Neuroimaging is commonly used in medicine to identify neuropathology and is widely considered to be a reliable and valid diagnostic modality. Personality testing is commonly used to identify psychopathology but is generally perceived to have less clinical efficacy than neuroimaging. The purpose of the current study was to compare the clinical efficacy of personality tests to neuroimaging using meta-analysis.

Multiple databases were searched for original research utilizing either personality tests or neuroimaging. The search interval covered articles published within the last 10 years. Studies were selected based on the criteria of having a clinical group and a healthy control sample with a reported diagnostic outcome. For this meta-analysis, neuroimaging studies focusing on diagnostic utility for Alzheimer’s dementia were included. Personality testing studies were included if they broadly reported a clinical outcome, due to fewer studies in this area. Studies were coded using a complex multi-comparison, outcome, and subgroup schema, and were analyzed under random-effects modeling.

Out of the 240 studies identified for the personality domain, 13 were selected for the meta-analysis. Out of 6522 studies identified for the neuroimaging domain, 21 studies were selected for the meta-analysis. Results indicated a significant difference between the neuroimaging and personality testing effect sizes. Specifically, neuroimaging [Hedge’s g = -1.623, 95% CI = -1.973 to -1.273, p<.001] yielded a greater effect size in comparison to the personality tests effect size [Hedge’s g = -0.658, 95% CI = -0.751 to -0.565, p<.001]. The effect size for clinical utility of neuroimaging was close to double that of the effect for personality tests diagnostic utility.

Findings from this meta-analysis showed a significant difference in the effect sizes obtained from neuroimaging studies compared to the studies of personality tests. While both neuroimaging and personality testing demonstrated meaningful clinical utility, neuroimaging studied had a larger effect size.

Those at genetic risk for Alzheimer's Disease (AD) because of the ApoE ε4 allele show differences in activation during olfactory information processing and memory in areas such as MTL structures, entorhinal cortex, posterior cingulate, precuneus, and inferior parietal lobule, suggesting preclinical AD neuropathology and olfactory impairment as a biomarker for predicting later AD onset (Murphy, 2019). The effects of smoking on AD have varied, with early studies suggesting either no effect or protective effects, and recent studies suggesting smoking as a risk factor for AD but with the need for further investigation in preclinical stages. Therefore, this study focused on olfaction and smoking as risk factors for preclinical AD neuropathology by studying differences in fMRI BOLD signal changes in smokers and nonsmokers during olfactory tasks.

Archival data from 25 non-demented older adults recruited from the UCSD Alzheimer's Disease Research Center who completed an Assessment Scale-Cognitive Subscale (ADAS-Cog) and functional MRI scans at 3T, acquired during performance of an odor identification task. Odor Identification (OI) measured correct (hits) or incorrect (misses) identification of odors presented by an olfactometer to deliver the odor stimuli in short, controlled durations during fMRI scanning.

fMRI data were preprocessed using fMRIprep, smoothed at 4mm, scaled, and first level analyses were conducted using 3dDeconvolve in AFNI with time points corresponding to hits and misses as regressors. Differences between smokers and nonsmokers revealed smokers show a larger difference in BOLD signal change from hits minus misses at five significant clusters (p = 0.01 with the minimum cluster size [voxels] at 42). Peak areas of significant clusters included the right precuneus, right calcarine gyrus, left inferior parietal lobule, left superior parietal lobule, and left middle occipital gyrus. Analyses suggested a greater difference in activity between hits and misses in smokers compared to nonsmokers, with more activity during hits.

Differences in activation between smokers and nonsmokers during an olfactory identification task, with greater activity in smokers during hits, suggests greater effort to correctly identify an odor. These findings of hyperactivation in areas (such as the precuneus and inferior parietal lobule) are similar to findings of hyperactivation during odor memory observed in studies of ε4 carriers during preclinical stages. Results provide further insight into smoking as a risk factor for AD. Moreover, results suggest the risk of smoking could potentially be reflected in altered activity in olfactory information processing networks in preclinical stages of AD. The study highlights the need for research to further understand the role smoking plays in the development of AD and the use of olfaction as a biomarker to aid in disease detection, prevention, and stage-associated treatments.

Despite growing evidence regarding the association between exercise training (ET) and functional brain connectivity, little is known about the effects of ET on within- and between-network functional connectivity (FC) of core brain networks. We investigated the effects of ET on within- and between-network functional connectivity of the default mode network (DMN), frontoparietal network (FPN), and salience network (SAL) in older adults with intact cognition (CN) and older adults diagnosed with mild cognitive impairment (MCI). We further examined whether the ET-induced changes in FC were associated with changes in cognitive performance.

