or with clinical variables (p>0.05). Diffuse cortical white matter alterations on DWI in bipolar disorder denote widespread disruption of white matter integrity and may be due to altered myelination and/or axonal integrity.

Is neuregulin 1 involved in determining cerebral volumes in schizophrenia? Preliminary results showing a decrease in superior temporal gyrus volume.

BACKGROUND/AIMS: Reduced left superior temporal gyrus (STG) volume is one of the most replicated imaging findings in schizophrenia. However, it remains unclear whether genes play any role in our understanding of such structural alteration. It has been proposed that Neuregulin 1 (NRG1) might be a promising gene involved in schizophrenia, because of its role in neurodevelopment and neuroplasticity. In this study, the association between NRG1 and STG anatomy in patients with schizophrenia was explored for the first time. METHODS: We investigated a 1-year treated prevalence cohort of patients with schizophrenia in contact with the South Verona Community-Based Mental Health Service. A blood sample was collected for DNA extraction and brain structure was assessed with an MRI scan. A total of 27 subjects with schizophrenia underwent both assessments and were included in the study. RESULTS: We investigated the association between the polymorphism SNP8NRG222662 (rs4623364) of NRG1 and volume of the STG. We found that patients homozygous for the C allele had reduced left STG gray and white matter volumes in comparison to those homozygous for the G allele (p < 0.01 and p < 0.001, respectively). CONCLUSIONS: This exploratory study suggests that NRG1 may be involved in determining STG size in schizophrenia, and may play a role in the neurogenetic basis of the language disturbances seen in this disorder. However, due to our small sample size, the results should be regarded as preliminary and replicated in a larger sample.

Thalamic-insular dysconnectivity in schizophrenia: evidence from structural equation modeling.

Structural and functional studies have shown that schizophrenia is often associated with frontolimbic abnormalities in the prefrontal and mediotemporal regions. It is still unclear, however, if such dysfunctional interaction extends as well to relay regions such as the thalamus and the anterior insula. Here, we measured gray matter volumes of five right-hemisphere regions in 68 patients with schizophrenia and 77 matched healthy subjects. The regions were amygdala, thalamus, and entorhinal cortex (identified as anomalous by prior studies on the same population) and dorsolateral prefrontal cortex and anterior insula (isolated by voxel-based morphometry analysis). We used structural equation modeling and found altered path coefficients connecting the thalamus to the anterior insula, the amygdala to the DLPFC, and the entorhinal cortex to the DLPFC. In particular, patients exhibited a stronger thalamus-insular connection than healthy controls. Instead, controls showed positive entorhinal-DLPFC and negative amygdalar-DLPFC connections, both of which were absent in the clinical population. Our data provide evidence that schizophrenia is characterized by an impaired right-hemisphere network, in which intrahemispheric communication involving relay structures may play a major role in sustaining the pathophysiology of the disease.

A new shape diffusion descriptor for brain classification.

In this paper, we exploit spectral shape analysis techniques to detect brain morphological abnormalities. We propose a new shape descriptor able to encode morphometric properties of a brain image or region using diffusion geometry techniques based on the local Heat Kernel. Using this approach, it is possible to design a versatile signature, employed in this case to classify between normal subjects and patients affected by schizophrenia. Several diffusion strategies are assessed to verify the robustness of the proposed descriptor under different deformation variations. A dataset consisting of MRI scans from 30 patients and 30 control subjects is utilized to test the proposed approach, which achieves promising classification accuracies, up to 83.33%. This constitutes a drastic improvement in comparison with other shape description techniques.

Cerebellar and lobar blood flow in schizophrenia: a perfusion weighted imaging study.

It is still not clear whether brain hemodynamics plays a role in the functional and structural alterations in schizophrenia, since prior imaging studies showed conflicting findings. In this study we non-invasively explored cerebral and cerebellar lobe perfusion in the largest population of participants with schizophrenia thus far studied with perfusion-weighted imaging (PWI). Forty-seven participants affected by schizophrenia and 29 normal controls were recruited. PWI images were acquired following the intravenous injection of a paramagnetic contrast agent. Regional cerebral blood volume (CBV), blood flow (rCBF), and mean transit time (MTT) were obtained with the block-Circulant Singular Value Decomposition (cSVD) for frontal, temporal, parietal, occipital, and cerebellar lobes, bilaterally. Perfusion parameters were separately obtained for both gray and white matter in each lobe. Subjects with schizophrenia showed no significant differences in perfusion parameters when compared with controls. Interestingly, inverse correlations between age at onset and occipital, frontal and cerebellar MTT and between length of illness and frontal CBV were found. Preserved cerebral and cerebellar perfusion in our chronic population may in part be due to the effects of antipsychotic treatment which may have normalized blood volume and flow. Hypoperfusion in relation to chronicity, particularly in the frontal lobe, has been observed in accordance with earlier studies using positron emission tomography.

