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1. Neuroimmune mechanisms connecting violence with internalizing symptoms: A high‐dimensional multimodal mediation analysis

   https://doi.org/10.1002/hbm.26615  

   Butler, Ellyn R. ; Samia, Noelle ; White, Stuart ; Gratton, Caterina ; Nusslock, Robin ( February 2024 , Human Brain Mapping)

   Violence exposure is associated with worsening anxiety and depression symptoms among adolescents. Mechanistically, social defeat stress models in mice indicate that violence increases peripherally derived macrophages in threat appraisal regions of the brain, which have been causally linked to anxious behavior. In the present study, we investigate if there is a path connecting violence exposure with internalizing symptom severity through peripheral inflammation and amygdala connectivity. Two hundred and thirty‐three adolescents, ages 12–15, from the Chicago area completed clinical assessments, immune assays and neuroimaging. A high‐dimensional multimodal mediation model was fit, using violence exposure as the predictor, 12 immune variables as the first set of mediators and 288 amygdala connectivity variables as the second set, and internalizing symptoms as the primary outcome measure. 56.2% of the sample had been exposed to violence in their lifetime. Amygdala–hippocampus connectivity mediated the association between violence exposure and internalizing symptoms (, ). There was no evidence that inflammation or inflammation and amygdala connectivity in tandem mediated the association. Considering the amygdala and the hippocampus work together to encode, consolidate, and retrieve contextual fear memories, violence exposure may be associated with greater connectivity between the amygdala and the hippocampus because it could be adaptive for the amygdala and the hippocampus to be in greater communication following violence exposure to facilitate evaluation of contextual threat cues. Therefore, chronic elevations of amygdala–hippocampal connectivity may indicate persistent vigilance that leads to internalizing symptoms.

    

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2. Nod‐like receptors are critical for gut–brain axis signalling in mice

   https://doi.org/10.1113/JP278640  

   Pusceddu, Matteo M. ; Barboza, Mariana ; Keogh, Ciara E. ; Schneider, Melinda ; Stokes, Patricia ; Sladek, Jessica A. ; Kim, Hyun Jung D. ; Torres‐Fuentes, Cristina ; Goldfild, Lily R. ; Gillis, Shane E. ; et al ( November 2019 , The Journal of Physiology)

   Nucleotide binding oligomerization domain (Nod)‐like receptors regulate cognition, anxiety and hypothalamic–pituitary–adrenal axis activation.

   Nod‐like receptors regulate central and peripheral serotonergic biology.

   Nod‐like receptors are important for maintenance of gastrointestinal physiology.

   Intestinal epithelial cell expression of Nod1 receptors regulate behaviour.

   Gut–brain axis signalling is critical for maintaining health and homeostasis. Stressful life events can impact gut–brain signalling, leading to altered mood, cognition and intestinal dysfunction. In the present study, we identified nucleotide binding oligomerization domain (Nod)‐like receptors (NLR), Nod1 and Nod2, as novel regulators for gut–brain signalling. NLR are innate immune pattern recognition receptors expressed in the gut and brain, and are important in the regulation of gastrointestinal physiology. We found that mice deficient in both Nod1 and Nod2 (NodDKO) demonstrate signs of stress‐induced anxiety, cognitive impairment and depression in the context of a hyperactive hypothalamic–pituitary–adrenal axis. These deficits were coupled with impairments in the serotonergic pathway in the brain, decreased hippocampal cell proliferation and immature neurons, as well as reduced neural activation. In addition, NodDKO mice had increased gastrointestinal permeability and altered serotonin signalling in the gut following exposure to acute stress. Administration of the selective serotonin reuptake inhibitor, fluoxetine, abrogated behavioural impairments and restored serotonin signalling. We also identified that intestinal epithelial cell‐specific deletion of Nod1 (VilCre⁺Nod1^f/f), but not Nod2, increased susceptibility to stress‐induced anxiety‐like behaviour and cognitive impairment following exposure to stress. Together, these data suggest that intestinal epithelial NLR are novel modulators of gut–brain communication and may serve as potential novel therapeutic targets for the treatment of gut–brain disorders.

