Transcutaneous vagus nerve stimulation (tVNS) is a promising potential intervention for Alzheimer's disease (AD) due to its influence on brain functions and mechanisms important in disease progression. Regions of interest include projection to the nucleus of the solitary tract, locus coeruleus, and hippocampus. Deterioration of the hippocampus is one of the most prominent early characteristics of AD, particularly during the mild cognitive impairment (MCI) stage. tVNS could modify function of the hippocampus. We examined resting state functional connectivity from the bilateral hippocampus in response to tVNS in patients with MCI.

Fifty older adults (28 women, 60-89 years of age) diagnosed with MCI were assessed. MCI was confirmed via diagnostic consensus conference with a neurologist and neuropsychologist (sources of information: Montreal Cognitive Assessment Test [MoCA], Clinical Dementia Rating scale [CDR], Functional Activities Questionnaire (FAQ), Hopkins Verbal Learning Test - Revised [HVLT-R] and medical record review). Resting state functional magnetic resonance imaging (fMRI) was collected on a 3T Siemens Prisma scanner while participants received either unilateral tVNS (left tragus, n = 25) or sham stimulation (left ear lobe, n = 25). fMRI data were processed using CONN toolbox v18b and hippocampal seed to voxel (whole brain) analyses were conducted with voxel and cluster level multiple comparison correction.

Contrasting tVNS and sham stimulation, whole-brain seed-to-voxel analysis demonstrated significant changes in connectivity from the left hippocampus to several cortical and subcortical regions bilaterally. Specifically, there was increased connectivity to prefrontal regions and cingulate gyri, and decreased connectivity to anterior and medial temporal lobes. A seed-to-voxel analysis from the right hippocampus indicated significant decrease in connectivity to a single cluster of regions in the left anterior temporal lobe in response to tVNS.

In conclusion, tVNS modified connectivity from the hippocampus to multiple brain regions implicated in semantic and salience functions, in which disruption correlates with deterioration in AD. These findings indicate afferent target engagement of tVNS. Future work is needed to investigate the long-term effects of tVNS in patients with MCI and whether it could contribute to meaningful cognitive change and subsequent improvements in quality of life.

Traumatic brain injury (TBI) is a prevalent cause of long-term morbidity in children and adolescents and can lead to persistent difficulties with social and behavioral function. TBI may impact brain structures that support social cognition, social perception, and day-to-day social interactions—termed the social brain network (SBN). We examined differences in links among the SBN and regions of interest from other neural networks thought to support social outcomes, i.e., the default mode network (DMN) and salience network (SN). Furthermore, we examined how differences in co-activation among the SBN and these other key networks were associated with ratings of social and day-to-day adaptive outcomes.

Participants included children and adolescents with moderate to severe TBI (msTBI; n=11, Mage=11.78, 6 male), complicated-mild TBI (cmTBI; n=12, Mage=12.59, 9 male), and orthopedic injury (OI; n=22, Mage=11.69, 15 male). Participants underwent resting-state functional MRI on a 3Tesla Siemens Prisma scanner. Parents rated their child’s social and adaptive function on the Child Behavior Checklist (CBCL) and Adaptive Behavior Assessment System-Third Edition (ABAS-3). Resting-state connectivity was assessed using the CONN Toolbox, including preprocessing, denoising, and alignment to the participants’ processed T1 MPRAGE sequence followed by seed-to-voxel analysis using a SBN mask and targeted regions of interest within the DMN and SN. Individual-level r-to-z correlations were extracted from resulting clusters of co-activation with the SBN mask and exported into SPSSv28.0 for integration with behavioral data.

One-way ANOVAs used to examine group differences in social and adaptive outcome revealed significant group differences in CBCL Social Competence (F=4.49, p=.019) and all composite scores on the ABAS-3 (Fs=3.78 to 5.17, ps=.031 to .010). In each domain, children with msTBI were rated as having elevated difficulties relative to cmTBI or OI, whereas cmTBI and OI groups did not differ. Connectivity also differed significantly between groups, with children with OI demonstrating greater connectivity between the SBN and the anterior cingulate cortex of the SN (t=5.19, p(FDR)<.0001) and posterior cingulate cortex of the DMN (f=4.30, p(FDR)<.001) than children with msTBI. Children with cmTBI also showed greater connectivity between the SBN and left temporal pole of the DMN (t=7.45, p(FDR)<.000001) than children with msTBI. Degree of connectivity between the SBN and posterior cingulate was significantly positively correlated across all domains of adaptive function (rs=.451 to .504, ps=.010 to .003), whereas degree of connectivity between the SBN and left temporal pole was strongly positively related to Social Competence (a=.633, p=.006) and conceptual adaptive skills on the ABAS (A=.437, p=.037).

Our findings provide insights into the neural substrates of social and adaptive morbidity after pediatric TBI, particularly msTBI, by linking alterations in connectivity among the SBN, DMN, and SN with measures of social and adaptive outcome. While the posterior cingulate was broadly associated with adaptive outcome, the temporal pole was particularly strongly associated with social competence. This may reflect the diverse functions and high degree of interconnectivity of the posterior cingulate, which contributes to various cognitive and attentional processes, relative to the strong amygdala/limbic connections of the temporal pole.

Motor imagery is defined as a dynamic state during which a subject mentally simulates a given action without overt movements. Our aim was to use near-infrared spectroscopy to investigate differences in cerebral hemodynamic during motor imagery of self-feeding with chopsticks using the dominant or non-dominant hand.

Twenty healthy right-handed people participated in this study. The motor imagery task involved eating sliced cucumber pickles using chopsticks with the dominant (right) or non-dominant (left) hand. Activation of regions of interest (pre-supplementary motor area, supplementary motor area, pre-motor area, pre-frontal cortex, and sensorimotor cortex was assessed.

