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Caenorhabditis elegans Learning and Memory  

James S.H. Wong and Catharine H. Rankin

The nematode, Caenorhabditis elegans (C. elegans), is an organism useful for the study of learning and memory at the molecular, cellular, neural circuitry, and behavioral levels. Its genetic tractability, transparency, connectome, and accessibility for in vivo cellular and molecular analyses are a few of the characteristics that make the organism such a powerful system for investigating mechanisms of learning and memory. It is able to learn and remember across many sensory modalities, including mechanosensation, chemosensation, thermosensation, oxygen sensing, and carbon dioxide sensing. C. elegans habituates to mechanosensory stimuli, and shows short-, intermediate-, and long-term memory, and context conditioning for mechanosensory habituation. The organism also displays chemotaxis to various chemicals, such as diacetyl and sodium chloride. This behavior is associated with several forms of learning, including state-dependent learning, classical conditioning, and aversive learning. C. elegans also shows thermotactic learning in which it learns to associate a particular temperature with the presence or absence of food. In addition, both oxygen preference and carbon dioxide avoidance in C. elegans can be altered by experience, indicating that they have memory for the oxygen or carbon dioxide environment they were reared in. Many of the genes found to underlie learning and memory in C. elegans are homologous to genes involved in learning and memory in mammals; two examples are crh-1, which is the C. elegans homolog of the cAMP response element-binding protein (CREB), and glr-1, which encodes an AMPA glutamate receptor subunit. Both of these genes are involved in long-term memory for tap habituation, context conditioning in tap habituation, and chemosensory classical conditioning. C. elegans offers the advantage of having a very small nervous system (302 neurons), thus it is possible to understand what these conserved genes are doing at the level of single identified neurons. As many mechanisms of learning and memory in C. elegans appear to be similar in more complex organisms including humans, research with C. elegans aids our ever-growing understanding of the fundamental mechanisms of learning and memory across the animal kingdom.


Olfactory Perception  

Daniel W. Wesson, Sang Eun Ryu, and Hillary L. Cansler

The perception of odors exerts powerful influences on moods, decisions, and actions. Indeed, odor perception is a major driving force underlying some of the most important human behaviors. How is it that the simple inhalation of airborne molecules can exert such strong effects on complex aspects of human functions? Certainly, just like in the case of vision and audition, the perception of odors is dictated by the ability to transduce environmental information into an electrical “code” for the brain to use. However, the use of that information, including whether or not the information is used at all, is governed strongly by many emotional and cognitive factors, including learning and experiences, as well as states of arousal and attention. Understanding the manners whereby these factors regulate both the perception of odors and how an individual responds to those percepts are paramount for appreciating the orchestration of behavior.


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.


Understanding How Humans Learn and Adapt to Changing Environments  

Daphne Bavelier and Aaron Cochrane

Compared to other animals or to artificial agents, humans are unique in the extent of their abilities to learn and adapt to changing environments. When focusing on skill learning and model-based approaches, learning can be conceived as a progression of increasing, then decreasing, dimensions of representing knowledge. First, initial learning demands exploration of the learning space and the identification of the relevant dimensions for the novel task at hand. Second, intermediate learning requires a refinement of these relevant dimensions of knowledge and behavior to continue improving performance while increasing efficiency. Such improvements utilize chunking or other forms of dimensionality reduction to diminish task complexity. Finally, late learning ensures automatization of behavior through habit formation and expertise development, thereby reducing the need to effortfully control behavior. While automatization greatly increases efficiency, there is also a trade-off with the ability to generalize, with late learning tending to be highly specific to the learned features and contexts. In each of these phases a variety of interacting factors are relevant: Declarative instructions, prior knowledge, attentional deployment, and cognitive fitness have unique roles to play. Neural contributions to processes involved also shift from earlier to later points in learning as effortfulness initially increases and then gives way to automaticity. Interestingly, video games excel at providing uniquely supportive environments to guide the learner through each of these learning stages. This fact makes video games a useful tool for both studying learning, due to their engaging nature and dynamic range of complexity, as well as engendering learning in domains such as education or cognitive training.


