A neuronal network for computing population vectors in the leech

A population of descending neurons that regulates the flight motor of Drosophila

Like many insect species, Drosophila melanogaster are capable of maintaining a stable flight trajectory for periods lasting up to several hours^1,2. Because aerodynamic torque is roughly proportional to the fifth power of wing length³, even small asymmetries in wing size require the maintenance of subtle bilateral differences in flapping motion to maintain a stable path. Flies can even fly straight after losing half of a wing, a feat they accomplish via very large, sustained kinematic changes to both the damaged and intact wings⁴. Thus, the neural network responsible for stable flight must be capable of sustaining fine-scaled control over wing motion across a large dynamic range. In this paper, we describe an unusual type of descending neuron (DNg02) that projects directly from visual output regions of the brain to the dorsal flight neuropil of the ventral nerve cord. Unlike many descending neurons, which exist as single bilateral pairs with unique morphology, there is a population of at least 15 DNg02 cell pairs with nearly identical shape. By optogenetically activating different numbers of DNg02 cells, we demonstrate that these neurons regulate wingbeat amplitude over a wide dynamic range via a population code. Using 2-photon functional imaging, we show that DNg02 cells are responsive to visual motion during flight in a manner that would make them well suited to continuously regulate bilateral changes in wing kinematics. Collectively, we have identified a critical set of DNs that provide the sensitivity and dynamic range required for flight control.

Using an activation screen in flying flies, Namiki et al. identify a population of descending neurons that regulates wing amplitude over a large dynamic range. Via functional imaging and activation of different numbers of cells, they show that this population is a core component of the flight circuit, allowing the fly to steer and fly straight.

Synergistic population coding of natural communication stimuli by hindbrain electrosensory neurons

Understanding how neural populations encode natural stimuli with complex spatiotemporal structure to give rise to perception remains a central problem in neuroscience. Here we investigated population coding of natural communication stimuli by hindbrain neurons within the electrosensory system of weakly electric fish Apteronotus leptorhynchus. Overall, we found that simultaneously recorded neural activities were correlated: signal but not noise correlations were variable depending on the stimulus waveform as well as the distance between neurons. Combining the neural activities using an equal-weight sum gave rise to discrimination performance between different stimulus waveforms that was limited by redundancy introduced by noise correlations. However, using an evolutionary algorithm to assign different weights to individual neurons before combining their activities (i.e., a weighted sum) gave rise to increased discrimination performance by revealing synergistic interactions between neural activities. Our results thus demonstrate that correlations between the neural activities of hindbrain electrosensory neurons can enhance information about the structure of natural communication stimuli that allow for reliable discrimination between different waveforms by downstream brain areas.

Transcriptional profiling of identified neurons in leech

Background

While leeches in the genus Hirudo have long been models for neurobiology, the molecular underpinnings of nervous system structure and function in this group remain largely unknown. To begin to bridge this gap, we performed RNASeq on pools of identified neurons of the central nervous system (CNS): sensory T (touch), P (pressure) and N (nociception) neurons; neurosecretory Retzius cells; and ganglia from which these four cell types had been removed.

Results

Bioinformatic analyses identified 3565 putative genes whose expression differed significantly among the samples. These genes clustered into 9 groups which could be associated with one or more of the identified cell types. We verified predicted expression patterns through in situ hybridization on whole CNS ganglia, and found that orthologous genes were for the most part similarly expressed in a divergent leech genus, suggesting evolutionarily conserved roles for these genes. Transcriptional profiling allowed us to identify candidate phenotype-defining genes from expanded gene families. Thus, we identified one of eight hyperpolarization-activated cyclic-nucleotide gated (HCN) channels as a candidate for mediating the prominent sag current in P neurons, and found that one of five inositol triphosphate receptors (IP3Rs), representing a sub-family of IP3Rs absent from vertebrate genomes, is expressed with high specificity in T cells. We also identified one of two piezo genes, two of ~ 65 deg/enac genes, and one of at least 16 transient receptor potential (trp) genes as prime candidates for involvement in sensory transduction in the three distinct classes of leech mechanosensory neurons.

Conclusions

Our study defines distinct transcriptional profiles for four different neuronal types within the leech CNS, in addition to providing a second ganglionic transcriptome for the species. From these data we identified five gene families that may facilitate the sensory capabilities of these neurons, thus laying the basis for future work leveraging the strengths of the leech system to investigate the molecular processes underlying and linking mechanosensation, cell type specification, and behavior.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07526-0.

Multi-regional circuits underlying visually guided decision-making in Drosophila

Visually guided decision-making requires integration of information from distributed brain areas, necessitating a brain-wide approach to examine its neural mechanisms. New tools in Drosophila melanogaster enable circuits spanning the brain to be charted with single cell-type resolution. Here, we highlight recent advances uncovering the computations and circuits that transform and integrate visual information across the brain to make behavioral choices. Visual information flows from the optic lobes to three primary central brain regions: a sensorimotor mapping area and two 'higher' centers for memory or spatial orientation. Rapid decision-making during predator evasion emerges from the spike timing dynamics in parallel sensorimotor cascades. Goal-directed decisions may occur through memory, navigation and valence processing in the central complex and mushroom bodies.

Phase-Specific Motor Efference during a Rhythmic Motor Pattern

Neuronal circuits that control motor behaviors orchestrate multiple tasks, including the inhibition of self-generated sensory signals. In the hermaphroditic leech, T and P mechanosensory neurons respond to light touch and pressure on the skin, respectively. We show that the low threshold T cells were also sensitive to topological changes of the animal surface, caused by contraction of the muscles that erect the skin annuli. P cells were unresponsive to this movement. Annuli erection is part of the contraction phase of crawling, a leech locomotive behavior. In isolated ganglia, T cells showed phase-dependent IPSPs during dopamine-induced fictive crawling, whereas P cells were unaffected. The timing and magnitude of the T-IPSPs were highly correlated with the activity of the motoneurons excited during the contraction phase. Together, the results suggest that the central network responsible for crawling sends a reafferent signal onto the T cells, concomitant with the signal to the motoneurons. This reafference is specifically targeted at the sensory neurons that are affected by the movements; and it is behaviorally relevant as excitation of T cells affected the rhythmic motor pattern, probably acting upon the rhythmogenic circuit. Corollary discharge is a highly conserved function of motor systems throughout evolution, and we provide clear evidence of the specificity of its targets and timing and of the benefit of counteracting self-generated sensory input.SIGNIFICANCE STATEMENT Neuronal circuits that control motor behaviors orchestrate multiple tasks, including inhibition of sensory signals originated by the animal movement, a phenomenon known as corollary discharge. Leeches crawl on solid surfaces through a sequence of elongation and contraction movements. During the contraction, the skin topology changes, affecting a subpopulation of mechanosensory receptors, T (touch) neurons, but not P (pressure) sensory neurons. In the isolated nervous system, T neurons were inhibited during the contraction but not during the elongation phase, whereas P cells were unaffected throughout crawling. Excitation of T cells during the contraction phase temporarily disrupted the rhythmic pattern. Thus, corollary discharge was target (T vs P) and phase (contraction vs elongation) specific, and prevented self-generated signals to perturb motor behaviors.

