Gendered Citation Practices in the Field of Communication

Measurement and Assessment of Head-to-Helmet Contact Forces

PURPOSE

To evaluate the population variation in head-to-helmet contact forces in helmet users.

METHODS

Four different size Kevlar composite helmets were instrumented with contact pressure sensors and chinstrap tension meters. A total number of 89 volunteers (25 female and 64 male volunteers) participated in the study. The length, width, and circumference of their heads were measured and each volunteer was assigned a helmet size. Volunteers were asked to wear the helmet in three different configurations and the chinstrap tension and contact force between the head and each of the seven interior pads were recorded.

RESULTS

The majority of forces measured on any individual pad were between 0 and 5 N. However, some users exhibited pressure points with forces as high as 30 N. The contact force distribution is non-uniform across the interior of the helmet, with the largest force concentrated at the front. Head shape is a major driver of the observed contact force. There was a statistically significant difference between female and male volunteers, and between groups with different experience levels.

CONCLUSIONS

The fit of helmet systems is highly subject specific. The current metrics used to assign helmet sizes may not accurately predict correct helmet fit.

Network structure influences the strength of learned neural representations

From sequences of discrete events, humans build mental models of their world. Referred to as graph learning, the process produces a model encoding the graph of event-to-event transition probabilities. Recent evidence suggests that some networks are easier to learn than others, but the neural underpinnings of this effect remain unknown. Here we use fMRI to show that even over short timescales the network structure of a temporal sequence of stimuli determines the fidelity of event representations as well as the dimensionality of the space in which those representations are encoded: when the graph was modular as opposed to lattice-like, BOLD representations in visual areas better predicted trial identity and displayed higher intrinsic dimensionality. Broadly, our study shows that network context influences the strength of learned neural representations, motivating future work in the design, optimization, and adaptation of network contexts for distinct types of learning.

Heritability of movie-evoked brain activity and connectivity

The neural bases of sensory processing are conserved across people, but no two individuals experience the same stimulus in exactly the same way. Recent work has established that the idiosyncratic nature of subjective experience is underpinned by individual variability in brain responses to sensory information. However, the fundamental origins of this individual variability have yet to be systematically investigated. Here, we establish a genetic basis for individual differences in sensory processing by quantifying (1) the heritability of high-dimensional brain responses to movies and (2) the extent to which this heritability is grounded in lower-level aspects of brain function. Specifically, we leverage 7T fMRI data collected from a twin sample to first show that movie-evoked brain activity and connectivity patterns are heritable across the cortex. Next, we use hyperalignment to decompose this heritability into genetic similarity in where vs. how sensory information is processed. Finally, we show that the heritability of brain activity patterns can be partially explained by the heritability of the neural timescale, a one-dimensional measure of local circuit functioning. These results demonstrate that brain responses to complex stimuli are heritable, and that this heritability is due, in part, to genetic control over stable aspects of brain function.

Gender Imbalance in Citation Practices in Communication Sciences and Disorders Before and During the COVID-19 Pandemic

PURPOSE

Despite recent advances, gender inequality remains a major concern within the workforce. One manifestation of gender inequality in academia is the undercitation of women-authored compared to men-authored papers that is thought to reflect implicit biases and has important implications for the academic advancement for research-intensive female faculty. These studies largely stem from male-dominant professions. Thus, in this study, we investigated gendered citation practices within communication sciences and disorders (CSD), a female-dominant discipline. We also examined the impacts of the COVID-19 pandemic as an exogenous driver of short-term change in publication and citation practices in CSD.

METHOD

Using methods from Dworkin et al. (2020), we characterized expected versus actual man first/man last-authored (MM), man first/woman last-authored (MW), woman first/man last-authored (WM), and woman first/woman last-authored (WW) articles published within a 24-year time span in the four American Speech-Language-Hearing Association journals. We compared gendered publication and citation practices in the 10 years before (2010-2019) to during (August 2020-November 2022) the COVID-19 pandemic.

RESULTS

Across journals, we found WW publications increased while MM publications decreased from 1998 to 2022. We found a pattern of overcitation of WW papers and undercitation of MM papers, which was driven primarily by the citation practices of WM and WW teams. These citation trends were found for the years before and during the pandemic and remained when controlling for relevant paper characteristics and author and paper network variables.

CONCLUSIONS

Consistent with our predictions, we found gender-based citation imbalances that aligned with the gender distributions of CSD, like other fields. The findings align with the notion of homophily (i.e., like attracts like). We review the findings within the context of citation research from other fields as well as discuss the larger implications of these patterns for professional practices in CSD.

Citation bias, diversity, and ethics

How often a researcher is cited usually plays a decisive role in that person's career advancement, because academic institutions often use citation metrics, either explicitly or implicitly, to estimate research impact and productivity. Research has shown, however, that citation patterns and practices are affected by various biases, including the prestige of the authors being cited and their gender, race, and nationality, whether self-attested or perceived. Some commentators have proposed that researchers can address biases related to social identity or position by including a Citation Diversity Statement in a manuscript submitted for publication. A Citation Diversity Statement is a paragraph placed before the reference section of a manuscript in which the authors address the diversity and equitability of their references in terms of gender, race, ethnicity, or other factors and affirm a commitment to promoting equity and diversity in sources and references. The present commentary considers arguments in favor of Citation Diversity Statements, and some practical and ethical issues that these statements raise.

