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7th HLF – Lindau Lecture: Edvard Moser
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Edvard Moser: “Space and time: Internal dynamics of the brain’s entorhinal cortex”
In mammals, space is mapped by specialized position-coding cell types in entorhinal cortex and hippocampus, including entorhinal grid cells, which are active only when animals are at locations that tile environments in a periodic hexagonal pattern. I will first show how space-coding neurons in the medial entorhinal cortex (MEC) collectively form a low-dimensional representation that persists across behavioral tasks and activity states. This low-dimensionality points to network architecture as a determinant of firing patterns and continuous attractor models have been proposed to account for the dynamics. Current models do not easily account for the representation of the unidirectional flow of experience, however. In the second part of my talk, I will thus ask how entorhinal networks are organized in time. Which trajectories in high-dimensional state space do cell ensembles take during experience? To determine how activity is self-organized in the MEC network, we tested mice in a spontaneous locomotion task under sensory-deprived conditions, when activity is determined primarily by the intrinsic structure of the network. Mice were head-fixed and ran on a spherical cylinder in darkness. Using 2-photon calcium imaging, we monitored the activity of several hundreds of MEC layer-2 neurons. Both linear and non-linear dimensionality reduction techniques were applied to the spike matrix of each individual session. When the cells were sorted according to their contribution to one of the first principal components of a principal components analysis, stereotyped motifs appeared, involving the sequential activation of neurons over epochs of tens of seconds to minutes. Transitions between cells that were close in principal-component space were favored, while transitions between clusters farther apart happened with a lower frequency than chance. Such stereotyped sequence elements may be recruited during encoding of space, and more widely experience, in the entorhinal-hippocampal network. Deficiencies in these mechanisms may be at the core of neurological diseases characterized by early entorhinal cell death, spatial disorientation and memory dysfunction, such as Alzheimer’s disease.
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The opinions expressed in this video do not necessarily reflect the views of the Heidelberg Laureate Forum Foundation or any other person or associated institution involved in the making and distribution of the video.
More information to the Heidelberg Laureate Forum:
In mammals, space is mapped by specialized position-coding cell types in entorhinal cortex and hippocampus, including entorhinal grid cells, which are active only when animals are at locations that tile environments in a periodic hexagonal pattern. I will first show how space-coding neurons in the medial entorhinal cortex (MEC) collectively form a low-dimensional representation that persists across behavioral tasks and activity states. This low-dimensionality points to network architecture as a determinant of firing patterns and continuous attractor models have been proposed to account for the dynamics. Current models do not easily account for the representation of the unidirectional flow of experience, however. In the second part of my talk, I will thus ask how entorhinal networks are organized in time. Which trajectories in high-dimensional state space do cell ensembles take during experience? To determine how activity is self-organized in the MEC network, we tested mice in a spontaneous locomotion task under sensory-deprived conditions, when activity is determined primarily by the intrinsic structure of the network. Mice were head-fixed and ran on a spherical cylinder in darkness. Using 2-photon calcium imaging, we monitored the activity of several hundreds of MEC layer-2 neurons. Both linear and non-linear dimensionality reduction techniques were applied to the spike matrix of each individual session. When the cells were sorted according to their contribution to one of the first principal components of a principal components analysis, stereotyped motifs appeared, involving the sequential activation of neurons over epochs of tens of seconds to minutes. Transitions between cells that were close in principal-component space were favored, while transitions between clusters farther apart happened with a lower frequency than chance. Such stereotyped sequence elements may be recruited during encoding of space, and more widely experience, in the entorhinal-hippocampal network. Deficiencies in these mechanisms may be at the core of neurological diseases characterized by early entorhinal cell death, spatial disorientation and memory dysfunction, such as Alzheimer’s disease.
This video is also available on another stream:
The opinions expressed in this video do not necessarily reflect the views of the Heidelberg Laureate Forum Foundation or any other person or associated institution involved in the making and distribution of the video.
More information to the Heidelberg Laureate Forum:
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