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Abstract This study examines neural mechanisms of negative overgeneralization, the increased likelihood of generalizing negative information, in peri-puberty. Theories suggest that weak pattern separation [overlapping representations are made distinct, indexed by dentate gyrus/ cornu ammonis (CA)3 hippocampal subfield activation] underlies negative overgeneralization. We alternatively propose that neuro-maturational changes that favor pattern completion (cues reinstate stored representations, indexed by CA1 activation) are modulated by circuitry involved in emotional responding [amygdala, medial prefrontal cortices (mPFC)] to drive negative overgeneralization. Youth (n = 34, 9–14 years) recruited from community and clinic settings participated in an emotional mnemonic similarity task while undergoing magnetic resonance imaging. At study, participants indicated the valence of images; at test, participants made recognition memory judgments. Critical lure stimuli, which were similar to images at study, were presented at test, and errors (‘false alarms’) to negative relative to neutral stimuli reflected negative overgeneralization. Negative overgeneralization was related to greater and more similar patterns of activation in CA1 and both dorsal mPFC (dmPFC)and ventral mPFC (vmPFC) for negative relative to neutral stimuli. At study, amygdala exhibited greater functional coupling with CA1 and dmPFC during negative items that were later generalized. Negative overgeneralization is rooted in amygdala and mPFC modulation at encoding and pattern completion at retrieval.

Sleep-related problems often precede escalating anxiety in early adolescence. Pushing beyond broad sleep-mental health associations and toward mechanistic theories of their interplay can inform etiological models of psychopathology. Recent studies suggest that sleep depotentiates neural (e.g., amygdala) reactivity during reexposure to negative emotional stimuli in adults. Persistent amygdala reactivity to negative experiences and poor sleep characterize anxiety, particularly at the transition to adolescence. We propose that sleep depotentiates amygdala reactivity in youth but fails to do so among youth with anxiety. Participants (n = 34; 18 males; age, mean [ M ] = 11.35, standard deviation [ SD ] = 2.00) recruited from the community and specialty anxiety clinics viewed valenced images (positive, negative, and neutral) across two fMRI sessions (Study, Test), separated by a 10–12-hour retention period of sleep or wake (randomized). Mixed linear models regressed basolateral amygdala (BLA) activation and BLA-medial prefrontal cortex (mPFC) functional connectivity to negative images on Time, Condition, and Anxiety Severity. There were greater reductions in BLA activations to negative target images from Study to Test in the Sleep Condition, which was blunted with higher anxiety ( b = −0.065, z = −2.355, p = 0.019). No such sleep- or anxiety-related effects were observed for BLA-mPFC functional connectivity ( p s > 0.05). Sleep supports depotentiation of amygdala reactivity to negative stimuli in youth, but this effect is blunted at higher levels of anxiety. Disruptions in sleep-related affective habituation may be a critical, modifiable driver of anxiety.

Diffusion Weighted Imaging is a tool that can non-invasively provide insights into the microstructure of a given brain region. Various advanced techniques exist within the diffusion weighted imaging space that each provide valuable insights into different aspects of microstructure. In the following study, we sought to examine whether the combination of derived diffusion metrics (tensors, neurite orientation dispersion and density imaging (NODDI), and mean apparent propagator (MAP) MRI) in grey-matter regions could reliably predict cognitive performance in older adults, and whether these findings were replicable across datasets. First, we demonstrated that all combinations of diffusion metrics could reliably determine participant characteristics and were significant predictors of age. Second, we found that a combination of Tensor, NODDI, and MAP-MRI metrics within the hippocampus could predict RAVLT performance in older adults above and beyond any combination of two metrics alone. We also found these diffusion metrics were able to reliably predict RAVLT performance, but not Trails B or Digit Symbol Substitution Task performance. We also found that these same combinations of metrics could predict working memory performance, but not memory performance within a region associated with working memory (Brodmann Areas 9 and 46). Taken together, these findings indicate that these diffusion metrics provide valuable information on grey-matter microstructure independent of one another, and that the ability to obtain both NODDI and MAP-MRI based information from multi-shell diffusion scans more than justifies the added length.

