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- Volume 44, 2021
Annual Review of Neuroscience - Volume 44, 2021
Volume 44, 2021
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Sources of Individual Differences in Pain
Vol. 44 (2021), pp. 1–25More LessPain is an immense clinical and societal challenge, and the key to understanding and treating it is variability. Robust interindividual differences are consistently observed in pain sensitivity, susceptibility to developing painful disorders, and response to analgesic manipulations. This review examines the causes of this variability, including both organismic and environmental sources. Chronic pain development is a textbook example of a gene-environment interaction, requiring both chance initiating events (e.g., trauma, infection) and more immutable risk factors. The focus is on genetic factors, since twin studies have determined that a plurality of the variance likely derives from inherited genetic variants, but sex, age, ethnicity, personality variables, and environmental factors are also considered.
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Current Status of and Perspectives on the Application of Marmosets in Neurobiology
Vol. 44 (2021), pp. 27–48More LessThe common marmoset (Callithrix jacchus), a small New World primate, is receiving substantial attention in the neuroscience and biomedical science fields because its anatomical features, functional and behavioral characteristics, and reproductive features and its amenability to available genetic modification technologies make it an attractive experimental subject. In this review, I outline the progress of marmoset neuroscience research and summarize both the current status (opportunities and limitations) of and the future perspectives on the application of marmosets in neuroscience and disease modeling.
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Astrocytes and Behavior
Vol. 44 (2021), pp. 49–67More LessAnimal behavior was classically considered to be determined exclusively by neuronal activity, whereas surrounding glial cells such as astrocytes played only supportive roles. However, astrocytes are as numerous as neurons in the mammalian brain, and current findings indicate a chemically based dialog between astrocytes and neurons. Activation of astrocytes by synaptically released neurotransmitters converges on regulating intracellular Ca2+ in astrocytes, which then can regulate the efficacy of near and distant tripartite synapses at diverse timescales through gliotransmitter release. Here, we discuss recent evidence on how diverse behaviors are impacted by this dialog. These recent findings support a paradigm shift in neuroscience, in which animal behavior does not result exclusively from neuronal activity but from the coordinated activity of both astrocytes and neurons. Decoding how astrocytes and neurons interact with each other in various brain circuits will be fundamental to fully understanding how behaviors originate and become dysregulated in disease.
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A Common Space Approach to Comparative Neuroscience
Vol. 44 (2021), pp. 69–86More LessComparative neuroscience is entering the era of big data. New high-throughput methods and data-sharing initiatives have resulted in the availability of large, digital data sets containing many types of data from ever more species. Here, we present a framework for exploiting the new possibilities offered. The multimodality of the data allows vertical translations, which are comparisons of different aspects of brain organization within a single species and across scales. Horizontal translations compare particular aspects of brain organization across species, often by building abstract feature spaces. Combining vertical and horizontal translations allows for more sophisticated comparisons, including relating principles of brain organization across species by contrasting horizontal translations, and for making formal predictions of unobtainable data based on observed results in a model species.
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Parkinson's Disease Genetics and Pathophysiology
Vol. 44 (2021), pp. 87–108More LessParkinson's disease (PD) is a common neurodegenerative disorder characterized by degeneration of the substantia nigra pars compacta and by accumulation of α-synuclein in Lewy bodies. PD is caused by a combination of environmental factors and genetic variants. These variants range from highly penetrant Mendelian alleles to alleles that only modestly increase disease risk. Here, we review what is known about the genetics of PD. We also describe how PD genetics have solidified the role of endosomal, lysosomal, and mitochondrial dysfunction in PD pathophysiology. Finally, we highlight how all three pathways are affected by α-synuclein and how this knowledge may be harnessed for the development of disease-modifying therapeutics.
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Neural and Molecular Mechanisms of Biological Embedding of Social Interactions
Vol. 44 (2021), pp. 109–128More LessAnimals operate in complex environments, and salient social information is encoded in the nervous system and then processed to initiate adaptive behavior. This encoding involves biological embedding, the process by which social experience affects the brain to influence future behavior. Biological embedding is an important conceptual framework for understanding social decision-making in the brain, as it encompasses multiple levels of organization that regulate how information is encoded and used to modify behavior. The framework we emphasize here is that social stimuli provoke short-term changes in neural activity that lead to changes in gene expression on longer timescales. This process, simplified—neurons are for today and genes are for tomorrow—enables the assessment of the valence of a social interaction, an appropriate and rapid response, and subsequent modification of neural circuitry to change future behavioral inclinations in anticipation of environmental changes. We review recent research on the neural and molecular basis of biological embedding in the context of social interactions, with a special focus on the honeybee.
