Does Cognition Have a Role in Plasticity of "Innate Behavior"? A Perspective From Drosophila

Play-like behavior exhibited by the vinegar fly Drosophila melanogaster

Anecdotal accounts about animals repeatedly exposing themselves to sources of passive movement by engaging with swings, slides, or carousels are generally assumed to be "play." Criteria for play-like behavior require the activity to be (1) of no immediate relevance for survival; (2) voluntary, intentional, and rewarding; (3) non-ethotypical; (4) repeated, yet unstereotyped; and (5) free from stress.1,2 Play-like behavior following these rules is pervasive across the vertebrate subphylum2; recent studies in rats even identified and characterized the involved brain regions.3,4 In invertebrates, sparse reports have so far addressed either social play in parasitoid wasps or spiders,5,6 object play in bumblebees,7 or are anecdotal.1 Contrary to social play or object play, which are thought to train social interaction or muscle/motor skills, respectively, a convincing hypothesis of the adaptive value of voluntary passive movement play-like behavior is currently lacking in any organism. Like other animals, flies are highly sensitive to the direction of gravitational pull,8 hence such intentional passive motion could be sufficient to induce proprioceptive stimulation externally.9 Here, we identify voluntary spinning on a carousel as idiosyncratic play-like behavior in the vinegar fly Drosophila melanogaster: while some flies show spontaneous avoidance, others actively seek stimulation, engaging in repeated, prolonged visits to the carousel. We propose that animals voluntarily expose themselves to external forces, thus intentionally receiving exafferent stimulation. This deliberate, yet indirect, proprioceptive stimulation provides an efficient way to improve self-perception via internal model training and shaping multisensory integration. Importantly, this theoretical framework can now be tested empirically in flies. VIDEO ABSTRACT.

Instinct to insight: Neural correlates of ethological strategy learning

In ethological behaviors like parenting, animals innately follow stereotyped patterns of choices to decide between uncertain outcomes but can learn to modify their strategies to incorporate new information. For example, female mice in a T-maze instinctively use spatial-memory to search for pups where they last found them but can learn more efficient strategies employing pup-associated acoustic cues. We uncovered neural correlates for transitioning between these innate and learned strategies. Auditory cortex (ACx) was required during learning. ACx firing at the nest increased with learning and correlated with subsequent search speed but not outcome. Surprisingly, ACx suppression rather than facilitation during search was more prognostic of correct sound-cued outcomes - even before adopting a sound-cued strategy. Meanwhile medial prefrontal cortex encoded the last pup location, but this decayed as the spatial-memory strategy declined. Our results suggest a neural competition between a weakening spatial-memory and strengthening sound-cued neural representation to mediate strategy switches.

Antennal movements can be used as behavioral readout of odor valence in honey bees

The fact that honey bees have a relatively simple nervous system that allows complex behaviors has made them an outstanding model for studying neurobiological processes. Studies on learning and memory routinely use appetitive and aversive learning paradigms that involve recording of the proboscis or the sting extension. However, these protocols are based on all-or-none responses, which has the disadvantage of occluding intermediate and more elaborated behaviors. Nowadays, the great advances in tracking software and data analysis, combined with affordable video recording systems, have made it possible to extract very detailed information about animal behavior. Here we describe antennal movements that are elicited by odor that have no, positive or negative valence. We show that animals orient their antennae towards the source of the odor when it is positive, and orient them in the opposite direction when the odor is negative. Moreover, we found that this behavior was modified between animals that had been trained based on protocols of different strength. Since this procedure allows a more accurate description of the behavioral outcome using a relatively small number of animals, it represents a great tool for studying different cognitive processes and olfactory perception.

The Neurobiology of Behavior and Its Applicability for Animal Welfare: A Review

Simple Summary

Animal welfare is the result of physical and psychological well-being and is expected to occur if animals are free: (1) from hunger, thirst and malnutrition, (2) from discomfort, (3) from pain, (4) to express normal behavior, and (5) from fear and distress. Nevertheless, well-being is not a constant state but rather the result of certain brain dynamics underlying innate motivated behaviors and learned responses. Thus, by understanding the foundations of the neurobiology of behavior we fathom how emotions and well-being occur in the brain. Herein, we discuss the potential applicability of this approach for animal welfare. First, we provide a general view of the basic responses coordinated by the central nervous system from the processing of internal and external stimuli. Then, we discuss how those stimuli mediate activity in seven neurobiological systems that evoke innate emotional and behavioral responses that directly influence well-being and biological fitness. Finally, we discuss the basic mechanisms of learning and how it affects motivated responses and welfare.

Abstract

Understanding the foundations of the neurobiology of behavior and well-being can help us better achieve animal welfare. Behavior is the expression of several physiological, endocrine, motor and emotional responses that are coordinated by the central nervous system from the processing of internal and external stimuli. In mammals, seven basic emotional systems have been described that when activated by the right stimuli evoke positive or negative innate responses that evolved to facilitate biological fitness. This review describes the process of how those neurobiological systems can directly influence animal welfare. We also describe examples of the interaction between primary (innate) and secondary (learned) processes that influence behavior.