The FLASH effect expands the therapeutic ratio of tumor control to normal tissue toxicity observed after delivery of ultra-high (>100 Gy/s FLASH-RT) vs. conventional dose rate radiation (CONV-RT). In this first exploratory study, we assessed whether ex-vivo Magnetic Resonance Imaging (MRI) could reveal long-term differences after FLASH-RT and CONV-RT whole-brain irradiation. Female C57BL/6 mice were divided into three groups: control (non-irradiated), conventional (CONV-RT 0.1 Gy/s), and ultra-high dose rates (FLASH-RT 1 pulse, 5.5 × 10^6 Gy/s), and received 10 Gy of whole-brain irradiation in a single fraction at 10 weeks of age. Mice were evaluated by Novel Object Recognition cognitive testing at 10 months post-irradiation and were sampled at 13 months post-irradiation. Ex-vivo brains were imaged with a 14.1 Tesla/26 cm magnet with a multimodal MRI protocol, including T2-weighted TurboRare (T2W) and diffusion-weighted imaging (DWI) sequences. In accordance with previous results, cognitive tests indicated that animals receiving CONV-RT exhibited a decline in cognitive function, while FLASH-RT performed similarly to the controls. MRI showed decreased hippocampal mean intensity in the CONV-RT mice compared to controls but not in the FLASH-RT group. Comparing CONV-RT to control, we found significant changes in multiple whole-brain diffusion metrics, including the mean Apparent Diffusion Coefficient (ADC) and Mean Apparent Propagator (MAP) metrics. By contrast, no significant diffusion changes were found between the FLASH-RT and control groups. In an exploratory analysis compared to controls, regional diffusion metrics were primarily altered in the basal forebrain and the insular cortex after CONV-RT, and after FLASH-RT, a trend reduction was also observed. This study presents initial evidence that MRI can uncover clear changes in the brain after CONV-RT but not after FLASH-RT. The MRI results aligned with the observed cognitive protection after FLASH-RT, indicating the potential use of MRI to analyze the FLASH response.

The rise of large neuroimaging datasets and multi-dataset mega-analyses brings the power to study interindividual differences in brain structure and function on a heretofore unseen scale. However, unknown and poorly characterized intra-individual variability continues to undermine the detection of robust brain-behavior associations and, ultimately, our understanding of the brain on the whole. Women’s and reproductive health underlie variability in more than half of the population, but have long been overlooked in the study of both inter- and intra-individual differences in the brain. To this end, the Dense Investigation of Variability in Affect (DIVA) Study was designed to study intra-individual variability in the brain and behavior across the menstrual cycle in a small cohort of premenopausal female participants. The DIVA Study acquired weekly actigraphy, self-report, biospecimen, and both functional and structural magnetic resonance imaging data with concurrent peripheral physiological recordings. These data facilitate the study of several common sources of variability in the brain and behavior: the menstrual cycle and ovarian hormones, sleep, stress, exercise, and exogenous sources of hemodynamic variability.

Abstract The hippocampal formation (HF) facilitates the creation of declarative memories, with subfields providing unique contributions to the discriminability and generalizability of events. The HF itself and its connections with other structures exhibit a protracted development. Maturational differences across subfields facilitate a shift towards memory specificity, with peri-puberty sitting at the inflection point. Peri-puberty also happens to be a sensitive period in the development of anxiety disorders. Taken together, we believe HF development is critical to negative overgeneralization, a common feature of anxiety disorders. To investigate the role of the HF in behavioral discrimination and generalization we examined the relation between behavior and cross-sectional indices of HF maturity derived from subfield volume. Participants aged 9-14 years, recruited from clinical and community sources, performed a recognition task with emotionally valent (positive, negative) and neutral images. T1-weighted and diffusion-weighted structural scans were collected. Partial least squares correlations were used to derive a singular metric of maturity for both HF volume and structural connectivity. We found our volumetric HF maturity index was positively associated with discrimination for neutral images and generalization for negative images. Hippocampal-medial prefrontal cortex structural connectivity maturity metric evidenced a similar trend with behavior as the HF volumetric approach. These findings are important because they reflect a novel developmentally related balance between discrimination and generalization behavior supported by the hippocampus and its connections with other regions. Maturational shifts in this balance may contribute to negative overgeneralization, a common feature of anxiety disorders that escalates during the same developmental window. Significance Statement The hippocampal formation (HF) facilitates declarative memory specificity and is composed of subfields whose development during adolescence overlaps with the onset of anxiety disorders. Aberrations in mechanisms governing memory specificity may contribute to negative overgeneralization in anxious youth. Participants completed an emotional memory discrimination task while in the scanner. Using a multivariate maturity metric based on subfield volume we found individuals with more “mature” HF were better at differentiating similar neutral images and more likely to generalize similar negative images. These findings are important because they capture a novel developmental mechanism related to the balance between discrimination and generalization. Shifts in this balance, may contribute to negative overgeneralization, a common feature of anxiety disorders. Competing Interest Statement The authors have declared no competing interest.