Combinatorial Neural Inhibition for Stimulus Selection across Space

The ability to select the most salient among competing stimuli is essential for animal behavior and operates no matter which spatial locations stimuli happen to occupy. We provide evidence that the brain employs a combinatorially optimized inhibition strategy for selection across all pairs of stimulus locations. With experiments in a key inhibitory nucleus in the vertebrate midbrain selection network, called isthmi pars magnocellularis (Imc) in owls, we discovered that Imc neurons encode visual space with receptive fields that have multiple excitatory hot spots (“lobes“). Such multilobed encoding is necessitated by scarcity of Imc neurons. Although distributed seemingly randomly, the locations of these lobes are optimized across the high-firing Imc neurons, allowing them to combinatorially solve selection across space. This strategy minimizes metabolic and wiring costs, a principle that also accounts for observed asymmetries between azimuthal and elevational coding. Combinatorially optimized inhibition may be a general neural principle for efficient stimulus selection.

Mahajan et al. show that a sparse set of midbrain inhibitory neurons encodes visual space with unusual multilobed receptive fields. This results in a combinatorially optimized solution for selection at all pairs of stimulus locations, which minimizes metabolic and neural wiring costs.

Linking neural responses to behavior with information-preserving population vectors

All systems for processing signals, both artificial and within animals, must obey fundamental statistical laws for how information can be processed. We discuss here recent results using information theory that provide a blueprint for building circuits where signals can be read-out without information loss. Many properties that are necessary to build information-preserving circuits are actually observed in real neurons, at least approximately. One such property is the use of logistic nonlinearity for relating inputs to neural response probability. Such nonlinearities are common in neural and intracellular networks. With this nonlinearity type, there is a linear combination of neural responses that is guaranteed to preserve Shannon information contained in the response of a neural population, no matter how many neurons it contains. This read-out measure is related to a classic quantity known as the population vector that has been quite successful in relating neural responses to animal behavior in a wide variety of cases. Nevertheless, the population vector did not withstand the scrutiny of detailed information-theoretical analyses that showed that it discards substantial amounts of information contained in the responses of a neural population. We discuss recent theoretical results showing how to modify the population vector expression to make it 'information-preserving', and what is necessary in terms of neural circuit organization to allow for lossless information transfer. Implementing these strategies within artificial systems is likely to increase their efficiency, especially for brain-machine interfaces.

Behavioral analysis of substrate texture preference in a leech, Helobdella austinensis

Leeches in the wild are often found on smooth surfaces, such as vegetation, smooth rocks or human artifacts such as bottles and cans, thus exhibiting what appears to be a "substrate texture preference". Here, we have reproduced this behavior under controlled circumstances, by allowing leeches to step about freely on a range of silicon carbide substrates (sandpaper). To begin to understand the neural mechanisms underlying this texture preference behavior, we have determined relevant parameters of leech behavior both on uniform substrates of varying textures, and in a behavior choice paradigm in which the leech is confronted with a choice between rougher and smoother substrate textures at each step. We tested two non-exclusive mechanisms which could produce substrate texture preference: (1) a Differential Diffusion mechanism, in which a leech is more likely to stop moving on a smooth surface than on a rough one, and (2) a Smoothness Selection mechanism, in which a leech is more likely to attach its front sucker (prerequisite for taking a step) to a smooth surface than to a rough one. We propose that both mechanisms contribute to the texture preference exhibited by leeches.

Circuit architecture for somatotopic action selection in invertebrates

Invertebrate species have significantly contributed to neuroscience owing to the accessibility they provide to cellular- and molecular-level understanding of brain functions. Somatotopic action selection is one of the key features of animal behavior, and studying this process in invertebrates is potentially a sweet spot in understanding the general relationship between neuronal morphology, circuit structure, and animal behavior. In this review, we introduce circuit architectures that realize somatotopic action selection, from simple reflexes to patterned motor outputs, in different invertebrate species. We then discuss future directions towards understanding the general principles underlying the development and evolution of the circuit architecture that enables sensorimotor transformation and action selection in the animal kingdom.

Attention Selectively Reshapes the Geometry of Distributed Semantic Representation

Humans prioritize different semantic qualities of a complex stimulus depending on their behavioral goals. These semantic features are encoded in distributed neural populations, yet it is unclear how attention might operate across these distributed representations. To address this, we presented participants with naturalistic video clips of animals behaving in their natural environments while the participants attended to either behavior or taxonomy. We used models of representational geometry to investigate how attentional allocation affects the distributed neural representation of animal behavior and taxonomy. Attending to animal behavior transiently increased the discriminability of distributed population codes for observed actions in anterior intraparietal, pericentral, and ventral temporal cortices. Attending to animal taxonomy while viewing the same stimuli increased the discriminability of distributed animal category representations in ventral temporal cortex. For both tasks, attention selectively enhanced the discriminability of response patterns along behaviorally relevant dimensions. These findings suggest that behavioral goals alter how the brain extracts semantic features from the visual world. Attention effectively disentangles population responses for downstream read-out by sculpting representational geometry in late-stage perceptual areas.

