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Article

Caenorhabditis elegans Olfaction  

Douglas K. Reilly and Jagan Srinivasan

To survive, animals must properly sense their surrounding environment. The types of sensation that allow for detecting these changes can be categorized as tactile, thermal, aural, or olfactory. Olfaction is one of the most primitive senses, involving the detection of environmental chemical cues. Organisms must sense and discriminate between abiotic and biogenic cues, necessitating a system that can react and respond to changes quickly. The nematode, Caenorhabditis elegans, offers a unique set of tools for studying the biology of olfactory sensation. The olfactory system in C. elegans is comprised of 14 pairs of amphid neurons in the head and two pairs of phasmid neurons in the tail. The male nervous system contains an additional 89 neurons, many of which are exposed to the environment and contribute to olfaction. The cues sensed by these olfactory neurons initiate a multitude of responses, ranging from developmental changes to behavioral responses. Environmental cues might initiate entry into or exit from a long-lived alternative larval developmental stage (dauer), or pheromonal stimuli may attract sexually mature mates, or repel conspecifics in crowded environments. C. elegans are also capable of sensing abiotic stimuli, exhibiting attraction and repulsion to diverse classes of chemicals. Unlike canonical mammalian olfactory neurons, C. elegans chemosensory neurons express more than one receptor per cell. This enables detection of hundreds of chemical structures and concentrations by a chemosensory nervous system with few cells. However, each neuron detects certain classes of olfactory cues, and, combined with their synaptic pathways, elicit similar responses (i.e., aversive behaviors). The functional architecture of this chemosensory system is capable of supporting the development and behavior of nematodes in a manner efficient enough to allow for the genus to have a cosmopolitan distribution.

Article

The Insect Central Complex  

Stanley Heinze

The central complex (CX) is the only unpaired brain region of the insect brain. It is located at the interface of sensory processing and motor control and plays a vital role in context dependent action selection. The CX has four main tasks. First, the encoding of the insect’s orientation in space, i.e., the generation of an internal head direction signal based on both rotational self-motion and external sensory signals. Second, the generation of goal direction representations. Third, the selection of an appropriate goal direction based on context, internal state, and previous experience. And finally, the initiation of motor steering signals based on comparing heading direction and goal directions. The highly regular, almost crystalline neuroarchitecture of repeating computational elements provide the structural basis for these computations. These tight structure function relationships have revealed that the CX performs highly efficient, vector-based computations, in which vectors are encoded as sinusoidal activity patterns across populations of neurons. The deep insight into the computational algorithms implemented in this brain area have made the CX a prime model system to study the neural basis of context-dependent action selection and behavioral decisions, as well as the mechanisms of circuit evolution.

Article

Cephalopod Nervous System Organization  

Z. Yan Wang and Clifton W. Ragsdale

Over 700 species of cephalopods live in the Earth’s waters, occupying almost every marine zone, from the benthic deep to the open ocean to tidal waters. The greatly varied forms and charismatic behaviors of these animals have long fascinated humans. Cephalopods are short-lived, highly mobile predators with sophisticated brains that are the largest among the invertebrates. While cephalopod brains share a similar anatomical organization, the nervous systems of coleoids (octopus, squid, cuttlefish) and nautiloids all display important lineage-specific neural adaptations. The octopus brain, for example, has for its arms a well-developed tactile learning and memory system that is vestigial in, or absent from, that of other cephalopods. The unique anatomy of the squid giant fiber system enables rapid escape in the event of capture. The brain of the nautilus comprises fewer lobes than its coleoid counterparts, but contains olfactory system structures and circuits not yet identified in other cephalopods.

Article

Drosophila Reward Circuits  

John S. Hernandez, Tariq M. Brown, and Karla R. Kaun

The ability to sense and respond to a rewarding stimulus is a key advantage for animals in their natural environment. The circuits that mediate these responses are complex, and it has been difficult to identify the fundamental principles of reward structure and function. However, the well-characterized brain anatomy and sophisticated neurogenetic tools in Drosophila melanogaster make the fly an ideal model to understand the mechanisms through which reward is encoded. Drosophila find food, water, intoxicating substances, and social acts rewarding. Basic monoaminergic neurotransmitters, including dopamine (DA), serotonin (5-HT), and octopamine (OA), play a central role in encoding these rewards. DA is central to sensing, encoding, responding, and predicting reward, whereas 5-HT and OA carry information about the environment that influences DA circuit activity. In contrast, slower-acting neuromodulators such as hormones and neuropeptides play a key role in both encoding the pleasurable stimulus and modulating how the internal environment of the fly influences reward sensation and seeking. Recurring circuit motifs for reward signaling identified in Drosophila suggest that these key principles will help elucidate understanding of how reward circuits function in all animals.

