All-optical physiology resolves a synaptic basis for behavioral timescale plasticity.

Learning has been associated with modifications of synaptic and circuit properties, but the precise changes storing information in mammals have remained largely unclear. We combined genetically targeted voltage imaging with targeted optogenetic activation and silencing of pre- and post-synaptic neurons to study the mechanisms underlying hippocampal behavioral timescale plasticity. In mice navigating a virtual-reality environment, targeted optogenetic activation of individual CA1 cells at specific places induced stable representations of these places in the targeted cells. Optical elicitation, recording, and modulation of synaptic transmission in behaving mice revealed that activity in presynaptic CA2/3 cells was required for the induction of plasticity in CA1 and, furthermore, that during induction of these place fields in single CA1 cells, synaptic input from CA2/3 onto these same cells was potentiated. These results reveal synaptic implementation of hippocampal behavioral timescale plasticity and define a methodology to resolve synaptic plasticity during learning and memory in behaving mammals.

ASICs Mediate Food Responses in an Enteric Serotonergic Neuron that Controls Foraging Behaviors.

Animals must respond to the ingestion of food by generating adaptive behaviors, but the role of gut-brain signaling in behavioral regulation is poorly understood. Here, we identify conserved ion channels in an enteric serotonergic neuron that mediate its responses to food ingestion and decipher how these responses drive changes in foraging behavior. We show that the C. elegans serotonergic neuron NSM acts as an enteric sensory neuron that acutely detects food ingestion. We identify the novel and conserved acid-sensing ion channels (ASICs) DEL-7 and DEL-3 as NSM-enriched channels required for feeding-dependent NSM activity, which in turn drives slow locomotion while animals feed. Point mutations that alter the DEL-7 channel change NSM dynamics and associated behavioral dynamics of the organism. This study provides causal links between food ingestion, molecular and physiological properties of an enteric serotonergic neuron, and adaptive feeding behaviors, yielding a new view of how enteric neurons control behavior.

Glia Accumulate Evidence that Actions Are Futile and Suppress Unsuccessful Behavior.

When a behavior repeatedly fails to achieve its goal, animals often give up and become passive, which can be strategic for preserving energy or regrouping between attempts. It is unknown how the brain identifies behavioral failures and mediates this behavioral-state switch. In larval zebrafish swimming in virtual reality, visual feedback can be withheld so that swim attempts fail to trigger expected visual flow. After tens of seconds of such motor futility, animals became passive for similar durations. Whole-brain calcium imaging revealed noradrenergic neurons that responded specifically to failed swim attempts and radial astrocytes whose calcium levels accumulated with increasing numbers of failed attempts. Using cell ablation and optogenetic or chemogenetic activation, we found that noradrenergic neurons progressively activated brainstem radial astrocytes, which then suppressed swimming. Thus, radial astrocytes perform a computation critical for behavior: they accumulate evidence that current actions are ineffective and consequently drive changes in behavioral states. VIDEO ABSTRACT.

Therapeutic Potential of PTB Inhibition Through Converting Glial Cells to Neurons in the Brain.

Cell replacement therapy represents a promising approach for treating neurodegenerative diseases. Contrary to the common addition strategy to generate new neurons from glia by overexpressing a lineage-specific transcription factor(s), a recent study introduced a subtraction strategy by depleting a single RNA-binding protein, Ptbp1, to convert astroglia to neurons not only in vitro but also in the brain. Given its simplicity, multiple groups have attempted to validate and extend this attractive approach but have met with difficulty in lineage tracing newly induced neurons from mature astrocytes, raising the possibility of neuronal leakage as an alternative explanation for apparent astrocyte-to-neuron conversion. This review focuses on the debate over this critical issue. Importantly, multiple lines of evidence suggest that Ptbp1 depletion can convert a selective subpopulation of glial cells into neurons and, via this and other mechanisms, reverse deficits in a Parkinson's disease model, emphasizing the importance of future efforts in exploring this therapeutic strategy.

Competitive Disinhibition Mediates Behavioral Choice and Sequences in Drosophila.

