Memory Formation in Tritonia via Recruitment of Variably Committed Neurons

Surprising multifunctionality of a Tritonia swim CPG neuron: C2 drives the early phase of postswim crawling despite being silent during the behavior

In response to a suitably aversive skin stimulus, the marine mollusk Tritonia diomedea launches an escape swim followed by several minutes of high-speed crawling. The two escape behaviors are highly dissimilar: whereas the swim is a muscular behavior involving alternating ventral and dorsal whole body flexions, the crawl is a nonrhythmic gliding behavior mediated by the beating of foot cilia. The serotonergic dorsal swim interneurons (DSIs) are members of the swim central pattern generator (CPG) and also strongly drive crawling. Although the swim network is very well understood, the Tritonia crawling network to date comprises only three neurons: the DSIs and pedal neurons 5 and 21 (Pd5 and Pd21). Since Tritonia's swim network has been suggested to have arisen from a preexisting crawling network, we examined the possible role that another swim CPG neuron, C2, may play in crawling. Because of its complete silence in the postswim crawling period, C2 had not previously been considered to play a role in driving crawling. However, semi-intact preparation experiments demonstrated that a brief C2 spike train surprisingly and strongly drives the foot cilia for ∼30 s, something that cannot be explained by its synaptic connections to Pd5 and Pd21. Voltage-sensitive dye (VSD) imaging in the pedal ganglion identified many candidate crawling motor neurons that fire at an elevated rate after the swim and also revealed several pedal neurons that are strongly excited by C2. It is intriguing that unlike the DSIs, which fire tonically after the swim to drive crawling, C2 does so despite its postswim silence.NEW & NOTEWORTHY Tritonia swim central pattern generator (CPG) neuron C2 surprisingly and strongly drives the early phase of postswim crawling despite being silent during this period. In decades of research, C2 had not been suspected of driving crawling because of its complete silence after the swim. Voltage-sensitive dye imaging revealed that the Tritonia crawling motor network may be much larger than previously known and also revealed that many candidate crawling neurons are excited by C2.

Current Practice in Using Voltage Imaging to Record Fast Neuronal Activity: Successful Examples from Invertebrate to Mammalian Studies

The optical imaging of neuronal activity with potentiometric probes has been credited with being able to address key questions in neuroscience via the simultaneous recording of many neurons. This technique, which was pioneered 50 years ago, has allowed researchers to study the dynamics of neural activity, from tiny subthreshold synaptic events in the axon and dendrites at the subcellular level to the fluctuation of field potentials and how they spread across large areas of the brain. Initially, synthetic voltage-sensitive dyes (VSDs) were applied directly to brain tissue via staining, but recent advances in transgenic methods now allow the expression of genetically encoded voltage indicators (GEVIs), specifically in selected neuron types. However, voltage imaging is technically difficult and limited by several methodological constraints that determine its applicability in a given type of experiment. The prevalence of this method is far from being comparable to patch clamp voltage recording or similar routine methods in neuroscience research. There are more than twice as many studies on VSDs as there are on GEVIs. As can be seen from the majority of the papers, most of them are either methodological ones or reviews. However, potentiometric imaging is able to address key questions in neuroscience by recording most or many neurons simultaneously, thus providing unique information that cannot be obtained via other methods. Different types of optical voltage indicators have their advantages and limitations, which we focus on in detail. Here, we summarize the experience of the scientific community in the application of voltage imaging and try to evaluate the contribution of this method to neuroscience research.

