Chronically-implanted Neuropixels probes enable high yield recordings in freely moving mice: dataset

The advent of high-yield electrophysiology using Neuropixels probes is now enabling researchers to simultaneously record hundreds of neurons with remarkably high signal to noise. However, these probes have not been well-suited to use in freely moving mice. It is critical to study neural activity in unrestricted animals for many reasons, such as leveraging ethological approaches to study neural circuits. We designed and implemented a novel device that allows Neuropixels probes to be customized for chronically-implanted experiments in freely moving mice. We demonstrate the ease and utility of this approach in recording hundreds of neurons during an ethological behavior across weeks of experiments. We provide the technical drawings and procedures for other researchers to do the same. Importantly, our approach enables researchers to explant and reuse these valuable probes, a transformative step which has not been established for recordings with any type of chronically-implanted probe

Chronically-implanted Neuropixels probes enable high yield recordings in freely moving mice

The advent of high-yield electrophysiology using Neuropixels probes is now enabling researchers to simultaneously record hundreds of neurons with remarkably high signal to noise. However, these probes have not been well-suited to use in freely moving mice. It is critical to study neural activity in unrestricted animals for many reasons, such as leveraging ethological approaches to study neural circuits. We designed and implemented a novel device that allows Neuropixels probes to be customized for chronically-implanted experiments in freely moving mice. We demonstrate the ease and utility of this approach in recording hundreds of neurons during an ethological behavior across weeks of experiments. We provide the technical drawings and procedures for other researchers to do the same. Importantly, our approach enables researchers to explant and reuse these valuable probes, a transformative step which has not been established for recordings with any type of chronically-implanted probe

A systematic topographical relationship between mouse lateral posterior thalamic neurons and their visual cortical projection targets.

Higher-order visual thalamus communicates broadly and bi-directionally with primary and extrastriate cortical areas in various mammals. In primates, the pulvinar is a topographically and functionally organized thalamic nucleus that is largely dedicated to visual processing. Still, a more granular connectivity map is needed to understand the role of thalamocortical loops in visually guided behavior. Similarly, the secondary visual thalamic nucleus in mice (the lateral posterior nucleus, LP) has extensive connections with cortex. To resolve the precise connectivity of these circuits, we first mapped mouse visual cortical areas using intrinsic signal optical imaging and then injected fluorescently tagged retrograde tracers (cholera toxin subunit B) into retinotopically-matched locations in various combinations of seven different visual areas. We find that LP neurons representing matched regions in visual space but projecting to different extrastriate areas are found in different topographically organized zones, with few double-labeled cells (~4-6%). In addition, V1 and extrastriate visual areas received input from the ventrolateral part of the laterodorsal nucleus of the thalamus (LDVL). These observations indicate that the thalamus provides topographically organized circuits to each mouse visual area and raise new questions about the contributions from LP and LDVL to cortical activity

Neuromatch Academy: Teaching Computational Neuroscience with Global Accessibility

Neuromatch Academy (NMA) designed and ran a fully online 3-week Computational Neuroscience Summer School for 1757 students with 191 teaching assistants (TAs) working in virtual inverted (or flipped) classrooms and on small group projects. Fourteen languages, active community management, and low cost allowed for an unprecedented level of inclusivity and universal accessibility

Neuromatch Academy: Teaching Computational Neuroscience with global accessibility

Neuromatch Academy designed and ran a fully online 3-week Computational Neuroscience summer school for 1757 students with 191 teaching assistants working in virtual inverted (or flipped) classrooms and on small group projects. Fourteen languages, active community management, and low cost allowed for an unprecedented level of inclusivity and universal accessibility.Comment: 10 pages, 3 figures. Equal contribution by the executive committee members of Neuromatch Academy: Tara van Viegen, Athena Akrami, Kate Bonnen, Eric DeWitt, Alexandre Hyafil, Helena Ledmyr, Grace W. Lindsay, Patrick Mineault, John D. Murray, Xaq Pitkow, Aina Puce, Madineh Sedigh-Sarvestani, Carsen Stringer. and equal contribution by the board of directors of Neuromatch Academy: Gunnar Blohm, Konrad Kording, Paul Schrater, Brad Wyble, Sean Escola, Megan A. K. Peter

Pattern and Component Motion Responses in Mouse Visual Cortical Areas

© 2015 Elsevier Ltd. Spanning about 9mm2 of the posterior cortex surface, the mouse's small but organized visual cortex has recently gained attention for its surprising sophistication and experimental tractability [1-3]. Though it lacks the highly ordered orientation columns of primates [4], mouse visual cortex is organized retinotopically [5] and contains at least ten extrastriate areas that likely integrate more complex visual features via dorsal and ventral streams of processing [6-14]. Extending our understanding of visual perception to the mouse model is justified by the evolving ability to interrogate specific neural circuits using genetic and molecular techniques [15, 16]. In order to probe the functional properties of the putative mouse dorsal stream, we used moving plaids, which demonstrate differences between cells that identify local motion (component cells) and those that integrate global motion of the plaid (pattern cells; Figure1A; [17]). In primates, there are sparse pattern cell responses in primate V1 [18, 19], but many more in higher-order regions; 25%-30% of cells in MT [17] and 40%-60% in MST [20] are pattern direction selective. We present evidence that mice have small numbers of pattern cells in areas LM and RL, while V1, AL, and AM are largely component-like. Although the proportion of pattern cells is smaller in mouse visual cortex than in primate MT, this study provides evidence that the organization of the mouse visual system shares important similarities to that of primates and opens the possibility of using mice to probe motion computation mechanisms. Juavinett etal. expand on the growing interest of the mouse as a model for visual neuroscience, demonstrating that cells in two areas of mouse visual cortex can compute the global motion of a plaid. The report of these pattern direction cells in areas LM and RL, but not V1, AL, or AM, further delineates dorsal and ventral streams in the mouse