Crustacean Visual Circuits Underlying Behavior  

Daniel Tomsic and Julieta Sztarker

Decapod crustaceans, in particular semiterrestrial crabs, are highly visual animals that greatly rely on visual information. Their responsiveness to visual moving stimuli, with behavioral displays that can be easily and reliably elicited in the laboratory, together with their sturdiness for experimental manipulation and the accessibility of their nervous system for intracellular electrophysiological recordings in the intact animal, make decapod crustaceans excellent experimental subjects for investigating the neurobiology of visually guided behaviors. Investigations of crustaceans have elucidated the general structure of their eyes and some of their specializations, the anatomical organization of the main brain areas involved in visual processing and their retinotopic mapping of visual space, and the morphology, physiology, and stimulus feature preferences of a number of well-identified classes of neurons, with emphasis on motion-sensitive elements. This anatomical and physiological knowledge, in connection with results of behavioral experiments in the laboratory and the field, are revealing the neural circuits and computations involved in important visual behaviors, as well as the substrate and mechanisms underlying visual memories in decapod crustaceans.


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.


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.


Investigating Learning and Memory in Humans  

Evangelia G. Chrysikou, Elizabeth Espinal, and Alexandra E. Kelly

Memory refers to the set of cognitive systems and the neural structures that support them that allow humans to learn from experience, leverage this knowledge to understand and guide behavior in the present, and use past memories to think about and plan for the future. Neuroscience research on learning and memory has leveraged advances in behavioral methods, structural and functional brain imaging, noninvasive brain stimulation, and lesion studies to evaluate synergies and dissociations among small- and large-scale neural networks in support of memory performance. Overall, this work has converged to a conceptualization of new memories as representations of distributed patterns of neural activity across cortical and subcortical brain systems that provide neural grounding of sensorimotor and perceptual experiences, actions, thoughts, and emotions, and which can be reinstated as a result of internal or external cues. Most of this literature has supported dissociations among working and long-term memory, as well as between procedural, episodic, and semantic memories. On the other hand, progress in human neuroscience methodologies has revealed the interdependence of these memory systems in the context of complex cognitive tasks and suggests a dynamic and highly interactive neural architecture underlying human learning and memory. Future neuroscience research is anticipated to focus on understanding the neural mechanisms supporting this interactivity at the cellular and systems levels, as well as investigating the time course of their engagement.


Behavioral Neuroendocrinology: Cognition  

Victoria Luine

The demonstration of steroid binding proteins in brain areas outside of the hypothalamus was a key neuroendocrine discovery in the 1980s. These findings suggested that gonadal hormones, estradiol and testosterone, may have additional functions besides controlling reproduction through the hypothalamic–pituitary–gonadal axis (HPG) and that glucocorticoids may also influence neural functions not related to the hypothalamic–pituitary–adrenal axis (HPA). In the past 30 years, since the early 1990s, a body of neuroendocrine studies in animals has provided evidence for these hypotheses, and in 2020, it is generally accepted that steroid hormones exert robust influences over cognition—both learning and memory. Gonadal hormones, predominantly estrogens, enhance learning and memory in rodents and humans and influence cognitive processes throughout the lifespan. Gonadal hormones bind to classical nuclear estrogen receptors and to membrane receptors to influence cognition. In contrast to the generally positive effects of gonadal hormones on learning and memory, adrenal hormones (glucocorticoids in rodents or cortisol in primates) released during chronic stress have adverse effects on cognition, causing impairments in both learning and memory. However, emerging evidence suggests that impairments may be limited only to males, as chronic stress in females does not usually impair cognition and, in many cases, enhances it. The cognitive resilience of females to stress may result from interactions between the HPG and HPA axis, with estrogens exerting neuroprotective effects against glucocorticoids at both the morphological and neurochemical level. Overall, knowledge of the biological underpinnings of hormonal effects on cognitive function has enormous implications for human health and well-being by providing novel tools for mitigating memory loss, for treating stress-related disorders, and for understanding the bases for resilience versus susceptibility to stress.