Higher Network Activity Induced by Tactile Compared to Electrical Stimulation of Leech Mechanoreceptors

The tiny ensemble of neurons in the leech ganglion can discriminate the locations of touch stimuli on the skin as precisely as a human fingertip. The leech uses this ability to locally bend the body-wall away from the stimulus. It is assumed that a three-layered feedforward network of pressure mechanoreceptors, interneurons, and motor neurons controls this behavior. Most previous studies identified and characterized the local bend network based on electrical stimulation of a single pressure mechanoreceptor, which was sufficient to trigger the local bend response. Recent studies showed, however, that up to six mechanoreceptors of three types innervating the stimulated patch of skin carry information about both touch intensity and location simultaneously. Therefore, we hypothesized that interneurons involved in the local bend network might require the temporally concerted inputs from the population of mechanoreceptors representing tactile stimuli, to decode the tactile information and to provide appropriate synaptic inputs to the motor neurons. We examined the influence of current injection into a single mechanoreceptor on activity of postsynaptic interneurons in the network and compared it to responses of interneurons to skin stimulation with different pressure intensities. We used voltage-sensitive dye imaging to monitor the graded membrane potential changes of all visible cells on the ventral side of the ganglion. Our results showed that stimulation of a single mechanoreceptor activates several local bend interneurons, consistent with previous intracellular studies. Tactile skin stimulation, however, evoked a more pronounced, longer-lasting, stimulus intensity-dependent network dynamics involving more interneurons. We concluded that the underlying local bend network enables a non-linear processing of tactile information provided by population of mechanoreceptors. This task requires a more complex network structure than previously assumed, probably containing polysynaptic interneuron connections and feedback loops. This small, experimentally well-accessible neuronal system highlights the general importance of selecting adequate sensory stimulation to investigate the network dynamics in the context of natural behavior.

Effects of Touch Location and Intensity on Interneurons of the Leech Local Bend Network

Touch triggers highly precise behavioural responses in the leech. The underlying network of this so-called local bend reflex consists of three layers of individually characterised neurons. While the population of mechanosensory cells provide multiplexed information about the stimulus, not much is known about how interneurons process this information. Here, we analyse the responses of two local bend interneurons (cell 157 and 159) to a mechanical stimulation of the skin and show their response characteristics to naturalistic stimuli. Intracellular dye-fills combined with structural imaging revealed that these interneurons are synaptically coupled to all three types of mechanosensory cells (T, P, and N cells). Since tactile stimulation of the skin evokes spikes in one to two cells of each of the latter types, interneurons combine inputs from up to six mechanosensory cells. We find that properties of touch location and intensity can be estimated reliably and accurately based on the graded interneuron responses. Connections to several mechanosensory cell types and specific response characteristics of the interneuron types indicate specialised filter and integration properties within this small neuronal network, thus providing evidence for more complex signal processing than previously thought.

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.

A classic model animal in the 21st century: recent lessons from the leech nervous system

The medicinal leech (genus Hirudo) is a classic model animal in systems neuroscience. The leech has been central to many integrative studies that establish how properties of neurons and their interconnections give rise to the functioning of the animal at the behavioral level. Leeches exhibit several discrete behaviors (such as crawling, swimming and feeding) that are each relatively simple. Importantly, these behaviors can all be studied - at least at a basal level - in the isolated nervous system. The leech nervous system is particularly amenable to such studies because of its distributed nature; sensory processing and generation of behavior occur to a large degree in iterated segmental ganglia that each contain only ∼400 neurons. Furthermore, the neurons are relatively large and are arranged with stereotyped topography on the surface of the ganglion, which greatly facilitates their identification and accessibility. This Commentary provides an overview of recent work on the leech nervous system, with particular focus on circuits that underlie leech behavior. Studies that combine the unique features of the leech with modern optical and genetic techniques are also discussed. Thus, this Commentary aims to explain the continued appeal of the leech as an experimental animal in the 21st century.

Encoding of Tactile Stimuli by Mechanoreceptors and Interneurons of the Medicinal Leech

For many animals processing of tactile information is a crucial task in behavioral contexts like exploration, foraging, and stimulus avoidance. The leech, having infrequent access to food, developed an energy efficient reaction to tactile stimuli, avoiding unnecessary muscle movements: The local bend behavior moves only a small part of the body wall away from an object touching the skin, while the rest of the animal remains stationary. Amazingly, the precision of this localized behavioral response is similar to the spatial discrimination threshold of the human fingertip, although the leech skin is innervated by an order of magnitude fewer mechanoreceptors and each midbody ganglion contains only 400 individually identified neurons in total. Prior studies suggested that this behavior is controlled by a three-layered feed-forward network, consisting of four mechanoreceptors (P cells), approximately 20 interneurons and 10 individually characterized motor neurons, all of which encode tactile stimulus location by overlapping, symmetrical tuning curves. Additionally, encoding of mechanical force was attributed to three types of mechanoreceptors reacting to distinct intensity ranges: T cells for touch, P cells for pressure, and N cells for strong, noxious skin stimulation. In this study, we provide evidences that tactile stimulus encoding in the leech is more complex than previously thought. Combined electrophysiological, anatomical, and voltage sensitive dye approaches indicate that P and T cells both play a major role in tactile information processing resulting in local bending. Our results indicate that tactile encoding neither relies on distinct force intensity ranges of different cell types, nor location encoding is restricted to spike count tuning. Instead, we propose that P and T cells form a mixed type population, which simultaneously employs temporal response features and spike counts for multiplexed encoding of touch location and force intensity. This hypothesis is supported by our finding that previously identified local bend interneurons receive input from both P and T cells. Some of these interneurons seem to integrate mechanoreceptor inputs, while others appear to use temporal response cues, presumably acting as coincidence detectors. Further voltage sensitive dye studies can test these hypotheses how a tiny nervous system performs highly precise stimulus processing.

Network feedback regulates motor output across a range of modulatory neuron activity

Modulatory projection neurons alter network neuron synaptic and intrinsic properties to elicit multiple different outputs. Sensory and other inputs elicit a range of modulatory neuron activity that is further shaped by network feedback, yet little is known regarding how the impact of network feedback on modulatory neurons regulates network output across a physiological range of modulatory neuron activity. Identified network neurons, a fully described connectome, and a well-characterized, identified modulatory projection neuron enabled us to address this issue in the crab (Cancer borealis) stomatogastric nervous system. The modulatory neuron modulatory commissural neuron 1 (MCN1) activates and modulates two networks that generate rhythms via different cellular mechanisms and at distinct frequencies. MCN1 is activated at rates of 5-35 Hz in vivo and in vitro. Additionally, network feedback elicits MCN1 activity time-locked to motor activity. We asked how network activation, rhythm speed, and neuron activity levels are regulated by the presence or absence of network feedback across a physiological range of MCN1 activity rates. There were both similarities and differences in responses of the two networks to MCN1 activity. Many parameters in both networks were sensitive to network feedback effects on MCN1 activity. However, for most parameters, MCN1 activity rate did not determine the extent to which network output was altered by the addition of network feedback. These data demonstrate that the influence of network feedback on modulatory neuron activity is an important determinant of network output and feedback can be effective in shaping network output regardless of the extent of network modulation.

