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1. Human neocortical expansion involves glutamatergic neuron diversification

Author

Tim S. Heistek, Thomas Braun, Natalia A. Goriounova, Michael Tieu, Lindsay Ng, Michael Hawrylycz, Kris Bickley, Anton Arkhipov, Colin Farrell, Trangthanh Pham, Alexandra Glandon, Daniel Park, Gábor Molnár, Herman Tung, Allan R. Jones, Lisa Keene, Gáspár Oláh, Thomas Chartrand, Amy Torkelson, Jae Geun Yoon, Rachel A. Dalley, Aaron Szafer, Nick Dee, Brian E. Kalmbach, Eliza Barkan, Allison Beller, Krissy Brouner, Andrew L. Ko, Alex M. Henry, Viktor Szemenyei, Julie Nyhus, Staci A. Sorensen, Samuel Dingman Lee, Norbert Mihut, Amy Bernard, Lisa Kim, Anatoly Buchin, Melissa Gorham, Lucas T. Graybuck, Lydia Potekhina, Katelyn Ward, Caitlin S. Latimer, Aaron Oldre, Gabe J. Murphy, Boaz P. Levi, Trygve E. Bakken, René Wilbers, Jonathan T. Ting, Kimberly A. Smith, Amanda Gary, Songlin Ding, Alice Mukora, Matthew Kroll, Anoop P. Patel, Wayne Wakeman, Hongkui Zeng, Nadezhda Dotson, Rusty Mann, Victoria Omstead, Leona Mezei, Desiree A. Marshall, Shea Ransford, Lydia Ng, Sara Kebede, Gábor Tamás, Jeffrey G. Ojemann, Stephanie Mok, Nathan Hansen, Christina A. Pom, Brian Lee, Jim Berg, Ramkumar Rajanbabu, John W. Phillips, Philip R. Nicovich, Matthew Mallory, Richard G. Ellenbogen, Rachel Enstrom, Luke Esposito, Tim Jarsky, Di Jon Hill, Idan Segev, Darren Bertagnolli, Agata Budzillo, Sander Idema, Daniel L. Silbergeld, Costas A. Anastassiou, Chris Hill, Michelle Maxwell, Mean Hwan Kim, Charles Cobbs, Delissa McMillen, Bosiljka Tasic, Olivia Fong, Medea McGraw, Hong Gu, Kirsten Crichton, David Reid, Kristen Hadley, Lauren Alfiler, Manuel Ferreira, Elliot R. Thomsen, Kiet Ngo, Josef Sulc, Augustin Ruiz, Katherine Baker, Zizhen Yao, Erica J. Melief, Femke Waleboer, Hanchuan Peng, Grace Williams, Rebecca D. Hodge, Kyla Berry, Katherine E. Link, David Sandman, Tsega Desta, Christine Rimorin, Jeff Goldy, Ryder P. Gwinn, Djai B. Heyer, Changkyu Lee, Jeremy A. Miller, Nathan W. Gouwens, Pál Barzó, Attila Ozsvár, Huibert D. Mansvelder, Sergey L. Gratiy, Rafael Yuste, David Feng, Jessica Trinh, Clare Gamlin, Tamara Casper, C. Dirk Keene, Susan M. Sunkin, Tom Egdorf, Philip C. De Witt Hamer, Rebecca de Frates, Peter Chong, Szabina Furdan, Patrick R. Hof, Jasmine Bomben, Christiaan P. J. de Kock, Eline J. Mertens, Ed S. Lein, Anna A. Galakhova, Florence D’Orazi, Christof Koch, Madie Hupp, Neurosurgery, Amsterdam Neuroscience - Systems & Network Neuroscience, Integrative Neurophysiology, Amsterdam Neuroscience - Cellular & Molecular Mechanisms, and Amsterdam Neuroscience - Compulsivity, Impulsivity & Attention

Subjects
Cell type, Multidisciplinary, Neocortex, Neurofilament, Molecular neuroscience, Biology, Article, Cellular neuroscience, chemistry.chemical_compound, Glutamatergic, medicine.anatomical_structure, chemistry, Biocytin, medicine, Neuron, Neuroscience
Abstract

