Diagnosis of Alzheimer’s Disease from EEG by Means of Synchrony Measures in Optimized Frequency Bands

Several clinical studies have reported that EEG synchrony is affected by Alzheimer’s disease (AD). In this paper a frequency band analysis of AD EEG signals is presented, with the aim of improving the diagnosis of AD using EEG signals. In this paper, multiple synchrony measures are assessed through statistical tests (Mann–Whitney U test), including correlation, phase synchrony and Granger causality measures. Moreover, linear discriminant analysis (LDA) is conducted with those synchrony measures as features. For the data set at hand, the frequency range (5-6Hz) yields the best accuracy for diagnosing AD, which lies within the classical theta band (4-8Hz). The corresponding classification error is 4.88% for directed transfer function (DTF) Granger causality measure. Interestingly, results show that EEG of AD patients is more synchronous than in healthy subjects within the optimized range 5-6Hz, which is in sharp contrast with the loss of synchrony in AD EEG reported in many earlier studies. This new finding may provide new insights about the neurophysiology of AD. Additional testing on larger AD datasets is required to verify the effectiveness of the proposed approach.

Dual role of LldR in regulation of the lldPRD operon, involved in l-Lactate metabolism in Escherichia coli.

The lldPRD operon of Escherichia coli, involved in L-lactate metabolism, is induced by growth in this compound. We experimentally identified that this system is transcribed from a single promoter with an initiation site located 110 nucleotides upstream of the ATG start codon. On the basis of computational data, it had been proposed that LldR and its homologue PdhR act as regulators of the lldPRD operon. Nevertheless, no experimental data on the function of these regulators have been reported so far. Here we show that induction of an lldP-lacZ fusion by L-lactate is lost in an lldR mutant, indicating the role of LldR in this induction. Expression analysis of this construct in a pdhR mutant ruled out the participation of PdhR in the control of lldPRD. Gel shift experiments showed that LldR binds to two operator sites, O1 (positions 105 to 89) and O2 (positions 22 to 38), with O1 being filled at a lower concentration of LldR. L-Lactate induced a conformational change in LldR that did not modify its DNA binding activity. Mutations in O1 and O2 enhanced the basal transcriptional level. However, only mutations in O1 abolished induction by L-lactate. Mutants with a change in helical phasing between O1 and O2 behaved like O2 mutants. These results were consistent with the hypothesis that LldR has a dual role, acting as a repressor or an activator of lldPRD. We propose that in the absence of L-lactate, LldR binds to both O1 and O2, probably leading to DNA looping and the repression of transcription. Binding of L-lactate to LldR promotes a conformational change that may disrupt the DNA loop, allowing the formation of the transcription open complex.

Patología Dual y rasgos de personalidad:situación actual y líneas futuras de trabajo

Dual diagnosis (DD) is the co-occurrence, in the same person, of a mental disorder (MD) and a substance use disorder (SUD). Nowadays, the study of the personality with DD is realized mainly from a categorical view, focusing on the detection of personality disorders and not on the traits associated to DD and the possible differential profile compared to those patients with only MD or SUD. Studies analyzing personality traits of patients with DD and their possible differential profile are very limited. However, existing data indicates that DD patients show higher levels of Sensation Seeking, Impulsivity, Harm Avoidance and Neuroticism; and lower levels of Persistence, Self-Direction, Self-Transcendence and Cooperation. Therefore, DD is associated to personality characteristics that suggest more disruptive behaviors, fewer resources for recovering and keeping abstinent and worse prognosis compared to those with only one disorder. Progress in the characterization of personality traits in DD, taking into consideration the methodological aspects to be improved could allow better adaptation of the integrated treatment of these patients in the future.

Networks of noisy oscillators with correlated degree and frequency dispersion

We investigate how correlations between the diversity of the connectivity of networks and the dynamics at their nodes affect the macroscopic behavior. In particular, we study the synchronization transition of coupled stochastic phase oscillators that represent the node dynamics. Crucially in our work, the variability in the number of connections of the nodes is correlated with the width of the frequency distribution of the oscillators. By numerical simulations on Erdös-Rényi networks, where the frequencies of the oscillators are Gaussian distributed, we make the counterintuitive observation that an increase in the strength of the correlation is accompanied by an increase in the critical coupling strength for the onset of synchronization. We further observe that the critical coupling can solely depend on the average number of connections or even completely lose its dependence on the network connectivity. Only beyond this state, a weighted mean-field approximation breaks down. If noise is present, the correlations have to be stronger to yield similar observations.