The Consistency of Gastropod Identified Neurons Distinguishes Intra-Individual Plasticity From Inter-Individual Variability in Neural Circuits

Gastropod mollusks are known for their large, individually identifiable neurons, which are amenable to long-term intracellular recordings that can be repeated from animal to animal. The constancy of individual neurons can help distinguish state-dependent or temporal variation within an individual from actual variability between individual animals. Investigations into the circuitry underlying rhythmic swimming movements of the gastropod species, Tritonia exsulans and Pleurobranchaea californica have uncovered intra- and inter-individual variability in synaptic connectivity and serotonergic neuromodulation. Tritonia has a reliably evoked escape swim behavior that is produced by a central pattern generator (CPG) composed of a small number of identifiable neurons. There is apparent individual variability in some of the connections between neurons that is inconsequential for the production of the swim behavior under normal conditions, but determines whether that individual can swim following a neural lesion. Serotonergic neuromodulation of synaptic strength intrinsic to the CPG creates neural circuit plasticity within an individual and contributes to reorganization of the network during recovery from injury and during learning. In Pleurobranchaea, variability over time in the modulatory actions of serotonin and in expression of serotonin receptor genes in an identified neuron directly reflects variation in swimming behavior. Tracking behavior and electrophysiology over hours to days was necessary to identify the functional consequences of these intra-individual, time-dependent variations. This work demonstrates the importance of unambiguous neuron identification, properly assessing the animal and network states, and tracking behavior and physiology over time to distinguish plasticity within the same animal at different times from variability across individual animals.

Neuronal population activity dynamics reveal a low-dimensional signature of operant learning in Aplysia

Learning engages a high-dimensional neuronal population space spanning multiple brain regions. However, it remains unknown whether it is possible to identify a low-dimensional signature associated with operant conditioning, a ubiquitous form of learning in which animals learn from the consequences of behavior. Using single-neuron resolution voltage imaging, here we identify two low-dimensional motor modules in the neuronal population underlying Aplysia feeding. Our findings point to a temporal shift in module recruitment as the primary signature of operant learning. Our findings can help guide characterization of learning signatures in systems in which only a smaller fraction of the relevant neuronal population can be monitored.

Costa et al. use single-neuron resolution voltage imaging to identify two low-dimensional motor modules in the neuronal population underlying Aplysia feeding. Their findings point to a temporal shift in module recruitment as the primary signature of operant learning.

Feeding state functionally reconfigures a sensory circuit to drive thermosensory behavioral plasticity

Internal state alters sensory behaviors to optimize survival strategies. The neuronal mechanisms underlying hunger-dependent behavioral plasticity are not fully characterized. Here we show that feeding state alters C. elegans thermotaxis behavior by engaging a modulatory circuit whose activity gates the output of the core thermotaxis network. Feeding state does not alter the activity of the core thermotaxis circuit comprised of AFD thermosensory and AIY interneurons. Instead, prolonged food deprivation potentiates temperature responses in the AWC sensory neurons, which inhibit the postsynaptic AIA interneurons to override and disrupt AFD-driven thermotaxis behavior. Acute inhibition and activation of AWC and AIA, respectively, restores negative thermotaxis in starved animals. We find that state-dependent modulation of AWC-AIA temperature responses requires INS-1 insulin-like peptide signaling from the gut and DAF-16/FOXO function in AWC. Our results describe a mechanism by which functional reconfiguration of a sensory network via gut-brain signaling drives state-dependent behavioral flexibility.

Photodiode-Based Optical Imaging for Recording Network Dynamics with Single-Neuron Resolution in Non-Transgenic Invertebrates

The development of transgenic invertebrate preparations in which the activity of specifiable sets of neurons can be recorded and manipulated with light represents a revolutionary advance for studies of the neural basis of behavior. However, a downside of this development is its tendency to focus investigators on a very small number of "designer" organisms (e.g., C. elegans and Drosophila), potentially negatively impacting the pursuit of comparative studies across many species, which is needed for identifying general principles of network function. The present article illustrates how optical recording with voltage-sensitive dyes in the brains of non-transgenic gastropod species can be used to rapidly (i.e., within the time course of single experiments) reveal features of the functional organization of their neural networks with single-cell resolution. We outline in detail the dissection, staining, and recording methods used by our laboratory to obtain action potential traces from dozens to ~150 neurons during behaviorally relevant motor programs in the CNS of multiple gastropod species, including one new to neuroscience - the nudibranch Berghia stephanieae. Imaging is performed with absorbance voltage-sensitive dyes and a 464-element photodiode array that samples at 1,600 frames/second, fast enough to capture all action potentials generated by the recorded neurons. Multiple several-minute recordings can be obtained per preparation with little to no signal bleaching or phototoxicity. The raw optical data collected through the methods described can subsequently be analyzed through a variety of illustrated methods. Our optical recording approach can be readily used to probe network activity in a variety of non-transgenic species, making it well suited for comparative studies of how brains generate behavior.