Motor imagery vividness of the dominant hand tended to be significantly higher than that of the non-dominant hand. The time of peak oxygenated hemoglobin was significantly earlier in the right pre-frontal cortex than in the supplementary motor area and left pre-motor area. Hemodynamic correlations were detected in more regions of interest during dominant-hand motor imagery than during non-dominant-hand motor imagery.

Hemodynamic might be affected by differences in motor imagery vividness caused by variations in motor manipulation.

Understanding the factors contributing to optimal cognitive function throughout the aging process is essential to better understand successful cognitive aging. Processing speed is an age sensitive cognitive domain that usually declines early in the aging process; however, this cognitive skill is essential for other cognitive tasks and everyday functioning. Evaluating brain network interactions in cognitively healthy older adults can help us understand how brain characteristics variations affect cognitive functioning. Functional connections among groups of brain areas give insight into the brain’s organization, and the cognitive effects of aging may relate to this large-scale organization. To follow-up on our prior work, we sought to replicate our findings regarding network segregation’s relationship with processing speed. In order to address possible influences of node location or network membership we replicated the analysis across 4 different node sets.

Data were acquired as part of a multi-center study of 85+ cognitively normal individuals, the McKnight Brain Aging Registry (MBAR). For this analysis, we included 146 community-dwelling, cognitively unimpaired older adults, ages 85-99, who had undergone structural and BOLD resting state MRI scans and a battery of neuropsychological tests. Exploratory factor analysis identified the processing speed factor of interest. We preprocessed BOLD scans using fmriprep, Ciftify, and XCPEngine algorithms. We used 4 different sets of connectivity-based parcellation: 1)MBAR data used to define nodes and Power (2011) atlas used to determine node network membership, 2) Younger adults data used to define nodes (Chan 2014) and Power (2011) atlas used to determine node network membership, 3) Older adults data from a different study (Han 2018) used to define nodes and Power (2011) atlas used to determine node network membership, and 4) MBAR data used to define nodes and MBAR data based community detection used to determine node network membership.

Segregation (balance of within-network and between-network connections) was measured within the association system and three wellcharacterized networks: Default Mode Network (DMN), Cingulo-Opercular Network (CON), and Fronto-Parietal Network (FPN). Correlation between processing speed and association system and networks was performed for all 4 node sets.

We replicated prior work and found the segregation of both the cortical association system, the segregation of FPN and DMN had a consistent relationship with processing speed across all node sets (association system range of correlations: r=.294 to .342, FPN: r=.254 to .272, DMN: r=.263 to .273). Additionally, compared to parcellations created with older adults, the parcellation created based on younger individuals showed attenuated and less robust findings as those with older adults (association system r=.263, FPN r=.255, DMN r=.263).

This study shows that network segregation of the oldest-old brain is closely linked with processing speed and this relationship is replicable across different node sets created with varied datasets. This work adds to the growing body of knowledge about age-related dedifferentiation by demonstrating replicability and consistency of the finding that as essential cognitive skill, processing speed, is associated with differentiated functional networks even in very old individuals experiencing successful cognitive aging.

Cognitive decline is a common non-motor feature of Parkinson's disease (PD). However, the underlying mechanisms of cognitive impairment in PD require further elucidation. FDG PET imaging data analyses have revealed distinct brain metabolic patterns associated with the cognitive features of PD. The PD cognition-related pattern (PDCP) and default mode network (DMN) are two overlapping, but topographically distinct, networks that may serve as biomarkers of cognitive decline in PD. Decreased activity of the resting-state DMN and increased expression of the PDCP are associated with cognitive impairment in PD. Studies have consistently demonstrated the association between neuropsychological memory test performance and PDCP expression. Thus, we examined whether memory performance could offer additional value in predicting PDCP expression in PD patients. We hypothesized that DMN and memory performance would predict greater variance in PDCP expression than the DMN alone.

Participants included 48 PD patients ages 46-80 (mean (SD) Age: 61.9 (8.1), Education: 15.0 (2.8), IQ: 112.5 (14.9), DRS total: 136.7 (5.8)). All participants completed the FDG PET and neuropsychological evaluation 8-12 hours after their last dose of Levodopa. Neuropsychological memory testing included the California Verbal Learning Test (CVLT) z score of sum of learning trials. PDCP and DMN values were z scores generated from normal controls in previous studies. Data were analyzed using linear regression analyses.

A hierarchical regression was performed to predict PDCP as a function of DMN and CVLT learning performance. Variables were entered in two separate blocks. The first block included DMN as a predictor, and the overall regression was significant (R2 = 0.55, F(1, 39)= 47.0, p < 0.001). As hypothesized, DMN significantly predicted PCDP expression (β= -0.74, p < 0.001). The second block of the regression included CVLT learning memory performance. Both DMN and CVLT performance explained a significant amount of variance in PDCP (R2 change = 0.05, F(2, 39)= 27.6, p < 0.001). CVLT performance significantly predicted PDCP (β= -0.22, p =0.048). The final model accounted for 60.0% of the variance inPDCP.

Disruptions in functional connectivity within brain networks have become increasingly recognized as mechanisms responsible for cognitive impairment in patients. As demonstrated in previous studies, our results indicated that DMN loss is a strong predictor of PDCP expression, likely due to the networks' overlapping spatial regions. However, we found that the addition of memory performance to the model could explain a small amount of variance (5%) over and above DMN expression. Overall, the current findings demonstrate a functional (i.e., learning) distinction between population-specific (PDCP) and more general brain networks (DMN).

