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.
Stomatogastric Nervous System
Neural Processing of Pain and Itch
Taylor Follansbee, Mirela Iodi Carstens, and E. Carstens
Pain is defined as “An unpleasant sensory and emotional experience associated with, or resembling that associated with, actual or potential tissue damage,” while itch can be defined as “an unpleasant sensation that evokes the desire to scratch.” These sensations are normally elicited by noxious or pruritic stimuli that excite peripheral sensory neurons connected to spinal circuits and ascending pathways involved in sensory discrimination, emotional aversiveness, and respective motor responses. Specialized molecular receptors expressed by cutaneous nerve endings transduce stimuli into action potentials conducted by C- and Aδ-fiber nociceptors and pruriceptors into the outer lamina of the dorsal horn of the spinal cord. Here, neurons selectively activated by nociceptors, or by convergent input from nociceptors, pruriceptors, and often mechanoreceptors, transmit signals to ascending spinothalamic and spinoparabrachial pathways. The spinal circuitry for itch requires interneurons expressing gastrin-releasing peptide and its receptor, while spinal pain circuitry involves other excitatory neuropeptides; both itch and pain are transmitted by ascending pathways that express the receptor for substance P. Spinal itch- and pain-transmitting circuitry is segmentally modulated by inhibitory interneurons expressing dynorphin, GABA, and glycine, which mediate the antinociceptive and antipruritic effects of noxious counterstimulation. Spinal circuits are also under descending modulation from the brainstem rostral ventromedial medulla. Opioids like morphine inhibit spinal pain-transmitting circuits segmentally and via descending inhibitory pathways, while having the opposite effect on itch. The supraspinal targets of ascending pain and itch pathways exhibit extensive overlap and include the somatosensory thalamus, parabrachial nucleus, amygdala, periaqueductal gray, and somatosensory, anterior cingulate, insular, and supplementary motor cortical areas. Following tissue injury, enhanced pain is evoked near the injury (primary hyperalgesia) due to release of inflammatory mediators that sensitize nociceptors. Within a larger surrounding area of secondary hyperalgesia, innocuous mechanical stimuli elicit pain (allodynia) due to central sensitization of pain pathways. Pruriceptors can also become sensitized in pathophysiological conditions, such as dermatitis. Under chronic itch conditions, low-threshold tactile stimulation can elicit itch (alloknesis), presumably due to central sensitization of itch pathways, although this has not been extensively studied. There is considerable overlap in pain- and itch-signaling pathways and it remains unclear how these sensations are discriminated. Specificity theory states that itch and pain are separate sensations with their own distinct pathways (“labeled lines”). Selectivity theory is similar but incorporates the observation that pruriceptive neurons are also excited by algogenic stimuli that inhibit spinal itch transmission. In contrast, intensity theory states that itch is signaled by low firing rates, and pain by high firing rates, in a common sensory pathway. Finally, the spatial contrast theory proposes that itch is elicited by focal activation of a few nociceptors while activation of more nociceptors over a larger area elicits pain. There is evidence supporting each theory, and it remains to be determined how the nervous system distinguishes between pain and itch.
Quentin Gaudry and Jonathan Schenk
Olfactory systems are tasked with converting the chemical environment into electrical signals that the brain can use to optimize behaviors such as navigating towards resources, finding mates, or avoiding danger. Drosophila melanogaster has long served as a model system for several attributes of olfaction. Such features include sensory coding, development, and the attempt to link sensory perception to behavior. The strength of Drosophila as a model system for neurobiology lies in the myriad of genetic tools made available to the experimentalist, and equally importantly, the numerical reduction in cell numbers within the olfactory circuit. Modern techniques have recently made it possible to target nearly all cell types in the antennal lobe to directly monitor their physiological activity or to alter their expression of endogenous proteins or transgenes.
Normalization Principles in Computational Neuroscience
Kenway Louie and Paul W. Glimcher
A core question in systems and computational neuroscience is how the brain represents information. Identifying principles of information coding in neural circuits is critical to understanding brain organization and function in sensory, motor, and cognitive neuroscience. This provides a conceptual bridge between the underlying biophysical mechanisms and the ultimate behavioral goals of the organism. Central to this framework is the question of computation: what are the relevant representations of input and output, and what algorithms govern the input-output transformation? Remarkably, evidence suggests that certain canonical computations exist across different circuits, brain regions, and species. Such computations are implemented by different biophysical and network mechanisms, indicating that the unifying target of conservation is the algorithmic form of information processing rather than the specific biological implementation. A prime candidate to serve as a canonical computation is divisive normalization, which scales the activity of a given neuron by the activity of a larger neuronal pool. This nonlinear transformation introduces an intrinsic contextual modulation into information coding, such that the selective response of a neuron to features of the input is scaled by other input characteristics. This contextual modulation allows the normalization model to capture a wide array of neural and behavioral phenomena not captured by simpler linear models of information processing. The generality and flexibility of the normalization model arises from the normalization pool, which allows different inputs to directly drive and suppress a given neuron, effectively separating information that drives excitation and contextual modulation. Originally proposed to describe responses in early visual cortex, normalization has been widely documented in different brain regions, hierarchical levels, and modalities of sensory processing; furthermore, recent work shows that the normalization extends to cognitive processes such as attention, multisensory integration, and decision making. This ubiquity reinforces the canonical nature of the normalization computation and highlights the importance of an algorithmic framework in linking biological mechanism and behavior.
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.