Serotonin and the search for the anatomical substrate of aggression

Abstract

All species of animals display aggression in order to obtain resources such as territories, mates, or food. Appropriate displays of aggression rely on the correct identification of a potential competitor, an evaluation of the environmental signals, and the physiological state of the animal. With a hard-wired circuitry involving fixed numbers of neurons, neuromodulators like serotonin offer adaptive flexibility in behavioral responses without changing the “hard-wiring”. In a recent report, we combined intersectional genetics, quantitative behavioral assays and morphological analyses to identify single serotonergic neurons that modulate the escalation of aggression. We found anatomical target areas within the brain where these neurons appear to form synaptic contacts with 5HT1A receptor-expressing neurons, and then confirmed the likelihood of those connections on a functional level. In this Extra View article, we offer an extended discussion of these recent findings and elaborate on how they can link a cellular and functional mapping of an aggression-regulating circuit at a single-cell resolution level.     

A model of naturalistic decision making in preference tests

Decisions as to whether to continue with an ongoing activity or to switch to an alternative are a constant in an animal’s natural world, and in particular underlie foraging behavior and performance in food preference tests. Stimuli experienced by the animal both impact the choice and are themselves impacted by the choice, in a dynamic back and forth. Here, we present model neural circuits, based on spiking neurons, in which the choice to switch away from ongoing behavior instantiates this back and forth, arising as a state transition in neural activity. We analyze two classes of circuit, which differ in whether state transitions result from a loss of hedonic input from the stimulus (an “entice to stay” model) or from aversive stimulus-input (a “repel to leave” model). In both classes of model, we find that the mean time spent sampling a stimulus decreases with increasing value of the alternative stimulus, a fact that we linked to the inclusion of depressing synapses in our model. The competitive interaction is much greater in “entice to stay” model networks, which has qualitative features of the marginal value theorem, and thereby provides a framework for optimal foraging behavior. We offer suggestions as to how our models could be discriminatively tested through the analysis of electrophysiological and behavioral data.     

Visual Receptive Field Properties of Neurons in the Mouse Lateral Geniculate Nucleus

The lateral geniculate nucleus (LGN) is increasingly regarded as a “smart-gating” operator for processing visual information. Therefore, characterizing the response properties of LGN neurons will enable us to better understand how neurons encode and transfer visual signals. Efforts have been devoted to study its anatomical and functional features, and recent advances have highlighted the existence in rodents of complex features such as direction/orientation selectivity. However, unlike well-researched higher-order mammals such as primates, the full array of response characteristics vis-à-vis its morphological features have remained relatively unexplored in the mouse LGN. To address the issue, we recorded from mouse LGN neurons using multisite-electrode-arrays (MEAs) and analysed their discharge patterns in relation to their location under a series of visual stimulation paradigms. Several response properties paralleled results from earlier studies in the field and these include centre-surround organization, size of receptive field, spontaneous firing rate and linearity of spatial summation. However, our results also revealed “high-pass” and “low-pass” features in the temporal frequency tuning of some cells, and greater average contrast gain than reported by earlier studies. In addition, a small proportion of cells had direction/orientation selectivity. Both “high-pass” and “low-pass” cells, as well as direction and orientation selective cells, were found only in small numbers, supporting the notion that these properties emerge in the cortex. ON- and OFF-cells showed distinct contrast sensitivity and temporal frequency tuning properties, suggesting parallel projections from the retina. Incorporating a novel histological technique, we created a 3-D LGN volume model explicitly capturing the morphological features of mouse LGN and localising individual cells into anterior/middle/posterior LGN. Based on this categorization, we show that the ON/OFF, DS/OS and linear response properties are not regionally restricted. Our study confirms earlier findings of spatial pattern selectivity in the LGN, and builds on it to demonstrate that relatively elaborate features are computed early in the visual pathway.     

