Gradients and Modulation of K+ Channels Optimize Temporal Accuracy in Networks of Auditory Neurons

Accurate timing of action potentials is required for neurons in auditory brainstem nuclei to encode the frequency and phase of incoming sound stimuli. Many such neurons express “high threshold” Kv3-family channels that are required for firing at high rates (>∼200 Hz). Kv3 channels are expressed in gradients along the medial-lateral tonotopic axis of the nuclei. Numerical simulations of auditory brainstem neurons were used to calculate the input-output relations of ensembles of 1–50 neurons, stimulated at rates between 100–1500 Hz. Individual neurons with different levels of potassium currents differ in their ability to follow specific rates of stimulation but all perform poorly when the stimulus rate is greater than the maximal firing rate of the neurons. The temporal accuracy of the combined synaptic output of an ensemble is, however, enhanced by the presence of gradients in Kv3 channel levels over that measured when neurons express uniform levels of channels. Surprisingly, at high rates of stimulation, temporal accuracy is also enhanced by the occurrence of random spontaneous activity, such as is normally observed in the absence of sound stimulation. For any pattern of stimulation, however, greatest accuracy is observed when, in the presence of spontaneous activity, the levels of potassium conductance in all of the neurons is adjusted to that found in the subset of neurons that respond better than their neighbors. This optimization of response by adjusting the K+ conductance occurs for stimulus patterns containing either single and or multiple frequencies in the phase-locking range. The findings suggest that gradients of channel expression are required for normal auditory processing and that changes in levels of potassium currents across the nuclei, by mechanisms such as protein phosphorylation and rapid changes in channel synthesis, adapt the nuclei to the ongoing auditory environment

Circumstantial evidence and explanatory models for synapses in large-scale spike recordings

Whether, when, and how causal interactions between neurons can be meaningfully studied from observations of neural activity alone are vital questions in neural data analysis. Here we aim to better outline the concept of functional connectivity for the specific situation where systems neuroscientists aim to study synapses using spike train recordings. In some cases, cross-correlations between the spikes of two neurons are such that, although we may not be able to say that a relationship is causal without experimental manipulations, models based on synaptic connections provide precise explanations of the data. Additionally, there is often strong circumstantial evidence that pairs of neurons are monosynaptically connected. Here we illustrate how circumstantial evidence for or against synapses can be systematically assessed and show how models of synaptic effects can provide testable predictions for pair-wise spike statistics. We use case studies from large-scale multi-electrode spike recordings to illustrate key points and to demonstrate how modeling synaptic effects using large-scale spike recordings opens a wide range of data analytic questions

Elementary properties of Ca(2+) channels and their influence on multivesicular release and phase-locking at auditory hair cell ribbon synapses.

Voltage-gated calcium (Cav1.3) channels in mammalian inner hair cells (IHCs) open in response to sound and the resulting Ca(2+) entry triggers the release of the neurotransmitter glutamate onto afferent terminals. At low to mid sound frequencies cell depolarization follows the sound sinusoid and pulses of transmitter release from the hair cell generate excitatory postsynaptic currents (EPSCs) in the afferent fiber that translate into a phase-locked pattern of action potential activity. The present article summarizes our current understanding on the elementary properties of single IHC Ca(2+) channels, and how these could have functional implications for certain, poorly understood, features of synaptic transmission at auditory hair cell ribbon synapses