The neocortex is disproportionately expanded in human compared with mouse1,2, both in its total volume relative to subcortical structures and in the proportion occupied by supragranular layers composed of neurons that selectively make connections within the neocortex and with other telencephalic structures. Single-cell transcriptomic analyses of human and mouse neocortex show an increased diversity of glutamatergic neuron types in supragranular layers in human neocortex and pronounced gradients as a function of cortical depth3. Here, to probe the functional and anatomical correlates of this transcriptomic diversity, we developed a robust platform combining patch clamp recording, biocytin staining and single-cell RNA-sequencing (Patch-seq) to examine neurosurgically resected human tissues. We demonstrate a strong correspondence between morphological, physiological and transcriptomic phenotypes of five human glutamatergic supragranular neuron types. These were enriched in but not restricted to layers, with one type varying continuously in all phenotypes across layers 2 and 3. The deep portion of layer 3 contained highly distinctive cell types, two of which express a neurofilament protein that labels long-range projection neurons in primates that are selectively depleted in Alzheimer’s disease4,5. Together, these results demonstrate the explanatory power of transcriptomic cell-type classification, provide a structural underpinning for increased complexity of cortical function in humans, and implicate discrete transcriptomic neuron types as selectively vulnerable in disease., Combined patch clamp recording, biocytin staining and single-cell RNA-sequencing of human neurocortical neurons shows an expansion of glutamatergic neuron types relative to mouse that characterizes the greater complexity of the human neocortex.

Published
2021
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2. A whole-brain monosynaptic input connectome to neuron classes in mouse visual cortex

Author

Kat North, Jasmin Bomben, Shenqin Yao, Bosiljka Tasic, Nicole Hancock, Shea Ransford, Thuyanh V. Nguyen, Ali Williford, Karla E. Hirokawa, Wayne Wakeman, Stefan Mihalas, Lydia Ng, Fiona Griffin, Robert Howard, Julie A. Harris, Rachel Enstrom, Tom Egdorf, Nadezhda Dotson, Eric Lee, Kyla Mace, Amanda Gary, Peter A. Groblewski, Michelle Maxwell, Lydia Potekhina, Tanya L. Daigle, Nhan-Kiet Ngo, Medea McGraw, Krissy Brouner, Philip R. Nicovich, Benjamin Ouellette, Jennifer Luviano, Emily Gelfand, Sam Seid, Chelsea Nayan, Maitham Naeemi, Marty Mortrud, Jackie Swapp, Cho A, Ali Cetin, Hong Gu, Hongkui Zeng, M. J. Taormina, Sophie Lambert, Leonard Kuan, Ruweida Ahmed, Thomas Zhou, Melissa Gorham, Augustin Ruiz, Linzy Casal, Shiella Caldejon, and Quanxin Wang

Subjects
General Neuroscience, Rabies virus, Tracing, Biology, medicine.disease_cause, Entire visual cortex, Visual cortex, medicine.anatomical_structure, medicine, Connectome, Excitatory postsynaptic potential, Neuron, Neuroscience, Brain function
Abstract

Identification of the structural connections between neurons is a prerequisite to understanding brain function. We developed a pipeline to systematically map brain-wide monosynaptic inputs to specific neuronal populations using Cre-driver mouse lines and the recombinant rabies tracing system. We first improved the rabies virus tracing strategy to accurately identify starter cells and to efficiently quantify presynaptic inputs. We then mapped brain-wide presynaptic inputs to different excitatory and inhibitory neuron subclasses in the primary visual cortex and seven higher visual areas. Our results reveal quantitative target-, layer- and cell-class-specific differences in the retrograde connectomes, despite similar global input patterns to different neuronal populations in the same anatomical area. The retrograde connectivity we define is consistent with the presence of the ventral and dorsal visual information processing streams and reveals further subnetworks within the dorsal stream. The hierarchical organization of the entire visual cortex can be derived from intracortical feedforward and feedback pathways mediated by upper- and lower-layer input neurons, respectively. This study expands our knowledge of the brain-wide inputs regulating visual areas and demonstrates that our improved rabies virus tracing strategy can be used to scale up the effort in dissecting connectivity of genetically defined cell populations in the whole mouse brain.

