From correlation to communication: Disentangling hidden factors from functional connectivity changes

AbstractWhile correlations in the BOLD fMRI signal are widely used to capture functional connectivity (FC) and its changes across contexts, its interpretation is often ambiguous. The entanglement of multiple factors including local coupling of two neighbors and nonlocal inputs from the rest of the network (affecting one or both regions) limits the scope of the conclusions that can be drawn from correlation measures alone. Here we present a method of estimating the contribution of nonlocal network input to FC changes across different contexts. To disentangle the effect of task-induced coupling change from the network input change, we propose a new metric, “communication change,” utilizing BOLD signal correlation and variance. With a combination of simulation and empirical analysis, we demonstrate that (1) input from the rest of the network accounts for a moderate but significant amount of task-induced FC change and (2) the proposed “communication change” is a promising candidate for tracking the local coupling in task context-induced change. Additionally, when compared to FC change across three different tasks, communication change can better discriminate specific task types. Taken together, this novel index of local coupling may have many applications in improving our understanding of local and widespread interactions across large-scale functional networks

Specialized late cingulo-opercular network activation elucidates the mechanisms underlying decisions about ambiguity

Cortical task control networks, including the cingulo-opercular (CO) network play a key role in decision-making across a variety of functional domains. In particular, the CO network functions in a performance reporting capacity that supports successful task performance, especially in response to errors and ambiguity. In two studies testing the contribution of the CO network to ambiguity processing, we presented a valence bias task in which masked clearly and ambiguously valenced emotional expressions were slowly revealed over several seconds. This slow reveal task design provides a window into the decision-making mechanisms as they unfold over the course of a trial. In the main study, the slow reveal task was administered to 32 young adults in the fMRI environment and BOLD time courses were extracted from regions of interest in three control networks. In a follow-up study, the task was administered to a larger, online sample (n = 81) using a more extended slow reveal design with additional unmasking frames. Positive judgments of surprised faces were uniquely accompanied by slower response times and strong, late activation in the CO network. These results support the initial negativity hypothesis, which posits that the default response to ambiguity is negative and positive judgments are associated with a more effortful controlled process, and additionally suggest that this controlled process is mediated by the CO network. Moreover, ambiguous trials were characterized by a second CO response at the end of the trial, firmly placing CO function late in the decision-making process

The community structure of functional brain networks exhibits scale-specific patterns of inter- and intra-subject variability

The network organization of the human brain varies across individuals, changes with development and aging, and differs in disease. Discovering the major dimensions along which this variability is displayed remains a central goal of both neuroscience and clinical medicine. Such efforts can be usefully framed within the context of the brain\u27s modular network organization, which can be assessed quantitatively using computational techniques and extended for the purposes of multi-scale analysis, dimensionality reduction, and biomarker generation. Although the concept of modularity and its utility in describing brain network organization is clear, principled methods for comparing multi-scale communities across individuals and time are surprisingly lacking. Here, we present a method that uses multi-layer networks to simultaneously discover the modular structure of many subjects at once. This method builds upon the well-known multi-layer modularity maximization technique, and provides a viable and principled tool for studying differences in network communities across individuals and within individuals across time. We test this method on two datasets and identify consistent patterns of inter-subject community variability, demonstrating that this variability - which would be undetectable using past approaches - is associated with measures of cognitive performance. In general, the multi-layer, multi-subject framework proposed here represents an advance over current approaches by straighforwardly mapping community assignments across subjects and holds promise for future investigations of inter-subject community variation in clinical populations or as a result of task constraints

BOLD cofluctuation \u27events\u27 are predicted from static functional connectivity

Recent work identified single time points ( events ) of high regional cofluctuation in functional Magnetic Resonance Imaging (fMRI) which contain more large-scale brain network information than other, low cofluctuation time points. This suggested that events might be a discrete, temporally sparse signal which drives functional connectivity (FC) over the timeseries. However, a different, not yet explored possibility is that network information differences between time points are driven by sampling variability on a constant, static, noisy signal. Using a combination of real and simulated data, we examined the relationship between cofluctuation and network structure and asked if this relationship was unique, or if it could arise from sampling variability alone. First, we show that events are not discrete - there is a gradually increasing relationship between network structure and cofluctuation; ∼50% of samples show very strong network structure. Second, using simulations we show that this relationship is predicted from sampling variability on static FC. Finally, we show that randomly selected points can capture network structure about as well as events, largely because of their temporal spacing. Together, these results suggest that, while events exhibit particularly strong representations of static FC, there is little evidence that events are unique timepoints that drive FC structure. Instead, a parsimonious explanation for the data is that events arise from a single static, but noisy, FC structure