Dynamically Allocated Hub in Task-Evoked Network Predicts the Vulnerable Prefrontal Locus for Contextual Memory Retrieval in Macaques

Neuroimaging and neurophysiology have revealed that multiple areas in the prefrontal cortex (PFC) are activated in a specific memory task, but severity of impairment after PFC lesions is largely different depending on which activated area is damaged. The critical relationship between lesion sites and impairments has not yet been given a clear mechanistic explanation. Although recent works proposed that a whole-brain network contains hubs that play integrative roles in cortical information processing, this framework relying on an anatomy-based structural network cannot account for the vulnerable locus for a specific task, lesioning of which would bring impairment. Here, we hypothesized that (i) activated PFC areas dynamically form an ordered network centered at a task-specific “functional hub” and (ii) the lesion-effective site corresponds to the “functional hub,” but not to a task-invariant “structural hub.” To test these hypotheses, we conducted functional magnetic resonance imaging experiments in macaques performing a temporal contextual memory task. We found that the activated areas formed a hierarchical hub-centric network based on task-evoked directed connectivity, differently from the anatomical network reflecting axonal projection patterns. Using a novel simulated-lesion method based on support vector machine, we estimated severity of impairment after lesioning of each area, which accorded well with a known dissociation in contextual memory impairment in macaques (impairment after lesioning in area 9/46d, but not in area 8Ad). The predicted severity of impairment was proportional to the network “hubness” of the virtually lesioned area in the task-evoked directed connectivity network, rather than in the anatomical network known from tracer studies. Our results suggest that PFC areas dynamically and cooperatively shape a functional hub-centric network to reallocate the lesion-effective site depending on the cognitive processes, apart from static anatomical hubs. These findings will be a foundation for precise prediction of behavioral impacts of damage or surgical intervention in human brains.     

A Passive Exoskeleton Can Push Your Life Up: Application on Multiple Sclerosis Patients

In the present study, we report the benefits of a passive and fully articulated exoskeleton on multiple sclerosis patients by means of behavioral and electrophysiological measures, paying particular attention to the prefrontal cortex activity. Multiple sclerosis is a neurological condition characterized by lesions of the myelin sheaths that encapsulate the neurons of the brain, spine and optic nerve, and it causes transient or progressive symptoms and impairments in gait and posture. Up to 50% of multiple sclerosis patients require walking aids and 10% are wheelchair-bound 15 years following the initial diagnosis. We tested the ability of a new orthosis, the “Human Body Posturizer”, designed to improve the structural and functional symmetry of the body through proprioception, in multiple sclerosis patients. We observed that a single Human Body Posturizer application improved mobility, ambulation and response accuracy, in all of the tested patients. Most importantly, we associated these clinical observations and behavioral effects to changes in brain activity, particularly in the prefrontal cortex.     

Networks of Causal Linkage Between Eigenmodes Characterize Behavioral Dynamics of Caenorhabditis elegans

Behavioral phenotyping of model organisms has played an important role in unravelling the complexities of animal behavior. Techniques for classifying behavior often rely on easily identified changes in posture and motion. However, such approaches are likely to miss complex behaviors that cannot be readily distinguished by eye (e.g., behaviors produced by high dimensional dynamics). To explore this issue, we focus on the model organism Caenorhabditis elegans, where behaviors have been extensively recorded and classified. Using a dynamical systems lens, we identify high dimensional, nonlinear causal relationships between four basic shapes that describe worm motion (eigenmodes, also called “eigenworms”). We find relationships between all pairs of eigenmodes, but the timescales of the interactions vary between pairs and across individuals. Using these varying timescales, we create “interaction profiles” to represent an individual’s behavioral dynamics. As desired, these profiles are able to distinguish well-known behavioral states: i.e., the profiles for foraging individuals are distinct from those of individuals exhibiting an escape response. More importantly, we find that interaction profiles can distinguish high dimensional behaviors among divergent mutant strains that were previously classified as phenotypically similar. Specifically, we find it is able to detect phenotypic behavioral differences not previously identified in strains related to dysfunction of hermaphrodite-specific neurons.     

Entrepreneurial Regions: Do Macro-Psychological Cultural Characteristics of Regions Help Solve the “Knowledge Paradox” of Economics?

In recent years, modern economies have shifted away from being based on physical capital and towards being based on new knowledge (e.g., new ideas and inventions). Consequently, contemporary economic theorizing and key public policies have been based on the assumption that resources for generating knowledge (e.g., education, diversity of industries) are essential for regional economic vitality. However, policy makers and scholars have discovered that, contrary to expectations, the mere presence of, and investments in, new knowledge does not guarantee a high level of regional economic performance (e.g., high entrepreneurship rates). To date, this “knowledge paradox” has resisted resolution. We take an interdisciplinary perspective to offer a new explanation, hypothesizing that “hidden” regional culture differences serve as a crucial factor that is missing from conventional economic analyses and public policy strategies. Focusing on entrepreneurial activity, we hypothesize that the statistical relation between knowledge resources and entrepreneurial vitality (i.e., high entrepreneurship rates) in a region will depend on “hidden” regional differences in entrepreneurial culture. To capture such “hidden” regional differences, we derive measures of entrepreneurship-prone culture from two large personality datasets from the United States (N = 935,858) and Great Britain (N = 417,217). In both countries, the findings were consistent with the knowledge-culture-interaction hypothesis. A series of nine additional robustness checks underscored the robustness of these results. Naturally, these purely correlational findings cannot provide direct evidence for causal processes, but the results nonetheless yield a remarkably consistent and robust picture in the two countries. In doing so, the findings raise the idea of regional culture serving as a new causal candidate, potentially driving the knowledge paradox; such an explanation would be consistent with research on the psychological characteristics of entrepreneurs.     