Gender differences in representation, citations, and h-index: An empirical examination of the field of communication across the ten most productive countries

Women researchers have been shown to be underrepresented in science, especially among the most productive scholars. This is especially relevant in the social sciences and humanities fields, where gender parity is closer, but disparities among top scholars are still pronounced. The gender gap in the field of communication has been explored from several approaches, but studies focusing on gender differences in representation, citations, and h-index are rather scarce. Drawing upon data retrieved from SciVal, we conducted a comparative study of the top 500 and top 100 most productive scholars (N = 5000) for each of the ten most productive countries in communication research in the 2019-2022 period: the United States, the United Kingdom, China, Spain, Germany, India, Australia, Canada, Italy, and the Netherlands. The results indicate a consistent underrepresentation of women, particularly among the top 500, across countries. Despite women being cited more frequently than men in some countries over shorter time frames, a gender bias persists favoring men, particularly when considering the h-index. All in all, our study shows that, despite hints of gender equality in citation patterns, the gender gap still constitutes a structural part of the field of communication when addressing gender representation in research productivity and long-term dynamics of research impact.

Rapid eye and hand responses in an interception task are differentially modulated by context-dependent predictability

When catching a falling ball or avoiding a collision with traffic, humans can quickly generate eye and limb responses to unpredictable changes in their environment. Mechanisms of limb and oculomotor control when responding to sudden changes in the environment have mostly been investigated independently. Here, we investigated eye-hand coordination in a rapid interception task where human participants used a virtual paddle to intercept a moving target. The target moved vertically down a computer screen and could suddenly jump to the left or right. In high-certainty blocks, the target always jumped; in low-certainty blocks, the target only jumped in a portion of the trials. Further, we manipulated response urgency by varying the time of target jumps, with early jumps requiring less urgent responses and late jumps requiring more urgent responses. Our results highlight differential effects of certainty and urgency on eye-hand coordination. Participants initiated both eye and hand responses earlier for high-certainty compared with low-certainty blocks. Hand reaction times decreased and response vigor increased with increasing urgency levels. However, eye reaction times were lowest for medium-urgency levels and eye vigor was unaffected by urgency. Across all trials, we found a weak positive correlation between eye and hand responses. Taken together, these results suggest that the limb and oculomotor systems use similar early sensorimotor processing; however, rapid responses are modulated differentially to attain system-specific sensorimotor goals.

Architectural styles of curiosity in global Wikipedia mobile app readership

Intrinsically motivated information seeking is an expression of curiosity believed to be central to human nature. However, most curiosity research relies on small, Western convenience samples. Here, we analyze a naturalistic population of 482,760 readers using Wikipedia's mobile app in 14 languages from 50 countries or territories. By measuring the structure of knowledge networks constructed by readers weaving a thread through articles in Wikipedia, we replicate two styles of curiosity previously identified in laboratory studies: the nomadic "busybody" and the targeted "hunter." Further, we find evidence for another style-the "dancer"-which was previously predicted by a historico-philosophical examination of texts over two millennia and is characterized by creative modes of knowledge production. We identify associations, globally, between the structure of knowledge networks and population-level indicators of spatial navigation, education, mood, well-being, and inequality. These results advance our understanding of Wikipedia's global readership and demonstrate how cultural and geographical properties of the digital environment relate to different styles of curiosity.

Prenatal environment is associated with the pace of cortical network development over the first three years of life

Environmental influences on brain structure and function during early development have been well-characterized, but whether early environments are associated with the pace of brain development is not clear. In pre-registered analyses, we use flexible non-linear models to test the theory that prenatal disadvantage is associated with differences in trajectories of intrinsic brain network development from birth to three years (n = 261). Prenatal disadvantage was assessed using a latent factor of socioeconomic disadvantage that included measures of mother's income-to-needs ratio, educational attainment, area deprivation index, insurance status, and nutrition. We find that prenatal disadvantage is associated with developmental increases in cortical network segregation, with neonates and toddlers with greater exposure to prenatal disadvantage showing a steeper increase in cortical network segregation with age, consistent with accelerated network development. Associations between prenatal disadvantage and cortical network segregation occur at the local scale and conform to a sensorimotor-association hierarchy of cortical organization. Disadvantage-associated differences in cortical network segregation are associated with language abilities at two years, such that lower segregation is associated with improved language abilities. These results shed light on associations between the early environment and trajectories of cortical development.