Around 200,000 veterans (up to 32% of those deployed) of the 1991 Gulf War (GW) suffer from GW veterans’ illness (GWVI). GWVI is a poorly understood chronic medical condition, characterized by symptoms indicative of brain function deficits in multiple domains. Among the symptoms of brain impairment GWVI-related chronic headaches and body muscle and joint pain conditions (GWVI-HAP) are the most debilitating, affecting around 64% of the GWVI veterans. Further, depression carries a very high co-morbid rate (>50%) in patients with chronic pain, including GWVI-HAP. In this preliminary study, we examined the integrity of brain function networks in a group of GWI-HAP veterans, with resting state fMRI (rsfMRI).

Data from the first twenty-two GWVI-HAP veterans from two ongoing parallel clinical trials was examined. Of these 14 subjects (GWVI-HAP-DM) had mild depression (Hamilton Rating Scale for Depression (HSRD < 13); and 8 subjects (GWVI-HAP-DS) had moderate to severe depression (HSRD > 14). Written informed consent was obtained from all participants in the protocol approved by the local Institutional Review Board. RsfMRI data was acquired on a Siemens 3T Prisma-Fit MRI scanner using a 10-minute whole-brain high resolution simultaneous multi-slice (SMS) gradient echo echo-planar imaging (EPI) sequence: TR/TE/FA = 2.2 sec/ 27 msec/80°, and analyzed with well-established image processing pipelines. Functional connectivity (FC) to different regions implicated in depression and chronic pain was assessed with seed-based correlation analysis. Between group differences in FC were obtained with 2-sample t-tests.

GWVI-HAP-DS group exhibited significantly (p < 0.05) reduced FC compared to GWVI-HAP-DM between frontal lobe (medial (mPFC), and dorsolateral (dlPFC) prefrontal cortex) and the striatum. This indicates that malfunction of fronto-striatal circuits could be a source of the increased chronic pain and depression seen in veterans with GWVI- HAP-DS. Dysregulation of fronto-striatal networks has been implicated in major depressive disorder as well as many chronic pain conditions. In addition, FC between mPFC, and salience network (SN; anterior insula and dorsal anterior cingulate) and limbic (subgenual and ventral anterior cingulate) regions were also reduced in GWVI-HAP-DS. Similarly, mPFC and SN also exhibited reduced FC to pain processing regions (posterior insula, centromedian thalamus and cerebellum). These FC impairments could reflect greater deficits in regulation of and salience attribution to emotions and nociception in the GWVI-HAP-DS group. Finally, GWVI-HAP-DS also exhibited reduced FC between nodes of the default mode network. DMN impairments also have been observed in many depressive and chronic pain conditions.

The results of this preliminary analysis implicate impairments in cognitive control of emotion and nociception as a mechanism underlying the enhanced chronic pain and depression observed in GWVI-HAP veterans, especially those with moderate to severe depression. A fuller picture of deficits in FC in brain function networks is expected to emerge as more GWI-HAP subjects of both groups along with age matched healthy controls are examined in this ongoing project. Better understanding of impairments in these networks in GWI-HAP will benefit the rehabilitation of veterans with GWI-HAP.

Adolescent and young adult survivors of pediatric brain tumors often live with long-term neuropsychological deficits, which have been found to be related to functional and structural brain changes related to the presence of the tumor itself as well as treatments such as radiation therapy. The importance of brain networks has become a central focus of research over recent decades across neurological populations. Graph theory is one way of analyzing network properties that can describe the integration, segregation, and other aspects of network organization. The existing literature using graph theory with survivors of brain tumor is small and inconsistent; therefore, more work is needed, particularly in survivors of pediatric brain tumors. The present study used graph theory to determine whether functional network properties in this population differ from healthy controls; whether graph metrics relate to core cognitive skills: attention, working memory, and processing speed; and whether they relate to a cumulative measure of neurological risk.

31 survivors and 31 matched controls completed neuropsychological testing including measures of attention, working memory, and processing speed. They also underwent resting state functional magnetic resonance imaging. Resting state data were preprocessed and spatially constrained independent component analysis was completed to construct connectivity matrices. Finally, graph metrics were calculated utilizing an area under the curve method, including global efficiency, clustering coefficient, betweenness centrality, and small-worldness. Group differences and associations between graph metrics, cognitive outcomes, and neurological risk were analyzed using SPSS version 28.0.

Results revealed a significant difference such that brain tumor survivors exhibited less small-world properties in their functional brain networks. This was found to be related to working memory, such that less smallworldness in the network was related to poorer performance. There were no significant relationships with neurological risk, but there were nonsignificant correlations of small-moderate effect size such that lower global efficiency and clustering coefficient were associated with greater neurological risk. Comparisons to structural network analysis from a similar sample and additional post-hoc analyses are also discussed.

These findings reveal that survivors of pediatric brain tumor indeed display significant differences in functional brain networks that are quantifiable by graph theory. It is also possible that, with further work, we might better understand how metrics such as smallworldness can be used to predict long-term cognitive outcomes and functional independence in adulthood.

The stria terminalis (ST) is a white matter tract with connections to limbic and autonomic brain structures that is implicated in affective functioning. Recent works suggests that ST functional integrity and connectivity is associated with faster responses to emotional cues (Dzafic et al., 2019) and may be influenced by environmental factors including socioeconomic status (SES) and childhood adversity (Banihashemi et al., 2020). The role of the ST in the experience of more daily affective experiences, such as depressive symptoms, remains unexplored. Therefore, the present study examined the role of the ST and SES, as assessed by household income, in the relationship between age and depressive symptoms in typically developing children and adolescents.