Published
2021
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3. 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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4. Local Connectivity and Synaptic Dynamics in Mouse and Human Neocortex

Author

Michael Tieu, Amy Bernard, Lisa Kim, Samuel Dingman Lee, Tim Jarsky, Corinne Teeter, Martin Schroedter, Alex Hoggarth, Kimberly A. Smith, Amanda Gary, Charles Cobb, John W. Phillips, Christina A. Pom, Herman Tung, Hongkui Zeng, Daniel Carey, Phillip Bohn, Colin Farrell, Bosiljka Tasic, Rusty Nicovich, Medea McGraw, Krissy Brouner, Andrew L. Ko, Katherine Wadhwani, Lauren Ellingwood, Tom Egdorf, Anton Arkhipov, Aaron Szafer, Michael Clark, Kirsten Crichton, Kyla Berry, Josef Sulc, Nick Dee, Gabe J. Murphy, Luke Esposito, Trangthanh Pham, Thomas Chartrand, Alex M. Henry, Rachel A. Dalley, Rachel Enstrom, Thomas Braun, Luke Campagnola, Cristina Radaelli, C. Dirk Keene, Tanya L. Daigle, Cliff Slaughterbeck, Sara Kebede, Rachael Larsen, Jeffrey G. Ojemann, Juia Andrade, Michelle Maxwell, Staci A. Sorensen, Jeff Goldy, Jessica Gloe, David Sandman, Shinya Ito, Susan M. Sunkin, Wayne Wakeman, Travis A. Hage, Melissa Gorham, Ryder P. Gwinn, Pasha A. Davoudian, Augustin Ruiz, Grace Williams, Clare Gamlin, Christof Koch, La'Akea Siverts, Stephanie C. Seeman, Jasmine Bomben, Florence D’Orazi, Madie Hupp, Ed S. Lein, Nadia Dotson, Shea Ransford, Nika Hejazinia, Mean Hwan Kim, Delissa McMillen, David Feng, Jessica Trinh, Lydia Potekhina, Alice Mukora, Lauren Alfiler, Tamara Casper, Shu Shi, Matthew Kroll, Kiet Ngo, Richard G. Ellenbogen, Daniel L. Silbergeld, and Miranda Walker

Subjects
Synapse, Cell type, Neocortex, medicine.anatomical_structure, Excitatory synapse, Cortex (anatomy), medicine, Excitatory postsynaptic potential, Biology, Inhibitory postsynaptic potential, Neuroscience, Subclass
Abstract

To elucidate cortical microcircuit structure and synaptic properties we present a unique, extensive, and public synaptic physiology dataset and analysis platform. Through its application, we reveal principles that relate cell type to synapse properties and intralaminar circuit organization in the mouse and human cortex. The dynamics of excitatory synapses align with the postsynaptic cell subclass, whereas inhibitory synapse dynamics partly align with presynaptic cell subclass but with considerable overlap. Despite these associations, synaptic properties are heterogeneous in most subclass to subclass connections. The two main axes of heterogeneity are strength and variability. Cell subclasses divide along the variability axis, while the strength axis accounts for significant heterogeneity within the subclass. In human cortex, excitatory to excitatory synapse dynamics are distinct from those in mouse and short-term plasticity varies with depth across layers 2 and 3. With a novel connectivity analysis that enables fair comparisons between circuit elements, we find that intralaminar connection probability among cell subclasses exhibits a strong layer dependence.These and other findings combined with the analysis platform create new opportunities for the neuroscience community to advance our understanding of cortical microcircuits.