Even a simple sensory stimulus can elicit distinct innate behaviors and sequences. During sensorimotor decisions, competitive interactions among neurons that promote distinct behaviors must ensure the selection and maintenance of one behavior, while suppressing others. The circuit implementation of these competitive interactions is still an open question. By combining comprehensive electron microscopy reconstruction of inhibitory interneuron networks, modeling, electrophysiology, and behavioral studies, we determined the circuit mechanisms that contribute to the Drosophila larval sensorimotor decision to startle, explore, or perform a sequence of the two in response to a mechanosensory stimulus. Together, these studies reveal that, early in sensory processing, (1) reciprocally connected feedforward inhibitory interneurons implement behavioral choice, (2) local feedback disinhibition provides positive feedback that consolidates and maintains the chosen behavior, and (3) lateral disinhibition promotes sequence transitions. The combination of these interconnected circuit motifs can implement both behavior selection and the serial organization of behaviors into a sequence.

From Whole-Brain Data to Functional Circuit Models: The Zebrafish Optomotor Response.

Detailed descriptions of brain-scale sensorimotor circuits underlying vertebrate behavior remain elusive. Recent advances in zebrafish neuroscience offer new opportunities to dissect such circuits via whole-brain imaging, behavioral analysis, functional perturbations, and network modeling. Here, we harness these tools to generate a brain-scale circuit model of the optomotor response, an orienting behavior evoked by visual motion. We show that such motion is processed by diverse neural response types distributed across multiple brain regions. To transform sensory input into action, these regions sequentially integrate eye- and direction-specific sensory streams, refine representations via interhemispheric inhibition, and demix locomotor instructions to independently drive turning and forward swimming. While experiments revealed many neural response types throughout the brain, modeling identified the dimensions of functional connectivity most critical for the behavior. We thus reveal how distributed neurons collaborate to generate behavior and illustrate a paradigm for distilling functional circuit models from whole-brain data.

How Cortical Circuits Implement Cortical Computations: Mouse Visual Cortex as a Model.

The mouse, as a model organism to study the brain, gives us unprecedented experimental access to the mammalian cerebral cortex. By determining the cortex's cellular composition, revealing the interaction between its different components, and systematically perturbing these components, we are obtaining mechanistic insight into some of the most basic properties of cortical function. In this review, we describe recent advances in our understanding of how circuits of cortical neurons implement computations, as revealed by the study of mouse primary visual cortex. Further, we discuss how studying the mouse has broadened our understanding of the range of computations performed by visual cortex. Finally, we address how future approaches will fulfill the promise of the mouse in elucidating fundamental operations of cortex.

Drosophila sechellia: A Genetic Model for Behavioral Evolution and Neuroecology.

Defining the mechanisms by which animals adapt to their ecological niche is an important problem bridging evolution, genetics, and neurobiology. We review the establishment of a powerful genetic model for comparative behavioral analysis and neuroecology, Drosophila sechellia. This island-endemic fly species is closely related to several cosmopolitan generalists, including Drosophila melanogaster, but has evolved extreme specialism, feeding and reproducing exclusively on the noni fruit of the tropical shrub Morinda citrifolia. We first describe the development and use of genetic approaches to facilitate genotype/phenotype associations in these drosophilids. Next, we survey the behavioral, physiological, and morphological adaptations of D. sechellia throughout its life cycle and outline our current understanding of the genetic and cellular basis of these traits. Finally, we discuss the principles this knowledge begins to establish in the context of host specialization, speciation, and the neurobiology of behavioral evolution and consider open questions and challenges in the field.

Addressing distress management challenges: Recommendations from the consensus panel of the American Psychosocial Oncology Society and the Association of Oncology Social Work.

Distress management (DM) (screening and response) is an essential component of cancer care across the treatment trajectory. Effective DM has many benefits, including improving patients' quality of life; reducing distress, anxiety, and depression; contributing to medical cost offsets; and reducing emergency department visits and hospitalizations. Unfortunately, many distressed patients do not receive needed services. There are several multilevel barriers that represent key challenges to DM and affect its implementation. The Consolidated Framework for Implementation Research was used as an organizational structure to outline the barriers and facilitators to implementation of DM, including: 1) individual characteristics (individual patient characteristics with a focus on groups who may face unique barriers to distress screening and linkage to services), 2) intervention (unique aspects of DM intervention, including specific challenges in screening and psychosocial intervention, with recommendations for resolving these challenges), 3) processes for implementation of DM (modality and timing of screening, the challenge of triage for urgent needs, and incorporation of patient-reported outcomes and quality measures), 4) organization-inner setting (the context of the clinic, hospital, or health care system); and 5) organization-outer setting (including reimbursement strategies and health-care policy). Specific recommendations for evidence-based strategies and interventions for each of the domains of the Consolidated Framework for Implementation Research are also included to address barriers and challenges.