Stability of spontaneous, correlated activity in mouse auditory cortex

Neural systems can be modeled as complex networks in which neural elements are represented as nodes linked to one another through structural or functional connections. The resulting network can be analyzed using mathematical tools from network science and graph theory to quantify the system’s topological organization and to better understand its function. Here, we used two-photon calcium imaging to record spontaneous activity from the same set of cells in mouse auditory cortex over the course of several weeks. We reconstruct functional networks in which cells are linked to one another by edges weighted according to the correlation of their fluorescence traces. We show that the networks exhibit modular structure across multiple topological scales and that these multi-scale modules unfold as part of a hierarchy. We also show that, on average, network architecture becomes increasingly dissimilar over time, with similarity decaying monotonically with the distance (in time) between sessions. Finally, we show that a small fraction of cells maintain strongly-correlated activity over multiple days, forming a stable temporal core surrounded by a fluctuating and variable periphery. Our work indicates a framework for studying spontaneous activity measured by two-photon calcium imaging using computational methods and graphical models from network science. The methods are flexible and easily extended to additional datasets, opening the possibility of studying cellular level network organization of neural systems and how that organization is modulated by stimuli or altered in models of disease.

Neurons coordinate their activity with one another, forming networks that help support adaptive, flexible behavior. Still, little is known about the organization of these networks at the cellular scale and their stability over time. Here, we reconstruct networks from calcium imaging data recorded in mouse primary auditory cortex. We show that these networks exhibit spatially constrained, hierarchical modular structure, which may facilitate specialized information processing. However, we show that connection weights and modular structure are also variable over time, changing on a timescale of days and adopting novel network configurations. Despite this, a small subset of neurons maintain their connections to one another and preserve their modular organization across time, forming a stable temporal core surrounded by a flexible periphery. These findings represent a conceptual bridge linking network analyses of macroscale and cellular-level neuroimaging data. They also represent a complementary approach to existing circuits- and systems-based interrogation of nervous system function, opening the door for deeper and more targeted analysis in the future.

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.

Multimodal sensory information is represented by a combinatorial code in a sensorimotor system

A ubiquitous feature of the nervous system is the processing of simultaneously arriving sensory inputs from different modalities. Yet, because of the difficulties of monitoring large populations of neurons with the single resolution required to determine their sensory responses, the cellular mechanisms of how populations of neurons encode different sensory modalities often remain enigmatic. We studied multimodal information encoding in a small sensorimotor system of the crustacean stomatogastric nervous system that drives rhythmic motor activity for the processing of food. This system is experimentally advantageous, as it produces a fictive behavioral output in vitro, and distinct sensory modalities can be selectively activated. It has the additional advantage that all sensory information is routed through a hub ganglion, the commissural ganglion, a structure with fewer than 220 neurons. Using optical imaging of a population of commissural neurons to track each individual neuron's response across sensory modalities, we provide evidence that multimodal information is encoded via a combinatorial code of recruited neurons. By selectively stimulating chemosensory and mechanosensory inputs that are functionally important for processing of food, we find that these two modalities were processed in a distributed network comprising the majority of commissural neurons imaged. In a total of 12 commissural ganglia, we show that 98% of all imaged neurons were involved in sensory processing, with the two modalities being processed by a highly overlapping set of neurons. Of these, 80% were multimodal, 18% were unimodal, and only 2% of the neurons did not respond to either modality. Differences between modalities were represented by the identities of the neurons participating in each sensory condition and by differences in response sign (excitation versus inhibition), with 46% changing their responses in the other modality. Consistent with the hypothesis that the commissural network encodes different sensory conditions in the combination of activated neurons, a new combination of excitation and inhibition was found when both pathways were activated simultaneously. The responses to this bimodal condition were distinct from either unimodal condition, and for 30% of the neurons, they were not predictive from the individual unimodal responses. Thus, in a sensorimotor network, different sensory modalities are encoded using a combinatorial code of neurons that are activated or inhibited. This provides motor networks with the ability to differentially respond to categorically different sensory conditions and may serve as a model to understand higher-level processing of multimodal information.

