Estimating duration depends on the sequential integration (accumulation) of temporal information in working memory. Using fMRI, we directly compared the accumulation of information in temporal versus spatial domains. Participants estimated either the duration or distance of the dynamic trajectory of a moving dot or, in a control condition, a static line stimulus. Comparing the duration versus distance of static lines activated an extensive cortico-striatal network. By contrast, comparing the duration versus distance of dynamic trajectories, both of which required sequential integration of information, activated SMA alone. Indeed, activity in SMA, as well as right inferior occipital cortex, increased parametrically as a function of stimulus duration and also correlated with individual differences in the propensity to overestimate stimulus duration. By contrast, activity in primary visual cortex increased parametrically as a function of stimulus distance. Crucially, a direct comparison of the parametric responses to duration versus distance revealed that activity in SMA increased incrementally as a function of stimulus duration but not as a function of stimulus distance. Collectively, our results indicate that SMA responds to the active accumulation of information selectively in the temporal domain.
Purpose Using optimized fast volumic echo planar spectroscopic imaging (3D-EPSI), we aimed to detect local metabolic abnormalities over the complete human brain in multiple sclerosis patients. Materials and methods Weighted mean combination of two 3D-EPSI covering the whole brain acquired at 3T in AC-PC and AC-PC+15° axial planes was performed to obtain high quality metabolite maps for five metabolites: N-acetyl aspartate (NAA), glutamate+glutamine (Glx), choline (Cho), myo-inositol (m-Ins) and creatine+phosphocreatine (tCr). After spatial normalisation, maps from 19 patients suffering from relapsing-remitting multiple sclerosis were compared to 19 matched controls using statistical mapping analyses to determine the topography of metabolic abnormalities. Probabilistic white matter (WM) T2 lesion maps and grey matter (GM) atrophy maps were also generated. Results Two-group ANOVA (SPM8, p<0.005, FDR corrected p<0.05 at the cluster level with age and sex as confounding covariates) comparing Patients and controls matched for age and sex showed clusters of abnormal metabolite levels with i) decreased NAA (around −15%) and Glx (around 20%) predominantly in GM within prefrontal cortices, motor cortices, bilateral thalami and mesial temporal cortices in line with neuronal/neuro-astrocytic dysfunction, ii) increased m-Ins (around +20%) inside WM T2 lesions and in the normal appearing WM of temporal-occipital lobes suggesting glial activation. Conclusion We demonstrated the ability to map non-invasively over the complete brain - from vertex to cerebellum – with a validated sequence, the metabolic abnormalities associated with MS, for characterizing the topography of pathological processes affecting widespread areas of WM and GM and its functional impact.
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