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@@ -111579,23 +111579,6 @@ CONCLUSIONS: Centrifugal axons in the macaque retina are part of the system of a
nlmuniqueid = {8102140}
}
@article{Waters2019,
title = {Biological variation in the sizes, shapes and locations of visual cortical areas in the mouse.},
author = {Waters, Jack and Lee, Eric and Gaudreault, Nathalie and Griffin, Fiona and Lecoq, Jerome and Slaughterbeck, Cliff and Sullivan, David and Farrell, Colin and Perkins, Jed and Reid, David and Feng, David and Graddis, Nile and Garrett, Marina and Li, Yang and Long, Fuhui and Mochizuki, Chris and Roll, Kate and Zhuang, Jun and Thompson, Carol},
journal = {PLoS One},
volume = {14},
number = {5},
year = {2019},
pages = {e0213924},
abstract = {Visual cortex is organized into discrete sub-regions or areas that are arranged into a hierarchy and serves different functions in the processing of visual information. In retinotopic maps of mouse cortex, there appear to be substantial mouse-to-mouse differences in visual area location, size and shape. Here we quantify the biological variation in the size, shape and locations of 11 visual areas in the mouse, after separating biological variation and measurement noise. We find that there is biological variation in the locations and sizes of visual areas.},
pmid = {31042712},
doi = {10.1371/journal.pone.0213924},
pii = {PONE-D-18-29482},
pmc = {PMC6493719},
eprint = {https://www.ncbi.nlm.nih.gov/pubmed/31042712},
url = {},
nlmuniqueid = {101285081}
}
@article{Ghanbari2019,
title = {Cortex-wide neural interfacing via transparent polymer skulls.},
@@ -113149,3 +113132,483 @@ CONCLUSIONS: Centrifugal axons in the macaque retina are part of the system of a
nlmuniqueid = {0410462}
}
@article{Patel2015,
title = {Automated quantification of neuronal networks and single-cell calcium dynamics using calcium imaging.},
author = {Patel, Tapan P and Man, Karen and Firestein, Bonnie L and Meaney, David F},
journal = {J Neurosci Methods},
volume = {243},
year = {2015},
month = {Mar},
pages = {26-38},
abstract = {Recent advances in genetically engineered calcium and membrane potential indicators provide the potential to estimate the activation dynamics of individual neurons within larger, mesoscale networks (100s-1000+neurons). However, a fully integrated automated workflow for the analysis and visualization of neural microcircuits from high speed fluorescence imaging data is lacking.},
keywords = {Calcium imaging; Event detection; FluoroSNNAP; Functional connectivity; Neuronal phenotype; Synchrony; Access to Information; Algorithms; Animals; Calcium; Cells, Cultured; Hippocampus; Humans; Mice, Transgenic; Mutation; Neocortex; Neural Pathways; Neurons; Optical Imaging; Pattern Recognition, Automated; Periodicity; Rats, Sprague-Dawley; Single-Cell Analysis; Software; Wavelet Analysis; tau Proteins; },
pubmed = {25629800},
pii = {S0165-0270(15)00021-7},
doi = {10.1016/j.jneumeth.2015.01.020},
pmc = {PMC5553047},
mid = {NIHMS886628},
url = {papers/Patel_JNeurosciMethods2015-25629800.pdf},
nlmuniqueid = {7905558}
}
@article{Pnevmatikakis2016,
title = {Simultaneous Denoising, Deconvolution, and Demixing of Calcium Imaging Data.},
author = {Pnevmatikakis, Eftychios A and Soudry, Daniel and Gao, Yuanjun and Machado, Timothy A and Merel, Josh and Pfau, David and Reardon, Thomas and Mu, Yu and Lacefield, Clay and Yang, Weijian and Ahrens, Misha and Bruno, Randy and Jessell, Thomas M and Peterka, Darcy S and Yuste, Rafael and Paninski, Liam},
journal = {Neuron},
volume = {89},
number = {2},
year = {2016},
month = {Jan},
pages = {285-99},
abstract = {We present a modular approach for analyzing calcium imaging recordings of large neuronal ensembles. Our goal is to simultaneously identify the locations of the neurons, demix spatially overlapping components, and denoise and deconvolve the spiking activity from the slow dynamics of the calcium indicator. Our approach relies on a constrained nonnegative matrix factorization that expresses the spatiotemporal fluorescence activity as the product of a spatial matrix that encodes the spatial footprint of each neuron in the optical field and a temporal matrix that characterizes the calcium concentration of each neuron over time. This framework is combined with a novel constrained deconvolution approach that extracts estimates of neural activity from fluorescence traces, to create a spatiotemporal processing algorithm that requires minimal parameter tuning. We demonstrate the general applicability of our method by applying it to in vitro and in vivo multi-neuronal imaging data, whole-brain light-sheet imaging data, and dendritic imaging data. },
keywords = {Action Potentials; Animals; Calcium; Dendrites; Fluorescent Dyes; Mice; Mice, Inbred C57BL; Microscopy, Fluorescence; Neurons; Statistics as Topic; },
pubmed = {26774160},
pii = {S0896-6273(15)01084-3},
doi = {10.1016/j.neuron.2015.11.037},
pmc = {PMC4881387},
mid = {NIHMS778164},
url = {papers/Pnevmatikakis_Neuron2016-26774160.pdf},
nlmuniqueid = {8809320}
}
@article{Glasser2016,
title = {A multi-modal parcellation of human cerebral cortex.},
author = {Glasser, Matthew F and Coalson, Timothy S and Robinson, Emma C and Hacker, Carl D and Harwell, John and Yacoub, Essa and Ugurbil, Kamil and Andersson, Jesper and Beckmann, Christian F and Jenkinson, Mark and Smith, Stephen M and Van Essen, David C},
journal = {Nature},
volume = {536},
number = {7615},
year = {2016},
month = {08},
pages = {171-178},
abstract = {Understanding the amazingly complex human cerebral cortex requires a map (or parcellation) of its major subdivisions, known as cortical areas. Making an accurate areal map has been a century-old objective in neuroscience. Using multi-modal magnetic resonance images from the Human Connectome Project (HCP) and an objective semi-automated neuroanatomical approach, we delineated 180 areas per hemisphere bounded by sharp changes in cortical architecture, function, connectivity, and/or topography in a precisely aligned group average of 210 healthy young adults. We characterized 97 new areas and 83 areas previously reported using post-mortem microscopy or other specialized study-specific approaches. To enable automated delineation and identification of these areas in new HCP subjects and in future studies, we trained a machine-learning classifier to recognize the multi-modal 'fingerprint' of each cortical area. This classifier detected the presence of 96.6% of the cortical areas in new subjects, replicated the group parcellation, and could correctly locate areas in individuals with atypical parcellations. The freely available parcellation and classifier will enable substantially improved neuroanatomical precision for studies of the structural and functional organization of human cerebral cortex and its variation across individuals and in development, aging, and disease.},
keywords = {Adult; Cerebral Cortex; Connectome; Female; Healthy Volunteers; Humans; Machine Learning; Male; Models, Anatomic; Multimodal Imaging; Neuroanatomy; Neuroimaging; Probability; Reproducibility of Results; Young Adult; },
pubmed = {27437579},
