Variations on a theme: species differences in synaptic connectivity do not predict central pattern generator activity

Uncovering the determinants of brain functioning, behavior and their interplay in the light of context

Notwithstanding the huge progress in molecular and cellular neuroscience, our ability to understand the brain and develop effective treatments promoting mental health is still limited. This can be partially ascribed to the reductionist, deterministic and mechanistic approaches in neuroscience that struggle with the complexity of the central nervous system. Here, I introduce the Context theory of constrained systems proposing a novel role of contextual factors and genetic, molecular and neural substrates in determining brain functioning and behavior. This theory entails key conceptual implications. First, context is the main driver of behavior and mental states. Second, substrates, from genes to brain areas, have no direct causal link to complex behavioral responses as they can be combined in multiple ways to produce the same response and different responses can impinge on the same substrates. Third, context and biological substrates play distinct roles in determining behavior: context drives behavior, substrates constrain the behavioral repertoire that can be implemented. Fourth, since behavior is the interface between the central nervous system and the environment, it is a privileged level of control and orchestration of brain functioning. Such implications are illustrated through the Kitchen metaphor of the brain. This theoretical framework calls for the revision of key concepts in neuroscience and psychiatry, including causality, specificity and individuality. Moreover, at the clinical level, it proposes treatments inducing behavioral changes through contextual interventions as having the highest impact to reorganize the complexity of the human mind and to achieve a long-lasting improvement in mental health.

Neuromodulation and the toolkit for behavioural evolution: can ecdysis shed light on an old problem?

The geneticist Thomas Dobzhansky famously declared: 'Nothing in biology makes sense except in the light of evolution'. A key evolutionary adaptation of Metazoa is directed movement, which has been elaborated into a spectacularly varied number of behaviours in animal clades. The mechanisms by which animal behaviours have evolved, however, remain unresolved. This is due, in part, to the indirect control of behaviour by the genome, which provides the components for both building and operating the brain circuits that generate behaviour. These brain circuits are adapted to respond flexibly to environmental contingencies and physiological needs and can change as a function of experience. The resulting plasticity of behavioural expression makes it difficult to characterize homologous elements of behaviour and to track their evolution. Here, we evaluate progress in identifying the genetic substrates of behavioural evolution and suggest that examining adaptive changes in neuromodulatory signalling may be a particularly productive focus for future studies. We propose that the behavioural sequences used by ecdysozoans to moult are an attractive model for studying the role of neuromodulation in behavioural evolution.

Predicting the Behavior of Sparsely-Sampled Systems Across Neurobiology and Epidemiology

Inference is a term that encompasses many techniques including statistical data assimilation (SDA). Unlike machine learning, which is designed to harness predictive power from extremely large data sets, SDA is designed for sparsely-sampled systems. This is the realm of study of nonlinear dynamical systems in nature. Formulated as an optimization procedure, SDA can be considered a path-integral approach to state and parameter estimation. Within this formulation, we can use the physical principle of least action to identify optimal solutions: solutions that are consistent with both measurements and a dynamical model assumed to give rise to those measurements. I review examples from neurobiology and an epidemiological model tailored to the coronavirus SARS-CoV-2, to demonstrate the versatility of SDA across the sciences, and how these distinct applications possess commonalities that can inform one another.

New insights from small rhythmic circuits

Small rhythmic circuits, such as those found in invertebrates, have provided fundamental insights into how circuit dynamics depend on individual neuronal and synaptic properties. Degenerate circuits are those with different network parameters and similar behavior. New work on degenerate circuits and their modulation illustrates some of the rules that help maintain stable and robust circuit function despite environmental perturbations. Advances in neuropeptide isolation and identification provide enhanced understanding of the neuromodulation of circuits for behavior. The advent of molecular studies of mRNA expression provides new insight into animal-to-animal variability and the homeostatic regulation of excitability in neurons and networks.