Octopamine Neuromodulation Regulates Gr32a-Linked Aggression and Courtship Pathways in Drosophila Males

Chemosensory pheromonal information regulates aggression and reproduction in many species, but how pheromonal signals are transduced to reliably produce behavior is not well understood. Here we demonstrate that the pheromonal signals detected by Gr32a-expressing chemosensory neurons to enhance male aggression are filtered through octopamine (OA, invertebrate equivalent of norepinephrine) neurons. Using behavioral assays, we find males lacking both octopamine and Gr32a gustatory receptors exhibit parallel delays in the onset of aggression and reductions in aggression. Physiological and anatomical experiments identify Gr32a to octopamine neuron synaptic and functional connections in the suboesophageal ganglion. Refining the Gr32a-expressing population indicates that mouth Gr32a neurons promote male aggression and form synaptic contacts with OA neurons. By restricting the monoamine neuron target population, we show that three previously identified OA-Fru^M neurons involved in behavioral choice are among the Gr32a-OA connections. Our findings demonstrate that octopaminergic neuromodulatory neurons function as early as a second-order step in this chemosensory-driven male social behavior pathway.     

Survey of neurotransmitter receptor gene expression into and out of parental care in the burying beetle Nicrophorus vespilloides

Understanding the genetic influences of traits of nonmodel organisms is crucial to understanding how novel traits arise. Do new traits require new genes or are old genes repurposed? How predictable is this process? Here, we examine this question for gene expression influencing parenting behavior in a beetle, Nicrophorus vespilloides. Parental care, produced from many individual behaviors, should be influenced by changes of expression of multiple genes, and one suggestion is that the genes can be predicted based on knowledge of behavior expected to be precursors to parental care, such as aggression, resource defense, and mating on a resource. Thus, testing gene expression during parental care allows us to test expectations of this “precursor hypothesis” for multiple genes and traits. We tested for changes of the expression of serotonin, octopamine/tyramine, and dopamine receptors, as well as one glutamate receptor, predicting that these gene families would be differentially expressed during social interactions with offspring and associated resource defense. We found that serotonin receptors were strongly associated with social and aggression behavioral transitions. Octopamine receptors produced a complex picture of gene expression over a reproductive cycle. Dopamine was not associated with the behavioral transitions sampled here, while the glutamate receptor was most consistent with a behavioral change of resource defense/aggression. Our results generate new hypotheses, refine candidate lists for further studies, and inform the genetic mechanisms that are co‐opted during the evolution of parent–offspring interactions, a likely evolutionary path for many lineages that become fully social. The precursor hypothesis, while not perfect, does provide a starting point for identifying candidate genes.     

Analyzing Self-Similar and Fractal Properties of the C. elegans Neural Network

The brain is one of the most studied and highly complex systems in the biological world. While much research has concentrated on studying the brain directly, our focus is the structure of the brain itself: at its core an interconnected network of nodes (neurons). A better understanding of the structural connectivity of the brain should elucidate some of its functional properties. In this paper we analyze the connectome of the nematode Caenorhabditis elegans. Consisting of only 302 neurons, it is one of the better-understood neural networks. Using a Laplacian Matrix of the 279-neuron “giant component” of the network, we use an eigenvalue counting function to look for fractal-like self similarity. This matrix representation is also used to plot visualizations of the neural network in eigenfunction coordinates. Small-world properties of the system are examined, including average path length and clustering coefficient. We test for localization of eigenfunctions, using graph energy and spacial variance on these functions. To better understand results, all calculations are also performed on random networks, branching trees, and known fractals, as well as fractals which have been “rewired” to have small-world properties. We propose algorithms for generating Laplacian matrices of each of these graphs.     

