[Show abstract][Hide abstract] ABSTRACT: After 140 years from the discovery of Golgi's black reaction, the study of connectivity of the cerebellum remains a fascinating yet challenging task. Current histological techniques provide powerful methods for unravelling local axonal architecture, but the relatively low volume of data that can be acquired in a reasonable amount of time limits their application to small samples. State-of-the-art in vivo magnetic resonance imaging (MRI) methods, such as diffusion tractography techniques, can reveal trajectories of the major white matter pathways, but their correspondence with underlying anatomy is yet to be established. Hence, a significant gap exists between these two approaches as neither of them can adequately describe the three-dimensional complexity of fibre architecture at the level of the mesoscale (from a few millimetres to micrometres). In this study, we report the application of MR diffusion histology and micro-tractography methods to reveal the combined cytoarchitectural organisation and connectivity of the human cerebellum at a resolution of 100-μm (2 nl/voxel volume). Results show that the diffusion characteristics for each layer of the cerebellar cortex correctly reflect the known cellular composition and its architectural pattern. Micro-tractography also reveals details of the axonal connectivity of individual cerebellar folia and the intra-cortical organisation of the different cerebellar layers. The direct correspondence between MR diffusion histology and micro-tractography with immunohistochemistry indicates that these approaches have the potential to complement traditional histology techniques by providing a non-destructive, quantitative and three-dimensional description of the microstructural organisation of the healthy and pathological tissue.
[Show abstract][Hide abstract] ABSTRACT: BACKGROUND: Bipolar disorder (BD) is one of the leading causes of disability worldwide. Patients are further disadvantaged by delays in accurate diagnosis ranging between 5 and 10 years. We applied Gaussian process classifiers (GPCs) to structural magnetic resonance imaging (sMRI) data to evaluate the feasibility of using pattern recognition techniques for the diagnostic classification of patients with BD. Method GPCs were applied to gray (GM) and white matter (WM) sMRI data derived from two independent samples of patients with BD (cohort 1: n��=��26; cohort 2: n��=��14). Within each cohort patients were matched on age, sex and IQ to an equal number of healthy controls. RESULTS: The diagnostic accuracy of the GPC for GM was 73% in cohort 1 and 72% in cohort 2; the sensitivity and specificity of the GM classification were respectively 69% and 77% in cohort 1 and 64% and 99% in cohort 2. The diagnostic accuracy of the GPC for WM was 69% in cohort 1 and 78% in cohort 2; the sensitivity and specificity of the WM classification were both 69% in cohort 1 and 71% and 86% respectively in cohort 2. In both samples, GM and WM clusters discriminating between patients and controls were localized within cortical and subcortical structures implicated in BD. CONCLUSIONS: Our results demonstrate the predictive value of neuroanatomical data in discriminating patients with BD from healthy individuals. The overlap between discriminative networks and regions implicated in the pathophysiology of BD supports the biological plausibility of the classifiers.
[Show abstract][Hide abstract] ABSTRACT: Neuroimaging data are increasingly being used to predict potential outcomes or groupings, such as clinical severity, drug dose response, and transitional illness states. In these examples, the variable (target) we want to predict is ordinal in nature. Conventional classification schemes assume that the targets are nominal and hence ignore their ranked nature, whereas parametric and/or non-parametric regression models enforce a metric notion of distance between classes. Here, we propose a novel, alternative multivariate approach that overcomes these limitations - whole brain probabilistic ordinal regression using a Gaussian process framework. We applied this technique to two data sets of pharmacological neuroimaging data from healthy volunteers. The first study was designed to investigate the effect of ketamine on brain activity and its subsequent modulation with two compounds - lamotrigine and risperidone. The second study investigates the effect of scopolamine on cerebral blood flow and its modulation using donepezil. We compared ordinal regression to multi-class classification schemes and metric regression. Considering the modulation of ketamine with lamotrigine, we found ordinal regression significantly outperformed multi-class classification and metric regression in terms of accuracy and mean absolute error. However, for risperidone ordinal regression significantly outperformed metric regression but performed similarly to multi-class classification both in terms of accuracy and mean absolute error. For the scopolamine dataset, ordinal regression was found to outperform both multi-class and metric regression techniques considering the regional cerebral blood flow in the anterior cingulate cortex. Ordinal regression was thus the only method that performed well in all cases. Our results indicate the potential of an ordinal regression approach for neuroimaging data while providing a fully probabilistic framework with elegant approaches for model selection.