doi = {10.1038/nature18933},
pmc = {PMC4990127},
mid = {EMS68870},
url = {papers/Glasser_Nature2016-27437579.pdf},
nlmuniqueid = {0410462}
}
@article{Wiltschko2015,
title = {Mapping Sub-Second Structure in Mouse Behavior.},
author = {Wiltschko, Alexander B and Johnson, Matthew J and Iurilli, Giuliano and Peterson, Ralph E and Katon, Jesse M and Pashkovski, Stan L and Abraira, Victoria E and Adams, Ryan P and Datta, Sandeep Robert},
journal = {Neuron},
volume = {88},
number = {6},
year = {2015},
month = {Dec},
pages = {1121-1135},
abstract = {Complex animal behaviors are likely built from simpler modules, but their systematic identification in mammals remains a significant challenge. Here we use depth imaging to show that 3D mouse pose dynamics are structured at the sub-second timescale. Computational modeling of these fast dynamics effectively describes mouse behavior as a series of reused and stereotyped modules with defined transition probabilities. We demonstrate this combined 3D imaging and machine learning method can be used to unmask potential strategies employed by the brain to adapt to the environment, to capture both predicted and previously hidden phenotypes caused by genetic or neural manipulations, and to systematically expose the global structure of behavior within an experiment. This work reveals that mouse body language is built from identifiable components and is organized in a predictable fashion; deciphering this language establishes an objective framework for characterizing the influence of environmental cues, genes and neural activity on behavior.},
keywords = {Animals; Behavior, Animal; Computer Simulation; Imaging, Three-Dimensional; Kinesics; Machine Learning; Male; Mice; Mice, Inbred C57BL; Mice, Transgenic; Optogenetics; },
pubmed = {26687221},
pii = {S0896-6273(15)01037-5},
doi = {10.1016/j.neuron.2015.11.031},
pmc = {PMC4708087},
mid = {NIHMS745523},
url = {papers/Wiltschko_Neuron2016-26687221.pdf},
nlmuniqueid = {8809320}
}
@article{Maccione2014,
title = {Following the ontogeny of retinal waves: pan-retinal recordings of population dynamics in the neonatal mouse.},
author = {Maccione, Alessandro and Hennig, Matthias H and Gandolfo, Mauro and Muthmann, Oliver and van Coppenhagen, James and Eglen, Stephen J and Berdondini, Luca and Sernagor, Evelyne},
journal = {J Physiol},
volume = {592},
number = {7},
year = {2014},
month = {Apr},
pages = {1545-63},
abstract = {The immature retina generates spontaneous waves of spiking activity that sweep across the ganglion cell layer during a limited period of development before the onset of visual experience. The spatiotemporal patterns encoded in the waves are believed to be instructive for the wiring of functional connections throughout the visual system. However, the ontogeny of retinal waves is still poorly documented as a result of the relatively low resolution of conventional recording techniques. Here, we characterize the spatiotemporal features of mouse retinal waves from birth until eye opening in unprecedented detail using a large-scale, dense, 4096-channel multielectrode array that allowed us to record from the entire neonatal retina at near cellular resolution. We found that early cholinergic waves propagate with random trajectories over large areas with low ganglion cell recruitment. They become slower, smaller and denser when GABAA signalling matures, as occurs beyond postnatal day (P) 7. Glutamatergic influences dominate from P10, coinciding with profound changes in activity dynamics. At this time, waves cease to be random and begin to show repetitive trajectories confined to a few localized hotspots. These hotspots gradually tile the retina with time, and disappear after eye opening. Our observations demonstrate that retinal waves undergo major spatiotemporal changes during ontogeny. Our results support the hypotheses that cholinergic waves guide the refinement of retinal targets and that glutamatergic waves may also support the wiring of retinal receptive fields. },
keywords = {Action Potentials; Age Factors; Animals; Animals, Newborn; Cholinergic Neurons; GABAergic Neurons; Glutamic Acid; Light Signal Transduction; Mice, Inbred C57BL; Receptors, GABA-A; Retina; Retinal Neurons; Time Factors; Vision, Ocular; },
pubmed = {24366261},
pii = {jphysiol.2013.262840},
doi = {10.1113/jphysiol.2013.262840},
pmc = {PMC3979611},
url = {papers/Maccione_JPhysiol2014-24366261.pdf},
nlmuniqueid = {0266262}
}
@article{Muller2018,
title = {Cortical travelling waves: mechanisms and computational principles.},
author = {Muller, Lyle and Chavane, Frédéric and Reynolds, John and Sejnowski, Terrence J},
journal = {Nat Rev Neurosci},
volume = {19},
number = {5},
year = {2018},
month = {05},
pages = {255-268},
abstract = {Multichannel recording technologies have revealed travelling waves of neural activity in multiple sensory, motor and cognitive systems. These waves can be spontaneously generated by recurrent circuits or evoked by external stimuli. They travel along brain networks at multiple scales, transiently modulating spiking and excitability as they pass. Here, we review recent experimental findings that have found evidence for travelling waves at single-area (mesoscopic) and whole-brain (macroscopic) scales. We place these findings in the context of the current theoretical understanding of wave generation and propagation in recurrent networks. During the large low-frequency rhythms of sleep or the relatively desynchronized state of the awake cortex, travelling waves may serve a variety of functions, from long-term memory consolidation to processing of dynamic visual stimuli. We explore new avenues for experimental and computational understanding of the role of spatiotemporal activity patterns in the cortex.},
keywords = {Animals; Brain Waves; Cerebral Cortex; Computer Simulation; Electroencephalography; Humans; Models, Neurological; Neural Pathways; },
pubmed = {29563572},
pii = {nrn.2018.20},
doi = {10.1038/nrn.2018.20},
pmc = {PMC5933075},
mid = {NIHMS961180},
url = {papers/Muller_NatRevNeurosci2019-29563572.pdf},
nlmuniqueid = {100962781}
}
@article{Huang2021,
title = {Relationship between simultaneously recorded spiking activity and fluorescence signal in GCaMP6 transgenic mice.},
author = {Huang, Lawrence and Ledochowitsch, Peter and Knoblich, Ulf and Lecoq, Jérôme and Murphy, Gabe J and Reid, R Clay and de Vries, Saskia Ej and Koch, Christof and Zeng, Hongkui and Buice, Michael A and Waters, Jack and Li, Lu},
journal = {Elife},
volume = {10},
year = {2021},
month = {03},
pages = {},
abstract = {Fluorescent calcium indicators are often used to investigate neural dynamics, but the relationship between fluorescence and action potentials (APs) remains unclear. Most APs can be detected when the soma almost fills the microscope's field of view, but calcium indicators are used to image populations of neurons, necessitating a large field of view, generating fewer photons per neuron, and compromising AP detection. Here, we characterized the AP-fluorescence transfer function in vivo for 48 layer 2/3 pyramidal neurons in primary visual cortex, with simultaneous calcium imaging and cell-attached recordings from transgenic mice expressing GCaMP6s or GCaMP6f. While most APs were detected under optimal conditions, under conditions typical of population imaging studies, only a minority of 1 AP and 2 AP events were detected (often <10% and ~20-30%, respectively), emphasizing the limits of AP detection under more realistic imaging conditions.},