Peripheral and Central Mechanisms of Temporal Pattern Recognition

Encoding information into the timing patterns of action potentials, or spikes, is a strategy used broadly in neural circuits. This type of coding scheme requires downstream neurons to be sensitive to the temporal patterns of presynaptic inputs. Indeed, neurons with temporal filtering properties have been found in a wide range of sensory pathways. However, how such response properties arise was previously not well understood. The goal of my dissertation research has been to elucidate how temporal filtering by single neurons contributes to the behavioral ability to recognize timing patterns in communication signals. I have addressed this question using mormyrid weakly electric fish, which vary the time intervals between successive electric pulses to communicate. Fish detect these signals with sensory receptors in their skin. In the majority of species, these receptors fire a single spike in response to each electric pulse. Spiking receptors faithfully encode the interpulse intervals in communication signals into interspike intervals, which are then decoded by interval-selective midbrain neurons. Using in vivo intracellular recordings from awake fish during sensory stimulation, I found that short-term depression and temporal summation play important roles in establishing single-neuron interval selectivity. Moreover, the combination of short-term depression and temporal summation in the circuit resulted in greater diversity of interval tuning properties across the population of neurons, which would increase the population’s ability to detect temporally patterned communication signals. Indeed, I found that the responses of single interval-selective neurons were sensitive to subtle variation in the timing patterns of a specific communication display produced by different individuals. A subset of mormyrid species has sensory receptors that produce spontaneously oscillating potentials. How the electrosensory system of these species established sensitivity to temporally patterned communication signals was completely unknown. Using in vivo extracellular recordings, I demonstrated that these receptors encode sensory stimuli into phase resets, which is the first clear instance of information coding by oscillatory phase reset. Furthermore, the ongoing oscillations conferred enhanced sensitivity to fast temporal patterns that are only found in the communication signals of a large group of fish. Behavioral playback experiments provided further support for the hypothesis that oscillating receptors are specialized for detecting communication signals produced by a group of conspecifics, which is a novel role for a sensory receptor. These findings demonstrate that temporal pattern sensitivity, which was previously thought to be a central processing problem, can also arise from peripheral filtering through a novel oscillatory phase reset mechanism

Analysis of neural circuits in vitro

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Brain and Cognitive Sciences, 2010.Cataloged from PDF version of thesis.Includes bibliographical references.This thesis is a collection of manuscripts addressing connectivity of neural circuits in cultured hippocampal neurons. These studies begin with an investigation of dopaminergic modulation of excitatory synapses in small circuits of neurons grown on glial micro islands. We found that dopamine transiently depressed excitatory synaptic transmission. Scaling up to larger circuits of neurons proved more challenging, since finding connected pairs became combinatorially more improbable. The discovery and use of light-activatable ion channel channel rhodopsin-2 (ChR2) promised to revolutionize the way in which we could map connectivity in vitro. We successfully delivered the gene for ChR2 in hippocampal cultures using recombinant adeno-associated virus and characterized the spatial resolution, as well as the reliability of stimulating action potentials. However, there were limitations to this technique that would render circuit maps ambiguous and incomplete. More recently, the engineering of rabies virus (RV) as a neural circuit tracer has produced an exciting method whereby viral infection can be targeted to a population of neurons and spread of the virus restricted to monosynaptically connected neurons. We further investigated potential mechanisms for previous observations which claim that RV spread is restricted to synaptically connected neurons by manipulating neural activity and synaptic vesicle release. We found that RV spread increased for blockade of synaptic vesicle exocytosis and for blockade of neural activity. The underlying premise for pursuing these methods to elucidate connectivity is that the computational power of the brain comes from changeable, malleable connectivity and that to test network models of computation in a biological brain, we must map the connectivity between individual neurons. This thesis builds a framework for experiments designed to bridge the gap between computational learning theories and networks of live neurons.by Jennifer Lynn Wang.Ph.D

The computational role of short-term plasticity and the balance of excitation and inhibition in neural microcircuits: experimental and theoretical analysis

The computations performed by the brain ultimately rely on the functional connectivity between neurons embedded in complex networks. It is well known that the neuronal connections, the synapses, are plastic, i.e. the contribution of each presynaptic neuron to the firing of a postsynaptic neuron can be independently adjusted. The modulation of effective synaptic strength can occur on time scales that range from tens or hundreds of milliseconds, to tens of minutes or hours, to days, and may involve pre- and/or post-synaptic modifications. The collection of these mechanisms is generally believed to underlie learning and memory and, hence, it is fundamental to understand their consequences in the behavior of neurons.(...