Nature Neuroscience presents this animation, which introduces the molecular, cellular and physiological mechanisms associated with Alzheimer's disease and highlights some of the most recent advances in our understanding of the onset and progression of this devastating neurological condition.
It is 200 years since Parkinson's disease was first described. This Outlook charts the progress of research in an engaging timeline and shows how our understanding of Parkinson's motor and non-motor symptoms has evolved. It also reveals the exciting new applications of smartphones in monitoring the disease.
Focus on human brain mapping p297 doi:10.1038/nn.4522 We present a special issue highlighting considerations and recent developments in noninvasive techniques that improve our understanding of neural measurements in humans, bridging the gap between human and animal research in neuroscience.
Fostering reproducible fMRI research p298 doi:10.1038/nn.4521 The validity of conclusions drawn from functional MRI research has been questioned for some time now. Nature Neuroscience and Nature Communications are committed to working with neuroimaging researchers to improve the robustness and reproducibility of their work.
Best practices in data analysis and sharing in neuroimaging using MRI pp299 - 303 Thomas E Nichols, Samir Das, Simon B Eickhoff, Alan C Evans, Tristan Glatard et al. doi:10.1038/nn.4500 Responding to widespread concerns about reproducibility, the Organization for Human Brain Mapping created a working group to identify best practices in data analysis, results reporting and data sharing to promote open and reproducible research in neuroimaging. We describe the challenges of open research and the barriers the field faces.
Computational approaches to fMRI analysis pp304 - 313 Jonathan D Cohen, Nathaniel Daw, Barbara Engelhardt, Uri Hasson, Kai Li et al. doi:10.1038/nn.4499 A revolution is underway in cognitive neuroscience, where tools and techniques from computer science and the tech industry are helping to extract more meaningful cognitive signals from noisy and increasingly large fMRI datasets. In this paper, the authors review the cutting edge of such computational analyses and discuss future opportunities and challenges.
Studying neuroanatomy using MRI pp314 - 326 Jason P Lerch, Andre J W van der Kouwe, Armin Raznahan, Tomas Paus, Heidi Johansen-Berg et al. doi:10.1038/nn.4501 The study of neuroanatomy using MRI enables key insights into how our brains function, are shaped by genes and environment, and how they change with development, aging and disease. The authors provide an overview of the methods for measuring the brain and also describe key artifacts and confounds
Magnetoencephalography for brain electrophysiology and imaging pp327 - 339 Sylvain Baillet doi:10.1038/nn.4504 Magnetoencephalography (MEG) tracks the millisecond electrical activity of the brain noninvasively. This review emphasizes MEG's unique assets, especially in terms of imaging and resolving the mechanisms underlying the apparent complexity of polyrhythmic brain dynamics. It also identifies practical challenges and clarifies misconceptions about the technique.
Dynamic models of large-scale brain activity pp340 - 352 Michael Breakspear doi:10.1038/nn.4497 Cognitive activity requires the collective behavior of cortical, thalamic and spinal neurons across large-scale systems of the CNS. This paper provides an illustrated introduction to dynamic models of large-scale brain activity, from the tenets of the underlying theory to challenges, controversies and recent breakthroughs.
Network neuroscience pp353 - 364 Danielle S Bassett and Olaf Sporns doi:10.1038/nn.4502 Network neuroscience tackles the challenge of discovering the principles underlying complex brain function and cognition from an explicitly integrative perspective. Here, the authors discuss emerging trends in network neuroscience, charting a path towards a better understanding of the brain that bridges computation, theory and experiment across spatial scales and species.
Building better biomarkers: brain models in translational neuroimaging pp365 - 377 Choong-Wan Woo, Luke J Chang, Martin A Lindquist and Tor D Wager doi:10.1038/nn.4478 Neuroimaging and pattern recognition are being combined to develop brain models of clinical disorders. Such models yield biomarkers that can be shared and validated across populations, narrowing the gap between neuroscience and clinical applications. The authors summarize 475 translational modeling studies, highlighting challenges and ways to improve biomarker development.