keywords = {action potential; calcium imaging; calibration; cell-attached recording; excitatory neurons; genetically encoded calcium indicator; mouse; neuroscience; Action Potentials; Animals; Calcium; Calcium-Binding Proteins; Female; Fluorescent Dyes; Male; Mice; Mice, Transgenic; Microscopy, Fluorescence; Primary Visual Cortex; Pyramidal Cells; },
pubmed = {33683198},
doi = {10.7554/eLife.51675},
pii = {51675},
pmc = {PMC8060029},
url = {papers/Huang_Elife2022-33683198.pdf},
nlmuniqueid = {101579614}
}
@article{Dan2013,
title = {DMD-based LED-illumination super-resolution and optical sectioning microscopy.},
author = {Dan, Dan and Lei, Ming and Yao, Baoli and Wang, Wen and Winterhalder, Martin and Zumbusch, Andreas and Qi, Yujiao and Xia, Liang and Yan, Shaohui and Yang, Yanlong and Gao, Peng and Ye, Tong and Zhao, Wei},
journal = {Sci Rep},
volume = {3},
year = {2013},
pages = {1116},
abstract = {Super-resolution three-dimensional (3D) optical microscopy has incomparable advantages over other high-resolution microscopic technologies, such as electron microscopy and atomic force microscopy, in the study of biological molecules, pathways and events in live cells and tissues. We present a novel approach of structured illumination microscopy (SIM) by using a digital micromirror device (DMD) for fringe projection and a low-coherence LED light for illumination. The lateral resolution of 90 nm and the optical sectioning depth of 120 μm were achieved. The maximum acquisition speed for 3D imaging in the optical sectioning mode was 1.6×10(7) pixels/second, which was mainly limited by the sensitivity and speed of the CCD camera. In contrast to other SIM techniques, the DMD-based LED-illumination SIM is cost-effective, ease of multi-wavelength switchable and speckle-noise-free. The 2D super-resolution and 3D optical sectioning modalities can be easily switched and applied to either fluorescent or non-fluorescent specimens.},
keywords = {Imaging, Three-Dimensional; Light; Lighting; Microscopy; },
pubmed = {23346373},
doi = {10.1038/srep01116},
pmc = {PMC3552285},
url = {papers/Dan_SciRep2013-23346373.pdf},
nlmuniqueid = {101563288}
}
@article{Waters2019,
title = {Biological variation in the sizes, shapes and locations of visual cortical areas in the mouse.},
author = {Waters, Jack and Lee, Eric and Gaudreault, Nathalie and Griffin, Fiona and Lecoq, Jerome and Slaughterbeck, Cliff and Sullivan, David and Farrell, Colin and Perkins, Jed and Reid, David and Feng, David and Graddis, Nile and Garrett, Marina and Li, Yang and Long, Fuhui and Mochizuki, Chris and Roll, Kate and Zhuang, Jun and Thompson, Carol},
journal = {PLoS One},
volume = {14},
number = {5},
year = {2019},
pages = {e0213924},
abstract = {Visual cortex is organized into discrete sub-regions or areas that are arranged into a hierarchy and serves different functions in the processing of visual information. In retinotopic maps of mouse cortex, there appear to be substantial mouse-to-mouse differences in visual area location, size and shape. Here we quantify the biological variation in the size, shape and locations of 11 visual areas in the mouse, after separating biological variation and measurement noise. We find that there is biological variation in the locations and sizes of visual areas.},
keywords = {Animals; Brain Mapping; Male; Mice; Visual Cortex; Visual Pathways; },
pubmed = {31042712},
doi = {10.1371/journal.pone.0213924},
pii = {PONE-D-18-29482},
pmc = {PMC6493719},
url = {papers/Waters_PLoSOne2020-31042712.pdf},
nlmuniqueid = {101285081}
}
@article{Cardin2020,
title = {Mesoscopic Imaging: Shining a Wide Light on Large-Scale Neural Dynamics.},
author = {Cardin, Jessica A and Crair, Michael C and Higley, Michael J},
journal = {Neuron},
volume = {108},
number = {1},
year = {2020},
month = {10},
pages = {33-43},
abstract = {Optical imaging has revolutionized our ability to monitor brain activity, spanning spatial scales from synapses to cells to circuits. Here, we summarize the rapid development and application of mesoscopic imaging, a widefield fluorescence-based approach that balances high spatiotemporal resolution with extraordinarily large fields of view. By leveraging the continued expansion of fluorescent reporters for neuronal activity and novel strategies for indicator expression, mesoscopic analysis enables measurement and correlation of network dynamics with behavioral state and task performance. Moreover, the combination of widefield imaging with cellular resolution methods such as two-photon microscopy and electrophysiology is bridging boundaries between cellular and network analyses. Overall, mesoscopic imaging provides a powerful option in the optical toolbox for investigation of brain function.},
keywords = {Animals; Brain; Calcium; Humans; Intravital Microscopy; Microscopy, Fluorescence, Multiphoton; Neurons; Optical Imaging; },
pubmed = {33058764},
pii = {S0896-6273(20)30755-8},
doi = {10.1016/j.neuron.2020.09.031},
pmc = {PMC7577373},
mid = {NIHMS1634083},
url = {papers/Cardin_Neuron2020-33058764.pdf},
nlmuniqueid = {8809320}
}
@article{Babola2018,
title = {Homeostatic Control of Spontaneous Activity in the Developing Auditory System.},
author = {Babola, Travis A and Li, Sally and Gribizis, Alexandra and Lee, Brian J and Issa, John B and Wang, Han Chin and Crair, Michael C and Bergles, Dwight E},
journal = {Neuron},
volume = {99},
number = {3},
year = {2018},
month = {08},
pages = {511-524.e5},
abstract = {Neurons in the developing auditory system exhibit spontaneous bursts of activity before hearing onset. How this intrinsically generated activity influences development remains uncertain, because few mechanistic studies have been performed in vivo. We show using macroscopic calcium imaging in unanesthetized mice that neurons responsible for processing similar frequencies of sound exhibit highly synchronized activity throughout the auditory system during this critical phase of development. Spontaneous activity normally requires synaptic excitation of spiral ganglion neurons (SGNs). Unexpectedly, tonotopic spontaneous activity was preserved in a mouse model of deafness in which glutamate release from hair cells is abolished. SGNs in these mice exhibited enhanced excitability, enabling direct neuronal excitation by supporting cell-induced potassium transients. These results indicate that homeostatic mechanisms maintain spontaneous activity in the pre-hearing period, with significant implications for both circuit development and therapeutic approaches aimed at treating congenital forms of deafness arising through mutations in key sensory transduction components.},
keywords = {Acoustic Stimulation; Animals; Auditory Cortex; Auditory Pathways; Cochlea; Female; Hair Cells, Auditory; Hearing; Homeostasis; Male; Mice; Mice, Transgenic; Random Allocation; Spiral Ganglion; },