A network of visual motion-sensitive neurons for computing object position in an arthropod

Highly active insects and crabs depend on visual motion information for detecting and tracking mates, prey, or predators, for which they require directional control systems containing internal maps of visual space. A neural map formed by large, motion-sensitive neurons implicated in processing panoramic flow is known to exist in an optic ganglion of the fly. However, an equivalent map for processing spatial positions of single objects has not been hitherto identified in any arthropod. Crabs can escape directly away from a visual threat wherever the stimulus is located in the 360° field of view. When tested in a walking simulator, the crab Neohelice granulata immediately adjusts its running direction after changes in the position of the visual danger stimulus smaller than 1°. Combining mass and single-cell staining with in vivo intracellular recording, we show that a particular class of motion-sensitive neurons of the crab's lobula that project to the midbrain, the monostratified lobula giants type 1 (MLG1), form a system of 16 retinotopically organized elements that map the 360° azimuthal space. The preference of these neurons for horizontally moving objects conforms the visual ecology of the crab's mudflat world. With a mean receptive field of 118°, MLG1s have a large superposition among neighboring elements. Our results suggest that the MLG1 system conveys information on object position as a population vector. Such computational code can enable the accurate directional control observed in the visually guided behaviors of crabs.

Responses to conflicting stimuli in a simple stimulus-response pathway

The "local bend response" of the medicinal leech (Hirudo verbana) is a stimulus-response pathway that enables the animal to bend away from a pressure stimulus applied anywhere along its body. The neuronal circuitry that supports this behavior has been well described, and its responses to individual stimuli are understood in quantitative detail. We probed the local bend system with pairs of electrical stimuli to sensory neurons that could not logically be interpreted as a single touch to the body wall and used multiple suction electrodes to record simultaneously the responses in large numbers of motor neurons. In all cases, responses lasted much longer than the stimuli that triggered them, implying the presence of some form of positive feedback loop to sustain the response. When stimuli were delivered simultaneously, the resulting motor neuron output could be described as an evenly weighted linear combination of the responses to the constituent stimuli. However, when stimuli were delivered sequentially, the second stimulus had greater impact on the motor neuron output, implying that the positive feedback in the system is not strong enough to render it immune to further input.

Near-optimal decoding of transient stimuli from coupled neuronal subpopulations

Coupling between sensory neurons impacts their tuning properties and correlations in their responses. How such coupling affects sensory representations and ultimately behavior remains unclear. We investigated the role of neuronal coupling during visual processing using a realistic biophysical model of the vertical system (VS) cell network in the blow fly. These neurons are thought to encode the horizontal rotation axis during rapid free-flight maneuvers. Experimental findings suggest that neurons of the VS are strongly electrically coupled, and that several downstream neurons driving motor responses to ego-rotation receive inputs primarily from a small subset of VS cells. These downstream neurons must decode information about the axis of rotation from a partial readout of the VS population response. To investigate the role of coupling, we simulated the VS response to a variety of rotating visual scenes and computed optimal Bayesian estimates from the relevant subset of VS cells. Our analysis shows that coupling leads to near-optimal estimates from a subpopulation readout. In contrast, coupling between VS cells has no impact on the quality of encoding in the response of the full population. We conclude that coupling at one level of the fly visual system allows for near-optimal decoding from partial information at the subsequent, premotor level. Thus, electrical coupling may provide a general mechanism to achieve near-optimal information transfer from neuronal subpopulations across organisms and modalities.

Complementary interactions between command-like interneurons that function to activate and specify motor programs

Motor activity is often initiated by a population of command-like interneurons. Command-like interneurons that reliably drive programs have received the most attention, so little is known about how less reliable command-like interneurons may contribute to program generation. We study two electrically coupled interneurons, cerebral-buccal interneuron-2 (CBI-2) and CBI-11, which activate feeding motor programs in the mollusk Aplysia californica. Earlier work indicated that, in rested preparations, CBI-2, a powerful activator of programs, can trigger ingestive and egestive programs. CBI-2 reliably generated ingestive patterns only when it was repeatedly stimulated. The ability of CBI-2 to trigger motor activity has been attributed to the two program-promoting peptides it contains, FCAP and CP2. Here, we show that CBI-11 differs from CBI-2 in that it contains FCAP but not CP2. Furthermore, it is weak in its ability to drive programs. On its own, CBI-11 is therefore less effective as a program activator. When it is successful, however, CBI-11 is an effective specifier of motor activity; that is, it drives mostly ingestive programs. Importantly, we found that CBI-2 and CBI-11 complement each other's actions. First, prestimulation of CBI-2 enhanced the ability of CBI-11 to drive programs. This effect appears to be partly mediated by CP2. Second, coactivation of CBI-11 with CBI-2 makes CBI-2 programs immediately ingestive. This effect may be mediated by specific actions that CBI-11 exerts on pattern-generating interneurons. Therefore, different classes of command-like neurons in a motor network may make distinct, but potentially complementary, contributions as either activators or specifiers of motor activity.

Discontinuous locomotion and prey sensing in the leech

The medicinal leech, Hirudo verbana, is an aquatic predator that utilizes water waves to locate its prey. However, to reach their prey, the leeches must move within the same water that they are using to sense prey. This requires that they either move ballistically towards a pre-determined prey location or that they account for their self-movement and continually track prey. We found that leeches do not localize prey ballistically. Instead, they require continual sensory information to track their prey. Indeed, in the event that the prey moves, leeches will approach the prey's new location. While leeches need to continually sense water disturbances to update their percept of prey location, their own behavior is discontinuous--prey involves switching between swimming, crawling and non-locomoting. Each of these behaviors may allow for different sensory capabilities and may require different sensory filters. Here, we examined the sensory capabilities of leeches during each of these behaviors. We found that while one could expect the non-locomoting phases to direct subsequent behaviors, crawling phases were more effective than non-locomotor phases for providing direction. During crawling bouts, leeches adjusted their heading so as to become more directed towards the stimulus. This was not observed during swimming. Furthermore, in the presence of prey-like stimuli, leeches crawled more often and for longer periods of time.