    

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3. Physical Activity Dynamics During a Digital Messaging Intervention Changed After the Pandemic Declaration

   https://doi.org/10.1093/abm/kaac051  

   Hojjatinia, Sahar ; Lee, Alexandra M. ; Hojjatinia, Sarah ; Lagoa, Constantino M. ; Brunke-Reese, Deborah ; Conroy, David E. ( August 2022 , Annals of Behavioral Medicine)

   The COVID-19 pandemic adversely impacted physical activity, but little is known about how contextual changes following the pandemic declaration impacted either the dynamics of people’s physical activity or their responses to micro-interventions for promoting physical activity.

   This paper explored the effect of the COVID-19 pandemic on the dynamics of physical activity responses to digital message interventions.

   Insufficiently-active young adults (18–29 years; N = 22) were recruited from November 2019 to January 2020 and wore a Fitbit smartwatch for 6 months. They received 0–6 messages/day via smartphone app notifications, timed and selected at random from three content libraries (Move More, Sit Less, and Inspirational Quotes). System identification techniques from control systems engineering were used to identify person-specific dynamical models of physical activity in response to messages before and after the pandemic declaration on March 13, 2020.

   Daily step counts decreased significantly following the pandemic declaration on weekdays (Cohen’s d = -1.40) but not on weekends (d = -0.26). The mean overall speed of the response describing physical activity (dominant pole magnitude) did not change significantly on either weekdays (d = -0.18) or weekends (d = -0.21). In contrast, there was limited rank-order consistency in specific features of intervention responses from before to after the pandemic declaration.

   Generalizing models of behavioral dynamics across dramatically different environmental contexts (and participants) may lead to flawed decision rules for just-in-time physical activity interventions. Periodic model-based adaptations to person-specific decision rules (i.e., continuous tuning interventions) for digital messages are recommended when contexts change.

    

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4. Work in Progress: Understanding Student Perceptions of Stress as part of Engineering Culture

   Cross, Kelly J. ; Jensen, Karin J. ( January 2018 , American Society of Engineering Education Conference Proceedings)