pubmed = {30077356},
pii = {S0896-6273(18)30544-0},
doi = {10.1016/j.neuron.2018.07.004},
pmc = {PMC6100752},
mid = {NIHMS1502189},
url = {papers/Babola_Neuron2019-30077356.pdf},
nlmuniqueid = {8809320}
}
@article{Imam2020,
title = {Self-organization of cortical areas in the development and evolution of neocortex.},
author = {Imam, Nabil and L Finlay, Barbara},
journal = {Proc Natl Acad Sci U S A},
volume = {117},
number = {46},
year = {2020},
month = {11},
pages = {29212-29220},
abstract = {While the mechanisms generating the topographic organization of primary sensory areas in the neocortex are well studied, what generates secondary cortical areas is virtually unknown. Using physical parameters representing primary and secondary visual areas as they vary from monkey to mouse, we derived a network growth model to explore if characteristic features of secondary areas could be produced from correlated activity patterns arising from V1 alone. We found that V1 seeded variable numbers of secondary areas based on activity-driven wiring and wiring-density limits within the cortical surface. These secondary areas exhibited the typical mirror-reversal of map topography on cortical area boundaries and progressive reduction of the area and spatial resolution of each new map on the caudorostral axis. Activity-based map formation may be the basic mechanism that establishes the matrix of topographically organized cortical areas available for later computational specialization.},
keywords = {cortical areas; development; evolution; network neuroscience; topographic maps; Animals; Biological Evolution; Brain; Macaca mulatta; Mice; Models, Biological; Neocortex; Nerve Net; Somatosensory Cortex; Visual Cortex; },
pubmed = {33139564},
pii = {2011724117},
doi = {10.1073/pnas.2011724117},
pmc = {PMC7682404},
url = {papers/Imam_ProcNatlAcadSciUSA2021-33139564.pdf},
nlmuniqueid = {7505876}
}
@article{Ekstrom2020,
title = {Grid coding, spatial representation, and navigation: Should we assume an isomorphism?},
author = {Ekstrom, Arne D and Harootonian, Sevan K and Huffman, Derek J},
journal = {Hippocampus},
volume = {30},
number = {4},
year = {2020},
month = {04},
pages = {422-432},
abstract = {Grid cells provide a compelling example of a link between cellular activity and an abstract and difficult to define concept like space. Accordingly, a representational perspective on grid coding argues that neural grid coding underlies a fundamentally spatial metric. Recently, some theoretical proposals have suggested extending such a framework to nonspatial cognition as well, such as category learning. Here, we provide a critique of the frequently employed assumption of an isomorphism between patterns of neural activity (e.g., grid cells), mental representation, and behavior (e.g., navigation). Specifically, we question the strict isomorphism between these three levels and suggest that human spatial navigation is perhaps best characterized by a wide variety of both metric and nonmetric strategies. We offer an alternative perspective on how grid coding might relate to human spatial navigation, arguing that grid coding is part of a much larger conglomeration of neural activity patterns that dynamically tune to accomplish specific behavioral outputs.},
keywords = {entorhinal cortex; grid cells; heuristics; human behavior; spatial navigation; Animals; Entorhinal Cortex; Grid Cells; Humans; Models, Neurological; Spatial Navigation; },
pubmed = {31742364},
doi = {10.1002/hipo.23175},
pmc = {PMC7409510},
mid = {NIHMS1583182},
url = {papers/Ekstrom_Hippocampus2021-31742364.pdf},
nlmuniqueid = {9108167}
}
@article{Liu2005,
title = {Postnatal developmental expressions of neurotransmitters and receptors in various brain stem nuclei of rats.},
author = {Liu, Qiuli and Wong-Riley, Margaret T T},
journal = {J Appl Physiol (1985)},
volume = {98},
number = {4},
year = {2005},
month = {Apr},
pages = {1442-57},
abstract = {Previously, we reported that the expression of cytochrome oxidase in a number of brain stem nuclei exhibited a plateau or reduction at postnatal day (P) 3-4 and a dramatic decrease at P12, against a general increase with age. The present study examined the expression of glutamate, N-methyl-D-aspartate receptor subunit 1 (NMDAR1), GABA, GABAB receptors, glycine receptors, and glutamate receptor subunit 2 (GluR2) in the ventrolateral subnucleus of the solitary tract nucleus, nucleus ambiguus, hypoglossal nucleus, medial accessory olivary nucleus, dorsal motor nucleus of the vagus, and cuneate nucleus, from P2 to P21 in rats. Results showed that 1) the expression of glutamate increased with age in a majority of the nuclei, whereas that of NMDAR1 showed heterogeneity among the nuclei; 2) GABA and GABAB expressions decreased with age, whereas that of glycine receptors increased with age; 3) GluR2 showed two peaks, at P3-4 and P12; and 4) glutamate and NMDAR1 showed a significant reduction, whereas GABA, GABAB receptors, glycine receptors, and GluR2 exhibited a concomitant increase at P12. These features were present but less pronounced in hypoglossal nucleus and dorsal motor nucleus of the vagus and were absent in the cuneate nucleus. These data suggest that brain stem nuclei, directly or indirectly related to respiratory control, share a common developmental trend with the pre-Botzinger complex in having a transient period of imbalance between inhibitory and excitatory drives at P12. During this critical period, the respiratory system may be more vulnerable to excessive exogenous stressors.},
keywords = {Aging; Animals; Animals, Newborn; Brain Stem; Gene Expression Regulation, Developmental; Glutamic Acid; Neurotransmitter Agents; Rats; Rats, Sprague-Dawley; Receptors, AMPA; Receptors, GABA-B; Receptors, Glycine; Receptors, N-Methyl-D-Aspartate; Sensory Receptor Cells; Tissue Distribution; gamma-Aminobutyric Acid; },
pubmed = {15618314},
pii = {01301.2004},
doi = {10.1152/japplphysiol.01301.2004},
url = {papers/Liu_JApplPhysiol(1985)2005-15618314.pdf},
nlmuniqueid = {8502536}
}
@article{Banino2018,
title = {Vector-based navigation using grid-like representations in artificial agents.},
author = {Banino, Andrea and Barry, Caswell and Uria, Benigno and Blundell, Charles and Lillicrap, Timothy and Mirowski, Piotr and Pritzel, Alexander and Chadwick, Martin J and Degris, Thomas and Modayil, Joseph and Wayne, Greg and Soyer, Hubert and Viola, Fabio and Zhang, Brian and Goroshin, Ross and Rabinowitz, Neil and Pascanu, Razvan and Beattie, Charlie and Petersen, Stig and Sadik, Amir and Gaffney, Stephen and King, Helen and Kavukcuoglu, Koray and Hassabis, Demis and Hadsell, Raia and Kumaran, Dharshan},
journal = {Nature},
volume = {557},
number = {7705},
year = {2018},
month = {05},
pages = {429-433},