Parallel hippocampal-parietal circuits for self- and goal-oriented processing

The hippocampus is critically important for a diverse range of cognitive processes, such as episodic memory, prospective memory, affective processing, and spatial navigation. Using individual-specific precision functional mapping of resting-state functional MRI data, we found the anterior hippocampus (head and body) to be preferentially functionally connected to the default mode network (DMN), as expected. The hippocampal tail, however, was strongly preferentially functionally connected to the parietal memory network (PMN), which supports goal-oriented cognition and stimulus recognition. This anterior-posterior dichotomy of resting-state functional connectivity was well-matched by differences in task deactivations and anatomical segmentations of the hippocampus. Task deactivations were localized to the hippocampal head and body (DMN), relatively sparing the tail (PMN). The functional dichotomization of the hippocampus into anterior DMN-connected and posterior PMN-connected parcels suggests parallel but distinct circuits between the hippocampus and medial parietal cortex for self- versus goal-oriented processing

Global Architecture of Planetary Systems (GAPS), a project for the whole Italian Community

The GAPS project is running since 2012 with the goal to optimize the science return of the HARPS-N instrument mounted at Telescopio Nazionale Galileo. A large number of astronomers is working together to allow the Italian community to gain an international position adequate to the HARPS-N capabilities in the exoplanetary researches. Relevant scientific results are being obtained on both the main guidelines of the collaboration, i.e., the discovery surveys and the characterization studies. The planetary system discovered around the southern component of the binary XO-2 and its characterization together with that of the system orbiting the northern component are a good example of the completeness of the topics matched by the GAPS project. The dynamics of some planetary systems are investigated by studying the Rossiter-McLaughlin effect, while host stars are characterized by means of asteroseismology and star-planet interaction

VizieR Online Data Catalog: Code to compute spectral line profile indicators (Lanza+, 2018)

A computer code (procedure) written in Interactive Data Language (IDL) to compute the spectral line profile indicators used in the above research article starting from the fits files provided by the data reduction software (DRS) of HARPS or HARPS-N. The procedure takes the cross-correlation function (CCF) files provided by the DRS as an input. An example for the input files and the corresponding output file is provided with the sole purpose of allowing to test the proper compilation and running of the procedure. Details on an auxiliary source file (mpfit.pro) required for compilation are provided in the header of the procedure file and in Appendix A of the above mentioned article. Interested users are warmly recommended to read them before compiling and running the procedure. (Notes: 4 data files)

The GAPS Programme with HARPS-N at TNG . XIV. Investigating giant planet migration history via improved eccentricity and mass determination for 231 transiting planets

We carried out a Bayesian homogeneous determination of the orbital parameters of 231 transiting giant planets (TGPs) that are alone or have distant companions; we employed differential evolution Markov chain Monte Carlo methods to analyse radial-velocity (RV) data from the literature and 782 new high-accuracy RVs obtained with the HARPS-N spectrograph for 45 systems over 3 years. Our work yields the largest sample of systems with a transiting giant exoplanet and coherently determined orbital, planetary, and stellar parameters. We found that the orbital parameters of TGPs in non-compact planetary systems are clearly shaped by tides raised by their host stars. Indeed, the most eccentric planets have relatively large orbital separations and/or high mass ratios, as expected from the equilibrium tide theory. This feature would be the outcome of planetary migration from highly eccentric orbits excited by planet-planet scattering, Kozai-Lidov perturbations, or secular chaos. The distribution of α = a/aR, where a and aR are the semi-major axis and the Roche limit, for well-determined circular orbits peaks at 2.5; this agrees with expectations from the high-eccentricity migration (HEM), although it might not be limited to this migration scenario. The few planets of our sample with circular orbits and α> 5 values may have migrated through disc-planet interactions instead of HEM. By comparing circularisation times with stellar ages, we found that hot Jupiters with a5 ≲ Q'p ≲ 109, and that stellar Q's ≳ 106 - 107 are required to explain the presence of eccentric planets at the same orbital distance. As aby-product of our analysis, we detected a non-zero eccentricity e = 0.104-0.018+0.021 for HAT-P-29; we determined that five planets that were previously regarded to be eccentric or to have hints of non-zero eccentricity, namely CoRoT-2b, CoRoT-23b, TrES-3b, HAT-P-23b, and WASP-54b, have circular orbits or undetermined eccentricities; we unveiled curvatures caused by distant companions in the RV time series of HAT-P-2, HAT-P-22, and HAT-P-29; we significantly improved the orbital parameters of the long-period planet HAT-P-17c; and we revised the planetary parameters of CoRoT-1b, which turned out to be considerably more inflated than previously found. Full Tables 1, 2, 5-9 are only available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (http://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/602/A10