33 older adults (78.0±7.0 years; 16 MCI and 17 CN) participated in the present study. Before and after a 12-week walking ET intervention, participants underwent cardiorespiratory fitness tests, the Controlled Oral Word Association Test (COWAT), the Rey Auditory Verbal Learning test (RAVLT), a narrative memory test (logical memory; LM), and a resting-state fMRI scan. We examined the within- and between-network connectivity of the DMN, FPN, and SAL before and after ET. We also used linear regression to examine associations between ET-related changes in the within- and between-network connectivity and cognitive function.

There were significant improvements in VO2peak, COWAT, RAVLT, and LM after ET across participants. Significant increases in within-network connectivity of the DMN and SAL were observed in response to ET across participants. FC between the DMN-FPN, DMN-SAL, and FPN-SAL were also increased after ET. Moreover, greater SAL within connectivity and FPN-SAL between connectivity were associated with enhanced LM immediate recall performance after ET. There were no significant interactions between Time (before vs after ET) and Group (CN vs MCI) for network connectivity or cognitive function.

Our findings suggest that increased within- and between-network connectivity following 12-weeks of walking exercise may subserve improvements in memory performance in older individuals with intact cognition and in those diagnosed with MCI.

Adaptive decision-making is necessary to sustain functional independence. Maladaptive decisions are among the most prevalent features of psychological and neurological disorders. One crucial aspect of decision-making involves arbitrating between exploring new avenues with risky but potentially lucrative outcomes or exploiting prior knowledge and endorsing predictable outcomes. Balancing this dichotomy creates a behavioral tension that shapes all decisions and is termed the exploration-exploitation trade-off. This trade-off has been linked to reward and affective drives and associated neural circuitry as well as neuropsychological dysfunction. However, the neural mechanisms underlying the exploration-exploitation trade-off are still uncertain, due to the scarcity of literature and the heterogeneity of paradigms. This study aimed to systematically quantify and disambiguate neuroanatomical correlates of the exploration-exploitation tradeoff in a normative adult sample. These findings provide a necessary starting point for future investigations of this fundamental aspect of decision-making across clinical populations, with potential implications for assessment and intervention.

We used the effect-location method of meta-analysis to analyze data from 10 functional neuroimaging studies investigating the exploration-exploitation tradeoff in non-clinical samples. We analyzed the location and frequency of significant neural activations across studies for both explorative and exploitative decisions and characterized them as core and non-core regions. Core activations were defined as those reported in over 50% of studies. Secondary and tertiary activations were defined as those reported in 40% and 30% of studies, respectively. The present review was conducted in accordance with the guidelines of the 2009 Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement.

The results revealed that explorative and exploitative choice behaviours differed markedly with respect to associated patterns of task-related brain activity. Exploration was associated with activity in brain regions implicated in externally directed, goal-based attentional processing and reward-related uncertainty, mainly tapping bilateral parietal and frontal circuitry, with relatively high consistency across studies. A core explorative network was revealed, consisting of activity in the frontal polar cortex, the dorsal anterior cingulate cortex, the bilateral medial frontal gyrus, the bilateral precuneus, and the bilateral intraparietal sulcus. Secondary and tertiary regions were also detected, including the bilateral anterior insula, the left precentral gyrus, the bilateral superior frontal gyrus, the right inferior frontal gyrus, the left supplementary motor area, the bilateral superior parietal lobule, and the bilateral thalamus. Exploitation was associated with brain regions implicated in internally directed processes including reward valuation, motivation, and memory. Core exploitative activations included the ventromedial prefrontal cortex, the bilateral anterior cingulate cortex, and the bilateral orbitofrontal cortex. Secondary and tertiary activations included the bilateral hippocampus, the left middle temporal gyrus, the bilateral angular gyrus, the left posterior cingulate cortex, the left superior frontal gyrus, and the bilateral superior temporal gyrus.

The exploration-exploitation trade-off provides a novel paradigmatic approach to study adaptive and maladaptive decision-making behaviour in humans. Our findings support the neural dichotomization of exploration and exploitation and illuminate potential neural networks underlying this fundamental feature of decision-making. Understanding these mechanistic networks opens a new avenue of inquiry into decision-making deficits in clinical populations, including neurodegenerative, neurodevelopmental, and neuropsychiatric syndromes.

Concussion patients frequently report increased distractibility, with more than half endorsing “concentration difficulty”. Previous studies have demonstrated impairments in maintaining attention and voluntary attentional allocation in concussion patients. However, involuntary attentional allocation (distraction) is not well understood in the context of concussion. The goal of this study was to examine distraction in acute pediatric concussion patients, monitoring frontal lobe activity using functional near-infrared spectroscopy (fNIRS) - a noninvasive measure of local hemodynamic activity - to elucidate whether post-concussion distractibility is associated with the availability of attentional control resources.

