Neuronal microcircuits for decision making in C. elegans

C. elegans foraging as a model for understanding the neuronal basis of decision-making

Animals have evolved to seek, select, and exploit food sources in their environment. Collectively termed foraging, these ubiquitous behaviors are necessary for animal survival. As a foundation for understanding foraging, behavioral ecologists established early theoretical and mathematical frameworks which have been subsequently refined and supported by field and laboratory studies of foraging animals. These simple models sought to explain how animals decide which strategies to employ when locating food, what food items to consume, and when to explore the environment for new food sources. These foraging decisions involve integration of prior experience with multimodal sensory information about the animal's current environment and internal state. We suggest that the nematode Caenorhabditis elegans is well-suited for a high-resolution analysis of complex goal-oriented behaviors such as foraging. We focus our discussion on behavioral studies highlighting C. elegans foraging on bacteria and summarize what is known about the underlying neuronal and molecular pathways. Broadly, we suggest that this simple model system can provide a mechanistic understanding of decision-making and present additional avenues for advancing our understanding of complex behavioral processes.

Innate Orientating Behavior of a Multi-Legged Robot Driven by the Neural Circuits of C. elegans

The objective of this research is to achieve biologically autonomous control by utilizing a whole-brain network model, drawing inspiration from biological neural networks to enhance the development of bionic intelligence. Here, we constructed a whole-brain neural network model of Caenorhabditis elegans (C. elegans), which characterizes the electrochemical processes at the level of the cellular synapses. The neural network simulation integrates computational programming and the visualization of the neurons and synapse connections of C. elegans, containing the specific controllable circuits and their dynamic characteristics. To illustrate the biological neural network (BNN)'s particular intelligent control capability, we introduced an innovative methodology for applying the BNN model to a 12-legged robot's movement control. Two methods were designed, one involving orientation control and the other involving locomotion generation, to demonstrate the intelligent control performance of the BNN. Both the simulation and experimental results indicate that the robot exhibits more autonomy and a more intelligent movement performance under BNN control. The systematic approach of employing the whole-brain BNN for robot control provides biomimetic research with a framework that has been substantiated by innovative methodologies and validated through the observed positive outcomes. This method is established as follows: (1) two integrated dynamic models of the C. elegans' whole-brain network and the robot moving dynamics are built, and all of the controllable circuits are discovered and verified; (2) real-time communication is achieved between the BNN model and the robot's dynamical model, both in the simulation and the experiments, including applicable encoding and decoding algorithms, facilitating their collaborative operation; (3) the designed mechanisms using the BNN model to control the robot are shown to be effective through numerical and experimental tests, focusing on 'foraging' behavior control and locomotion control.

A tonically active master neuron modulates mutually exclusive motor states at two timescales

Continuity of behaviors requires animals to make smooth transitions between mutually exclusive behavioral states. Neural principles that govern these transitions are not well understood. Caenorhabditis elegans spontaneously switch between two opposite motor states, forward and backward movement, a phenomenon thought to reflect the reciprocal inhibition between interneurons AVB and AVA. Here, we report that spontaneous locomotion and their corresponding motor circuits are not separately controlled. AVA and AVB are neither functionally equivalent nor strictly reciprocally inhibitory. AVA, but not AVB, maintains a depolarized membrane potential. While AVA phasically inhibits the forward promoting interneuron AVB at a fast timescale, it maintains a tonic, extrasynaptic excitation on AVB over the longer timescale. We propose that AVA, with tonic and phasic activity of opposite polarities on different timescales, acts as a master neuron to break the symmetry between the underlying forward and backward motor circuits. This master neuron model offers a parsimonious solution for sustained locomotion consisted of mutually exclusive motor states.

Specific configurations of electrical synapses filter sensory information to drive choices in behavior

Synaptic configurations in precisely wired circuits underpin how sensory information is processed by the nervous system, and the emerging animal behavior. This is best understood for chemical synapses, but far less is known about how electrical synaptic configurations modulate, in vivo and in specific neurons, sensory information processing and context-specific behaviors. We discovered that INX-1, a gap junction protein that forms electrical synapses, is required to deploy context-specific behavioral strategies during C. elegans thermotaxis behavior. INX-1 couples two bilaterally symmetric interneurons, and this configuration is required for the integration of sensory information during migration of animals across temperature gradients. In inx-1 mutants, uncoupled interneurons display increased excitability and responses to subthreshold temperature stimuli, resulting in abnormally longer run durations and context-irrelevant tracking of isotherms. Our study uncovers a conserved configuration of electrical synapses that, by increasing neuronal capacitance, enables differential processing of sensory information and the deployment of context-specific behavioral strategies.

