Olivera Sveljo

The functional neuroimaging evidence of cerebellar involvement in the simple cognitive task.

Cerebellar involvement in cognitive functions has been revealed in numerous anatomical, clinical and neuroimaging studies and several hypotheses about potential the role of the cerebellum in higher level brain function have been established. The aim of this study was to show involvement of the cerebellum in simple cognitive tasks. For this matter, we contrasted two tasks from the same semantic domain with specific cognitive content and level of practice: counting forward and counting backward. Twelve volunteers participated in this fMRI study and they were asked to perform both tasks within the same number range (1 to 30 and vice versa). Results showed greater activation in the right cerebellum for the task of counting forward than for counting backward, while for counting backward greater activation was found in prefrontal cortex, supplementary motor area, and anterior cingulate of both hemispheres. Our results correlate with already established hypotheses about cerebellar role in precise and smooth control, not only in well-trained motor but in well trained cognitive tasks as well.

Multidisciplinary investigation links backward-speech trait and working memory through genetic mutation.

Case studies of unusual traits can provide unique snapshots of the effects of modified systems. In this study, we report on an individual from a Serbian family with the ability to rapidly, accurately and voluntarily speak backwards. We consider psychological, neural and genetic correlates of this trait to identify specific relevant neural mechanisms and new molecular pathways for working memory and speech-related tasks. EEG data suggest that the effect of word reversal precedes semantic integration of visually presented backward-words, and that event-related potentials above the frontal lobe are affected by both word reversal and the maintenance of backward-words in working memory. fMRI revealed that the left fusiform gyrus may facilitate the production of backward-speech. Exome sequencing identified three novel coding variants of potential significance in the RIC3, RIPK1 and ZBED5 genes. Taken together, our data suggest that, in this individual, the ability to speak backwards is afforded by an extraordinary working memory capacity. We hypothesise that this is served by cholinergic projections from the basal forebrain to the frontal cortex and supported by visual semantic loops within the left fusiform gyrus and that these neural processes may be mediated by a genetic mutation in RIC3; a chaperone for nicotinic acetylcholine receptors.

Ictal spitting in left temporal lobe epilepsy and fMRI speech lateralization.

Ictal spitting is a “rare” peri-ictal vegetative sign (PIVS) observed n temporal lobe epilepsy (TLE). Some articles analyzing its lateralzing value have demonstrated that ictal spitting indicates a seizure nset in the non-dominant speech hemisphere [1]. Other studies nd case reports have not shown a lateralizing value for ictal spiting, probably because of low incidence and small sample size [2]. n a recent paper, ictal spitting occurred in 1.03% of patients with LE and 0.26% of seizures arising from the non-dominant temporal obe [3]. We report a man with pharmacoresistent epilepsy who ad a dysembryoplastic neuroepithelial tumor (DNET) in the left emporal lobe and who was considered as a surgical candidate. e recorded his typical seizures. His seizures were accompaied by ictal spitting that might suggest seizure origin from the on-dominant temporal lobe, but the fMRI language lateralization evealed speech activation on the left side.

fMRI resting state analysis using empirical mode decomposition

The paper studies connectivity pattern between two functionally specialized brain areas: the primary motor area and the occipital (visual) cortex in the resting state fMRI using empirical mode decomposition (EMD). EMD enables identification of low frequency oscillatory modes in the resting state range [0, 01-0, 1 Hz]. Three frequency modes were determined in the resting state band in 13 subjects with the mean frequencies 0,07Hz, 0,034Hz and 0,016Hz. The temporal correlations among the oscillatory modes were strongest within homologous (corresponding) sources in left and right hemisphere, and weakest between the motor-occipital fMRI signal pairs. The functional connectivity - spatial distribution of temporal correlations in the resting state - has been identified and refined by the oscillatory modes. Connectivity graph obtained across all subjects and all IMFs showed high connectivity rate between homologous areas in the left and right hemisphere and among the visual cortex areas. Combining EMD with the Hilbert transformation may provide an additional tool for exploring correlations between frequency and amplitude ridges in task related problems.

Estimation of subcutaneous and visceral fat tissue volume on abdominal MR images

Fat depots at different location are associated with variable metabolic risks. It has been noted that visceral abdominal adipose tissue contributes more to these risks than subcutaneous adipose tissue. For discrimination between subcutaneous and visceral adipose tissue contemporary studies primarily use cross sectional medical imaging. Fat volume at different anatomical locations is usually identified and determined either manually or in semiautomatic manner. In this study we combined different image processing methods for unsupervised discrimination of subcutaneous and visceral adipose tissue on abdominal T1 MR images. Procedure has been tested on 16 subjects and results are compared with visceral and subcutaneous volume obtained by semiautomatic method from the literature. High correlation was achieved for subcutaneous fat tissue volume (0.98) while for visceral fat tissue good correlation has been noted (0.86).

FMRI based connectivity analysis of perisylvian language related brain areas

Usually, the focus of fMRI studies is the identification of brain regions that change level of activations as a response to specific stimuli. On the other hand, possible connectivity modeling between activated brain areas remains an open question. Based on fMRI data, in the last decades different methods for uncovering interactions between brain areas have been proposed. In this study we used the generalized Partial Directed Coherence (gPDC) to identify directed interactions between activated brain areas during self paced block fMRI paradigm for the identification of perisylvian language related brain areas.