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BDNF-Induced Plasticity of Spinal Circuits Underlying Pain and Learning  

Sandra M. Garraway

Understanding of the various types of plasticity that occur in the spinal cord, as well as understanding of spinal cord functions, has vastly improved over the past 50 years, mainly due to an increase in the number of research studies and review articles on the subject. It is now understood that the spinal cord is not merely a passive conduit of neural impulses. Instead, the spinal cord can independently execute complex functions. Numerous experimental approaches have been utilized for more targeted exploration of spinal cord functions. For example, isolating the spinal cord from supraspinal influences has been used to demonstrate that simple forms of learning can be performed by spinal neuronal networks. Moreover, reduced preparations, such as acute spinal cord slices, have been used to show that spinal neurons undergo different types of modulation, including activity-dependent synaptic modification. Most spinal cord processes, ranging from integration of incoming sensory input to execution of locomotor outputs, involve plasticity. Nociceptive processing that leads to pain and spinal learning is an example of plasticity that is well-studied in the spinal cord. At the neural level, both processes involve an interplay of cellular mediators, which include glutamate receptors, protein kinases, and growth factors. The neurotrophin brain-derived neurotrophic factor (BDNF) has also been implicated in these processes, specifically as a promoter of both pro-nociception and spinal learning mechanisms. Interestingly, the role of BDNF in mediating spinal plasticity can be altered by injury. The literature spanning approximately 5 decades is reviewed and the role of BDNF is discussed in mediating cellular plasticity underlying pain processing and learning within the spinal cord.


Neural Mechanisms for Odor-Guided Behavior  

Giuliano Gaeta, Regina M. Sullivan, and Donald A. Wilson

Odor- or chemical-guided behavior is expressed in all species. Such behavioral responses to odors begin with transduction at olfactory receptors and, after initial processing in early stages of the olfactory system (e.g., vertebrate olfactory bulb, invertebrate antennal lobe), the information is rapidly (within one to two synapses) distributed to diverse brain regions controlling hedonics, metabolic balance, mating, and spatial navigation, among many other basic functions. Odors can not only drive or guide specific behavioral responses but can also modulate behavioral choices and affective state, in many cases in humans without conscious awareness. Many of the specific neural circuits underlying odor-guided behaviors have been partially described, though much remains unknown. Neural processes underlying odor-guided reward and aversion, kin recognition, feeding, orientation, and navigation across diverse species have been discussed, as well as odor modulation of human behavior and emotion.


Neural Mechanisms of Tinnitus  

Adam Hockley and Susan E. Shore

Tinnitus is the perception of sound that is independent from an external stimulus. Despite the word tinnitus being derived from the Latin verb for ring, tinnire, it can present as buzzing, hissing, or clicking. Tinnitus is generated centrally in the auditory pathway; however, the neural mechanisms underlying this generation have been disputed for decades. Although it is well accepted that tinnitus is produced by damage to the auditory system by exposure to loud sounds, the level of damage required and how this damage results in tinnitus are unclear. Neural recordings in the auditory brainstem, midbrain, and forebrain of animals with models of tinnitus have revealed increased spontaneous firing rates, capable of being perceived as a sound. There are many proposed mechanisms of how this increase is produced, including spike-timing-dependent plasticity, homeostatic plasticity, central gain, reduced inhibition, thalamocortical dysrhythmia, and increased inflammation. Animal studies are highly useful for testing these potential mechanisms because the noise damage can be carefully titrated and recordings can be made directly from neural populations of interest. These studies have advanced the field greatly; however, the limitations are that the variety of models for tinnitus induction and quantification are not well standardized, which may explain some of the variability seen across studies. Human studies use patients with tinnitus (but an unknown level of cochlear damage) to probe neural mechanisms of tinnitus. They use noninvasive methods, often recoding gross evoked potentials, oscillations, or imaging brain activity to determine if tinnitus sufferers show altered processing of sounds or silence. These studies have also revealed putative neural mechanisms of tinnitus, such as increased delta- or gamma-band cortical activity, altered Bayesian prediction of incoming sound, and changes to limbic system activity. Translation between animal and human studies has allowed some neural correlates of tinnitus to become more widely accepted, which has in turn allowed deeper research into the underlying mechanism of the correlates. As the understanding of neural mechanisms of tinnitus grows, the potential for treatments is also improved, with the ultimate goal being a true treatment for tinnitus perception.


