Classifying post-traumatic stress disorder using the magnetoencephalographic connectome and machine learning

Given the subjective nature of conventional diagnostic methods for post-traumatic stress disorder (PTSD), an objectively measurable biomarker is highly desirable; especially to clinicians and researchers. Macroscopic neural circuits measured using magnetoencephalography (MEG) has previously been shown to be indicative of the PTSD phenotype and severity. In the present study, we employed a machine learning-based classification framework using MEG neural synchrony to distinguish combat-related PTSD from trauma-exposed controls. Support vector machine (SVM) was used as the core classification algorithm. A recursive random forest feature selection step was directly incorporated in the nested SVM cross validation process (CV-SVM-rRF-FS) for identifying the most important features for PTSD classification. For the five frequency bands tested, the CV-SVM-rRF-FS analysis selected the minimum numbers of edges per frequency that could serve as a PTSD signature and be used as the basis for SVM modelling. Many of the selected edges have been reported previously to be core in PTSD pathophysiology, with frequency-specific patterns also observed. Furthermore, the independent partial least squares discriminant analysis suggested low bias in the machine learning process. The final SVM models built with selected features showed excellent PTSD classification performance (area-under-curve value up to 0.9). Testament to its robustness when distinguishing individuals from a heavily traumatised control group, these developments for a classification model for PTSD also provide a comprehensive machine learning-based computational framework for classifying other mental health challenges using MEG connectome profiles

Addressing the Language Binding Problem With Dynamic Functional Connectivity During Meaningful Spoken Language Comprehension

During speech, how does the brain integrate information processed on different timescales and in separate brain areas so we can understand what is said? This is the language binding problem. Dynamic functional connectivity (brief periods of synchronization in the phase of EEG oscillations) may provide some answers. Here we investigate time and frequency characteristics of oscillatory power and phase synchrony (dynamic functional connectivity) during speech comprehension. Twenty adults listened to meaningful English sentences and non-sensical “Jabberwocky” sentences in which pseudo-words replaced all content words, while EEG was recorded. Results showed greater oscillatory power and global connectivity strength (mean phase lag index) in the gamma frequency range (30–80 Hz) for English compared to Jabberwocky. Increased power and connectivity relative to baseline was also seen in the theta frequency range (4–7 Hz), but was similar for English and Jabberwocky. High-frequency gamma oscillations may reflect a mechanism by which the brain transfers and integrates linguistic information so we can extract meaning and understand what is said. Slower frequency theta oscillations may support domain-general processing of the rhythmic features of speech. Our findings suggest that constructing a meaningful representation of speech involves dynamic interactions among distributed brain regions that communicate through frequency-specific functional networks

Evidence that smooth pursuit velocity, not eye position, modulates alpha and beta oscillations in human middle temporal cortex

Suppression of 5–25 Hz oscillations have been observed in MT1 during pursuit eye move- ments, suggesting oscillations that play a role in oculomotor control and/or the integration of extrareti- nal signals during pursuit. The amplitude of these rhythms appears to covary with head-centered eye position, but an alternative is that they depend on a velocity signal that lags the movement of the eyes. To investigate, we explored how alpha and beta amplitude changes related to ongoing eye move- ment depended on pursuit at different eccentricities. The results revealed largely identical patterns of modulation in the alpha and beta amplitude, irrespective of the eccentricity at which the pursuit eye movement was performed. The signals we measured therefore do not depend on head-centered posi- tion. A second experiment was designed to investigate whether the alpha and beta oscillations depended on the direction of pursuit, as opposed to just speed. We found no evidence that alpha or beta oscillations depended on direction, but there was a significant effect of eye speed on the magni- tude of the beta suppression. This suggests distinct functional roles for alpha and beta suppression in pursuit behavior

Atypical functional connectivity during unfamiliar music listening in children with autism

