Sara De Simoni

Pattern classification of working memory networks reveals differential effects of methylphenidate, atomoxetine, and placebo in healthy volunteers

Stimulant and non-stimulant drugs can reduce symptoms of attention deficit/hyperactivity disorder (ADHD). The stimulant drug methylphenidate (MPH) and the non-stimulant drug atomoxetine (ATX) are both widely used for ADHD treatment, but their differential effects on human brain function remain unclear. We combined event-related fMRI with multivariate pattern recognition to characterize the effects of MPH and ATX in healthy volunteers performing a rewarded working memory (WM) task. The effects of MPH and ATX on WM were strongly dependent on their behavioral context. During non-rewarded trials, only MPH could be discriminated from placebo (PLC), with MPH producing a similar activation pattern to reward. During rewarded trials both drugs produced the opposite effect to reward, that is, attenuating WM networks and enhancing task-related deactivations (TRDs) in regions consistent with the default mode network (DMN). The drugs could be directly discriminated during the delay component of rewarded trials: MPH produced greater activity in WM networks and ATX produced greater activity in the DMN. Our data provide evidence that: (1) MPH and ATX have prominent effects during rewarded WM in task-activated and -deactivated networks; (2) during the delay component of rewarded trials, MPH and ATX have opposing effects on activated and deactivated networks: MPH enhances TRDs more than ATX, whereas ATX attenuates WM networks more than MPH; and (3) MPH mimics reward during encoding. Thus, interactions between drug effects and motivational state are crucial in defining the effects of MPH and ATX.

Dissociable effects of methylphenidate, atomoxetine and placebo on regional cerebral blood flow in healthy volunteers at rest: a multi-class pattern recognition approach.

The stimulant drug methylphenidate (MPH) and the non-stimulant drug atomoxetine (ATX) are both widely used for the treatment of attention deficit/hyperactivity disorder (ADHD), but their differential effects on human brain function are poorly understood. PET and blood oxygen level dependent (BOLD) fMRI have been used to study the effects of MPH and BOLD fMRI is beginning to be used to delineate the effects of MPH and ATX in the context of cognitive tasks. The BOLD signal is a proxy for neuronal activity and is dependent on three physiological parameters: regional cerebral blood flow (rCBF), cerebral metabolic rate of oxygen and cerebral blood volume. To identify areas sensitive to MPH and ATX and assist interpretation of BOLD studies in healthy volunteers and ADHD patients, it is therefore of interest to characterize the effects of these drugs on rCBF. In this study, we used arterial spin labeling (ASL) MRI to measure rCBF non-invasively in healthy volunteers after administration of MPH, ATX or placebo. We employed multi-class pattern recognition (PR) to discriminate the neuronal effects of the drugs, which accurately discriminated all drug conditions from one another and provided activity patterns that precisely localized discriminating brain regions. We showed common and differential effects in cortical and subcortical brain regions. The clearest differential effects were observed in four regions: (i) in the caudate body where MPH but not ATX increased rCBF, (ii) in the midbrain/substantia nigra and (iii) thalamus where MPH increased and ATX decreased rCBF plus (iv) a large region of cerebellar cortex where ATX increased rCBF relative to MPH. Our results demonstrate that combining ASL and PR yields a sensitive method for detecting the effects of these drugs and provides insights into the regional distribution of brain networks potentially modulated by these compounds.

Modulatory effects of ketamine, risperidone and lamotrigine on resting brain perfusion in healthy human subjects

RationaleResting brain perfusion, measured using the MRI-based arterial spin labelling (ASL) technique, is sensitive to detect central effects of single, clinically effective, doses of pharmacological compounds. However, pharmacological interaction experiments, such as the modulation of one drug response in the presence of another, have not been widely investigated using a task-free ASL approach.ObjectivesWe assessed the effects of three psychoactive compounds (ketamine, risperidone and lamotrigine), and their interaction, on resting brain perfusion in healthy human volunteers.MethodsA multivariate Gaussian process classification (GPC) and more conventional univariate analyses were applied. The four pre-infusion conditions for each subject comprised risperidone, lamotrigine and two placebo sessions. The two placebo conditions enabled us to evaluate the classification performance in a test-retest setting, in addition to its performance in distinguishing the active oral drugs from placebo (direct effect on brain perfusion). The post ketamine- or saline-infusion scans allowed the effect of ketamine, and its interaction with risperidone and lamotrigine, on brain perfusion to be characterised.ResultsThe pseudo-continuous ASL measurements of perfusion were sensitive to the effects of ketamine infusion and risperidone. The GPC captured consistent changes in perfusion across the group and contextualised the univariate changes with a larger pattern of regions contributing to accurate discrimination of ketamine from placebo.ConclusionsThe findings argue against perfusion changes confounding in the previously described evoked BOLD response to ketamine and emphasise the blockade of the NMDA receptor over neuronal glutamate release in determining the perfusion changes induced by ketamine.