   High levels of stress and anxiety are common amongst college students, particularly engineering students. Students report lack of sleep, grades, competition, change in lifestyle, and other significant stressors throughout their undergraduate education (1, 2). Stress and anxiety have been shown to negatively impact student experience (3-6), academic performance (6-8), and retention (9). Previous studies have focused on identifying factors that cause individual students stress while completing undergraduate engineering degree programs (1). However, it not well-understood how a culture of stress is perceived and is propagated in engineering programs or how this culture impacts student levels of identification with engineering. Further, the impact of student stress has not been directly considered in engineering regarding recruitment, retention, and success. Therefore, our guiding research question is: Does the engineering culture create stress for students that hinder their engineering identity development? To answer our research question, we designed a sequential mixed methods study with equal priority of quantitative survey data and qualitative individual interviews. Our study participants are undergraduate engineering students across all levels and majors at a large, public university. Our sample goal is 2000 engineering student respondents. We combined three published surveys to build our quantitative data collection instrument, including the Depression Anxiety Stress Scales (DASS), Identification with engineering subscale, and Engineering Department Inclusion Level subscale. The objective of the quantitative instrument is to illuminate individual perceptions of the existence of an engineering stress culture (ESC) and create an efficient tool to measure the impact ESC on engineering identity development. Specifically, we seek to understand the relationships among the following constructs; 1) identification with engineering, 2) stress and anxiety, and 3) feelings of inclusion within their department. The focus of this paper presents the results of the pilot of the proposed instrument with 20 participants and a detailed data collection and analysis process. In an effort to validate our instrument, we conducted a pilot study to refine our data collection process and the results will guide the data collection for the larger study. In addition to identifying relationships among construct, the survey data will be further analyzed to specify which demographics are mediating or moderating factors of these relationships. For example, does a student’s 1st generation status influence their perception of stress or engineering identity development? Our analysis may identify discipline-specific stressors and characterize culture components that promote student anxiety and stress. Our objective is to validate our survey instrument and use it to inform the protocol for the follow-up interviews to gain a deeper understanding of the responses to the survey instrument. Understanding what students view as stressful and how students identify stress as an element of program culture will support the development of interventions to mitigate student stress. References 1. Schneider L (2007) Perceived stress among engineering students. A Paper Presented at St. Lawrence Section Conference. Toronto, Canada. Retrieved from: www. asee. morrisville. edu. 2. Ross SE, Niebling BC, & Heckert TM (1999) Sources of stress among college students. Social psychology 61(5):841-846. 3. Goldman CS & Wong EH (1997) Stress and the college student. Education 117(4):604-611. 4. Hudd SS, et al. (2000) Stress at college: Effects on health habits, health status and self-esteem. College Student Journal 34(2):217-228. 5. Macgeorge EL, Samter W, & Gillihan SJ (2005) Academic Stress, Supportive Communication, and Health A version of this paper was presented at the 2005 International Communication Association convention in New York City. Communication Education 54(4):365-372. 6. Burt KB & Paysnick AA (2014) Identity, stress, and behavioral and emotional problems in undergraduates: Evidence for interaction effects. Journal of college student development 55(4):368-384. 7. Felsten G & Wilcox K (1992) Influences of stress and situation-specific mastery beliefs and satisfaction with social support on well-being and academic performance. Psychological Reports 70(1):291-303. 8. Pritchard ME & Wilson GS (2003) Using emotional and social factors to predict student success. Journal of college student development 44(1):18-28. 9. Zhang Z & RiCharde RS (1998) Prediction and Analysis of Freshman Retention. AIR 1998 Annual Forum Paper. 

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5. Multimodal subspace identification for modeling discrete-continuous spiking and field potential population activity

   https://doi.org/10.1088/1741-2552/ad1053  

   Ahmadipour, Parima ; Sani, Omid G. ; Pesaran, Bijan ; Shanechi, Maryam M. ( March 2024 , Journal of Neural Engineering)

   Objective.Learning dynamical latent state models for multimodal spiking and field potential activity can reveal their collective low-dimensional dynamics and enable better decoding of behavior through multimodal fusion. Toward this goal, developing unsupervised learning methods that are computationally efficient is important, especially for real-time learning applications such as brain–machine interfaces (BMIs). However, efficient learning remains elusive for multimodal spike-field data due to their heterogeneous discrete-continuous distributions and different timescales.Approach.Here, we develop a multiscale subspace identification (multiscale SID) algorithm that enables computationally efficient learning for modeling and dimensionality reduction for multimodal discrete-continuous spike-field data. We describe the spike-field activity as combined Poisson and Gaussian observations, for which we derive a new analytical SID method. Importantly, we also introduce a novel constrained optimization approach to learn valid noise statistics, which is critical for multimodal statistical inference of the latent state, neural activity, and behavior. We validate the method using numerical simulations and with spiking and local field potential population activity recorded during a naturalistic reach and grasp behavior.Main results.We find that multiscale SID accurately learned dynamical models of spike-field signals and extracted low-dimensional dynamics from these multimodal signals. Further, it fused multimodal information, thus better identifying the dynamical modes and predicting behavior compared to using a single modality. Finally, compared to existing multiscale expectation-maximization learning for Poisson–Gaussian observations, multiscale SID had a much lower training time while being better in identifying the dynamical modes and having a better or similar accuracy in predicting neural activity and behavior.Significance.Overall, multiscale SID is an accurate learning method that is particularly beneficial when efficient learning is of interest, such as for online adaptive BMIs to track non-stationary dynamics or for reducing offline training time in neuroscience investigations.

    

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