A structural variation reference for medical and population genetics.

Structural variants (SVs) rearrange large segments of DNA and can have profound consequences in evolution and human disease. As national biobanks, disease-association studies, and clinical genetic testing have grown increasingly reliant on genome sequencing, population references such as the Genome Aggregation Database (gnomAD) have become integral in the interpretation of single-nucleotide variants (SNVs). However, there are no reference maps of SVs from high-coverage genome sequencing comparable to those for SNVs.

Simultaneous voltage and calcium imaging and optogenetic stimulation with high sensitivity and a wide field of view.

Transmembrane voltage and intracellular calcium concentration are coupled parameters essential to the function of neurons, cardiomyocytes, and other excitable cells. Here we introduce the microscope for simultaneous optogenetic stimulation and voltage and calcium imaging with fluorescent proteins using three spectrally distinct visible color bands. Firefly-HR combines patterned stimulation, near-total internal reflection laser excitation through a prism located between the sample and a water-immersion objective, and concurrent imaging of three color channels.

All-Optical Electrophysiology for Disease Modeling and Pharmacological Characterization of Neurons.

A key challenge for establishing a phenotypic screen for neuronal excitability is measurement of membrane potential changes with high throughput and accuracy. Most approaches for probing excitability rely on low-throughput, invasive methods or lack cell-specific information. These limitations stimulated the development of novel strategies for characterizing the electrical properties of cultured neurons.

Sloppy morphological tuning in identified neurons of the crustacean stomatogastric ganglion.

Neuronal physiology depends on a neuron's ion channel composition and unique morphology. Variable ion channel compositions can produce similar neuronal physiologies across animals. Less is known regarding the morphological precision required to produce reliable neuronal physiology.

Automatic parameter estimation of multicompartmental neuron models via minimization of trace error with control adjustment.

We describe a new technique to fit conductance-based neuron models to intracellular voltage traces from isolated biological neurons. The biological neurons are recorded in current-clamp with pink (1/f) noise injected to perturb the activity of the neuron. The new algorithm finds a set of parameters that allows a multicompartmental model neuron to match the recorded voltage trace.

Statistics of neuronal identification with open- and closed-loop measures of intrinsic excitability.

In complex nervous systems patterns of neuronal activity and measures of intrinsic neuronal excitability are often used as criteria for identifying and/or classifying neurons. We asked how well identification of neurons by conventional measures of intrinsic excitability compares with a measure of neuronal excitability derived from a neuron's behavior in a dynamic clamp constructed two-cell network. We used four cell types from the crab stomatogastric ganglion: the pyloric dilator, lateral pyloric, gastric mill, and dorsal gastric neurons.

Compensation for variable intrinsic neuronal excitability by circuit-synaptic interactions.

Recent theoretical and experimental work indicates that neurons tune themselves to maintain target levels of excitation by modulating ion channel expression and synaptic strengths. As a result, functionally equivalent circuits can produce similar activity despite disparate underlying network and cellular properties. To experimentally test the extent to which synaptic and intrinsic conductances can produce target activity in the presence of variability in neuronal intrinsic properties, we used the dynamic clamp to create hybrid two-cell circuits built from four types of stomatogastric neurons coupled to the same model Morris-Lecar neuron by reciprocal inhibition.

Reliable neuromodulation from circuits with variable underlying structure.

Recent work argues that similar network performance can result from highly variable sets of network parameters, raising the question of whether neuromodulation can be reliable across individuals with networks with different sets of synaptic strengths and intrinsic membrane conductances. To address this question, we used the dynamic clamp to construct 2-cell reciprocally inhibitory networks from gastric mill (GM) neurons of the crab stomatogastric ganglion. When the strength of the artificial inhibitory synapses (g(syn)) and the conductance of an artificial I(h) (g(h)) were varied with the dynamic clamp, a variety of network behaviors resulted, including regions of stable alternating bursting.

Effects of temperature acclimation on a central neural circuit and its behavioral output.

In this study, we address the impact of temperature acclimation on neuronal properties in the Mauthner (M-) system, a brain stem network that initiates the startle-escape behavior in goldfish. The M-cell can be studied at cellular and behavioral levels, since it is uniquely identifiable physiologically within the intact vertebrate brain, and a single action potential in this neuron determines not only whether a startle response will occur but also the direction of the escape. Using animals acclimated to 15 degrees C as a control, 25 degrees C-acclimated fish showed a significant increase in escape probability and a decrease in the ability to discriminate escape directionality.

Using ICA and realistic BOLD models to obtain joint EEG/fMRI solutions to the problem of source localization.

We develop two techniques to solve for the spatio-temporal neural activity patterns using Electroencephalogram (EEG) and Functional Magnetic Resonance Imaging (fMRI) data. EEG-only source localization is an inherently underconstrained problem, whereas fMRI by itself suffers from poor temporal resolution. Combining the two modalities transforms source localization into an overconstrained problem, and produces a solution with the high temporal resolution of EEG and the high spatial resolution of fMRI.

What grid cells convey about rat location.

We characterize the relationship between the simultaneously recorded quantities of rodent grid cell firing and the position of the rat. The formalization reveals various properties of grid cell activity when considered as a neural code for representing and updating estimates of the rat's location. We show that, although the spatially periodic response of grid cells appears wasteful, the code is fully combinatorial in capacity.

Three mechanisms for power laws on the Cayley tree.

We compare preferential growth, critical phase transitions, and highly optimized tolerance (HOT) as mechanisms for generating power laws in the familiar and analytically tractable context of lattice percolation and forest fire models on the Cayley tree. All three mechanisms have been widely discussed in the context of complexity in natural and technological systems. This parallel study enables direct comparison of the mechanisms and associated lattice solutions.