A Novel and Functionally Diverse Class of Acetylcholine-Gated Ion Channels

Fast cholinergic neurotransmission is mediated by acetylcholine-gated ion channels; in particular, excitatory nicotinic acetylcholine receptors play well established roles in virtually all nervous systems. Acetylcholine-gated inhibitory channels have also been identified in some invertebrate phyla, yet their roles in the nervous system are less well understood. We report the existence of multiple new inhibitory ion channels with diverse ligand activation properties in Caenorhabditis elegans We identify three channels, LGC-40, LGC-57, and LGC-58, whose primary ligand is choline rather than acetylcholine, as well as the first evidence of a truly polymodal channel, LGC-39, which is activated by both cholinergic and aminergic ligands. Using our new ligand-receptor pairs we uncover the surprising extent to which single neurons in the hermaphrodite nervous system express both excitatory and inhibitory channels, not only for acetylcholine but also for the other major neurotransmitters. The results presented in this study offer new insight into the potential evolutionary benefit of a vast and diverse repertoire of ligand-gated ion channels to generate complexity in an anatomically compact nervous system.SIGNIFICANCE STATEMENT Here we describe the diversity of cholinergic signaling in the nematode Caenorhabditis elegans We identify and characterize a novel family of ligand-gated ion channels and show that they are preferentially gated by choline rather than acetylcholine and expressed broadly in the nervous system. Interestingly, we also identify one channel gated by chemically diverse ligands including acetylcholine and aminergic ligands. By using our new knowledge of these ligand-gated ion channels, we built a model to predict the synaptic polarity in the C. elegans connectome. This model can be used for generating hypotheses on neural circuit function.

Theory and practice of using cell strainers to sort Caenorhabditis elegans by size

The nematode Caenorhabditis elegans is a model organism widely used in basic, translational, and industrial research. C. elegans development is characterized by five morphologically distinct stages, including four larval stages and the adult stage. Stages differ in a variety of aspects including size, gene expression, physiology, and behavior. Enrichment for a particular developmental stage is often the first step in experimental design. When many hundreds of worms are required, the standard methods of enrichment are to grow a synchronized population of hatchlings for a fixed time, or to sort a mixed population of worms according to size. Current size-sorting methods have higher throughput than synchronization and avoid its use of harsh chemicals. However, these size-sorting methods currently require expensive instrumentation or custom microfluidic devices, both of which are unavailable to the majority C. elegans laboratories. Accordingly, there is a need for inexpensive, accessible sorting strategies. We investigated the use of low-cost, commercially available cell strainers to filter C. elegans by size. We found that the probability of recovery after filtration as a function of body size for cell strainers of three different mesh sizes is well described by logistic functions. Application of these functions to predict filtration outcomes revealed non-ideal properties of filtration of worms by cell strainers that nevertheless enhanced filtration outcomes. Further, we found that serial filtration using a pair of strainers that have different mesh sizes can be used to enrich for particular larval stages with a purity close to that of synchronization, the most widely used enrichment method. Throughput of the cell strainer method, up to 14,000 worms per minute, greatly exceeds that of other enrichment methods. We conclude that size sorting by cell strainers is a useful addition to the array of existing methods for enrichment of particular developmental stages in C. elegans.

Interneuron control of C. elegans developmental decision-making

Natural environments are highly dynamic, and this complexity challenges animals to accurately integrate external cues to shape their responses. Adaptive developmental plasticity enables organisms to remodel their physiology, morphology, and behavior to better suit the predicted future environment and ultimately enhance their ecological success.¹ Understanding how an animal generates a neural representation of current and forecasted environmental conditions and converts these circuit computations into a predictive adaptive physiological response may provide fundamental insights into the molecular and cellular basis of decision-making over developmentally relevant timescales. Although it is known that sensory cues usually trigger the developmental switch and that downstream inter-tissue signaling pathways enact the alternative developmental phenotype, the integrative neural mechanisms that transduce external inputs into effector pathways are less clear.^2,3 In adverse environments, Caenorhabditis elegans larvae can enter a stress-resistant diapause state with arrested metabolism and reproductive physiology.⁴ Amphid sensory neurons feed into both rapid chemotactic and short-term foraging mode decisions, mediated by amphid and pre-motor interneurons, as well as the long-term diapause entry decision. Here, we identify amphid interneurons that integrate pheromone cues and propagate this information via a neuropeptidergic pathway to influence larval developmental fate, bypassing the pre-motor system. AIA interneuron-derived FLP-2 neuropeptide signaling promotes reproductive growth, and AIA activity is suppressed by pheromones. FLP-2 signaling is inhibited by upstream glutamatergic transmission via the metabotropic receptor MGL-1 and mediated by the broadly expressed neuropeptide G-protein-coupled receptor NPR-30. Thus, metabotropic signaling allows the reuse of parts of a sensory system for a decision with a distinct timescale.

Modelling learning in C. elegans chemosensory and locomotive circuitry for T-maze navigation

Recently, a new type of Caenorhabditis elegans associative learning was reported, where nematodes learn to reach a target arm in an empty T‐maze, after they have successfully located reward (food) in the same side arm of a similar, baited, training maze. Here, we present a simplified mathematical model of C. elegans chemosensory and locomotive circuitry that replicates C. elegans navigation in a T‐maze and predicts the underlying mechanisms generating maze learning. Based on known neural circuitry, the model circuit responds to food‐released chemical cues by modulating motor neuron activity that drives simulated locomotion. We show that, through modulation of interneuron activity, such a circuit can mediate maze learning by acquiring a turning bias, even after a single training session. Simulated nematode maze navigation during training conditions in food‐baited mazes and during testing conditions in empty mazes is validated by comparing simulated behaviour with new experimental video data, extracted through the implementation of a custom‐made maze tracking algorithm. Our work provides a mathematical framework for investigating the neural mechanisms underlying this novel learning behaviour in C. elegans. Model results predict neuronal components involved in maze and spatial learning and identify target neurons and potential neural mechanisms for future experimental investigations into this learning behaviour.