Setting the mood for love pp379 - 380 Gül Dölen doi:10.1038/nn.4514 McHenry and colleagues delineate a neural circuit controlling female sexual behavior. These experiments shed light on how the brain optimizes reproductive behavior to coincide with phases of peak fertility.
Rodent see, rodent fear pp381 - 382 Yoav Kfir and Rony Paz doi:10.1038/nn.4512 To learn from others' experience, one must link environmental conditions with social cues. A specific amygdala circuit underlies social learning of fear, and targeted activation normalizes behavior in a rodent model of autism.
Glucose utilization: still in the synapse pp382 - 384 A Jon Stoessl doi:10.1038/nn.4513 Many people still associate brain glucose metabolism with neurons. A new report shows that stimulation of astrocytic glutamate uptake increases glucose utilization, suggesting that astrocytes play a major role in the glucose uptake signal. However, this still reflects synaptic activity.
Hypothalamic CRFR1 is essential for HPA axis regulation following chronic stress pp385 - 388 Assaf Ramot, Zhiying Jiang, Jin-Bin Tian, Tali Nahum, Yael Kuperman et al. doi:10.1038/nn.4491 Dysfunction of the neuroendocrine HPA axis is associated with a variety of physiological and psychological pathologies. The authors show that corticotropin-releasing factor type 1 receptors within the hypothalamic paraventricular nucleus are a key central component of HPA axis regulation that prepares the organism for chronic exposure to stressful stimuli.
An inhibitory pull-push circuit in frontal cortex pp389 - 392 Pablo Garcia-Junco-Clemente, Taruna Ikrar, Elaine Tring, Xiangmin Xu, Dario L Ringach et al. doi:10.1038/nn.4483 Using large-network calcium imaging in alert mouse frontal cortex, the authors identify a significant covariance of responses of VIP interneurons and pyramidal cells. Optogenetic interrogation of this brain region revealed a pull-push inhibitory circuit driven by neuromodulation of VIP interneurons that contrasts with canonical feedforward push-pull excitation.
[18F]FDG PET signal is driven by astroglial glutamate transport pp393 - 395 Eduardo R Zimmer, Maxime J Parent, Debora G Souza, Antoine Leuzy, Clotilde Lecrux et al. doi:10.1038/nn.4492 The identity of the cell types contributing to the [18F]FDG positron emission tomography signal remain highly controversial. In this study, the authors demonstrate that activating glutamate astrocytic transport increases brain [18F]FDG uptake. These findings indicate that astrocytes may also impact [18F]FDG positron emission tomography signal.
Shimadzu's LIGHTNIRS expands opportunities for brain imaging research by providing high-quality Blood Oxygen Level Dependent signals of the cerebral cortex in a compact, wearable design. The portability of LIGHTNIRS allows visualizing brain function activity in real time in a more natural state than other methods.
Identification of diverse astrocyte populations and their malignant analogs pp396 - 405 Chia-Ching John Lin, Kwanha Yu, Asante Hatcher, Teng-Wei Huang, Hyun Kyoung Lee et al. doi:10.1038/nn.4493 The nature of astrocyte diversity in the adult brain has remained poorly defined. The authors identify five astrocyte subpopulations in the brain that exhibit extensive molecular and functional diversity. They uncover correlative populations in malignant glioma, providing insight into how diverse astrocyte populations contribute to synaptogenesis, tumor pathophysiology and neurological disease.
Pericyte degeneration leads to neurovascular uncoupling and limits oxygen supply to brain pp406 - 416 Kassandra Kisler, Amy R Nelson, Sanket V Rege, Anita Ramanathan, Yaoming Wang et al. doi:10.1038/nn.4489 The role of pericytes in the regulation of cerebral blood flow (CBF) and neurovascular coupling remains unclear. Using loss-of-function pericyte-deficient mice, the authors report that pericyte degeneration reduces CBF responses to neuronal stimuli and oxygen supply to the brain, leading to metabolic stress, neuronal dysfunction and neurodegeneration.