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Smartphones and the Neuroscience of Mental Health
Vol. 44 (2021), pp. 129–151More LessImprovements in understanding the neurobiological basis of mental illness have unfortunately not translated into major advances in treatment. At this point, it is clear that psychiatric disorders are exceedingly complex and that, in order to account for and leverage this complexity, we need to collect longitudinal data sets from much larger and more diverse samples than is practical using traditional methods. We discuss how smartphone-based research methods have the potential to dramatically advance our understanding of the neuroscience of mental health. This, we expect, will take the form of complementing lab-based hard neuroscience research with dense sampling of cognitive tests, clinical questionnaires, passive data from smartphone sensors, and experience-sampling data as people go about their daily lives. Theory- and data-driven approaches can help make sense of these rich data sets, and the combination of computational tools and the big data that smartphones make possible has great potential value for researchers wishing to understand how aspects of brain function give rise to, or emerge from, states of mental health and illness.
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Integrated Patterning Programs During Drosophila Development Generate the Diversity of Neurons and Control Their Mature Properties
Vol. 44 (2021), pp. 153–172More LessDuring the approximately 5 days of Drosophila neurogenesis (late embryogenesis to the beginning of pupation), a limited number of neural stem cells produce approximately 200,000 neurons comprising hundreds of cell types. To build a functional nervous system, neuronal types need to be produced in the proper places, appropriate numbers, and correct times. We discuss how neural stem cells (neuroblasts) obtain so-called area codes for their positions in the nervous system (spatial patterning) and how they keep time to sequentially produce neurons with unique fates (temporal patterning). We focus on specific examples that demonstrate how a relatively simple patterning system (Notch) can be used reiteratively to generate different neuronal types. We also speculate on how different modes of temporal patterning that operate over short versus long time periods might be linked. We end by discussing how specification programs are integrated and lead to the terminal features of different neuronal types.
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Consolidating the Circuit Model for Addiction
Vol. 44 (2021), pp. 173–195More LessAddiction is a disease characterized by compulsive drug seeking and consumption observed in 20–30% of users. An addicted individual will favor drug reward over natural rewards, despite major negative consequences. Mechanistic research on rodents modeling core components of the disease has identified altered synaptic transmission as the functional substrate of pathological behavior. While the initial version of a circuit model for addiction focused on early drug adaptive behaviors observed in all individuals, it fell short of accounting for the stochastic nature of the transition to compulsion. The model builds on the initial pharmacological effect common to all addictive drugs—an increase in dopamine levels in the mesolimbic system. Here, we consolidate this early model by integrating circuits underlying compulsion and negative reinforcement. We discuss the genetic and epigenetic correlates of individual vulnerability. Many recent data converge on a gain-of-function explanation for circuit remodeling, revealing blueprints for novel addiction therapies.
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Ensheathment and Myelination of Axons: Evolution of Glial Functions
Vol. 44 (2021), pp. 197–219More LessMyelination of axons provides the structural basis for rapid saltatory impulse propagation along vertebrate fiber tracts, a well-established neurophysiological concept. However, myelinating oligodendrocytes and Schwann cells serve additional functions in neuronal energy metabolism that are remarkably similar to those of axon-ensheathing glial cells in unmyelinated invertebrates. Here we discuss myelin evolution and physiological glial functions, beginning with the role of ensheathing glia in preventing ephaptic coupling, axoglial metabolic support, and eliminating oxidative radicals. In both vertebrates and invertebrates, axoglial interactions are bidirectional, serving to regulate cell fate, nerve conduction, and behavioral performance. One key step in the evolution of compact myelin in the vertebrate lineage was the emergence of the open reading frame for myelin basic protein within another gene. Several other proteins were neofunctionalized as myelin constituents and help maintain a healthy nervous system. Myelination in vertebrates became a major prerequisite of inhabiting new ecological niches.
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Neocortical Layer 1: An Elegant Solution to Top-Down and Bottom-Up Integration
Vol. 44 (2021), pp. 221–252More LessMany of our daily activities, such as riding a bike to work or reading a book in a noisy cafe, and highly skilled activities, such as a professional playing a tennis match or a violin concerto, depend upon the ability of the brain to quickly make moment-to-moment adjustments to our behavior in response to the results of our actions. Particularly, they depend upon the ability of the neocortex to integrate the information provided by the sensory organs (bottom-up information) with internally generated signals such as expectations or attentional signals (top-down information). This integration occurs in pyramidal cells (PCs) and their long apical dendrite, which branches extensively into a dendritic tuft in layer 1 (L1). The outermost layer of the neocortex, L1 is highly conserved across cortical areas and species. Importantly, L1 is the predominant input layer for top-down information, relayed by a rich, dense mesh of long-range projections that provide signals to the tuft branches of the PCs. Here, we discuss recent progress in our understanding of the composition of L1 and review evidence that L1 processing contributes to functions such as sensory perception, cross-modal integration, controlling states of consciousness, attention, and learning.
