Functional Magnetic Resonance Imaging Data Analysis by Autoregressive Estimator

The autoregressive (AR) estimator, a non-parametric method, is used to analyze functional magnetic resonance imaging (fMRI) data. The same method has been used, with success, in several other time series data analysis. It uses exclusively the available experimental data points to estimate the most plausible power spectra compatible with the experimental data and there is no need to make any assumption about non-measured points. The time series, obtained from fMRI block paradigm data, is analyzed by the AR method to determine the brain active regions involved in the processing of a given stimulus. This method is considerably more reliable than the fast Fourier transform or the parametric methods. The time series corresponding to each image pixel is analyzed using the AR estimator and the corresponding poles are obtained. The pole distribution gives the shape of power spectra, and the pixels with poles at the stimulation frequency are considered as the active regions. The method was applied in simulated and real data, its superiority is shown by the receiver operating characteristic curves which were obtained using the simulated data.

Promoter regions of Plasmodium vivax are poorly or not recognized by Plasmodium falciparum

Abstract Background Heterologous promoter analysis in Plasmodium has revealed the existence of conserved cis regulatory elements as promoters from different species can drive expression of reporter genes in heterologous transfection assays. Here, the functional characterization of different Plasmodium vivax promoters in Plasmodium falciparum using luciferase as the reporter gene is presented. Methods Luciferase reporter plasmids harboring the upstream regions of the msp1, dhfr, and vir3 genes as well as the full-length intergenic regions of the vir23/24 and ef-1α genes of P. vivax were constructed and transiently transfected in P. falciparum. Results Only the constructs with the full-length intergenic regions of the vir23/24 and ef-1α genes were recognized by the P. falciparum transcription machinery albeit to values approximately two orders of magnitude lower than those reported by luc plasmids harbouring promoter regions from P. falciparum and Plasmodium berghei. A bioinformatics approach allowed the identification of a motif (GCATAT) in the ef-1α intergenic region that is conserved in five Plasmodium species but is degenerate (GCANAN) in P. vivax. Mutations of this motif in the P. berghei ef-1α promoter region decreased reporter expression indicating it is active in gene expression in Plasmodium. Conclusion Together, this data indicates that promoter regions of P. vivax are poorly or not recognized by the P. falciparum transcription machinery suggesting the existence of P. vivax-specific transcription regulatory elements.

Increased coherence among striatal regions in the theta range during attentive wakefulness

The striatum, the largest component of the basal ganglia, is usually subdivided into associative, motor and limbic components. However, the electrophysiological interactions between these three subsystems during behavior remain largely unknown. We hypothesized that the striatum might be particularly active during exploratory behavior, which is presumably associated with increased attention. We investigated the modulation of local field potentials (LFPs) in the striatum during attentive wakefulness in freely moving rats. To this end, we implanted microelectrodes into different parts of the striatum of Wistar rats, as well as into the motor, associative and limbic cortices. We then used electromyograms to identify motor activity and analyzed the instantaneous frequency, power spectra and partial directed coherence during exploratory behavior. We observed fine modulation in the theta frequency range of striatal LFPs in 92.5 ± 2.5% of all epochs of exploratory behavior. Concomitantly, the theta power spectrum increased in all striatal channels (P < 0.001), and coherence analysis revealed strong connectivity (coefficients >0.7) between the primary motor cortex and the rostral part of the caudatoputamen nucleus, as well as among all striatal channels (P < 0.001). Conclusively, we observed a pattern of strong theta band activation in the entire striatum during attentive wakefulness, as well as a strong coherence between the motor cortex and the entire striatum. We suggest that this activation reflects the integration of motor, cognitive and limbic systems during attentive wakefulness.