abstract = {Deep neural networks have achieved impressive successes in fields ranging from object recognition to complex games such as Go1,2. Navigation, however, remains a substantial challenge for artificial agents, with deep neural networks trained by reinforcement learning3-5 failing to rival the proficiency of mammalian spatial behaviour, which is underpinned by grid cells in the entorhinal cortex 6 . Grid cells are thought to provide a multi-scale periodic representation that functions as a metric for coding space7,8 and is critical for integrating self-motion (path integration)6,7,9 and planning direct trajectories to goals (vector-based navigation)7,10,11. Here we set out to leverage the computational functions of grid cells to develop a deep reinforcement learning agent with mammal-like navigational abilities. We first trained a recurrent network to perform path integration, leading to the emergence of representations resembling grid cells, as well as other entorhinal cell types 12 . We then showed that this representation provided an effective basis for an agent to locate goals in challenging, unfamiliar, and changeable environments-optimizing the primary objective of navigation through deep reinforcement learning. The performance of agents endowed with grid-like representations surpassed that of an expert human and comparison agents, with the metric quantities necessary for vector-based navigation derived from grid-like units within the network. Furthermore, grid-like representations enabled agents to conduct shortcut behaviours reminiscent of those performed by mammals. Our findings show that emergent grid-like representations furnish agents with a Euclidean spatial metric and associated vector operations, providing a foundation for proficient navigation. As such, our results support neuroscientific theories that see grid cells as critical for vector-based navigation7,10,11, demonstrating that the latter can be combined with path-based strategies to support navigation in challenging environments.},
keywords = {Animals; Biomimetics; Entorhinal Cortex; Environment; Grid Cells; Humans; Machine Learning; Neural Networks, Computer; Spatial Navigation; },
pubmed = {29743670},
doi = {10.1038/s41586-018-0102-6},
pii = {10.1038/s41586-018-0102-6},
url = {papers/Banino_Nature2018-29743670.pdf},
nlmuniqueid = {0410462}
}
@article{Vesuna2020,
title = {Deep posteromedial cortical rhythm in dissociation.},
author = {Vesuna, Sam and Kauvar, Isaac V and Richman, Ethan and Gore, Felicity and Oskotsky, Tomiko and Sava-Segal, Clara and Luo, Liqun and Malenka, Robert C and Henderson, Jaimie M and Nuyujukian, Paul and Parvizi, Josef and Deisseroth, Karl},
journal = {Nature},
volume = {586},
number = {7827},
year = {2020},
month = {10},
pages = {87-94},
abstract = {Advanced imaging methods now allow cell-type-specific recording of neural activity across the mammalian brain, potentially enabling the exploration of how brain-wide dynamical patterns give rise to complex behavioural states1-12. Dissociation is an altered behavioural state in which the integrity of experience is disrupted, resulting in reproducible cognitive phenomena including the dissociation of stimulus detection from stimulus-related affective responses. Dissociation can occur as a result of trauma, epilepsy or dissociative drug use13,14, but despite its substantial basic and clinical importance, the underlying neurophysiology of this state is unknown. Here we establish such a dissociation-like state in mice, induced by precisely-dosed administration of ketamine or phencyclidine. Large-scale imaging of neural activity revealed that these dissociative agents elicited a 1-3-Hz rhythm in layer 5 neurons of the retrosplenial cortex. Electrophysiological recording with four simultaneously deployed high-density probes revealed rhythmic coupling of the retrosplenial cortex with anatomically connected components of thalamus circuitry, but uncoupling from most other brain regions was observed-including a notable inverse correlation with frontally projecting thalamic nuclei. In testing for causal significance, we found that rhythmic optogenetic activation of retrosplenial cortex layer 5 neurons recapitulated dissociation-like behavioural effects. Local retrosplenial hyperpolarization-activated cyclic-nucleotide-gated potassium channel 1 (HCN1) pacemakers were required for systemic ketamine to induce this rhythm and to elicit dissociation-like behavioural effects. In a patient with focal epilepsy, simultaneous intracranial stereoencephalography recordings from across the brain revealed a similarly localized rhythm in the homologous deep posteromedial cortex that was temporally correlated with pre-seizure self-reported dissociation, and local brief electrical stimulation of this region elicited dissociative experiences. These results identify the molecular, cellular and physiological properties of a conserved deep posteromedial cortical rhythm that underlies states of dissociation.},
keywords = {Action Potentials; Animals; Behavior; Brain Waves; Cerebral Cortex; Dissociative Disorders; Electrophysiology; Female; Humans; Hyperpolarization-Activated Cyclic Nucleotide-Gated Channels; Ketamine; Male; Mice; Mice, Inbred C57BL; Neurons; Optogenetics; Self Report; Thalamus; },
pubmed = {32939091},
doi = {10.1038/s41586-020-2731-9},
pii = {10.1038/s41586-020-2731-9},
pmc = {PMC7553818},
mid = {HHMIMS1634078},
url = {papers/Vesuna_Nature2021-32939091.pdf},
nlmuniqueid = {0410462}
}
@article{West2021,
title = {Wide-Field Calcium Imaging of Dynamic Cortical Networks during Locomotion.},
author = {West, Sarah L and Aronson, Justin D and Popa, Laurentiu S and Feller, Kathryn D and Carter, Russell E and Chiesl, William M and Gerhart, Morgan L and Shekhar, Aditya C and Ghanbari, Leila and Kodandaramaiah, Suhasa B and Ebner, Timothy J},
journal = {Cereb Cortex},
year = {2021},
month = {Oct},
pages = {},
abstract = {Motor behavior results in complex exchanges of motor and sensory information across cortical regions. Therefore, fully understanding the cerebral cortex's role in motor behavior requires a mesoscopic-level description of the cortical regions engaged, their functional interactions, and how these functional interactions change with behavioral state. Mesoscopic Ca2+ imaging through transparent polymer skulls in mice reveals elevated activation of the dorsal cerebral cortex during locomotion. Using the correlations between the time series of Ca2+ fluorescence from 28 regions (nodes) obtained using spatial independent component analysis (sICA), we examined the changes in functional connectivity of the cortex from rest to locomotion with a goal of understanding the changes to the cortical functional state that facilitate locomotion. Both the transitions from rest to locomotion and from locomotion to rest show marked increases in correlation among most nodes. However, once a steady state of continued locomotion is reached, many nodes, including primary motor and somatosensory nodes, show decreases in correlations, while retrosplenial and the most anterior nodes of the secondary motor cortex show increases. These results highlight the changes in functional connectivity in the cerebral cortex, representing a series of changes in the cortical state from rest to locomotion and on return to rest.},
pubmed = {34689209},
pii = {6408797},
doi = {10.1093/cercor/bhab373},
url = {papers/West_CerebCortex2022-34689209.pdf},
nlmuniqueid = {9110718}
}
@article{Waters2020,