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Human Representation Learning
Vol. 44 (2021), pp. 253–273More LessThe central theme of this review is the dynamic interaction between information selection and learning. We pose a fundamental question about this interaction: How do we learn what features of our experiences are worth learning about? In humans, this process depends on attention and memory, two cognitive functions that together constrain representations of the world to features that are relevant for goal attainment. Recent evidence suggests that the representations shaped by attention and memory are themselves inferred from experience with each task. We review this evidence and place it in the context of work that has explicitly characterized representation learning as statistical inference. We discuss how inference can be scaled to real-world decisions by approximating beliefs based on a small number of experiences. Finally, we highlight some implications of this inference process for human decision-making in social environments.
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Dense Circuit Reconstruction to Understand Neuronal Computation: Focus on Zebrafish
Vol. 44 (2021), pp. 275–293More LessThe dense reconstruction of neuronal wiring diagrams from volumetric electron microscopy data has the potential to generate fundamentally new insights into mechanisms of information processing and storage in neuronal circuits. Zebrafish provide unique opportunities for dynamical connectomics approaches that combine reconstructions of wiring diagrams with measurements of neuronal population activity and behavior. Such approaches have the power to reveal higher-order structure in wiring diagrams that cannot be detected by sparse sampling of connectivity and that is essential for neuronal computations. In the brain stem, recurrently connected neuronal modules were identified that can account for slow, low-dimensional dynamics in an integrator circuit. In the spinal cord, connectivity specifies functional differences between premotor interneurons. In the olfactory bulb, tuning-dependent connectivity implements a whitening transformation that is based on the selective suppression of responses to overrepresented stimulus features. These findings illustrate the potential of dynamical connectomics in zebrafish to analyze the circuit mechanisms underlying higher-order neuronal computations.
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The Role of the Medial Prefrontal Cortex in Moderating Neural Representations of Self and Other in Primates
Vol. 44 (2021), pp. 295–313More LessAs a frontal node in the primate social brain, the medial prefrontal cortex (MPFC) plays a critical role in coordinating one's own behavior with respect to that of others. Current literature demonstrates that single neurons in the MPFC encode behavior-related variables such as intentions, actions, and rewards, specifically for self and other, and that the MPFC comes into play when reflecting upon oneself and others. The social moderator account of MPFC function can explain maladaptive social cognition in people with autism spectrum disorder, which tips the balance in favor of self-centered perspectives rather than taking into consideration the perspective of others. Several strands of evidence suggest a hypothesis that the MPFC represents different other mental models, depending on the context at hand, to better predict others’ emotions and behaviors. This hypothesis also accounts for aberrant MPFC activity in autistic individuals while they are mentalizing others.
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Inferring Macroscale Brain Dynamics via Fusion of Simultaneous EEG-fMRI
Vol. 44 (2021), pp. 315–334More LessAdvances in the instrumentation and signal processing for simultaneously acquired electroencephalography and functional magnetic resonance imaging (EEG-fMRI) have enabled new ways to observe the spatiotemporal neural dynamics of the human brain. Central to the utility of EEG-fMRI neuroimaging systems are the methods for fusing the two data streams, with machine learning playing a key role. These methods can be dichotomized into those that are symmetric and asymmetric in terms of how the two modalities inform the fusion. Studies using these methods have shown that fusion yields new insights into brain function that are not possible when each modality is acquired separately. As technology improves and methods for fusion become more sophisticated, the future of EEG-fMRI for noninvasive measurement of brain dynamics includes mesoscale mapping at ultrahigh magnetic resonance fields, targeted perturbation-based neuroimaging, and using deep learning to uncover nonlinear representations that link the electrophysiological and hemodynamic measurements.
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Ion Channel Degeneracy, Variability, and Covariation in Neuron and Circuit Resilience
Vol. 44 (2021), pp. 335–357More LessThe large number of ion channels found in all nervous systems poses fundamental questions concerning how the characteristic intrinsic properties of single neurons are determined by the specific subsets of channels they express. All neurons display many different ion channels with overlapping voltage- and time-dependent properties. We speculate that these overlapping properties promote resilience in neuronal function. Individual neurons of the same cell type show variability in ion channel conductance densities even though they can generate reliable and similar behavior. This complicates a simple assignment of function to any conductance and is associated with variable responses of neurons of the same cell type to perturbations, deletions, and pharmacological manipulation. Ion channel genes often show strong positively correlated expression, which may result from the molecular and developmental rules that determine which ion channels are expressed in a given cell type.