A specialized spinal circuit for command amplification and directionality during escape behavior

We are constantly faced with a choice moving to the left or right; understanding how the brain solves the selection of action direction is of tremendous interest both from biological and clinical perspectives. In vertebrates, action selection is often considered to be the realm of higher cognitive processing. However, by combining electrophysiology, serial block-face electron microscopy, and behavioral analyses in zebrafish, we have revealed a pivotal role, as well as the full functional connectome of a specialized spinal circuit relying on strong axo-axonic synaptic connections. This includes identifying a class of cholinergic V2a interneurons and establishing that they act as a segmentally repeating hub that receives and amplifies escape commands from the brain to ensure the appropriate escape directionality.

In vertebrates, action selection often involves higher cognition entailing an evaluative process. However, urgent tasks, such as defensive escape, require an immediate implementation of the directionality of escape trajectory, necessitating local circuits. Here we reveal a specialized spinal circuit for the execution of escape direction in adult zebrafish. A central component of this circuit is a unique class of segmentally repeating cholinergic V2a interneurons expressing the transcription factor Chx10. These interneurons amplify brainstem-initiated escape commands and rapidly deliver the excitation via a feedforward circuit to all fast motor neurons and commissural interneurons to direct the escape maneuver. The information transfer within this circuit relies on fast and reliable axo-axonic synaptic connections, bypassing soma and dendrites. Unilateral ablation of cholinergic V2a interneurons eliminated escape command propagation. Thus, in vertebrates, local spinal circuits can implement directionality of urgent motor actions vital for survival.

From Bench to Keyboard and Back Again: A Brief History of Lambda Phage Modeling

Cellular decision making is the process whereby cells choose one developmental pathway from multiple possible ones, either spontaneously or due to environmental stimuli. Examples in various cell types suggest an almost inexhaustible plethora of underlying molecular mechanisms. In general, cellular decisions rely on the gene regulatory network, which integrates external signals to drive cell fate choice. The search for general principles of such a process benefits from appropriate biological model systems that reveal how and why certain gene regulatory mechanisms drive specific cellular decisions according to ecological context and evolutionary outcomes. In this article, we review the historical and ongoing development of the phage lambda lysis-lysogeny decision as a model system to investigate all aspects of cellular decision making. The unique generality, simplicity, and richness of phage lambda decision making render it a constant source ofmathematical modeling-aided inspiration across all of biology. We discuss the origins and progress of quantitative phage lambda modeling from the 1950s until today, as well as its possible future directions. We provide examples of how modeling enabled methods and theory development, leading to new biological insights by revealing gaps in the theory and pinpointing areas requiring further experimental investigation. Overall, we highlight the utility of theoretical approaches both as predictive tools, to forecast the outcome of novel experiments, and as explanatory tools, to elucidate the natural processes underlying experimental data.

Caenorhabditis elegans learning in a structured maze is a multisensory behavior

We show that C. elegans nematodes learn to associate food with a combination of proprioceptive cues and information on the structure of their surroundings (maze), perceived through mechanosensation. By using the custom-made Worm-Maze platform, we demonstrate that C. elegans young adults can locate food in T-shaped mazes and, following that experience, learn to reach a specific maze arm. C. elegans learning inside the maze is possible after a single training session, it resembles working memory, and it prevails over conflicting environmental cues. We provide evidence that the observed learning is a food-triggered multisensory behavior, which requires mechanosensory and proprioceptive input, and utilizes cues about the structural features of nematodes' environment and their body actions. The CREB-like transcription factor and dopamine signaling are also involved in maze performance. Lastly, we show that the observed aging-driven decline of C. elegans learning ability in the maze can be reversed by starvation.

Chemosensory signal transduction in Caenorhabditis elegans

Chemosensory neurons translate perception of external chemical cues, including odorants, tastants, and pheromones, into information that drives attraction or avoidance motor programs. In the laboratory, robust behavioral assays, coupled with powerful genetic, molecular and optical tools, have made Caenorhabditis elegans an ideal experimental system in which to dissect the contributions of individual genes and neurons to ethologically relevant chemosensory behaviors. Here, we review current knowledge of the neurons, signal transduction molecules and regulatory mechanisms that underlie the response of C. elegans to chemicals, including pheromones. The majority of identified molecules and pathways share remarkable homology with sensory mechanisms in other organisms. With the development of new tools and technologies, we anticipate that continued study of chemosensory signal transduction and processing in C. elegans will yield additional new insights into the mechanisms by which this animal is able to detect and discriminate among thousands of chemical cues with a limited sensory neuron repertoire.

Adaptive behaviour and learning in slime moulds: the role of oscillations

The slime mould Physarum polycephalum, an aneural organism, uses information from previous experiences to adjust its behaviour, but the mechanisms by which this is accomplished remain unknown. This article examines the possible role of oscillations in learning and memory in slime moulds. Slime moulds share surprising similarities with the network of synaptic connections in animal brains. First, their topology derives from a network of interconnected, vein-like tubes in which signalling molecules are transported. Second, network motility, which generates slime mould behaviour, is driven by distinct oscillations that organize into spatio-temporal wave patterns. Likewise, neural activity in the brain is organized in a variety of oscillations characterized by different frequencies. Interestingly, the oscillating networks of slime moulds are not precursors of nervous systems but, rather, an alternative architecture. Here, we argue that comparable information-processing operations can be realized on different architectures sharing similar oscillatory properties. After describing learning abilities and oscillatory activities of P. polycephalum, we explore the relation between network oscillations and learning, and evaluate the organism's global architecture with respect to information-processing potential. We hypothesize that, as in the brain, modulation of spontaneous oscillations may sustain learning in slime mould. This article is part of the theme issue 'Basal cognition: conceptual tools and the view from the single cell'.

