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Journal articles on the topic 'Neuronal mapping'

Author: Grafiati

Published: 2 June 2025

Last updated: 31 July 2025

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1

Hurtley, S. M. "Mapping the Neuronal Map." Science Signaling 2, no. 82 (2009): ec262-ec262. http://dx.doi.org/10.1126/scisignal.282ec262.

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2

Stiefel, Klaus M., and Terrence J. Sejnowski. "Mapping Function Onto Neuronal Morphology." Journal of Neurophysiology 98, no. 1 (2007): 513–26. http://dx.doi.org/10.1152/jn.00865.2006.

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Neurons have a wide range of dendritic morphologies the functions of which are largely unknown. We used an optimization procedure to find neuronal morphological structures for two computational tasks: first, neuronal morphologies were selected for linearly summing excitatory synaptic potentials (EPSPs); second, structures were selected that distinguished the temporal order of EPSPs. The solutions resembled the morphology of real neurons. In particular the neurons optimized for linear summation electrotonically separated their synapses, as found in avian nucleus laminaris neurons, and neurons o

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3

Clarkson, Andrew N., and S. Tomas Carmichael. "Cortical excitability and post-stroke recovery." Biochemical Society Transactions 37, no. 6 (2009): 1412–14. http://dx.doi.org/10.1042/bst0371412.

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Stroke is the leading cause of adult disability. Recent studies show that the brain can engage in a limited process of neural repair after stroke: re-mapping of sensory and motor function and sprouting of new connections in peri-infarct cortex surrounding the stroke. Changes in cortical sensory and motor maps and alterations in axonal structure are dependent on patterned neuronal activity. The central cellular process in these events is alteration in neuronal response to incoming inputs – manipulations that increase neuronal firing to a given input are likely to induce changes in neuronal stru

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4

Wichterle, Hynek, David Gifford, and Esteban Mazzoni. "Mapping Neuronal Diversity One Cell at a Time." Science 341, no. 6147 (2013): 726–27. http://dx.doi.org/10.1126/science.1235884.

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5

Smith, Marie L., P. Fries, F. Gosselin, R. Goebel, and P. G. Schyns. "Inverse Mapping the Neuronal Substrates of Face Categorizations." Cerebral Cortex 19, no. 10 (2009): 2428–38. http://dx.doi.org/10.1093/cercor/bhn257.

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6

Babayan, Benedicte M., Rashmi Sarnaik, and Mariela Zirlinger. "Spotlight on Neurotechnology: Building and Mapping Neuronal Networks." Neuron 107, no. 6 (2020): 989. http://dx.doi.org/10.1016/j.neuron.2020.09.008.

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7

Okano, Hideyuki, Atsushi Miyawaki, and Kiyoto Kasai. "Brain/MINDS: brain-mapping project in Japan." Philosophical Transactions of the Royal Society B: Biological Sciences 370, no. 1668 (2015): 20140310. http://dx.doi.org/10.1098/rstb.2014.0310.

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There is an emerging interest in brain-mapping projects in countries across the world, including the USA, Europe, Australia and China. In 2014, Japan started a brain-mapping project called Brain Mapping by Integrated Neurotechnologies for Disease Studies (Brain/MINDS). Brain/MINDS aims to map the structure and function of neuronal circuits to ultimately understand the vast complexity of the human brain, and takes advantage of a unique non-human primate animal model, the common marmoset ( Callithrix jacchus ). In Brain/MINDS, the RIKEN Brain Science Institute acts as a central institute. The ob

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Zhou, Yang, Yining Liu, and Mingsha Zhang. "Neuronal Correlates of Many-To-One Sensorimotor Mapping in Lateral Intraparietal Cortex." Cerebral Cortex 30, no. 10 (2020): 5583–96. http://dx.doi.org/10.1093/cercor/bhaa145.

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Abstract Efficiently mapping sensory stimuli onto motor programs is crucial for rapidly choosing appropriate behavioral responses. While neuronal mechanisms underlying simple, one-to-one sensorimotor mapping have been extensively studied, how the brain achieves complex, many-to-one sensorimotor mapping remains unclear. Here, we recorded single neuron activity from the lateral intraparietal (LIP) cortex of monkeys trained to map multiple spatial positions of visual cue onto two opposite saccades. We found that LIP neurons’ activity was consistent with directly mapping multiple cue positions to

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Furlanis, Elisabetta, and Peter Scheiffele. "Regulation of Neuronal Differentiation, Function, and Plasticity by Alternative Splicing." Annual Review of Cell and Developmental Biology 34, no. 1 (2018): 451–69. http://dx.doi.org/10.1146/annurev-cellbio-100617-062826.