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Oxytocin, Neural Plasticity, and Social Behavior
Vol. 44 (2021), pp. 359–381More LessOxytocin regulates parturition, lactation, parental nurturing, and many other social behaviors in both sexes. The circuit mechanisms by which oxytocin modulates social behavior are receiving increasing attention. Here, we review recent studies on oxytocin modulation of neural circuit function and social behavior, largely enabled by new methods of monitoring and manipulating oxytocin or oxytocin receptor neurons in vivo. These studies indicate that oxytocin can enhance the salience of social stimuli and increase signal-to-noise ratios by modulating spiking and synaptic plasticity in the context of circuits and networks. We highlight oxytocin effects on social behavior in nontraditional organisms such as prairie voles and discuss opportunities to enhance the utility of these organisms for studying circuit-level modulation of social behaviors. We then discuss recent insights into oxytocin neuron activity during social interactions. We conclude by discussing some of the major questions and opportunities in the field ahead.
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Physiology and Pathophysiology of Mechanically Activated PIEZO Channels
Vol. 44 (2021), pp. 383–402More LessNearly all structures in our body experience mechanical forces. At a molecular scale, these forces are detected by ion channels that function as mechanotransducers converting physical forces into electrochemical responses. Here we focus on PIEZOs, a family of mechanically activated ion channels comprising PIEZO1 and PIEZO2. The significance of these channels is highlighted by their roles in touch and pain sensation as well as in cardiovascular and respiratory physiology, among others. Moreover, mutations in PIEZOs cause somatosensory, proprioceptive, and blood disorders. The goal here is to present the diverse physiology and pathophysiology of these unique channels, discuss ongoing research and critical gaps in the field, and explore the pharmaceutical interest in targeting PIEZOs for therapeutic development.
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The Geometry of Information Coding in Correlated Neural Populations
Vol. 44 (2021), pp. 403–424More LessNeurons in the brain represent information in their collective activity. The fidelity of this neural population code depends on whether and how variability in the response of one neuron is shared with other neurons. Two decades of studies have investigated the influence of these noise correlations on the properties of neural coding. We provide an overview of the theoretical developments on the topic. Using simple, qualitative, and general arguments, we discuss, categorize, and relate the various published results. We emphasize the relevance of the fine structure of noise correlation, and we present a new approach to the issue. Throughout this review, we emphasize a geometrical picture of how noise correlations impact the neural code.
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The Cortical Motor Areas and the Emergence of Motor Skills: A Neuroanatomical Perspective
Vol. 44 (2021), pp. 425–447More LessWhat changes in neural architecture account for the emergence and expansion of dexterity in primates? Dexterity, or skill in performing motor tasks, depends on the ability to generate highly fractionated patterns of muscle activity. It also involves the spatiotemporal coordination of activity in proximal and distal muscles across multiple joints. Many motor skills require the generation of complex movement sequences that are only acquired and refined through extensive practice. Improvements in dexterity have enabled primates to manufacture and use tools and humans to engage in skilled motor behaviors such as typing, dance, musical performance, and sports. Our analysis leads to the following synthesis: The neural substrate that endows primates with their enhanced motor capabilities is due, in part, to (a) major organizational changes in the primary motor cortex and (b) the proliferation of output pathways from other areas of the cerebral cortex, especially from the motor areas on the medial wall of the hemisphere.
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Perceptual Inference, Learning, and Attention in a Multisensory World
Vol. 44 (2021), pp. 449–473More LessAdaptive behavior in a complex, dynamic, and multisensory world poses some of the most fundamental computational challenges for the brain, notably inference, decision-making, learning, binding, and attention. We first discuss how the brain integrates sensory signals from the same source to support perceptual inference and decision-making by weighting them according to their momentary sensory uncertainties. We then show how observers solve the binding or causal inference problem—deciding whether signals come from common causes and should hence be integrated or else be treated independently. Next, we describe the multifarious interplay between multisensory processing and attention. We argue that attentional mechanisms are crucial to compute approximate solutions to the binding problem in naturalistic environments when complex time-varying signals arise from myriad causes. Finally, we review how the brain dynamically adapts multisensory processing to a changing world across multiple timescales.