[Show abstract][Hide abstract] ABSTRACT: RATIONALE: The increasing demand to develop more efficient compounds to treat cognitive impairments in schizophrenia has led to the development of experimental model systems. One such model system combines the study of surrogate populations expressing high levels of schizotypy with oculomotor biomarkers. OBJECTIVES: We aimed (1) to replicate oculomotor deficits in a psychometric schizotypy sample and (2) to investigate whether the expected deficits can be remedied by compounds shown to ameliorate impairments in schizophrenia. METHODS: In this randomized double-blind, placebo-controlled study 233 healthy participants performed prosaccade (PS), antisaccade (AS) and smooth pursuit eye movement (SPEM) tasks after being randomly assigned to one of four drug groups (nicotine, risperidone, amisulpride, placebo). Participants were classified into medium- and high-schizotypy groups based on their scores on the Schizotypal Personality Questionnaire (SPQ, Raine (Schizophr Bull 17:555-564, 1991)). RESULTS: AS error rate showed a main effect of Drug (p < 0.01), with nicotine improving performance, and a Drug by Schizotypy interaction (p = 0.04), indicating higher error rates in medium schizotypes (p = 0.01) but not high schizotypes under risperidone compared to placebo. High schizotypes had higher error rates than medium schizotypes under placebo (p = 0.03). There was a main effect of Drug for saccadic peak velocity and SPEM velocity gain (both p ≤ 0.01) indicating impaired performance with risperidone. CONCLUSIONS: We replicate the observation of AS impairments in high schizotypy under placebo and show that nicotine enhances performance irrespective of group status. Caution should be exerted in applying this model as no beneficial effects of antipsychotics were seen in high schizotypes.
[Show abstract][Hide abstract] ABSTRACT: Ketamine acts as an N-methyl D-aspartate (NMDA) receptor antagonist and evokes psychotomimetic symptoms resembling schizophrenia in healthy humans. Imaging markers of acute ketamine challenge have the potential to provide a powerful assay of novel therapies for psychiatric illness, although to date this assay has not been fully validated in humans. Pharmacological magnetic resonance imaging (phMRI) was conducted in a randomised, placebo-controlled cross-over design in healthy volunteers. The study comprised a control and three ketamine infusion sessions, two of which included pre-treatment with lamotrigine or risperidone, compounds hypothesised to reduce ketamine-induced glutamate release. The modulation of the ketamine phMRI response was investigated using univariate analysis of pre-specified regions and a novel application of multivariate analysis across the whole-brain response. Lamotrigine and risperidone resulted in widespread attenuation of the ketamine-induced increases in signal, including frontal and thalamic regions. A contrasting effect across both pre-treatments was observed only in the subgenual prefrontal cortex, for which ketamine produced a reduction in signal. Multivariate techniques proved successful in both classifying ketamine from placebo (100%) and identifying the probability of scans belonging to the ketamine class: ketamine pre-treated with placebo - 0.89. Following pre-treatment these predictive probabilities were reduced to 0.58 and 0.49 for lamotrigine and risperidone, respectively. We have provided clear demonstration of a ketamine phMRI response and its attenuation with both lamotrigine and risperidone. The analytical methodology used could be readily applied to investigate the mechanistic action of novel compounds relevant for psychiatric disorders such as schizophrenia and depression.
Journal of Pharmacology and Experimental Therapeutics 01/2013;
[Show abstract][Hide abstract] ABSTRACT: The non-competitive N-methyl-D-aspartate receptor antagonist ketamine leads to transient psychosis-like symptoms and impairments in oculomotor performance in healthy volunteers. This study examined whether the adverse effects of ketamine on oculomotor performance can be reversed by the atypical antipsychotic risperidone. In this randomized double-blind, placebo-controlled study, 72 healthy participants performed smooth pursuit eye movements (SPEM), prosaccades (PS) and antisaccades (AS) while being randomly assigned to one of four drug groups (intravenous 100 ng ml(-1) ketamine, 2 mg oral risperidone, 100 ng ml(-1) ketamine plus 2 mg oral risperidone, placebo). Drug administration did not lead to harmful adverse events. Ketamine increased saccadic frequency and decreased velocity gain of SPEM (all P<0.01) but had no significant effects on PS or AS (all P0.07). An effect of risperidone was observed for amplitude gain and peak velocity of PS and AS, indicating hypometric gain and slower velocities compared with placebo (both P0.04). No ketamine by risperidone interactions were found (all P0.26). The results confirm that the administration of ketamine produces oculomotor performance deficits similar in part to those seen in schizophrenia. The atypical antipsychotic risperidone did not reverse ketamine-induced deteriorations. These findings do not support the cognitive enhancing potential of risperidone on oculomotor biomarkers in this model system of schizophrenia and point towards the importance of developing alternative performance-enhancing compounds to optimise pharmacological treatment of schizophrenia.