Serial-section atlas of the Tritonia pedal ganglion

The pedal ganglion of the nudibranch gastropod Tritonia diomedea has been the focus of neurophysiological studies for more than 50 yr. These investigations have examined the neural basis of behaviors as diverse as swimming, crawling, reflex withdrawals, orientation to water flow, orientation to the earth's magnetic field, and learning. Despite this sustained research focus, most studies have confined themselves to the layer of neurons that are visible on the ganglion surface, leaving many neurons, which reside in deeper layers, largely unknown and thus unstudied. To facilitate work on such neurons, the present study used serial-section light microscopy to generate a detailed pictorial atlas of the pedal ganglion. One pedal ganglion was sectioned horizontally at 2-µm intervals and another vertically at 5-µm intervals. The resulting images were examined separately or combined into stacks to generate movie tours through the ganglion. These were also used to generate 3D reconstructions of individual neurons and rotating movies of digitally desheathed whole ganglia to reveal all surface neurons. A complete neuron count of the horizontally sectioned ganglion yielded 1,885 neurons. Real and virtual sections from the image stacks were used to reveal the morphology of individual neurons, as well as the major axon bundles traveling within the ganglion to and between its several nerves and connectives. Extensive supplemental data are provided, as well as a link to the Dryad Data Repository site, where the complete sets of high-resolution serial-section images can be downloaded. NEW & NOTEWORTHY Because of the large size and relatively low numbers of their neurons, gastropod mollusks are widely used for investigations of the neural basis of behavior. Most studies, however, focus on the neurons visible on the ganglion surface, leaving the majority, located out of sight below the surface, unexamined. The present light microscopy study generates the first detailed visual atlas of all neurons of the highly studied Tritonia pedal ganglion.

The Wisdom of Networks: A General Adaptation and Learning Mechanism of Complex Systems: The Network Core Triggers Fast Responses to Known Stimuli; Innovations Require the Slow Network Periphery and Are Encoded by Core-Remodeling

I hypothesize that re-occurring prior experience of complex systems mobilizes a fast response, whose attractor is encoded by their strongly connected network core. In contrast, responses to novel stimuli are often slow and require the weakly connected network periphery. Upon repeated stimulus, peripheral network nodes remodel the network core that encodes the attractor of the new response. This "core-periphery learning" theory reviews and generalizes the heretofore fragmented knowledge on attractor formation by neural networks, periphery-driven innovation, and a number of recent reports on the adaptation of protein, neuronal, and social networks. The core-periphery learning theory may increase our understanding of signaling, memory formation, information encoding and decision-making processes. Moreover, the power of network periphery-related "wisdom of crowds" inventing creative, novel responses indicates that deliberative democracy is a slow yet efficient learning strategy developed as the success of a billion-year evolution. Also see the video abstract here: https://youtu.be/IIjP7zWGjVE.