The use of dendrograms to describe the electrical activity of motoneurons underlying behaviors in leeches

The present manuscript aims at identifying patterns of electrical activity recorded from neurons of the leech nervous system, characterizing specific behaviors. When leeches are at rest, the electrical activity of neurons and motoneurons is poorly correlated. When leeches move their head and/or tail, in contrast, action potential (AP) firing becomes highly correlated. When the head or tail suckers detach, specific patterns of electrical activity are detected. During elongation and contraction the electrical activity of motoneurons in the Medial Anterior and Dorsal Posterior nerves increase, respectively, and several motoneurons are activated both during elongation and contraction. During crawling, swimming, and pseudo-swimming patterns of electrical activity are better described by the dendrograms of cross-correlations of motoneurons pairs. Dendrograms obtained from different animals exhibiting the same behavior are similar and by averaging these dendrograms we obtained a template underlying a given behavior. By using this template, the corresponding behavior is reliably identified from the recorded electrical activity. The analysis of dendrograms during different leech behavior reveals the fine orchestration of motoneurons firing specific to each stereotyped behavior. Therefore, dendrograms capture the subtle changes in the correlation pattern of neuronal networks when they become involved in different tasks or functions.

The spontaneous electrical activity of neurons in leech ganglia

Using the newly developed voltage-sensitive dye VF2.1.Cl, we monitored simultaneously the spontaneous electrical activity of ∼80 neurons in a leech ganglion, representing around 20% of the entire neuronal population. Neurons imaged on the ventral surface of the ganglion either fired spikes regularly at a rate of 1–5 Hz or fired sparse spikes irregularly. In contrast, neurons imaged on the dorsal surface, fired spikes in bursts involving several neurons. The overall degree of correlated electrical activity among leech neurons was limited in control conditions but increased in the presence of the neuromodulator serotonin. The spontaneous electrical activity in a leech ganglion is segregated in three main groups: neurons comprising Retzius cells, Anterior Pagoda, and Annulus Erector motoneurons firing almost periodically, a group of neurons firing sparsely and randomly, and a group of neurons firing bursts of spikes of varying durations. These three groups interact and influence each other only weakly.

Eight pairs of descending visual neurons in the dragonfly give wing motor centers accurate population vector of prey direction

Intercepting a moving object requires prediction of its future location. This complex task has been solved by dragonflies, who intercept their prey in midair with a 95% success rate. In this study, we show that a group of 16 neurons, called target-selective descending neurons (TSDNs), code a population vector that reflects the direction of the target with high accuracy and reliability across 360°. The TSDN spatial (receptive field) and temporal (latency) properties matched the area of the retina where the prey is focused and the reaction time, respectively, during predatory flights. The directional tuning curves and morphological traits (3D tracings) for each TSDN type were consistent among animals, but spike rates were not. Our results emphasize that a successful neural circuit for target tracking and interception can be achieved with few neurons and that in dragonflies this information is relayed from the brain to the wing motor centers in population vector form.

Voltage fluctuations in neurons: signal or noise?

Noise and variability are fundamental companions to ion channels and synapses and thus inescapable elements of brain function. The overriding unresolved issue is to what extent noise distorts and limits signaling on one hand and at the same time constitutes a crucial and fundamental enrichment that allows and facilitates complex adaptive behavior in an unpredictable world. Here we review the growing experimental evidence that functional network activity is associated with intense fluctuations in membrane potential and spike timing. We trace origins and consequences of noise and variability. Finally, we discuss noise-free neuronal signaling and detrimental and beneficial forms of noise in large-scale functional neural networks. Evidence that noise and variability in some cases go hand in hand with behavioral variability and increase behavioral choice, richness, and adaptability opens new avenues for future studies.

Multiplexing of motor information in the discharge of a collision detecting neuron during escape behaviors

Locusts possess an identified neuron, the descending contralateral movement detector (DCMD), conveying visual information about impending collision from the brain to thoracic motor centers. We built a telemetry system to simultaneously record, in freely behaving animals, the activity of the DCMD and of motoneurons involved in jump execution. Cocontraction of antagonistic leg muscles, a required preparatory phase, was triggered after the DCMD firing rate crossed a threshold. Thereafter, the number of DCMD spikes predicted precisely motoneuron activity and jump occurrence. Additionally, the time of DCMD peak firing rate predicted that of jump. Ablation experiments suggest that the DCMD, together with a nearly identical ipsilateral descending neuron, is responsible for the timely execution of the escape. Thus, three distinct features that are multiplexed in a single neuron's sensory response to impending collision-firing rate threshold, peak firing time, and spike count-probably control three distinct motor aspects of escape behaviors.

Gap junction expression is required for normal chemical synapse formation

Electrical and chemical synapses provide two distinct modes of direct communication between neurons, and the embryonic development of the two is typically not simultaneous. Instead, in both vertebrates and invertebrates, gap junction-based electrical synapses arise before chemical synaptogenesis, and the early circuits composed of gap junction-based electrical synapses resemble those produced later by chemical synapses. This developmental sequence from electrical to chemical synapses has led to the hypothesis that, in developing neuronal circuits, electrical junctions are necessary forerunners of chemical synapses. Up to now, it has been difficult to test this hypothesis directly, but we can identify individual neurons in the leech nervous system from before the time when synapses are first forming, so we could test the hypothesis. Using RNA interference, we transiently reduced gap junction expression in individual identified neurons during the 2-4 d when chemical synapses normally form. We found that the expected chemical synapses failed to form on schedule, and they were still missing months later when the nervous system was fully mature. We conclude that the formation of gap junctions between leech neurons is a necessary step in the formation of chemical synaptic junctions, confirming the predicted relation between electrical synapses and chemical synaptogenesis.

Which coordinate system for modelling path integration?

Path integration is a navigation strategy widely observed in nature where an animal maintains a running estimate, called the home vector, of its location during an excursion. Evidence suggests it is both ancient and ubiquitous in nature, and has been studied for over a century. In that time, canonical and neural network models have flourished, based on a wide range of assumptions, justifications and supporting data. Despite the importance of the phenomenon, consensus and unifying principles appear lacking. A fundamental issue is the neural representation of space needed for biological path integration. This paper presents a scheme to classify path integration systems on the basis of the way the home vector records and updates the spatial relationship between the animal and its home location. Four extended classes of coordinate systems are used to unify and review both canonical and neural network models of path integration, from the arthropod and mammalian literature. This scheme demonstrates analytical equivalence between models which may otherwise appear unrelated, and distinguishes between models which may superficially appear similar. A thorough analysis is carried out of the equational forms of important facets of path integration including updating, steering, searching and systematic errors, using each of the four coordinate systems. The type of available directional cue, namely allothetic or idiothetic, is also considered. It is shown that on balance, the class of home vectors which includes the geocentric Cartesian coordinate system, appears to be the most robust for biological systems. A key conclusion is that deducing computational structure from behavioural data alone will be difficult or impossible, at least in the absence of an analysis of random errors. Consequently it is likely that further theoretical insights into path integration will require an in-depth study of the effect of noise on the four classes of home vectors.