Participants included concussion patients (cases; n=19) presenting to specialty care within 28 days of injury (M=8.05, SD=5.55) and controls (n=16) presenting for reasons other than concussion. Participants were 13-17 years old (M=14.83, SD=1.10) and 57.1% female. Participants completed a computerized measure of behavioral distraction (the additional singleton paradigm) while frontal lobe activity was recorded using fNIRS 4-channel split sensor. On each trial, an array of shapes (five squares and one circle) was presented, and participants reported the orientation of a line segment inside a target shape (circle). The search array included a distractor (a square that differed in color) on 50% of trials. For each participant, the fNIR signal for epochs of each trial type (distractor present/absent) were averaged and subjected to a linear regression in which the data were fitted to a hemodynamic response function (HRF).

34 participants (19 cases, 15 controls) were included in our behavioral analysis. Reaction time (RT) was significantly slower on distractor present compared to distractor absent trials; F(1,32)=17.151, p<.001. There was no significant effect of group (case/control) on RT (F(1,32)=1.24, p=.273) or interaction between group and trial type (F(1,32)=1.05, p=.313). 29 participants (15 cases, 14 controls) were included in fNIRS analyses. The effect of group and distractor presence/absence on oxygenated hemoglobin (HbO2) was examined for each channel. A significant effect of distractor presence/absence was observed in channel 3; F(1,27)=8.510, p=.007. There were no significant effects of group or interactions between group and distractor presence/absence.

Lastly, a capture index was calculated for each participant by subtracting average RT on distractor absent trials from distractor present trials and correlated with HbO2 (beta weights averaged across trial type) for each group at each channel. No significant correlations were observed. There was a trend towards a negative correlation for case participants, particularly in channel 1, which strengthened when an outlier was removed (r=-.407, p=.149).

Reaction time and frontal lobe activity - which serves as a proxy for attentional control resources - were significantly higher when a distractor was present. Although there were no significant differences in behavioral distraction between groups, concussion patients trended towards higher levels of frontal lobe activity. Likewise, although not statistically significant, there was a trend towards a negative correlation for cases such that more attentional control resources (i.e., higher frontal lobe activity) was associated with less behavioral distraction (i.e., smaller capture index). This suggests that concussion patients may recruit more neural resources to produce comparable behavioral responses to healthy controls.

To examine the feasibility of implementing a cardiorespiratory exercise stimulus during functional Magnetic Resonance Imaging (fMRI).

12 young adults (age: 18-22 years) completed progressive maximal exercise testing and a brain MRI scan. During scanning, participants completed three runs of functional MRI (volumes = 619; TR = 800 ms; multiband = 4; voxel size = 3 mm3). During each 8 minute fMRI run, participants completed an exercise challenge consisting of alternating blocks of exercise and rest. Exercise was implemented with a cardiostepper, an MRI-compatible device (similar to a Stairmaster) capable of generating a cardiorespiratory exercise stimulus. During exercise blocks, participants stepped at a rate of 60 Hz with pedal resistance determined by participants' fitness level. Heart rate and respiration data were collected during MRI. fMRI data were processed and analyzed using FMRIB Software Library (FSL). The ARtifact Detection Toolbox (ART) software was also used to identify volumes with significant artifact, and ICA-AROMA was used to remove motion-related BOLD signal components.

During exercise blocks, heart rate increased (mean = 131 beats per minute) compared to rest (mean = 87 beats per minute; t(34) = 4.3; p < .001). The mean heart rate during exercise blocks corresponds to an exercise intensity in the light to moderate intensity range for this age group. Motion (median framewise displacement) was significantly higher during exercise (mean = .53 mm) than rest (mean = .36 mm). Across all blocks, ART classified 19.8% of brain volumes as artifact-containing outliers, with 69% of the outliers occurring during exercise blocks. Although greater head motion was observed during exercise, the use of ICA-AROMA reduced the impact of motion considerably, recovering an additional 25% of the task-related signal, relative to noise. Comparison of fMRI activity during exercise versus rest revealed significant associations with primary and supplementary motor cortices, hippocampus, and the insula, among other regions.

The current study demonstrates the feasibility of eliciting light to moderate intensity cardiorespiratory exercise (using a lower body stepping exercise) during functional MRI. Although increased head motion was observed during exercise compared to rest, the degree of head motion was roughly approximate to the values published in previous fMRI studies and post image acquisition processing improved task-related signal. During exercise, increased brain activation was observed in regions associated with the central command network, which regulates autonomic nervous system and musculoskeletal function during exercise.

Metacognition is defined as the ability to observe, monitor, and make judgments about one’s own cognitive status. Judgments of learning (JOLs) and retrospective confidence judgments (RCJs) are two elements of metacognition related to memory, or metamemory. JOLs refer to one’s assumptions of their memory performance prior to completing a memory task, while RCJs describe one’s subjective assessment of their memory performance after they have completed the task. Traumatic brain injury (TBI) is known to negatively impact general metacognitive functioning. However, the nuanced effects of TBI on constituent metacognitive subprocesses like JOLs and RCJs remain unclear. This study aimed to characterize patterns of brain activity that occur when individuals with TBI render JOLs and RCJs during a meta-memory task. Differences between JOL- and RCJ-related patterns of activation were also explored.

