HomeResearchNeural Circuits for Innate, "Emotional" Behaviors in Flies and Mice

Our Scientists

Neural Circuits for Innate, "Emotional" Behaviors in Flies and Mice

Research Summary

David Anderson is using molecular genetic techniques to map and functionally dissect neural circuits that underlie emotional behaviors, such as aggression and defensive behaviors, in both mice and fruit flies. These innate behavioral responses and associated internal states (such as arousal) form the evolutionary underpinnings of emotional behavior in higher organisms. These studies may ultimately lead to a deeper understanding of human psychiatric disorders.

Intermale aggression in Drosophila melanogaster...

Research in this laboratory is aimed at understanding the neurobiology of emotion. We seek to elucidate how fundamental properties common to emotional states, such as arousal, are encoded in the circuitry and chemistry of the brain and how these internal states combine with sensory stimuli to elicit specific emotional behaviors, such as fear or aggression. Our work employs molecular genetic tools to mark, map, and manipulate specific circuits to determine how identifiable populations of neurons contribute in a causal manner to behavior. These studies are complemented by the use of electrophysiology and functional imaging to measure activity in neural circuits. We use mice and the fruit fly Drosophila melanogaster as model organisms, with roughly equal emphasis on each.

Emotion Circuits in the Mouse Brain
Research using the laboratory mouse Mus musculus focuses on understanding the neural circuitry of fear/anxiety, aggression, and pain/pleasure.

Our studies of fear are currently centered on the function of circuits in the amygdala, a medial temporal lobe structure that plays an important role in Pavlovian learned fear, a form of classical conditioning. We have identified genes that mark several subpopulations of neurons that form a dynamic microcircuit within the central nucleus of the amygdala. The function of this microcircuit in fear behavior has been dissected using optogenetic tools, such as channelrhodopsin, and pharmacogenetic tools, such as the ivermectin-gated glutamate-sensitive chloride channel (GluCl), together with acute slice electrophysiology and genetically based anatomical tracing of synaptic pathways. These studies have revealed unexpected functions for inhibitory microcircuits in the control of information processing within the amygdala.

In the case of aggression, we are focusing on circuits within the hypothalamus, an area that has long been known to control innate, goal-directed behaviors such as feeding, mating, and fighting. We are using chronic in vivo multiunit recording to probe the relationship between neuronal activity and aggression, as well as mating, and we have also employed genetically based functional perturbations to understand how these two related social behaviors are processed by hypothalamic structures. Our results revealed that the ventromedial hypothalamic nucleus contains distinct but partially overlapping populations of neurons active during both mating and aggressive behavior. This suggests that the circuitry for these behaviors is intimately linked in the brain, a result with clear implications for psychiatry.

Pain has both a sensory and an affective component. We have used genetically based methods to probe the functional roles of different subpopulations of primary sensory neurons identified by the expression of Mrgprs, a family of orphan G protein–coupled receptors (GPCRs) that we previously discovered. Our results indicate that sensory neurons expressing different members of this GPCR family are involved in processing either noxious (painful) or pleasant stimuli. These data support the idea that the distinct sensations and affective states produced by different types of cutaneous stimuli are mediated by modality-specific subsets of C-fibers, which presumably engage distinct higher-order circuits in the central brain.

Emotion Circuits in Drosophila
The pioneering work of the late Seymour Benzer (California Institute of Technology) proved that the powerful genetics of Drosophila could be used to dissect the genetic underpinnings of many types of complex behaviors. Until recently, however, it was not clear whether this model system could also be applied to understanding the neurobiology of emotion and affect. We are taking two complementary approaches to investigate this question. One approach is to dissect the neural circuitry underlying behaviors that are analogous to defensive behaviors in higher organisms, such as avoidance, behavioral inhibition, or aggression. Our studies of aggression have identified pheromones that control this behavior, and shown that they act in a hierarchical manner.

More recently, we have discovered male-specific neurons that play a key role in aggression, but not in courtship behavior. These neurons express a neuropeptide, tachykinin, whose vertebrate homolog substance P has been implicated in the control of aggression in several mammalian systems. Moreover, increased levels of substance P in the cerebrospinal fluid have been correlated with increased aggressiveness in human patients with borderline personality disorder. These data represent the first identification of a gene with a conserved role in aggression from flies to mammals. Additional work on aggression circuitry in flies, and the relationship of these circuits to those controlling mating behavior, is revealing remarkable analogies with aggression and mating circuitry in mice.

A complementary approach to the study of emotional behaviors in Drosophila is to model internal states or processes that are fundamental to many types of emotional responses, such as arousal. These studies have revealed that arousal is not unitary, but rather that there are different types of behavior-specific arousal states that can be oppositely regulated by the same dopamine receptor acting in different neural circuits. These studies have depended on the development of novel behavioral assays, as well as (in collaboration with Pietro Perona, Caltech) automated behavior-detection algorithms based on machine vision and machine learning, to facilitate the objectivity and throughput of behavioral measurements.

Grants from the National Institutes of Health, the National Science Foundation, the Brain and Behavior Research Foundation, the Weston Havens Foundation, the Ellison Medical Foundation, and the Paul G. Allen Family Foundation supported portions of this work.

As of December 3, 2013

Scientist Profile

Investigator
California Institute of Technology
Genetics, Neuroscience