State-dependent presynaptic inhibition regulates central pattern generator feedback to descending inputs

Central pattern generators (CPGs) provide feedback to their projection neuron inputs. However, it is unknown whether this feedback is regulated and how that might shape CPG output. We are studying feedback from the pyloric CPG to identified projection neurons that regulate the gastric mill CPG, in the crab stomatogastric nervous system. Both CPGs are located in the stomatogastric ganglion (STG) and are influenced by projection neurons originating in the paired commissural ganglia (CoGs). Two extrinsic inputs [ventral cardiac neurons (VCNs) and postoesophageal commissure (POC) neurons] trigger distinct gastric mill rhythms despite acting via the same projection neurons [modulatory commissural neuron 1 (MCN1); commissural projection neuron 2 (CPN2)]. These projection neurons receive feedback inhibition from the pyloric CPG interneuron anterior burster (AB), resulting in their exhibiting pyloric-timed activity during the retraction phase of the VCN- and POC-triggered gastric mill rhythms. However, during the gastric mill protraction phase, MCN1/CPN2 exhibit pyloric-timed activity during the POC-triggered rhythm but fire tonically during the VCN-triggered rhythm. Here, we show that the latter, tonic activity pattern results from the elimination of AB inhibition of MCN1/CPN2, despite persistent AB actions within the STG and AB action potentials still propagating into each CoG. This loss of pyloric-timed AB input likely results from presynaptic inhibition of AB in each CoG because, when a secondary rhythmic AB burst initiation zone in the CoG is activated, the associated action potentials are selectively suppressed during the VCN protraction phase. Thus, rhythmic CPG feedback can be locally regulated, in a state-dependent manner, enabling the same projection neurons to drive multiple motor patterns from the same neuronal circuit.

Multifunctional pattern-generating circuits

The ability of distinct anatomical circuits to generate multiple behavioral patterns is widespread among vertebrate and invertebrate species. These multifunctional neuronal circuits are the result of multistable neural dynamics and modular organization. The evidence suggests multifunctional circuits can be classified by distinct architectures, yet the activity patterns of individual neurons involved in more than one behavior can vary dramatically. Several mechanisms, including sensory input, the parallel activity of projection neurons, neuromodulation, and biomechanics, are responsible for the switching between patterns. Recent advances in both analytical and experimental tools have aided the study of these complex circuits.

From synapses to behavior: development of a sensory-motor circuit in the leech

The development of neuronal circuits has been advanced greatly by the use of imaging techniques that reveal the activity of neurons during the period when they are constructing synapses and forming circuits. This review focuses on experiments performed in leech embryos to characterize the development of a neuronal circuit that produces a simple segmental behavior called "local bending." The experiments combined electrophysiology, anatomy, and FRET-based voltage-sensitive dyes (VSDs). The VSDs offered two major advantages in these experiments: they allowed us to record simultaneously the activity of many neurons, and unlike other imaging techniques, they revealed inhibition as well as excitation. The results indicated that connections within the circuit are formed in a predictable sequence: initially neurons in the circuit are connected by electrical synapses, forming a network that itself generates an embryonic behavior and prefigures the adult circuit; later chemical synapses, including inhibitory connections, appear, "sculpting" the circuit to generate a different, mature behavior. In this developmental process, some of the electrical connections are completely replaced by chemical synapses, others are maintained into adulthood, and still others persist and share their targets with chemical synaptic connections.

A newly identified extrinsic input triggers a distinct gastric mill rhythm via activation of modulatory projection neurons

Neuronal network flexibility enables animals to respond appropriately to changes in their internal and external states. We are using the isolated crab stomatogastric nervous system to determine how extrinsic inputs contribute to network flexibility. The stomatogastric system includes the well-characterized gastric mill (chewing) and pyloric (filtering of chewed food) motor circuits in the stomatogastric ganglion. Projection neurons with somata in the commissural ganglia (CoGs) regulate these rhythms. Previous work characterized a unique gastric mill rhythm that occurred spontaneously in some preparations, but whose origin remained undetermined. This rhythm includes a distinct protractor phase activity pattern, during which a key gastric mill circuit neuron (LG neuron) and the projection neurons MCN1 and CPN2 fire in a pyloric rhythm-timed activity pattern instead of the tonic firing pattern exhibited by these neurons during previously studied gastric mill rhythms. Here we identify a new extrinsic input, the post-oesophageal commissure (POC) neurons, relatively brief stimulation (30 s) of which triggers a long-lasting (tens of minutes) activation of this novel gastric mill rhythm at least in part via its lasting activation of MCN1 and CPN2. Immunocytochemical and electrophysiological data suggest that the POC neurons excite MCN1 and CPN2 by release of the neuropeptide Cancer borealis tachykinin-related peptide Ia (CabTRP Ia). These data further suggest that the CoG arborization of the POC neurons comprises the previously identified anterior commissural organ (ACO), a CabTRP Ia-containing neurohemal organ. This endocrine organ thus appears to also have paracrine actions, including activation of a novel and lasting gastric mill rhythm.

Neurostatistics: applications, challenges and expectations

Brain function and its relations to cognition and behavior can be elucidated only by the use of various complementary methods. Over the past 20 years, we have been studying the brain mechanisms underlying spatial processes using different methods, including the recording of single cell activity in behaving monkeys, functional magnetic resonance imaging (fMRI) and magnetoencephalography (MEG) in human subjects, all performing the same tasks. These methods provide partially overlapping perspectives, resulting in a gain in knowledge beyond the province of the individual method. A common aspect in this endeavor is the statistical analysis of the data acquired by different methods, especially regarding the encoding of information in unitary elements (single cell activity in neurophysiology, blood oxygenation level-dependent (BOLD) activation of voxels in fMRI, magnetic field strength in MEG) and the decoding of information from ensembles. In this paper we illustrate the various approaches, their data analysis and possible applications to medicine in the context of operations in space.

