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Background and ObjectivesTask fMRI is a clinical tool for language lateralization, but has limitations, and cannot provide information about network-level plasticity. Additional methods are needed to improve the precision of presurgical language mapping. We investigate language resting-state functional connectivity (RS fMRI; FC) in typically developing children (TD) and children with epilepsy. Our objectives were to (1) understand how FC components differ between TD children and those with epilepsy; (2) elucidate how the location of disease (frontal/temporal epilepsy foci) affects FC; and (3) investigate the relationship between age and FC.MethodsOur sample included 55 TD children (mean age 12 years, range 7–18) and 31 patients with focal epilepsy (mean age 13 years, range 7–18). All participants underwent RS fMRI. Using a bilateral canonical language map as target, vertex-wise intrahemispheric FC map and interhemispheric FC map for each participant were computed and thresholded at top 10% to compute an FC laterality index (FCLI; [(L – R)/(L + R)]) of the frontal and temporal regions for both integration (intrahemispheric FC; FCLIi) and segregation (interhemispheric FC; FCLIs) maps.ResultsWe found FC differences in the developing language network based on disease, seizure foci location, and age. Frontal and temporal FCLIi was different between groups (t[84] = 2.82, p < 0.01; t[84] = 4.68, p < 0.01, respectively). Frontal epilepsy foci had the largest differences from TD (Cohen d frontal FCLIi = 0.84, FCLIs = 0.51; temporal FCLIi = 1.29). Development and disease have opposing influences on the laterality of FC based on groups. In the frontal foci group, FCLIi decreased with age (r = −0.42), whereas in the temporal foci group, FCLIi increased with age (r = 0.40). Within the epilepsy group, increases in right frontal integration FCLI relates to increased right frontal task activation in our mostly left language dominant group (r = 0.52, p < 0.01). Language network connectivity is associated with higher verbal intelligence in children with epilepsy (r = 0.45, p < 0.05).DiscussionThese findings lend preliminary evidence that FC reflects network plasticity in the form of adaptation and compensation, or the ability to recruit support and reallocate resources within and outside of the traditional network to compensate for disease. FC expands on task-based fMRI and provides complementary and potentially useful information about the language network that is not captured using task-based fMRI alone.

The improved use of Electronic Health Record (EHR) Systems provides an opportunity to improve the overall efficiency and quality of care of patients with epilepsy. Tools and strategies that may be incorporated into the use of EHRs include utilizing patient generated data, clinical decision support systems and natural language processing systems. Standardization of data from EHR systems may lead to improvement in clinical research through the creation of data collections and multi-center collaborations. Challenges to collaborative use of EHR Systems across centers include costs and the diversity of EHR systems.

Two hypotheses of autism spectrum disorder (ASD) propose that this condition is characterized by deficits in Theory of Mind and by hypoconnectivity between remote cortical regions with hyperconnectivity locally. The default mode network (DMN) is a set of remote, functionally connected cortical nodes less active during executive tasks than at rest and is implicated in Theory of Mind, episodic memory, and other self-reflective processes. We show that children with ASD have reduced connectivity between DMN nodes and increased local connectivity within DMN nodes and the visual and motor resting-state networks. We show that, like the trajectory of synaptogenesis, internodal DMN functional connectivity increased as a quadratic function of age in typically developing children, peaking between, 11 and 13 years. In children with ASD, these long-distance connections fail to develop during adolescence. These findings support the “developmental disconnection model” of ASD, provide a possible mechanistic explanation for the Theory-of-Mind hypothesis of ASD, and show that the window for effectively treating ASD could be wider than previously thought.

Novel deception detection techniques have been in creation for centuries. Functional magnetic resonance imaging (fMRI) is a neuroscience technology that non-invasively measures brain activity associated with behavior and cognition. A number of investigators have explored the utilization and efficiency of fMRI in deception detection. In this study, 18 subjects were instructed during an fMRI "line-up" task to either conceal (lie) or reveal (truth) the identities of individuals seen in study sets in order to determine the neural correlates of intentionally misidentifying previously known faces (lying about recognition). A repeated measures ANOVA (lie vs. truth and familiar vs. unfamiliar) and two paired t-tests (familiar vs. unfamiliar and familiar lie vs. familiar truth) revealed areas of activation associated with deception in the right MGF, red nucleus, IFG, SMG, SFG (with ACC), DLPFC, and bilateral precuneus. The areas activated in the present study may be involved in the suppression of truth, working and visuospatial memories, and imagery when providing misleading (deceptive) responses to facial identification prompts in the form of a "line-up".

Neural networks for processing language often are reorganized in patients with epilepsy. However, the extent and location of within and between hemisphere re-organization are not established. We studied 45 patients, all with a left hemisphere seizure focus (mean age 22.8, seizure onset 13.3), and 19 normal controls (mean age 24.8) with an fMRI word definition language paradigm to assess the location of language processing regions. Individual patient SPM maps were compared to the normal group in a voxel-wise comparison; a voxel was considered to be significant if its z-value exceeded mid R:2mid R:. Subsequently, we used principal component analysis with hierarchical clustering of variance patterns from individual difference maps to identify four patient sub-groups. One did not differ from normal controls; one had increased left temporal activation on the margin of regions activated in controls; two others had recruitment in right inferior frontal gyrus, middle frontal gyrus and temporal cortex. Right hemisphere activation in these two groups occurred in homologues of left hemisphere regions that sustained task activation. Our study used novel data driven methods to find evidence for constraints on inter-hemispheric reorganization of language in recruitment of right homologues, and, in a subpopulation of patients, evidence for intra-hemispheric reorganization of language limited to the margins of typical left temporal regional activation. These methods may be applied to investigate both normal and pathological variance in other developmental disorders and cognitive domains.