Deciphering Pyramidal Neuron Diversity: Delineating Perceptual Functions of Projection-Defined Neuronal Types
Authors: Ning-long Xu
Journal: Neuron (2020)

Axonal projection patterns are increasingly recognized as a defining feature for neuronal classification. How could such structural distinctions be linked to functions? In this issue of Neuron, Tang and Higley, 2020Tang L. Higley M.J. Layer 5 Circuits in V1 Differentially Control Visuomotor Behavior.Neuron. 2020; 105 (this issue): 346-354Abstract Full Text Full Text PDF PubMed Scopus (29) Google Scholar disambiguate behavior-level functions of two projection-defined subtypes of cortical projection neurons. Axonal projection patterns are increasingly recognized as a defining feature for neuronal classification. How could such structural distinctions be linked to functions? In this issue of Neuron, Tang and Higley, 2020Tang L. Higley M.J. Layer 5 Circuits in V1 Differentially Control Visuomotor Behavior.Neuron. 2020; 105 (this issue): 346-354Abstract Full Text Full Text PDF PubMed Scopus (29) Google Scholar disambiguate behavior-level functions of two projection-defined subtypes of cortical projection neurons. Understanding neuronal diversity in the nervous system has been a major challenge in neurobiology ever since the seminal work by Ramon y Cajal, whose work largely focused on morphological classification of neurons. In the past two decades, the diversity of GABAergic interneurons in the cerebral cortex received ample attention (Kepecs and Fishell, 2014Kepecs A. Fishell G. Interneuron cell types are fit to function.Nature. 2014; 505: 318-326Crossref PubMed Scopus (645) Google Scholar). With a rich spectrum of molecular and genetic tools being developed to target specific subtypes of GABAergic interneurons (Taniguchi et al., 2011Taniguchi H. He M. Wu P. Kim S. Paik R. Sugino K. Kvitsiani D. Fu Y. Lu J. Lin Y. et al.A resource of Cre driver lines for genetic targeting of GABAergic neurons in cerebral cortex.Neuron. 2011; 71: 995-1013Abstract Full Text Full Text PDF PubMed Scopus (1145) Google Scholar), understanding of the diversity of GABAergic interneurons in the cerebral cortex has been substantially advanced (Kepecs and Fishell, 2014Kepecs A. Fishell G. Interneuron cell types are fit to function.Nature. 2014; 505: 318-326Crossref PubMed Scopus (645) Google Scholar). But until recently, excitatory pyramidal neurons in the cerebral cortex have been considered to be more or less homogeneous, with their subtype diversity less appreciated. Cortical pyramidal neurons are most commonly classified according to their soma locations, e.g., the layer 2/3 neurons and layer 5 neurons in the neocortex and the CA1 and CA3 neurons in the hippocampus. Within a local cortical region, pyramidal neurons resemble each other in their somatodendritic morphology, such that the local morphological features are not informative enough for cell-type classification, which might have in turn hindered the development of molecular and genetic strategies to target different subtypes of pyramidal neurons. However, single-cell RNA sequencing of mouse cortical neurons showed that there are 19 types of glutamatergic neurons and 23 types GABAergic neurons among the transcriptome-defined cell types (Tasic et al., 2016Tasic B. Menon V. Nguyen T.N. Kim T.K. Jarsky T. Yao Z. Levi B. Gray L.T. Sorensen S.A. Dolbeare T. et al.Adult mouse cortical cell taxonomy revealed by single cell transcriptomics.Nat. Neurosci. 