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Adaptive Prediction for Social Contexts: The Cerebellar Contribution to Typical and Atypical Social Behaviors
Vol. 44 (2021), pp. 475–493More LessSocial interactions involve processes ranging from face recognition to understanding others’ intentions. To guide appropriate behavior in a given context, social interactions rely on accurately predicting the outcomes of one's actions and the thoughts of others. Because social interactions are inherently dynamic, these predictions must be continuously adapted. The neural correlates of social processing have largely focused on emotion, mentalizing, and reward networks, without integration of systems involved in prediction. The cerebellum forms predictive models to calibrate movements and adapt them to changing situations, and cerebellar predictive modeling is thought to extend to nonmotor behaviors. Primary cerebellar dysfunction can produce social deficits, and atypical cerebellar structure and function are reported in autism, which is characterized by social communication challenges and atypical predictive processing. We examine the evidence that cerebellar-mediated predictions and adaptation play important roles in social processes and argue that disruptions in these processes contribute to autism.
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Neurophysiology of Human Perceptual Decision-Making
Vol. 44 (2021), pp. 495–516More LessThe discovery of neural signals that reflect the dynamics of perceptual decision formation has had a considerable impact. Not only do such signals enable detailed investigations of the neural implementation of the decision-making process but they also can expose key elements of the brain's decision algorithms. For a long time, such signals were only accessible through direct animal brain recordings, and progress in human neuroscience was hampered by the limitations of noninvasive recording techniques. However, recent methodological advances are increasingly enabling the study of human brain signals that finely trace the dynamics of the unfolding decision process. In this review, we highlight how human neurophysiological data are now being leveraged to furnish new insights into the multiple processing levels involved in forming decisions, to inform the construction and evaluation of mathematical models that can explain intra- and interindividual differences, and to examine how key ancillary processes interact with core decision circuits.
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How Cortical Circuits Implement Cortical Computations: Mouse Visual Cortex as a Model
Vol. 44 (2021), pp. 517–546More LessThe mouse, as a model organism to study the brain, gives us unprecedented experimental access to the mammalian cerebral cortex. By determining the cortex's cellular composition, revealing the interaction between its different components, and systematically perturbing these components, we are obtaining mechanistic insight into some of the most basic properties of cortical function. In this review, we describe recent advances in our understanding of how circuits of cortical neurons implement computations, as revealed by the study of mouse primary visual cortex. Further, we discuss how studying the mouse has broadened our understanding of the range of computations performed by visual cortex. Finally, we address how future approaches will fulfill the promise of the mouse in elucidating fundamental operations of cortex.
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Spatial Transcriptomics: Molecular Maps of the Mammalian Brain
Vol. 44 (2021), pp. 547–562More LessMaps of the nervous system inspire experiments and theories in neuroscience. Advances in molecular biology over the past decades have revolutionized the definition of cell and tissue identity. Spatial transcriptomics has opened up a new era in neuroanatomy, where the unsupervised and unbiased exploration of the molecular signatures of tissue organization will give rise to a new generation of brain maps. We propose that the molecular classification of brain regions on the basis of their gene expression profile can circumvent subjective neuroanatomical definitions and produce common reference frameworks that can incorporate cell types, connectivity, activity, and other modalities. Here we review the technological and conceptual advances made possible by spatial transcriptomics in the context of advancing neuroanatomy and discuss how molecular neuroanatomy can redefine mapping of the nervous system.
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Previous Volumes
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Volume 47 (2024)
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Volume 46 (2023)
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Volume 45 (2022)
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Volume 44 (2021)
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Volume 43 (2020)
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Volume 42 (2019)
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Volume 41 (2018)
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Volume 40 (2017)
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Volume 39 (2016)
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Volume 38 (2015)
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Volume 37 (2014)
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Volume 36 (2013)
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Volume 35 (2012)
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Volume 34 (2011)
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Volume 33 (2010)
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Volume 32 (2009)
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Volume 31 (2008)
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Volume 30 (2007)
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Volume 29 (2006)
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Volume 28 (2005)
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Volume 27 (2004)
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Volume 26 (2003)
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Volume 25 (2002)
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Volume 24 (2001)
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Volume 23 (2000)
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Volume 22 (1999)
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Volume 21 (1998)
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Volume 20 (1997)
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Volume 19 (1996)
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Volume 18 (1995)
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Volume 17 (1994)
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Volume 16 (1993)
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Volume 15 (1992)
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Volume 14 (1991)
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Volume 13 (1990)
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Volume 12 (1989)
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Volume 11 (1988)
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Volume 10 (1987)
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Volume 9 (1986)
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Volume 8 (1985)
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Volume 7 (1984)
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Volume 6 (1983)
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Volume 5 (1982)
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Volume 4 (1981)
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Volume 3 (1980)
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Volume 2 (1979)
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Volume 1 (1978)
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Volume 0 (1932)