20 participants with moderate-to-severe TBI completed a metacognition task while undergoing functional magnetic resonance imaging (fMRI). Participants were first exposed to target slides with a set of polygons placed in specific locations, then asked to identify the target slides within a set of distractors. Before identifying the target slides, participants rated how well they believed they would remember the polygons’ shape and location (JOL). After answering, they rated how confident they were that the answer they provided was correct (RCJ). First-level time series analyses of fMRI data were conducted for each participant using FSL FEAT. Higher-level random effects modeling was then performed to assess average activation across all participants. Finally, contrasts were applied to examine and compare JOL- and RCJ-specific patterns of activation.

JOLs were associated with activation of the left frontal gyri, bilateral anterior cingulate, left insula, and right putamen (p < 0.01). RCJs were associated with activation of the bilateral frontal gyri, bilateral posterior and anterior cingulate, left insula, right putamen, and left thalamus (p < 0.01). Compared to RCJs, JOLs demonstrated greater left insula activation (p < 0.01). Compared to JOLs, RCJs demonstrated greater activation of the left superior frontal gyrus, bilateral middle frontal gyrus, and bilateral anterior cingulate (p < 0.01).

The areas of activation found in this study were consistent with structures previously identified in the broader metacognition literature. Overall, RCJs produced activity in a greater number of regions that was more bilaterally distributed compared to JOLs. Moreover, several regions that were active during both metacognitive subprocesses tended to be even more active during RCJs. A hypothesis for this observation suggests that, unlike JOLs, the additional involvement of reflecting on one’s immediate memory of completing the task during RCJs may require greater recruitment of resources compared to JOLs. Importantly, these findings suggest that, while different metacognitive subprocesses may recruit similar brain circuitry, some subprocesses may require more potent and widespread activation of this circuitry than others. As such, subprocesses with greater activational needs and complexity, such as RCJs, may be more susceptible to damage caused by TBI. Future research should aim to compare patterns of activation associated with certain metacognitive subprocesses between survivors of TBI and healthy controls.

Alzheimer’s disease (AD) pathophysiology, including β-amyloid (Aβ), can be appreciated with molecular PET imaging. Among older adults, the distribution of Aβ standard uptake value ratios (SUVR) is typically bimodal and a diagnostic cut is applied to define those who are amyloid ‘positive’ and ‘negative’. However, it is unclear whether the dynamic range of SUVRs in amyloid positive and negative individuals is meaningful and associated with cognition. Previous work by Insel and colleagues (2020) used screening data from the Anti-Amyloid Treatment in Asymptomatic Alzheimer’s (A4) trial to demonstrate subtle associations between a cortical summary SUVR and cognition, particularly on the Free and Cued Selective Reminding Test (FCSRT). We followed up this study to determine the extent to which regional SUVR is associated with performance on the FCSRT in amyloid positive and negative participants screened for participation in the A4 study.

We accessed regional Aβ SUVR, including anterior cingulate, posterior cingulate, parietal, precuneus, temporal, and medial/orbital frontal regions, along with FCSRT15 and demographic data from 4492 A4 participants at screening. Participants were coded as amyloid positive (n=1329; 30%) or amyloid negative (n=3169; 70%) based on a summary SUVR of greater than or equal to 1.15. We used separate general linear models to examine the association of total or regional SUVR, amyloid positivity status, and the interaction of SUVR and amyloid status with FCSRT scores. We compared model fits across regions with the Akaike Information Criterion (AIC). We ran post hoc correlational analyses examining the relationship between SUVR and FCSRT scores stratified by amyloid status in the case of significant interactions. Results were similar with and without demographic adjustment.

There was a significant interaction of summary and all regional SUVR with FCSRT scores in addition to main effects of amyloid positivity. In all models, there were small negative associations between SUVR and memory in amyloid positive individuals. For amyloid negative individuals, there was a significant and very small negative association between SUVR and FCSRT scores only in the parietal lobes and precuneus regions. Model fits were generally similar across the different analyses.

In this sample of individuals screened for a secondary prevention trial of AD, there were consistent associations between Aβ SUVR in all regions and memory for those considered amyloid positive. However, for individuals considered amyloid negative, there were only very small associations between SUVR and memory in parietal and precuneus regions. We conclude that the dynamic range of amyloid may be relevant among those with diagnostic evidence of amyloidosis, but that subtle Aβ accumulation in posterior regions may relate to declining memory in “subthreshold” states.

Epilepsy includes recurrent, unprovoked seizures and affects 470,000 children in the US, of which 7% have drug-resistant epilepsy due to failing two or more antiseizure medication trials. For some patients with drug-resistant epilepsy, surgery has been successful in reducing seizure burden. Functional MRI (fMRI) and intracranial mapping of neurocognitive functions, especially language, are increasingly done to assess potential functional loss from epilepsy surgery. However, these procedures vary by medical institute. The purpose of this review was to examine published literature on fMRI and intracranial mapping procedures for pediatric epilepsy surgery workup toward development of a standardized protocol that can be used across institutes as a guide to standard-of-care best practices for predicting loss of function associated with epilepsy surgery.