A double-sided microscope to realize whole-ganglion imaging of membrane potential in the medicinal leech

Studies of neuronal network emergence during sensory processing and motor control are greatly facilitated by technologies that allow us to simultaneously record the membrane potential dynamics of a large population of neurons in single cell resolution. To achieve whole-brain recording with the ability to detect both small synaptic potentials and action potentials, we developed a voltage-sensitive dye (VSD) imaging technique based on a double-sided microscope that can image two sides of a nervous system simultaneously. We applied this system to the segmental ganglia of the medicinal leech. Double-sided VSD imaging enabled simultaneous recording of membrane potential events from almost all of the identifiable neurons. Using data obtained from double-sided VSD imaging, we analyzed neuronal dynamics in both sensory processing and generation of behavior and constructed functional maps for identification of neurons contributing to these processes.

In every animal, networks of nerve cells work together to interpret signals from the environment and to coordinate responses. Being able to record the activity of all the neurons in a brain at once would greatly advance our understanding of how the brain works. Yet it is not possible to do this for a human brain, which contains several billion neurons. The medicinal leech, on the other hand, has a much simpler nervous system. It has 21 brain-like units called segmental ganglia, which control how the parts of its body move, and each one contains about 400 neurons arranged on a single layer.

The activity of large populations of neurons can be monitored using a technique called fluorescent imaging. Most fluorescent dyes, however, are not sensitive enough to report low levels of activity or fast enough to track individual nerve impulses. Also, current microscopy techniques only allow one surface to be imaged at any one time. These limitations constrain the kinds of questions that neuroscientists can ask about how networks of nerve cells function.

Tomina and Wagenaar have now developed a double-sided fluorescent microscope system that allows a ganglion in a medicinal leech to be viewed from both sides at once. Using a new generation of dyes, which rapidly change their brightness as individual neurons become active or are inhibited, subtle changes in the activity of hundreds of individual neurons were monitored at the same time. In a test of the system, Tomina and Wagenaar recorded activity for different leech behaviors, like bending, swimming and crawling. For the first time, the relationships between neurons on both sides of the ganglion could be seen.

This new technique for examining the activity in neuronal circuitry will allow complex networks of neurons to be studied in more detail. The data that these images generate could then be analyzed mathematically to better understand how the brain processes information from its senses and generates behavior.

A spiral attractor network drives rhythmic locomotion

The joint activity of neural populations is high dimensional and complex. One strategy for reaching a tractable understanding of circuit function is to seek the simplest dynamical system that can account for the population activity. By imaging Aplysia's pedal ganglion during fictive locomotion, here we show that its population-wide activity arises from a low-dimensional spiral attractor. Evoking locomotion moved the population into a low-dimensional, periodic, decaying orbit - a spiral - in which it behaved as a true attractor, converging to the same orbit when evoked, and returning to that orbit after transient perturbation. We found the same attractor in every preparation, and could predict motor output directly from its orbit, yet individual neurons' participation changed across consecutive locomotion bouts. From these results, we propose that only the low-dimensional dynamics for movement control, and not the high-dimensional population activity, are consistent within and between nervous systems.

Inferring neuronal network functional connectivity with directed information

A major challenge in neuroscience is to develop effective tools that infer the circuit connectivity from large-scale recordings of neuronal activity patterns. In this study, context tree maximizing (CTM) was used to estimate directed information (DI), which measures causal influences among neural spike trains in order to infer putative synaptic connections. In contrast to existing methods, the method presented here is data driven and can readily identify both linear and nonlinear relations between neurons. This CTM-DI method reliably identified circuit structures underlying simulations of realistic conductance-based networks. It also inferred circuit properties from voltage-sensitive dye recordings of the buccal ganglion of Aplysia. This method can be applied to other large-scale recordings as well. It offers a systematic tool to map network connectivity and to track changes in network structure such as synaptic strengths as well as the degrees of connectivity of individual neurons, which in turn could provide insights into how modifications produced by learning are distributed in a neural network.NEW & NOTEWORTHY This study brings together the techniques of voltage-sensitive dye recording and information theory to infer the functional connectome of the feeding central pattern generating network of Aplysia. In contrast to current statistical approaches, the inference method developed in this study is data driven and validated by conductance-based model circuits, can distinguish excitatory and inhibitory connections, is robust against synaptic plasticity, and is capable of detecting network structures that mediate motor patterns.

