Self-similar correlation function in brain resting-state fMRI

Adaptive behavior, cognition and emotion are the result of a bewildering variety of brain spatiotemporal activity patterns. An important problem in neuroscience is to understand the mechanism by which the human brain's 100 billion neurons and 100 trillion synapses manage to produce this large repertoire of cortical configurations in a flexible manner. In addition, it is recognized that temporal correlations across such configurations cannot be arbitrary, but they need to meet two conflicting demands: while diverse cortical areas should remain functionally segregated from each other, they must still perform as a collective, i.e., they are functionally integrated. Here, we investigate these large-scale dynamical properties by inspecting the character of the spatiotemporal correlations of brain resting-state activity. In physical systems, these correlations in space and time are captured by measuring the correlation coefficient between a signal recorded at two different points in space at two different times. We show that this two-point correlation function extracted from resting-state fMRI data exhibits self-similarity in space and time. In space, self-similarity is revealed by considering three successive spatial coarse-graining steps while in time it is revealed by the 1/f frequency behavior of the power spectrum. The uncovered dynamical self-similarity implies that the brain is spontaneously at a continuously changing (in space and time) intermediate state between two extremes, one of excessive cortical integration and the other of complete segregation. This dynamical property may be seen as an important marker of brain well-being both in health and disease.Comment: 14 pages 13 figures; published online before print September 2

Understanding inner music: A dimensional approach to musical imagery

Musical imagery—hearing music inside your head that isn’t playing in the environment—is a common yet complex experience. To capture the diversity of musical imagery, the present research develops a new conceptual framework consisting of five dimensions, including a distinction between initiation and management as different ways in which musical imagery can be voluntary. A dimensional approach can represent both common and unusual forms of musical imagery, and it can highlight conceptual similarities between seemingly different experiences. In an experience-sampling study, musicians and people from the university community (n = 132) were contacted throughout the day via a smartphone app and asked about their in vivo experiences with musical imagery, with an emphasis on five dimensions: valence, repetitiveness, vividness, length, and mental control. The results indicated substantial variability at both the within-person and between-person levels on each dimension—people have a wide variety of musical imagery experiences, not a few types. A within-person network model illustrated that the dimensions were internally coherent and distinct from each other. Taken together, the findings reveal rich heterogeneity in musical imagery and indicate that mental control over musical imagery is both common and multifaceted

Network structure of the Wisconsin Schizotypy Scales—Short Forms: Examining psychometric filtering approaches

Schizotypy is a multidimensional construct that provides a useful framework for understanding the etiology, development, and risk for schizophrenia-spectrum disorders. Past research has applied traditional methods, such as factor analysis, to uncovering common dimensions of schizotypy. In the present study, we aimed to advance the construct of schizotypy, measured by the Wisconsin Schizotypy Scales–Short Forms (WSS-SF), beyond this general scope by applying two different psychometric network filtering approaches—the state-of-the-art approach (lasso), which has been employed in previous studies, and an alternative approach (information-filtering networks; IFNs). First, we applied both filtering approaches to two large, independent samples of WSS-SF data (ns = 5,831 and 2,171) and assessed each approach’s representation of the WSS-SF’s schizotypy construct. Both filtering approaches produced results similar to those from traditional methods, with the IFN approach producing results more consistent with previous theoretical interpretations of schizotypy. Then we evaluated how well both filtering approaches reproduced the global and local network characteristics of the two samples. We found that the IFN approach produced more consistent results for both global and local network characteristics. Finally, we sought to evaluate the predictability of the network centrality measures for each filtering approach, by determining the core, intermediate, and peripheral items on the WSS-SF and using them to predict interview reports of schizophrenia-spectrum symptoms. We found some similarities and differences in their effectiveness, with the IFN approach’s network structure providing better overall predictive distinctions. We discuss the implications of our findings for schizotypy and for psychometric network analysis more generally

Creative fixation is no laughing matter: The effects of funny and unfunny examples on humor production

How do people come up with humorous ideas? In creative cognition research, exposure to good examples sometimes causes fixation (people get “stuck” on the examples) but other times sparks inspiration (people's responses are more creative). The present research examined the effects of funny and unfunny examples on joke production. A sample of 175 adults read scenarios that they completed with funny responses. All participants were instructed to be funny, but before responding they read (a) funny responses as examples of good responses to emulate, (b) unfunny responses as examples of poor responses to avoid, or (c) no examples. The participants’ own responses were rated for funniness and for similarity to the example responses, and response times were recorded. Reading either funny or unfunny examples, compared to no examples, caused people to come up with funnier jokes. Similarity to the examples was low in all conditions, so fixation was relatively modest, but people who saw unfunny examples spent more time coming up with their responses. Taken together, the findings support the growing literature showing that examples are often inspiring rather than constraining, and they imply that good and bad examples spark creative thought via different paths

Characterization of E2F8, a novel E2F-like cell-cycle regulated repressor of E2F-activated transcription

The E2F family of transcription factors are downstream effectors of the retinoblastoma protein, pRB, pathway and are essential for the timely regulation of genes necessary for cell-cycle progression. Here we describe the characterization of human and murine E2F8, a new member of the E2F family. Sequence analysis of E2F8 predicts the presence of two distinct E2F-related DNA binding domains suggesting that E2F8 and, the recently, identified E2F7 form a subgroup within the E2F family. We show that E2F transcription factors bind the E2F8 promoter in vivo and that expression of E2F8 is being induced at the G1/S transition. Purified recombinant E2F8 binds specifically to a consensus E2F-DNA-binding site indicating that E2F8, like E2F7, binds DNA without the requirement of co-factors such as DP1. E2F8 inhibits E2F-driven promoters suggesting that E2F8 is transcriptional repressor like E2F7. Ectopic expression of E2F8 in diploid human fibroblasts reduces expression of E2F-target genes and inhibits cell growth consistent with a role for repressing E2F transcriptional activity. Taken together, these data suggest that E2F8 has an important role in turning of the expression of E2F-target genes in the S-phase of the cell cycle