Our literature review includes information from 8 electronic databases for peer-reviewed, English language studies of evaluation for pediatric epilepsy surgery candidacy. Thirty-one studies were selected based on inclusion criteria. Only studies including fMRI and intracranial mapping conducted with pediatric patients being worked up for epilepsy surgery were selected.

Our review revealed that the most common task used in fMRI and intracranial mapping procedures is visual-object naming, but type of naming tasks and the way they are administered varies widely across medical institutes and includes published measures and those created on site. Variability makes examining findings across studies and designing best practice for these procedures challenging.

Creating gold-standard procedures for fMRI and intracranial mapping administration for epilepsy surgery evaluations is critical in optimizing treatment and functional outcomes for our pediatric patients. Our review is an initial step in this process.

Functional near infrared spectroscopy (fNIRS) is a form of non-invasive neuroimaging that uses light to measure changes in oxygenated and deoxygenated hemoglobin (Yucel et. al., 2021). Relative to fMRI, fNIRS is significantly cheaper and less susceptible to motion artifacts thereby enabling researchers to acquire data in more ecologically valid environments and has a higher temporal resolution that makes it well-suited for connectivity analyses (Tak and Ye, 2014). fNIRS is, however, uniquely limited by cortical anatomy. With a typical probe array having a penetrance depth of up to 3cm, the benefits of fNIRS may be limited by the neocortical atrophy that is characteristic in those with neurodegeneration. We present preliminary findings comparing fNIRS probe sensitivity in older adults diagnosed with posterior cortical atrophy (PCA) relative to cognitively intact older adults using Monte Carlo (MC) simulations. MC simulations offer probabilistic models that simulate photon movement through tissues of interest. We were particularly interested in fNIRS' sensitivity in the occipitoparietal cortices since these are regions characteristically affected in PCA.

We acquired high resolution structural (T1) MRI on 3 cognitively intact older adults and 3 individuals who received a clinical diagnosis of PCA according to Crutch et al. (2017) criteria. Individual T1 scans were preprocessed and transformed into a twodimensional (2D) surface using FreeSurfer. This continuous 2D surface was then segmented into its main tissue priors, as well as its pial surfaces. Segmented MRIs were then imported into AtlasViewer software and registered to our full head fNIRS probe array via an affine transformation. We embedded the GPU-accelerated Monte Carlo Extreme 3D light transport simulator software (Fang and Boas, 2009) into AtlasViewer which enabled us to launch 10 million photons from each optode, compared to the 1 million that AtlasViewer is set to by default, thereby providing more accurate results (Aasted et. al., 2015). We then assessed the sensitivity profile (log units), a mathematical estimate of optical density, of the inferior and superior occipital gyri, middle occipital gyrus, the superior and inferior parietal lobules, and left and right precunei.

Among the regions interrogated, five channels on our fNIRS probe were markedly different between the controls and those with PCA. Specifically, sensitivity values for channels covering the right inferior (hedges g = 8.04) and left superior occipital gyrus (hedges g = 2.46), the right inferior parietal lobule (hedges g = 8.89), and the right (hedges g = 9.43) and left (hedges g = 14.83) precunei were all markedly lower in those with PCA.

We provided preliminary evidence that the sensitivity of fNIRS appears to be markedly reduced in those with PCA. This is especially relevant for researchers using fNIRS in populations with neurodegeneration. Future work will evaluate these findings in a larger sample as well as in other neurologic conditions with the goal of helping researchers appropriately power their studies and interpret their results.

Parental history (PH) of problematic substance use has been identified as a risk factor for adolescent substance use, which can lead to increased use in adulthood. Researchers hypothesize that individuals with PH exhibit premorbid differences in their reward processing, increasing their likelihood of engaging in reward-driven behavior. Studies have shown that preadolescents with PH have greater activation in their putamen and nucleus accumbens (NA); however, most research has only investigated PH of alcohol use (PHA), not PH of drug use (PHD). Additionally, limited research has assessed whether reward processing develops differently among youth with (PH+) to youth without (PH-). The present study utilizes the national, prospective Adolescent Brain Cognitive Development SM (ABCD) Study to examine whether reward anticipation in the nucleus accumbens (NA) differs in preadolescents with and without parental substance use history and whether patterns of reward anticipation change over time during a two-year follow-up period. Further, it will also examine whether PHA and PHD predict similar activation patterns.

