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- Volume 40, 2017
Annual Review of Neuroscience - Volume 40, 2017
Volume 40, 2017
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The Role of Variability in Motor Learning
Vol. 40 (2017), pp. 479–498More LessTrial-to-trial variability in the execution of movements and motor skills is ubiquitous and widely considered to be the unwanted consequence of a noisy nervous system. However, recent studies have suggested that motor variability may also be a feature of how sensorimotor systems operate and learn. This view, rooted in reinforcement learning theory, equates motor variability with purposeful exploration of motor space that, when coupled with reinforcement, can drive motor learning. Here we review studies that explore the relationship between motor variability and motor learning in both humans and animal models. We discuss neural circuit mechanisms that underlie the generation and regulation of motor variability and consider the implications that this work has for our understanding of motor learning.
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Architecture, Function, and Assembly of the Mouse Visual System
Vol. 40 (2017), pp. 499–538More LessVision is the sense humans rely on most to navigate the world, make decisions, and perform complex tasks. Understanding how humans see thus represents one of the most fundamental and important goals of neuroscience. The use of the mouse as a model for parsing how vision works at a fundamental level started approximately a decade ago, ushered in by the mouse's convenient size, relatively low cost, and, above all, amenability to genetic perturbations. In the course of that effort, a large cadre of new and powerful tools for in vivo labeling, monitoring, and manipulation of neurons were applied to this species. As a consequence, a significant body of work now exists on the architecture, function, and development of mouse central visual pathways. Excitingly, much of that work includes causal testing of the role of specific cell types and circuits in visual perception and behavior—something rare to find in studies of the visual system of other species. Indeed, one could argue that more information is now available about the mouse visual system than any other sensory system, in any species, including humans. As such, the mouse visual system has become a platform for multilevel analysis of the mammalian central nervous system generally. Here we review the mouse visual system structure, function, and development literature and comment on the similarities and differences between the visual system of this and other model species. We also make it a point to highlight the aspects of mouse visual circuitry that remain opaque and that are in need of additional experimentation to enrich our understanding of how vision works on a broad scale.
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Mood, the Circadian System, and Melanopsin Retinal Ganglion Cells
Vol. 40 (2017), pp. 539–556More LessThe discovery of a third type of photoreceptors in the mammalian retina, intrinsically photosensitive retinal ganglion cells (ipRGCs), has had a revolutionary impact on chronobiology. We can now properly account for numerous non-vision-related functions of light, including its effect on the circadian system. Here, we give an overview of ipRGCs and their function as it relates specifically to mood and biological rhythms. Although circadian disruptions have been traditionally hypothesized to be the mediators of light's effects on mood, here we present an alternative model that dispenses with assumptions of causality between the two phenomena and explains mood regulation by light via another ipRGC-dependent mechanism.
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Inhibitory Plasticity: Balance, Control, and Codependence
Vol. 40 (2017), pp. 557–579More LessInhibitory neurons, although relatively few in number, exert powerful control over brain circuits. They stabilize network activity in the face of strong feedback excitation and actively engage in computations. Recent studies reveal the importance of a precise balance of excitation and inhibition in neural circuits, which often requires exquisite fine-tuning of inhibitory connections. We review inhibitory synaptic plasticity and its roles in shaping both feedforward and feedback control. We discuss the necessity of complex, codependent plasticity mechanisms to build nontrivial, functioning networks, and we end by summarizing experimental evidence of such interactions.
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Replay Comes of Age
Vol. 40 (2017), pp. 581–602More LessHippocampal place cells take part in sequenced patterns of reactivation after behavioral experience, known as replay. Since replay was first reported, nearly 20 years ago, many new results have been found, necessitating revision of the original interpretations. We review some of these results with a focus on the phenomenology of replay.
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Mechanisms of Persistent Activity in Cortical Circuits: Possible Neural Substrates for Working Memory
Vol. 40 (2017), pp. 603–627More LessA commonly observed neural correlate of working memory is firing that persists after the triggering stimulus disappears. Substantial effort has been devoted to understanding the many potential mechanisms that may underlie memory-associated persistent activity. These rely either on the intrinsic properties of individual neurons or on the connectivity within neural circuits to maintain the persistent activity. Nevertheless, it remains unclear which mechanisms are at play in the many brain areas involved in working memory. Herein, we first summarize the palette of different mechanisms that can generate persistent activity. We then discuss recent work that asks which mechanisms underlie persistent activity in different brain areas. Finally, we discuss future studies that might tackle this question further. Our goal is to bridge between the communities of researchers who study either single-neuron biophysical, or neural circuit, mechanisms that can generate the persistent activity that underlies working memory.
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Transcriptomic Perspectives on Neocortical Structure, Development, Evolution, and Disease
Vol. 40 (2017), pp. 629–652More LessThe cerebral cortex is the source of our most complex cognitive capabilities and a vulnerable target of many neurological and neuropsychiatric disorders. Transcriptomics offers a new approach to understanding the cortex at the level of its underlying genetic code, and rapid technological advances have propelled this field to the high-throughput study of the complete set of transcribed genes at increasingly fine resolution to the level of individual cells. These tools have revealed features of the genetic architecture of adult cortical areas, layers, and cell types, as well as spatiotemporal patterning during development. This has allowed a fresh look at comparative anatomy as well, illustrating surprisingly large differences between mammals while at the same time revealing conservation of some features from avians to mammals. Finally, transcriptomics is fueling progress in understanding the causes of neurodevelopmental diseases such as autism, linking genetic association studies to specific molecular pathways and affected brain regions.
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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)