Functional Dissection of Glutamatergic and GABAergic Neurons in the Bed Nucleus of the Stria Terminalis

The bed nucleus of the stria terminalis (BNST)—a key part of the extended amygdala—has been implicated in the regulation of diverse behavioral states, ranging from anxiety and reward processing to feeding behavior. Among the host of distinct types of neurons within the BNST, recent investigations employing cell type- and projection-specific circuit dissection techniques (such as optogenetics, chemogenetics, deep-brain calcium imaging, and the genetic and viral methods for targeting specific types of cells) have highlighted the key roles of glutamatergic and GABAergic neurons and their axonal projections. As anticipated from their primary roles in excitatory and inhibitory neurotransmission, these studies established that the glutamatergic and GABAergic subpopulations of the BNST oppositely regulate diverse behavioral states. At the same time, these studies have also revealed unexpected functional specificity and heterogeneity within each subpopulation. In this Minireview, we introduce the body of studies that investigated the function of glutamatergic and GABAergic BNST neurons and their circuits. We also discuss unresolved questions and future directions for a more complete understanding of the cellular diversity and functional heterogeneity within the BNST.     

Dissociable Neural Mechanisms Underlying the Modulation of Pain and Anxiety? An fMRI Pilot Study

The down-regulation of pain through beliefs is commonly discussed as a form of emotion regulation. In line with this interpretation, the analgesic effect has been shown to co-occur with reduced anxiety and increased activity in the ventrolateral prefrontal cortex (VLPFC), which is a key region of emotion regulation. This link between pain and anxiety modulation raises the question whether the two effects are rooted in the same neural mechanism. In this pilot fMRI study, we compared the neural basis of the analgesic and anxiolytic effect of two types of threat modulation: a “behavioral control” paradigm, which involves the ability to terminate a noxious stimulus, and a “safety signaling” paradigm, which involves visual cues that signal the threat (or absence of threat) that a subsequent noxious stimulus might be of unusually high intensity. Analgesia was paralleled by VLPFC activity during behavioral control. Safety signaling engaged elements of the descending pain control system, including the rostral anterior cingulate cortex that showed increased functional connectivity with the periaqueductal gray and VLPFC. Anxiety reduction, in contrast, scaled with dorsolateral prefrontal cortex activation during behavioral control but had no distinct neural signature during safety signaling. Our pilot data therefore suggest that analgesic and anxiolytic effects are instantiated in distinguishable neural mechanisms and differ between distinct stress- and pain-modulatory approaches, supporting the recent notion of multiple pathways subserving top-down modulation of the pain experience. Additional studies in larger cohorts are needed to follow up on these preliminary findings.     

Evolution of innate behavioral strategies through competitive population dynamics

Many organism behaviors are innate or instinctual and have been “hard-coded” through evolution. Current approaches to understanding these behaviors model evolution as an optimization problem in which the traits of organisms are assumed to optimize an objective function representing evolutionary fitness. Here, we use a mechanistic birth-death dynamics approach to study the evolution of innate behavioral strategies in a simulated population of organisms. In particular, we performed agent-based stochastic simulations and mean-field analyses of organisms exploring random environments and competing with each other to find locations with plentiful resources. We find that when organism density is low, the mean-field model allows us to derive an effective objective function, predicting how the most competitive phenotypes depend on the exploration-exploitation trade-off between the scarcity of high-resource sites and the increase in birth rate those sites offer organisms. However, increasing organism density alters the most competitive behavioral strategies and precludes the derivation of a well-defined objective function. Moreover, there exists a range of densities for which the coexistence of many phenotypes persists for evolutionarily long times.     

Welcome Back: Responses of Female Bonobos (Pan paniscus) to Fusions

In species with a high degree of fission-fusion social dynamics, fusions may trigger social conflict and thus provide an opportunity to identify sources of social tension and mechanisms related to its alleviation. We characterized behavioral and endocrine responses of captive female bonobos (Pan paniscus) to fusions within a zoo facility designed to simulate naturalistic fission-fusion social dynamics. We compared urinary cortisol levels and frequencies of aggression, grooming and socio-sexual interactions between female bonobos while in stable sub-groups and when one “joiner” was reunited with the “residents” of another sub-group. We hypothesized that fusions would trigger increases in aggression and cortisol levels among reunited joiners and resident females. We further predicted that females who face more uncertainty in their social interactions following fusions may use grooming and/or socio-sexual behavior to reduce social tension and aggression. The only aggression on reunion days occurred between reunited females, but frequencies of aggression remained low across non-reunion and reunion days, and there was no effect of fusions on cortisol levels. Fusions did not influence patterns of grooming, but there were increases in socio-sexual solicitations and socio-sexual interactions between joiners and resident females. Joiners who had been separated from residents for longer received the most solicitations, but were also more selective in their acceptance of solicitations and preferred to have socio-sexual interactions with higher-ranking residents. Our results suggest that socio-sexual interactions play a role in reintegrating female bonobos into social groups following fusions. In addition, females who receive a high number of solicitations are able to gain more control over their socio-sexual interactions and may use socio-sexual interactions for other purposes, such as to enhance their social standing.     