Dopamine neurons do not constitute an obligatory stage in the final common path for the evaluation and pursuit of brain stimulation reward

The neurobiological study of reward was launched by the discovery of intracranial self-stimulation (ICSS). Subsequent investigation of this phenomenon provided the initial link between reward-seeking behavior and dopaminergic neurotransmission. We re-evaluated this relationship by psychophysical, pharmacological, optogenetic, and computational means. In rats working for direct, optical activation of midbrain dopamine neurons, we varied the strength and opportunity cost of the stimulation and measured time allocation, the proportion of trial time devoted to reward pursuit. We found that the dependence of time allocation on the strength and cost of stimulation was similar formally to that observed when electrical stimulation of the medial forebrain bundle served as the reward. When the stimulation is strong and cheap, the rats devote almost all their time to reward pursuit; time allocation falls off as stimulation strength is decreased and/or its opportunity cost is increased. A 3D plot of time allocation versus stimulation strength and cost produces a surface resembling the corner of a plateau (the “reward mountain”). We show that dopamine-transporter blockade shifts the mountain along both the strength and cost axes in rats working for optical activation of midbrain dopamine neurons. In contrast, the same drug shifted the mountain uniquely along the opportunity-cost axis when rats worked for electrical MFB stimulation in a prior study. Dopamine neurons are an obligatory stage in the dominant model of ICSS, which positions them at a key nexus in the final common path for reward seeking. This model fails to provide a cogent account for the differential effect of dopamine transporter blockade on the reward mountain. Instead, we propose that midbrain dopamine neurons and neurons with non-dopaminergic, MFB axons constitute parallel limbs of brain-reward circuitry that ultimately converge on the final-common path for the evaluation and pursuit of rewards.

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 Input-Output Relationship of AIY Interneurons in Caenorhabditis elegans in Noisy Environment

Determining how neurotransmitter input causes various neuronal activities is crucial to understanding neuronal information processing. In Caenorhabditis elegans, AIY interneurons receive several sources of sensory information as glutamate inputs and regulate behavior by integrating these inputs. However, the relationship between glutamate input and the Ca2+ response in AIY under environmental noise, in other words, without explicit stimulation, remains unknown. Here, we show that glutamate-input fluctuations evoke a sporadic Ca2+ response in AIY without stimulation. To ensure that Ca2+ response can be considered AIY output, we show that the membrane-potential depolarization precedes Ca2+ responses in AIY. We used an odor as model stimulation to modulate the sensory inputs. Simultaneous imaging of glutamate input and Ca2+ response, together with glutamate transmission mutants, showed that glutamate-input fluctuations evoke sporadic Ca2+ responses. We identified the input-output relationships under environmental noise in vivo, and our results address the relationship between sensory-input fluctuations and behavioral variability.

Modelling the ballistic-to-diffusive transition in nematode motility reveals variation in exploratory behaviour across species

A quantitative understanding of organism-level behaviour requires predictive models that can capture the richness of behavioural phenotypes, yet are simple enough to connect with underlying mechanistic processes. Here, we investigate the motile behaviour of nematodes at the level of their translational motion on surfaces driven by undulatory propulsion. We broadly sample the nematode behavioural repertoire by measuring motile trajectories of the canonical laboratory strain Caenorhabditis elegans N2 as well as wild strains and distant species. We focus on trajectory dynamics over time scales spanning the transition from ballistic (straight) to diffusive (random) movement and find that salient features of the motility statistics are captured by a random walk model with independent dynamics in the speed, bearing and reversal events. We show that the model parameters vary among species in a correlated, low-dimensional manner suggestive of a common mode of behavioural control and a trade-off between exploration and exploitation. The distribution of phenotypes along this primary mode of variation reveals that not only the mean but also the variance varies considerably across strains, suggesting that these nematode lineages employ contrasting 'bet-hedging' strategies for foraging.

Bounded rationality in C. elegans is explained by circuit-specific normalization in chemosensory pathways

Rational choice theory assumes optimality in decision-making. Violations of a basic axiom of economic rationality known as "Independence of Irrelevant Alternatives" (IIA) have been demonstrated in both humans and animals and could stem from common neuronal constraints. Here we develop tests for IIA in the nematode Caenorhabditis elegans, an animal with only 302 neurons, using olfactory chemotaxis assays. We find that in most cases C. elegans make rational decisions. However, by probing multiple neuronal architectures using various choice sets, we show that violations of rationality arise when the circuit of olfactory sensory neurons is asymmetric. We further show that genetic manipulations of the asymmetry between the AWC neurons can make the worm irrational. Last, a context-dependent normalization-based model of value coding and gain control explains how particular neuronal constraints on information coding give rise to irrationality. Thus, we demonstrate that bounded rationality could arise due to basic neuronal constraints.