Published
2021
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5. Human cortical expansion involves diversification and specialization of supragranular intratelencephalic-projecting neurons

Author

Sergey L. Gratiy, Sara Kebede, Chris Hill, Clare Gamlin, Jeffrey G. Ojemann, Tom Egdorf, Ed S. Lein, Lydia Potekhina, Alice Mukora, Shea Ransford, Matthew Mallory, Tim S. Heistek, Jonathan T. Ting, Gábor Tamás, Philip C. De Witt Hamer, Rebecca de Frates, Medea McGraw, Gábor Molnár, Jim Berg, Szabina Furdan, Patrick R. Hof, Natalia A. Goriounova, David Feng, David Reid, Elliot R. Thomsen, Michael Tieu, Katelyn Ward, C. Dirk Keene, Florence D’Orazi, Mean Hwan Kim, Daniel Park, Amy Torkelson, Agata Budzillo, Katherine Baker, Michael Hawrylycz, Krissy Brouner, Andrew L. Ko, DiJon Hill, Kyla Berry, Peter Chong, Jessica Trinh, Desiree A. Marshall, Katherine E. Link, Brian Lee, Jasmine Bomben, Aaron Szafer, Gabe J. Murphy, Viktor Szemenyei, Madie Hupp, Lauren Alfiler, Nick Dee, Zizhen Yao, Luke Esposito, Tamara Casper, Erica J. Melief, Susan M. Sunkin, Lindsay Ng, Hongkui Zeng, Pál Barzó, Allison Beller, Lydia Ng, Charles Cobbs, Darren Bertagnolli, Kiet Ngo, Bosiljka Tasic, John W. Phillips, Christine Rimorin, Alex M. Henry, Aaron Oldre, Michelle Maxwell, Wayne Wakeman, Delissa McMillen, Amanda Gary, Tsega Desta, Nathan Hansen, Hong Gu, Julie Nyhus, Staci A. Sorensen, Gáspár Oláh, Thomas Chartrand, Kirsten Crichton, Matthew Kroll, Josef Sulc, Jeremy A. Miller, Amy Bernard, Lisa Kim, Herman Tung, Idan Segev, Kristen Hadley, David Sandman, Anoop P. Patel, Colin Farrell, Allan R. Jones, Lisa Keene, Sander Idema, Changkyu Lee, Stephanie Mok, Augustin Ruiz, Caitlin S. Latimer, Tim Jarsky, Kris Bickley, Anton Arkhipov, Ramkumar Rajanbabu, Thomas Braun, Costas A. Anastassiou, Anatoly Buchin, Nathan W. Gouwens, Philip R. Nicovich, Richard G. Ellenbogen, Olivia Fong, Grace Williams, Rachel Enstrom, Rachel A. Dalley, Daniel L. Silbergeld, Attila Ozsvár, Kimberly A. Smith, Ryder P. Gwinn, Songlin Ding, Rafael Yuste, Manuel Ferreira, Victoria Omstead, Samuel Dingman Lee, Norbert Mihut, Hanchuan Peng, Brian E. Kalmbach, Eliza Barkan, Melissa Gorham, Boaz P. Levi, Trygve E. Bakken, Jeff Goldy, Djai B. Heyer, Nadezhda Dotson, Rusty Mann, Rebecca D. Hodge, Christof Koch, René Wilbers, Leona Mezei, Eline J. Mertens, Jae-Geun Yoon, Anna A. Galakhova, Christina A. Pom, Trangthanh Pham, Alexandra Glandon, Christiaan P. J. de Kock, Lucas T. Graybuck, and Huibert D. Mansvelder

Subjects
0303 health sciences, Cell type, Neocortex, Neurofilament, Biology, Transcriptome, 03 medical and health sciences, Glutamatergic, 0302 clinical medicine, medicine.anatomical_structure, Cortex (anatomy), Specialization (functional), medicine, Neuroscience, 030217 neurology & neurosurgery, Function (biology), 030304 developmental biology
Abstract