Translational In Vivo Assays in Behavioral Biology.

The failure of preclinical research to advance successful candidate medications in psychiatry has created a paradigmatic crisis in psychiatry. The Research Domain Criteria (RDoC) initiative was designed to remedy this situation with a neuroscience-based approach that employs multimodal and cross-species in vivo methodology to increase the probability of translational findings and, consequently, drug discovery. The present review underscores the feasibility of this methodological approach by briefly reviewing, first, the use of multidimensional and cross-species methodologies in traditional behavioral pharmacology and, subsequently, the utility of this approach in contemporary neuroimaging and electrophysiology research-with a focus on the value of functionally homologous studies in nonhuman and human subjects. The final section provides a brief review of the RDoC, with a focus on the potential strengths and weaknesses of its domain-based underpinnings. Optimistically, this mechanistic and multidimensional approach in neuropsychiatric research will lead to novel therapeutics for the management of neuropsychiatric disorders.

Variants in ZFX are associated with an X-linked neurodevelopmental disorder with recurrent facial gestalt.

Pathogenic variants in multiple genes on the X chromosome have been implicated in syndromic and non-syndromic intellectual disability disorders. ZFX on Xp22.11 encodes a transcription factor that has been linked to diverse processes including oncogenesis and development, but germline variants have not been characterized in association with disease. Here, we present clinical and molecular characterization of 18 individuals with germline ZFX variants. Exome or genome sequencing revealed 11 variants in 18 subjects (14 males and 4 females) from 16 unrelated families. Four missense variants were identified in 11 subjects, with seven truncation variants in the remaining individuals. Clinical findings included developmental delay/intellectual disability, behavioral abnormalities, hypotonia, and congenital anomalies. Overlapping and recurrent facial features were identified in all subjects, including thickening and medial broadening of eyebrows, variations in the shape of the face, external eye abnormalities, smooth and/or long philtrum, and ear abnormalities. Hyperparathyroidism was found in four families with missense variants, and enrichment of different tumor types was observed. In molecular studies, DNA-binding domain variants elicited differential expression of a small set of target genes relative to wild-type ZFX in cultured cells, suggesting a gain or loss of transcriptional activity. Additionally, a zebrafish model of ZFX loss displayed an altered behavioral phenotype, providing additional evidence for the functional significance of ZFX. Our clinical and experimental data support that variants in ZFX are associated with an X-linked intellectual disability syndrome characterized by a recurrent facial gestalt, neurocognitive and behavioral abnormalities, and an increased risk for congenital anomalies and hyperparathyroidism.

Academics are more specific, and practitioners more sensitive, in forecasting interventions to strengthen democratic attitudes.

Concern over democratic erosion has led to a proliferation of proposed interventions to strengthen democratic attitudes in the United States. Resource constraints, however, prevent implementing all proposed interventions. One approach to identify promising interventions entails leveraging domain experts, who have knowledge regarding a given field, to forecast the effectiveness of candidate interventions. We recruit experts who develop general knowledge about a social problem (academics), experts who directly intervene on the problem (practitioners), and nonexperts from the public to forecast the effectiveness of interventions to reduce partisan animosity, support for undemocratic practices, and support for partisan violence. Comparing 14,076 forecasts submitted by 1,181 forecasters against the results of a megaexperiment (n = 32,059) that tested 75 hypothesized effects of interventions, we find that both types of experts outperformed members of the public, though experts differed in how they were accurate. While academics' predictions were more specific (i.e., they identified a larger proportion of ineffective interventions and had fewer false-positive forecasts), practitioners' predictions were more sensitive (i.e., they identified a larger proportion of effective interventions and had fewer false-negative forecasts). Consistent with this, practitioners were better at predicting best-performing interventions, while academics were superior in predicting which interventions performed worst. Our paper highlights the importance of differentiating types of experts and types of accuracy. We conclude by discussing factors that affect whether sensitive or specific forecasters are preferable, such as the relative cost of false positives and negatives and the expected rate of intervention success.