title = {Sources of widefield fluorescence from the brain.},
author = {Waters, Jack},
journal = {Elife},
volume = {9},
year = {2020},
month = {11},
pages = {},
abstract = {Widefield fluorescence microscopy is used to monitor the spiking of populations of neurons in the brain. Widefield fluorescence can originate from indicator molecules at all depths in cortex and the relative contributions from somata, dendrites, and axons are often unknown. Here, I simulate widefield illumination and fluorescence collection and determine the main sources of fluorescence for several GCaMP mouse lines. Scattering strongly affects illumination and collection. One consequence is that illumination intensity is greatest ~300-400 µm below the pia, not at the brain surface. Another is that fluorescence from a source deep in cortex may extend across a diameter of 3-4 mm at the brain surface, severely limiting lateral resolution. In many mouse lines, the volume of tissue contributing to fluorescence extends through the full depth of cortex and fluorescence at most surface locations is a weighted average across multiple cortical columns and often more than one cortical area.},
keywords = {cortex; fluorescence; imaging; microscopy; neuroscience; none; widefield; Animals; Brain; Cell Line; Fluorescence; Mice; Microscopy, Fluorescence; Monte Carlo Method; },
pubmed = {33155981},
doi = {10.7554/eLife.59841},
pii = {59841},
pmc = {PMC7647397},
url = {papers/Waters_Elife2021-33155981.pdf},
nlmuniqueid = {101579614}
}
@article{Mckeown1998,
author = {Mckeown, Martin J. and Makeig, Scott and Brown, Greg G. and Jung, Tzyy-Ping and Kindermann, Sandra S. and Bell, Anthony J. and Sejnowski, Terrence J.},
title = {Analysis of fMRI data by blind separation into independent spatial components},
journal = {Human Brain Mapping},
volume = {6},
number = {3},
pages = {160-188},
keywords = {functional magnetic resonance imaging, independent component analysis, higher-order statistics},
pubmed = {9673671},
doi = {10.1002/(SICI)1097-0193(1998)6:3<160::AID-HBM5>3.0.CO;2-1},
url = {Mckeown_HumBrainMap1998.pdf},
abstract = {Abstract Current analytical techniques applied to functional magnetic resonance imaging (fMRI) data require a priori knowledge or specific assumptions about the time courses of processes contributing to the measured signals. Here we describe a new method for analyzing fMRI data based on the independent component analysis (ICA) algorithm of Bell and Sejnowski ([1995]: Neural Comput 7:1129–1159). We decomposed eight fMRI data sets from 4 normal subjects performing Stroop color-naming, the Brown and Peterson word/number task, and control tasks into spatially independent components. Each component consisted of voxel values at fixed three-dimensional locations (a component “map”), and a unique associated time course of activation. Given data from 144 time points collected during a 6-min trial, ICA extracted an equal number of spatially independent components. In all eight trials, ICA derived one and only one component with a time course closely matching the time course of 40-sec alternations between experimental and control tasks. The regions of maximum activity in these consistently task-related components generally overlapped active regions detected by standard correlational analysis, but included frontal regions not detected by correlation. Time courses of other ICA components were transiently task-related, quasiperiodic, or slowly varying. By utilizing higher-order statistics to enforce successively stricter criteria for spatial independence between component maps, both the ICA algorithm and a related fourth-order decomposition technique (Comon [1994]: Signal Processing 36:11–20) were superior to principal component analysis (PCA) in determining the spatial and temporal extent of task-related activation. For each subject, the time courses and active regions of the task-related ICA components were consistent across trials and were robust to the addition of simulated noise. Simulated movement artifact and simulated task-related activations added to actual fMRI data were clearly separated by the algorithm. ICA can be used to distinguish between nontask-related signal components, movements, and other artifacts, as well as consistently or transiently task-related fMRI activations, based on only weak assumptions about their spatial distributions and without a priori assumptions about their time courses. ICA appears to be a highly promising method for the analysis of fMRI data from normal and clinical populations, especially for uncovering unpredictable transient patterns of brain activity associated with performance of psychomotor tasks. Hum. Brain Mapping 6:160–188, 1998. © 1998 Wiley-Liss, Inc.},
year = {1998}
}
@article{Pruim2015,
title = {ICA-AROMA: A robust ICA-based strategy for removing motion artifacts from fMRI data.},
author = {Pruim, Raimon H R and Mennes, Maarten and van Rooij, Daan and Llera, Alberto and Buitelaar, Jan K and Beckmann, Christian F},
journal = {Neuroimage},
volume = {112},
year = {2015},
month = {May},
pages = {267-277},
abstract = {Head motion during functional MRI (fMRI) scanning can induce spurious findings and/or harm detection of true effects. Solutions have been proposed, including deleting ('scrubbing') or regressing out ('spike regression') motion volumes from fMRI time-series. These strategies remove motion-induced signal variations at the cost of destroying the autocorrelation structure of the fMRI time-series and reducing temporal degrees of freedom. ICA-based fMRI denoising strategies overcome these drawbacks but typically require re-training of a classifier, needing manual labeling of derived components (e.g. ICA-FIX; Salimi-Khorshidi et al. (2014)). Here, we propose an ICA-based strategy for Automatic Removal of Motion Artifacts (ICA-AROMA) that uses a small (n=4), but robust set of theoretically motivated temporal and spatial features. Our strategy does not require classifier re-training, retains the data's autocorrelation structure and largely preserves temporal degrees of freedom. We describe ICA-AROMA, its implementation, and initial validation. ICA-AROMA identified motion components with high accuracy and robustness as illustrated by leave-N-out cross-validation. We additionally validated ICA-AROMA in resting-state (100 participants) and task-based fMRI data (118 participants). Our approach removed (motion-related) spurious noise from both rfMRI and task-based fMRI data to larger extent than regression using 24 motion parameters or spike regression. Furthermore, ICA-AROMA increased sensitivity to group-level activation. Our results show that ICA-AROMA effectively reduces motion-induced signal variations in fMRI data, is applicable across datasets without requiring classifier re-training, and preserves the temporal characteristics of the fMRI data. },
keywords = {Artifact; Connectivity; Functional MRI; Independent component analysis; Motion; Resting state; Algorithms; Artifacts; Artificial Intelligence; Cerebrospinal Fluid; Humans; Image Processing, Computer-Assisted; Magnetic Resonance Imaging; Motion; Principal Component Analysis; Reproducibility of Results; Rest; },