Cannabis and opioid perceptions, co-use, and substitution among patients across 4 NCI-Designated Cancer Centers

Prescription opioids are used for managing pain in persons with cancer, however, there are socioeconomic and racial disparities in medication access. Cannabis is increasingly used for cancer symptom management and as an opioid alternative. Limited data are available about patterns of opioid and cannabis use among patients with cancer. We used survey data from 4 National Cancer Institute-designated cancer centers in 3 states (n = 1220) to assess perceptions, use of cannabis and opioids for pain, their substitution, and racial and ethnic differences in each outcome. Compared with White patients, Black patients were less likely to use opioids for pain (odds ratio [OR] = 0.66; P = .035) and more likely to report that cannabis was more effective than opioids (OR = 2.46; P = .03). Race effects were mitigated (P > .05) after controlling for socioeconomic factors. Further research is needed to understand cannabis and opioid use patterns and how overlapping social determinants of health create a disadvantage in cancer symptom management for Black patients.

The relationship between event boundary strength and pattern shifts across the cortical hierarchy during naturalistic movie-viewing

Our continuous experience is spontaneously segmented by the brain into discrete events. However, the beginning of a new event (an event boundary) is not always sharply identifiable: phenomenologically, event boundaries vary in salience. How are the response profiles of cortical areas at event boundaries modulated by boundary strength during complex, naturalistic movie-viewing? Do cortical responses scale in a graded manner with boundary strength, or do they merely detect boundaries in a binary fashion? We measured "cortical boundary shifts" as transient changes in multi-voxel patterns at event boundaries with different strengths (weak, moderate, and strong), determined by across-subject agreement. Cortical regions with different processing timescales were examined. In auditory areas, which have short timescales, cortical boundary shifts exhibited a clearly graded profile both in group-level and individual-level analyses. In cortical areas with long timescales, including the default mode network, boundary strength modulated pattern shift magnitude at the individual subject level. We also observed a positive relationship between boundary strength and the extent of temporal alignment of boundary shifts across different levels of the cortical hierarchy. Additionally, hippocampal activity was highest at event boundaries for which cortical boundary shifts were most aligned across hierarchical levels. Overall, we found that event boundary strength modulated cortical pattern shifts strongly in sensory areas and more weakly in higher-level areas, and that stronger boundaries were associated with greater alignment of these shifts across the cortical hierarchy.

Breaking reflection symmetry: evolving long dynamical cycles in Boolean systems

In interacting dynamical systems, specific local interaction rules for system components give rise to diverse and complex global dynamics. Long dynamical cycles are a key feature of many natural interacting systems, especially in biology. Examples of dynamical cycles range from circadian rhythms regulating sleep to cell cycles regulating reproductive behavior. Despite the crucial role of cycles in nature, the properties of network structure that give rise to cycles still need to be better understood. Here, we use a Boolean interaction network model to study the relationships between network structure and cyclic dynamics. We identify particular structural motifs that support cycles, and other motifs that suppress them. More generally, we show that the presence of dynamical reflection symmetry in the interaction network enhances cyclic behavior. In simulating an artificial evolutionary process, we find that motifs that break reflection symmetry are discarded. We further show that dynamical reflection symmetries are over-represented in Boolean models of natural biological systems. Altogether, our results demonstrate a link between symmetry and functionality for interacting dynamical systems, and they provide evidence for symmetry's causal role in evolving dynamical functionality.

Gender imbalances in the editorial activities of a selective journal run by academic editors

The fairness of decisions made at various stages of the publication process is an important topic in meta-research. Here, based on an analysis of data on the gender of authors, editors and reviewers for 23,876 initial submissions and 7,192 full submissions to the journal eLife, we report on five stages of the publication process. We find that the board of reviewing editors (BRE) is men-dominant (69%) and that authors disproportionately suggest male editors when making an initial submission. We do not find evidence for gender bias when Senior Editors consult Reviewing Editors about initial submissions, but women Reviewing Editors are less engaged in discussions about these submissions than expected by their proportion. We find evidence of gender homophily when Senior Editors assign full submissions to Reviewing Editors (i.e., men are more likely to assign full submissions to other men (77% compared to the base assignment rate to men RE of 70%), and likewise for women (41% compared to women RE base assignment rate of 30%))). This tendency was stronger in more gender-balanced scientific disciplines. However, we do not find evidence for gender bias when authors appeal decisions made by editors to reject submissions. Together, our findings confirm that gender disparities exist along the editorial process and suggest that merely increasing the proportion of women might not be sufficient to eliminate this bias. Measures accounting for women's circumstances and needs (e.g., delaying discussions until all RE are engaged) and raising editorial awareness to women's needs may be essential to increasing gender equity and enhancing academic publication.

Smokers' Curiosity Facilitates Recall of Tobacco-Related Health Information

Curiosity promotes learning. Two open questions concern the extent to which tobacco smokers exhibit curiosity about smoking-related health information and whether this curiosity can facilitate recall of this information. Participants (n = 324 smokers; n = 280 nonsmokers) performed a Trivia Guessing Task wherein participants guessed the answers to general trivia and smoking-related trivia questions and provided ratings of their curiosity prior to viewing the answers to the questions. A subset of participants (n = 121 smokers; n = 97 nonsmokers) completed a surprise Trivia Memory Task one-week later and answered the previously-viewed questions. Results indicate that smokers are no less curious about smoking-related trivia than they are about general trivia and that curiosity about the answer to smoking-related trivia is associated with more accurate recall of smoking-related trivia answers one week later. Findings suggest that engendering states of curiosity for smoking-related information may facilitate retention of that information in smokers.