The neocortex is disproportionately expanded in human compared to mouse, both in its total volume relative to subcortical structures and in the proportion occupied by supragranular layers that selectively make connections within the cortex and other telencephalic structures. Single-cell transcriptomic analyses of human and mouse cortex show an increased diversity of glutamatergic neuron types in supragranular cortex in human and pronounced gradients as a function of cortical depth. To probe the functional and anatomical correlates of this transcriptomic diversity, we describe a robust Patch-seq platform using neurosurgically-resected human tissues. We characterize the morphological and physiological properties of five transcriptomically defined human glutamatergic supragranular neuron types. Three of these types have properties that are specialized compared to the more homogeneous properties of transcriptomically defined homologous mouse neuron types. The two remaining supragranular neuron types, located exclusively in deep layer 3, do not have clear mouse homologues in supragranular cortex but are transcriptionally most similar to deep layer mouse intratelencephalic-projecting neuron types. Furthermore, we reveal the transcriptomic types in deep layer 3 that express high levels of non-phosphorylated heavy chain neurofilament protein that label long-range neurons known to be selectively depleted in Alzheimer’s disease. Together, these results demonstrate the power of transcriptomic cell type classification, provide a mechanistic underpinning for increased complexity of cortical function in human cortical evolution, and implicate discrete transcriptomic cell types as selectively vulnerable in disease.

Published
2020
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6. Toward an integrated classification of neuronal cell types: morphoelectric and transcriptomic characterization of individual GABAergic cortical neurons

Author

David Feng, Jessica Trinh, Tamara Casper, Lisa Kim, Rohan Gala, Clare Gamlin, Matthew Kroll, Uygar Sümbül, Lauren Alfiler, Thomas Braun, Jasmine Bomben, Bosiljka Tasic, Colin Farrell, Hongkui Zeng, Lydia Potekhina, Tsega Desta, Kiet Ngo, Lydia Ng, Alice Mukora, Fahimeh Baftizadeh, Aaron Szafer, Rachel A. Dalley, Shea Ransford, Changkyu Lee, Nick Dee, Brian Lee, Kirsten Crichton, Luke Esposito, Miranda Robertson, Josef Sulc, Alex M. Henry, Darren Bertagnolli, Tom Egdorf, Nadezhda Dotson, Zhi Zhou, Jim Berg, Philip R. Nicovich, Rusty Mann, Madie Hupp, Daniel Park, Delissa McMillen, Samuel Dingman Lee, Agata Budzillo, Eliza Barkan, Olivia Fong, Thanh Pham, Jeff Goldy, Ed S. Lein, Rebecca de Frates, Kimberly A. Smith, Amy Torkelson, Tim Jarsky, Michelle Maxwell, Michael Tieu, Susan M. Sunkin, Michael Hawrylycz, Lucas T. Graybuck, Herman Tung, David Reid, DiJon Hill, Alexandra Glandon, Kara Ronellenfitch, Aaron Oldre, Amanda Gary, Nathan W. Gouwens, Christof Koch, Alice Pom, Wayne Wakeman, Sara Kebede, Matthew Mallory, Tae Kyung Kim, Tanya L. Daigle, Kris Bickley, Anton Arkhipov, Osnat Penn, Staci A. Sorensen, Rachel Enstrom, Hanchuan Peng, Ramkumar Rajanbabu, Jonathan T. Ting, Zizhen Yao, Lauren Ellingwood, Medea McGraw, Gabe J. Murphy, Katherine Baker, Krissy Brouner, Hong Gu, David Sandman, Katelyn Ward, Kyla Berry, Katherine E. Link, Lindsay Ng, Christine Rimorin, Kristen Hadley, Augustin Ruiz, Grace Williams, and Melissa Gorham

Subjects
Transcriptome, Electrophysiology, Cell type, medicine.anatomical_structure, Visual cortex, Interneuron, nervous system, genetic structures, medicine, GABAergic, Cortical neurons, Biology, Neuroscience
Abstract

Neurons are frequently classified into distinct groups or cell types on the basis of structural, physiological, or genetic attributes. To better constrain the definition of neuronal cell types, we characterized the transcriptomes and intrinsic physiological properties of over 3,700 GABAergic mouse visual cortical neurons and reconstructed the local morphologies of 350 of those neurons. We found that most transcriptomic types (t-types) occupy specific laminar positions within mouse visual cortex, and many of those t-types exhibit consistent electrophysiological and morphological features. We observed that these properties could vary continuously between t-types, which limited the ability to predict specific t-types from other data modalities. Despite that, the data support the presence of at least 20 interneuron met-types that have congruent morphological, electrophysiological, and transcriptomic properties.HighlightsPatch-seq data obtained from >3,700 GABAergic cortical interneuronsComprehensive characterization of morpho-electric features of transcriptomic types20 interneuron met-types that have congruent properties across data modalitiesDifferent Sst met-types preferentially innervate different cortical layers