Neuronal, mathematical, and molecular bases of perceptual decision-making in C. elegans

Animals process sensory information from the environment to make behavioral decisions. Although environmental information may be ambiguous or gradually changing, animals can still choose one behavioral option among several through perceptual decision-making. Perceptual decision-making has been intensively studied in primates and rodents, and neural activity that accumulates sensory information has been shown to be crucial. However, it remains unclear how the accumulating neural activity is generated, and whether such activity is a conserved decision-making strategy across the animal kingdom. Here, we review the previous perceptual decision-making studies in vertebrates and invertebrates and our recent achievement in an invertebrate model animal, the nematode Caenorhabditis elegans. In the study, we analyzed temporal dynamics of neuronal activity during perceptual decision-making in navigational behavior of C. elegans. We identified neural activity that accumulates sensory information and elucidated the molecular mechanism for the accumulating activity, which may be relevant to decision-making across the animal kingdom.

C. elegans AWA Olfactory Neurons Fire Calcium-Mediated All-or-None Action Potentials

Neurons in Caenorhabditis elegans and other nematodes have been thought to lack classical action potentials. Unexpectedly, we observe membrane potential spikes with defining characteristics of action potentials in C. elegans AWA olfactory neurons recorded under current-clamp conditions. Ion substitution experiments, mutant analysis, pharmacology, and modeling indicate that AWA fires calcium spikes, which are initiated by EGL-19 voltage-gated CaV1 calcium channels and terminated by SHK-1 Shaker-type potassium channels. AWA action potentials result in characteristic signals in calcium imaging experiments. These calcium signals are also observed when intact animals are exposed to odors, suggesting that natural odor stimuli induce AWA spiking. The stimuli that elicit action potentials match AWA's specialized function in climbing odor gradients. Our results provide evidence that C. elegans neurons can encode information through regenerative all-or-none action potentials, expand the computational repertoire of its nervous system, and inform future modeling of its neural coding and network dynamics.

The tactile receptive fields of freely moving Caenorhabditis elegans nematodes

Sensory neurons embedded in skin are responsible for the sense of touch. In humans and other mammals, touch sensation depends on thousands of diverse somatosensory neurons. By contrast, Caenorhabditis elegans nematodes have six gentle touch receptor neurons linked to simple behaviors. The classical touch assay uses an eyebrow hair to stimulate freely moving C. elegans, evoking evasive behavioral responses. This assay has led to the discovery of genes required for touch sensation, but does not provide control over stimulus strength or position. Here, we present an integrated system for performing automated, quantitative touch assays that circumvents these limitations and incorporates automated measurements of behavioral responses. The Highly Automated Worm Kicker (HAWK) unites a microfabricated silicon force sensor holding a glass bead forming the contact surface and video analysis with real-time force and position control. Using this system, we stimulated animals along the anterior-posterior axis and compared responses in wild-type and spc-1(dn) transgenic animals, which have a touch defect due to expression of a dominant-negative α-spectrin protein fragment. As expected from prior studies, delivering large stimuli anterior and posterior to the mid-point of the body evoked a reversal and a speed-up, respectively. The probability of evoking a response of either kind depended on stimulus strength and location; once initiated, the magnitude and quality of both reversal and speed-up behavioral responses were uncorrelated with stimulus location, strength, or the absence or presence of the spc-1(dn) transgene. Wild-type animals failed to respond when the stimulus was applied near the mid-point. These results show that stimulus strength and location govern the activation of a characteristic motor program and that the C. elegans body surface consists of two receptive fields separated by a gap.

Optimal synaptic signaling connectome for locomotory behavior in Caenorhabditis elegans: Design minimizing energy cost

The detailed knowledge of C. elegans connectome for 3 decades has not contributed dramatically to our understanding of worm's behavior. One of main reasons for this situation has been the lack of data on the type of synaptic signaling between particular neurons in the worm's connectome. The aim of this study was to determine synaptic polarities for each connection in a small pre-motor circuit controlling locomotion. Even in this compact network of just 7 neurons the space of all possible patterns of connection types (excitation vs. inhibition) is huge. To deal effectively with this combinatorial problem we devised a novel and relatively fast technique based on genetic algorithms and large-scale parallel computations, which we combined with detailed neurophysiological modeling of interneuron dynamics and compared the theory to the available behavioral data. As a result of these massive computations, we found that the optimal connectivity pattern that matches the best locomotory data is the one in which all interneuron connections are inhibitory, even those terminating on motor neurons. This finding is consistent with recent experimental data on cholinergic signaling in C. elegans, and it suggests that the system controlling locomotion is designed to save metabolic energy. Moreover, this result provides a solid basis for a more realistic modeling of neural control in these worms, and our novel powerful computational technique can in principle be applied (possibly with some modifications) to other small-scale functional circuits in C. elegans.

Functionality and Robustness of Injured Connectomic Dynamics in C. elegans: Linking Behavioral Deficits to Neural Circuit Damage

Using a model for the dynamics of the full somatic nervous system of the nematode C. elegans, we address how biological network architectures and their functionality are degraded in the presence of focal axonal swellings (FAS) arising from neurodegenerative disease and/or traumatic brain injury. Using biophysically measured FAS distributions and swelling sizes, we are able to simulate the effects of injuries on the neural dynamics of C. elegans, showing how damaging the network degrades its low-dimensional dynamical responses. We visualize these injured neural dynamics by mapping them onto the worm's low-dimensional postures, i.e. eigenworm modes. We show that a diversity of functional deficits arise from the same level of injury on a connectomic network. Functional deficits are quantified using a statistical shape analysis, a procrustes analysis, for deformations of the limit cycles that characterize key behaviors such as forward crawling. This procrustes metric carries information on the functional outcome of injuries in the model. Furthermore, we apply classification trees to relate injury structure to the behavioral outcome. This makes testable predictions for the structure of an injury given a defined functional deficit. More critically, this study demonstrates the potential role of computational simulation studies in understanding how neuronal networks process biological signals, and how this processing is impacted by network injury.

