Jason T. Ritt

Synchronization and oscillatory dynamics in heterogeneous, mutually inhibited neurons.

We study some mechanisms responsible for synchronous oscillations and loss of synchrony at physiologically relevant frequencies (10–200 Hz) in a network of heterogeneous inhibitory neurons. We focus on the factors that determine the level of synchrony and frequency of the network response, as well as the effects of mild heterogeneity on network dynamics. With mild heterogeneity, synchrony is never perfect and is relatively fragile. In addition, the effects of inhibition are more complex in mildly heterogeneous networks than in homogeneous ones. In the former, synchrony is broken in two distinct ways, depending on the ratio of the synaptic decay time to the period of repetitive action potentials (τs/T), where T can be determined either from the network or from a single, self-inhibiting neuron. With τs/T > 2, corresponding to large applied current, small synaptic strength or large synaptic decay time, the effects of inhibition are largely tonic and heterogeneous neurons spike relatively independently. With τs/T < 1, synchrony breaks when faster cells begin to suppress their less excitable neighbors; cells that fire remain nearly synchronous. We show numerically that the behavior of mildly heterogeneous networks can be related to the behavior of single, self-inhibiting cells, which can be studied analytically.

Selective optical drive of thalamic reticular nucleus generates thalamic bursts and cortical spindles

The thalamic reticular nucleus (TRN) is hypothesized to regulate neocortical rhythms and behavioral states. Using optogenetics and multi-electrode recording in behaving mice, we found that brief selective drive of TRN switched the thalamocortical firing mode from tonic to bursting and generated state-dependent neocortical spindles. These findings provide causal support for the involvement of the TRN in state regulation in vivo and introduce a new model for addressing the role of this structure in behavior.

Neural Correlates of Vibrissa Resonance: Band-Pass and Somatotopic Representation of High-Frequency Stimuli

The array of vibrissae on a rats face is the first stage of a high-resolution tactile sensing system. Recently, it was discovered that vibrissae (whiskers) resonate when stimulated at specific frequencies, generating several-fold increases in motion amplitude. We investigated the neural correlates of vibrissa resonance in trigeminal ganglion and primary somatosensory cortex (SI) neurons (regular and fast spiking units) by presenting low-amplitude, high-frequency vibrissa stimulation. We found that somatosensory neurons showed band-pass tuning and enhanced sensitivity to small amplitude stimuli, reflecting the resonance amplification of vibrissa motion. Further, a putative somatotopic map of frequency selectivity was observed in SI, with isofrequency columns extending along the representations of arcs of vibrissae, in agreement with the gradient in vibrissa resonance across the vibrissa pad. These findings suggest several parallels between frequency processing in the vibrissa system and the auditory system and have important implications for detection and discrimination of tactile information.

Frequency Control in Synchronized Networks of Inhibitory Neurons

We analyze the control of frequency for a synchronized inhibitory neuronal network. The analysis is done for a reduced membrane model with a biophysically based synaptic influence. We argue that such a reduced model can quantitatively capture the frequency behavior of a larger class of neuronal models. We show that in different parameter regimes, the network frequency depends in different ways on the intrinsic and synaptic time constants. Only in one portion of the parameter space, called phasic, is the network period proportional to the synaptic decay time. These results are discussed in connection with previous work of the authors, which showed that for mildly heterogeneous networks, the synchrony breaks down, but coherence is preserved much more for systems in the phasic regime than in the other regimes. These results imply that for mildly heterogeneous networks, the existence of a coherent rhythm implies a linear dependence of the network period on synaptic decay time and a much weaker dependence on the drive to the cells. We give experimental evidence for this conclusion.

Control strategies for underactuated neural ensembles driven by optogenetic stimulation.