Consequences of degeneracy in network function

Often distinct elements serve similar functions within a network. However, it is unclear whether this network degeneracy is beneficial, or merely a reflection of tighter regulation of overall network performance relative to individual neuronal properties. We review circumstances where data strongly suggest that degeneracy is beneficial in that it makes network function more robust. Importantly, network degeneracy is likely to have functional consequences that are not widely appreciated. This is likely to be true when network activity is configured by modulators with persistent actions, and the history of network activity potentially impacts subsequent functioning. Data suggest that degeneracy in this context may be important for the creation of latent memories, and for state-dependent task switching.

Recruitment of Polysynaptic Connections Underlies Functional Recovery of a Neural Circuit after Lesion

The recruitment of additional neurons to neural circuits often occurs in accordance with changing functional demands. Here we found that synaptic recruitment plays a key role in functional recovery after neural injury. Disconnection of a brain commissure in the nudibranch mollusc, Tritonia diomedea, impairs swimming behavior by eliminating particular synapses in the central pattern generator (CPG) underlying the rhythmic swim motor pattern. However, the CPG functionally recovers within a day after the lesion. The strength of a spared inhibitory synapse within the CPG from Cerebral Neuron 2 (C2) to Ventral Swim Interneuron B (VSI) determines the level of impairment caused by the lesion, which varies among individuals. In addition to this direct synaptic connection, there are polysynaptic connections from C2 and Dorsal Swim Interneurons to VSI that provide indirect excitatory drive but play only minor roles under normal conditions. After disconnecting the pedal commissure (Pedal Nerve 6), the recruitment of polysynaptic excitation became a major source of the excitatory drive to VSI. Moreover, the amount of polysynaptic recruitment, which changed over time, differed among individuals and correlated with the degree of recovery of the swim motor pattern. Thus, functional recovery was mediated by an increase in the magnitude of polysynaptic excitatory drive, compensating for the loss of direct excitation. Since the degree of susceptibility to injury corresponds to existing individual variation in the C2 to VSI synapse, the recovery relied upon the extent to which the network reorganized to incorporate additional synapses.

Watching a memory form-VSD imaging reveals a novel memory mechanism

Studies of the mechanisms underlying memory formation have largely focused on the synapse. However, recent evidence suggests that additional, non-synaptic, mechanisms also play important roles in this process. We recently described a novel memory mechanism whereby a particular class of neurons was recruited into the Tritonia escape swim network with sensitization, a non-associative form of learning. Neurons that in the naïve state were loosely-affiliated with the network were rapidly recruited in, transitioning from variably bursting (VB) to reliably bursting (RB). Even after the memory had faded some new neurons remained, and some original members had left, leaving the network in an altered state. Further, we identified a candidate cellular mechanism underlying these network changes. Our study supports the view that brain networks may have surprisingly fluid functional structures and adds to the growing body of evidence that non-synaptic mechanisms often operate synergistically with changes at the synapse to mediate memory formation.

What Can Ethobehavioral Studies Tell Us about the Brain's Fear System?

Foraging-associated predation risk is a natural problem all prey must face. Fear evolved due to its protective functions, guiding and shaping behaviors that help animals adapt to various ecological challenges. Despite the breadth of risky situations in nature that demand diversity in fear behaviors, contemporary neurobiological models of fear stem largely from Pavlovian fear conditioning studies that focus on how a particular cue becomes capable of eliciting learned fear responses, thus oversimplifying the brain's fear system. Here we review fear from functional, mechanistic, and phylogenetic perspectives where environmental threats cause animals to alter their foraging strategies in terms of spatial and temporal navigation, and discuss whether the inferences we draw from fear conditioning studies operate in the natural world.