Network models to enhance the translational impact of cross-species studies

Neuroscience studies are often carried out in animal models for the purpose of understanding specific aspects of the human condition. However, the translation of findings across species remains a substantial challenge. Network science approaches can enhance the translational impact of cross-species studies by providing a means of mapping small-scale cellular processes identified in animal model studies to larger-scale inter-regional circuits observed in humans. In this Review, we highlight the contributions of network science approaches to the development of cross-species translational research in neuroscience. We lay the foundation for our discussion by exploring the objectives of cross-species translational models. We then discuss how the development of new tools that enable the acquisition of whole-brain data in animal models with cellular resolution provides unprecedented opportunity for cross-species applications of network science approaches for understanding large-scale brain networks. We describe how these tools may support the translation of findings across species and imaging modalities and highlight future opportunities. Our overarching goal is to illustrate how the application of network science tools across human and animal model studies could deepen insight into the neurobiology that underlies phenomena observed with non-invasive neuroimaging methods and could simultaneously further our ability to translate findings across species.

Prenatal environment is associated with the pace of cortical network development over the first three years of life

Environmental influences on brain structure and function during early development have been well-characterized. In pre-registered analyses, we test the theory that socioeconomic status (SES) is associated with differences in trajectories of intrinsic brain network development from birth to three years (n = 261). Prenatal SES is associated with developmental increases in cortical network segregation, with neonates and toddlers from lower-SES backgrounds showing a steeper increase in cortical network segregation with age, consistent with accelerated network development. Associations between SES and cortical network segregation occur at the local scale and conform to a sensorimotor-association hierarchy of cortical organization. SES-associated differences in cortical network segregation are associated with language abilities at two years, such that lower segregation is associated with improved language abilities. These results yield key insight into the timing and directionality of associations between the early environment and trajectories of cortical development.

Network structure influences the strength of learned neural representations

Human experience is built upon sequences of discrete events. From those sequences, humans build impressively accurate models of their world. This process has been referred to as graph learning, a form of structure learning in which the mental model encodes the graph of event-to-event transition probabilities [1], [2], typically in medial temporal cortex [3]-[6]. Recent evidence suggests that some network structures are easier to learn than others [7]-[9], but the neural properties of this effect remain unknown. Here we use fMRI to show that the network structure of a temporal sequence of stimuli influences the fidelity with which those stimuli are represented in the brain. Healthy adult human participants learned a set of stimulus-motor associations following one of two graph structures. The design of our experiment allowed us to separate regional sensitivity to the structural, stimulus, and motor response components of the task. As expected, whereas the motor response could be decoded from neural representations in postcentral gyrus, the shape of the stimulus could be decoded from lateral occipital cortex. The structure of the graph impacted the nature of neural representations: when the graph was modular as opposed to lattice-like, BOLD representations in visual areas better predicted trial identity in a held-out run and displayed higher intrinsic dimensionality. Our results demonstrate that even over relatively short timescales, graph structure determines the fidelity of event representations as well as the dimensionality of the space in which those representations are encoded. More broadly, our study shows that network context influences the strength of learned neural representations, motivating future work in the design, optimization, and adaptation of network contexts for distinct types of learning over different timescales.

Curiosity, Surprise, and the Recall of Tobacco-Related Health Information in Adolescents

A key goal of health communications designed to prevent smoking initiation during adolescence is for the tobacco-related information to be retained in memory beyond immediate message exposure. Here, we test the role for epistemic emotions, specifically curiosity and surprise, in facilitating memory for tobacco-related health information. Participants (n = 294 never-smoking adolescents, ages 14-16 years) performed a trivia guessing task wherein they guessed the answers to general trivia and smoking-related trivia questions. A subset of participants (n = 154) completed a surprise trivia memory task one week later and answered the previously viewed questions. Results indicate that curiosity about the answers to smoking-related trivia is associated with more accurate recall of smoking-related trivia answers one week later. Surprise also facilitated memory for smoking-related trivia, but the association was limited to cases where confidence in prior knowledge was low. Indeed, when participants had high confidence in their prior knowledge, surprise about the answer to trivia questions was associated with worse recall. Findings suggest that engendering states of curiosity for smoking-related information may facilitate retention of that information in never-smoking adolescents and highlight the need to examine both surprise and confidence in health communications to avoid low message recall.

Quantifying trial-by-trial variability during cortico-cortical evoked potential mapping of epileptogenic tissue

OBJECTIVE

Measuring cortico-cortical evoked potentials (CCEPs) is a promising tool for mapping epileptic networks, but it is not known how variability in brain state and stimulation technique might impact the use of CCEPs for epilepsy localization. We test the hypotheses that (1) CCEPs demonstrate systematic variability across trials and (2) CCEP amplitudes depend on the timing of stimulation with respect to endogenous, low-frequency oscillations.

