Daniel Margoliash - US grants

sound frequency; neural information processing; vocalization; auditory feedback; animal communication behavior; stimulus /response; auditory stimulus; computer simulation; neurophysiology; neuroanatomy; acoustic nerve; mathematical model; histology; Aves;

A long-term objective of neurobiology is to describe behaviors of relevance to the human condition such as vocal learning in quantitative terms based on neuronal mechanisms. An excellent model system for vocal learning is the acquisition of avian song. Song learning exhibits a variety of developmental phenomena that are remarkably similar to speech acquisition in humans, including sensitive phases that depend on external models for acquisition of sounds, and that requirement for intact auditory feedback during development but not (in general) in adulthood. Thus, the mechanistic analysis of song learning can increase knowledge of the specific animal test system, can inform larger neuroethological theories of behavior, and can shed light on specific pathological human conditions such as congenital deafness. Song learning endows neurons in "song system" nuclei such as HVc with specificity for acoustic parameters of the individual bird's autogenous song(AS). These properties result from learned sensorimotor interactions in the song system. HIVc gives rise to a motor pathway and to a pathway involved in song learning. This proposal is to analyze the functional interactions between the HVc projection neurons giving rise to the two pathways. It is predicted that lesions of the X-projecting HVc neurons (HVc-Xn) will result in stabilization of an abnormal song, that lesions of the RA-projecting HVc neurons (HVc-RAn) will result in recovery of the normal song, that different subdivisions of HVc will have different roles in song production and differences in morphology, physiology and recovery, and that interactions between HVc-RAn and HVc-Xn are necessary to establish AS selectivity. In Exp. I, the roles of Hvc-Xn and HVc-RAn in song production will be tested by assessing changes in song production over extended periods of time following selective laser photoablation of projection neurons retrogradely labeled with the phototoxic dye eosin. Songs will be analyzed by newly developed algorithms. Control experiments will establish standardized treatments. The role of auditory feedback in song stabization and song recovery will then by assessed by eliminating auditory feedback or by provide altered auditory feedback. The potential role of adult neurogenesis in song stabilization and song recovery will be assessed using the standardized treatments combined with histological techniques to identify the disposition of new HVcRAn that are incorporated in circuits subsequent to the photolesions. In Exp. 2 and 3, fluorescently-labeled HVc projection neurons will be visualized in vivo. In Exp. 2 extracellular recordings will measure spontaneous activity, selectivity/specificity to AS, synchronous activity, and changes in those properties in each subdivision immediately after and in days following lesions restricted to HVc-RAn and/or HVc-Xn of a single subdivision. In the third experiment, the morphology of intracellularly labeled neurons in each subdivision of HVc will be characterized to help establish an anatomical basis for the functional differences.

verbal learning; neurophysiology; developmental neurobiology; sensorimotor system; behavior; synapses; electrophysiology; brain mapping; auditory feedback; neuroanatomy; norepinephrine; songbirds; biological models; behavioral /social science research tag;

[unreadable] DESCRIPTION (provided by applicant): Auditory neurons are characterized by their receptive field properties, which describe the organization of parameters such as frequency and amplitude of stimuli that the neurons respond to. Receptive fields are relatively better described for neurons at lower levels of the auditory system, but higher-order neurons exhibit complex non-linearities that have resisted systematic quantification. Characterization of higher-order receptive fields, however, is fundamental to understanding normal and abnormal auditory perceptual processes, and also may help optimize performance of prosthetic devices. An attractive model system has been described whereby high-order auditory neurons in starlings become highly selective for acoustic objects ("motifs") embedded in natural signals (songs). Recent results implicate remarkable sequence parsing abilities of starlings that exhibit sensitivity to prototypic grammar-like structures. In the proposed research, novel statistical techniques will be combined with physiological recordings of "cmHV" neurons of starlings whose song recognition behavior is under operant control. In the first experiment, the statistical methodologies will be developed for learning efficient basis sets for motif structure and for estimating feature-based receptive fields with hierarchical non-linear regression, using Markov random fields of Bayesian inference models and incorporating non-linear temporal dynamics. In the second experiment, operant procedures will be used to identify natural features of motifs and parameters of motif sequences that starlings utilize in song recognition behavior. In the third experiment, cmHV responses will be characterized, with emphasis on analysis of the features identified by behavioral testing, and using the statistical methods for characterization of non-linear properties. Successful development of this approach would give quantitative neurophysiological insight into complex acoustic object and sequence recognition behavior while developing an approach of general utility to cortical sensory physiology. [unreadable] [unreadable]

An award is made to The University of Chicago to acquire and install a biplanar videofluoroscopy system that uses X-rays to measure 3-dimensional movements of the inside of animals through a method called X-ray Reconstruction of Moving Morphology (XROMM). XROMM generates 3D measurements and animations of biological movement by integrating 3D movement data collected using bi-planar digital videofluoroscopy with CT scan-based reconstructions of animal anatomy. XROMM makes it possible to measure movements of internal skeletal elements to which external markers cannot be attached without disrupting animal function, to study internal mechanics of small animals, such as mice, rats, and songbirds which are too small for external markers, to study animals that will only behave in optically opaque environment, such as in the dark, under soil, in water and/or in structurally complex environments, and to image internal soft tissue structures, such as muscles. The ability to make these measurements will enhance and expand research and training in integrative and evolutionary biomechanics, neuromechanics and neuroscience in the Chicago area. In particular, XROMM will enable innovations in the following areas: (1) Comparisons of locomotion and feeding movements of fish and amphibians in complex aquatic and terrestrial environments, and their relationship to evolutionary changes in form at the origin of tetrapods,(2) the diversity, complexity and control of 3D jaw and tongue movements during feeding in living mammals, and their relationship to changes in the structure of the feeding system during the origin and radiation of mammals, and (3) the role of the brain in control of 3D movements of a range of musculoskeletal organs, including jaws, tongues, eye muscles, and hands.

