Anthony Leonardo

Decrystallization of adult birdsong by perturbation of auditory feedback

Young birds learn to sing by using auditory feedback to compare their own vocalizations to a memorized or innate song pattern; ifthey are deafened as juveniles, they will not develop normal songs,. The completion of song development is called crystallization. After this stage, song shows little variation in its temporal or spectral properties. However, the mechanisms underlying this stability are largely unknown. Here we present evidence that auditory feedback is actively used in adulthood to maintain the stability of song structure. We found that perturbing auditory feedback during singing in adult zebra finches caused their songto deteriorate slowly. This ‘decrystallization’ consisted of a marked loss of the spectral and temporal stereotypy seen in crystallized song, including stuttering, creation, deletion and distortion ofsong syllables. After normal feedback was restored, these deviations gradually disappeared and the original song was recovered. Thus, adult birds that do not learn new songs nevertheless retain a significant amount of plasticity in the brain.

Large-scale, high-density (up to 512 channels) recording of local circuits in behaving animals

Monitoring representative fractions of neurons from multiple brain circuits in behaving animals is necessary for understanding neuronal computation. Here, we describe a system that allows high-channel-count recordings from a small volume of neuronal tissue using a lightweight signal multiplexing headstage that permits free behavior of small rodents. The system integrates multishank, high-density recording silicon probes, ultraflexible interconnects, and a miniaturized microdrive. These improvements allowed for simultaneous recordings of local field potentials and unit activity from hundreds of sites without confining free movements of the animal. The advantages of large-scale recordings are illustrated by determining the electroanatomic boundaries of layers and regions in the hippocampus and neocortex and constructing a circuit diagram of functional connections among neurons in real anatomic space. These methods will allow the investigation of circuit operations and behavior-dependent interregional interactions for testing hypotheses of neural networks and brain function.

Miniature motorized microdrive and commutator system for chronic neural recording in small animals

The use of chronically implanted electrodes for neural recordings in small, freely behaving animals poses several unique technical challenges. Because of the need for an extremely lightweight apparatus, chronic recording technology has been limited to manually operated microdrives, despite the advantage of motorized manipulators for positioning electrodes. Here we describe a motorized, miniature chronically implantable microdrive for independently positioning three electrodes in the brain. The electrodes are controlled remotely, avoiding the need to disturb the animal during electrode positioning. The microdrive is approximately 6 mm in diameter, 17 mm high and weighs only 1.5 g, including the headstage preamplifier. Use of the motorized microdrive has produced a ten-fold increase in our data yield compared to those experiments done using a manually operated drive. In addition, we are able to record from multiple single neurons in the behaving animal with signal quality comparable to that seen in a head-fixed anesthetized animal. We also describe a motorized commutator that actively tracks animal rotation based on a measurement of torque in the tether.

Ensemble Coding of Vocal Control in Birdsong

Zebra finch song is represented in the high-level motor control nucleus high vocal center (HVC) (Reiner et al., 2004) as a sparse sequence of spike bursts. In contrast, the vocal organ is driven continuously by smoothly varying muscle control signals. To investigate how the sparse HVC code is transformed into continuous vocal patterns, we recorded in the singing zebra finch from populations of neurons in the robust nucleus of arcopallium (RA), a premotor area intermediate between HVC and the motor neurons. We found that highly similar song elements are typically produced by different RA ensembles. Furthermore, although the song is modulated on a wide range of time scales (10-100 ms), patterns of neural activity in RA change only on a short time scale (5-10 ms). We suggest that song is driven by a dynamic circuit that operates on a single underlying clock, and that the large convergence of RA neurons to vocal control muscles results in a many-to-one mapping of RA activity to song structure. This permits rapidly changing RA ensembles to drive both fast and slow acoustic modulations, thereby transforming the sparse HVC code into a continuous vocal pattern.

Internal models direct dragonfly interception steering

Sensorimotor control in vertebrates relies on internal models. When extending an arm to reach for an object, the brain uses predictive models of both limb dynamics and target properties. Whether invertebrates use such models remains unclear. Here we examine to what extent prey interception by dragonflies (Plathemis lydia), a behaviour analogous to targeted reaching, requires internal models. By simultaneously tracking the position and orientation of a dragonfly’s head and body during flight, we provide evidence that interception steering is driven by forward and inverse models of dragonfly body dynamics and by models of prey motion. Predictive rotations of the dragonfly’s head continuously track the prey’s angular position. The head–body angles established by prey tracking appear to guide systematic rotations of the dragonfly’s body to align it with the prey’s flight path. Model-driven control thus underlies the bulk of interception steering manoeuvres, while vision is used for reactions to unexpected prey movements. These findings illuminate the computational sophistication with which insects construct behaviour.

