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Your search keyword '"Colin Farrell"' showing total 2 results
Start Over Author "Colin Farrell" Journal nature neuroscience
2 results on '"Colin Farrell"'

1. A large-scale standardized physiological survey reveals functional organization of the mouse visual cortex

Author

Thuyanh V. Nguyen, Melise Edwards, Linzy Casal, Michael A. Buice, Shiella Caldejon, Derric Williams, Nathalie Gaudreault, Ryan Valenza, Nicholas Cain, Cliff Slaughterbeck, Jennifer Luviano, Saskia E. J. de Vries, Fuhui Long, Jianghong Shi, Ali Williford, Shawn R. Olsen, Stefan Mihalas, Terri L. Gilbert, Nicholas Bowles, Daniela Witten, Jed Perkins, David Feng, Nathan Sjoquist, Lu Li, Eric Shea-Brown, Michael Oliver, Wayne Wakeman, Kyla Mace, Tom Keenan, Gabriel Koch Ocker, Chris Lau, Sissy Cross, Perry Hargrave, Amy Bernard, R. Clay Reid, Jack Waters, Kate Roll, Peter Ledochowitsch, John W. Phillips, Ulf Knoblich, Felix Lee, Andrew Cho, Miranda Robertson, Peter A. Groblewski, John Galbraith, Sean Jewell, Arielle Leon, Tim A. Dolbeare, Sam Seid, Marina Garrett, Fiona Griffin, Josh D Larkin, Nika H. Keller, Robert Howard, Chinh Dang, Chris Barber, Colin Farrell, White C, Nathan Berbesque, Carol L. Thompson, Eric Lee, Jun Zhuang, Hongkui Zeng, Daniel Millman, Lydia Ng, Leonard Kuan, Christof Koch, Brandon Blanchard, David Sullivan, Jérôme Lecoq, Rachael Larsen, and Lawrence Huang

Subjects
0301 basic medicine, Dorsum, Visual perception, genetic structures, Extramural, General Neuroscience, Datasets as Topic, Sensory system, Stimulus (physiology), Biology, Article, Visual motion, Mice, 03 medical and health sciences, 030104 developmental biology, 0302 clinical medicine, Visual cortex, medicine.anatomical_structure, medicine, Animals, Functional organization, Neuroscience, 030217 neurology & neurosurgery, Visual Cortex
Abstract

To understand how the brain processes sensory information to guide behavior, we must know how stimulus representations are transformed throughout the visual cortex. Here we report an open, large-scale physiological survey of activity in the awake mouse visual cortex: the Allen Brain Observatory Visual Coding dataset. This publicly available dataset includes the cortical activity of nearly 60,000 neurons from six visual areas, four layers, and 12 transgenic mouse lines in a total of 243 adult mice, in response to a systematic set of visual stimuli. We classify neurons on the basis of joint reliabilities to multiple stimuli and validate this functional classification with models of visual responses. While most classes are characterized by responses to specific subsets of the stimuli, the largest class is not reliably responsive to any of the stimuli and becomes progressively larger in higher visual areas. These classes reveal a functional organization wherein putative dorsal areas show specialization for visual motion signals.

Published
2019

2. Classification of electrophysiological and morphological neuron types in the mouse visual cortex

Author

David Sandman, Brian Lee, Michael Hawrylycz, Sara Kebede, Tom Egdorf, David Reid, Rob Young, Nivretta Thatra, Stefan Mihalas, David Feng, John W. Phillips, Rebecca de Frates, DiJon Hill, Cliff Slaughterbeck, Samuel R Josephsen, Tamara Casper, Xiaoxiao Liu, Hanchuan Peng, Peter Chong, Colin Farrell, Zhi Zhou, Sheana Parry, Jed Perkins, Brian Long, Susan M. Sunkin, Matthew Kroll, Krissy Brouner, Melissa Gorham, Aaron Szafer, Wayne Wakeman, Hong Gu, Marissa Garwood, Daniel Park, Kristen Hadley, Michael S. Fisher, Lydia Potekhina, Ed Lein, Alice Mukora, Hongkui Zeng, Nick Dee, Aaron Oldre, Lindsay Ng, Thomas Braun, Grace Williams, Tracy Lemon, Julie A. Harris, Medea McGraw, Nadezhda Dotson, Philip R. Nicovich, Amanda Gary, Rusty Mann, Alex M. Henry, Caroline Habel, Samuel Dingman, Katherine E. Link, Nathalie Gaudreault, Gilberto J. Soler-Llavina, Thuc Nghi Nguyen, Nicole Blesie, Bosiljka Tasic, Lydia Ng, Christine Cuhaciyan, Tim Jarsky, Keith B. Godfrey, Costas A. Anastassiou, Kirsten Crichton, Josef Sulc, Martin Schroedter, Dan Castelli, Miranda Robertson, Amy Bernard, Lisa Kim, Songlin Ding, Alyse Doperalski, Nathan W. Gouwens, Herman Tung, Tsega Desta, Corinne Teeter, James Harrington, Jonathan T. Ting, Kris Bickley, Anton Arkhipov, Kiet Ngo, Changkyu Lee, Jim Berg, Agata Budzillo, Emma Garren, Tanya L. Daigle, Christof Koch, Rachel A. Dalley, Eliza Barkan, Staci A. Sorensen, Gabe J. Murphy, Shiella Caldejon, and Naz Taskin

Subjects
0301 basic medicine, Genetically modified mouse, Cell type, Patch-Clamp Techniques, Databases, Factual, Action Potentials, Datasets as Topic, Mice, Transgenic, Biology, Article, Neuron types, Mice, 03 medical and health sciences, chemistry.chemical_compound, 0302 clinical medicine, Genes, Reporter, Biocytin, medicine, Animals, Cell shape, Cell Shape, Visual Cortex, Neurons, General Neuroscience, Laboratory mouse, Electrophysiology, 030104 developmental biology, Visual cortex, medicine.anatomical_structure, chemistry, Transcriptome, Neuroscience, 030217 neurology & neurosurgery
Abstract

Understanding the diversity of cell types in the brain has been an enduring challenge and requires detailed characterization of individual neurons in multiple dimensions. To systematically profile morpho-electric properties of mammalian neurons, we established a single-cell characterization pipeline using standardized patch-clamp recordings in brain slices and biocytin-based neuronal reconstructions. We built a publicly accessible online database, the Allen Cell Types Database, to display these datasets. Intrinsic physiological properties were measured from 1,938 neurons from the adult laboratory mouse visual cortex, morphological properties were measured from 461 reconstructed neurons, and 452 neurons had both measurements available. Quantitative features were used to classify neurons into distinct types using unsupervised methods. We established a taxonomy of morphologically and electrophysiologically defined cell types for this region of the cortex, with 17 electrophysiological types, 38 morphological types and 46 morpho-electric types. There was good correspondence with previously defined transcriptomic cell types and subclasses using the same transgenic mouse lines.

Published
2019

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