Neural Processing of Taste Information  

Alfredo Fontanini and Lindsey Czarnecki

The gustatory system has evolved to detect molecules dissolved into the saliva. It is responsible for the perception of taste and flavor, for mediating the interaction between perception and internal homoeostatic states, and for driving ingestive decisions. The widely recognized five basic taste categories (sweet, salty, bitter, sour, and umami) provide information about the nutritional or potentially harmful content in what is being consumed. Sweetness is typical of sugars that are carbohydrate dense; saltiness is the percept of ions which are necessary for physiological function and electrolytic homeostasis; bitterness is associated with alkaloids and other potential toxins; sourness is the percept of acidity signaling spoiling foods; and umami is the sensation associated with amino acids in protein-rich foods. In addition to taste, the act of eating also engages sensations of temperature, texture, and odor—the integration of all these sensations leads to the unitary percept of flavor. These same senses, and others such as vision and audition, are also engaged before an ingestive event. Sights, sounds, and smells can alert organisms to the presence of food as well as inform the organism as to the specifics of which taste(s) to expect. As such, the neurophysiology of taste is necessarily intertwined with that of other senses and with that of cognitive and homeostatic systems.


Plasticity of Information Processing in the Auditory System  

Andrew J. King

Information processing in the auditory system shows considerable adaptive plasticity across different timescales. This ranges from very rapid changes in neuronal response properties—on the order of hundreds of milliseconds when the statistics of sounds vary or seconds to minutes when their behavioral relevance is altered—to more gradual changes that are shaped by experience and learning. Many aspects of auditory processing and perception are sculpted by sensory experience during sensitive or critical periods of development. This developmental plasticity underpins the acquisition of language and musical skills, matches neural representations in the brain to the statistics of the acoustic environment, and enables the neural circuits underlying the ability to localize sound to be calibrated by the acoustic consequences of growth-related changes in the anatomy of the body. Although the length of these critical periods depends on the aspect of auditory processing under consideration, varies across species and brain level, and may be extended by experience and other factors, it is generally accepted that the potential for plasticity declines with age. Nevertheless, a substantial degree of plasticity is exhibited in adulthood. This is important for the acquisition of new perceptual skills; facilitates improvements in the detection or discrimination of fine differences in sound properties; and enables the brain to compensate for changes in inputs, including those resulting from hearing loss. In contrast to the plasticity that shapes the developing brain, perceptual learning normally requires the sound attribute in question to be behaviorally relevant and is driven by practice or training on specific tasks. Progress has recently been made in identifying the brain circuits involved and the role of neuromodulators in controlling plasticity, and an understanding of plasticity in the central auditory system is playing an increasingly important role in the treatment of hearing disorders.


The Neural Basis of Behavioral Sequences in Cortical and Subcortical Circuits  

Katherine E. Conen and Theresa M. Desrochers

Sequences of actions and experiences are a central part of daily life in many species. Sequences consist of a set of ordered steps with a distinct beginning and end. They are defined by the serial order and relationships between items, though not necessarily by precise timing intervals. Sequences can be composed from a wide range of elements, including motor actions, perceptual experiences, memories, complex behaviors, or abstract goals. However, despite this variation, different types of sequences may share common features in neural coding. Examining the neural responses that support sequences is important not only for understanding the sequential behavior in daily life but also for investigating the array of diseases and disorders that impact sequential processes and the impact of therapeutics used to treat them. Research into the neural coding of sequences can be organized into the following broad categories: responses to ordinal position, coding of adjacency and inter-item relationships, boundary responses, and gestalt coding (representation of the sequence as a whole). These features of sequence coding have been linked to changes in firing rate patterns and neuronal oscillations across a range of cortical and subcortical brain areas and may be integrated in the lateral prefrontal cortex. Identification of these coding schemes has laid out an outline for understanding how sequences are represented at a neural level. Expanding from this work, future research faces fundamental questions about how these coding schemes are linked together to generate the complex range of sequential processes that influence cognition and behavior across animal species.