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Posttranscriptional mechanisms provide powerful means to expand the coding power of genomes. In nervous systems, alternative splicing has emerged as a fundamental mechanism not only for the diversification of protein isoforms but also for the spatiotemporal control of transcripts. Thus, alternative splicing programs play instructive roles in the development of neuronal cell type–specific properties, neuronal growth, self-recognition, synapse specification, and neuronal network function. Here we discuss the most recent genome-wide efforts on mapping RNA codes and RNA-binding proteins for neuron

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10

Papanicolaou, Andrew C. "Non-Invasive Mapping of the Neuronal Networks of Language." Brain Sciences 13, no. 10 (2023): 1457. http://dx.doi.org/10.3390/brainsci13101457.

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This review consists of three main sections. In the first, the Introduction, the main theories of the neuronal mediation of linguistic operations, derived mostly from studies of the effects of focal lesions on linguistic performance, are summarized. These models furnish the conceptual framework on which the design of subsequent functional neuroimaging investigations is based. In the second section, the methods of functional neuroimaging, especially those of functional Magnetic Resonance Imaging (fMRI) and of Magnetoencephalography (MEG), are detailed along with the specific activation tasks em

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11

Mazurkiewicz, Marta, Anvitha Kambham, Belle Pace, Daria Skwarzynska, Pravin Wagley, and Jennifer Burnsed. "Neuronal activity mapping during exploration of a novel environment." Brain Research 1776 (February 2022): 147748. http://dx.doi.org/10.1016/j.brainres.2021.147748.

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12

Amirali, Asif, Greg Tsai, Donald Weisz, Nicole SchrAder, and Ira Sanders. "Mapping of Brain Stem Neuronal Circuitry Active during Swallowing." Annals of Otology, Rhinology & Laryngology 110, no. 6 (2001): 502–13. http://dx.doi.org/10.1177/000348940111000603.

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13

MacVicar, Brian A. "REVIEW ■ : Mapping Neuronal Activity by Imaging Intrinsic Optical Signals." Neuroscientist 3, no. 6 (1997): 381–88. http://dx.doi.org/10.1177/107385849700300611.

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14

Nido, Gonzalo S., Christian Dölle, Irene Flønes, et al. "Ultradeep mapping of neuronal mitochondrial deletions in Parkinson's disease." Neurobiology of Aging 63 (March 2018): 120–27. http://dx.doi.org/10.1016/j.neurobiolaging.2017.10.024.

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15

Goldschmidt, Jürgen, Werner Zuschratter, and Henning Scheich. "High-resolution mapping of neuronal activity by thallium autometallography." NeuroImage 23, no. 2 (2004): 638–47. http://dx.doi.org/10.1016/j.neuroimage.2004.05.023.

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16

Wieland, Donald M., Karen C. Rosenspire, Gary D. Hutchins, et al. "Neuronal mapping of the heart with 6-[18F]fluorometaraminol." Journal of Medicinal Chemistry 33, no. 3 (1990): 956–64. http://dx.doi.org/10.1021/jm00165a012.

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17

O'Connor, Kelly, Krishna Sheth, and Tuan Nguyen. "Mapping Neuronal Connectivity using Laser Photostimulation and Calcium Imaging." Biophysical Journal 110, no. 3 (2016): 147a. http://dx.doi.org/10.1016/j.bpj.2015.11.831.

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18

Baron, Jean-Claude. "Mapping neuronal density in peri-infarct cortex with PET." Human Brain Mapping 38, no. 11 (2017): 5822–24. http://dx.doi.org/10.1002/hbm.23733.

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19

Van Dort, Marcian E., David L. Gildersleeve, and Donald M. Wieland. "Synthesis of 3H-labeled sympathomimetic amines for neuronal mapping." Journal of Labelled Compounds and Radiopharmaceuticals 28, no. 7 (1990): 831–40. http://dx.doi.org/10.1002/jlcr.2580280713.

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20

Xie, Ziyan, Tasuku Kayama, Nahoko Kuga, Musashi Yamakawa, and Takuya Sasaki. "Whole-brain mapping of neuronal activation by peripheral inflammation." Proceedings for Annual Meeting of The Japanese Pharmacological Society 97 (2023): 1—B—P—084. http://dx.doi.org/10.1254/jpssuppl.97.0_1-b-p-084.