Bursting emerges from the complementary roles of neurons in a four-cell network

Reciprocally inhibitory modules that form half-center oscillators require mechanisms for escaping or being released from inhibition. The central pattern generator underlying swimming by the nudibranch mollusc, Dendronotus iris, is composed of only four neurons that are organized into two competing modules of a half-center oscillator. In this system, bursting activity in left-right alternation is an emergent property of the network as a whole; none of the neurons produces bursts on its own. We found that the unique synaptic actions and membrane properties of the two neurons in each module (Si2 and the contralateral Si3) play complementary roles in generating stable bursting in this network oscillator. Although Si2 and Si3 each inhibit their contralateral counterpart, Si2 plays a dominant role in evoking fast and strong inhibition of the other module, the termination of which initiates post-inhibitory rebound in the Si3 of that module by activating a hyperpolarization-activated inward current. Within each module, the synaptic actions and membrane properties of the two neurons complement each other: Si3 excites Si2, which then feeds back slow inhibition to Si3, terminating the burst. Using dynamic clamp, we showed that the magnitude of the slow inhibition sets the period of the oscillator. Thus, the synaptic actions of Si2 provide the hyperpolarization needed for the other module to rebound stably, whereas the membrane properties of Si3 in each module cause it to rebound first and excite Si2 to maintain the burst until terminated by the slow inhibition from Si2, which releases the other module to become active.

Towards more biologically plausible central-pattern-generator models

Central pattern generators (CPGs) are relatively small neural networks that play a fundamental role in the control of animal locomotion. In this paper we define a method for the systematic design of CPG models able to exhibit biologically plausible gait transitions by implementing short-term synaptic plasticity mechanisms. As a case study, we focus on a simple CPG for quadruped locomotion. By applying the proposed method, three of four standard quadruped gaits were correctly reproduced by the obtained CPG model, not only in terms of the alternating sequence of the limbs but also in terms of frequency, duty cycle, and phase lags.

Generalized half-center oscillators with short-term synaptic plasticity

How can we develop simple yet realistic models of the small neural circuits known as central pattern generators (CPGs), which contribute to generate complex multiphase locomotion in living animals? In this paper we introduce a new model (with design criteria) of a generalized half-center oscillator, (pools of) neurons reciprocally coupled by fast/slow inhibitory and excitatory synapses, to produce either alternating bursting or other rhythmic patterns, characterized by different phase lags, depending on the sensory or other external input. We also show how to calibrate its parameters, based on both physiological and functional criteria and on bifurcation analysis. This model accounts for short-term neuromodulation in a biophysically plausible way and is a building block to develop more realistic and functionally accurate CPG models. Examples and counterexamples are used to point out the generality and effectiveness of our design approach.

Expanding evolutionary neuroscience: insights from comparing variation in behavior

Neuroscientists have long studied species with convenient biological features to discover how behavior emerges from conserved molecular, neural, and circuit level processes. With the advent of new tools, from viral vectors and gene editing to automated behavioral analyses, there has been a recent wave of interest in developing new, "nontraditional" model species. Here, we advocate for a complementary approach to model species development, that is, model clade development, as a way to integrate an evolutionary comparative approach with neurobiological and behavioral experiments. Capitalizing on natural behavioral variation in and investing in experimental tools for model clades will be a valuable strategy for the next generation of neuroscience discovery.

Statistical data assimilation for estimating electrophysiology simultaneously with connectivity within a biological neuronal network

A method of data assimilation (DA) is employed to estimate electrophysiological parameters of neurons simultaneously with their synaptic connectivity in a small model biological network. The DA procedure is cast as an optimization, with a cost function consisting of both a measurement error and a model error term. An iterative reweighting of these terms permits a systematic method to identify the lowest minimum, within a local region of state space, on the surface of a nonconvex cost function. In the model, two sets of parameter values are associated with two particular functional modes of network activity: simultaneous firing of all neurons and a pattern-generating mode wherein the neurons burst in sequence. The DA procedure is able to recover these modes if: (i) the stimulating electrical currents have chaotic waveforms and (ii) the measurements consist of the membrane voltages of all neurons in the circuit. Further, this method is able to prune a model of unnecessarily high dimensionality to a representation that contains the maximum dimensionality required to reproduce the provided measurements. This paper offers a proof-of-concept that DA has the potential to inform laboratory designs for estimating properties in small and isolatable functional circuits.