ABSTRACT BACKGROUND This study examines neural mechanisms of negative overgeneralization in peri-puberty to identify potential contributors to escalating anxiety during this sensitive period. Theories suggest that weak pattern separation (a neurocomputational process by which overlapping representations are made distinct, indexed by DG/CA3 hippocampal subfields) is a major contributor to negative overgeneralization. We alternatively propose that neuromaturation related to generalization and anxiety-related pathology in peri-puberty predicts contributions from strong pattern completion (a partial match of cues reinstates stored representations, indexed by CA1) and related modulatory mechanisms (amygdala, medial prefrontal cortices [mPFC]). METHODS Youth (N=34, 9-14 years) recruited from community and clinic settings participated in an emotional mnemonic similarity task while undergoing MRI. At Study, participants indicated the valence of images; at Test, participants made an ‘old/new’ recognition memory judgment. Critical lure stimuli, that were similar but not the same as images from Study, were presented at Test, and errors (“false alarms”) to negative relative to neutral stimuli reflected negative overgeneralization. Univariate, multivariate, and functional connectivity analyses were performed to evaluate mechanisms of negative overgeneralization. RESULTS Negative overgeneralization was related to greater and more similar patterns of activation in CA1 and both dorsal and ventral mPFC for negative relative to neutral stimuli. At Study, amygdala increased functional coupling with CA1 and dorsal mPFC during negative items that were later generalized. CONCLUSIONS Negative overgeneralization is rooted in amygdala and mPFC modulation at encoding and pattern completion at retrieval. These mechanisms could prove to reflect etiological roots of anxiety that precede symptom escalation across adolescence. Competing Interest Statement The authors have declared no competing interest.

Lung cancer is the leading cause of cancer-related death in the United States. Here, we evaluated the potential clinical utility of soluble human epidermal growth factor receptor 2 (sHER2) for the risk assessment, screening, and diagnosis of non-small cell lung cancer (NSCLC) using an unmatched case-control study design. Serum sHER2 concentrations were measured by immunoassay in 244 primary NSCLC cases and 218 healthy controls. Wilcoxon rank-sum tests, logistic regression models, and receiver operating characteristic plots were used to assess whether sHER2 is associated with lung cancer. Median serum sHER2 concentrations are higher in patients with adenocarcinoma than squamous cell carcinoma regardless of gender, and sHER2 is a weak, independent biomarker of adenocarcinoma, but not of squamous cell carcinoma, adjusted for age and gender. The age-adjusted relative risk (odds) of adenocarcinoma is 3.95 (95% CI: 1.22, 12.81) and 7.93 (95% CI: 2.26, 27.82) greater for women and men with high sHER2 concentrations (≥6.60 ng/mL) vs. low sHER2 concentrations (≤1.85 ng/mL), respectively. When adjusted for each other, sHER2, age, and gender discern healthy controls from patients with primary adenocarcinomas of the lung with 85.9% accuracy. We conclude that even though serum sHER2 is not a strong, stand-alone discriminatory biomarker of adenocarcinoma, sHER2 may be a useful, independent covariate in multivariate risk assessment, screening, and diagnostic models of lung cancer.