[Show abstract][Hide abstract] ABSTRACT: Progressive supranuclear palsy (PSP), multiple system atrophy (MSA) and idiopathic Parkinson's disease (IPD) can be clinically indistinguishable, especially in the early stages, despite distinct patterns of molecular pathology. Structural neuroimaging holds promise for providing objective biomarkers for discriminating these diseases at the single subject level but all studies to date have reported incomplete separation of disease groups. In this study, we employed multi-class pattern recognition to assess the value of anatomical patterns derived from a widely available structural neuroimaging sequence for automated classification of these disorders. To achieve this, 17 patients with PSP, 14 with IPD and 19 with MSA were scanned using structural MRI along with 19 healthy controls (HCs). An advanced probabilistic pattern recognition approach was employed to evaluate the diagnostic value of several pre-defined anatomical patterns for discriminating the disorders, including: (i) a subcortical motor network; (ii) each of its component regions and (iii) the whole brain. All disease groups could be discriminated simultaneously with high accuracy using the subcortical motor network. The region providing the most accurate predictions overall was the midbrain/brainstem, which discriminated all disease groups from one another and from HCs. The subcortical network also produced more accurate predictions than the whole brain and all of its constituent regions. PSP was accurately predicted from the midbrain/brainstem, cerebellum and all basal ganglia compartments; MSA from the midbrain/brainstem and cerebellum and IPD from the midbrain/brainstem only. This study demonstrates that automated analysis of structural MRI can accurately predict diagnosis in individual patients with Parkinsonian disorders, and identifies distinct patterns of regional atrophy particularly useful for this process.
[Show abstract][Hide abstract] ABSTRACT: Wedeen et al. (Reports, 30 March 2012, p. 1628) proposed a geometrical grid pattern in the brain that could help the understanding of the brain's organization and connectivity. We show that whole-brain fiber crossing quantification does not support their theory. Our results suggest that the grid pattern is most likely an artifact attributable to the limitations of their method.
[Show abstract][Hide abstract] ABSTRACT: The pharmacological MRI (phMRI) technique is being increasingly used in both pre-clinical and clinical models to investigate pharmacological effects on task-free brain function. Ketamine, an N-methyl-d-aspartate receptor (NMDAR) antagonist, induces a strong phMRI response and represents a promising pharmacological model to investigate the role of glutamatergic abnormalities in psychiatric symptomatology. The aim of this study was to assess whether the brain response to ketamine is reliable in order to validate ketamine phMRI as a mechanistic marker of glutamatergic dysfunction and to determine its utility in repeated measures designs to detect the modulatory effect of other drugs. Thus we assessed the test-retest reliability of the brain response to ketamine in healthy volunteers and identified an optimal modelling approach with reliability as our selection criterion. PhMRI data were collected from 10 healthy male participants, at rest, on two separate occasions. Subanaesthetic doses of I.V. ketamine infusion (target plasma levels 50ng/mL and 75ng/mL) were administered in both sessions. Test-retest reliability of the ketamine phMRI response was assessed voxel-wise and on pre-defined ROIs for a range of temporal design matrices including different combinations of nuisance regressors designed to model shape variance, linear drift and head motion. Effect sizes are also reported. All models showed a significant and widespread response to low-dose ketamine in predicted cerebral networks and as expected, increasing the number of model parameters improved model fit. Reliability of the predefined ROIs differed between the different models assessed. Using reliability as the selection criterion, a model capturing subject motion and linear drift performed the best across two sessions. The anatomical distribution of effects for all models was consistent with results of previous imaging studies in humans with BOLD signal increases in regions including midline cingulate and supracingulate cortex, thalamus, insula, anterior temporal lobe and ventrolateral prefrontal structures, and BOLD signal decreases in the subgenual cingulate cortex. This study represents the first investigation of the test-retest reliability of the BOLD phMRI response to acute ketamine challenge. All models tested were effective at describing the ketamine response although the design matrix associated with the highest reliability may represent a robust and well-characterised ketamine phMRI assay more suitable for repeated-measures designs. This ketamine assay is applicable as a model of neurotransmitter dysfunction suitable as a pharmacodynamic imaging tool to test and validate modulatory interventions, as a model of NMDA hypofunction in psychiatric disorders, and may be adapted to understand potential antidepressant and analgesic effects of NMDAR antagonists.
[Show abstract][Hide abstract] ABSTRACT: Neural oscillations in the gamma band are of increasing interest, but separating them from myogenic electrical activity has proved difficult. A novel algorithm has been developed to reduce the effect of tonic scalp and neck muscle activity on the gamma band of the EEG. This uses mathematical modelling to fit individual muscle spikes and then subtracts them from the data. The method was applied to the detection of motor associated gamma in two separate groups of eight subjects using different sampling rates. A reproducible increase in high gamma (65-85 Hz) magnitude occurred immediately after the motor action in the left central area (p = 0.02 and p = 0.0002 for the two cohorts with individually optimized algorithm parameters, compared to p = 0.03 and p = 0.16 before correction). Whilst the magnitude of this event-related gamma synchronisation was not reduced by the application of the EMG reduction algorithm, the baseline left central gamma magnitude was significantly reduced by an average of 23 % with a faster sampling rate (p < 0.05). In comparison, at left and right temporo-parietal locations the gamma amplitude was reduced by 60 and 54 % respectively (p < 0.05). The reduction of EMG contamination by fitting and subtraction of individual spikes shows promise as a method of improving the signal to noise ratio of high frequency neural oscillations in scalp EEG.
Brain Topography 09/2012;
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