The C. elegans Connectome Consists of Homogenous Circuits with Defined Functional Roles

A major goal of systems neuroscience is to decipher the structure-function relationship in neural networks. Here we study network functionality in light of the common-neighbor-rule (CNR) in which a pair of neurons is more likely to be connected the more common neighbors it shares. Focusing on the fully-mapped neural network of C. elegans worms, we establish that the CNR is an emerging property in this connectome. Moreover, sets of common neighbors form homogenous structures that appear in defined layers of the network. Simulations of signal propagation reveal their potential functional roles: signal amplification and short-term memory at the sensory/inter-neuron layer, and synchronized activity at the motoneuron layer supporting coordinated movement. A coarse-grained view of the neural network based on homogenous connected sets alone reveals a simple modular network architecture that is intuitive to understand. These findings provide a novel framework for analyzing larger, more complex, connectomes once these become available.

A circuit motif in the zebrafish hindbrain for a two alternative behavioral choice to turn left or right

Animals collect sensory information from the world and make adaptive choices about how to respond to it. Here, we reveal a network motif in the brain for one of the most fundamental behavioral choices made by bilaterally symmetric animals: whether to respond to a sensory stimulus by moving to the left or to the right. We define network connectivity in the hindbrain important for the lateralized escape behavior of zebrafish and then test the role of neurons by using laser ablations and behavioral studies. Key inhibitory neurons in the circuit lie in a column of morphologically similar cells that is one of a series of such columns that form a developmental and functional ground plan for building hindbrain networks. Repetition within the columns of the network motif we defined may therefore lie at the foundation of other lateralized behavioral choices.

DOI:http://dx.doi.org/10.7554/eLife.16808.001

Humans and other vertebrate animals constantly make choices about whether to respond to the left or to the right. Do they look left or right; turn left or right; reach left or right? In humans, the distinction between left and right is so fundamental that it has entered our collective thinking. Many societies define their political positions, for example, in terms of leaning to the left or to the right.

However, we know little about the wiring of the brain that accomplishes the task of making physical left-right choices. Koyama et al. therefore set out to identify the neural circuit responsible for the decision to turn either left or right. Zebrafish larvae were chosen as subjects because they execute rapid left or right turns to escape predators. Given that one wrong turn can result in the death of the zebrafish, a correct choice matters more than in most of the other decisions that animals make.

Experiments revealed that a process of competition between neurons on the left and right sides of the brain underlies this decision-making. Neurons on the right collect evidence that an attack is coming from the right, and drive turns to the left, away from the threat. These neurons also attempt to silence competing neurons on the left that act to produce turns to the right. By weighing up the evidence from left and right sides, the circuit as a whole comes to a decision about the best direction in which to turn.

The region of the brain that controls the left versus right escape response in zebrafish is present in all vertebrates. Moreover, it appears to have a similar structure across species, consisting of repeating columns of neurons. This raises the possibility that other left-right choices in fish and other animals occur in a similar way – a principle that can be tested in future work.

DOI:http://dx.doi.org/10.7554/eLife.16808.002

The whole worm: brain-body-environment models of C. elegans

Brain, body and environment are in continuous dynamical interaction, and it is becoming increasingly clear that an animal's behavior must be understood as a product not only of its nervous system, but also of the ongoing feedback of this neural activity through the biomechanics of its body and the ecology of its environment. Modeling has an essential integrative role to play in such an understanding. But successful whole-animal modeling requires an animal for which detailed behavioral, biomechanical and neural information is available and a modeling methodology which can gracefully cope with the constantly changing balance of known and unknown biological constraints. Here we review recent progress on both optogenetic techniques for imaging and manipulating neural activity and neuromechanical modeling in the nematode worm Caenorhabditis elegans. This work demonstrates both the feasibility and challenges of whole-animal modeling.

FLP-4 neuropeptide and its receptor in a neuronal circuit regulate preference choice through functions of ASH-2 trithorax complex in Caenorhabditis elegans

Preference choice on food is an important response strategy for animals living in the environment. Using assay system of preference choice on bacterial foods, OP50 and PA14, we identified the involvement of ADL sensory neurons in the control of preference choice in Caenorhabditis elegans. Both genetically silencing and ChR2-mediated activation of ADL sensory neurons significantly affected preference choice. ADL regulated preference choice by inhibiting function of G protein-coupled receptor (GPCR)/SRH-220. ADL sensory neurons might regulate preference choice through peptidergic signals of FLP-4 and NLP-10, and function of FLP-4 or NLP-10 in regulating preference choice was regulated by SRH-220. FLP-4 released from ADL sensory neurons further regulated preference choice through its receptor of NPR-4 in AIB interneurons. In AIB interneurons, NPR-4 was involved in the control of preference choice by activating the functions of ASH-2 trithorax complex consisting of SET-2, ASH-2, and WDR-5, implying the crucial role of molecular machinery of trimethylation of histone H3K4 in the preference choice control. The identified novel neuronal circuit and the underlying molecular mechanisms will strengthen our understanding neuronal basis of preference choice in animals.