A model for the neuronal substrate of dead reckoning and memory in arthropods: a comparative computational and behavioral study

Returning to the point of departure after exploring the environment is a key capability for most animals. In the absence of landmarks, this task will be solved by integrating direction and distance traveled over time. This is referred to as path integration or dead reckoning. An important question is how the nervous systems of navigating animals such as the 1 mm(3) brain of ants can integrate local information in order to make global decision. In this article we propose a neurobiologically plausible system of storing and retrieving direction and distance information. The path memory of our model builds on the well established concept of population codes, moreover our system does not rely on trigonometric functions or other complex non-linear operations such as multiplication, but only uses biologically plausible operations such as integration and thresholding. We test our model in two paradigms; in the first paradigm the system receives input from a simulated compass, in the second paradigm, the model is tested against behavioral data recorded from 17 ants. We were able to show that our path memory system was able to reliably encode and compute the angle of the vector pointing to the start location, and that the system stores the total length of the trajectory in a dependable way. From the structure and behavior of our model, we derive testable predictions both at the level of observable behavior as well as on the anatomy and physiology of its underlying neuronal substrate.

Widespread inhibition proportional to excitation controls the gain of a leech behavioral circuit

Changing gain in a neuronal system has important functional consequences, but the underlying mechanisms have been elusive. Models have suggested a variety of neuronal and systems properties to accomplish gain control. Here, we show that the gain of the neuronal network underlying local bending behavior in leeches depends on widespread inhibition. Using behavioral analysis, intracellular recordings, and voltage-sensitive dye imaging, we compared the effects of blocking just the known lateral inhibition with blocking all GABAergic inhibition. This revealed an additional source of inhibition, which was widespread and increased in proportion to increasing stimulus intensity. In a model of the input/output functions of the three-layered local bending network, we showed that inhibiting all interneurons in proportion to the stimulus strength produces the experimentally observed change in gain. This relatively simple mechanism for controlling behavioral gain could be prevalent in vertebrate as well as invertebrate nervous systems.

Auditory cortical contrast enhancing by global winner-take-all inhibitory interactions

Brains decompose the world into discrete objects of perception, thereby facing the problem of how to segregate and selectively address similar objects that are concurrently present in a scene. Theoretical models propose that this could be achieved by neuronal implementations of so-called winner-take-all algorithms where neuronal representations of objects or object features interact in a competitive manner. Here we present evidence for the existence of such a mechanism in an animal species. We present electrophysiological, neuropharmacological and neuroanatomical data which suggest a novel view of the role of GABA(A)-mediated inhibition in primary auditory cortex (AI), where intracortical GABA(A)-mediated inhibition operates on a global scale within a circular map of sound periodicity representation in AI, with functionally inhibitory projections of similar effect from any location throughout the whole map. These interactions could underlie the proposed competitive "winner-take-all" algorithm to support object segregation, e.g., segregation of different speakers in cocktail-party situations.

Cellular substrates of action selection: a cluster of higher-order descending neurons shapes body posture and locomotion

The selection of distinct movements involved in various body postures and locomotion is often dependent on higher-order descending neurons. To study how such cells select different actions, we used a nearly-intact leech preparation (Hirudo sp.) in which cephalic projection interneurons were recorded and stimulated while the leech generated overt behaviors. Two long-distance projecting neurons were identified in the sub-packet of the third neuromere (R3b) of the subesophageal ganglion. These interneurons, named R3b2 and R3b3, produced changes in whole-body posture, crawling and swimming. Cell R3b2 reliably caused the body to become turgid, to hyper-elongate, and to thrash cyclically. Such robust activity resembled struggling behavior exhibited by intact leeches when grasped. The neighboring cell R3b3 elicited body elongation accompanied by a static whole-body bend to the left or right. R3b3 activity was context-dependent, oscillated in phase with crawling, reset the crawl rhythm, and terminated swimming. Both neuronal types responded to multi-modal sensory stimulation delivered to various rostral and caudal regions of the body. Our study illustrates the need to study behavioral selection with a neuroethological approach, and provides a cellular substrate for the motor action-selection cluster proposed for the vertebrate brainstem.

Multiple contributions of an input-representing neuron to the dynamics of the aplysia feeding network

In Aplysia, mutually antagonistic ingestive and egestive behaviors are produced by the same multifunctional central pattern generator (CPG) circuit. Interestingly, higher-order inputs that activate the CPG do not directly specify whether the resulting motor program is ingestive or egestive because the slow dynamics of the network intervene. One input, the commandlike cerebral-buccal interneuron 2 (CBI-2), slowly drives the motor output toward ingestion, whereas another input, the esophageal nerve (EN), drives the motor output toward egestion. When the input is switched from EN to CBI-2, the motor output does not switch immediately and remains egestive. Here, we investigated how these slow dynamics are implemented on the interneuronal level. We found that activity of two CPG interneurons, B20 and B40, tracked the motor output regardless of the input, whereas activity of another CPG interneuron, B65, tracked the input regardless of the motor output. Furthermore, we show that the slow dynamics of the network are implemented, at least in part, in the slow dynamics of the interaction between the input-representing and the output-representing neurons. We conclude that 1) a population of CPG interneurons, recruited during a particular motor program, simultaneously encodes both the input that is used to elicit the motor program and the output elicited by this input; and 2) activity of the input-representing neurons may serve to bias the future motor programs.

Large-Scale Organization of Preferred Directions in the Motor Cortex. II. Analysis of Local Distributions

The spatial arrangement of preferred directions (PDs) in the primary motor cortex has revealed evidence for columnar organization and short-range order. We investigated the large-scale properties of this arrangement. We recorded neural activity at sites on a grid covering a large region of the arm area of the motor cortex while monkeys performed a 3D reaching task. Sites were projected to the cortical surface along anatomically defined cortical columns and a PD was extracted from each site with directionally tuned activity. We analyzed the resulting 2D surface map of PDs. Consistent with previous studies, we found that any particular reaching direction was rerepresented at many points across the recorded area. In particular, we determined that the median radius of a cortical region required to represent the full complement of reaching directions is at most 1 mm. We also found that for the majority of regions of this size, the distribution of PDs within them exhibits an enrichment for the representation of forward and backward reaching directions (see companion paper). Finally, we found that the error of a population vector estimate of reaching direction constructed from neural activity within these regions is small on average, but varies significantly across different sections of the motor cortex, with the highest levels of error sustained near the fundus of the central sulcus and lowest levels achieved near the crown. We interpret these findings in the context of two well-known features of motor cortex, that is, its highly distributed anatomical organization and its behaviorally dependent plasticity.

