Investigating the peculiar emission from the new VHE gamma-ray source H1722+119

The MAGIC (Major Atmospheric Gamma-ray Imaging Cherenkov) telescopes observed the BL Lac object H1722+119 (redshift unknown) for six consecutive nights between 2013 May 17 and 22, for a total of 12.5 h. The observations were triggered by high activity in the optical band measured by the KVA (Kungliga Vetenskapsakademien) telescope. The source was for the first time detected in the very high energy (VHE, E > 100 GeV) γ-ray band with a statistical significance of 5.9 σ. The integral flux above 150 GeV is estimated to be (2.0 ± 0.5) per cent of the Crab Nebula flux. We used contemporaneous high energy (HE, 100MeV < E < 100 GeV) γ-ray observations from Fermi-LAT (Large Area Telescope) to estimate the redshift of the source. Within the framework of the current extragalactic background light models, we estimate the redshift to be z = 0.34±0.15. Additionally, we used contemporaneous X-ray to radio data collected by the instruments on board the Swift satellite, the KVA, and the OVRO (Owens Valley Radio Observatory) telescope to study multifrequency characteristics of the source. We found no significant temporal variability of the flux in the HE and VHE bands. The flux in the optical and radio wavebands, on the other hand, did vary with different patterns. The spectral energy distribution (SED) of H1722+119 shows surprising behaviour in the ∼ 3×1014 −1018 Hz frequency range. It can be modelled using an inhomogeneous helical jet synchrotron self-Compton model.

Test-Retest Reliability of Resting-State Magnetoencephalography Power in Sensor and Source Space

Several studies have reported changes in spontaneous brain rhythms that could be used asclinical biomarkers or in the evaluation of neuropsychological and drug treatments in longitudinal studies using magnetoencephalography (MEG). There is an increasing necessity to use these measures in early diagnosis and pathology progression; however, there is a lack of studies addressing how reliable they are. Here, we provide the first test-retest reliability estimate of MEG power in resting-state at sensor and source space. In this study, we recorded 3 sessions of resting-state MEG activity from 24 healthy subjects with an interval of a week between each session. Power values were estimated at sensor and source space with beamforming for classical frequency bands: delta (2–4 Hz), theta (4–8 Hz), alpha (8–13 Hz), low beta (13–20 Hz), high beta (20–30 Hz), and gamma (30–45 Hz). Then, test-retest reliability was evaluated using the intraclass correlation coefficient (ICC). We also evaluated the relation between source power and the within-subject variability. In general, ICC of theta, alpha, and low beta power was fairly high (ICC > 0.6) while in delta and gamma power was lower. In source space, fronto-posterior alpha, frontal beta, and medial temporal theta showed the most reliable profiles. Signal-to-noise ratio could be partially responsible for reliability as low signal intensity resulted inhigh within-subject variability, but also the inherent nature of some brain rhythms in resting-state might be driving these reliability patterns. In conclusion, our results described the reliability of MEG power estimates in each frequency band, which could be considered in disease characterization or clinical trials.

Fitting model-based psychometric functions to simultaneity and temporal-order judgment data: MATLAB and R routines

Research on temporal-order perception uses temporal-order judgment (TOJ) tasks or synchrony judgment (SJ) tasks in their binary SJ2 or ternary SJ3 variants. In all cases, two stimuli are presented with some temporal delay, and observers judge the order of presentation. Arbitrary psychometric functions are typically fitted to obtain performance measures such as sensitivity or the point of subjective simultaneity, but the parameters of these functions are uninterpretable. We describe routines in MATLAB and R that fit model-based functions whose parameters are interpretable in terms of the processes underlying temporal-order and simultaneity judgments and responses. These functions arise from an independent-channels model assuming arrival latencies with exponential distributions and a trichotomous decision space. Different routines fit data separately for SJ2, SJ3, and TOJ tasks, jointly for any two tasks, or also jointly for the three tasks (for common cases in which two or even the three tasks were used with the same stimuli and participants). Additional routines provide bootstrap p-values and confidence intervals for estimated parameters. A further routine is included that obtains performance measures from the fitted functions. An R package for Windows and source code of the MATLAB and R routines are available as Supplementary Files.