C. elegans

Random search is a behavioral strategy used by organisms from bacteria to humans to locate food that is randomly distributed and undetectable at a distance. We investigated this behavior in the nematode Caenorhabditis elegans, an organism with a small, well-described nervous system. Here we formulate a mathematical model of random search abstracted from the C. elegans connectome and fit to a large-scale kinematic analysis of C. elegans behavior at submicron resolution. The model predicts behavioral effects of neuronal ablations and genetic perturbations, as well as unexpected aspects of wild type behavior. The predictive success of the model indicates that random search in C. elegans can be understood in terms of a neuronal flip-flop circuit involving reciprocal inhibition between two populations of stochastic neurons. Our findings establish a unified theoretical framework for understanding C. elegans locomotion and a testable neuronal model of random search that can be applied to other organisms.

An animal’s ability to rapidly and efficiently locate new sources of food in its environment can mean the difference between life and death. As a result, animals have evolved foraging strategies that are adapted to the distribution and detectability of food sources. Organisms ranging from bacteria to humans use one such strategy, called random search, to locate food that cannot be detected at a distance and that is randomly distributed in their surroundings. The biological mechanisms that underpin random search are relatively well understood in single-cell organisms such as bacteria, but this information tells us little about the mechanisms that are used by animals, which use their nervous system to control their foraging behavior.

Roberts et al. have now investigated the biological basis for random search behavior in a tiny roundworm called Caenorhabditis elegans. This worm forages for pockets of bacteria in decaying plant matter and has a simple and well-understood nervous system. Roberts et al. used information on how the cells in this worm’s nervous system connect together into so-called “neural circuits” to generate a mathematical model of random searching.

The model revealed that the worm’s neural circuitry for random searching can be understood in terms of two groups of neuron-like components that switch randomly between “ON” and “OFF” states. While one group promotes forward movement, the other promotes backward movement, which is associated with a change in search direction. These two groups inhibit each other so that only one group usually is active at a given time. By adjusting this model to reproduce the behavioral records of real worms searching for food, Roberts et al. could predict the key neuronal connections involved. These predictions were then confirmed by taking electrical recordings from neurons. The model could also account for the unexpected behavioral effects that are seen when a neuron in one of these groups was destroyed or altered by a genetic mutation.

These findings thus reveal a biological mechanism for random search behavior in worms that might operate in other animals as well. The findings might also provide future insight into the neural circuits involved in sleep and wakefulness in mammals, which is organized in a similar way.

Aversion and attraction through olfaction

Sensory cues that predict reward or punishment are fundamental drivers of animal behavior. For example, attractive odors of palatable food or a potential mate predict reward, while aversive odors of pathogen-laced food or a predator predict punishment. Aversive and attractive odors can be detected by intermingled sensory neurons that express highly related olfactory receptors and display similar central projections. These findings raise basic questions of how innate odor valence is extracted from olfactory circuits, how such circuits are developmentally endowed and modulated by state, and how innate and learned odor responses are related. Here, we review odors, receptors and neural circuits associated with stimulus valence, discussing salient principles derived from studies on nematodes, insects and vertebrates. Understanding the organization of neural circuitry that mediates odor aversion and attraction will provide key insights into how the brain functions.

A Hardwired Circuit Supplemented with Endocannabinoids Encodes Behavioral Choice in Zebrafish

Animals constantly make behavioral choices to facilitate moving efficiently through their environment. When faced with a threat, animals make decisions in the midst of other ongoing behaviors through a context-dependent integration of sensory stimuli. In vertebrates, the mechanisms underlying behavioral selection are poorly understood. Here, we show that ongoing swimming in zebrafish is suppressed by escape. The selection of escape over swimming is mediated by switching between two distinct motoneuron pools. A hardwired circuit mediates this switch by acting as a clutch-like mechanism to disengage the swimming motoneuron pool and engage the escape motoneuron pool. Threshold for escape initiation is lowered and swimming suppression is prolonged by endocannabinoid neuromodulation. Thus, our results reveal a novel cellular mechanism involving a hardwired circuit supplemented with endocannabinoids acting as a clutch-like mechanism to engage/disengage distinct motor pools to ensure behavioral selection and a smooth execution of motor action sequences in a vertebrate system.

Sperm navigation along helical paths in 3D chemoattractant landscapes

Sperm require a sense of direction to locate the egg for fertilization. They follow gradients of chemical and physical cues provided by the egg or the oviduct. However, the principles underlying three-dimensional (3D) navigation in chemical landscapes are unknown. Here using holographic microscopy and optochemical techniques, we track sea urchin sperm navigating in 3D chemoattractant gradients. Sperm sense gradients on two timescales, which produces two different steering responses. A periodic component, resulting from the helical swimming, gradually aligns the helix towards the gradient. When incremental path corrections fail and sperm get off course, a sharp turning manoeuvre puts sperm back on track. Turning results from an ‘off' Ca²⁺ response signifying a chemoattractant stimulation decrease and, thereby, a drop in cyclic GMP concentration and membrane voltage. These findings highlight the computational sophistication by which sperm sample gradients for deterministic klinotaxis. We provide a conceptual and technical framework for studying microswimmers in 3D chemical landscapes.

Sperm use external cues to find the egg using ill-defined principles. Here the authors use holographic microscopy and optochemical tools to study sperm swimming in light-sculpted chemical 3D landscapes; they show that sperm translate the temporal stimulation pattern into multiple swimming behaviours to orient deterministically in a gradient.

