Multi-modal characterization and simulation of human epileptic circuitry

Temporal lobe epilepsy is the fourth most common neurological disorder with about 40% of patients not responding to pharmacological treatment. Increased cellular loss in the hippocampus is linked to disease severity and pathological phenotypes such as heightened seizure propensity. While the hippocampus is the target of therapeutic interventions such as temporal lobe resection, the impact of the disease at the cellular level remains unclear in humans. Here we show that properties of hippocampal granule cells change with disease progression as measured in living, resected hippocampal tissue excised from epilepsy patients. We show that granule cells increase excitability and shorten response latency while also enlarging in cellular volume, surface area and spine density. Single-cell RNA sequencing combined with simulations ascribe the observed electrophysiological changes to gradual modification in three key ion channel conductances: BK, Cav2.2 and Kir2.1. In a bio-realistic computational network model, we show that the changes related to disease progression bring the circuit into a more excitable state. In turn, we observe that by reversing these changes in the three key conductances produces a less excitable, early disease-like state. These results provide mechanistic understanding of epilepsy in humans and will inform future therapies such as viral gene delivery to reverse the course of the disorder

Measurement of host-to-activator transfer efficiency in nano-crystalline Y2O3:Eu3+ under VUV excitation

We have conducted a systematic study of the excitation and reflectance spectra of nano-crystalline Y2O3:Eu prepared by combustion synthesis. Excitation through the host lattice becomes relatively more efficient as the firing temperature of the precursor is increased, while reflectance properties remain essentially unchanged. Using these data, host-to-activator transfer efficiencies were calculated for excitation at the band edge of Y2O3, and evaluated using a competition kinetics model. From this analysis we conclude that the relatively low luminous efficiency of these materials is due more to poor bulk crystallinity than to surface loss effects

A Queueing Approach to Optimal Resource Replication in Wireless Sensor Networks

We develop a queueing model for analyzing resource replication strategies in wireless sensor networks. The model can be used to minimize either the total transmission rate of the network (an energy-centric approach) or to ensure the proportion of query failures does not exceed a predetermined threshold (a failure-centric approach). The model explicitly considers the limited availability of network resources, as well as the frequency of resource requests and query deadlines, to determine the optimal replication strategy for a network resource. While insufficient resource replication increases query failures and transmission rates, replication levels beyond the optimum result in only marginal decreases in the proportion of query failures at a cost of higher total energy expenditure and network traffic

A Trajectory-based Selective Broadcast Query Protocol for Large-Scale, High Density Wireless Sensor Networks

We present a small-footprint search protocol designed to facilitate any-type queries for data content and services in large population, high-density wireless sensor networks. Our protocol, termed Trajectory-based Selective Broadcast Query (TSBQ), works in conjunction with time division multiple access- or schedule-based medium access control protocols to reduce per-query energy expenditure. We compare the performance of TSBQ to unicast- and local broadcast-based search algorithms and also determine a critical node density based on the energy expended by nodes to transmit and receive. Minimal energy expenditure is achieved by determining the optimal number of data/service replicates and the number of nodes designated to receive each query transmission. Numerical results indicate that TSBQ significantly reduces the total energy expenditure of a network as compared to unicast and local broadcast-based search protocols

Multi-modal characterization and simulation of human epileptic circuitry.

Temporal lobe epilepsy is the fourth most common neurological disorder, with about 40% of patients not responding to pharmacological treatment. Increased cellular loss is linked to disease severity and pathological phenotypes such as heightened seizure propensity. While the hippocampus is the target of therapeutic interventions, the impact of the disease at the cellular level remains unclear. Here, we show that hippocampal granule cells change with disease progression as measured in living, resected hippocampal tissue excised from patients with epilepsy. We show that granule cells increase excitability and shorten response latency while also enlarging in cellular volume and spine density. Single-nucleus RNA sequencing combined with simulations ascribes the changes to three conductances: BK, Cav2.2, and Kir2.1. In a network model, we show that these changes related to disease progression bring the circuit into a more excitable state, while reversing them produces a less excitable, early-disease-like state

Morphoelectric and transcriptomic divergence of the layer 1 interneuron repertoire in human versus mouse neocortex

Neocortical layer 1 (L1) is a site of convergence between pyramidal-neuron dendrites and feedback axons where local inhibitory signaling can profoundly shape cortical processing. Evolutionary expansion of human neocortex is marked by distinctive pyramidal neurons with extensive L1 branching, but whether L1 interneurons are similarly diverse is underexplored. Using Patch-seq recordings from human neurosurgical tissue, we identified four transcriptomic subclasses with mouse L1 homologs, along with distinct subtypes and types unmatched in mouse L1. Subclass and subtype comparisons showed stronger transcriptomic differences in human L1 and were correlated with strong morphoelectric variability along dimensions distinct from mouse L1 variability. Accompanied by greater layer thickness and other cytoarchitecture changes, these findings suggest that L1 has diverged in evolution, reflecting the demands of regulating the expanded human neocortical circuit