Shared impairment in associative learning in schizophrenia and bipolar disorder.

BACKGROUND: Schizophrenia (SCZ) and bipolar disorder (BD) share some cognitive commonalities. However, the role of associative learning, which is a cornerstone of human cognition mainly relying on hippocampus, has been under-investigated. We assessed behavioral performance during associative learning in a group of SCZ, BD and healthy controls (HC). METHODS: Nineteen patients with SCZ (36 ± 8.1 years; 13 males, 6 females; all Caucasians), 14 patients with BD (41 ± 9.6 years; 5 males, 9 females; all Caucasians) and 45 HC (27.7 ± 6.9 years; 18 males, 27 females; all Caucasians) were studied. Learning was assessed using an established object-location paired-associative learning paradigm. Subjects learned associations between nine equi-familiar common objects and locations in a nine-location grid. Performance data were analyzed in a repeated measures analysis of variance with time (repeated) and group as factors. RESULTS: Learning curves (performance = (1-e(-k x time)) fitted to average performance data in the three groups revealed lower learning rates in SCZ and BD (k = 0.17 and k = 0.34) than HC (k = 0.78). Significant effects of group (F = 11.05, p < 0.001) and time (F = 122.06, p < 0.001) on learning performance were observed. CONCLUSIONS: Our study showed that associative learning is impaired in both SCZ and BD, being potentially not affected by medication. Future studies should investigate the neural substrates of learning deficits in SCZ and BD, particularly focusing on hippocampus function and glutamatergic transmission.

The impact of schizophrenia on frontal perfusion parameters: a DSC-MRI study.

We performed a dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI) analysis to study the role of the demographic/clinical information on perfusion parameters between patients with schizophrenia and normal control subjects. 39 schizophrenia patients and 27 normal controls were studied with a Siemens 1.5T magnet. PWI images were obtained following intravenous injection of paramagnetic contrast agent (gadolinium-DTPA). For each perfusion parameter, i.e. relative cerebral blood flow (rCBF), relative cerebral blood volume (rCBV), mean transit time (MTT) and time-to-peak (TTP), the best predictor model was computed in left and right frontal cortex following a stepwise strategy. First of all, a linear model, including all the sociodemographic information and clinical variables as predictors was computed. At each step, the least significant predictor was excluded and a new linear model was evaluated until all predictors were excluded. Then, the best predictor model was selected based on the F statistic value and on the p value. The models for the rCBF and the rCBV both in the left and right frontal cortex were estimated independently from each other, and the best models contained the same predictors, i.e. clinical state, age, and length of illness. No significant models were obtained for the MTT and the TTP. This study showed a decrease in rCBF and rCBV frontal cortex values in subject affected by schizophrenia. Future DSC-MRI studies should further investigate the role of cerebral perfusion for the pathophysiology of the disease by recruiting first-episode patients and by considering cerebellar, parietal and temporal regions.

Altered white matter integrity and development in children with autism: a combined voxel-based morphometry and diffusion imaging study.