A Turing test of whether AI chatbots are behaviorally similar to humans.

We administer a Turing test to AI chatbots. We examine how chatbots behave in a suite of classic behavioral games that are designed to elicit characteristics such as trust, fairness, risk-aversion, cooperation, etc., as well as how they respond to a traditional Big-5 psychological survey that measures personality traits. ChatGPT-4 exhibits behavioral and personality traits that are statistically indistinguishable from a random human from tens of thousands of human subjects from more than 50 countries. Chatbots also modify their behavior based on previous experience and contexts "as if" they were learning from the interactions and change their behavior in response to different framings of the same strategic situation. Their behaviors are often distinct from average and modal human behaviors, in which case they tend to behave on the more altruistic and cooperative end of the distribution. We estimate that they act as if they are maximizing an average of their own and partner's payoffs.

Showing high-achieving college applicants past admissions outcomes increases undermatching.

More than 40% of US high school students have access to Naviance, a proprietary tool designed to guide college search and application decisions. The tool displays, for individual colleges, the standardized test scores, grade-point averages, and admissions outcomes of past applicants from a student's high school, so long as a sufficient number of students from previous cohorts applied to a given college. This information is intended to help students focus their efforts on applying to the most suitable colleges, but it may also influence application decisions in undesirable ways. Using data on 70,000 college applicants across 220 public high schools, we assess the effects of access to Naviance on application undermatch, or applying only to schools for which a candidate is academically overqualified. By leveraging variation in the year that high schools adopted the tool, we estimate that Naviance increased application undermatching by more than 50% among 17,000 high-achieving students in our dataset. This phenomenon may be due to increased conservatism: Students may be less likely to apply to colleges when they know their academic qualifications fall below the average of admitted students from their high school. These results illustrate how information on college competitiveness, when not appropriately presented and contextualized, can lead to unintended consequences.

Correcting misperceptions of the other political party does not robustly reduce support for undemocratic practices or partisan violence.

A growing consensus suggests that a cause of support for undemocratic practices and partisan violence is that partisans misperceive the other side. That is, they vastly exaggerate the extent to which members of the other party support undemocratic practices and violence. When these misperceptions are corrected, citizens' own beliefs moderate. I present results from an experiment that show that misperception corrections do not have an effect in the presence of competing information (i.e., that challenges the validity of the correction or offers a conflicting narrative). Basic corrections do not constitute a robust way to counter democratic backsliding stemming from citizens' misperceptions. The results highlight the need to devise stronger misperception interventions and, more generally, to consider competing information environments when devising any scalable behavioral intervention.

Integrating biogeography and behavioral ecology to rapidly address biodiversity loss.

Addressing climate change and biodiversity loss will be the defining ecological, political, and humanitarian challenge of our time. Alarmingly, policymakers face a narrowing window of opportunity to prevent the worst impacts, necessitating complex decisions about which land to set aside for biodiversity preservation. Yet, our ability to make these decisions is hindered by our limited capacity to predict how species will respond to synergistic drivers of extinction risk. We argue that a rapid integration of biogeography and behavioral ecology can meet these challenges because of the distinct, yet complementary levels of biological organization they address, scaling from individuals to populations, and from species and communities to continental biotas. This union of disciplines will advance efforts to predict biodiversity's responses to climate change and habitat loss through a deeper understanding of how biotic interactions and other behaviors modulate extinction risk, and how responses of individuals and populations impact the communities in which they are embedded. Fostering a rapid mobilization of expertise across behavioral ecology and biogeography is a critical step toward slowing biodiversity loss.

Conditional bribery: Insights from incentivized experiments across 18 nations.

Bribery, a grand global challenge, often occurs across national jurisdictions. Behavioral research studying bribery to inform anticorruption interventions, however, has merely examined bribery within single nations. Here, we report online experiments and provide insights into crossnational bribery. We ran a pilot study (across three nations) and a large, incentivized experiment using a bribery game played across 18 nations (N = 5,582, total number of incentivized decisions = 346,084). The results show that people offer disproportionally more bribes to interaction partners from nations with a high (vs. low) reputation for foreign bribery, measured by macrolevel indicators of corruption perceptions. People widely share nation-specific expectations about a nation's bribery acceptance levels. However, these nation-specific expectations negatively correlate with actual bribe acceptance levels, suggesting shared yet inaccurate stereotypes about bribery tendencies. Moreover, the interaction partner's national background (more than one's own national background) drives people's decision to offer or accept a bribe-a finding we label conditional bribery.