The current sample (N=6,600, Mage = 10.9; range = 9-13.8 years old; 46.7% female) was drawn from the national ABCD Study. To assess reward processing, the Monetary Incentive Delay Task (MID), a fMRI task-based paradigm, was administered at baseline and 2 year follow-up. The primary regions of interest (ROI) were the left and right NA and neutral vs anticipation of large rewards was the selected contrast. The Family History Assessment was used to assess problematic parental alcohol and drug use for both parents, with scores ranging from 0-2, with two indicating that both parents demonstrate problematic use. Three PH contrasts (PH- vs.PH+1, PH-vs.PH+2, & PH+1 vs. PH+2) were created for each group (PHA and PHD) (Martz et al., 2022). Separate linear mixed-effect models with predictors variables (parental contrasts, timepoint, and parental contrasts-by-time-point) and covariates (age, sex, race/ethnicity, income, parental education, parental warmth, parental monitoring, and the random effects of MRI model, family status, and subject) were run to predict reward anticipation.

Results indicated that PHA and,not PHD, was predictive of reward anticipation. PHA+1 youth showed greater activation in the l-NA (b= .02827, p= .03) and r-NA (b= .03476, p=.005), compared to PH- youth. Additionally, PHA+1 youth showed greater activation in the r-NA (b=-.07029, p=.008) compared to PHA+2 youth, but not in the l-NA. Those with PHA+2 demonstrated blunted activity in both the l-NA (b= -.07244, p=.02) and right nucleus accumbens (b= -.1091, p=001) when compared to those with PH-. No interactions with time were found.

Preadolescents with a PHA+ for both parents had blunted activity in reward anticipation, conferring a unique risk not seen in youth with only one parent with problematic alcohol use, or in youth with a PH of drug use. Future research should attempt to disentangle both genetic and environmental factors that may explain these discrepancies in reward processing, as well as the protective factors that may mitigate it. The current study found no interaction between PHA+ and time, suggesting that during preadolescents, the pattern of reward functioning remains consistent, but future work should assess if this pattern holds up across adolescence

Metacognition refers to one’s ability to make online, in-the-moment judgments regarding their own cognitive performance, and has significant implications for one’s abilities to function in daily life. It has been documented that individuals with TBI often present with metacognitive deficits, and are slower than neurotypical peers in making such judgments. Preliminary attempts have been made to determine how neural contributions to metacognitive functioning differ after injury. Studies thus far have found unique roles of prefrontal gray matter volume and inter-network connectivity in metacognitive functioning after injury, but functional activation directly associated with metacognitive processing has yet to be investigated. This event-related functional magnetic resonance imaging (fMRI) study aimed to document differences in functional activation between adults with TBI and neurotypical peers when completing metacognitive confidence judgments.

16 adults with moderate to severe TBI and 10 healthy adults (HCs) completed a metacognitive task while in the fMRI scanner. All participants were exposed to target slides with polygons arranged in various positions, then asked to identify the target slide from a group including 3 other distractor slides. Following each response, participants provided a metacognitive retrospective confidence judgment (RCJ) by rating their confidence that the answer they provided was correct. Meta d', a signal-detection based metric of metacognitive accuracy, was calculated. FSL FEAT was used for processing and analysis of the imaging data. Contrasts were created to model activation that was greater when RCJs were made compared to target recognition, mixed effects modeling was then used to investigate group differences. Cluster based thresholding set to z>2.3, p<0.01 was used for multiple comparisons correction.

Healthy controls performed significantly better on the target identification task (p<0.01), and were faster at making RCJs (p=0.03). Individuals with TBI had greater meta d’ scores (p=0.03). Significant activation beyond what was present during target recognition (RCJ>recognition) was found in left supramarginal gyrus, left posterior cingulate, and left cerebellum when individuals with TBI made RCJs, while HCs showed significant activation in the left precuneus, and bilateral superior temporal gyri. Individuals with TBI demonstrated more activation in the lateral occipital cortex bilaterally and the left cerebellum than HCs when completing RCJs. HCs presented with more activation in the left supramarginal gyrus than the TBI group when making RCJs.

The areas of activation present in both the TBI and HC groups are consistent with previous imaging findings from studies of healthy samples. Interestingly, two structures previously implicated in self-directed cognition and consciousness, the posterior cingulate and precuneus, were differentially activated by the groups. The lack of a common network between the two groups suggests that survivors may rely on separate neural substrates to facilitate metacognition after injury. The TBI group was found to recruit more functional areas when completing the RCJs. These findings, paired with the behavioral data indicating metacognitive performance differences, suggests that neural recruitment may occur after injury to allow for survivors to engage in making metacognitive judgments. Future qualitative investigations of the metacognitive judgments are needed to determine the compensatory nature of this postinjury recruitment.

PD patients commonly exhibit executive dysfunction early in the disease course which may or may not predict further cognitive decline over time. Early emergence of visuospatial and memory impairments, in contrast, are more consistent predictors of an evolving dementia syndrome. Most prior studies using fMRI have focused on mechanisms of executive dysfunction and have demonstrated that PD patients exhibit hyperactivation that is dependent on the degree of cognitive impairment, suggestive of compensatory strategies. No study has evaluated whether PD patients with normal cognition (PD-NC) and PD patients with Mild Cognitive Impairment (PD-MCI) exhibit compensatory activation patterns during visuospatial task performance.