Background: Atypical processing of unfamiliar, but less so familiar, stimuli has been described in Autism Spectrum Disorder (ASD), in particular in relation to face processing. We examined the construct of familiarity in ASD using familiar and unfamiliar songs, to investigate the link between familiarity and autism symptoms, such as repetitive behavior. Methods: Forty-eight children, 24 with ASD (21 males, mean age = 9.96 years ± 1.54) and 24 typically developing (TD) controls (21 males, mean age = 10.17 ± 1.90) completed a music familiarity task using individually identified familiar compared to unfamiliar songs, while magnetoencephalography (MEG) was recorded. Each song was presented for 30 s. We used both amplitude envelope correlation (AEC) and the weighted phase lag index (wPLI) to assess functional connectivity between specific regions of interest (ROI) and non-ROI parcels, as well as at the whole brain level, to understand what is preserved and what is impaired in familiar music listening in this population. Results: Increased wPLI synchronization for familiar vs. unfamiliar music was found for typically developing children in the gamma frequency. There were no significant differences within the ASD group for this comparison. During the processing of unfamiliar music, we demonstrated left lateralized increased theta and beta band connectivity in children with ASD compared to controls. An interaction effect found greater alpha band connectivity in the TD group compared to ASD to unfamiliar music only, anchored in the left insula.Conclusion: Our results revealed atypical processing of unfamiliar songs in children with ASD, consistent with previous studies in other modalities reporting that processing novelty is a challenge for ASD. Relatively typical processing of familiar stimuli may represent a strength and may be of interest to strength-based intervention planning.info:eu-repo/semantics/publishedVersio

The Acquisition of Human B Cell Memory in Response to Plasmodium Falciparum Malaria

Immunity to Plasmodium falciparum (Pf), the most deadly agent of malaria, is only acquired after years of repeated infections and appears to wane rapidly without ongoing exposure. Antibodies (Abs) are central to malaria immunity, yet little is known about the B‐cell biology that underlies Pf‐specific humoral immunity. To address this gap in our knowledge we carried out a year‐long prospective study of the acquisition and maintenance of long‐lived plasma cells (LLPCs) and memory B cells (MBCs) in 225 individuals aged two to twenty‐five years in Mali, in an area of intense seasonal transmission. Using protein microarrays containing approximately 25% of the Pf proteome we determined that Pf‐specific Abs were acquired only gradually, in a stepwise fashion over years of Pf exposure. Pf‐specific Ab levels were significantly boosted each year during the transmission season but the majority of these Abs were short lived and were lost over the subsequent six month period of no transmission. Thus, we observed only a small incremental increase in stable Ab levels each year, presumably reflecting the slow acquisition LLPCs. The acquisition Pf‐specific MBCs mirrored the slow step‐wise acquisition of LLPCs. This slow acquisition of Pf‐specific LLPCs and MBCs was in sharp contrast to that of tetanus toxoid (TT)‐specific LLPCs and MBCs that were vi vi rapidly acquired and stably maintained following a single vaccination in individuals in this cohort. In addition to the development of normal MBCs we observed an expansion of atypical MBCs that are phenotypically similar to hyporesponsive FCRL4+ cells described in HIV‐infected individuals. Atypical MBC expansion correlated with cumulative exposure to Pf, and with persistent asymptomatic Pf‐infection in children, suggesting that the parasite may play a role in driving the expansion of atypical MBCs. Collectively, these observations provide a rare glimpse into the process of the acquisition of human B cell memory in response to infection and provide evidence for a selective deficit in the generation of Pf‐specific LLPCs and MBCs during malaria. Future studies will address the mechanisms underlying the slow acquisition of LLPCs and MBCs and the generation and function of atypical MBCs

The Atacama Cosmology Telescope: Cross Correlation with Planck maps

We present the temperature power spectrum of the Cosmic Microwave Background obtained by cross-correlating maps from the Atacama Cosmology Telescope (ACT) at 148 and 218 GHz with maps from the Planck satellite at 143 and 217 GHz, in two overlapping regions covering 592 square degrees. We find excellent agreement between the two datasets at both frequencies, quantified using the variance of the residuals between the ACT power spectra and the ACTxPlanck cross-spectra. We use these cross-correlations to calibrate the ACT data at 148 and 218 GHz, to 0.7% and 2% precision respectively. We find no evidence for anisotropy in the calibration parameter. We compare the Planck 353 GHz power spectrum with the measured amplitudes of dust and cosmic infrared background (CIB) of ACT data at 148 and 218 GHz. We also compare planet and point source measurements from the two experiments.Comment: 9 pages, 8 figure

