Quantum Conditions on Dynamics and Control in Open Systems

Quantum conditions on the control of dynamics of a system coupled to an environment are obtained. Specifically, consider a system initially in a system subspace $H_{0}$ of dimensionality $M_{0}$, which evolves to populate system subspaces $H_{1}$, $H_{2}$ of dimensionality $M_{1}$, $M_{2}$. Then there always exists an initial state in $H_0$ that does not evolve into $H_2$ if $M_{0}>dM_{2},$ where $2 \leq d \leq (M_0 +M_1 +M_2)^2$ is the number of operators in the Kraus representation. Note, significantly, that the maximum $d$ can be far smaller than the dimension of the bath. If this condition is not satisfied then dynamics from $H_{0}$ that avoids $H_{2}$ can only be attained physically under stringent conditions. An example from molecular dynamics and spectroscopy, i.e. donor to acceptor energy transfer, is provided.Comment: 4 pages, no figur

General anesthesia globally synchronizes activity selectively in layer 5 cortical pyramidal neurons

General anesthetics induce loss of consciousness, a global change in behavior. However, a corresponding global change in activity in the context of defined cortical cell types has not been identified. Here, we show that spontaneous activity of mouse layer 5 pyramidal neurons, but of no other cortical cell type, becomes consistently synchronized invivo by different general anesthetics. This heightened neuronal synchrony is aperiodic, present across large distances, and absent in cortical neurons presynaptic to layer 5 pyramidal neurons. During the transition to and from anesthesia, changes in synchrony in layer 5 coincide with the loss and recovery of consciousness. Activity within both apical and basal dendrites is synchronous, but only basal dendrites' activity is temporally locked to somatic activity. Given that layer 5 is a major cortical output, our results suggest that brain-wide synchrony in layer 5 pyramidal neurons may contribute to the loss of consciousness during general anesthesia. Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved

Large-scale automated histology in the pursuit of connectomes

How does the brain compute? Answering this question necessitates neuronal connectomes, annotated graphs of all synaptic connections within defined brain areas. Further, understanding the energetics of the brain's computations requires vascular graphs. The assembly of a connectome requires sensitive hardware tools to measure neuronal and neurovascular features in all three dimensions, as well as software and machine learning for data analysis and visualization. We present the state of the art on the reconstruction of circuits and vasculature that link brain anatomy and function. Analysis at the scale of tens of nanometers yields connections between identified neurons, while analysis at the micrometer scale yields probabilistic rules of connection between neurons and exact vascular connectivit