Molecular mechanisms of homeostatic plasticity in central pattern generator networks

Central pattern generator (CPG) networks rely on a balance of intrinsic and network properties to produce reliable, repeatable activity patterns. This balance is maintained by homeostatic plasticity where alterations in neuronal properties dynamically maintain appropriate neural output in the face of changing environmental conditions and perturbations. However, it remains unclear just how these neurons and networks can both monitor their ongoing activity and use this information to elicit homeostatic physiological responses to ensure robustness of output over time. Evidence exists that CPG networks use a mixed strategy of activity-dependent, activity-independent, modulator-dependent, and synaptically regulated homeostatic plasticity to achieve this critical stability. In this review, we focus on some of the current understanding of the molecular pathways and mechanisms responsible for this homeostatic plasticity in the context of central pattern generator function, with a special emphasis on some of the smaller invertebrate networks that have allowed for extensive cellular-level analyses that have brought recent insights to these questions.

Command or Obey? Homologous Neurons Differ in Hierarchical Position for the Generation of Homologous Behaviors

In motor systems, higher-order neurons provide commands to lower-level central pattern generators (CPGs) that autonomously produce rhythmic motor patterns. Such hierarchical organization is often thought to be inherent in the anatomical position of the neurons. Here, however, we report that a neuron that is member of a CPG in one species acts as a higher-order neuron in another species. In the nudibranch mollusc, Melibe leonina, swim interneuron 1 (Si1) is in the CPG underlying swimming, firing rhythmic bursts of action potentials as part of the swim motor pattern. We found that its homolog in another nudibranch, Dendronotus iris, serves as a neuromodulatory command neuron for the CPG of a homologous swimming behavior. In Dendronotus, Si1 fired irregularly throughout the swim motor pattern. The burst and spike frequencies of Dendronotus swim CPG neurons correlated with Si1 firing frequency. Si1 activity was both necessary and sufficient for the initiation and maintenance of the swim motor pattern. Each Si1 was electrically coupled to all of the CPG neurons and made monosynaptic excitatory synapses with both Si3s. Si1 also bilaterally potentiated the excitatory synapse from Si3 to Si2. "Virtual neuromodulation" of both Si3-to-Si2 synapses using dynamic clamp combined with depolarization of both Si3s mimicked the effects of Si1 stimulation on the swim motor pattern. Thus, in Dendronotus, Si1 is a command neuron that turns on, maintains, and accelerates the motor pattern through synaptic and neuromodulatory actions, thereby differing from its homolog in Melibe in its functional position in the motor hierarchy.SIGNIFICANCE STATEMENT Cross-species comparisons of motor system organization can provide fundamental insights into their function and origin. Central pattern generators (CPGs) are lower in the functional hierarchy than the neurons that initiate and modulate their activity. This functional hierarchy is often reflected in neuroanatomical organization. This paper definitively shows that an identified cerebral ganglion neuron that is a member of a CPG underlying swimming in one nudibranch species serves as a command neuron for the same behavior in another species. We describe and test the synaptic and neuromodulatory mechanisms by which the command neuron initiates and accelerates rhythmic motor patterns. Thus, the functional position of neurons in a motor hierarchy can shift from one level to another over evolutionary time.

The importance of identified neurons in gastropod molluscs to neuroscience

Gastropod molluscs have large neurons that are uniquely identifiable across individuals and across species based on neuroanatomical and neurochemical criteria, facilitating research into neural signaling and neural circuits. Novel neuropeptides have been identified through RNA sequencing and mass spectroscopic analysis of single neurons. The roles of peptides and other signaling molecules including second messengers have been placed in the context of small circuits that control simple behaviors. Despite the stereotypy, neurons vary over time in their activity in large ensembles. Furthermore, there is both intra-species and inter-species variation in synaptic properties and gene expression. Research on gastropod identified neurons highlights the features that might be expected to be stable in more complex systems when trying to identify cell types.