Over-representation of fundamental decision variables in the prefrontal cortex underlies decision bias

The brain is organized into anatomically distinct structures consisting of a variety of projection neurons. While such evolutionarily conserved neural circuit organization underlies the innate ability of animals to swiftly adapt to environments, they can cause biased cognition and behavior. Although recent studies have begun to address the causal importance of projection-neuron types as distinct computational units, it remains unclear how projection types are functionally organized in encoding variables during cognitive tasks. This review focuses on the neural computation of decision making in the prefrontal cortex and discusses what decision variables are encoded by single neurons, neuronal populations, and projection type, alongside how specific projection types constrain decision making. We focus particularly on "over-representations" of distinct decision variables in the prefrontal cortex that reflect the biological and subjective significance of the variables for the decision makers. We suggest that task-specific over-representation in the prefrontal cortex involves the refinement of the given decision making, while generalized over-representation of fundamental decision variables is associated with suboptimal decision biases, including pathological ones such as those in patients with psychiatric disorders. Such over-representation of the fundamental decision variables in the prefrontal cortex appear to be tightly constrained by afferent and efferent connections that can be optogenetically intervened on. These ideas may provide critical insights into potential therapeutic targets for psychiatric disorders, including addiction and depression.

Studying neural circuits of decision-making in Drosophila larva

To study neural circuits underlying decisions, the model organism used for that purpose has to be simple enough to be able to dissect the circuitry neuron by neuron across the nervous system and in the same time complex enough to be able to perform different types of decisions. Here, I lay out the case: (1) that Drosophila larva is an advantageous model system that balances well these two requirements and (2) the insights gained from this model, assuming that circuit principles may be shared across species, can be used to advance our knowledge of neural circuit implementation of decision-making in general, including in more complex brains.

The case for emulating insect brains using anatomical "wiring diagrams" equipped with biophysical models of neuronal activity

Developing whole-brain emulation (WBE) technology would provide immense benefits across neuroscience, biomedicine, artificial intelligence, and robotics. At this time, constructing a simulated human brain lacks feasibility due to limited experimental data and limited computational resources. However, I suggest that progress toward this goal might be accelerated by working toward an intermediate objective, namely insect brain emulation (IBE). More specifically, this would entail creating biologically realistic simulations of entire insect nervous systems along with more approximate simulations of non-neuronal insect physiology to make "virtual insects." I argue that this could be realistically achievable within the next 20 years. I propose that developing emulations of insect brains will galvanize the global community of scientists, businesspeople, and policymakers toward pursuing the loftier goal of emulating the human brain. By demonstrating that WBE is possible via IBE, simulating mammalian brains and eventually the human brain may no longer be viewed as too radically ambitious to deserve substantial funding and resources. Furthermore, IBE will facilitate dramatic advances in cognitive neuroscience, artificial intelligence, and robotics through studies performed using virtual insects.

MARGO (Massively Automated Real-time GUI for Object-tracking), a platform for high-throughput ethology

Fast object tracking in real time allows convenient tracking of very large numbers of animals and closed-loop experiments that control stimuli for many animals in parallel. We developed MARGO, a MATLAB-based, real-time animal tracking suite for custom behavioral experiments. We demonstrated that MARGO can rapidly and accurately track large numbers of animals in parallel over very long timescales, typically when spatially separated such as in multiwell plates. We incorporated control of peripheral hardware, and implemented a flexible software architecture for defining new experimental routines. These features enable closed-loop delivery of stimuli to many individuals simultaneously. We highlight MARGO's ability to coordinate tracking and hardware control with two custom behavioral assays (measuring phototaxis and optomotor response) and one optogenetic operant conditioning assay. There are currently several open source animal trackers. MARGO's strengths are 1) fast and accurate tracking, 2) high throughput, 3) an accessible interface and data output and 4) real-time closed-loop hardware control for for sensory and optogenetic stimuli, all of which are optimized for large-scale experiments.

MARGO (Massively Automated Real-time GUI for Object-tracking), a platform for high-throughput ethology

Fast object tracking in real time allows convenient tracking of very large numbers of animals and closed-loop experiments that control stimuli for many animals in parallel. We developed MARGO, a MATLAB-based, real-time animal tracking suite for custom behavioral experiments. We demonstrated that MARGO can rapidly and accurately track large numbers of animals in parallel over very long timescales, typically when spatially separated such as in multiwell plates. We incorporated control of peripheral hardware, and implemented a flexible software architecture for defining new experimental routines. These features enable closed-loop delivery of stimuli to many individuals simultaneously. We highlight MARGO's ability to coordinate tracking and hardware control with two custom behavioral assays (measuring phototaxis and optomotor response) and one optogenetic operant conditioning assay. There are currently several open source animal trackers. MARGO's strengths are 1) fast and accurate tracking, 2) high throughput, 3) an accessible interface and data output and 4) real-time closed-loop hardware control for for sensory and optogenetic stimuli, all of which are optimized for large-scale experiments.