Article

Stomatogastric Nervous System  

Wolfgang Stein

The crustacean stomatogastric nervous system contains a set of distinct but interacting rhythmic motor circuits that control movements of the foregut. When isolated, these circuits produce activity patterns that are almost perfect replicas of their behavior in vivo. The ease with which distinct circuit neurons are identified, recorded, and manipulated has provided considerable insight into the general principles of how motor circuits operate and are controlled at the cellular level. The small number of relatively large neurons has facilitated several technical advances in neuroscience research and allowed the identification of one of the earliest circuit connectomes. This enabled, for the first time, studies of circuit dynamics using the relationships between all component neurons of a nervous center. A major discovery was that circuits are not dedicated to producing a single neuronal activity pattern, and that the involved neurons are not committed to particular circuits. This flexibility results predominantly from the ability of neuromodulators to change the cellular and synaptic properties of circuit neurons. The relatively unique access to, and detailed documentation of, identified circuit, sensory, and descending pathways has also started new avenues into examining how individual modulatory neurons and transmitters affect their target cells. Groundbreaking experimental and modeling work has further demonstrated that the intrinsic properties of neurons depend on their recent history of activation and that neurons and circuits counterbalance destabilizing influences by compensatory homeostatic regulation of ionic conductances. The stomatogastric microcircuits continue to provide key insight into neural circuit operation in numerically larger and less accessible systems.

Article

Single Neuron Computational Modeling  

Yeonjoo Yoo and Fabrizio Gabbiani

Computational modeling is essential to understand how the complex dendritic structure and membrane properties of a neuron process input signals to generate output signals. Compartmental models describe how inputs, such as synaptic currents, affect a neuron’s membrane potential and produce outputs, such as action potentials, by converting membrane properties into the components of an electrical circuit. The simplest such model consists of a single compartment with a leakage conductance which represents a neuron having spatially uniform membrane potential and a constant conductance summarizing the combined effect of every ion flowing across the neuron’s membrane. The Hodgkin-Huxley model introduces two additional active channels; the sodium channel and the delayed rectifier potassium channel whose associated conductances change depending on the membrane potential and that are described by an additional set of three nonlinear differential equations. Since its conception in 1952, many kinds of active channels have been discovered with a variety of characteristics that can successfully be modeled within the same framework. As the membrane potential varies spatially in a neuron, the next refinement consists in describing a neuron as an electric cable to account for membrane potential attenuation and signal propagation along dendritic or axonal processes. A discrete version of the cable equation results in compartments with possibly different properties, such as different types of ion channels or spatially varying maximum conductances to model changes in channel densities. Branching neural processes such as dendrites can be modeled with the cable equation by considering the junctions of cables with different radii and electrical properties. Single neuron computational models are used to investigate a variety of topics and reveal insights that cannot be evidenced directly by experimental observation. Studies on action potential initiation and on synaptic integration provide prototypical examples illustrating why computational models are essential. Modeling action potential initiation constrains the localization and density of channels required to reproduce experimental observations, while modeling synaptic integration sheds light on the interaction between the morphological and physiological characteristics of dendrites. Finally, reduced compartmental models demonstrate how a simplified morphological structure supplemented by a small number of ion channel-related variables can provide clear explanations about complex intracellular membrane potential dynamics.

