The visual system is used for object recognition and visually guided actions. These diverse functions are generated by extracting spatial contrast, motion and chromatic cues from the visual scene and sending them to specialized circuits in the midbrain and thalamus. In the cortex the parallel input channels from the lateral geniculate nucleus converge, intermix through specific connections that create new response properties, which are sorted into distinct modules that send outputs into segregated streams of interconnected areas in dorsal and ventral extrastriate cortex. Most of this knowledge derives from groundbreaking studies in primates. At present, however, it is challenging to see how it will be experimentally possible in primates to link specific molecules, neurons and synaptic circuits to particular behaviors. Such advances appear to be critical for finding treatments for visuospatial disorders and agnosias. Many experimental tools for manipulating specific circuits are available to make progress in the mouse. These new opportunities have intensified the need to develop the mouse as model for research of networks underlying object recognition and visually guided actions. The present proposal originated from the rapidly spreading recognition that the mouse visual cortex shares basic similarities with the columnar, modular, areal and hierarchical organization of processing streams in primates. The application challenges the view that mouse primary visual cortex lacks columns and systematic maps of functionally distinct modules embodied in the daisy architecture of horizontal connections. We have arrived at this perspective by first finding that mouse visual cortex contains almost a dozen distinct areas which were recently shown to be functionally specialized. Our findings suggest that these diverse cortical properties emerge from parallel geniculocortical channels, specialized for the processing of spatial detail and rapidly changing stimuli. Further, we have found that within the cortex these inputs are distributed into dorsal and ventral streams of interconnected areas. Most recently we have discovered that mouse primary visual cortex contains a systematic array of type 2 muscarinic acetylcholine receptor expressing modules, which organize geniculocortical inputs, local horizontal connections within V1 and feedback pathways from higher visual areas. Our preliminary results demonstrate that these modules are functionally specialized and are differentially connected to dorsal and ventral streams. Thus, we hypothesize that modules play a role in mixing, sorting and sending distinct information into temporal circuits for object recognition and posterior parietal networks for visually guided actions. To test this general hypothesis we propose to determine by: 1) anatomical tracing and weight analysis of the inputs and outputs of V1 modules, 2) channelrhodopsin-assisted circuit mapping whether anatomical connections represent synaptic connections of a specific strength, and 3) single unit recordings whether modules have distinct receptive field properties.

Public Health Relevance

The visual system is used for object recognition and visually guided actions. In primates these functions are extracted from retinal cues about the spatial contrast and motion content of the visual scene. In the primary visual cortex this process involves the mixing of parallel inputs in layers and modules as well as the distribution of outputs to dorsal and ventral streams formed by connections between higher cortical areas. Similar to primates, we have found that mouse visual cortex has a modular architecture. This provides the exciting opportunity to study in experimentally more tractable mice, the structure of the network(s) by which subcortical inputs are transformed in the cortex, new response properties are generated and outputs to higher cortical areas lead to distinct behaviors. We therefore propose to study in mouse visual cortex the structure of the modular static network, its dynamic synaptic connectivity and visual response properties. If successful, the project will show that the mouse is a suitable model for visual neuroscience that can be used for studies of circuits that are altered in agnosias and visuospatial disorders.

Agency
National Institute of Health (NIH)
Institute
National Eye Institute (NEI)
Type
Research Project (R01)
Project #
1R01EY022090-01A1
Application #
8438125
Study Section
Special Emphasis Panel (SPC)
Program Officer
Steinmetz, Michael A
Project Start
2013-01-01
Project End
2017-12-31
Budget Start
2013-01-01
Budget End
2013-12-31
Support Year
1
Fiscal Year
2013
Total Cost
$380,000
Indirect Cost
$130,000
Name
Washington University
Department
Neurosciences
Type
Schools of Medicine
DUNS #
068552207
City
Saint Louis
State
MO
Country
United States
Zip Code
63130
G?m?nu?, R?zvan; Kennedy, Henry; Toroczkai, Zoltán et al. (2018) The Mouse Cortical Connectome, Characterized by an Ultra-Dense Cortical Graph, Maintains Specificity by Distinct Connectivity Profiles. Neuron 97:698-715.e10
Horvát, Szabolcs; G?m?nu?, R?zvan; Ercsey-Ravasz, Mária et al. (2016) Spatial Embedding and Wiring Cost Constrain the Functional Layout of the Cortical Network of Rodents and Primates. PLoS Biol 14:e1002512
Barth, Alison; Burkhalter, Andreas; Callaway, Edward M et al. (2016) Comment on ""Principles of connectivity among morphologically defined cell types in adult neocortex"". Science 353:1108
D'Souza, Rinaldo David; Meier, Andrew Max; Bista, Pawan et al. (2016) Recruitment of inhibition and excitation across mouse visual cortex depends on the hierarchy of interconnecting areas. Elife 5:
Ji, Weiqing; G?m?nu?, R?zvan; Bista, Pawan et al. (2015) Modularity in the Organization of Mouse Primary Visual Cortex. Neuron 87:632-43
Wang, Quanxin; Burkhalter, Andreas (2013) Stream-related preferences of inputs to the superior colliculus from areas of dorsal and ventral streams of mouse visual cortex. J Neurosci 33:1696-705
Yang, Weiguo; Carrasquillo, Yarimar; Hooks, Bryan M et al. (2013) Distinct balance of excitation and inhibition in an interareal feedforward and feedback circuit of mouse visual cortex. J Neurosci 33:17373-84