METHODS

We studied 11 patients who underwent CCEP mapping after stereo-electroencephalography electrode implantation for surgical evaluation of drug-resistant epilepsy. Evoked potentials were measured from all electrodes after each pulse of a 30 s, 1 Hz bipolar stimulation train. We quantified monotonic trends, phase dependence, and standard deviation (SD) of N1 (15-50 ms post-stimulation) and N2 (50-300 ms post-stimulation) amplitudes across the 30 stimulation trials for each patient. We used linear regression to quantify the relationship between measures of CCEP variability and the clinical seizure-onset zone (SOZ) or interictal spike rates.

RESULTS

We found that N1 and N2 waveforms exhibited both positive and negative monotonic trends in amplitude across trials. SOZ electrodes and electrodes with high interictal spike rates had lower N1 and N2 amplitudes with higher SD across trials. Monotonic trends of N1 and N2 amplitude were more positive when stimulating from an area with higher interictal spike rate. We also found intermittent synchronization of trial-level N1 amplitude with low-frequency phase in the hippocampus, which did not localize the SOZ.

SIGNIFICANCE

These findings suggest that standard approaches for CCEP mapping, which involve computing a trial-averaged response over a .2-1 Hz stimulation train, may be masking inter-trial variability that localizes to epileptogenic tissue. We also found that CCEP N1 amplitudes synchronize with ongoing low-frequency oscillations in the hippocampus. Further targeted experiments are needed to determine whether phase-locked stimulation could have a role in localizing epileptogenic tissue.

Angiotensin II Increases Oxidative Stress and Inflammation in Female, But Not Male, Endothelial Cells

Introduction

Women are at elevated risk for certain cardiovascular diseases, including pulmonary arterial hypertension, Alzheimer's disease, and vascular complications of diabetes. Angiotensin II (AngII), a circulating stress hormone, is elevated in cardiovascular disease; however, our knowledge of sex differences in the vascular effects of AngII are limited. We therefore analyzed sex differences in human endothelial cell response to AngII treatment.

Methods

Male and female endothelial cells were treated with AngII for 24 h and analyzed by RNA sequencing. We then used endothelial and mesenchymal markers, inflammation assays, and oxidative stress indicators to measure female and male endothelial cell functional changes in response to AngII.

Results

Our data show that female and male endothelial cells are transcriptomically distinct. Female endothelial cells treated with AngII had widespread gene expression changes related to inflammatory and oxidative stress pathways, while male endothelial cells had few gene expression changes. While both female and male endothelial cells maintained their endothelial phenotype with AngII treatment, female endothelial cells showed increased release of the inflammatory cytokine interleukin-6 and increased white blood cell adhesion following AngII treatment concurrent with a second inflammatory cytokine. Additionally, female endothelial cells had elevated reactive oxygen species production compared to male endothelial cells after AngII treatment, which may be partially due to nicotinamide adenine dinucleotide phosphate oxidase-2 (NOX2) escape from X-chromosome inactivation.

Conclusions

These data suggest that endothelial cells have sexually dimorphic responses to AngII, which could contribute to increased prevalence of some cardiovascular diseases in women.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12195-023-00762-2.

Mindful attention promotes control of brain network dynamics for self-regulation and discontinues the past from the present

Mindful attention is characterized by acknowledging the present experience as a transient mental event. Early stages of mindfulness practice may require greater neural effort for later efficiency. Early effort may self-regulate behavior and focalize the present, but this understanding lacks a computational explanation. Here we used network control theory as a model of how external control inputs-operationalizing effort-distribute changes in neural activity evoked during mindful attention across the white matter network. We hypothesized that individuals with greater network controllability, thereby efficiently distributing control inputs, effectively self-regulate behavior. We further hypothesized that brain regions that utilize greater control input exhibit shorter intrinsic timescales of neural activity. Shorter timescales characterize quickly discontinuing past processing to focalize the present. We tested these hypotheses in a randomized controlled study that primed participants to either mindfully respond or naturally react to alcohol cues during fMRI and administered text reminders and measurements of alcohol consumption during 4 wk postscan. We found that participants with greater network controllability moderated alcohol consumption. Mindful regulation of alcohol cues, compared to one's own natural reactions, reduced craving, but craving did not differ from the baseline group. Mindful regulation of alcohol cues, compared to the natural reactions of the baseline group, involved more-effortful control of neural dynamics across cognitive control and attention subnetworks. This effort persisted in the natural reactions of the mindful group compared to the baseline group. More-effortful neural states had shorter timescales than less effortful states, offering an explanation for how mindful attention promotes being present.