10 PD-NC, 12 PD-MCI, and 14 age and sex-matched healthy controls (HC) participated in the study. PD participants were diagnosed with MCI based on the Movement Disorders Society Task Force, Level II assessment (comprehensive assessment). Functional magnetic resonance imaging (fMRI) was performed during a motion discrimination task that required participants to identify the direction of horizontal global coherent motion embedded within dynamic visual noise under Low and High coherence conditions. Behavioral accuracy and functional activation were evaluated using 3 * 2 analyses of covariance (ANCOVAs) (group [HC, PD-NC, PD-MCI] * Coherence [High vs. Low]) accounting for age, sex, and education. Analyses were performed in R (v4.1.2(Team, 2013)).

PD-MCI (0.702± 0.269) patients exhibited significantly lower accuracy on the motion discrimination task than HC (0.853 ± 0.241; p = 0.033) and PD-NC (0.880 ± 0.208; p =0.039). A Group * Coherence interaction was identified in which several regions, including orbitofrontal, posterior parietal and occipital cortex, showed increased activation during High relative to Low coherence trials in the PD patient groups but not in the HC group. HC showed default mode deactivation and frontal-parietal activation during Low relative to High coherence trials that was not evident in the patient groups.

PD-MCI patients exhibited worse visuospatial performance on a motion discrimination task than PD-NC and HC participants and exhibited hyperactivation of the posterior parietal and occipital regions during motion discrimination, suggesting possible compensatory activation.

Functional near-infrared spectroscopy (fNIRS) is a non-invasive functional neuroimaging method that takes advantage of the optical properties of hemoglobin to provide an indirect measure of brain activation via task-related relative changes in oxygenated hemoglobin (HbO). Its advantage over fMRI is that fNIRS is portable and can be used while walking and talking. In this study, we used fNIRS to measure brain activity in prefrontal and motor region of interests (ROIs) during single- and dual-task walking, with the goal of identifying neural correlates.

Nineteen healthy young adults [mean age=25.4 (SD=4.6) years; 14 female] engaged in five tasks: standing single-task cognition (serial-3 subtraction); single-task walking at a self-selected comfortable speed on a 24.5m oval-shaped course (overground walking) and on a treadmill; and dual-task cognition+walking on the same overground course and treadmill (8 trials/condition: 20 seconds standing rest, 30 seconds task). Performance on the cognitive task was quantified as the number of correct subtractions, number of incorrect subtractions, number of self-corrected errors, and percent accuracy over the 8 trials. Walking speed (m/sec) was recorded for all walking conditions. fNIRS data were collected on a system consisting of 16 sources, 15 detectors, and 8 short-separation detectors in the following ROIs: right and left lateral frontal (RLF, LLF), right and left medial frontal (RMF, LMF), right and left medial superior frontal (RMSF, LMSF), and right and left motor (RM, LM). Lateral and medial refer to ROIs’ relative positions on lateral prefrontal cortex. fNIRS data were analyzed in Homer3 using a spline motion correction and the iterative weighted least squares method in the general linear model. Correlations between the cognitive/speed variables and ROI HbO data were applied using a Bonferroni adjustment for multiple comparisons.

Subjects with missing cognitive data were excluded from analyses, resulting in sample sizes of 18 for the single-task cognition, dual-task overground walking, and dual-task treadmill walking conditions. During dual-task overground walking, there was a significant positive correlation between walking speed and relative change in HbO in RMSF [r(18)=.51, p<.05] and RM [r(18)=.53, p<.05)]. There was a significant negative correlation between total number of correct subtractions and relative change in HbO in LMSF ([r(18)=-.75, p<.05] and LM [r(18)=-.52, p<.05] during dual-task overground walking. No other significant correlations were identified.

These results indicate that there is lateralization of the cognitive and motor components of overground dual-task walking. The right hemisphere appears to be more active the faster people walk during the dual-task. By contrast, the left hemisphere appears to be less active when people are working faster on the cognitive task (i.e., serial-3 subtraction). The latter results suggest that automaticity of the cognitive task (i.e., more total correct subtractions) is related to decreased brain activity in the left hemisphere. Future research will investigate whether there is a change in cognitive automaticity over trials and if there are changes in lateralization patterns in neurodegenerative disorders that are known to differentially affect the hemispheres (e.g., Parkinson’s disease).

Agricultural workers are immersed in environments associated with increased risk for adverse psychiatric and neurological outcomes. Agricultural work-related risks to brain health include exposure to pesticides, heavy metals, and organic dust. Despite this, there is a gap in our understanding of the underlying brain systems impacted by these risks. This study explores clinical and cognitive domains, and functional brain activity in agricultural workers. We hypothesized that a history of agricultural work-related risks would be associated with poorer clinical and cognitive outcomes as well as changes in functional brain activity within cortico-striatal regions.

