Monday, September 16th, 2024

Time	Event
12:48p	A structural MRI marker predicts individual differences in impulsivity and classifies patients with behavioral-variant frontotemporal dementia from matched controls Impulsivity and higher preference for sooner over later rewards (i.e., delay discounting) are transdiagnostic markers of many psychiatric and neurodegenerative disorders. Yet, their neurobiological basis is still debated. Here, we aimed at 1) identifying a structural MRI signature of delay discounting in healthy adults, and 2) validating it in patients with behavioral variant frontotemporal dementia (bvFTD), a neurodegenerative disease characterized by high impulsivity. We used a machine-learning algorithm to predict individual differences in delay discounting rates based on whole-brain grey matter density maps in healthy male adults (Study 1, N=117). This resulted in a cross-validated prediction-outcome correlation of r=0.35 (p=0.0028). We tested the validity of this brain signature in an independent sample of 166 healthy adults (Study 2) and its clinical relevance in 24 bvFTD patients and 18 matched controls (Study 3). In Study 2, responses of the brain signature did not correlate significantly with discounting rates, but in both Studies 1 and 2, they correlated with psychometric measures of trait urgency, a measure of impulsivity. In Study 3, brain-based predictions correlated with discounting rates, separated bvFTD patients from controls with 81% accuracy, and were associated with the severity of disinhibition among patients. Our results suggest a new structural brain pattern, the Structural Impulsivity Signature (SIS), which predicts individual differences in impulsivity from whole-brain structure, albeit with small-to-moderate effect sizes. It provides a new brain target that can be tested in future studies to assess its diagnostic value in bvFTD and other neurodegenerative and psychiatric conditions characterized by high impulsivity. (Comment on this)
2:45p	Visual imagery of familiar people and places in category selective cortex Visual mental imagery is a dynamic process that involves a network of multiple brain regions. We used an electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) fusion approach to ask how the neural dynamics of category selective mental imagery in EEG related to activity within medial parietal, ventral temporal, and primary visual cortex (V1). Subjects attended separate EEG and fMRI sessions where they were asked to recall personally familiar people and place stimuli. The fMRI contrast of places versus people successfully replicated previous findings of category-selectivity in the medial parietal cortex during visual recall (Silson et al., 2019), as well as other regions including the ventral and lateral place memory areas, the fusiform face area, and frontal eye fields. Using multivariate decoding analysis in pre-defined fMRI regions of interest (ROIs), we tested the hypothesis that we would be able to decode individual stimuli within the preferred category for each region. This was largely the case in the ventral temporal ROIs, but a more complex pattern emerged in the medial parietal cortex; these regions represented information during imagery that was not restricted to their preferred category. EEG-fMRI fusion indicated that the timing of both medial parietal and ventral temporal involvement peaked early on during recall but did not clearly differ from each other. However, place-selective regions generally peaked earlier than people-selective regions, suggesting that representations of place stimuli evolved more quickly for these subjects. This mirrors the results from EEG stimuli decoding, where individual places were decodable earlier in time than people. In contrast, fusion correlations in V1 occurred later during the recall period, possibly reflecting the top-down progression of mental imagery from category-selective regions to primary visual cortex. (Comment on this)
2:45p	Transdiagnostic Symptom Domains are Associated with Head Motion During Multimodal Imaging in Children Background: Head motion is a challenge for neuroimaging research in developmental populations. However, it is unclear how transdiagnostic symptom domains including attention, disruptive behavior (e.g., externalizing behavior), and internalizing problems are linked to scanner motion in children, particularly across structural and functional MRI. The current study examined whether transdiagnostic domains of attention, disruptive behavior, and internalizing symptoms are associated with scanner motion in children during multimodal imaging. Methods: In a sample of 9,045 children aged 9-10 years in the Adolescent Brain Cognitive Development (ABCD) Study, logistic regression and linear mixed-effects models were used to examine associations between motion and behavior. Motion was indexed using ABCD Study quality control metrics and mean framewise displacement for the following: T1-weighted structural, resting-state fMRI, diffusion MRI, Stop-Signal Task, Monetary Incentive Delay task, and Emotional n-Back task. The Child Behavior Checklist was used as a continuous measure of symptom severity. Results: Greater attention and disruptive behavior problem severity was associated with a lower likelihood of passing motion quality control across several imaging modalities. In contrast, increased internalizing severity was associated with a higher likelihood of passing motion quality control. Increased attention and disruptive behavior problem severity was also associated with increased mean motion, whereas increased internalizing problem severity was associated with decreased mean motion. Conclusion: Transdiagnostic domains emerged as predictors of motion in youths. These findings have implications for advancing development of generalizable and robust brain-based biomarkers, computational approaches for mitigating motion effects, and enhancing accessibility of imaging protocols for children with varying symptom severities. (Comment on this)
3:18p	TRPV3 channel activity helps cortical neurons stay active during fever Fever raises body temperature (Tb) from ~37{degrees}C to beyond 38{degrees}C to combat pathogens. While generally well tolerated below 40{degrees}C, fevers can induce seizures in 2-5-year-old neurotypical children. This study investigates how neuronal activity is maintained during fever-range temperatures. Recordings of layer (L) 4-evoked spiking in L2/3 mouse somatosensory cortex show that excitatory pyramidal neurons (PNs) may remain inactive, stay active, cease activity, or initiate activity as temperature rises from 30{degrees}C (standard in electrophysiology studies) to 36{degrees}C (normal Tb) and then to 39{degrees}C (fever-range). Similar proportions of neurons cease or initiate spiking. Thus, "STAY" PNs, which remain active across temperatures changes, are crucial for maintaining stable spiking activity. STAY PNs are more prevalent at younger postnatal ages. To sustain spiking during temperature increases, STAY PNs adjust their depolarization levels to match the spike threshold while remaining temperature-insensitive in input resistance. In the striatum, STAY medium-spiny neurons are likely dopamine (D)2-type receptor-expressing and share similar characteristics with STAY PNs. Intracellular blockade of the thermosensitive channel TRPV3, but not TRPV4, significantly decreased the population of STAY PNs and reduced spiking at 39{degrees}C. Therefore, TRPV3 function may be critical for maintaining cortical activity during fever. (Comment on this)

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