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21

Berndt, Andre, Denise Cai, Adam Cohen, et al. "Current Status and Future Strategies for Advancing Functional Circuit MappingIn Vivo." Journal of Neuroscience 43, no. 45 (2023): 7587–98. http://dx.doi.org/10.1523/jneurosci.1391-23.2023.

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The human brain represents one of the most complex biological systems, containing billions of neurons interconnected through trillions of synapses. Inherent to the brain is a biochemical complexity involving ions, signaling molecules, and peptides that regulate neuronal activity and allow for short- and long-term adaptations. Large-scale and noninvasive imaging techniques, such as fMRI and EEG, have highlighted brain regions involved in specific functions and visualized connections between different brain areas. A major shortcoming, however, is the need for more information on specific cell ty

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22

Hogstrom, L. J., S. M. Guo, K. Murugadoss, and M. Bathe. "Advancing multiscale structural mapping of the brain through fluorescence imaging and analysis across length scales." Interface Focus 6, no. 1 (2016): 20150081. http://dx.doi.org/10.1098/rsfs.2015.0081.

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Brain function emerges from hierarchical neuronal structure that spans orders of magnitude in length scale, from the nanometre-scale organization of synaptic proteins to the macroscopic wiring of neuronal circuits. Because the synaptic electrochemical signal transmission that drives brain function ultimately relies on the organization of neuronal circuits, understanding brain function requires an understanding of the principles that determine hierarchical neuronal structure in living or intact organisms. Recent advances in fluorescence imaging now enable quantitative characterization of neuron

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23

Stöber, Franziska, Kathrin Baldauf, Iryna Ziabreva, et al. "Single-Cell Resolution Mapping of Neuronal Damage in Acute Focal Cerebral Ischemia Using Thallium Autometallography." Journal of Cerebral Blood Flow & Metabolism 34, no. 1 (2013): 144–52. http://dx.doi.org/10.1038/jcbfm.2013.177.

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Neuronal damage shortly after onset or after brief episodes of cerebral ischemia has remained difficult to assess with clinical and preclinical imaging techniques as well as with microscopical methods. We here show, in rodent models of middle cerebral artery occlusion (MCAO), that neuronal damage in acute focal cerebral ischemia can be mapped with single-cell resolution using thallium autometallography (TlAMG), a histochemical technique for the detection of the K+-probe thallium (Tl+) in the brain. We intravenously injected rats and mice with thallium diethyldithiocarbamate (TlDDC), a lipophil

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24

Jia, Shanshan, Dajun Xing, Zhaofei Yu, and Jian K. Liu. "Dissecting cascade computational components in spiking neural networks." PLOS Computational Biology 17, no. 11 (2021): e1009640. http://dx.doi.org/10.1371/journal.pcbi.1009640.

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Finding out the physical structure of neuronal circuits that governs neuronal responses is an important goal for brain research. With fast advances for large-scale recording techniques, identification of a neuronal circuit with multiple neurons and stages or layers becomes possible and highly demanding. Although methods for mapping the connection structure of circuits have been greatly developed in recent years, they are mostly limited to simple scenarios of a few neurons in a pairwise fashion; and dissecting dynamical circuits, particularly mapping out a complete functional circuit that conve

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25

Azzi, João C. B., Ricardo Gattass, Bruss Lima, Juliana G. M. Soares, and Mario Fiorani. "Precise visuotopic organization of the blind spot representation in primate V1." Journal of Neurophysiology 113, no. 10 (2015): 3588–99. http://dx.doi.org/10.1152/jn.00418.2014.

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The optic disk is a region of the retina consisting mainly of ganglion cell axons and blood vessels, which generates a visual scotoma known as the blind spot (BS). Information present in the surroundings of the BS can be used to complete the missing information. However, the neuronal mechanisms underlying these perceptual phenomena are poorly understood. We investigate the topography of the BS representation (BSR) in cortical area V1 of the capuchin monkey, using single and multiple electrodes. Receptive fields (RFs) of neurons inside the BSR were investigated using two distinct automatic bias

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26

Peyron, Christelle, and Thomas S. Kilduff. "Mapping the Hypocretin/Orexin Neuronal System: An Unexpectedly Productive Journey." Journal of Neuroscience 37, no. 9 (2017): 2268–72. http://dx.doi.org/10.1523/jneurosci.1708-16.2016.