Participants include 64 typically developing children and adolescents age 8-21 (Mage=13.27, SD=3.15) who participated in an ongoing study of development of neurocognitive and social-cognitive skills. Participants completed imaging on a 3Tesla MR Siemens PRISMA scanner. Tractography was executed via ENIGMA tract-based spatial statistics to quantify WM integrity and provided values for mean fractional anisotropy (mFA) of the ST. Depressive symptoms were measured with the Behavior Assessment Scale for Children-Third Edition (BASC-3) parent report scale, and annual family income was obtained per parent report. Mediation and moderation analyses were conducted using Process version 4.1 (Hayes, 2022) in SPSS version 28. As depression symptoms are often higher in early adolescence than later, we examined the indirect effect of age on depressive symptoms through ST mFA and evaluated this relationship at different levels of family income.

Age was associated with lower levels of depressive symptoms (b=-.98, t=-2.18, p<.05), whereas greater right ST mFA was associated with higher levels of depressive symptoms (b=42.05, t=2.50, p<.05). Right ST mFA explained significant variance in the relationship between age and parent-reported depression (ab=.13, 95% CI [.02, .29]). The conditional indirect effect of family income was significant for children with annual family incomes between 25-50k (effect=.16, 95% CI [.01, .38]) and 75-100k (effect=.13, 95% CI [.001, .31]), but not for 100k+ (effect=.11, 95% CI [-.05, .33]).

The present study revealed a significant, positive relationship between white matter integrity in the right ST and parent-reported depressive symptoms in healthy children and young adults. Finding extend on prior work implicating the ST in threat responsivity (Dzafic et al., 2019). Moreover,results suggest the role of the ST in the relationship between age and depression depends on level of family income, such that ST mFA explains more variance at lower income levels, and is no longer significant for children from families with income greater than 100k. These findings support the notion that environmental stressors (such as lower family income) may strengthen ST pathways via activity-dependent plasticity and repeated, coordinated activation (Rinaman et al., 2011). Future studies should examine these brain-behavior associations, as they may replicate in a larger sample, with more nuanced indicators of environmental stress.

Interventions using a cognitive training paradigm called the Useful Field of View (UFOV) task have shown to be efficacious in slowing cognitive decline. However, no studies have looked at the engagement of functional networks during UFOV task completion. The current study aimed to (a) assess if regions activated during the UFOV fMRI task were functionally connected and related to task performance (henceforth called the UFOV network), (b) compare connectivity of the UFOV network to 7 resting-state functional connectivity networks in predicting proximal (UFOV) and near-transfer (Double Decision) performance, and (c) explore the impact of network segregation between higher-order networks and UFOV performance.

336 healthy older adults (mean age=71.6) completed the UFOV fMRI task in a Siemens 3T scanner. UFOV fMRI accuracy was calculated as the number of correct responses divided by 56 total trials. Double Decision performance was calculated as the average presentation time of correct responses in log ms, with lower scores equating to better processing speed. Structural and functional MRI images were processed using the default pre-processing pipeline within the CONN toolbox. The Artifact Rejection Toolbox was set at a motion threshold of 0.9mm and participants were excluded if more than 50% of volumes were flagged as outliers. To assess connectivity of regions associated with the UFOV task, we created 10 spherical regions of interest (ROIs) a priori using the WFU PickAtlas in SPM12. These include the bilateral pars triangularis, supplementary motor area, and inferior temporal gyri, as well as the left pars opercularis, left middle occipital gyrus, right precentral gyrus and right superior parietal lobule. We used a weighted ROI-to-ROI connectivity analysis to model task-based within-network functional connectivity of the UFOV network, and its relationship to UFOV accuracy. We then used weighted ROI-to-ROI connectivity analysis to compare the efficacy of the UFOV network versus 7 resting-state networks in predicting UFOV fMRI task performance and Double Decision performance. Finally, we calculated network segregation among higher order resting state networks to assess its relationship with UFOV accuracy. All functional connectivity analyses were corrected at a false discovery threshold (FDR) at p<0.05.

ROI-to-ROI analysis showed significant within-network functional connectivity among the 10 a priori ROIs (UFOV network) during task completion (all pFDR<.05). After controlling for covariates, greater within-network connectivity of the UFOV network associated with better UFOV fMRI performance (pFDR=.008). Regarding the 7 resting-state networks, greater within-network connectivity of the CON (pFDR<.001) and FPCN (pFDR=. 014) were associated with higher accuracy on the UFOV fMRI task. Furthermore, greater within-network connectivity of only the UFOV network associated with performance on the Double Decision task (pFDR=.034). Finally, we assessed the relationship between higher-order network segregation and UFOV accuracy. After controlling for covariates, no significant relationships between network segregation and UFOV performance remained (all p-uncorrected>0.05).

To date, this is the first study to assess task-based functional connectivity during completion of the UFOV task. We observed that coherence within 10 a priori ROIs significantly predicted UFOV performance. Additionally, enhanced within-network connectivity of the UFOV network predicted better performance on the Double Decision task, while conventional resting-state networks did not. These findings provide potential targets to optimize efficacy of UFOV interventions.

Behavior is the product of interconnected brain regions that work together as networks. This case study examines whether there are differences between a participant with a large congenital left temporal lobe cyst, which impacted the volume of structures in the region, and control subjects of similar age on cognitive tasks and network connectivity as measured by resting-state functional magnetic resonance imaging (rs-fMRI).