This research equipment will have multiple impacts beyond research, including teaching and training, public outreach and exhibit development, robotics and applied biomechanics. The XROMM instrumentation will provide postdoctoral researchers, graduate and undergraduate students with access to state-of-the-art research equipment in a dynamic intellectual environment that will make possible novel approaches to integrative analyses of animal movement. Graduate programs with access to XROMM will include: at the University of Chicago, the Graduate Program in Integrative Biology, the Committee on Evolutionary Biology, the Committee on Computational Neuroscience and the Committee on Medical Physics; at Northwestern University, the graduate programs in Biomedical Engineering, Physical Medicine & Rehabilitation, and Physiology; and the inter-institution, interdisciplinary NSF IGERT program, Integrative Training in Motor Control and Movement. Faculty and graduate students in these programs are actively involved in outreach locally (Sisters 4 Science; Global Village Science Project; Brain Day), and at national and international levels (Outreach programs in Fiji, New Guinea; Encyclopedia of Life Project; Biomechanics Exhibit, Field Museum of Natural History). The XROMM instrumentation will significantly augment these efforts by generating visually compelling animations of animal movement for presentation and online distribution. In making possible novel research into the role of the brain in control of movement, this equipment will contribute to understanding of motor control disorders including Parkinson's Disease and stroke.

Speaking is one of the most complicated human behaviors and yet speech is produced easily and with little conscious effort. Understanding the way the brain controls the various organs and muscles of vocalization is a basic scientific question that may illuminate more general principles that can describe how the brain programs and controls all behavior. In order to understand the neural mechanisms of motor behavior in vocal production, the proposed research will test specific hypotheses about the timing of different brain regions, the timing of muscles that produce vocal behavior, and the response to normal and abnormal auditory feedback. Understanding the neural mechanisms of motor control can have broad implications, including the development of more human-like robots, better computer-generated speech and vocal prostheses, as well as new therapies for treating articulatory disorders such as stuttering, dysarthria, aphasia, and other problems in speech production.

The proposed research will measure the timing of neural circuits that control vocalization in humans and song birds. The bird song production system has long been used as a model system that has relevance to understanding speech production. While simpler than humans and with less behavioral control of the experiments, studying birdsong is complementary in providing more granular measurements of neural activity in a vocal learning system than possible in humans. The experiments will test a novel hypothesis, that the motor system is not organized by the commonly assumed "top down" organizational scheme, but by a coherent network that operates as a unitary mechanism as described by certain mathematics of non-linear systems. The comparison between species will also be informative about how robust the results are across very different species and neural systems offering the possibility of generalization of the results.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Project Summary Mechanistically linking network connectivity and the dynamics of neural networks to variation in the behavior of individuals is an overarching goal of neuroscience. Here we address this goal using techniques from network science to calculate functional networks that summarize pair-wise and higher order interactions between all recorded neurons. Network activity will be assessed using sophisticated two-photon (2P) imaging of activity- dependent Ca2+ signaling optimized to maximize the rate of recording and the numbers of neurons recorded. Multineuronal interactions within the networks will be identified, giving rise to encoding models to predict the network activity. Techniques from statistical physics will be used to optimally couple data from intracellular recordings to biologically realistic Hodgkin-Huxley (HH) models representing the contributions of ion currents and other free model parameters of the individual neurons. Networks of HH neurons using model synapses will replace pair-wise correlations to delinate the interrelationships between the ion currents of individual neurons and network interactions and dynamics. Taking advantage of the birdsong learning model, in the proposed experiments these approaches will be applied to the cortical song system HVC nucleus, allowing us to link these scales of investigation directly to behavior. Recent results demonstrate that changes in the intrinsic properties (IP) (ion current magnitudes) of HVC neurons is related to each individual's song, implicating changes within neurons as well as at synapses and networks that are related to learning. Aim 1: fast 2P imaging will be made in brain slices containing HVC that express spontaneous network activity. Model building will be supported by extensive efforts at 3-cell and 4-cell whole cell patch recordings, to better characterize HVC connectivity. The hypothesis that network structure depends on learning will be tested by examining how models vary between individual birds who sang similar or different songs. Models will be extended to in vivo observations by fast 2P imaging in sleeping birds while eliciting fictive singing using song playback, and in singing birds using 1P imaging. Results from the other Aims will further constrain the network and HH model building of Aim 1. Aim 2: the predictive power of the models will be further tested by using cellular resolution 2P optogenetic inhibition of selected neurons in in vivo and in vitro preparations. Aim 3: the role of neuronal IP in shaping network dynamics will be tested by using genetic and viral techniques to transiently modify specific ion channels in specific classes of HVC neurons. Changes in birds' singing behavior will be compared against a predictive HH model relating song structure and ion channel efficacy. Fast 2P imaging in slice and multisite extracellular recordings in singing birds will help to define how IP contribute to network models. Aim 4: single cell gene expression techniques will be used to identify all the HVC cell classes, the ion channels they express, and assess individual variation by examining cohorts of related birds or those singing the same songs. The overall goals and the four Aims are also designed to align with a subsequent U19 application.