Pathways and Cell Types Underlying Visual Perception in the Mouse

The primary challenge of systems neuroscience is identifying the circuits and cell types that underlie sensation and behavior. Faced with the daunting task of unraveling six layers of cortex, a hierarchy of visual areas, and a multitude of cell types, visual neuroscience relies on innovative technologies to achieve a circuit-level understanding of perceptual phenomena. This dissertation aims to be an extension of this effort by using advanced tools to address several longstanding questions regarding the structure and function of the visual system. In the past decade, mouse visual cortex has come to the forefront of systems neuroscience, serving as a common ground to study the role of cell types in behavior. Armed with a remarkable arsenal of genetic and molecular tools in transgenic mice, we are poised to observe and manipulate visual circuits in a cell-type specific manner. Yet doing so requires a comprehensive understanding of the system at hand. In the work presented here, I extend our knowledge of the mouse visual system so that we may exploit its experimental advantages to address circuit-level questions. Spanning multiple techniques and circuits, this dissertation investigates the mouse visual system from several angles. First, it refines our understanding of mouse visual cortex functional organization with bulk loaded calcium indicators and a well-studied higher-order stimulus, moving plaids (Chapter 1). Secondly, it characterizes the functional response properties of three different genetically defined layer 5 cell types, using in vivo two-photon imaging in the primary visual cortex (Chapter 2). Lastly, it delineates the topography of thalamocortical projections from the secondary visual thalamic nucleus (LP) to multiple visual cortical areas with classic tracing methods as well as novel viral combinations (Chapter 3). Together, these three studies advance our understanding of the connectivity and function of the mouse visual system, bringing us closer to bridging neurons and behavior

Pathways and Cell Types Underlying Visual Perception in the Mouse

The primary challenge of systems neuroscience is identifying the circuits and cell types that underlie sensation and behavior. Faced with the daunting task of unraveling six layers of cortex, a hierarchy of visual areas, and a multitude of cell types, visual neuroscience relies on innovative technologies to achieve a circuit-level understanding of perceptual phenomena. This dissertation aims to be an extension of this effort by using advanced tools to address several longstanding questions regarding the structure and function of the visual system. In the past decade, mouse visual cortex has come to the forefront of systems neuroscience, serving as a common ground to study the role of cell types in behavior. Armed with a remarkable arsenal of genetic and molecular tools in transgenic mice, we are poised to observe and manipulate visual circuits in a cell-type specific manner. Yet doing so requires a comprehensive understanding of the system at hand. In the work presented here, I extend our knowledge of the mouse visual system so that we may exploit its experimental advantages to address circuit-level questions. Spanning multiple techniques and circuits, this dissertation investigates the mouse visual system from several angles. First, it refines our understanding of mouse visual cortex functional organization with bulk loaded calcium indicators and a well-studied higher-order stimulus, moving plaids (Chapter 1). Secondly, it characterizes the functional response properties of three different genetically defined layer 5 cell types, using in vivo two-photon imaging in the primary visual cortex (Chapter 2). Lastly, it delineates the topography of thalamocortical projections from the secondary visual thalamic nucleus (LP) to multiple visual cortical areas with classic tracing methods as well as novel viral combinations (Chapter 3). Together, these three studies advance our understanding of the connectivity and function of the mouse visual system, bringing us closer to bridging neurons and behavior

Pattern and Component Motion Responses in Mouse Visual Cortical Areas

SummarySpanning about 9 mm2 of the posterior cortex surface, the mouse’s small but organized visual cortex has recently gained attention for its surprising sophistication and experimental tractability [1–3]. Though it lacks the highly ordered orientation columns of primates [4], mouse visual cortex is organized retinotopically [5] and contains at least ten extrastriate areas that likely integrate more complex visual features via dorsal and ventral streams of processing [6–14]. Extending our understanding of visual perception to the mouse model is justified by the evolving ability to interrogate specific neural circuits using genetic and molecular techniques [15, 16]. In order to probe the functional properties of the putative mouse dorsal stream, we used moving plaids, which demonstrate differences between cells that identify local motion (component cells) and those that integrate global motion of the plaid (pattern cells; Figure 1A; [17]). In primates, there are sparse pattern cell responses in primate V1 [18, 19], but many more in higher-order regions; 25%–30% of cells in MT [17] and 40%–60% in MST [20] are pattern direction selective. We present evidence that mice have small numbers of pattern cells in areas LM and RL, while V1, AL, and AM are largely component-like. Although the proportion of pattern cells is smaller in mouse visual cortex than in primate MT, this study provides evidence that the organization of the mouse visual system shares important similarities to that of primates and opens the possibility of using mice to probe motion computation mechanisms