The case participant (CP; 71 year old female) and controls (CON; n = 25; 48% female) were recruited as part of a larger aging study. CON were chosen from the larger study population by age (+/- 10 years from CP; Range = 68-86 years). Cognitive tasks included: Shopping list memory task, Montreal Cognitive Assessment, WAIS-IV subtests: Digit Span, Digit-Symbol, Symbol Span, and Letter-Number Sequencing. For rs-fMRI, we administered four blood-oxygen level dependent (BOLD) functional connectivity (rs-fMRI) scans at 6 minutes each. Image processing was conducted using the CONN toolbox. Independent sample t-tests evaluated differences between CP and CON. Segregation was evaluated in the Auditory (Au), Cerebellar-basal ganglia (CBBG), Cingulo-Opercular Task Control (COTC), Dorsal Attention (DA), Default Mode (DMN), Fronto-Parietal Task Control (FPTC), Salience (Sa), Sensory Somatomotor Hand (SSH), Sensory Somatomotor Mouth (SSM), Visual (Vi), and Ventral Attention (VA) networks to assess CP’s functional segregation by network throughout the brain. Bonferroni correction was applied to account for multiple comparisons in cognitive testing (.05/7 for significance at p < 0.007) and network segregation (.05/11 for significance at p < .005).

Independent samples t-tests did not reveal significant differences across cognitive tasks (t(24) <1.04, p > .05). Network segregation did not reveal significant differences between CP and CON across networks examined (t(24) < 1.269, p > .005). However, DMN and DA segregation trended toward significance (t(24) = -2.724, p = .006 and t(24) =-2.006, p = .028), respectively) with CP demonstrating lower segregation as compared to CON.

CP performed similarly on cognitive testing to CON, indicating that the congenital presence of a large temporal lobe cyst did not impact global cognition, list learning and memory, working memory, or processing speed. CP did not demonstrate significantly different segregation across networks of interest after Bonferroni correction. Our cognitive performance results are consistent with a similar case-study examining language, which revealed intact linguistic abilities (Tuckete et al., 2022). The lack of differences in cognitive performance and segregation highlight the capacity for plasticity in the human brain, even in the presence of a large structural abnormality. This also suggests that the processes of aging in this case are not markedly different from controls. In future research we intend to expand on this case study by evaluating right temporal to hippocampal seeds and language network seeds to delve deeper into memory and language functioning.

Aging is associated with disruptions in functional connectivity within the default mode (DMN), frontoparietal control (FPCN), and cingulo-opercular (CON) resting-state networks. Greater within-network connectivity predicts better cognitive performance in older adults. Therefore, strengthening network connectivity, through targeted intervention strategies, may help prevent age-related cognitive decline or progression to dementia. Small studies have demonstrated synergistic effects of combining transcranial direct current stimulation (tDCS) and cognitive training (CT) on strengthening network connectivity; however, this association has yet to be rigorously tested on a large scale. The current study leverages longitudinal data from the first-ever Phase III clinical trial for tDCS to examine the efficacy of an adjunctive tDCS and CT intervention on modulating network connectivity in older adults.

This sample included 209 older adults (mean age = 71.6) from the Augmenting Cognitive Training in Older Adults multisite trial. Participants completed 40 hours of CT over 12 weeks, which included 8 attention, processing speed, and working memory tasks. Participants were randomized into active or sham stimulation groups, and tDCS was administered during CT daily for two weeks then weekly for 10 weeks. For both stimulation groups, two electrodes in saline-soaked 5x7 cm2 sponges were placed at F3 (cathode) and F4 (anode) using the 10-20 measurement system. The active group received 2mA of current for 20 minutes. The sham group received 2mA for 30 seconds, then no current for the remaining 20 minutes.

Participants underwent resting-state fMRI at baseline and post-intervention. CONN toolbox was used to preprocess imaging data and conduct region of interest (ROI-ROI) connectivity analyses. The Artifact Detection Toolbox, using intermediate settings, identified outlier volumes. Two participants were excluded for having greater than 50% of volumes flagged as outliers. ROI-ROI analyses modeled the interaction between tDCS group (active versus sham) and occasion (baseline connectivity versus postintervention connectivity) for the DMN, FPCN, and CON controlling for age, sex, education, site, and adherence.

Compared to sham, the active group demonstrated ROI-ROI increases in functional connectivity within the DMN following intervention (left temporal to right temporal [T(202) = 2.78, pFDR < 0.05] and left temporal to right dorsal medial prefrontal cortex [T(202) = 2.74, pFDR < 0.05]. In contrast, compared to sham, the active group demonstrated ROI-ROI decreases in functional connectivity within the FPCN following intervention (left dorsal prefrontal cortex to left temporal [T(202) = -2.96, pFDR < 0.05] and left dorsal prefrontal cortex to left lateral prefrontal cortex [T(202) = -2.77, pFDR < 0.05]). There were no significant interactions detected for CON regions.

These findings (a) demonstrate the feasibility of modulating network connectivity using tDCS and CT and (b) provide important information regarding the pattern of connectivity changes occurring at these intervention parameters in older adults. Importantly, the active stimulation group showed increases in connectivity within the DMN (a network particularly vulnerable to aging and implicated in Alzheimer’s disease) but decreases in connectivity between left frontal and temporal FPCN regions. Future analyses from this trial will evaluate the association between these changes in connectivity and cognitive performance post-intervention and at a one-year timepoint.

Autism Spectrum Disorders (ASD) and Attention Deficit Hyperactivity Disorder (ADHD) are neurodevelopmental disorders with overlapping symptomatology and shared genetic makeup. Numerous previous studies have investigated ASD and ADHD using resting state functional networks. One functional network of particular interest is the Default Mode Network (DMN), as it has been shown to be abnormal in several mental disorders. Previous studies have investigated the DMN in ASD and ADHD separately but reported mixed trends of increased and decreased functional connectivity (FC) in the DMN in ASD and increased FC in ADHD. Additionally, little studies have investigated executive and attentional network dysfunction in the DMN for ASD and ADHD populations. To better understand the shared characteristics between ASD and ADHD, this study analyzed the DMN FC in children with ASD and ADHD.

