The biology of psychology: 'Simple' conditioning?

Wings of Change: aPKC/FoxP-dependent plasticity in steering motor neurons underlies operant self-learning in Drosophila

Background

Motor learning is central to human existence, such as learning to speak or walk, sports moves, or rehabilitation after injury. Evidence suggests that all forms of motor learning share an evolutionarily conserved molecular plasticity pathway. Here, we present novel insights into the neural processes underlying operant self-learning, a form of motor learning in the fruit fly Drosophila.

Methods

We operantly trained wild type and transgenic Drosophila fruit flies, tethered at the torque meter, in a motor learning task that required them to initiate and maintain turning maneuvers around their vertical body axis (yaw torque). We combined this behavioral experiment with transgenic peptide expression, CRISPR/Cas9-mediated, spatio-temporally controlled gene knock-out and confocal microscopy.

Results

We find that expression of atypical protein kinase C (aPKC) in direct wing steering motoneurons co-expressing the transcription factor FoxP is necessary for this type of motor learning and that aPKC likely acts via non-canonical pathways. We also found that it takes more than a week for CRISPR/Cas9-mediated knockout of FoxP in adult animals to impair motor learning, suggesting that adult FoxP expression is required for operant self-learning.

Conclusions

Our experiments suggest that, for operant self-learning, a type of motor learning in Drosophila, co-expression of atypical protein kinase C (aPKC) and the transcription factor FoxP is necessary in direct wing steering motoneurons. Some of these neurons control the wing beat amplitude when generating optomotor responses, and we have discovered modulation of optomotor behavior after operant self-learning. We also discovered that aPKC likely acts via non-canonical pathways and that FoxP expression is also required in adult flies.

Human Factors at Play: Understanding the Impact of Conditioning on Presence and Reaction Time in Mixed Reality

A prerequisite to improving the presence of a user in mixed reality (MR) is the ability to measure and quantify presence. Traditionally, subjective questionnaires have been used to assess the level of presence. However, recent studies have shown that presence is correlated with objective and systemic human performance measures such as reaction time. These studies analyze the correlation between presence and reaction time when technical factors such as object realism and plausibility of the object's behavior change. However, additional psychological and physiological human factors can also impact presence. It is unclear if presence can be mapped to and correlated with reaction time when human factors such as conditioning are involved. To answer this question, we conducted an exploratory study ($N=60$) where the relationship between presence and reaction time was assessed under three different conditioning scenarios: control, positive, and negative. We demonstrated that human factors impact presence. We found that presence scores and reaction times are significantly correlated (correlation coefficient of -0.64), suggesting that the impact of human factors on reaction time correlates with its effect on presence. In demonstrating that, our study takes another important step toward using objective and systemic measures like reaction time as a presence measure.

Associative learning in the box jellyfish Tripedalia cystophora

Associative learning, such as classical or operant conditioning, has never been unequivocally associated with animals outside bilatarians, e.g., vertebrates, arthropods, or mollusks. Learning modulates behavior and is imperative for survival in the vast majority of animals. Obstacle avoidance is one of several visually guided behaviors in the box jellyfish, Tripedalia cystophora Conant, 1897 (Cnidaria: Cubozoa), and it is intimately associated with foraging between prop roots in their mangrove habitat. The obstacle avoidance behavior (OAB) is a species-specific defense reaction (SSDR) for T. cystophora, so identifying such SSDR is essential for testing the learning capacity of a given animal. Using the OAB, we show that box jellyfish performed associative learning (operant conditioning). We found that the rhopalial nervous system is the learning center and that T. cystophora combines visual and mechanical stimuli during operant conditioning. Since T. cystophora has a dispersed central nervous system lacking a conventional centralized brain, our work challenges the notion that associative learning requires complex neuronal circuitry. Moreover, since Cnidaria is the sister group to Bilateria, it suggests the intriguing possibility that advanced neuronal processes, like operant conditioning, are a fundamental property of all nervous systems.

High-throughput automated methods for classical and operant conditioning of Drosophila larvae

Learning which stimuli (classical conditioning) or which actions (operant conditioning) predict rewards or punishments can improve chances of survival. However, the circuit mechanisms that underlie distinct types of associative learning are still not fully understood. Automated, high-throughput paradigms for studying different types of associative learning, combined with manipulation of specific neurons in freely behaving animals, can help advance this field. The Drosophila melanogaster larva is a tractable model system for studying the circuit basis of behaviour, but many forms of associative learning have not yet been demonstrated in this animal. Here, we developed a high-throughput (i.e. multi-larva) training system that combines real-time behaviour detection of freely moving larvae with targeted opto- and thermogenetic stimulation of tracked animals. Both stimuli are controlled in either open- or closed-loop, and delivered with high temporal and spatial precision. Using this tracker, we show for the first time that Drosophila larvae can perform classical conditioning with no overlap between sensory stimuli (i.e. trace conditioning). We also demonstrate that larvae are capable of operant conditioning by inducing a bend direction preference through optogenetic activation of reward-encoding serotonergic neurons. Our results extend the known associative learning capacities of Drosophila larvae. Our automated training rig will facilitate the study of many different forms of associative learning and the identification of the neural circuits that underpin them.