BACKGROUND: A combined protocol of voxel-based morphometry (VBM) and diffusion-weighted imaging (DWI) was applied to investigate the neurodevelopment of gray and white matter in autism. METHODS: Twenty children with autism (mean age= 7 ± 2.75 years old; age range: 4-14; 2 girls) and 22 matched normally developing children (mean age = 7.68 ± 2.03 years old; age range: 4-11; 2 girls) underwent magnetic resonance imaging (MRI). VBM was employed by applying the Template-o-Matic toolbox (TOM), a new approach which constructs the age-matched customized template for tissue segmentation. Also, the apparent diffusion coefficients (ADC) of water molecules were obtained from the analysis of DWI. Regions of interests (ROIs), standardized at 5 pixels, were placed in cortical lobes and corpus callosum on the non-diffusion weighted echo-planar images (b = 0) and were then automatically transferred to the corresponding maps to obtain the ADC values. RESULTS: Compared to normal children, individuals with autism had significantly: (1) increased white matter volumes in the right inferior frontal gyrus, the right fusiform gyrus, the left precentral and supplementary motor area and the left hippocampus, (2) increased gray matter volumes in the inferior temporal gyri bilaterally, the right inferior parietal cortex, the right superior occipital lobe and the left superior parietal lobule, and (3) decreased gray matter volumes in the right inferior frontal gyrus and the left supplementary motor area. Abnormally increased ADC values in the bilateral frontal cortex and in the left side of the genu of the corpus callosum were also reported in autism. Finally, age correlated negatively with lobar and callosal ADC measurements in individuals with autism, but not in children with normal development. CONCLUSIONS: These findings suggest cerebral dysconnectivity in the early phases of autism coupled with an altered white matter maturation trajectory during childhood potentially taking place in the frontal and parietal lobes, which may represent a neurodevelopmental marker of the disorder, possibly accounting for the cognitive and social deficits.

Increased left parietal volumes relate to delayed language development in autism: a structural mri study.

The neural basis of language and motor deficits in autism is still not completely clear. The aim of this study was to explore the involvement of the parietal lobe in language and motor development in autism, in view of the recognized role of this region in language and imitation functions. Twenty-eight autistic children underwent an extensive clinical assessment and an MRI examination. A significant direct correlation between age at first word and left parietal gray matter volumes was found (r=0.50, p=0.007). Conversely, age at reaching milestones of motor development, such as the ability to sit and to walk unaided, was not significantly associated with parietal size, after correcting for chronological age and for gender. To the best of our knowledge, this is the first structural MRI report demonstrating a role of left parietal gray matter volumes in delayed language development in autistic children representative of the 'real world' autistic population.

Laterality effects in schizophrenia and bipolar disorder.

There are numerous reports in the literature of lateralised structural cerebral abnormalities and alterations of the corpus callosum in the major psychoses. In the light of these findings the purpose of this study was to directly compare hemispheric differences and callosal interhemispheric transmission (IT) in schizophrenia and bipolar disorder. To do that we tested schizophrenic (SCZ), bipolar disorder (BD) patients and controls in a simple manual reaction time (RT) task with lateralised visual stimuli (Poffenberger paradigm) which enables one to test both laterality effects and IT time. We found an overall slowing of responses with the right hand in schizophrenics but not in bipolar patients, who, like controls, showed no hand differences. This selective slowing down of the right hand is likely to be related to abnormalities of intrahemispheric cortico-cortical connections in the left hemisphere. In contrast, IT time was similar in SCZ and BD patients and did not differ with respect to controls. Two are the novel findings of the present study: first both SZC and BD share a normal IT of visuomotor information despite the presence of callosal abnormalities. Second, an impairment of intrahemispheric left hemispheric processing is present only in SCZ patients. This represents a potentially important clue to a further understanding of the pathogenetic differences between the two major psychoses.

Brain structural changes associated with chronicity and antipsychotic treatment in schizophrenia.

Accumulating evidence suggest a life-long impact of disease related mechanisms on brain structure in schizophrenia which may be modified by antipsychotic treatment. The aim of the present study was to investigate in a large sample of patients with schizophrenia the effect of illness duration and antipsychotic treatment on brain structure. Seventy-one schizophrenic patients and 79 age and gender matched healthy participants underwent brain magnetic resonance imaging (MRI). All images were processed with voxel based morphometry, using SPM5. Compared to healthy participants, patients showed decrements in gray matter volume in the left medial and left inferior frontal gyrus. In addition, duration of illness was negatively associated with gray matter volume in prefrontal regions bilaterally, in the temporal pole on the left and the caudal superior temporal gyrus on the right. Cumulative exposure to antipsychotics correlated positively with gray matter volumes in the cingulate gyrus for typical agents and in the thalamus for atypical drugs. These findings (a) indicate that structural abnormalities in prefrontal and temporal cortices in schizophrenia are progressive and, (b) suggest that antipsychotic medication has a significant impact on brain morphology.