Upper motor neuron | EPFL Graph Search

Upper motor neurons (UMNs) is a term introduced by William Gowers in 1886. They are found in the cerebral cortex and brainstem and carry information down to activate interneurons and lower motor neurons, which in turn directly signal muscles to contract or relax. UMNs in the cerebral cortex are the main source of voluntary movement. They are the larger pyramidal cells in the cerebral cortex. There is a type of giant pyramidal cell called Betz cells and are found just below the surface of the cerebral cortex within layer V of the primary motor cortex. The cell bodies of Betz cell neurons are the largest in the brain, approaching nearly 0.1 mm in diameter. The primary motor cortex, or precentral gyrus, is the most posterior gyrus of the frontal lobe and lies anterior to the central sulcus. The pyramidal cells of the precentral gyrus are also called upper motor neurons. The fibers of the upper motor neurons project out of the precentral gyrus ending in the brainstem, where they wil

Data-driven reconstruction of a point neuron mouse brain

Csaba Erö

In this work, we present a semi-automatic method to reconstruct a mouse whole-brain model at the point-neuron level by integrating a wide array of biological data. Our process has three parts: cell position and type assignment, connectivity mapping, and simulation. Additional validation is performed at every step of the workflow. We obtain cell positions from a voxelized data sets derived from high-resolution Nissl stained microscope image stacks in the Allen Mouse Brain reference atlas (Lein, et al. 2007), and global constraint numbers for the whole-brain (Herculano-Houzel, Ribeiro, et al. 2011). We then assign the type of each cell using In Situ Hybridization (ISH) image data from the same atlas. Cells are classified as glia subtypes, excitatory neurons, or inhibitory neurons, leaving the possibility to further expand the diversity of assigned cell types by using more genes in this step. We furthermore integrate region-specific cell densities from literature into our model. We then study cell type correlations throughout the brain and compare the resulting numbers to literature data in order to validate the process. In the second step, we use two-photon tomography images of recombinant Adeno-Associated Virus (rAAV) labeled axonal projections from the Allen Mouse Connectivity Atlas (Oh, et al. 2014) to determine the mesoscale connectivity between the neurons in different brain regions. For this step a comprehensive comparison to experimental data is difficult due to lack of similar connectivity data. We then obtain a network configuration that can be simulated with state-of the art software like Nest. We show results from a simulated whisker stimulation experiment and compare the evoked activity patterns to imaging data from Voltage Sensitive Dye (VSD) experiments (Ferezou, Haiss, et al. 2007). Finally, we build a glossary of possible whole-brain behaviors of our model, and briefly explore the possibility of a biologically plausible mapping of its input and output pathways.

EPFL2018

Neural Circuits for Goal-Directed Sensorimotor Transformations

Sylvain Crochet, Seung-Hee Lee, Carl Petersen

Precisely wired neuronal circuits process sensory information in a learning- and context-dependent manner in order to govern behavior. Simple sensory decision-making tasks in rodents are now beginning to reveal the contributions of distinct cell types and brain regions participating in the conversion of sensory information into learned goal-directed motor output. Task learning is accompanied by target specific routing of sensory information to specific downstream cortical regions, with higher-order cortical regions such as the posterior parietal cortex, medial prefrontal cortex, and hippocampus appearing to play important roles in learning- and context-dependent processing of sensory input. An important challenge for future research is to connect cell-type-specific activity in these brain regions with motor neurons responsible for action initiation.

ELSEVIER SCIENCE LONDON2019

Spontaneous and evoked synaptic rewiring in the neonatal neocortex

Jean-Vincent Le Bé, Henry Markram

The local microcircuitry of the neocortex is structurally a tabula rasa, with the axon of each pyramidal neuron having numerous submicrometer appositions with the dendrites of all neighboring pyramidal neurons, but is functionally highly selective, with synapses formed onto only a small proportion of these targets. This design leaves a vast potential for the microcircuit to rewire without extensive axonal or dendritic growth. To examine whether rewiring does take place, we used multineuron patch-clamp recordings on 12- to 14-day-old rat neocortical slices and studied long-term changes in synaptic connectivity within clusters of neurons. We found pyramidal neurons spontaneously connecting and disconnecting from each other and that exciting the slice with glutamate greatly increases the number of new connections established. Evoked emergence of new synaptic connections requires action potential activity and activation of metabotropic glutamate receptor 5, but not NMDA receptor or group II or group III metabotropic glutamate receptor activation. We also found that it is the weaker connections that are selectively eliminated. These results provide direct evidence for spontaneous and evoked rewiring of the neocortical microcircuitry involving entire functional multisynaptic connections. We speculate that this form of microcircuit plasticity enables an evolution of the microcircuit connectivity by natural selection as a function of experience.

2006

Data-driven reconstruction of a point neuron mouse brain

Csaba Erö

EPFL2018