Brain network connectivity differs across individuals. For example, older adults exhibit less segregated resting-state subnetworks relative to younger adults (Chan et al., 2014). It has been hypothesized that individual differences in network connectivity impact the recruitment of brain areas during task execution. While recent studies have described the spatial overlap between resting-state functional correlation (RSFC) subnetworks and task-evoked activity, it is unclear whether individual variations in the connectivity pattern of a brain area (topology) relates to its activity during task execution. We report data from 238 cognitively normal participants (humans), sampled across the adult life span (20–89 years), to reveal that RSFC-based network organization systematically relates to the recruitment of brain areas across two functionally distinct tasks (visual and semantic). The functional activity of brain areas (network nodes) were characterized according to their patterns of RSFC: nodes with relatively greater connections to nodes in their own functional system (“non-connector” nodes) exhibited greater activity than nodes with relatively greater connections to nodes in other systems (“connector” nodes). This “activation selectivity” was specific to those brain systems that were central to each of the tasks. Increasing age was accompanied by less differentiated network topology and a corresponding reduction in activation selectivity (or differentiation) across relevant network nodes. The results provide evidence that connectional topology of brain areas quantified at rest relates to the functional activity of those areas during task. Based on these findings, we propose a novel network-based theory for previous reports of the “dedifferentiation” in brain activity observed in aging.SIGNIFICANCE STATEMENT Similar to other real-world networks, the organization of brain networks impacts their function. As brain network connectivity patterns differ across individuals, we hypothesized that individual differences in network connectivity would relate to differences in brain activity. Using functional MRI in a group of individuals sampled across the adult life span (20–89 years), we measured correlations at rest and related the functional connectivity patterns to measurements of functional activity during two independent tasks. Brain activity varied in relation to connectivity patterns revealed by large-scale network analysis. This relationship tracked the differences in connectivity patterns accompanied by older age, providing important evidence for a link between the topology of areal connectivity measured at rest and the functional recruitment of these areas during task performance.

The functional neuroimaging literature has become increasingly complex and thus difficult to navigate. This complexity arises from the rate at which new studies are published and from the terminology that varies widely from study-to-study and even more so from discipline-to-discipline. One way to investigate and manage this problem is to build a "semantic space" that maps the different vocabulary used in functional neuroimaging literature. Such a semantic space will also help identify the primary research domains of neuroimaging and their most commonly reported brain regions. In this work, we analyzed the multivariate semantic structure of abstracts in Neurosynth and found that there are six primary domains of the functional neuroimaging literature each with their own preferred reported brain regions.Our analyses also highlight possible semantic sources of reported brain regions within and across domains because some research topics (e.g., memory disorders, substance use disorder) use heterogeneous terminology. Furthermore, we highlight the growth and decline of the primary domains over time. Finally, we note that our techniques and results form the basis of a "recommendation engine" that could help readers better navigate the neuroimaging literature.Latent Semantic Space of Neurosynth BEATON, D. 4 IntroductionBecause terminology varies widely from study-to-study, and even more so from discipline-to-discipline, the neuroimaging literature is particularly difficult to synthesize. For example: (1) terminology changes over time (e.g., alcoholism to alcohol use disorders), (2) a single term can have many-or even amorphous-definitions (e.g., MVPA as multi-voxel or multivariate pattern analysis, which itself spans numerous different techniques), and (3) multiple terms describe the same concept (e.g., in vision studies "striate cortex," "calcarine sulcus," "V1," "primary visual cortex," and "Brodmann area 17," all describe, essentially, the same brain region in functional neuroimaging). Such a diversity of terminologies makes interpretations, and even reviews, of the literature difficult to perform and consume.To help navigate and consume results from the literature, several meta-analytic approaches (that link reported brain activations with keywords and topics) have been developed, such as coordinate-based meta-analysis (CBMA). CBMA was specifically developed for aggregating and synthesizing neuroimaging data reported in a standard format (P. T. Fox et al. 2014). Some of the most prominent CBMA tools used in research are BrainMap (Laird et al. 2005), SumsDB (Van Essen et al. 2009), Brede (Nielsen 2003) and NeuroSynth (Yarkoni et al. 2011)-the database of interest in this paper. The main functionalities of many CBMA tools are to (a) store coordinate information by study, and (b) provide spatially consistent meta-analytic activation maps. For example, Nielsen and colleagues (Nielsen et al.2004) analyzed 121 neuroimaging papers with 2,655 reported activations loci using probability models followed by a non-negative matrix...

The functional neuroimaging literature has become increasingly complex and thus difficult to navigate. This complexity arises from the rate at which new studies are published and from the terminology that varies widely from study-to-study and even more so from discipline-to-discipline. One way to investigate and manage this problem is to build a "semantic space" that maps the different vocabulary used in functional neuroimaging literature. Such a semantic space will also help identify the primary research domains of neuroimaging and their most commonly reported brain regions. In this work, we analyzed the multivariate semantic structure of abstracts in Neurosynth and found that there are six primary domains of the functional neuroimaging literature, each with their own preferred reported brain regions. Our analyses also highlight possible semantic sources of reported brain regions within and across domains because some research topics (e.g., memory disorders, substance use disorder) use heterogeneous terminology. Furthermore, we highlight the growth and decline of the primary domains over time. Finally, we note that our techniques and results form the basis of a "recommendation engine" that could help readers better navigate the neuroimaging literature.

Background: Single-unit recording in Pavlovian conditioning tasks requires the use of within-subject designs as well as sampling a considerable number of trials per trial type and session, which increases the total trial count. Pavlovian conditioning, on the other hand, requires a long average intertrial interval (ITI) relative to cue duration for cue-specific learning to occur. These requirements combined can make the session duration unfeasibly long. New method: To circumvent this issue, we developed a self-initiated variant of the Pavlovian magazine-approach procedure in rodents. Unlike the standard procedure, where the animals passively receive the trials, the selfinitiated procedure grants animals agency to self-administer and self-pace trials from a predetermined, pseudorandomized list. Critically, whereas in the standard procedure the typical ITI is in the order of minutes, our procedure uses a much shorter ITI (10 s).Results: Despite such a short ITI, discrimination learning in the self-initiated procedure is comparable to that observed in the standard procedure with a typical ITI, and superior to that observed in the standard procedure with an equally short ITI. Comparison with existing method(s): The self-initiated procedure permits delivering 100 trials in a ∼1-h session, almost doubling the number of trials safely attainable over that period with the standard procedure. Conclusions: The self-initiated procedure enhances the collection of neural correlates of cue-reward learning while producing good discrimination performance. Other advantages for neural recording studies include ensuring that at the start of each trial the animal is engaged, attentive and in the same location within the conditioning chamber.