Sleep and conditioning of the siphon withdrawal reflex in Aplysia

Sleep is essential for memory consolidation after learning as shown in mammals and invertebrates such as bees and flies. Aplysia californica displays sleep, and sleep in this mollusk was also found to support memory for an operant conditioning task. Here, we investigated whether sleep in Aplysia is also required for memory consolidation in a simpler type of learning, i.e. the conditioning of the siphon withdrawal reflex. Two groups of animals (Wake, Sleep, each n=11) were conditioned on the siphon withdrawal reflex, with the training following a classical conditioning procedure where an electrical tail shock served as the unconditioned stimulus (US) and a tactile stimulus to the siphon as the conditioned stimulus (CS). Responses to the CS were tested before (pre-test), and 24 and 48 h after training. While Wake animals remained awake for 6 h after training, Sleep animals had undisturbed sleep. The 24 h test in both groups was combined with extinction training, i.e. the extended presentation of the CS alone over two blocks. At the 24 h test, siphon withdrawal duration in response to the CS was distinctly enhanced in both Sleep and Wake groups with no significant difference between groups, consistent with the view that consolidation of a simple conditioned reflex response does not require post-training sleep. Surprisingly, extinction training did not reverse the enhancement of responses to the CS. On the contrary, at the 48 h test, withdrawal duration in response to the CS was even further enhanced across both groups. This suggests that processes of sensitization, an even simpler non-associative type of learning, contributed to the withdrawal responses. Our study provides evidence for the hypothesis that sleep preferentially benefits consolidation of more complex learning paradigms than conditioning of simple reflexes.

Evolutionary transitions in learning and cognition

We define a cognitive system as a system that can learn, and adopt an evolutionary-transition-oriented framework for analysing different types of neural cognition. This enables us to classify types of cognition and point to the continuities and discontinuities among them. The framework we use for studying evolutionary transitions in learning capacities focuses on qualitative changes in the integration, storage and use of neurally processed information. Although there are always grey areas around evolutionary transitions, we recognize five major neural transitions, the first two of which involve animals at the base of the phylogenetic tree: (i) the evolutionary transition from learning in non-neural animals to learning in the first neural animals; (ii) the transition to animals showing limited, elemental associative learning, entailing neural centralization and primary brain differentiation; (iii) the transition to animals capable of unlimited associative learning, which, on our account, constitutes sentience and entails hierarchical brain organization and dedicated memory and value networks; (iv) the transition to imaginative animals that can plan and learn through selection among virtual events; and (v) the transition to human symbol-based cognition and cultural learning. The focus on learning provides a unifying framework for experimental and theoretical studies of cognition in the living world. This article is part of the theme issue 'Basal cognition: multicellularity, neurons and the cognitive lens'.

The Transition to Minimal Consciousness through the Evolution of Associative Learning

The minimal state of consciousness is sentience. This includes any phenomenal sensory experience - exteroceptive, such as vision and olfaction; interoceptive, such as pain and hunger; or proprioceptive, such as the sense of bodily position and movement. We propose unlimited associative learning (UAL) as the marker of the evolutionary transition to minimal consciousness (or sentience), its phylogenetically earliest sustainable manifestation and the driver of its evolution. We define and describe UAL at the behavioral and functional level and argue that the structural-anatomical implementations of this mode of learning in different taxa entail subjective feelings (sentience). We end with a discussion of the implications of our proposal for the distribution of consciousness in the animal kingdom, suggesting testable predictions, and revisiting the ongoing debate about the function of minimal consciousness in light of our approach.