2016; 19: 335-346Crossref PubMed Scopus (908) Google Scholar), suggesting that the cortical excitatory neurons are no less diverse than the GABAergic interneurons. How could we better understand the subtype diversity of excitatory projection neurons in the cerebral cortex? First, it is important to recognize the distinct computational roles of excitatory projection neurons from those of GABAergic interneurons in the cortical circuits. Whereas the interneurons play key roles coordinating local circuits within a functionally and anatomically confined subregions and exhibit contrastingly different local morphological features, the pyramidal neurons are responsible for computations at greater spatial scales, transforming signals across different, often distant, brain regions; they either broadcast information received from a common source to divergent downstream regions or integrate diverse inputs to impact a common downstream target. From this perspective, the input-output connectivity or long-range projection patterns can be more relevant features for defining subtypes of projection neurons. Indeed, efforts have been made in earlier studies to understand the heterogeneity within layer 5 projection neurons by linking projection patterns with intrinsic electrophysiological properties (Hattox and Nelson, 2007Hattox A.M. Nelson S.B. Layer V neurons in mouse cortex projecting to different targets have distinct physiological properties.J. Neurophysiol. 2007; 98: 3330-3340Crossref PubMed Scopus (252) Google Scholar). More recently, using projection-based analysis to classify subtypes of pyramidal neurons and to identify their functional distinctions has grown into a fruitful trend. For example, the projection-specific subtypes of deep-layer cortical neurons in the frontal motor cortex play distinct roles in motor planning (Li et al., 2015Li N. Chen T.-W. Guo Z.V. Gerfen C.R. Svoboda K. A motor cortex circuit for motor planning and movement.Nature. 2015; 519: 51-56Crossref PubMed Scopus (289) Google Scholar). Greater efforts are being made to characterize long-range projection patterns using whole-brain single-neuron reconstruction (Winnubst et al., 2019Winnubst J. Bas E. Ferreira T.A. Wu Z. Economo M.N. Edson P. Arthur B.J. Bruns C. Rokicki K. Schauder D. et al.Reconstruction of 1,000 Projection Neurons Reveals New Cell Types and Organization of Long-Range Connectivity in the Mouse Brain.Cell. 2019; 179: 268-281.e13Abstract Full Text Full Text PDF PubMed Scopus (171) Google Scholar). An elegant study recently characterized brain-wide input patterns of three subtypes of layer 5 projection neurons in the visual cortex that differ in their projection targets using bacterial artificial chromosome Cre transgenic mouse lines (Kim et al., 2015Kim E.J. Juavinett A.L. Kyubwa E.M. Jacobs M.W. Callaway E.M. Three Types of Cortical Layer 5 Neurons That Differ in Brain-wide Connectivity and Function.Neuron. 2015; 88: 1253-1267Abstract Full Text Full Text PDF PubMed Scopus (157) Google Scholar), linking input and output connectivity organizations for different subtypes of layer 5 neurons. Yet we are still in the early stages of understanding the diversity of cortical projection neurons. Linking different subtypes with behaviorally relevant functions still represents a major challenge. Meanwhile, efficiently targeting specific subtypes of pyramidal neurons for recording or manipulation is also non-trivial because of limited availability of mouse driver lines, as opposed to those available for GABAergic interneurons (Taniguchi et al., 2011Taniguchi H. He M. Wu P. Kim S. Paik R. Sugino K. Kvitsiani D. Fu Y. Lu J. Lin Y. et al.A resource of Cre driver lines for genetic targeting of GABAergic neurons in cerebral cortex.Neuron. 2011; 71: 995-1013Abstract Full Text Full Text PDF PubMed Scopus (1145) Google Scholar). The Glt25d2-Cre line used in the Kim et al., 2015Kim E.J. Juavinett A.L. Kyubwa E.M. Jacobs M.W. Callaway E.M. Three Types of Cortical Layer 5 Neurons That Differ in Brain-wide Connectivity and Function.Neuron. 2015; 88: 1253-1267Abstract Full Text Full Text PDF PubMed Scopus (157) Google Scholar study identifies cortico-subcortical projection neurons but does not distinguish between different subcortical targets. In the current issue of Neuron, Tang and Higley, 2020Tang L. Higley M.J. Layer 5 Circuits in V1 Differentially Control Visuomotor Behavior.Neuron. 