Published
2020
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7. Toward an Integrated Classification of Cell Types: Morphoelectric and Transcriptomic Characterization of Individual GABAergic Cortical Neurons

Author

Kimberly A. Smith, Matthew Kroll, Sara Kebede, Susan M. Sunkin, David Reid, Nadezhda Dotson, Rusty Mann, DiJon Hill, Kara Ronellenfitch, Shea Ransford, Hongkui Zeng, David Feng, Jasmine Bomben, Bosiljka Tasic, Rachel Enstrom, Jessica Trinh, Matthew Mallory, Aaron Szafer, Rachel A. Dalley, Aaron Oldre, Amanda Gary, Eliza Barkan, Nick Dee, Lydia Ng, Tae Kyung Kim, Ed S. Lein, Colin Farrell, Tamara Casper, Tom Egdorf, Kirsten Crichton, Josef Sulc, Fahimeh Baftizadeh, Katelyn Ward, Kirsten Hadley, Alex M. Henry, Alice Pom, Brian Lee, Uygar Sümbül, Lisa Kim, Tim Jarsky, Madie Happ, Wayne Wakeman, Lauren Ellingwood, Luke Esposito, Daniel Park, Tanya L. Daigle, Darren Bertagnolli, Lucas T. Graybuck, Olivia Fong, Philip R. Nicovich, Gabe J. Murphy, Michelle Maxwell, Lindsay Ng, Rebeeca de Frates, Rohan Gala, Alice Mukora, Delissa McMillen, Miranda Robertson, Thanh Pham, Samuel Dingman Lee, Kris Bickley, Anton Arkhipov, Osnat Penn, Staci A. Sorensen, Alexandra Glandon, Zizhen Yao, Amy Torkelson, Jonathan T. Ting, Lauren Alfiler, Ramkumar Rajanbabu, Kiet Ngo, Kirssy Brouner, David Sandman, Michael Tieu, Michael Hawrylycz, Nathan W. Gouwens, Hanchuan Peng, Zhi Zhou, Jeff Goldy, Hong Gu, Herman Tung, Medea McGraw, Lyida Potekhina, Katherine Baker, Tsega Desta, Christof Koch, Changkyu Lee, Melissa Gorham, Clare Gamlin, Augustin Ruiz, Grace Williams, Jim Berg, Kyla Berry, Katherine E. Link, Agata Budzillo, Christine Rimorin, and Thomas Braun

Subjects
Cell type, genetic structures, Interneuron, Cortical neurons, Biology, Transcriptome, Electrophysiology, medicine.anatomical_structure, Visual cortex, nervous system, medicine, biology.protein, GABAergic, Neuroscience, Parvalbumin
Abstract

Neurons are frequently classified into distinct groups or cell types on the basis of structural, physiological, or genetic attributes. To better constrain the definition of neuronal cell types, we characterized the transcriptomes and intrinsic physiological properties of over 3,700 GABAergic mouse visual cortical neurons and reconstructed the local morphologies of 350 of those neurons. We found that most transcriptomic types (t-types) occupy specific laminar positions within mouse visual cortex, and many of those t-types exhibit consistent electrophysiological and morphological features. We observed that these properties could vary continuously between t- types, which limited the ability to predict specific t-types from other data modalities. Despite that, the data support the presence of at least 20 interneuron met-types that have congruent morphological, electrophysiological, and transcriptomic properties.