Archival datasets from Autism Brain Imaging Data Exchange (ABIDE)-I and ADHD-200 datasets were used, with 33 ADHD, 35 ASD, and 32 typically developing (TD) males (ages = 7-17 years). After applying a standard pre-processing pipeline, 11 regions of interest (ROIs) from the Dosenbach-160 atlas were examined with 55 ROI pairs generated for the 100 subjects.

Significant differences were noted between ASD-ADHD groups in attentional networks and executive functioning networks. Specifically, significant Group x VIQ interactions were noted for FC between the following pairs of regions: medial prefrontal cortex - ventromedial prefrontal cortex, anterior cingulate cortex -ventromedial prefrontal cortex, inferior temporal lobe - ventromedial prefrontal cortex, angular -ventromedial prefrontal cortex, angular -anterior cingulate cortex, inferior temporal lobe -ventrolateral prefrontal cortex, angular -superior frontal lobe, and intraparietal sulcus -superior frontal lobe. In the above FC pairs, FC in ADHD was negatively correlated with VIQ, with no correlation for ASD and positive correlation for TD. Previous literature has indicated that ADHD individuals demonstrate increased executive functioning deficits compared to ASD individuals. This study provides evidence at a neural level for these findings by demonstrating decreased FC trends in ADHD in attentional and executive functioning networks compared to ASD individuals. Group and VIQ main effects demonstrated mixed patterns across the three groups, as well as shared decreased FC in attention/executive networks for both ASD and ADHD groups.

In summary, this study found similar findings from previous studies regarding mixed connectivity patterns, as well as shared dysfunction between ASD and ADHD groups. These results help in solidifying the theory that ASD and ADHD share clinical and neural patterns which need to be examined further. Future directions include utilizing more ASD+ADHD comorbid individuals in studies comparing ASD and ADHD FC trends as well as seeking to further understand the neuropsychological and neuroimaging profiles in ASD and ADHD.

Socioeconomic status (SES) has been recognized as an important factor in psychological research within the last few decades. Past literature recognizes that having lower SES can have a negative impact on many aspects of one’s health, especially in diseases related to brain aging. A recent avenue for research regarding SES and the brain-behavior relationship suggests that socioeconomic status can act as a moderator for brain activation during task performance. The hypothesis for this project was that there will be a negative correlational relationship between brain activity and SES when controlling for participants’ age, sex, and performance on the episodic memory tasks, but a positive correlation between task performance and SES was expected.

With 100 middle-aged healthy adults from the Reference Ability Neural Network (RANN) study (53 male and 47 female, age M=48.0 +/- 7.55 years), three episodic memory fMRI tasks were performed and studied in relation to SES and age. The tasks were Logical Memory, Word Order, and Pair Associates tasks that involved episodic memory for story details, order of words presented, and pairing of words, respectively. We quantified memory performance with average accuracy from performance of the three tasks. We used the FSL software to preprocess and perform voxel-wise group analysis. All brain activation analyses were corrected for multiple comparison using cluster thresholds in FSL.

Correlation between SES and memory performance was found to be marginally significant (R=.188, p=.061). All tasks had areas of positively correlated activation for age. The Logical Memory task had multiple areas of brain activation that were positively correlated with age, particularly at the lateral occipital cortex, lingual gyrus, and the occipital fusiform gyrus, all areas that underlie visual processing. There were no areas of correlated brain activation for SES, sex, and task performance for the Pair Associates and Logical Memory tasks. Brain activation for the Word order task in the left precuneous cortex and the right middle frontal gyrus, left lateral occipital cortex, left occipital fusiform gyrus, and parts of the lingual gyrus was positively correlated with memory performance when controlled for age, sex, and SES.

The hypothesis was not entirely supported by the results of this study, but the marginal effect between SES and memory performance can suggest that SES may affect memory performance within middle-aged adults. While we did not find a brain association with SES in this age group, we observed regions that underlie task performance. Further research can be done on possible moderating effects of Socioeconomic Status on memory and executive function with structural neuroimaging to further investigate the effects of SES on cognition.

Functional connectivity of the default mode network (DMN) during rest has been shown to be different among adults with Mild Cognitive Impairment (MCI) relative to aged-matched individuals without MCI and is predictive of transition to dementia. Post-traumatic stress disorder (PTSD) is also associated with aberrant connectivity of the DMN. Prior work from this group has demonstrated a higher rate of MCI and PTSD among World Trade Center (WTC) responders relative to the general population. The current study sought to investigate the main and interactive effects of MCI and PTSD on DMN functioning. Based on prior work, we hypothesized that MCI, but not PTSD, would predict aberrant connectivity in the DMN.

99 WTC responders aged 44–65 stratified by MCI status (yes/no) and PTSD status (yes/no) and matched for age in years, sex (male vs. female), race (white, black, and other), and educational attainment (high school or less, some college / technical school, and university degree), and occupation on September 11, 2001 (law enforcement vs. other) underwent fMRI using a 3T Siemens Biograph MR scanner. A single 10-minute continuous functional MR sequence was acquired while participants were at rest with their eyes open. Group-level analyses were conducted using SPM-12, with correction for multiple comparisons using AFNI's 3dClustSim. Based on this threshold, the number of comparisons in our imaging volume, and the smoothness of our imaging data as measured by 3dFWHMx-acf, a minimum cluster size of 1134 voxels was required to have a corrected p . .05 with 2-sided thresholding. Spherical 3 mm seeds were placed in the dorsal (4, -50, 26) and ventral (4, -60, 46) posterior cingulate cortex (PCC).