Wireless Neural/EMG Telemetry Systems for Small Freely Moving Animals

We have developed miniature telemetry systems that capture neural, EMG, and acceleration signals from a freely moving insect or other small animal and transmit the data wirelessly to a remote digital receiver. The systems are based on custom low-power integrated circuits (ICs) that amplify, filter, and digitize four biopotential signals using low-noise circuits. One of the chips also digitizes three acceleration signals from an off-chip microelectromechanical-system accelerometer. All information is transmitted over a wireless ~ 900-MHz telemetry link. The first unit, using a custom chip fabricated in a 0.6- μm BiCMOS process, weighs 0.79 g and runs for two hours on two small batteries. We have used this system to monitor neural and EMG signals in jumping and flying locusts as well as transdermal potentials in weakly swimming electric fish. The second unit, using a custom chip fabricated in a 0.35-μ m complementary metal-oxide semiconductor CMOS process, weighs 0.17 g and runs for five hours on a single 1.5-V battery. This system has been used to monitor neural potentials in untethered perching dragonflies.

A Battery-Free Multichannel Digital Neural/EMG Telemetry System for Flying Insects

This paper presents a digital neural/EMG telemetry system small enough and lightweight enough to permit recording from insects in flight. It has a measured flight package mass of only 38 mg. This system includes a single-chip telemetry integrated circuit (IC) employing RF power harvesting for battery-free operation, with communication via modulated backscatter in the UHF (902-928 MHz) band. An on-chip 11-bit ADC digitizes 10 neural channels with a sampling rate of 26.1 kSps and 4 EMG channels at 1.63 kSps, and telemeters this data wirelessly to a base station. The companion base station transceiver includes an RF transmitter of +36 dBm (4 W) output power to wirelessly power the telemetry IC, and a digital receiver with a sensitivity of -70 dBm for 10-5 BER at 5.0 Mbps to receive the data stream from the telemetry IC. The telemetry chip was fabricated in a commercial 0.35 μ m 4M1P (4 metal, 1 poly) CMOS process. The die measures 2.36 × 1.88 mm, is 250 μm thick, and is wire bonded into a flex circuit assembly measuring 4.6 × 6.8 mm.

A wireless neural/EMG telemetry system for freely moving insects

We have developed a miniature telemetry system that captures neural, EMG, and acceleration signals from a freely moving insect and transmits the data wirelessly to a remote digital receiver. The system is based on a custom low-power integrated circuit that amplifies and digitizes four biopotential signals as well as three acceleration signals from an off-chip MEMS accelerometer, and transmits this information over a wireless 920-MHz telemetry link. The unit weighs 0.79 g and runs for two hours on two small batteries. We have used this system to monitor neural and EMG signals in jumping and flying locusts.

The Role of Motion Extrapolation in Amphibian Prey Capture.

Sensorimotor delays decouple behaviors from the events that drive them. The brain compensates for these delays with predictive mechanisms, but the efficacy and timescale over which these mechanisms operate remain poorly understood. Here, we assess how prediction is used to compensate for prey movement that occurs during visuomotor processing. We obtained high-speed video records of freely moving, tongue-projecting salamanders catching walking prey, emulating natural foraging conditions. We found that tongue projections were preceded by a rapid head turn lasting ∼130 ms. This motor lag, combined with the ∼100 ms phototransduction delay at photopic light levels, gave a ∼230 ms visuomotor response delay during which prey typically moved approximately one body length. Tongue projections, however, did not significantly lag prey position but were highly accurate instead. Angular errors in tongue projection accuracy were consistent with a linear extrapolation model that predicted prey position at the time of tongue contact using the average prey motion during a ∼175 ms period one visual latency before the head movement. The model explained successful strikes where the tongue hit the fly, and unsuccessful strikes where the fly turned and the tongue hit a phantom location consistent with the flys earlier trajectory. The model parameters, obtained from the data, agree with the temporal integration and latency of retinal responses proposed to contribute to motion extrapolation. These results show that the salamander predicts future prey position and that prediction significantly improves prey capture success over a broad range of prey speeds and light levels. SIGNIFICANCE STATEMENT Neural processing delays cause actions to lag behind the events that elicit them. To cope with these delays, the brain predicts what will happen in the future. While neural circuits in the retina and beyond have been suggested to participate in such predictions, few behaviors have been explored sufficiently to constrain circuit function. Here we show that salamanders aim their tongues by using extrapolation to estimate future prey position, thereby compensating for internal delays from both visual and motor processing. Predictions made just before a prey turn resulted in the tongue being projected to a position consistent with the preys pre-turn trajectory. These results define the computations and operating regimen for neural circuits that predict target motion.