2020; 105 (this issue): 346-354Abstract Full Text Full Text PDF PubMed Scopus (29) Google Scholar presented a timely study to address these issues. They employed a projection-based retrograde labeling technique that effectively identified two non-overlapping subpopulations of layer 5 neurons in the visual cortex that projected to distinct subcortical targets. Crucially, they established an effective paradigm to assess the functional relevance of the identified subpopulations of cortical projection neurons in simple yet fundamental sensorimotor behavior. Tang and Higley, 2020Tang L. Higley M.J. Layer 5 Circuits in V1 Differentially Control Visuomotor Behavior.Neuron. 2020; 105 (this issue): 346-354Abstract Full Text Full Text PDF PubMed Scopus (29) Google Scholar first used retrograde labeling methods to establish that the pons-projecting neurons and the striatum-projecting neurons are non-overlapping subpopulations, even though their cell bodies are commingled in the primary visual cortex (V1). This result supports the effectiveness of using the projection-based approach in separating subpopulations of projection neurons that are otherwise difficult to differentiate based on somatodendritic structures. An important but even more puzzling problem is that both the pons-projecting neurons and the striatum-projecting neurons are likely involved in sensorimotor functions, since both are routing information to subcortical motor-related regions. How could these two subpopulations of neurons be functionally distinguished at the behavioral level? Tang and Higley, 2020Tang L. Higley M.J. Layer 5 Circuits in V1 Differentially Control Visuomotor Behavior.Neuron. 2020; 105 (this issue): 346-354Abstract Full Text Full Text PDF PubMed Scopus (29) Google Scholar reasoned that the pons projection neurons may direct sensory information through the pons to the cerebellum, which is known to be critically involved in eyeblink conditioning. Thus, it is possible that a behavioral paradigm involving a visually cued eyeblink response may serve as an effective assay to test the function of the cortico-pons projection neurons. One caveat is that the classical eyeblink conditioning, when over-trained, may not necessarily involve cortical-level processing. However, if the behavioral task is carefully designed, simple and even innate motor readouts, such as eyeblink and licking, can still be used to assess perceptual functions. Here, Tang and Higley, 2020Tang L. Higley M.J. Layer 5 Circuits in V1 Differentially Control Visuomotor Behavior.Neuron. 2020; 105 (this issue): 346-354Abstract Full Text Full Text PDF PubMed Scopus (29) Google Scholar savvily avoided overtraining by first training mice using 100% visual stimulus contrast and then using varying contrasts to assess psychometric-level performance, which in theory requires perceptual-level processing. Indeed, lesion of V1 impaired the learning of this task, and acute inactivation of V1 using muscimol also impaired the contrast-dependent eyeblink responses. Interestingly, the contrast-dependent eyeblink also depended on running speed, which is known to influence visual perceptual function in mice, further supporting that this visually cued eyeblink response task involves perceptual and cortical functions. When examining the functional differences between subtypes of layer 5 projection neurons in the visual cortex, an obvious question is whether they show differential visual responses. A previous study from the same lab (Lur et al., 2016Lur G. Vinck M.A. Tang L. Cardin J.A. Higley M.J. Projection-Specific Visual Feature Encoding by Layer 5 Cortical Subnetworks.Cell Rep. 2016; 14: 2538-2545Abstract Full Text Full Text PDF PubMed Scopus (46) Google Scholar) and the study by Kim et al., 2015Kim E.J. Juavinett A.L. Kyubwa E.M. Jacobs M.W. Callaway E.M. Three Types of Cortical Layer 5 Neurons That Differ in Brain-wide Connectivity and Function.Neuron. 2015; 88: 1253-1267Abstract Full Text Full Text PDF PubMed Scopus (157) Google Scholar showed a certain level of differentiation in visual response properties between different subtypes of layer 5 projection neurons. However, without a behavioral task, it is difficult to understand how the differential visual response properties may contribute to perception and behavior. Here, Tang and Higley, 2020Tang L. Higley M.J. Layer 5 Circuits in V1 Differentially Control Visuomotor Behavior.Neuron. 