Brain hubs defined in the group do not overlap with regions of high inter-individual variability

Connector \u27hubs\u27 are brain regions with links to multiple networks. These regions are hypothesized to play a critical role in brain function. While hubs are often identified based on group-average functional magnetic resonance imaging (fMRI) data, there is considerable inter-subject variation in the functional connectivity profiles of the brain, especially in association regions where hubs tend to be located. Here we investigated how group hubs are related to locations of inter-individual variability. To answer this question, we examined inter-individual variation at group-level hubs in both the Midnight Scan Club and Human Connectome Project datasets. The top group hubs defined based on the participation coefficient did not overlap strongly with the most prominent regions of inter-individual variation (termed \u27variants\u27 in prior work). These hubs have relatively strong similarity across participants and consistent cross-network profiles, similar to what was seen for many other areas of cortex. Consistency across participants was further improved when these hubs were allowed to shift slightly in local position. Thus, our results demonstrate that the top group hubs defined with the participation coefficient are generally consistent across people, suggesting they may represent conserved cross-network bridges. More caution is warranted with alternative hub measures, such as community density (which are based on spatial proximity to network borders) and intermediate hub regions which show higher correspondence to locations of individual variability

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

Cholinergic, but not dopaminergic or noradrenergic, enhancement sharpens visual spatial perception in humans

The neuromodulator acetylcholine modulates spatial integration in visual cortex by altering the balance of inputs that generate neuronal receptive fields. These cholinergic effects may provide a neurobiological mechanism underlying the modulation of visual representations by visual spatial attention. However, the consequences of cholinergic enhancement on visuospatial perception in humans are unknown. We conducted two experiments to test whether enhancing cholinergic signaling selectively alters perceptual measures of visuospatial interactions in human subjects. In Experiment 1, a double-blind placebo-controlled pharmacology study, we measured how flanking distractors influenced detection of a small contrast decrement of a peripheral target, as a function of target-flanker distance. We found that cholinergic enhancement with the cholinesterase inhibitor donepezil improved target detection, and modeling suggested that this was mainly due to a narrowing of the extent of facilitatory perceptual spatial interactions. In Experiment 2, we tested whether these effects were selective to the cholinergic system or would also be observed following enhancements of related neuromodulators dopamine or norepinephrine. Unlike cholinergic enhancement, dopamine (bromocriptine) and norepinephrine (guanfacine) manipulations did not improve performance or systematically alter the spatial profile of perceptual interactions between targets and distractors. These findings reveal mechanisms by which cholinergic signaling influences visual spatial interactions in perception and improves processing of a visual target among distractors, effects that are notably similar to those of spatial selective attention

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

The GAPS Project: First Results

The GAPS programme is an Italian project aiming to search and characterize extra-solar planetary systems around stars with different characteristics (mass, metallicity, environment). GAPS was born in 2012, when single research groups joined in order to propose a long-term multi-purpose observing program for the exploitation of the extraordinary performances of the HARPS-N spectrograph, mounted at the Telescopio Nazionale Galileo. Now this group is a concerted community in which wide range of expertise and capabilities are shared in order to reach a more important role in the wider international context. We present the results achieved up to now from the GAPS radial velocity survey: they were obtained in both the two main objectives of the project, the planet detection and the characterization of already known exoplanetary systems. With GAPS we detected, for instance, the first confirmed binary system in which both components host planets (Desidera et al. 2014), the first planetary system around a star in an open cluster (Malavolta et al. 2016), a system of Super-Earths orbiting an M-dwarf star (Affer et al. 2016)