Perceptual distortions and delusional thinking following ketamine administration are related to increased pharmacological MRI signal changes in the parietal lobe

Ketamine produces effects in healthy humans that resemble the positive, negative and cognitive symptoms of schizophrenia. We investigated the effect of ketamine administration on brain activity as indexed by blood-oxygen-level-dependent (BOLD) signal change response, and its relationship to ketamine-induced subjective changes, including perceptual distortion. Thirteen healthy participants volunteered for the study. All underwent a 15-min functional MRI acquisition with a ketamine infusion commencing after 5 min (approx 0.26 mg/kg over 20s followed by an infusion of approx. 0.42 mg/kg/h). Following the scan, participants self-rated ketamine-induced effects using the Psychotomimetic States Inventory. Ketamine led to widespread cortical and subcortical increases in BOLD response (FWE-corrected p < 0.01). Self-rated perceptual distortions and delusional thoughts correlated with increased BOLD response in the paracentral lobule (FWE-corrected p < 0.01). The findings suggest that BOLD increases in parietal cortices reflect ketamine effects on circuits that contribute to its capacity to produce perceptual alterations and delusional interpretations.

Quantifying the attenuation of the ketamine phMRI response in humans: a validation using antipsychotic and glutamatergic agents

Ketamine acts as an N-methyl-D-aspartate 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 randomized, placebo-controlled crossover design in healthy volunteers. The study comprised a control and three ketamine infusion sessions, two of which included pretreatment with lamotrigine or risperidone, compounds hypothesized to reduce ketamine-induced glutamate release. The modulation of the ketamine phMRI response was investigated using univariate analysis of prespecified 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 the frontal and thalamic regions. A contrasting effect across both pretreatments was observed only in the subgenual prefrontal cortex, in 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 pretreated with placebo: 0.89). Following pretreatment, 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.

Quantifying the Information Content of Brain Voxels Using Target Information, Gaussian Processes and Recursive Feature Elimination

Multivariate pattern classification is emerging as a powerful tool for analysis of fMRI group studies and has the advantage that it utilizes spatial correlation between brain voxels. However, this makes quantifying the information content of brain voxels and localizing informative brain regions difficult. In this paper we a probabilistic Gaussian process classifiers to compute a sensitive measure of the information content of brain voxels (‘target information’/TI) which we combine with a recursive feature elimination strategy. We apply this approach to a pharmacological fMRI study investigating rewarded working memory and compare it to sparse logistic regression. We show our approach is better suited to fMRI group studies, yielding more accurate classifiers and a sparse representation of informative brain regions. We also show that TI furnishes better estimates of voxel information content than existing approaches.

Minocycline reduces chronic microglial activation after brain trauma but increases neurodegeneration

Head injury survivors can develop neurodegeneration associated with persistent neuroinflammation, but whether the latter is harmful or beneficial is unclear. Scott et al. report that minocycline reduces neuroinflammation months and years after injury but increases a blood marker of neurodegeneration, suggesting that persistent neuroinflammation has reparative effects long after injury.

Spatial patterns of progressive brain volume loss after moderate-severe traumatic brain injury

Using longitudinal neuroimaging, Cole et al. show that traumatic brain injury (TBI) results in progressive loss of brain tissue that continues for years after an injury. Tissue loss occurs predominantly in cerebral white matter and cortical sulci. Neuroimaging may be a feasible method for evaluating neuroprotective therapies after TBI.

Altered caudate connectivity is associated with executive dysfunction after traumatic brain injury

Traumatic brain injury often produces executive dysfunction, causing long-term problems with behaviour and personality. De Simoni et al. report that executive dysfunction following TBI is associated with altered corticostriatal interactions important for behavioural control. These findings provide a target for the evaluation of treatments aimed at improving executive function after TBI.

Data-driven modeling of BOLD drug response curves using Gaussian process learning

This paper presents a data-driven approach for modeling the temporal profile of pharmacological magnetic resonance imaging (phMRI) data, in which the blood oxygen level-dependent (BOLD) response to an acute drug challenge is measured. To date, this type of data have typically been analysed using general linear models applied to each voxel individually, an approach that requires a pre-defined model of the expected response to the pharmacological stimulus. Previous approaches have defined this model using pharmacokinetic profiles, phMRI data from pilot studies, cognitive or physiological variables that have been acquired during the experiment or a simple pre-post boxcar profile. In contrast, the approach presented here is data-driven; a basis function is fitted to the data in a Bayesian framework using Gaussian processes. This method outperforms two previous multivariate approaches to fMRI analysis while also providing information about the shape of the BOLD response and hence, increasing the model interpretability.