2020; 105 (this issue): 346-354Abstract Full Text Full Text PDF PubMed Scopus (29) Google Scholar showed that during the contrast-dependent eyeblink behavior, the pons-projecting neurons exhibited stronger contrast-dependent visual responses than the striatum-projecting ones, suggesting an interesting logic between the projection pattern and behaviorally relevant visual functions. Indeed, the activity of pons-projecting neurons predicted the trial-by-trial behavior significantly better than the striatum-projecting neurons, suggesting that the pons-projecting neurons encode greater amounts of behavior-relevant visual information. Last but not least, would the differential encoding of behavior-related visual information in the different projection-specific subtypes really matter? Tang and Higley, 2020Tang L. Higley M.J. Layer 5 Circuits in V1 Differentially Control Visuomotor Behavior.Neuron. 2020; 105 (this issue): 346-354Abstract Full Text Full Text PDF PubMed Scopus (29) Google Scholar used optogenetics to further examine this and provided an additional, critical piece of evidence supporting the differential roles of the two subtypes of layer 5 projection neurons in visuomotor behavior. Again, they used a retrograde viral labeling strategy to express the optogenetic suppressor ArchT in either the striatum-projecting or the pons-projecting V1 neurons in different animals. They found that optogenetic suppression of the activity of the pons-projecting neurons, but not the striatum-projecting neurons, impaired the contrast-dependent eyeblink responses, providing a definitive and conclusive answer to the last question. Understanding the neuronal diversity from the perspective of the structure-function relationship has become the most important undertaking in neuroscience today. With the rapid development of high-throughput technologies, large-scale datasets are being generated (Tasic et al., 2016Tasic B. Menon V. Nguyen T.N. Kim T.K. Jarsky T. Yao Z. Levi B. Gray L.T. Sorensen S.A. Dolbeare T. et al.Adult mouse cortical cell taxonomy revealed by single cell transcriptomics.Nat. Neurosci. 2016; 19: 335-346Crossref PubMed Scopus (908) Google Scholar, Winnubst et al., 2019Winnubst J. Bas E. Ferreira T.A. Wu Z. Economo M.N. Edson P. Arthur B.J. Bruns C. Rokicki K. Schauder D. et al.Reconstruction of 1,000 Projection Neurons Reveals New Cell Types and Organization of Long-Range Connectivity in the Mouse Brain.Cell. 2019; 179: 268-281.e13Abstract Full Text Full Text PDF PubMed Scopus (171) Google Scholar), with comprehensive roadmaps aimed at joining forces across multi-disciplinary teams to examine the systematic cell-type classification in the nervous system (Zeng and Sanes, 2017Zeng H. Sanes J.R. Neuronal cell-type classification: challenges, opportunities and the path forward.Nat. Rev. Neurosci. 2017; 18: 530-546Crossref PubMed Scopus (359) Google Scholar). Nonetheless, we are still at an early stage in deciphering neuronal diversity, especially for the excitatory projection neurons, the major computational units in the brain. Perhaps, as a complement to the large-scale “data-driven” approach, studies such as the one by Tang and Higley, 2020Tang L. Higley M.J. Layer 5 Circuits in V1 Differentially Control Visuomotor Behavior.Neuron. 2020; 105 (this issue): 346-354Abstract Full Text Full Text PDF PubMed Scopus (29) Google Scholar using quantitative behavior with savvy “hypothesis-driven” experimental designs, can provide important functional verification and conceptual guidance to alleviate the intimidating complexity of cell-type classification in the brain. Layer 5 Circuits in V1 Differentially Control Visuomotor BehaviorTang et al.NeuronNovember 19, 2019In BriefTang and Higley show that corticopontine neurons in visual cortex encode sensory and motor information during a visually cued eyeblink conditioning task and are necessary for performance, highlighting the existence of physically interspersed but functionally segregated networks that control behavior. Full-Text PDF Open Archive