pubmed = {25770991},
pii = {S1053-8119(15)00182-2},
doi = {10.1016/j.neuroimage.2015.02.064},
url = {papers/Pruim_Neuroimage2016-25770991.pdf},
nlmuniqueid = {9215515}
}
@article{Parkes2018,
title = {An evaluation of the efficacy, reliability, and sensitivity of motion correction strategies for resting-state functional MRI.},
author = {Parkes, Linden and Fulcher, Ben and Yücel, Murat and Fornito, Alex},
journal = {Neuroimage},
volume = {171},
year = {2018},
month = {05},
pages = {415-436},
abstract = {Estimates of functional connectivity derived from resting-state functional magnetic resonance imaging (rs-fMRI) are sensitive to artefacts caused by in-scanner head motion. This susceptibility has motivated the development of numerous denoising methods designed to mitigate motion-related artefacts. Here, we compare popular retrospective rs-fMRI denoising methods, such as regression of head motion parameters and mean white matter (WM) and cerebrospinal fluid (CSF) (with and without expansion terms), aCompCor, volume censoring (e.g., scrubbing and spike regression), global signal regression and ICA-AROMA, combined into 19 different pipelines. These pipelines were evaluated across five different quality control benchmarks in four independent datasets associated with varying levels of motion. Pipelines were benchmarked by examining the residual relationship between in-scanner movement and functional connectivity after denoising; the effect of distance on this residual relationship; whole-brain differences in functional connectivity between high- and low-motion healthy controls (HC); the temporal degrees of freedom lost during denoising; and the test-retest reliability of functional connectivity estimates. We also compared the sensitivity of each pipeline to clinical differences in functional connectivity in independent samples of people with schizophrenia and obsessive-compulsive disorder. Our results indicate that (1) simple linear regression of regional fMRI time series against head motion parameters and WM/CSF signals (with or without expansion terms) is not sufficient to remove head motion artefacts; (2) aCompCor pipelines may only be viable in low-motion data; (3) volume censoring performs well at minimising motion-related artefact but a major benefit of this approach derives from the exclusion of high-motion individuals; (4) while not as effective as volume censoring, ICA-AROMA performed well across our benchmarks for relatively low cost in terms of data loss; (5) the addition of global signal regression improved the performance of nearly all pipelines on most benchmarks, but exacerbated the distance-dependence of correlations between motion and functional connectivity; and (6) group comparisons in functional connectivity between healthy controls and schizophrenia patients are highly dependent on preprocessing strategy. We offer some recommendations for best practice and outline simple analyses to facilitate transparent reporting of the degree to which a given set of findings may be affected by motion-related artefact.},
keywords = {Artefact; Functional connectivity; Motion; Noise; Resting-state; fMRI; Adult; Algorithms; Artifacts; Brain Mapping; Datasets as Topic; Female; Head Movements; Humans; Image Processing, Computer-Assisted; Magnetic Resonance Imaging; Male; Motion; Reproducibility of Results; },
pubmed = {29278773},
pii = {S1053-8119(17)31097-2},
doi = {10.1016/j.neuroimage.2017.12.073},
url = {papers/Parkes_Neuroimage2018-29278773.pdf},
nlmuniqueid = {9215515}
}
@article{Murphy2016,
title = {High-throughput automated home-cage mesoscopic functional imaging of mouse cortex.},
author = {Murphy, Timothy H and Boyd, Jamie D and Bolaños, Federico and Vanni, Matthieu P and Silasi, Gergely and Haupt, Dirk and LeDue, Jeff M},
journal = {Nat Commun},
volume = {7},
year = {2016},
month = {06},
pages = {11611},
abstract = {Mouse head-fixed behaviour coupled with functional imaging has become a powerful technique in rodent systems neuroscience. However, training mice can be time consuming and is potentially stressful for animals. Here we report a fully automated, open source, self-initiated head-fixation system for mesoscopic functional imaging in mice. The system supports five mice at a time and requires minimal investigator intervention. Using genetically encoded calcium indicator transgenic mice, we longitudinally monitor cortical functional connectivity up to 24 h per day in >7,000 self-initiated and unsupervised imaging sessions up to 90 days. The procedure provides robust assessment of functional cortical maps on the basis of both spontaneous activity and brief sensory stimuli such as light flashes. The approach is scalable to a number of remotely controlled cages that can be assessed within the controlled conditions of dedicated animal facilities. We anticipate that home-cage brain imaging will permit flexible and chronic assessment of mesoscale cortical function.},
keywords = {Animals; Automation; Evoked Potentials, Visual; Female; Head; Imaging, Three-Dimensional; Mice; Mice, Transgenic; Nerve Net; Visual Cortex; },
pubmed = {27291514},
pii = {ncomms11611},
doi = {10.1038/ncomms11611},
pmc = {PMC4909937},
url = {papers/Murphy_NatCommun2018-27291514.pdf},
nlmuniqueid = {101528555}
}
@article{Beckmann2004,
title = {Probabilistic independent component analysis for functional magnetic resonance imaging.},
author = {Beckmann, Christian F and Smith, Stephen M},
journal = {IEEE Trans Med Imaging},
volume = {23},
number = {2},
year = {2004},
month = {Feb},
pages = {137-52},
abstract = {We present an integrated approach to probabilistic independent component analysis (ICA) for functional MRI (FMRI) data that allows for nonsquare mixing in the presence of Gaussian noise. In order to avoid overfitting, we employ objective estimation of the amount of Gaussian noise through Bayesian analysis of the true dimensionality of the data, i.e., the number of activation and non-Gaussian noise sources. This enables us to carry out probabilistic modeling and achieves an asymptotically unique decomposition of the data. It reduces problems of interpretation, as each final independent component is now much more likely to be due to only one physical or physiological process. We also describe other improvements to standard ICA, such as temporal prewhitening and variance normalization of timeseries, the latter being particularly useful in the context of dimensionality reduction when weak activation is present. We discuss the use of prior information about the spatiotemporal nature of the source processes, and an alternative-hypothesis testing approach for inference, using Gaussian mixture models. The performance of our approach is illustrated and evaluated on real and artificial FMRI data, and compared to the spatio-temporal accuracy of results obtained from classical ICA and GLM analyses.},
keywords = {Algorithms; Brain; Cerebral Cortex; Humans; Image Enhancement; Image Interpretation, Computer-Assisted; Magnetic Resonance Imaging; Models, Neurological; Models, Statistical; Neurons; Phantoms, Imaging; Principal Component Analysis; Reproducibility of Results; Sensitivity and Specificity; Stochastic Processes; Vision, Ocular; },