Article

Sensing Polarized Light in Insects  

Thomas F. Mathejczyk and Mathias F. Wernet

Evolution has produced vast morphological and behavioral diversity amongst insects, including very successful adaptations to a diverse range of ecological niches spanning the invasion of the sky by flying insects, the crawling lifestyle on (or below) the earth, and the (semi-)aquatic life on (or below) the water surface. Developing the ability to extract a maximal amount of useful information from their environment was crucial for ensuring the survival of many insect species. Navigating insects rely heavily on a combination of different visual and non-visual cues to reliably orient under a wide spectrum of environmental conditions while avoiding predators. The pattern of linearly polarized skylight that results from scattering of sunlight in the atmosphere is one important navigational cue that many insects can detect. Here we summarize progress made toward understanding how different insect species sense polarized light. First, we present behavioral studies with “true” insect navigators (central-place foragers, like honeybees or desert ants), as well as insects that rely on polarized light to improve more “basic” orientation skills (like dung beetles). Second, we provide an overview over the anatomical basis of the polarized light detection system that these insects use, as well as the underlying neural circuitry. Third, we emphasize the importance of physiological studies (electrophysiology, as well as genetically encoded activity indicators, in Drosophila) for understanding both the structure and function of polarized light circuitry in the insect brain. We also discuss the importance of an alternative source of polarized light that can be detected by many insects: linearly polarized light reflected off shiny surfaces like water represents an important environmental factor, yet the anatomy and physiology of underlying circuits remain incompletely understood.

Article

Gastropod Feeding Systems: Evolution of Neural Circuits that Generate Diverse Behaviors  

Paul Benjamin and Michael Crossley

It is conceptually reasonable to explore how the evolution of behavior involves changes in neural circuitry. Progress in determining this evolutionary relationship has been limited in neuroscience because of difficulties in identifying individual neurons that contribute to the evolutionary development of behaviors across species. However, the results from the feeding systems of gastropod mollusks provide evidence for this concept of co-evolution because the evolution of different types of feeding behaviors in this diverse group of mollusks is mirrored by species-specific changes in neural circuitry. The evolution of feeding behaviors involves changes in the motor actions that allow diverse food items to be acquired and ingested. The evolution in neural control accompanies this variation in food and the associated changes in flexibility of feeding behaviors. This is present in components of the feeding network that are involved in decision making, rhythm generation, and behavioral switching but is absent in background mechanisms that are conserved across species, such as those controlling arousal state. These findings show how evolutionary changes, even at the single neuron level, closely reflect the details of behavioral evolution.

Article

Crayfish Escape  

Donald Edwards

Crayfish are decapod crustaceans that use different forms of escape to flee from different types of predatory attacks. Lateral and Medial Giant escapes are released by giant interneurons of the same name in response to sudden, sharp attacks from the rear and front of the animal, respectively. A Lateral Giant (LG) escape uses a fast rostral abdominal flexion to pitch the animal up and forward at very short latency. It is succeeded by guided swimming movements powered by a series of rapid abdominal flexions and extensions. A Medial Giant (MG) escape uses a fast, full abdominal flexion to thrust the animal directly backward, and is also followed by swimming that moves the animal rapidly away from the attacker. More slowly developing attacks evoke Non-Giant (NG) escapes, which have a longer latency, are varied in the form of abdominal flexion, and are directed initially away from the attacker. They, too, are followed by swimming away from the attacker. The neural circuitry for LG escape has been extensively studied and has provided insights into the neural control of behavior, synaptic integration, coincidence detection, electrical synapses, behavioral and synaptic plasticity, neuroeconomical decision-making, and the modulatory effects of monoamines and of changes in the animal’s social status.

Article

Active Electroreception in Weakly Electric Fish  

Angel Ariel Caputi

American gymnotiformes and African mormyriformes have evolved an active sensory system using a self-generated electric field as a carrier of signals. Objects polarized by the discharge of a specialized electric organ project their images on the skin where electroreceptors tuned to the time course of the self-generated field transduce local signals carrying information about impedance, shape, size, and location of objects, as well as electrocommunication messages, and encode them as primary afferents trains of spikes. This system is articulated with other cutaneous systems (passive electroreception and mechanoception) as well as proprioception informing the shape of the fish’s body. Primary afferents project on the electrosensory lobe where electrosensory signals are compared with expectation signals resulting from the integration of recent past electrosensory, other sensory, and, in the case of mormyriformes, electro- and skeleton-motor corollary discharges. This ensemble of signals converges on the apical dendrites of the principal cells where a working memory of the recent past, and therefore predictable input, is continuously built up and updated as a pattern of synaptic weights. The efferent neurons of the electrosensory lobe also project to the torus and indirectly to other brainstem nuclei that implement automatic electro- and skeleton-motor behaviors. Finally, the torus projects via the preglomerular nucleus to the telencephalon where cognitive functions, including “electroperception” of shape-, size- and impedance-related features of objects, recognition of conspecifics, perception based decisions, learning, and abstraction, are organized.