Published
2020
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8. Integrated Morphoelectric and Transcriptomic Classification of Cortical GABAergic Cells

Author

Kris Bickley, Anton Arkhipov, Osnat Penn, Hanchuan Peng, Shea Ransford, Sara Kebede, Kara Ronellenfitch, Matthew Mallory, Krissy Brouner, Madie Hupp, Lydia Ng, Daniel Park, Staci A. Sorensen, Alice Pom, Susan M. Sunkin, Tanya L. Daigle, Fahimeh Baftizadeh, Wayne Wakeman, Aaron Oldre, Amanda Gary, Herman Tung, Brian Lee, Ed S. Lein, Medea McGraw, Rachel A. Dalley, Bosiljka Tasic, Hong Gu, Miranda Robertson, Katherine Baker, Lindsay Ng, David Sandman, Jasmine Bomben, Uygar Sümbül, Tae Kyung Kim, David Reid, Eliza Barkan, Luke Esposito, Kirsten Crichton, DiJon Hill, Zoran Popović, Josef Sulc, Nathan W. Gouwens, Ramkumar Rajanbabu, Lydia Potekhina, Thomas Braun, Alexandra Glandon, Tim Jarsky, Darren Bertagnolli, Tom Egdorf, Olivia Fong, Alice Mukora, Rebecca de Frates, Lauren Ellingwood, Jonathan T. Ting, Gabe J. Murphy, Katelyn Ward, Delissa McMillen, Samuel Dingman Lee, Melissa Gorham, Michelle Maxwell, Clare Gamlin, Zhi Zhou, Jeff Goldy, Rachel Enstrom, Kyla Berry, Colin Farrell, Katherine E. Link, Christine Rimorin, Zizhen Yao, Hongkui Zeng, Kristen Hadley, Augustin Ruiz, Grace Williams, Amy Torkelson, Kimberly A. Smith, Lisa Kim, Aaron Szafer, Nick Dee, Alex M. Henry, Rohan Gala, David Feng, Jessica Trinh, Tamara Casper, Matthew Kroll, Christof Koch, Michael Tieu, Michael Hawrylycz, Lauren Alfiler, Kiet Ngo, Philip R. Nicovich, Thanh Pham, Nadezhda Dotson, Rusty Mann, Tsega Desta, Lucas T. Graybuck, Changkyu Lee, Jim Berg, and Agata Budzillo

Subjects
0303 health sciences, Cell type, biology, Interneuron, General Biochemistry, Genetics and Molecular Biology, Transcriptome, 03 medical and health sciences, Electrophysiology, 0302 clinical medicine, medicine.anatomical_structure, Visual cortex, medicine, biology.protein, GABAergic, Axon, Neuroscience, 030217 neurology & neurosurgery, Parvalbumin, 030304 developmental biology
Abstract

Neurons are frequently classified into distinct types on the basis of structural, physiological, or genetic attributes. To better constrain the definition of neuronal cell types, we characterized the transcriptomes and intrinsic physiological properties of over 4,200 mouse visual cortical GABAergic interneurons and reconstructed the local morphologies of 517 of those neurons. We find that most transcriptomic types (t-types) occupy specific laminar positions within visual cortex, and, for most types, the cells mapping to a t-type exhibit consistent electrophysiological and morphological properties. These properties display both discrete and continuous variation among t-types. Through multimodal integrated analysis, we define 28 met-types that have congruent morphological, electrophysiological, and transcriptomic properties and robust mutual predictability. We identify layer-specific axon innervation pattern as a defining feature distinguishing different met-types. These met-types represent a unified definition of cortical GABAergic interneuron types, providing a systematic framework to capture existing knowledge and bridge future analyses across different modalities.

Published
2020
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9. Classification of electrophysiological and morphological types in mouse visual cortex

Author

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

Subjects
Genetically modified mouse, Cell type, Cell, Laboratory mouse, Biology, Electrophysiology, chemistry.chemical_compound, Visual cortex, medicine.anatomical_structure, chemistry, Biocytin, medicine, Patch clamp, Neuroscience
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 profile morpho-electric properties of mammalian neurons systematically, 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 data sets. Intrinsic physiological and morphological properties were measured from over 1,800 neurons from the adult laboratory mouse visual cortex. Quantitative features were used to classify neurons into distinct types using unsupervised methods. We establish a taxonomy of morphologically- and electrophysiologically-defined cell types for this region of cortex with 17 e-types and 35 m-types, as well as an initial correspondence with previously-defined transcriptomic cell types using the same transgenic mouse lines.

Published
2018
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