Experiment aversion does not appear to generalize.

Over the past decade, governments and organizations around the world have established behavioral insights teams advocating for randomized experiments. However, recent findings by M. N. Meyer et al., Proc. Natl. Acad. Sci. U.S.A. 116, 10723-10728 (2019) and P. R. Heck, C. F. Chabris, D. J. Watts, M. N. Meyer, Proc. Natl. Acad. Sci. U.S.A. 117, 18948-18950 (2020) suggest that people often rate randomized experiments as less appropriate than the policies they contain even when approving the implementation of either policy untested and when none of the individual policies is clearly superior. The authors warn that this could cause policymakers to avoid running large-scale field experiments or being transparent about running them and might contribute to an adverse heterogeneity bias in terms of who is participating in experiments. In one direct and six conceptual preregistered replications (total N = 5,200) of the previously published larger-effect studies, using the same main dependent variable but with variations in scenario wordings, recruitment platforms, and countries, and the addition of further measures to assess people's views, we test the generalizability and robustness of these findings. Together, we find that the original results do not appear to generalize. That is, our triangulation reveals insufficient evidence to conclude that people exhibit a common pattern of behavior that would be consistent with relative experiment aversion, thereby supporting recent findings by R. Mislavsky, B. Dietvorst, U. Simonsohn, Mark. Sci. 39, 1092-1104 (2020). Thus, policymakers may not need to be concerned about employing evidence-based practices more so than about universally implementing policies.

Dynamics in a behavioral-epidemiological model for individual adherence to a nonpharmaceutical intervention.

The SARS-CoV-2 pandemic has highlighted the importance of behavioral drivers in epidemic dynamics. With the relaxation of mandated nonpharmaceutical interventions (NPIs) formerly in place to decrease transmission, such as mask-wearing or social distancing, adherence to an NPI is now the result of individual decision-making. To study these coupled dynamics, we embed a game-theoretic model for individual NPI adherence within an epidemiological model. When the disease is endemic, we find that our model has multiple (but none concurrently stable) equilibria: one each with zero, complete, or partial NPI adherence. Surprisingly, for the equilibrium with partial NPI adherence, the number of infections is independent of the transmission rate. Therefore, in that regime, a change in the rate of pathogen transmission, e.g., due to another (mandated) NPI or a new variant, has no effect on endemic infection levels. On the other hand, we show that vaccination successfully decreases endemic infection levels, and, unexpectedly, also reduces the number of susceptibles at equilibrium when there is partial adherence. From a game-theoretic perspective, we find that highly effective NPIs lead at most to partial adherence. As this effectiveness decreases, partially effective NPIs initially lead to increases in population-level adherence, especially if the risk is high enough. However, a completely ineffective NPI results in no adherence. Furthermore, we identify parameter regions where the individual incentives may not align with those of society as a whole. Overall, our findings illustrate complexities that can arise due to behavioral-epidemiological feedback and suggest appropriate measures to avoid more pessimistic population-level outcomes.

Dynamic switching of neural oscillations in the prefrontal-amygdala circuit for naturalistic freeze-or-flight.

The medial prefrontal cortex (mPFC) and basolateral amygdala (BLA) are involved in the regulation of defensive behavior under threat, but their engagement in flexible behavior shifts remains unclear. Here, we report the oscillatory activities of mPFC-BLA circuit in reaction to a naturalistic threat, created by a predatory robot in mice. Specifically, we found dynamic frequency tuning among two different theta rhythms (~5 or ~10 Hz) was accompanied by agile changes of two different defensive behaviors (freeze-or-flight). By analyzing flight trajectories, we also found that high beta (~30 Hz) is engaged in the top-down process for goal-directed flights and accompanied by a reduction in fast gamma (60 to 120 Hz, peak near 70 Hz). The elevated beta nested the fast gamma activity by its phase more strongly. Our results suggest that the mPFC-BLA circuit has a potential role in oscillatory gear shifting allowing flexible information routing for behavior switches.