REM sleep selectively prunes and maintains new synapses in development and learning pp427 - 437 Wei Li, Lei Ma, Guang Yang and Wen-Biao Gan doi:10.1038/nn.4479 The function of rapid eye movement (REM) sleep remains unclear. By examining how REM sleep affects synapses in the mouse cortex, the authors show that REM sleep is fundamental to brain development, learning and memory consolidation by selectively pruning and maintaining newly formed synapses via dendritic calcium spike-dependent mechanisms.
Circuit specificity in the inhibitory architecture of the VTA regulates cocaine-induced behavior pp438 - 448 Nicholas J Edwards, Hugo A Tejeda, Marco Pignatelli, Shiliang Zhang, Ross A McDevitt et al. doi:10.1038/nn.4482 Inputs to midbrain dopamine neurons control rewarding and drug-related behaviors. The authors found that nucleus accumbens inputs and local GABA neurons inhibit dopamine neurons through distinct populations of GABA receptors. Furthermore, genetic deletion of GABAB receptors from dopamine neurons selectively increased behavioral sensitivity to cocaine.
Hormonal gain control of a medial preoptic area social reward circuit pp449 - 458 Jenna A McHenry, James M Otis, Mark A Rossi, J Elliott Robinson, Oksana Kosyk et al. doi:10.1038/nn.4487 Social behaviors require neural circuits to process social cues and orchestrate motivational states. This study identifies a subpopulation of hypothalamic neurons expressing neurotensin that are engaged by social and hormonal signals. These neurons project to midbrain dopaminergic reward systems to promote and reinforce social and motivated behavior in a hormone-sensitive manner.
An intra-amygdala circuit specifically regulates social fear learning pp459 - 469 Robert C Twining, Jaime E Vantrease, Skyelar Love, Mallika Padival and J Amiel Rosenkranz doi:10.1038/nn.4481 Effective social behavior requires comprehension of social cues and use of those cues to guide behavior. This study uncovers an amygdala circuit that is necessary for socially driven valuation of environmental cues. The strength of this circuit correlates with social learning, and augmentation of this circuit enhances abnormal social learning.
Overlearning hyperstabilizes a skill by rapidly making neurochemical processing inhibitory-dominant pp470 - 475 Kazuhisa Shibata, Yuka Sasaki, Ji Won Bang, Edward G Walsh, Maro G Machizawa et al. doi:10.1038/nn.4490 Using magnetic resonance spectroscopy, Shibata et al. show that continuous training conducted after performance improvement has been maximized hyperstabilizes the skill learned and protects it from subsequent new learning by drastically changing early visual areas from excitatory (glutamate)-dominant to inhibitory (GABA)-dominant neurochemical environments.
Neuronal activity modifies the chromatin accessibility landscape in the adult brain pp476 - 483 Yijing Su, Jaehoon Shin, Chun Zhong, Sabrina Wang, Prith Roychowdhury et al. doi:10.1038/nn.4494 Su et al. investigated the chromatin accessibility status of neurons in the adult mouse dentate gyrus at different timepoints after activation at the genome-wide level. Their study provides a potential mechanism by which neuronal activity may reshape the epigenetic landscape, thereby dynamically changing transcriptome and neuronal properties over time.
A molecular census of arcuate hypothalamus and median eminence cell types pp484 - 496 John N Campbell, Evan Z Macosko, Henning Fenselau, Tune H Pers, Anna Lyubetskaya et al. doi:10.1038/nn.4495 The hypothalamic arcuate-median eminence (Arc-ME) complex is rich with functionally distinct cell types, a fraction of which have been characterized. The authors profile 20,921 individual cells by single-cell RNA-seq, identifying 50 Arc-ME cell types and their markers, determining each's response to energy status and implicating two neuron populations in the genetic control of obesity.
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