Enhancements to the Rosetta Energy Function Enable Improved Identification of Small Molecules that Inhibit Protein-Protein Interactions

Protein-protein interactions are among today’s most exciting and promising targets for therapeutic intervention. To date, identifying small-molecules that selectively disrupt these interactions has proven particularly challenging for virtual screening tools, since these have typically been optimized to perform well on more “traditional” drug discovery targets. Here, we test the performance of the Rosetta energy function for identifying compounds that inhibit protein interactions, when these active compounds have been hidden amongst pools of “decoys.” Through this virtual screening benchmark, we gauge the effect of two recent enhancements to the functional form of the Rosetta energy function: the new “Talaris” update and the “pwSHO” solvation model. Finally, we conclude by developing and validating a new weight set that maximizes Rosetta’s ability to pick out the active compounds in this test set. Looking collectively over the course of these enhancements, we find a marked improvement in Rosetta’s ability to identify small-molecule inhibitors of protein-protein interactions.     

From empathy to caring: defining the ideal approach to a healing relationship

In recent years, “empathy” has been identified as a form of emotional engagement beneficial to patient care. Although usage varies, the term refers to sharing the feelings of another as a means of coming to a direct appreciation of the other. Defined this way, however, empathy may lead to mistaken assumptions and an absence of corrective curiosity: Once we think we understand what another is experiencing, we perceive less need to ask, listen, and learn. We propose the process of “caring” in place of “empathy” to embody the ideal emotional and behavioral approach to patient care. Caring refers to both an emotional reaction to another and the expression of that reaction in action, independent of the sharing of the other’s emotion or experience. The expression of caring in the clinical context is close observation, precise listening, and responsive questioning, in concert with committed engagement and actions directly addressing the patient’s problem, stripped of any assumptions about what the other might or might not be experiencing.     

Neural Computations Mediating One-Shot Learning in the Human Brain

Incremental learning, in which new knowledge is acquired gradually through trial and error, can be distinguished from one-shot learning, in which the brain learns rapidly from only a single pairing of a stimulus and a consequence. Very little is known about how the brain transitions between these two fundamentally different forms of learning. Here we test a computational hypothesis that uncertainty about the causal relationship between a stimulus and an outcome induces rapid changes in the rate of learning, which in turn mediates the transition between incremental and one-shot learning. By using a novel behavioral task in combination with functional magnetic resonance imaging (fMRI) data from human volunteers, we found evidence implicating the ventrolateral prefrontal cortex and hippocampus in this process. The hippocampus was selectively “switched” on when one-shot learning was predicted to occur, while the ventrolateral prefrontal cortex was found to encode uncertainty about the causal association, exhibiting increased coupling with the hippocampus for high-learning rates, suggesting this region may act as a “switch,” turning on and off one-shot learning as required.     

Octopamine neuromodulatory effects on a social behavior decision-making network in Drosophila males

Situations requiring rapid decision-making in response to dynamic environmental demands occur repeatedly in natural environments. Neuromodulation can offer important flexibility to the output of neural networks in coping with changing conditions, but the contribution of individual neuromodulatory neurons in social behavior networks remains relatively unknown. Here we manipulate the Drosophila octopaminergic system and assay changes in adult male decision-making in courtship and aggression paradigms. When the functional state of OA neural circuits is enhanced, males exhibit elevated courtship behavior towards other males in both behavioral contexts. Eliminating the expression of the male form of the neural sex determination factor, Fruitless (Fru(M)), in three OA suboesophageal ganglia (SOG) neurons also leads to increased male-male courtship behavior in these same contexts. We analyzed the fine anatomical structure through confocal examination of labeled single neurons to determine the arborization patterns of each of the three Fru(M)-positive OA SOG neurons. These neurons send processes that display mirror symmetric, widely distributed arbors of endings within brain regions including the ventrolateral protocerebra, the SOG and the peri-esophageal complex. The results suggest that a small subset of OA neurons have the potential to provide male selective modulation of behavior at a single neuron level.