PKC in motorneurons underlies self-learning, a form of motor learning in Drosophila

Tethering a fly for stationary flight allows for exquisite control of its sensory input, such as visual or olfactory stimuli or a punishing infrared laser beam. A torque meter measures the turning attempts of the tethered fly around its vertical body axis. By punishing, say, left turning attempts (in a homogeneous environment), one can train a fly to restrict its behaviour to right turning attempts. It was recently discovered that this form of operant conditioning (called operant self-learning), may constitute a form of motor learning in Drosophila. Previous work had shown that Protein Kinase C (PKC) and the transcription factor dFoxP were specifically involved in self-learning, but not in other forms of learning. These molecules are specifically involved in various forms of motor learning in other animals, such as compulsive biting in Aplysia, song-learning in birds, procedural learning in mice or language acquisition in humans. Here we describe our efforts to decipher which PKC gene is involved in self-learning in Drosophila. We also provide evidence that motorneurons may be one part of the neuronal network modified during self-learning experiments. The collected evidence is reminiscent of one of the simplest, clinically relevant forms of motor learning in humans, operant reflex conditioning, which also relies on motorneuron plasticity.

Drosophila FoxP mutants are deficient in operant self-learning

Intact function of the Forkhead Box P2 (FOXP2) gene is necessary for normal development of speech and language. This important role has recently been extended, first to other forms of vocal learning in animals and then also to other forms of motor learning. The homology in structure and in function among the FoxP gene members raises the possibility that the ancestral FoxP gene may have evolved as a crucial component of the neural circuitry mediating motor learning. Here we report that genetic manipulations of the single Drosophila orthologue, dFoxP, disrupt operant self-learning, a form of motor learning sharing several conceptually analogous features with language acquisition. Structural alterations of the dFoxP locus uncovered the role of dFoxP in operant self-learning and habit formation, as well as the dispensability of dFoxP for operant world-learning, in which no motor learning occurs. These manipulations also led to subtle alterations in the brain anatomy, including a reduced volume of the optic glomeruli. RNAi-mediated interference with dFoxP expression levels copied the behavioral phenotype of the mutant flies, even in the absence of mRNA degradation. Our results provide evidence that motor learning and language acquisition share a common ancestral trait still present in extant invertebrates, manifest in operant self-learning. This 'deep' homology probably traces back to before the split between vertebrate and invertebrate animals.

Selective prey avoidance learning in the predatory sea slug Pleurobranchaea californica

Predator-prey interactions involving aposematic signaling, where predators learn the warning cues of well-defended prey, are clear examples of cost-benefit decisions in foraging animals. However, knowledge of the selectivity of predator learning and the natural conditions where it occurs is lacking for those foragers simpler in brain and body plan. We pursued the question in the sea slug Pleurobranchaea californica, a generalist forager of marked simplicity of body form, nervous system and behavior. This predator exploits many different types of prey, some of which are costly to attack. When offered Flabellina iodinea, an aeolid nudibranch with a stinging defense, biting attack was followed by rapid rejection and aversive turns. The predatory sea slug rapidly learned avoidance. Notable exceptions were animals with extremely high or low feeding thresholds that either ignored F. iodinea or completely consumed it, respectively. Experienced slugs showed strong avoidance of F. iodinea for days after exposure. Aposematic odor learning was selective: avoidance was not linked to change in feeding thresholds, and trained animals readily attacked and consumed a related aeolid, Hermissenda crassicornis. For P. californica, aposematic learning is a cognitive adaptation in which sensation, motivation and memory are integrated to direct cost-benefit choice, and thereby lend flexibility to the generalist's foraging strategy.

Towards a scientific concept of free will as a biological trait: spontaneous actions and decision-making in invertebrates

Until the advent of modern neuroscience, free will used to be a theological and a metaphysical concept, debated with little reference to brain function. Today, with ever increasing understanding of neurons, circuits and cognition, this concept has become outdated and any metaphysical account of free will is rightfully rejected. The consequence is not, however, that we become mindless automata responding predictably to external stimuli. On the contrary, accumulating evidence also from brains much smaller than ours points towards a general organization of brain function that incorporates flexible decision-making on the basis of complex computations negotiating internal and external processing. The adaptive value of such an organization consists of being unpredictable for competitors, prey or predators, as well as being able to explore the hidden resource deterministic automats would never find. At the same time, this organization allows all animals to respond efficiently with tried-and-tested behaviours to predictable and reliable stimuli. As has been the case so many times in the history of neuroscience, invertebrate model systems are spearheading these research efforts. This comparatively recent evidence indicates that one common ability of most if not all brains is to choose among different behavioural options even in the absence of differences in the environment and perform genuinely novel acts. Therefore, it seems a reasonable effort for any neurobiologist to join and support a rather illustrious list of scholars who are trying to wrestle the term 'free will' from its metaphysical ancestry. The goal is to arrive at a scientific concept of free will, starting from these recently discovered processes with a strong emphasis on the neurobiological mechanisms underlying them.