Similarities and differences in circuit responses to applied Gly1-SIFamide and peptidergic (Gly1-SIFamide) neuron stimulation

Microcircuit modulation by peptides is well established, but the cellular/synaptic mechanisms whereby identified neurons with identified peptide transmitters modulate microcircuits remain unknown for most systems. Here, we describe the distribution of GYRKPPFNGSIFamide (Gly1-SIFamide) immunoreactivity (Gly1-SIFamide-IR) in the stomatogastric nervous system (STNS) of the crab Cancer borealis and the Gly1-SIFamide actions on the two feeding-related circuits in the stomatogastric ganglion (STG). Gly1-SIFamide-IR localized to somata in the paired commissural ganglia (CoGs), two axons in the nerves connecting each CoG with the STG, and the CoG and STG neuropil. We identified one Gly1-SIFamide-IR projection neuron innervating the STG as the previously identified modulatory commissural neuron 5 (MCN5). Brief (~10 s) MCN5 stimulation excites some pyloric circuit neurons. We now find that bath applying Gly1-SIFamide to the isolated STG also enhanced pyloric rhythm activity and activated an imperfectly coordinated gastric mill rhythm that included unusually prolonged bursts in two circuit neurons [inferior cardiac (IC), lateral posterior gastric (LPG)]. Furthermore, longer duration (>30 s) MCN5 stimulation activated a Gly1-SIFamide-like gastric mill rhythm, including prolonged IC and LPG bursting. The prolonged LPG bursting decreased the coincidence of its activity with neurons to which it is electrically coupled. We also identified local circuit feedback onto the MCN5 axon terminals, which may contribute to some distinctions between the responses to MCN5 stimulation and Gly1-SIFamide application. Thus, MCN5 adds to the few identified projection neurons that modulate a well-defined circuit at least partly via an identified neuropeptide transmitter and provides an opportunity to study peptide regulation of electrical coupled neurons in a functional context. NEW & NOTEWORTHY Limited insight exists regarding how identified peptidergic neurons modulate microcircuits. We show that the modulatory projection neuron modulatory commissural neuron 5 (MCN5) is peptidergic, containing Gly1-SIFamide. MCN5 and Gly1-SIFamide elicit similar output from two well-defined motor circuits. Their distinct actions may result partly from circuit feedback onto the MCN5 axon terminals. Their similar actions include eliciting divergent activity patterns in normally coactive, electrically coupled neurons, providing an opportunity to examine peptide modulation of electrically coupled neurons in a functional context.

Premotor Neuron Divergence Reflects Vocal Evolution

To identify mechanisms of behavioral evolution, we investigated the hindbrain circuit that generates distinct vocal patterns in two closely related frog species. Male Xenopus laevis and Xenopus petersii produce courtship calls that include a fast trill: trains of ∼60 Hz sound pulses. Although fast trill rates are similar, X. laevis fast trills have a longer duration and period than those of X. petersii To pinpoint the neural basis of these differences, we used whole-cell patch-clamp recordings in a key premotor hindbrain nucleus (the Xenopus parabrachial area, PB_X) in ex vivo brains that produce fictive vocalizations, vocal nerve activity corresponding to advertisement call patterns. We found two populations of PB_X neurons with distinct properties: fast trill neurons (FTNs) and early vocal neurons (EVNs). FTNs, but not EVNs, appear to be intrinsically tuned to produce each species' call patterns because: (1) X. laevis FTNs generate longer and slower depolarizations than X. petersii FTNs during their respective fictive vocalizations, (2) current steps in FTNs induce burst durations that are significantly longer in X. laevis than X. petersii, and (3) synaptically isolated FTNs oscillate in response to NMDA in a species-specific manner: longer and slower in X. laevis than in X. petersii Therefore, divergence of premotor neuron membrane properties is a strong candidate for generating vocal differences between species.SIGNIFICANCE STATEMENT The vertebrate hindbrain includes multiple neural circuits that generate rhythmic behaviors including vocalizations. Male African clawed frogs produce courtship calls that are unique to each species and differ in temporal patterns. Here, we identified two functional subtypes of neurons located in the parabrachial nucleus: a hindbrain region implicated in vocal and respiratory control across vertebrates. One of these neuronal subtypes exhibits distinct properties across species that can account for the evolutionary divergence of song patterns. Our results suggest that changes to this group of neurons during evolution may have had a major role in establishing novel behaviors in closely related species.