Cosmological Constraints from the SDSS maxBCG Cluster Catalog

We use the abundance and weak lensing mass measurements of the SDSS maxBCG cluster catalog to simultaneously constrain cosmology and the richness--mass relation of the clusters. Assuming a flat \LambdaCDM cosmology, we find \sigma_8(\Omega_m/0.25)^{0.41} = 0.832\pm 0.033 after marginalization over all systematics. In common with previous studies, our error budget is dominated by systematic uncertainties, the primary two being the absolute mass scale of the weak lensing masses of the maxBCG clusters, and uncertainty in the scatter of the richness--mass relation. Our constraints are fully consistent with the WMAP five-year data, and in a joint analysis we find \sigma_8=0.807\pm 0.020 and \Omega_m=0.265\pm 0.016, an improvement of nearly a factor of two relative to WMAP5 alone. Our results are also in excellent agreement with and comparable in precision to the latest cosmological constraints from X-ray cluster abundances. The remarkable consistency among these results demonstrates that cluster abundance constraints are not only tight but also robust, and highlight the power of optically-selected cluster samples to produce precision constraints on cosmological parameters.Comment: comments welcom

High resolution CMB power spectrum from the complete ACBAR data set

In this paper, we present results from the complete set of cosmic microwave background (CMB) radiation temperature anisotropy observations made with the Arcminute Cosmology Bolometer Array Receiver (ACBAR) operating at 150 GHz. We include new data from the final 2005 observing season, expanding the number of detector-hours by 210% and the sky coverage by 490% over that used for the previous ACBAR release. As a result, the band-power uncertainties have been reduced by more than a factor of two on angular scales encompassing the third to fifth acoustic peaks as well as the damping tail of the CMB power spectrum. The calibration uncertainty has been reduced from 6% to 2.1% in temperature through a direct comparison of the CMB anisotropy measured by ACBAR with that of the dipole-calibrated WMAP5 experiment. The measured power spectrum is consistent with a spatially flat, LambdaCDM cosmological model. We include the effects of weak lensing in the power spectrum model computations and find that this significantly improves the fits of the models to the combined ACBAR+WMAP5 power spectrum. The preferred strength of the lensing is consistent with theoretical expectations. On fine angular scales, there is weak evidence (1.1 sigma) for excess power above the level expected from primary anisotropies. We expect any excess power to be dominated by the combination of emission from dusty protogalaxies and the Sunyaev-Zel'dovich effect (SZE). However, the excess observed by ACBAR is significantly smaller than the excess power at ell > 2000 reported by the CBI experiment operating at 30 GHz. Therefore, while it is unlikely that the CBI excess has a primordial origin; the combined ACBAR and CBI results are consistent with the source of the CBI excess being either the SZE or radio source contamination.Comment: Submitted to ApJ; Changed to apply a WMAP5-based calibration. The cosmological parameter estimation has been updated to include WMAP

Evidence for dark energy from the cosmic microwave background alone using the Atacama Cosmology Telescope lensing measurements

For the first time, measurements of the cosmic microwave background radiation (CMB) alone favor cosmologies with $w=-1$ dark energy over models without dark energy at a 3.2-sigma level. We demonstrate this by combining the CMB lensing deflection power spectrum from the Atacama Cosmology Telescope with temperature and polarization power spectra from the Wilkinson Microwave Anisotropy Probe. The lensing data break the geometric degeneracy of different cosmological models with similar CMB temperature power spectra. Our CMB-only measurement of the dark energy density $\Omega_\Lambda$ confirms other measurements from supernovae, galaxy clusters and baryon acoustic oscillations, and demonstrates the power of CMB lensing as a new cosmological tool.Comment: 4 pages, 3 figures; replaced with version accepted by Physical Review Letters, added sentence on models with non-standard primordial power spectr

Detection of the Power Spectrum of Cosmic Microwave Background Lensing by the Atacama Cosmology Telescope

We report the first detection of the gravitational lensing of the cosmic microwave background through a measurement of the four-point correlation function in the temperature maps made by the Atacama Cosmology Telescope. We verify our detection by calculating the levels of potential contaminants and performing a number of null tests. The resulting convergence power spectrum at 2-degree angular scales measures the amplitude of matter density fluctuations on comoving length scales of around 100 Mpc at redshifts around 0.5 to 3. The measured amplitude of the signal agrees with Lambda Cold Dark Matter cosmology predictions. Since the amplitude of the convergence power spectrum scales as the square of the amplitude of the density fluctuations, the 4-sigma detection of the lensing signal measures the amplitude of density fluctuations to 12%.Comment: 4 pages, 4 figures, replaced title and author list with version accepted by Physical Review Letters. Likelihood code can be downloaded from http://bccp.lbl.gov/~sudeep/ACTLensLike.htm