pubmed = {14964560},
doi = {10.1109/TMI.2003.822821},
url = {papers/Beckmann_IEEETransMedImaging2004-14964560.pdf},
nlmuniqueid = {8310780}
}
@article{Clancy2019,
title = {Locomotion-dependent remapping of distributed cortical networks.},
author = {Clancy, Kelly B and Orsolic, Ivana and Mrsic-Flogel, Thomas D},
journal = {Nat Neurosci},
volume = {22},
number = {5},
year = {2019},
month = {05},
pages = {778-786},
abstract = {The interactions between neocortical areas are fluid and state-dependent, but how individual neurons couple to cortex-wide network dynamics remains poorly understood. We correlated the spiking of neurons in primary visual (V1) and retrosplenial (RSP) cortex to activity across dorsal cortex, recorded simultaneously by widefield calcium imaging. Neurons were correlated with distinct and reproducible patterns of activity across the cortical surface; while some fired predominantly with their local area, others coupled to activity in distal areas. The extent of distal coupling was predicted by how strongly neurons correlated with the local network. Changes in brain state triggered by locomotion strengthened affiliations of V1 neurons with higher visual and motor areas, while strengthening distal affiliations of RSP neurons with sensory cortices. Thus, the diverse coupling of individual neurons to cortex-wide activity patterns is restructured by running in an area-specific manner, resulting in a shift in the mode of cortical processing during locomotion.},
keywords = {Action Potentials; Animals; Cerebral Cortex; Female; Locomotion; Male; Mice, Transgenic; Neural Pathways; Neurons; Visual Cortex; },
pubmed = {30858604},
doi = {10.1038/s41593-019-0357-8},
pii = {10.1038/s41593-019-0357-8},
pmc = {PMC6701985},
mid = {EMS84025},
url = {papers/Clancy_NatNeurosci2019-30858604.pdf},
nlmuniqueid = {9809671}
}
@article{Vanni2017,
title = {Mesoscale Mapping of Mouse Cortex Reveals Frequency-Dependent Cycling between Distinct Macroscale Functional Modules.},
author = {Vanni, Matthieu P and Chan, Allen W and Balbi, Matilde and Silasi, Gergely and Murphy, Timothy H},
journal = {J Neurosci},
volume = {37},
number = {31},
year = {2017},
month = {08},
pages = {7513-7533},
abstract = {Connectivity mapping based on resting-state activity in mice has revealed functional motifs of correlated activity. However, the rules by which motifs organize into larger functional modules that lead to hemisphere wide spatial-temporal activity sequences is not clear. We explore cortical activity parcellation in head-fixed, quiet awake GCaMP6 mice from both sexes by using mesoscopic calcium imaging. Spectral decomposition of spontaneous cortical activity revealed the presence of two dominant frequency modes (<1 and ∼3 Hz), each of them associated with a unique spatial signature of cortical macro-parcellation not predicted by classical cytoarchitectonic definitions of cortical areas. Based on assessment of 0.1-1 Hz activity, we define two macro-organizing principles: the first being a rotating polymodal-association pinwheel structure around which activity flows sequentially from visual to barrel then to hindlimb somatosensory; the second principle is correlated activity symmetry planes that exist on many levels within a single domain such as intrahemispheric reflections of sensory and motor cortices. In contrast, higher frequency activity >1 Hz yielded two larger clusters of coactivated areas with an enlarged default mode network-like posterior region. We suggest that the apparent constrained structure for intra-areal cortical activity flow could be exploited in future efforts to normalize activity in diseases of the nervous system.SIGNIFICANCE STATEMENT Increasingly, functional connectivity mapping of spontaneous activity is being used to reveal the organization of the brain. However, because the brain operates across multiple space and time domains a more detailed understanding of this organization is necessary. We used in vivo wide-field calcium imaging of the indicator GCaMP6 in head-fixed, awake mice to characterize the organization of spontaneous cortical activity at different spatiotemporal scales. Correlation analysis defines the presence of two to three superclusters of activity that span traditionally defined functional territories and were frequency dependent. This work helps define the rules for how different cortical areas interact in time and space. We provide a framework necessary for future studies that explore functional reorganization of brain circuits in disease models.},
keywords = {awake mouse; calcium imaging; connectome; cortical dynamic; resting state; Animals; Brain Waves; Calcium Signaling; Cerebral Cortex; Computer Simulation; Connectome; Female; Male; Mice; Mice, Transgenic; Models, Neurological; Nerve Net; Rest; Spatio-Temporal Analysis; Voltage-Sensitive Dye Imaging; },
pubmed = {28674167},
pii = {JNEUROSCI.3560-16.2017},
doi = {10.1523/JNEUROSCI.3560-16.2017},
pmc = {PMC6596702},
url = {papers/Vanni_JNeurosci2017-28674167.pdf},
nlmuniqueid = {8102140}
}
@article{Allen2017,
title = {Global Representations of Goal-Directed Behavior in Distinct Cell Types of Mouse Neocortex.},
author = {Allen, William E and Kauvar, Isaac V and Chen, Michael Z and Richman, Ethan B and Yang, Samuel J and Chan, Ken and Gradinaru, Viviana and Deverman, Benjamin E and Luo, Liqun and Deisseroth, Karl},
journal = {Neuron},
volume = {94},
number = {4},
year = {2017},
month = {May},
pages = {891-907.e6},
abstract = {The successful planning and execution of adaptive behaviors in mammals may require long-range coordination of neural networks throughout cerebral cortex. The neuronal implementation of signals that could orchestrate cortex-wide activity remains unclear. Here, we develop and apply methods for cortex-wide Ca2+ imaging in mice performing decision-making behavior and identify a global cortical representation of task engagement encoded in the activity dynamics of both single cells and superficial neuropil distributed across the majority of dorsal cortex. The activity of multiple molecularly defined cell types was found to reflect this representation with type-specific dynamics. Focal optogenetic inhibition tiled across cortex revealed a crucial role for frontal cortex in triggering this cortex-wide phenomenon; local inhibition of this region blocked both the cortex-wide response to task-initiating cues and the voluntary behavior. These findings reveal cell-type-specific processes in cortex for globally representing goal-directed behavior and identify a major cortical node that gates the global broadcast of task-related information.},
keywords = {calcium imaging; cell type; cortex; goal-directed behavior; optogenetics; widefield; Animals; Behavior, Animal; Calcium; Decision Making; Frontal Lobe; Goals; Mice; Neocortex; Neurons; Optical Imaging; Optogenetics; },
pubmed = {28521139},
pii = {S0896-6273(17)30343-4},
doi = {10.1016/j.neuron.2017.04.017},
pmc = {PMC5723385},
mid = {HHMIMS923712},
url = {papers/Allen_Neuron2017-28521139.pdf},
nlmuniqueid = {8809320}
}