Transcriptional Regulation Underlying Long-Term Sensitization in Aplysia  

Robert J. Calin-Jageman, Theresa Wilsterman, and Irina E. Calin-Jageman

The induction of a long-term memory requires both transcriptional change and neural plasticity. Many of the links between transcription and memory have been revealed through the study of long-term sensitization in the Aplysia genus of marine mollusks. Sensitization is a conserved, non-associative form of pain memory in which a painful stimulus produces an increase in arousal and defensive behavior. The neural circuits that help encode sensitization memory are well characterized, and sensitization can be simulated in neuronal cell cultures. One feature of sensitization in Aplysia is that only some training protocols initiate transcription and produce long-term memory; others produce only short-term memories. This occurs because the induction of long-term sensitization requires the activation of two signal-transduction pathways that regulate transcription: (a) a fast but transient activation of the cAMP/PKA pathway that activates the transcription factor CREB1 and (b) a delayed activation of the ERK isoform of MAPK that deactivates the transcriptional repressor CREB2. The effectiveness of different training protocols is based on the synchronization of these pathways. The cAMP/PKA and MAPK pathways are complex, involving extracellular and trans-synaptic signaling, feedback loops, and crosstalk. It has proven possible to model transcriptional activation with enough fidelity to generate in silico predictions for optimized learning, which has been validated in cell cultures and intact animals. Training protocols that successfully activate CREB1 while deactivating CREB2 produce a complex transcriptional cascade that helps encode long-term sensitization memory. The transcriptional cascade involves a focused wave of immediate-early transcriptional activations. This includes the activation of additional transcription factors, such as C/EBP, as well as effectors such as uch, sensorin, and tolloid/BMP-1. These early transcriptional changes close feedback loops that help extend and stabilize the early wave of transcriptional changes, triggering a broader late wave of transcriptional changes likely to alter neural signaling, increase protein production, transport mRNAs, and induce meta-plasticity. A small set of transcripts participate in both the early and late waves, and several of these (CREB1, synataxin, eIF4) play essential roles in completing the induction of long-term sensitization. Most transcriptional changes fade as sensitization memory is forgotten, but some changes persist beyond forgetting, including a long-lasting up-regulation of an inhibitory peptide transmitter that could foster forgetting. The maintenance of long-term sensitization may involve self-sustaining transcriptional feedback loops. In particular, CREB1 binds to its own promoter, producing a long-lasting increase in CREB1 mRNA, protein, and gene activation that is essential for sustaining cellular correlates of sensitization for at least 1 day after induction. Many aspects of the induction, stabilization, and maintenance of sensitization memory in Aplysia are conserved, suggesting that it will continue to be a fruitful, simpler system for understanding the physical basis of lasting memory.


Plasticity of Stepping Rhythms in the Intact and Injured Mammalian Spinal Cord  

Serge Rossignol

The spinal cord is a prime example of how the central nervous system has evolved to execute and retain movements adapted to the environment. This results from the evolution of inborn intrinsic spinal circuits modified continuously by repetitive interactions with the outside world, as well as by developing internal needs or goals. This article emphasizes the underlying neuroplastic spinal mechanisms through observations of normal animal adaptive locomotor behavior in different imposed conditions. It further explores the motor spinal capabilities after various types of lesions to the spinal cord and the potential mechanisms underlying the spinal changes occurring after these lesions, leading to recovery of function. Together, these observations strengthen the idea of the immense potential of the motor rehabilitation approach in humans with spinal cord injury since extrinsic interventions (training, pharmacology, and electrical stimulation) can modulate and optimize remnant motor functions after injury.


Deep Neural Networks in Computational Neuroscience  

Tim C. Kietzmann, Patrick McClure, and Nikolaus Kriegeskorte

The goal of computational neuroscience is to find mechanistic explanations of how the nervous system processes information to give rise to cognitive function and behavior. At the heart of the field are its models, that is, mathematical and computational descriptions of the system being studied, which map sensory stimuli to neural responses and/or neural to behavioral responses. These models range from simple to complex. Recently, deep neural networks (DNNs) have come to dominate several domains of artificial intelligence (AI). As the term “neural network” suggests, these models are inspired by biological brains. However, current DNNs neglect many details of biological neural networks. These simplifications contribute to their computational efficiency, enabling them to perform complex feats of intelligence, ranging from perceptual (e.g., visual object and auditory speech recognition) to cognitive tasks (e.g., machine translation), and on to motor control (e.g., playing computer games or controlling a robot arm). In addition to their ability to model complex intelligent behaviors, DNNs excel at predicting neural responses to novel sensory stimuli with accuracies well beyond any other currently available model type. DNNs can have millions of parameters, which are required to capture the domain knowledge needed for successful task performance. Contrary to the intuition that this renders them into impenetrable black boxes, the computational properties of the network units are the result of four directly manipulable elements: input statistics, network structure, functional objective, and learning algorithm. With full access to the activity and connectivity of all units, advanced visualization techniques, and analytic tools to map network representations to neural data, DNNs represent a powerful framework for building task-performing models and will drive substantial insights in computational neuroscience.