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27

Cespedes-Garcia, Y., Y. Quintana-Orama, F. A. Llopiz-Morales, E. Mesa-Wong, M. Olivera-Vega, and J. A. Gonzalez-Hernandez. "P35-14 Mapping stroke-modified neuronal sensitivity to visual task." Clinical Neurophysiology 121 (October 2010): S314. http://dx.doi.org/10.1016/s1388-2457(10)61284-9.

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28

Hochman, Daryl W. "Optical Monitoring of Neuronal Activity: Brain-Mapping on a Shoestring." Brain and Cognition 42, no. 1 (2000): 56–59. http://dx.doi.org/10.1006/brcg.1999.1161.

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29

O’Neil, Darik A., Alejandro Akrouh, and Rafael Yuste. "Mapping neuronal ensembles and pattern-completion neurons through graphical models." STAR Protocols 4, no. 3 (2023): 102543. http://dx.doi.org/10.1016/j.xpro.2023.102543.

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30

Park, Joonkoo, and Jun Zhang. "Sensorimotor Locus of the Buildup Activity in Monkey Lateral Intraparietal Area Neurons." Journal of Neurophysiology 103, no. 5 (2010): 2664–74. http://dx.doi.org/10.1152/jn.00733.2009.

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A study in 2002 using a random-dot motion-discrimination paradigm showed that an information accumulation model with a threshold-crossing mechanism can account for activity of the lateral intraparietal area (LIP) neurons. Here, mathematical techniques were applied to the same dataset to quantitatively address the sensory versus motor representation of the neuronal activity during the time course of a trial. A technique based on Signal Detection Theory was applied to provide indices to quantify how neuronal firing activity is responsible for encoding the stimulus or selecting the response at th

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31

Martins, Nuno R. B., Wolfram Erlhagen, and Robert A. Freitas, Jr. "Human Connectome Mapping and Monitoring Using Neuronanorobots." Journal of Ethics and Emerging Technologies 26, no. 1 (2016): 1–25. http://dx.doi.org/10.55613/jeet.v26i1.49.

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Neuronanorobotics is the application of medical nanorobots to the human brain. This paper proposes three specific classes of neuronanorobots, named endoneurobots, gliabots and synaptobots, which together can non-destructively map and monitor the structural changes occurring on the 86 x 109 neurons and the 2.42 x 1014 synapses in the human brain, while also recording the synaptic-processed 4.31 x 1015 spikes/sec carrying electrical functional information processed in the neuronal and synaptic network.

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32

Koyama, Shinsuke. "On the Relation Between Encoding and Decoding of Neuronal Spikes." Neural Computation 24, no. 6 (2012): 1408–25. http://dx.doi.org/10.1162/neco_a_00279.

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Neural coding is a field of study that concerns how sensory information is represented in the brain by networks of neurons. The link between external stimulus and neural response can be studied from two parallel points of view. The first, neural encoding, refers to the mapping from stimulus to response. It focuses primarily on understanding how neurons respond to a wide variety of stimuli and constructing models that accurately describe the stimulus-response relationship. Neural decoding refers to the reverse mapping, from response to stimulus, where the challenge is to reconstruct a stimulus

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33

VOINEA, Alina–Ioana, Mirona Letitia DOBRI, Codrina MORARU, Petronela NECHITA, and Anamaria CIUBARA. "A Tale of Two Frontal Lobes. Clinical Perspectives of Cortical Interconnectivity." BRAIN. Broad Research in Artificial Intelligence and Neuroscience 11, no. 3 Sup.1 (2020): 127–36. https://doi.org/10.18662/brain/11.3Sup1/128.

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Even through centuries passed, while neurosciences weremistaken only for phrenology, and neuronal mapping did not exist as aself-sustained science, structural changes of the brain were associated, atvarious degrees, with reoccurring activities or behavioural patterns of thepatient. An extraordinary neuroplasticity was therefore described, meantto complete the cerebral network, which sustained superior cognitivefunctioning and played an essential role in adapting to the environment.Most of this web of electrical impulses has its nodes inside the frontalsystem, in such a way that no one lobe can

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34

Dmitriev, Ilia. "The mapping of human electroencephalogram correlation dimension." Izvestiya VUZ. Applied Nonlinear Dynamics 6, no. 6 (1998): 39–49. http://dx.doi.org/10.18500/0869-6632-1998-6-6-39-49.

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The paper studies а spatial distribution of correlation dimension extracted from human electroencephalogram recordings during some stages of brain activity. This method allows us to describe a spatiotemporal pattern of brain activity in terms of dimension of the system of coupled neuronal macrooscillators responsible for the electroencephalogram signal. The influence of elementary mental and physiological loads on correlation dimension map which corresponds to alert relaxation state is analyzed. The method is applied to the investigation of one subject’s altered states of consciousness.