Individuals with PTSD demonstrated significantly less connectivity of the dorsal posterior cingulate cortex (PCC) with medial insula (T = 5.21), subthalamic nucleus (T = 4.66), and postcentral gyrus (T = 3.81). There was no difference found in this study for connectivity between groups stratified by MCI status. There were no significant results for the ventral PCC seed.

Contrary to hypotheses that were driven by a study of cortical thickness in WTC responders, the impact of PTSD appears to outweigh the impact of MCI on dorsal DMN connectivity among WTC responders stratified by PTSD and MCI status. This study is limited by several issues, including low number of female and minority participants, relatively small group cell sizes (n = 23–27 per cell), a brief resting state sequence (10 minutes), and lack of a non-WTC control group. Importantly, responders are a unique population so generalizability to other populations may be limited. Individuals in the current study are now being followed longitudinally to relate baseline resting state functional connectivity with cognitive changes and changes in connectivity over a four-year period.

Studies suggest that internally oriented cognitive processes are central to creativity. Here, we distinguish between intentional and unintentional forms of mind wandering and explore their component contributions to creativity. Furthermore, we describe resting-state connectivity profiles associated with these trait-level measures of mind wandering. Bearing in mind the role of the DMN in internally directed cognitive processes, we hypothesize that, in general, mind wandering will be associated with increased connectivity of voxels in the medial prefrontal and posterior cingulate cortices, key nodes in the DMN. We further hypothesize that intentional and unintentional mind wandering will be associated with distinct patterns of connectivity across DMN core regions.

We used a sample of 155 healthy adults from the mind-brain-body dataset, all of whom completed resting-state fMRI scans and trait-level measures of mind wandering. We analyzed intentional and unintentional mind wandering tendencies using self-report measures. Next, we explored the relationship between mind wandering tendencies and creativity, as measured by a divergent thinking task. Additionally, we describe patterns of resting-state network connectivity associated with mind wandering, using graph theory (weighted degree) functional connectivity analysis.

At the behavioral level, results showed a significant positive association between creativity and both intentional and unintentional mind wandering. Neuroimaging analysis revealed higher weighted degree connectivity associated with both forms of mind wandering, implicating core regions of the default network and the left temporal pole. We observed topological connectivity differences within the default network: intentional mind wandering was associated with degree connectivity in posterior regions, whereas unintentional mind wandering showed greater involvement of prefrontal areas.

In this study, we highlight patterns of resting-state network connectivity associated with intentional and unintentional mind wandering, and provide novel evidence of a link between mind wandering and creativity. These findings represent a promising step towards understanding the neurocognitive mechanisms that underlie productive mind wandering and demonstrate its relevance for the study of creative thinking.

Mild traumatic brain injury (mTBI) remains one of the most silent recurrent head injuries reported in the United States. mTBI accounts for nearly 75 percent of all traumatic brain injuries in the American population. Brain injury is often associated with impulsivity, but the association between resting state functional connectivity (rsFC) and impulsivity at multiple stages since time-since-injury (TSI) is unclear. We hypothesized that rsFC within the default mode network (DMN) would predict impulsivity across multiples stages of recovery in mild TBI.

Participants healthy controls (HC: n=35 total [15 male, 20 female], age M=24.40, SD=5.95; mTBI: n=121 total [43 male; 78 female], age M=24.76, SD=7.48). Participants completed a cross-sectional study design at various post-injury time points ranging from (2W, 1M,3M,6M,12M). Participants a neuroimaging session and behavioral tasks including a psychomotor vigilance task. Impulsivity was assessed as a combination of false starts and impulsive responses on behavioral tasks. The neuroimaging session included a rsFC scan. To predict impulsivity from brain connectivity, we conducted a series of stepwise linear regression analyses with the 11 functional brain connections (extracted as Fisher’s z-transformed correlations between regions) as predictors and each of the 13 neurocognitive factor scores separately. We focus here on the outcomes for the impulsivity factor.

Results showed greater positive connectivity between the and Right Frontal Pole and the anterior cingulate cortex (ACC; seed) (ß = .158, t = 1.98, p = .049) which was associated with greater impulsivity. Individuals in the 2W group demonstrated one significant predictor (R = .632, R2 = .399, F = 5.32, p = .050). Largely, there was greater positive connectivity between the Right Frontal Pole and the ACC (seed) and (ß = .632, t = 2.31, p = .050) which was associated with higher impulsivity at the 2W time-since-injury. No predictors emerged for the 1M, 3M, or 6M conditions. However, individuals in the 12M group demonstrated two significant predictor connections (R = .497, R2 = .247, F = 5.73, p = .007). Overall, a linear combination of greater negative (anticorrelated) connectivity between the Right Frontal Pole and the mPFC (seed) (/? = -.576, t = -3.53, p = .002) and greater positive connectivity between the Paracingulate Cortex (seed) and the Left Lateral Prefrontal Cortex (ß = .368, t = 2.14, p = .039) was also associated with greater impulsivity in individuals with mTBI at 12M.

These findings suggest functional connectivity between the anterior node of the DMN and prefrontal cortex regions involved in behavioral control was predictive of higher impulsivity in individuals with mTBI at 2W and 12M post injury, but not at other time frames. Interestingly, these connections differed at the two time points. Acutely, greater impulsivity was associated with greater connectivity among regions involved in error detection, exploration, and emotion. At one year, the connections involve regions associated with error monitoring and inhibitory processes. This may reflect compensatory strategy development during recovery.