Encoding of Naturalistic Optic Flow by a Population of Blowfly Motion-Sensitive Neurons

In sensory systems information is encoded by the activity of populations of neurons. To analyze the coding properties of neuronal populations sensory stimuli have usually been used that were much simpler than those encountered in real life. It has been possible only recently to stimulate visual interneurons of the blowfly with naturalistic visual stimuli reconstructed from eye movements measured during free flight. Therefore we now investigate with naturalistic optic flow the coding properties of a small neuronal population of identified visual interneurons in the blowfly, the so-called VS and HS neurons. These neurons are motion sensitive and directionally selective and are assumed to extract information about the animal's self-motion from optic flow. We could show that neuronal responses of VS and HS neurons are mainly shaped by the characteristic dynamical properties of the fly's saccadic flight and gaze strategy. Individual neurons encode information about both the rotational and the translational components of the animal's self-motion. Thus the information carried by individual neurons is ambiguous. The ambiguities can be reduced by considering neuronal population activity. The joint responses of different subpopulations of VS and HS neurons can provide unambiguous information about the three rotational and the three translational components of the animal's self-motion and also, indirectly, about the three-dimensional layout of the environment.

Encoding and decoding touch location in the leech CNS

Spike times encode stimulus values in many sensory systems, but it is generally unknown whether such temporal variations are decoded (i.e., whether they influence downstream networks that control behavior). In the present study, we directly address this decoding problem by quantifying both sensory encoding and decoding in the leech. By mechanically stimulating the leech body wall while recording from mechanoreceptors, we show that pairs of leech sensory neurons with overlapping receptive fields encode touch location by their relative latencies, number of spikes, and instantaneous firing rates, with relative latency being the most accurate indicator of touch location. We then show that the relative latency and count are decoded by manipulating these variables in sensory neuron pairs while simultaneously monitoring the resulting behavior. Although both variables are important determinants of leech behavior, the decoding mechanisms are more sensitive to changes in relative spike count than changes in relative latency.

Learning cross-modal spatial transformations through spike timing-dependent plasticity

A common problem in tasks involving the integration of spatial information from multiple senses, or in sensorimotor coordination, is that different modalities represent space in different frames of reference. Coordinate transformations between different reference frames are therefore required. One way to achieve this relies on the encoding of spatial information with population codes. The set of network responses to stimuli in different locations (tuning curves) constitutes a set of basis functions that can be combined linearly through weighted synaptic connections to approximate nonlinear transformations of the input variables. The question then arises: how is the appropriate synaptic connectivity obtained? Here we show that a network of spiking neurons can learn the coordinate transformation from one frame of reference to another, with connectivity that develops continuously in an unsupervised manner, based only on the correlations available in the environment and with a biologically realistic plasticity mechanism (spike timing-dependent plasticity).

Statistical properties of information processing in neuronal networks

Information processing and coding were analysed in dissociated hippocampal cultures, grown on multielectrode arrays. Multisite stimulation was used to activate different neurons and pathways of the network. The neural activity was binned into firing rates and the variability of the firing of individual neurons and of the whole population was analysed. In individual neurons, the timing of the first action potential (AP) was rather precise from trial to trial, whereas the timing of later APs was much more variable. Pooling APs in an ensemble of neurons reduced the variability of the response and allowed stimuli varying in intensity to be distinguished reliably in a single trial. A similar decrease of variability was observed pooling the first evoked APs in an ensemble of neurons. The size of the neuronal pool (approximately 50-100 neurons) and the time bin (approximately 20 ms) necessary to provide reproducible responses are remarkably similar to those obtained in in vivo preparations and in small nervous systems. Blockage of excitatory synaptic pathways mediated by NMDA receptors improved the mutual information between the evoked response and stimulus properties. When inhibitory GABAergic pathways were blocked by bicuculline the opposite effect was obtained. These results show how ensemble averages and an appropriate balance between inhibition and excitation allow neuronal networks to process information in a fast and reliable way.

Movement control: dedicated or distributed?

Neural networks in which 'commands' spread 'horizontally' across multiple neurons have been believed to mediate motor pattern variation. A recent study shows that dedicated 'vertical' neural pathways can also underlie these variations.

Neuronal control of leech behavior

The medicinal leech has served as an important experimental preparation for neuroscience research since the late 19th century. Initial anatomical and developmental studies dating back more than 100 years ago were followed by behavioral and electrophysiological investigations in the first half of the 20th century. More recently, intense studies of the neuronal mechanisms underlying leech movements have resulted in detailed descriptions of six behaviors described in this review; namely, heartbeat, local bending, shortening, swimming, crawling, and feeding. Neuroethological studies in leeches are particularly tractable because the CNS is distributed and metameric, with only 400 identifiable, mostly paired neurons in segmental ganglia. An interesting, yet limited, set of discrete movements allows students of leech behavior not only to describe the underlying neuronal circuits, but also interactions among circuits and behaviors. This review provides descriptions of six behaviors including their origins within neuronal circuits, their modification by feedback loops and neuromodulators, and interactions between circuits underlying with these behaviors.

Degenerate coding in neural systems

When the dimensionality of a neural circuit is substantially larger than the dimensionality of the variable it encodes, many different degenerate network states can produce the same output. In this review I will discuss three different neural systems that are linked by this theme. The pyloric network of the lobster, the song control system of the zebra finch, and the odor encoding system of the locust, while different in design, all contain degeneracies between their internal parameters and the outputs they encode. Indeed, although the dynamics of song generation and odor identification are quite different, computationally, odor recognition can be thought of as running the song generation circuitry backwards. In both of these systems, degeneracy plays a vital role in mapping a sparse neural representation devoid of correlations onto external stimuli (odors or song structure) that are strongly correlated. I argue that degeneracy between input and output states is an inherent feature of many neural systems, which can be exploited as a fault-tolerant method of reliably learning, generating, and discriminating closely related patterns.

Electronic neuron within a ganglion of a leech (Hirudo medicinalis)

We report the construction of an electronic device that models and replaces a neuron in a midbody ganglion of the leech Hirudo medicinalis. In order to test the behavior of our device, we used a well-characterized synaptic interaction between the mechanosensory, sensitive to pressure, (P) cell and the anteropagoda (because of the action potential shape) (AP) neuron. We alternatively stimulated a P neuron and our device connected to the AP neuron, and studied the response of the latter. The number and timing of the AP spikes were the same when the electronic parameters were properly adjusted. Moreover, after changes in the depolarization of the AP cell, the responses under the stimulation of both the biological neuron and the electronic device vary in a similar manner.