Representations of Complex Contexts: A Role for Hippocampus

The hippocampus plays a critical role in supporting episodic memory, in large part by binding together experiences and items with surrounding contextual information. At present, however, little is known about the roles of different hippocampal subfields in supporting this item-context binding. To address this question, we constructed a task in which items were affiliated with differing types of context-cognitive associations that vary at the local, item level and membership in temporally organized lists that linked items together at a global level. Participants made item recognition judgments while undergoing high-resolution fMRI. We performed voxel pattern similarity analyses to answer the question of how human hippocampal subfields represent retrieved information about cognitive states and the time at which a past event took place. As participants recollected previously presented items, activity patterns in the CA23DG subregion carried information about prior cognitive states associated with these items. We found no evidence to suggest reinstatement of information about temporal context at the level of list membership, but exploratory analyses revealed representations of temporal context at a coarse level in conjunction with representations of cognitive contexts. Results are consistent with characterizations of CA23DG as a critical site for binding together items and contexts in the service of memory retrieval.

Asymmetric signaling across the hierarchy of cytoarchitecture within the human connectome

Cortical variations in cytoarchitecture form a sensory-fugal axis that shapes regional profiles of extrinsic connectivity and is thought to guide signal propagation and integration across the cortical hierarchy. While neuroimaging work has shown that this axis constrains local properties of the human connectome, it remains unclear whether it also shapes the asymmetric signaling that arises from higher-order topology. Here, we used network control theory to examine the amount of energy required to propagate dynamics across the sensory-fugal axis. Our results revealed an asymmetry in this energy, indicating that bottom-up transitions were easier to complete compared to top-down. Supporting analyses demonstrated that asymmetries were underpinned by a connectome topology that is wired to support efficient bottom-up signaling. Lastly, we found that asymmetries correlated with differences in communicability and intrinsic neuronal time scales and lessened throughout youth. Our results show that cortical variation in cytoarchitecture may guide the formation of macroscopic connectome topology.

Uncovering the biological basis of control energy: Structural and metabolic correlates of energy inefficiency in temporal lobe epilepsy

Network control theory is increasingly used to profile the brain's energy landscape via simulations of neural dynamics. This approach estimates the control energy required to simulate the activation of brain circuits based on structural connectome measured using diffusion magnetic resonance imaging, thereby quantifying those circuits' energetic efficiency. The biological basis of control energy, however, remains unknown, hampering its further application. To fill this gap, investigating temporal lobe epilepsy as a lesion model, we show that patients require higher control energy to activate the limbic network than healthy volunteers, especially ipsilateral to the seizure focus. The energetic imbalance between ipsilateral and contralateral temporolimbic regions is tracked by asymmetric patterns of glucose metabolism measured using positron emission tomography, which, in turn, may be selectively explained by asymmetric gray matter loss as evidenced in the hippocampus. Our investigation provides the first theoretical framework unifying gray matter integrity, metabolism, and energetic generation of neural dynamics.

Substance Use and Adherence to Antiretroviral Therapy among People Living with HIV in the United States

People with HIV (PWH) report substance use at higher rates than HIV-uninfected individuals. The potential negative impact of single and polysubstance use on HIV treatment among diverse samples of PWH is underexplored. PWH were recruited from the Center for Positive Living at the Montefiore Medical Center (Bronx, NY, USA) from May 2017-April 2018 and completed a cross-sectional survey with measures of substance use, antiretroviral therapy (ART) use, and ART adherence. The overall sample included 237 PWH (54.1% Black, 42.2% female, median age 53 years). Approximately half of the sample reported any current substance use with 23.1% reporting single substance use and 21.4% reporting polysubstance use. Polysubstance use was more prevalent among those with current cigarette smoking relative to those with no current smoking and among females relative to males. Alcohol and cannabis were the most commonly reported polysubstance combination; however, a sizeable proportion of PWH reported other two, three, and four-substance groupings. Single and polysubstance use were associated with lower ART adherence. A thorough understanding of substance use patterns and related adherence challenges may aid with targeted public health interventions to improve HIV care cascade goals, including the integration of substance use prevention into HIV treatment and care settings.

The Age of Reason: Functional Brain Network Development during Childhood

Human childhood is characterized by dramatic changes in the mind and brain. However, little is known about the large-scale intrinsic cortical network changes that occur during childhood because of methodological challenges in scanning young children. Here, we overcome this barrier by using sophisticated acquisition and analysis tools to investigate functional network development in children between the ages of 4 and 10 years ([Formula: see text]; 50 female, 42 male). At multiple spatial scales, age is positively associated with brain network segregation. At the system level, age was associated with segregation of systems involved in attention from those involved in abstract cognition, and with integration among attentional and perceptual systems. Associations between age and functional connectivity are most pronounced in visual and medial prefrontal cortex, the two ends of a gradient from perceptual, externally oriented cortex to abstract, internally oriented cortex. These findings suggest that both ends of the sensory-association gradient may develop early, in contrast to the classical theories that cortical maturation proceeds from back to front, with sensory areas developing first and association areas developing last. More mature patterns of brain network architecture, controlling for age, were associated with better visuospatial reasoning abilities. Our results suggest that as cortical architecture becomes more specialized, children become more able to reason about the world and their place in it.SIGNIFICANCE STATEMENT Anthropologists have called the transition from early to middle childhood the "age of reason", when children across cultures become more independent. We employ cutting-edge neuroimaging acquisition and analysis approaches to investigate associations between age and functional brain architecture in childhood. Age was positively associated with segregation between cortical systems that process the external world and those that process abstract phenomena like the past, future, and minds of others. Surprisingly, we observed pronounced development at both ends of the sensory-association gradient, challenging the theory that sensory areas develop first and association areas develop last. Our results open new directions for research into how brains reorganize to support rapid gains in cognitive and socioemotional skills as children reach the age of reason.