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35

Shriki, Oren, David Hansel, and Haim Sompolinsky. "Rate Models for Conductance-Based Cortical Neuronal Networks." Neural Computation 15, no. 8 (2003): 1809–41. http://dx.doi.org/10.1162/08997660360675053.

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Population rate models provide powerful tools for investigating the principles that underlie the cooperative function of large neuronal systems. However, biophysical interpretations of these models have been ambiguous. Hence, their applicability to real neuronal systems and their experimental validation have been severely limited. In this work, we show that conductance-based models of large cortical neuronal networks can be described by simplified rate models, provided that the network state does not possess a high degree of synchrony. We first derive a precise mapping between the parameters o

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36

Schubert, Marc, Wolfgang Wick, Thomas Kuner, Frank Winkler, and Varun Venkataramani. "CNSC-33. TRANSCRIPTOMIC NEURON-TUMOR INTERACTION MAPPING OF EXTRACRANIAL TUMORS AND BRAIN METASTASES." Neuro-Oncology 24, Supplement_7 (2022): vii29. http://dx.doi.org/10.1093/neuonc/noac209.114.

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Abstract Ongoing efforts in the field of Cancer Neuroscience seek to improve the understanding of neuron-cancer interactions and their effects on tumor progression. In glioma, synaptic neuronal input to tumor cells drives tumor progression and invasion. Even though neuron-cancer interactions have been described in brain metastases and extracranial tumors as well, the mechanisms of action between the nervous system and tumor cells are incompletely understood. Systematic transcriptomic analyses to detect overarching principles of neuron-tumor interaction have been lacking so far. Here, we perfor

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37

Gao, Peiran, Ben V. Benjamin, and Kwabena Boahen. "Dynamical System Guided Mapping of Quantitative Neuronal Models Onto Neuromorphic Hardware." IEEE Transactions on Circuits and Systems I: Regular Papers 59, no. 10 (2012): 2383–94. http://dx.doi.org/10.1109/tcsi.2012.2188956.

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38

Bertrand, Paul P., and Xiaochun Bian. "FROM ‘MACRO’ TO ‘MICRO’: MAPPING THE NEURONAL CIRCUITS OF THE INTESTINE." Clinical and Experimental Pharmacology and Physiology 35, no. 7 (2008): 715–16. http://dx.doi.org/10.1111/j.1440-1681.2008.04974.x.

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39

Carvalho, Joana, Azzurra Invernizzi, Khazar Ahmadi, Michael B. Hoffmann, Remco J. Renken, and Frans W. Cornelissen. "Micro-probing enables fine-grained mapping of neuronal populations using fMRI." NeuroImage 209 (April 2020): 116423. http://dx.doi.org/10.1016/j.neuroimage.2019.116423.

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40

Ghezzi, Alfredo, Yazan M. Al-Hasan, Harish R. Krishnan, Yan Wang, and Nigel S. Atkinson. "Functional Mapping of the Neuronal Substrates for Drug Tolerance in Drosophila." Behavior Genetics 43, no. 3 (2013): 227–40. http://dx.doi.org/10.1007/s10519-013-9583-0.

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41

Orr-Urtreger, Avi, Michael F. Seldin, Antonio Baldini та Arthur L. Beaudet. "Cloning and mapping of the mouse α7-neuronal nicotinic acetylcholine receptor". Genomics 26, № 2 (1995): 399–402. http://dx.doi.org/10.1016/0888-7543(95)80228-e.

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42

Channell, Paul, Gennady Cymbalyuk, and Andrey Shilnikov. "Applications of the Poincaré mapping technique to analysis of neuronal dynamics." Neurocomputing 70, no. 10-12 (2007): 2107–11. http://dx.doi.org/10.1016/j.neucom.2006.10.091.

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43

Mayo, J. P., A. DiTomasso, M. Sommer, and M. A. Smith. "An improved method for mapping neuronal receptive fields in prefrontal cortex." Journal of Vision 12, no. 9 (2012): 81. http://dx.doi.org/10.1167/12.9.81.

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44

Zhao, Chen, Ying Du, and Jan Deussing. "A SPLITCRE-LOXP DEPENDENT SYSTEM FOR MAPPING CRH-RELATED NEURONAL NETWORKS." IBRO Neuroscience Reports 15 (October 2023): S772. http://dx.doi.org/10.1016/j.ibneur.2023.08.1584.