The sample comprised 17 agricultural workers and a comparison group of 45 non-agricultural workers recruited in the Northern Colorado area. All participants identified as White and non-Hispanic. The mean age of participants was 51.7 years (SD = 21.4, range 18-77), 60% identified as female, and 37% identified as male. Participants completed the National Institute of Health Toolbox (NIH Toolbox) and Montreal Cognitive Assessment (MoCA) on their first visit. During the second visit, they completed NIH Patient-Reported Outcomes Measurement Information System (PROMIS) measures and underwent functional magnetic resonance imaging (fMRI; N = 15 agriculture and N = 35 non-agriculture) while completing a working memory task (Sternberg). Blood oxygen-level dependent (BOLD) response was compared between participants. Given the small sample size, the whole brain voxel-wise group comparison threshold was set at alpha = .05, but not otherwise corrected for multiple comparisons. Cohen’s d effect sizes were estimated for all voxels.

Analyses of cognitive scores showed significant deficits in episodic memory for the agricultural work group. Additionally, the agricultural work group scored higher on measures of self-reported anger, cognitive concerns, and social participation. Analyses of fMRI data showed increased BOLD activity around the orbitofrontal cortex (medium to large effects) and bilaterally in the entorhinal cortex (large effects) for the agricultural work group. The agricultural work group also showed decreased BOLD activity in the cerebellum and basal ganglia (medium to large effects).

To our knowledge, this study provides the first-ever evidence showing differences in brain activity associated with a history of working in agriculture. These findings of poorer memory, concerns about cognitive functioning, and increased anger suggest clinical relevance. Social participation associated with agricultural work should be explored as a potential protective factor for cognition and brain health. Brain imaging data analyses showed increased activation in areas associated with motor functioning, cognitive control, and emotion. These findings are limited by small sample size, lack of diversity in our sample, and coarsely defined risk. Despite these limitations, the results are consistent with an overall concern that risks associated with agricultural work can lead to cognitive and psychiatric harm via changes in brain health. Replications and future studies with larger sample sizes, more diverse participants, and more accurately defined risks (e.g., pesticide exposure) are needed.

Functional magnetic resonance imaging (fMRI) research has generally focused on drawing conclusions from average brain activation patterns. Importantly, the brain is inherently variable; growing literature has found that within-individual blood oxygen level-dependent (BOLD) signal variability may be meaningful, and not just “noise.” For example, recent research has identified increased BOLD signal variability in healthy younger and older adults during more effortful/complex task loads of n-back paradigms, commonly used tasks that involve important elements of executive function (e.g., attention, working memory, planning, inhibition, etc.). Verbal fluency is a complex cognitive domain that also involves similar processes to generate words given certain rules. As a result, the current study builds on existing literature to investigate within-individual BOLD signal variability patterns in peak coordinates of a verbal fluency network during different loads of a letter n-back task. Due to greater executive demands, greater variability was expected during more effortful/complex n-back task loads in regions of a verbal fluency network.

Forty-eight healthy young adults (Mage(SD) = 22.41(4.47), 25 females) from the Atlanta area completed a letter n-back task in an MRI scanner. After standard processing in AFNI, images were corrected for motion and physiological artifacts, which may be confounding sources of variability. Volumes associated with each load of the letter n-back task (0-back, 1-back, 2-back, 3-back, crosshair) were identified. Task runs were normalized and respective run means were subtracted prior to concatenating all runs for each load type. Standard deviations were calculated across this mean-run corrected time series. Ten peak regions of interest (ROIs) were identified from a verbal fluency network generated from 84 peer-reviewed publications for this domain gathered on NeuroSynth. Paired samples t-tests with Benjamini-Hochberg correction for multiple comparisons were conducted to explore differences in variability during n-back task loads.

In several of the verbal fluency network ROIs, within-individual BOLD signal variability was significantly greater for 2-back versus 0-back loads with medium to large effect sizes (p’s < .001 - < .01, Cohen’s d range: .53-.93). Variability was also significantly greater for 3-back versus 0-back loads with small to medium effect sizes (p’s < .001 - < .01, Cohen’s d range: .48-.74). Specific regions that evidenced this pattern included ROIs in the left inferior frontal gyrus, left cingulate, right inferior frontal gyrus, left middle frontal gyrus, and left superior parietal lobule. Only two regions demonstrated increased variability in the 1-back load versus crosshair (left middle frontal gyrus, p < .001, d = .63; left lentiform nucleus, p < .05, d = .42). No regions demonstrated a significant difference in variability in the 0-back load versus crosshair.

This study contributes to growing literature examining within-individual BOLD signal variability in healthy individuals by exploring variability patterns in a verbal fluency network. The observed pattern of results supports the hypothesis and is in line with previous research, demonstrating that greater variability occurs with greater executive task demands. Future research can use an inscanner task of verbal fluency and can extend variability findings during this in-scanner task to out-of-scanner measures of verbal fluency.