Vision and Art  

Bevil R. Conway

The premise of the field of vision and art is that studies of visual processing can inform an understanding of visual art and artistic practice, and a close reading of art, art history, and art practice can help generate hypotheses about how vision works. Paraphrasing David Hubel, visual neurobiology can enhance art just as knowledge of bones and muscles has for centuries informed artistic representations of the body. The umbrella of visual art encompasses a bewildering diversity of works. A focus on 2-dimensional artworks provides an introduction to the field. For each of the steps taken by the visual brain to turn retinal images into perception, one can ask how the biology informs one’s understanding of visual art, how visual artists have exploited aspects of how the brain processes visual information, and what the strategies deployed by visual artists reveal about neural mechanisms of vision.


The Processing of Hydrodynamic Stimuli With the Fish Lateral Line System  

Joachim Mogdans

All fish have a mechanosensory lateral line system for the detection of hydrodynamic stimuli. It is thus not surprising that the lateral line system is involved in numerous behaviors, including obstacle avoidance, localization of predators and prey, social communication, and orientation in laminar and turbulent flows. The sensory units of the lateral line system are the neuromasts, which occur freestanding on the skin (superficial neuromasts) and within subdermal canals (canal neuromasts). The canals are in contact with the surrounding water through a series of canal pores. Neuromasts consist of a patch of sensory hair cells covered by a gelatinous cupula. Water flow causes cupula motion, which in turn leads to a change in the hair cells’ receptor potentials and a subsequent change in the firing rate of the innervating afferent nerve fibers. These fibers encode velocity, direction, and vorticity of water motions by means of spike trains. They project predominantly to lateral line neurons in the brainstem for further processing of the received hydrodynamic signals. From the brainstem, lateral line information is transferred to the cerebellum and to midbrain and forebrain nuclei, where lateral line information is integrated with information from other sensory modalities to create a three-dimensional image of the hydrodynamic world surrounding the animal. For fish to determine spatial location and identity of a wave source as well as direction and velocity of water movements, the lateral line system must analyze the various types of hydrodynamic stimuli that fish are exposed to in their natural habitat. Natural hydrodynamic stimuli include oscillatory water motions generated by stationary vibratory sources, such as by small crustaceans; complex water motions produced by animate or inanimate moving objects, such as by swimming fish; bulk water flow in rivers and streams; and water flow containing vortices generated at the edges of objects in a water flow. To uncover the mechanisms that underlie the coding of hydrodynamic information by the lateral line system, neurophysiological experiments have been performed at the level of the primary afferent nerve fibers, but also in the central nervous system, predominantly in the brainstem and midbrain, using sinusoidally vibrating spheres, moving objects, vortex rings, bulk water flow, and Kármán vortex streets as wave sources. Unravelling these mechanisms is fundamental to understanding how the fish brain uses hydrodynamic information to adequately guide behavior.


Evolution, Homology, Cell Classification, and Parallel Processing for Vision  

W. Martin Usrey and S. Murray Sherman

A first step in analyzing complex systems is a classification of component elements. This applies to retinal organization as well as to other circuit components in the visual system. There is great variety in the types of retinal ganglion cells and the targets of their axonal projections. Thus, a prerequisite to any deep understanding of the early visual system is developing a proper classification of its elements. How many distinct classes of retinal ganglion cells are there? Can the main classes be broken down into subclasses? What sort of functional correlates can be established for each class? Can homologous relationships between apparently similar classes between species be established? Can a common nomenclature based on homologous cell and circuit classes be developed?


Confidence in Decision-Making  

Megan A.K. Peters

The human brain processes noisy information to help make adaptive choices under uncertainty. Accompanying these decisions about incoming evidence is a sense of confidence: a feeling about whether a decision is correct. Confidence typically covaries with the accuracy of decisions, in that higher confidence is associated with higher decisional accuracy. In the laboratory, decision confidence is typically measured by asking participants to make judgments about stimuli or information (type 1 judgments) and then to rate their confidence on a rating scale or by engaging in wagering (type 2 judgments). The correspondence between confidence and accuracy can be quantified in a number of ways, some based on probability theory and signal detection theory. But decision confidence does not always reflect only the probability that a decision is correct; confidence can also reflect many other factors, including other estimates of noise, evidence magnitude, nearby decisions, decision time, and motor movements. Confidence is thought to be computed by a number of brain regions, most notably areas in the prefrontal cortex. And, once computed, confidence can be used to drive other behaviors, such as learning rates or social interaction.