BOLD cofluctuation 'events' are predicted from static functional connectivity

Recent work identified single time points ("events") of high regional cofluctuation in functional Magnetic Resonance Imaging (fMRI) which contain more large-scale brain network information than other, low cofluctuation time points. This suggested that events might be a discrete, temporally sparse signal which drives functional connectivity (FC) over the timeseries. However, a different, not yet explored possibility is that network information differences between time points are driven by sampling variability on a constant, static, noisy signal. Using a combination of real and simulated data, we examined the relationship between cofluctuation and network structure and asked if this relationship was unique, or if it could arise from sampling variability alone. First, we show that events are not discrete - there is a gradually increasing relationship between network structure and cofluctuation; ∼50% of samples show very strong network structure. Second, using simulations we show that this relationship is predicted from sampling variability on static FC. Finally, we show that randomly selected points can capture network structure about as well as events, largely because of their temporal spacing. Together, these results suggest that, while events exhibit particularly strong representations of static FC, there is little evidence that events are unique timepoints that drive FC structure. Instead, a parsimonious explanation for the data is that events arise from a single static, but noisy, FC structure.

Citation counts and journal impact factors do not capture some indicators of research quality in the behavioural and brain sciences

Citation data and journal impact factors are important components of faculty dossiers and figure prominently in both promotion decisions and assessments of a researcher's broader societal impact. Although these metrics play a large role in high-stakes decisions, the evidence is mixed about whether they are strongly correlated with indicators of research quality. We use data from a large-scale dataset comprising 45 144 journal articles with 667 208 statistical tests and data from 190 replication attempts to assess whether citation counts and impact factors predict three indicators of research quality: (i) the accuracy of statistical reporting, (ii) the evidential value of the reported data and (iii) the replicability of a given experimental result. Both citation counts and impact factors were weak and inconsistent predictors of research quality, so defined, and sometimes negatively related to quality. Our findings raise the possibility that citation data and impact factors may be of limited utility in evaluating scientists and their research. We discuss the implications of these findings in light of current incentive structures and discuss alternative approaches to evaluating research.

Information content of brain states is explained by structural constraints on state energetics

Signal propagation along the structural connectome of the brain induces changes in the patterns of activity. These activity patterns define global brain states and contain information in accordance with their expected probability of occurrence. Being the physical substrate upon which information propagates, the structural connectome, in conjunction with the dynamics, determines the set of possible brain states and constrains the transition between accessible states. Yet, precisely how these structural constraints on state transitions relate to their information content remains unexplored. To address this gap in knowledge, we defined the information content as a function of the activation distribution, where statistically rare values of activation correspond to high information content. With this numerical definition in hand, we studied the spatiotemporal distribution of information content in functional magnetic resonance imaging (fMRI) data from the Human Connectome Project during different tasks, and report four key findings. First, information content strongly depends on cognitive context; its absolute level and spatial distribution depend on the cognitive task. Second, while information content shows similarities to other measures of brain activity, it is distinct from both Neurosynth maps and task contrast maps generated by a general linear model applied to the fMRI data. Third, the brain's structural wiring constrains the cost to control its state, where the cost to transition into high information content states is larger than that to transition into low information content states. Finally, all state transitions-especially those to high information content states-are less costly than expected from random network null models, thereby indicating the brains marked efficiency. Taken together, our findings establish an explanatory link between the information contained in a brain state and the energetic cost of attaining that state, thereby laying important groundwork for our understanding of large-scale cognitive computations.

Neural signatures associated with temporal compression in the verbal retelling of past events

When we retell our past experiences, we aim to reproduce some version of the original events; this reproduced version is often temporally compressed relative to the original. However, it is currently unclear how this compression manifests in brain activity. One possibility is that a compressed retrieved memory manifests as a neural pattern which is more dissimilar to the original, relative to a more detailed or vivid memory. However, we argue that measuring raw dissimilarity alone is insufficient, as it confuses a variety of interesting and uninteresting changes. To address this problem, we examine brain pattern changes that are consistent across people. We show that temporal compression in individuals’ retelling of past events predicts systematic encoding-to-recall transformations in several higher associative regions. These findings elucidate how neural representations are not simply reactivated, but can also be transformed due to temporal compression during a universal form of human memory expression: verbal retelling.

Brain patterns measured while participants first watched a movie in the fMRI scanner, then recalled the movie’s key narrative features, demonstrate that temporal compression in individuals’ retelling of past events predicts encoding-to-recall transformations.

