The neural correlates of specific executive dysfunctions in Parkinson's disease

Several functional neuroimaging studies in patients with Parkinson's disease (PD) have suggested that changes in the fronto-parietal-striatal networks are associated with deficits in executive functioning. However, executive functions (EF) are multifaceted and include three dissociable components: working memory, response inhibition, and task-switching. This study investigated which component of executive functioning is most strongly associated with fronto-parietal-striatal efficiency in PD. PD patients (with and without executive dysfunction), and age-matched healthy subjects, completed a battery of cognitive tests previously shown to discriminate among the three EF components. Principal component analysis conducted on the selected cognitive test variables yielded three expected EF components. The component scores were used in regression analysis to assess the relationship between the EF efficiency and blood oxygenation level-dependent (BOLD) signal related to performing the n-back, an experimental task that draws upon multiple components of executive functioning: working memory, response inhibition, and task-switching. We found distinct neural correlates of specific executive dysfunctions in patients with PD. However, all of them seem to be associated with fronto-parietal-striatal efficiency.

Changes in fMRI BOLD response to increasing and decreasing task difficulty during auditory perception of temporal order

We have discovered changes in brain activation during difficult and easy milliseconds timing. Structures engaged in difficult and easier auditory temporal-order judgment were identified in 17 young healthy listeners presented with paired-white-noises of different durations. Within each pair, a short (10 ms) and a long (50 ms) noise was separated by a silent gap of 10, 60 or 160 ms, corresponding to three levels of task difficulty, i.e. difficult, moderate and easy conditions, respectively. A block design paradigm was applied. In temporal-order judgment task subjects were required to define the order of noises within each pair, i.e. short-long or long-short. In the control task they only detected the presentation of the stimulus pair. A multiple regression with 'task difficulty' as a regressor ('difficult', 'moderate', 'easy') showed dynamic changes in neural activity. Increasing activations accompanying increased task difficulty were found in both bilateral inferior parietal lobuli and inferior frontal gyri, thus, in classic regions related to attentional and working memory processes. Conversely, decreased task difficulty was accompanied by increasing involvement of more specific timing areas, namely bilateral medial frontal gyri and left cerebellum. These findings strongly suggest engagement of different neural networks in difficult or easier timing and indicate a framework for understanding timing representation in the brain.

Functional imaging with MR T1 contrast: a feasibility study with blood-pool contrast agent

The aim of this study was to prove the concept of using a long intravenous half-life blood-pool T1 contrast agent as a new functional imaging method. For each of ten healthy subjects, two dynamic magnetic resonance (MR) protocols were carried out: (1) a reference run with a typical T2* echo-planar imaging (EPI) sequence based on the blood oxygenation level-dependent (BOLD) effect and (2) a run with a T1-sensitive three-dimensional (3D) gradient-echo (GRE) sequence using cerebral blood volume (CBV) contrast after intravenous administration of a contrast agent containing a chelate of gadolinium diethylene-triamine-pentaacetate with a phosphono-oxymethyl substituent. All sequences were performed during the execution of a block-type finger-tapping paradigm. SPM5 software was used for statistical analysis. For both runs maximum activations (peak Z-score = 5.5, cluster size 3,449 voxels) were localized in the left postcentral gyrus. Visual inspection of respective signal amplitudes suggests the T1 contrast to be substantially smaller than EPI (0.5% vs 1%). A new functional imaging method with potentially smaller image artefacts due to the nature of CBV contrast and characteristics of the T1 sequence was proposed and verified.

Improved recognition of sustained ventricular tachycardia from SAECG by support vector machine

OBJECTIVE

We present the improved method of recognition of sustained ventricular tachycardia (SVT) based on new filtering technique (FIR), extended signal-averaged electrocardiography (SAECG) description by 9 parameters and the application of support vector machine (SVM) classifier.

METHODS

The dataset consisted of 376 patients (100 patients with sustained ventricular tachycardia after myocardial infarction (MI) labelled as class SVT+, 176 patients without sustained ventricular tachycardia after MI and 77 healthy persons, 50% of data were left for validation. The analysis of SAECG was performed by 2 types of filtration: low pass four-pole IIR Butterworth filter and FIR filter with Kaiser window. We calculated 3 commonly used SAECG parameters: hfQRS (ms), RMS40 (microV), LAS<40 microV(ms) and 6 new parameters: LAS<25 microV(ms) - duration of the low amplitude <25 microV signals at the end of QRS complex; RMS QRS(microV) - root mean square voltage of the filtered QRS complex; pRMS(microV) - root mean square voltage of the first 40 ms of filtered QRS complex; pLAS(ms) - duration of the low amplitude <40 microV signals in front of QRS complex; RMS t1(microV) - root mean square voltage of the last 10 ms the filtered QRS complex; RMS t2(microV) - root mean square voltage of the last 20 ms the filtered QRS complex. For the recognition of SVT+ class patients we used the SVM with the Gaussian kernel.

RESULTS

The results confirmed good generalization of obtained models. The recognition score (calculated as correct classification/total number of patients) of SVT+patients on data set containing 3 standard parameters (Butterworth filter) is 92.55%. The same score was obtained for data set containing 9 parameters (Butterworth filter). The best score (95.21%) was obtained for data set based on 9 parameters and FIR filter.

CONCLUSION

Our approach improved risk stratification up to 95% based on SAECG due to the application of FIR filter, 6 new parameters and efficient statistical classifier, the support vector machine.

[P-wave ekg averaging technique--a new method of selecting patients with paroxysmal atrial fibrillation]

The aim of study was to assess the value of signal averaged ecg for detection of patients (pts) at risk for paroxysmal atrial fibrillation (paf). We examined three groups of pts: group I-41 pts with nonvalvular paf, group II-20 pts with hypertension and/or ischemic heart disease without paf and group 3-26 health persons, without organic heart disease. In all pts the signal-averaged electrocardiogram triggered by P waves was recorded. Seven parameters of the spatial magnitude of filtered P wave were measured. Significant difference between group I and group II or III was found in most parameters. Using the method of multidimensional variance analysis we constructed "the diagnostic vector" in multidimensional parameters space, which was used to determine patients belonging to group. Total percent of right decision was 85%. These findings suggest that pts at risk for paf could be detected while in sinus rhythm by using the P wave-triggered signal-averaged ecg.