Nonpathological aging has been linked to decline in both verbal and visuospatial memory abilities in older adults. Disruptions in resting-state functional connectivity within well-characterized, higherorder cognitive brain networks have also been coupled with poorer memory functioning in healthy older adults and in older adults with dementia. However, there is a paucity of research on the association between higherorder functional connectivity and verbal and visuospatial memory performance in the older adult population. The current study examines the association between resting-state functional connectivity within the cingulo-opercular network (CON), frontoparietal control network (FPCN), and default mode network (DMN) and verbal and visuospatial learning and memory in a large sample of healthy older adults. We hypothesized that greater within-network CON and FPCN functional connectivity would be associated with better immediate verbal and visuospatial memory recall. Additionally, we predicted that within-network DMN functional connectivity would be associated with improvements in delayed verbal and visuospatial memory recall. This study helps to glean insight into whether within-network CON, FPCN, or DMN functional connectivity is associated with verbal and visuospatial memory abilities in later life.

330 healthy older adults between 65 and 89 years old (mean age = 71.6 ± 5.2) were recruited at the University of Florida (n = 222) and the University of Arizona (n = 108). Participants underwent resting-state fMRI and completed verbal memory (Hopkins Verbal Learning Test - Revised [HVLT-R]) and visuospatial memory (Brief Visuospatial Memory Test - Revised [BVMT-R]) measures. Immediate (total) and delayed recall scores on the HVLT-R and BVMT-R were calculated using each test manual’s scoring criteria. Learning ratios on the HVLT-R and BVMT-R were quantified by dividing the number of stimuli (verbal or visuospatial) learned between the first and third trials by the number of stimuli not recalled after the first learning trial. CONN Toolbox was used to extract average within-network connectivity values for CON, FPCN, and DMN. Hierarchical regressions were conducted, controlling for sex, race, ethnicity, years of education, number of invalid scans, and scanner site.

Greater CON connectivity was significantly associated with better HVLT-R immediate (total) recall (ß = 0.16, p = 0.01), HVLT-R learning ratio (ß = 0.16, p = 0.01), BVMT-R immediate (total) recall (ß = 0.14, p = 0.02), and BVMT-R delayed recall performance (ß = 0.15, p = 0.01). Greater FPCN connectivity was associated with better BVMT-R learning ratio (ß = 0.13, p = 0.04). HVLT-R delayed recall performance was not associated with connectivity in any network, and DMN connectivity was not significantly related to any measure.

Connectivity within CON demonstrated a robust relationship with different components of memory function as well across verbal and visuospatial domains. In contrast, FPCN only evidenced a relationship with visuospatial learning, and DMN was not significantly associated with memory measures. These data suggest that CON may be a valuable target in longitudinal studies of age-related memory changes, but also a possible target in future non-invasive interventions to attenuate memory decline in older adults.

Mild traumatic brain injury (mTBI) remains one of the most prevalent brain injuries, affecting approximately one-in-sixty Americans. Previous studies have shown an association between white matter integrity and aggression at chronic stages (either 6-months or 12 months post-mTBI) however, the association between white matter axonal damage, neuropsychological outcomes, and elevated aggression in multiple stages since time-since-injury (TSI) is unclear. We hypothesized that functional connectivity between the default mode network (DMN), a key brain network involved in cognitive, self-reflective, and emotional processes, and other cortical regions would predict elevated aggression and emotional disturbances across multiples stages of recovery in mild TBI.

Participants healthy controls (HC: n=35 total [15 male, 20 female], age M=24.40, SD=5.95; mTBI: n=121 total [43 male; 78 female], age M = 24.76, SD=7.48). Participants completed a cross-sectional study design at specific post-injury time points ranging from (2W, 1M,3M,6M,12M). Participants completed a comprehensive neuropsychological battery and a neuroimaging session, including resting state functional connectivity (FC). Here, we focus on the FC outcomes for the DMN. During the neuropsychological assessment, participants completed tests that measured learning and memory, speed of information processing, executive function, and attention. To predict neuropsychological performance from brain connectivity, we conducted a series of stepwise linear regression analyses with the 11 functional brain connections (extracted as Fisher’s z-transformed correlations between regions) as predictors and each of the 13 neurocognitive factor scores separately.

Consistent with our hypothesis, one predictor materialized as significant (R = .187, R2 = .035, F = 5.55, p = .020) for the Total Sample. Largely, positive connectivity between Right Inferior Frontal Gyrus and the PCC (seed) was associated with increased aggression in the Total Sample of all participants (ß = .187, t = 2.36, p = .020). One predictor materialized as significant in Individuals the 2W group, (R = .719, R2 = .518, F = 8.58, p = .019). In general, greater negative (anticorrelated) connectivity between the Left Lateral Occipital Cortex (ß = -.719, t = -2.93, p = .019) and the PCC (seed) and was associated with greater aggression at 2W, but no predictors emerged at 1M or 3M. Individuals in the 6M group showed one significant predictor (R = .675, R2 = .455, F = 16.71, p = .001). Specifically, greater positive connectivity between the Right Lateral Occipital Cortex (/? = .675, t = 4.09, p = .001) and PCC (seed) was associated with greater aggression at 6M. No associations were evident at 12M.

Overall, these findings suggest functional connectivity between the posterior hub of the DMN and cortical regions within the occipital cortex was predictive of higher aggression in individuals with mTBI. However, the direction of this connectivity differed at 2W versus 6M, suggesting a complex process of recovery that may contribute differentially to aggression in patients with mTBI. As these regions are involved in self-consciousness and visual perception, this may point toward future avenues for aiding in functional recovery of emotional dysregulation in patients with persistent post-concussion syndrome.