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45

Villa, Giulia, Daniel Delev, and Dieter Henrik Heiland. "Mapping myeloid cell function: Spatial diversity in tumor and neuronal microenvironment." Cancer Cell 42, no. 6 (2024): 934–36. http://dx.doi.org/10.1016/j.ccell.2024.05.018.

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46

Zheng, Lvpiao, Zhouyan Feng, Yifan Hu, et al. "Adjust Neuronal Reactions to Pulses of High-Frequency Stimulation with Designed Inter-Pulse-Intervals in Rat Hippocampus In Vivo." Brain Sciences 11, no. 4 (2021): 509. http://dx.doi.org/10.3390/brainsci11040509.

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Sequences of electrical pulses have been applied in the brain to treat certain disorders. In recent years, altering inter-pulse-interval (IPI) regularly or irregularly in real time has emerged as a promising way to modulate the stimulation effects. However, algorithms to design IPI sequences are lacking. This study proposed a novel strategy to design pulse sequences with varying IPI based on immediate neuronal reactions. Firstly, to establish the correlationship between the neuronal reactions with varying IPIs, high-frequency stimulations with varying IPI in the range of 5–10 ms were applied a

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47

Sardar, Debosmita, Brittney Lozzi, Junsung Woo, et al. "Mapping Astrocyte Transcriptional Signatures in Response to Neuroactive Compounds." International Journal of Molecular Sciences 22, no. 8 (2021): 3975. http://dx.doi.org/10.3390/ijms22083975.

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Astrocytes play central roles in normal brain function and are critical components of synaptic networks that oversee behavioral outputs. Despite their close affiliation with neurons, how neuronal-derived signals influence astrocyte function at the gene expression level remains poorly characterized, largely due to difficulties associated with dissecting neuron- versus astrocyte-specific effects. Here, we use an in vitro system of stem cell-derived astrocytes to identify gene expression profiles in astrocytes that are influenced by neurons and regulate astrocyte development. Furthermore, we show

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48

Zhang, Dongyang, James M. Johnston, Michael D. Fox, et al. "Preoperative Sensorimotor Mapping in Brain Tumor Patients Using Spontaneous Fluctuations in Neuronal Activity Imaged With Functional Magnetic Resonance Imaging: Initial Experience." Operative Neurosurgery 65, suppl_6 (2009): ons226—ons236. http://dx.doi.org/10.1227/01.neu.0000350868.95634.ca.

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Abstract Objective: To describe initial experience with resting-state correlation mapping as a potential aid for presurgical planning of brain tumor resection. Methods: Resting-state blood oxygenation-dependent functional magnetic resonance imaging (fMRI) scans were acquired in 17 healthy young adults and 4 patients with brain tumors invading sensorimotor cortex. Conventional fMRI motor mapping (finger-tapping protocol) was also performed in the patients. Intraoperatively, motor hand area was mapped using cortical stimulation. Results: Robust and consistent delineation of sensorimotor cortex w

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49

Onozuka, M., M. Fujita, K. Watanabe, et al. "Mapping Brain Region Activity during Chewing: A Functional Magnetic Resonance Imaging Study." Journal of Dental Research 81, no. 11 (2002): 743–46. http://dx.doi.org/10.1177/0810743.

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Mastication has been suggested to increase neuronal activities in various regions of the human brain. However, because of technical difficulties, the fine anatomical and physiological regions linked to mastication have not been fully elucidated. Using functional magnetic resonance imaging during cycles of rhythmic gum-chewing and no chewing, we therefore examined the interaction between chewing and brain regional activity in 17 subjects (aged 20-31 years). In all subjects, chewing resulted in a bilateral increase in blood oxygenation level-dependent (BOLD) signals in the sensorimotor cortex, s

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Wang, Hao, Qingyuan Zhu, Lufeng Ding, et al. "Scalable volumetric imaging for ultrahigh-speed brain mapping at synaptic resolution." National Science Review 6, no. 5 (2019): 982–92. http://dx.doi.org/10.1093/nsr/nwz053.

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Abstract The speed of high-resolution optical imaging has been a rate-limiting factor for meso-scale mapping of brain structures and functional circuits, which is of fundamental importance for neuroscience research. Here, we describe a new microscopy method of Volumetric Imaging with Synchronized on-the-fly-scan and Readout (VISoR) for high-throughput, high-quality brain mapping. Combining synchronized scanning beam illumination and oblique imaging over cleared tissue sections in smooth motion, the VISoR system effectively eliminates motion blur to obtain undistorted images. By continuously im

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