Action Selection and Operant Conditioning: A Neurorobotic Implementation

Action selection (AS) is thought to represent the mechanism involved by natural agents when deciding what should be the next move or action. Is there a functional elementary core sustaining this cognitive process? Could we reproduce the mechanism with an artificial agent and more specifically in a neurorobotic paradigm? Unsupervised autonomous robots may require a decision-making skill to evolve in the real world and the bioinspired approach is the avenue explored through this paper. We propose simulating an AS process by using a small spiking neural network (SNN) as the lower neural organisms, in order to control virtual and physical robots. We base our AS process on a simple central pattern generator (CPG), decision neurons, sensory neurons, and motor neurons as the main circuit components. As novelty, this study targets a specific operant conditioning (OC) context which is relevant in an AS process; choices do influence future sensory feedback. Using a simple adaptive scenario, we show the complementarity interaction of both phenomena. We also suggest that this AS kernel could be a fast track model to efficiently design complex SNN which include a growing number of input stimuli and motor outputs. Our results demonstrate that merging AS and OC brings flexibility to the behavior in generic dynamical situations.

Dopamine receptors antagonistically regulate behavioral choice between conflicting alternatives in C. elegans

Caenorhabditis elegans is a useful model to study the neuronal or molecular basis for behavioral choice, a specific form of decision-making. Although it has been implied that both D1-like and D2-like dopamine receptors may contribute to the control of decision-making in mammals, the genetic interactions between D1-like and D2-like dopamine receptors in regulating decision-making are still largely unclear. In the present study, we investigated the molecular control of behavioral choice between conflicting alternatives (diacetyl and Cu2+) by D1-like and D2-like dopamine receptors and their possible genetic interactions with C. elegans as the assay system. In the behavioral choice assay system, mutation of dop-1 gene encoding D1-like dopamine receptor resulted in the enhanced tendency to cross the Cu2+ barrier compared with wild-type. In contrast, mutations of dop-2 or dop-3 gene encoding D2-like dopamine receptor caused the weak tendency to cross the Cu2+ barrier compared with wild-type. During the control of behavioral choice, DOP-3 antagonistically regulated the function of DOP-1. The behavioral choice phenotype of dop-2; dop-1dop-3 triple mutant further confirmed the possible antagonistic function of D2-like dopamine receptor on D1-like dopamine receptor in regulating behavioral choice. The genetic assays further demonstrate that DOP-3 might act through Gαo signaling pathway encoded by GOA-1 and EGL-10, and DOP-1 might act through Gαq signaling pathway encoded by EGL-30 and EAT-16 to regulate the behavioral choice. DOP-1 might function in cholinergic neurons to regulate the behavioral choice, whereas DOP-3 might function in GABAergic neurons, RIC, and SIA neurons to regulate the behavioral choice. In this study, we provide the genetic evidence to indicate the antagonistic relationship between D1-like dopamine receptor and D2-like dopamine receptor in regulating the decision-making of animals. Our data will be useful for understanding the complex functions of dopamine receptors in regulating decision-making in animals.

Nematode locomotion: dissecting the neuronal-environmental loop

With a fully reconstructed and extensively characterized neural circuit, the nematode Caenorhabditis elegans is a promising model system for integrating our understanding of neuronal, circuit and whole-animal dynamics. Fundamental to addressing this challenge is the need to consider the tight neuronal-environmental coupling that allows the animal to survive and adapt to changing conditions. Locomotion behaviors are affected by environmental variables both at the biomechanical level and via adaptive sensory responses that drive and modulate premotor and motor circuits. Here we review significant advances in our understanding of proprioceptive control of locomotion, and more abstract models of spatial orientation and navigation. The growing evidence of the complexity of the underlying circuits suggests that the intuition gained is but the first step in elucidating the secrets of neural computation in this relatively simple system.

Specific kinematics and motor-related neurons for aversive chemotaxis in Drosophila

BACKGROUND

Chemotaxis, the ability to direct movements according to chemical cues in the environment, is important for the survival of most organisms. The vinegar fly, Drosophila melanogaster, displays robust olfactory aversion and attraction, but how these behaviors are executed via changes in locomotion remains poorly understood. In particular, it is not clear whether aversion and attraction bidirectionally modulate a shared circuit or recruit distinct circuits for execution.

RESULTS

Using a quantitative behavioral assay, we determined that both aversive and attractive odorants modulate the initiation and direction of turns but display distinct kinematics. Using genetic tools to perturb these behaviors, we identified specific populations of neurons required for aversion, but not for attraction. Inactivation of these populations of cells affected the completion of aversive turns, but not their initiation. Optogenetic activation of the same populations of cells triggered a locomotion pattern resembling aversive turns. Perturbations in both the ellipsoid body and the ventral nerve cord, two regions involved in motor control, resulted in defects in aversion.

CONCLUSIONS

Aversive chemotaxis in vinegar flies triggers ethologically appropriate kinematics distinct from those of attractive chemotaxis and requires specific motor-related neurons.

Sexual attraction: sex-specific wiring of neural circuitry

Two recent studies describe mechanisms by which sexually dimorphic responses to pheromones in the nematode worm Caenorhabditis elegans are driven by differences in the balance of neural circuits that control attraction and repulsion behaviors.