Motivated by experiments employing optogenetic stimulation of cortical regions, we consider spike control strategies for ensembles of uncoupled integrate and fire neurons with a common conductance input. We construct strategies for control of spike patterns, that is, multineuron trains of action potentials, up to some maximal spike rate determined by the neural biophysics. We emphasize a constructive role for parameter heterogeneity, and find a simple rule for controllability in pairs of neurons. In particular, we determine parameters for which common drive is not limited to inducing synchronous spiking. For large ensembles, we determine how the number of controllable neurons varies with the number of observed (recorded) neurons, and what collateral spiking occurs in the full ensemble during control of the subensemble. While complete control of spiking in every neuron is not possible with a single input, we find that a degree of subensemble control is made possible by exploiting dynamical heterogeneity. As most available technologies for neural stimulation are underactuated, in the sense that the number of target neurons far exceeds the number of independent channels of stimulation, these results suggest partial control strategies that may be important in the development of sensory neuroprosthetics and other neurocontrol applications.

Chronically implanted hyperdrive for cortical recording and optogenetic control in behaving mice

Neural stimulation technology has undergone a revolutionary advance with the introduction of light sensitive ion channels and pumps into genetically identified subsets of cells. To exploit this technology, it is necessary to incorporate optical elements into traditional electrophysiology devices. Here we describe the design, construction and use of a “hyperdrive” capable of simultaneous electrical recordings and optical stimulation. The device consists of multiple microdrives for moving electrodes independently and a stationary fiber for delivering light to the tissue surrounding the electrodes. We present data demonstrating the effectiveness of inhibitory recruitment via optical stimulation and its interaction with physiological and behavioral states, determined by electrophysiological recording and videographic monitoring.

Neurocontrol: Methods, models and technologies for manipulating dynamics in the brain

This paper accompanies a tutorial session at the 2015 American Control Conference, and provides a survey of emerging technologies and research problems at the boundary between systems engineering, neuroscience and neural medicine. Emphasis will be placed on both recent theoretical developments - for example, system identification and controllability in neuronal networks - and real-world constraints in applications such as clinical deep brain stimulation, or optical stimulation in experimental neuroscience. Discussion will extend to how these constrains may necessitate the development of entirely new paradigms in systems and control theory that respond to the unprecedented challenges facing neural scientists and engineers.

Dual-modality endomicroscopy with co-registered fluorescence and phase contrast

We describe a dual-modality laser scanning endomicroscope that provides simultaneous fluorescence contrast based on confocal laser endomicroscopy (CLE) and phase-gradient contrast based on scanning oblique back-scattering microscopy (sOBM). The probe consists of a 2.6mm-diameter micro-objective attached to a 30,000-core flexible fiber bundle. The dual contrasts are inherently co-registered, providing complementary information on labeled and un-labeled sample structure. Proof of principle demonstrations are presented with ex-vivo mouse colon tissue.

Extraction of intended palpation times from facial EMGs in a mouse model of active sensing

The rodent whisker system is a common model for somatosensory neuroscience and sensorimotor integration. In support of ongoing efforts to assess neural stimulation approaches for future sensory prostheses, in which we deliver optogenetic stimulation to the somatosensory cortex of behaving mice, we must coordinate feedback in real time with active sensing whisker motions. Here we describe methods for extracting the times of whisker palpations from bilateral bipolar facial electromyograms (EMG). In particular, we show onset times extracted offline from EMG envelopes lead whisker motion onsets extracted from high speed video (HSV) by ≈ 16 ms. While HSV provides ground truth for sensing motions, it is not a feasible source of real time information suitable for neurofeedback experiments. As an alternative, we find the temporal derivative of the EMG envelope reliably predicts whisker motion onsets with short latency. Thus EMG, although providing noisy and partial information, can serve well as an input to control algorithms for testing neural processing of active sensing information, and providing stimulation for artificial touch experiments.

Non-negative inputs for underactuated control of spiking in coupled integrate-and-fire neurons

A rapidly growing area of research in neuroscience pertains to the use of external stimulation to manipulate the activity in ensembles of neurons. When such activity is modeled as the output of a dynamical system, the overall neurostimulation problem can be framed in the context of systems and control. Here, we present a particular form of control design for neurostimulation: the manipulation of spike timing with underactuated inputs. We first discuss formulations for spike sequence and pattern controllability, which relax the classical notions of controllability. Then, motivated by particular neurostimulation technologies, we discuss control design for achieving spike sequences and patterns with piecewise constant non-negative inputs in a model consisting of coupled integrate-and-fire neurons. The results provide the basis for a range of control theoretic studies related to manipulation of spiking dynamics in biophysical neuronal networks.