Neuronal activity in sensory cortex predicts the specificity of learning in mice

Learning to avoid dangerous signals while preserving normal responses to safe stimuli is essential for everyday behavior and survival. Following identical experiences, subjects exhibit fear specificity ranging from high (specializing fear to only the dangerous stimulus) to low (generalizing fear to safe stimuli), yet the neuronal basis of fear specificity remains unknown. Here, we identified the neuronal code that underlies inter-subject variability in fear specificity using longitudinal imaging of neuronal activity before and after differential fear conditioning in the auditory cortex of mice. Neuronal activity prior to, but not after learning predicted the level of specificity following fear conditioning across subjects. Stimulus representation in auditory cortex was reorganized following conditioning. However, the reorganized neuronal activity did not relate to the specificity of learning. These results present a novel neuronal code that determines individual patterns in learning.

The neural mechanisms underpinning the specificity of fear memories remains poorly understood. Here, the authors highlight how neural activity prior to fear learning impacts fear memory specificity.

Neurophysiological Evidence for Cognitive Map Formation during Sequence Learning

Humans deftly parse statistics from sequences. Some theories posit that humans learn these statistics by forming cognitive maps, or underlying representations of the latent space which links items in the sequence. Here, an item in the sequence is a node, and the probability of transitioning between two items is an edge. Sequences can then be generated from walks through the latent space, with different spaces giving rise to different sequence statistics. Individual or group differences in sequence learning can be modeled by changing the time scale over which estimates of transition probabilities are built, or in other words, by changing the amount of temporal discounting. Latent space models with temporal discounting bear a resemblance to models of navigation through Euclidean spaces. However, few explicit links have been made between predictions from Euclidean spatial navigation and neural activity during human sequence learning. Here, we use a combination of behavioral modeling and intracranial encephalography (iEEG) recordings to investigate how neural activity might support the formation of space-like cognitive maps through temporal discounting during sequence learning. Specifically, we acquire human reaction times from a sequential reaction time task, to which we fit a model that formulates the amount of temporal discounting as a single free parameter. From the parameter, we calculate each individual's estimate of the latent space. We find that neural activity reflects these estimates mostly in the temporal lobe, including areas involved in spatial navigation. Similar to spatial navigation, we find that low-dimensional representations of neural activity allow for easy separation of important features, such as modules, in the latent space. Lastly, we take advantage of the high temporal resolution of iEEG data to determine the time scale on which latent spaces are learned. We find that learning typically happens within the first 500 trials, and is modulated by the underlying latent space and the amount of temporal discounting characteristic of each participant. Ultimately, this work provides important links between behavioral models of sequence learning and neural activity during the same behavior, and contextualizes these results within a broader framework of domain general cognitive maps.

Efficient coding in the economics of human brain connectomics

In systems neuroscience, most models posit that brain regions communicate information under constraints of efficiency. Yet, evidence for efficient communication in structural brain networks characterized by hierarchical organization and highly connected hubs remains sparse. The principle of efficient coding proposes that the brain transmits maximal information in a metabolically economical or compressed form to improve future behavior. To determine how structural connectivity supports efficient coding, we develop a theory specifying minimum rates of message transmission between brain regions to achieve an expected fidelity, and we test five predictions from the theory based on random walk communication dynamics. In doing so, we introduce the metric of compression efficiency, which quantifies the trade-off between lossy compression and transmission fidelity in structural networks. In a large sample of youth (n = 1,042; age 8-23 years), we analyze structural networks derived from diffusion-weighted imaging and metabolic expenditure operationalized using cerebral blood flow. We show that structural networks strike compression efficiency trade-offs consistent with theoretical predictions. We find that compression efficiency prioritizes fidelity with development, heightens when metabolic resources and myelination guide communication, explains advantages of hierarchical organization, links higher input fidelity to disproportionate areal expansion, and shows that hubs integrate information by lossy compression. Lastly, compression efficiency is predictive of behavior-beyond the conventional network efficiency metric-for cognitive domains including executive function, memory, complex reasoning, and social cognition. Our findings elucidate how macroscale connectivity supports efficient coding and serve to foreground communication processes that utilize random walk dynamics constrained by network connectivity.

Learning continuous chaotic attractors with a reservoir computer

Neural systems are well known for their ability to learn and store information as memories. Even more impressive is their ability to abstract these memories to create complex internal representations, enabling advanced functions such as the spatial manipulation of mental representations. While recurrent neural networks (RNNs) are capable of representing complex information, the exact mechanisms of how dynamical neural systems perform abstraction are still not well-understood, thereby hindering the development of more advanced functions. Here, we train a 1000-neuron RNN-a reservoir computer (RC)-to abstract a continuous dynamical attractor memory from isolated examples of dynamical attractor memories. Furthermore, we explain the abstraction mechanism with a new theory. By training the RC on isolated and shifted examples of either stable limit cycles or chaotic Lorenz attractors, the RC learns a continuum of attractors as quantified by an extra Lyapunov exponent equal to zero. We propose a theoretical mechanism of this abstraction by combining ideas from differentiable generalized synchronization and feedback dynamics. Our results quantify abstraction in simple neural systems, enabling us to design artificial RNNs for abstraction and leading us toward a neural basis of abstraction.