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Teska, A.

Publications and source records attributed to Teska, A..

2 recordsLinked to original sources

Enhancement of brain atlases with region-specific coordinate systems: flatmaps and barrel column annotations

Digital brain atlases define a hierarchy of brain regions and their locations in three-dimensional Cartesian space. They provide a standard coordinate system in which diverse datasets can be integrated for visualization and analysis. Although this coordinate system has well-defined anatomical axes, it does not provide the best context to work with the complex geometries of layered brain regions such as the neocortex. To address that, we introduce laminar coordinate systems that consider the curvature and the laminar structure of the region of interest. These new coordinate systems consist of a principal axis, locally aligned to the vertical direction and measuring depth, and two other axes that describe a flatmap, a two-dimensional representation of the horizontal extents of layers. The main property of the flatmap is that it allows seamless mapping of information back and forth between 2D and 3D spaces, in a way consistent with the principal axis. It involves a structured dimensionality reduction where information is aggregated along depth. We propose a method to enhance brain atlases with laminar coordinate systems and flatmaps based on user specifications and define a set of metrics to characterize the quality of flatmaps. We applied our method to an atlas of rat somatosensory cortex based on Paxinos and Watsons rat brain atlas, enhancing it with a laminar coordinate system adapted to the geometry of this region. Further, we applied our method to enhance the Allen Mouse Brain Atlas Common Coordinate Framework version 3 with a flatmap of the whole isocortex. We used this flatmap to produce new annotations of 33 individual barrels and barrel columns in the barrel cortex. Thanks to the properties of the flatmap, the resulting annotations are non-overlapping and follow the curvature of the cortex. Additionally, we introduced several applications highlighting the utility of laminar coordinate systems for data visualization and data-driven modeling. We provide a free software implementation of our methods for the benefit of the community.

neuroscience↗

Modeling and Simulation of Neocortical Micro- and Mesocircuitry. Part II: Physiology and Experimentation

Cortical dynamics underlie many cognitive processes and emerge from complex multi-scale interactions, which are challenging to study in vivo. Large-scale, biophysically detailed models offer a tool which can complement laboratory approaches. We present a model comprising eight somatosensory cortex subregions, 4.2 million morphological and electrically-detailed neurons, and 13.2 billion local and mid-range synapses. In silico tools enabled reproduction and extension of complex laboratory experiments under a single parameterization, providing strong validation. The model reproduced millisecond-precise stimulus-responses, stimulus-encoding under targeted optogenetic activation, and selective propagation of stimulus-evoked activity to downstream areas. The models direct correspondence with biology generated predictions about how multiscale organization shapes activity; for example, how cortical activity is shaped by high-dimensional connectivity motifs in local and mid-range connectivity, and spatial targeting rules by inhibitory subpopulations. The latter was facilitated using a rewired connectome which included specific targeting rules observed for different inhibitory neuron types in electron microscopy. The model also predicted the role of inhibitory interneuron types and different layers in stimulus encoding. Simulation tools and a large subvolume of the model are made available to enable further community-driven improvement, validation and investigation.

neuroscience↗