Robust prediction of individual creative ability from brain functional connectivity

People’s ability to think creatively is a primary means of technological and cultural progress, yet the neural architecture of the highly creative brain remains largely undefined. Here, we employed a recently developed method in functional brain imaging analysis—connectome-based predictive modeling—to identify a brain network associated with high-creative ability, using functional magnetic resonance imaging (fMRI) data acquired from 163 participants engaged in a classic divergent thinking task. At the behavioral level, we found a strong correlation between creative thinking ability and self-reported creative behavior and accomplishment in the arts and sciences (r = 0.54). At the neural level, we found a pattern of functional brain connectivity related to high-creative thinking ability consisting of frontal and parietal regions within default, salience, and executive brain systems. In a leave-one-out cross-validation analysis, we show that this neural model can reliably predict the creative quality of ideas generated by novel participants within the sample. Furthermore, in a series of external validation analyses using data from two independent task fMRI samples and a large task-free resting-state fMRI sample, we demonstrate robust prediction of individual creative thinking ability from the same pattern of brain connectivity. The findings thus reveal a whole-brain network associated with high-creative ability comprised of cortical hubs within default, salience, and executive systems—intrinsic functional networks that tend to work in opposition—suggesting that highly creative people are characterized by the ability to simultaneously engage these large-scale brain networks

Thermal divergences on the event horizons of two-dimensional black holes

The expectation value of the stress-energy tensor \langleT_{\mu\nu}\rangle of a free conformally invariant scalar field is computed in a general static two-dimensional black hole spacetime when the field is in either a zero temperature vacuum state or a thermal state at a nonzero temperature. It is found that for every static two-dimensional black hole the stress-energy diverges strongly on the event horizon unless the field is in a state at the natural black hole temperature which is defined by the surface gravity of the event horizon. This implies that both extreme and nonextreme two-dimensional black holes can only be in equilibrium with radiation at the natural black hole temperature.Comment: 13 pages, REVTe

Solar-like oscillations in the G2 subgiant beta Hydri from dual-site observations

We have observed oscillations in the nearby G2 subgiant star beta Hyi using high-precision velocity observations obtained over more than a week with the HARPS and UCLES spectrographs. The oscillation frequencies show a regular comb structure, as expected for solar-like oscillations, but with several l=1 modes being strongly affected by avoided crossings. The data, combined with those we obtained five years earlier, allow us to identify 28 oscillation modes. By scaling the large frequency separation from the Sun, we measure the mean density of beta Hyi to an accuracy of 0.6%. The amplitudes of the oscillations are about 2.5 times solar and the mode lifetime is 2.3 d. A detailed comparison of the mixed l=1 modes with theoretical models should allow a precise estimate of the age of the star.Comment: 13 pages, 14 figures, accepted by ApJ. Fixed minor typo (ref to Fig 14

Semiclassical effects in black hole interiors

First-order semiclassical perturbations to the Schwarzschild black hole geometry are studied within the black hole interior. The source of the perturbations is taken to be the vacuum stress-energy of quantized scalar, spinor, and vector fields, evaluated using analytic approximations developed by Page and others (for massless fields) and the DeWitt-Schwinger approximation (for massive fields). Viewing the interior as an anisotropic collapsing cosmology, we find that minimally or conformally coupled scalar fields, and spinor fields, decrease the anisotropy as the singularity is approached, while vector fields increase the anisotropy. In addition, we find that massless fields of all spins, and massive vector fields, strengthen the singularity, while massive scalar and spinor fields tend to slow the growth of curvature.Comment: 29 pages, ReVTeX; 4 ps figure

General practice cooperatives: long waiting times for home visits due to long distances?

BACKGROUND: The introduction of large-scale out-of-hours GP cooperatives has led to questions about increased distances between the GP cooperatives and the homes of patients and the increasing waiting times for home visits in urgent cases. We studied the relationship between the patient's waiting time for a home visit and the distance to the GP cooperative. Further, we investigated if other factors (traffic intensity, home visit intensity, time of day, and degree of urgency) influenced waiting times. METHODS: Cross-sectional study at four GP cooperatives. We used variance analysis to calculate waiting times for various categories of traffic intensity, home visit intensity, time of day, and degree of urgency. We used multiple logistic regression analysis to calculate to what degree these factors affected the ability to meet targets in urgent cases. RESULTS: The average waiting time for 5827 consultations was 30.5 min. Traffic intensity, home visit intensity, time of day and urgency of the complaint all seemed to affect waiting times significantly. A total of 88.7% of all patients were seen within 1 hour. In the case of life-threatening complaints (U1), 68.8% of the patients were seen within 15 min, and 95.6% of those with acute complaints (U2) were seen within 1 hour. For patients with life-threatening complaints (U1) the percentage of visits that met the time target of 15 minuts decreased from 86.5% (less than 2.5 km) to 16.7% (equals or more than 20 km). DISCUSSION AND CONCLUSION: Although home visits waiting times increase with increasing distance from the GP cooperative, it appears that traffic intensity, home visit intensity, and urgency also influence waiting times. For patients with life-threatening complaints waiting times increase sharply with the distance