Jose Luis Pena - US grants

Abstract [This resubmitted project carries on the study of how auditory space is encoded in the barn owl's brain, with the overarching goal of understanding the interplay between midbrain and forebrain neural populations underlying discriminability and stimulus selection through auditory space. Behavioral spatial discrimination assays will be used to test the hypothesis that spatial discriminability is optimized by a built-in representation of natural cue statistics and in vivo recordings through multi-electrode arrays (MEAs) will be conducted in both anesthetized and awake barn owls for investigating activity patterns of midbrain neural populations underlying this effect (Aim 1). Population recordings in the midbrain space map, the hub of the midbrain stimulus selection network, will be used to investigate the interplay of stimulus temporal dynamics and brain oscillations in the coding of salient sounds across space (Aim 2). Simultaneous population recordings over brain regions will be used to investigate the routing of neural activity between midbrain and forebrain underlying sound localization (Aim 3). Recent findings by our group indicating commonalities of coding schemes across birds and mammals, including humans, support the premise that investigating mechanisms underlying discriminability, stimulus selection across space, and population-level midbrain and forebrain routing of activity, important open questions in sound localization, will be of significance across species. The group has recently developed multiunit recordings in awake animals, which will be used towards every specific aim.] Towards Aim 1, we will investigate the relationship between spatial discriminability and a representation of natural statistics of spatial cues, focusing on interaural time difference (ITD), a critical binaural cue for determining the azimuth location of sounds across species. This aim will test a hypothesis, based on premises supported by previous work from our group, that a built-in representation of natural ITD statistics, determined by the acoustical properties of the head, exists in the brain and optimizes sound localization. Behavioral studies will be conducted to assess spatial discriminability across frequency and space. MEAs will be used to record activity of the midbrain map of auditory space and use decoding analyses to investigate properties of population responses supporting the optimized discriminability pattern. [Recordings in awake birds will be used as a control for the effect of anesthesia. Preliminary data show feasibility of recordings in awake animals and a pattern of ITD discriminability across frequency and locations consistent with the hypothesis and properties of midbrain population responses supporting feasibility of this approach.] In Aim 2 we will scrutinize the midbrain stimulus selection network of barn owls on a population scale. Previous work suggested a role of gamma oscillations in stimulus selection and recent studies by our group showed a dependence between stimulus driven temporal spiking patterns and the location of sound sources relative to the preferred direction of space specific neurons of the owl?s midbrain. Based on this evidence, we will address the unexplored question of the interplay of brain oscillations and stimulus driven modulation of temporal spiking patterns in stimulus selection across space, a critical function of the sound localization system for detecting sounds based on their salience and location. [Population recordings in anesthetized and awake animals will be used to simultaneously track the power of brain oscillations across different frequency bands as well as envelope driven spiking patterns under competing sound stimulation. Preliminary data from MEA recordings across the midbrain space map show changes in population responses to competing sounds supporting the feasibility of the approach, and correlation between power of gamma oscillations and stimulus-driven temporal spiking patterning across the population consistent with an interplay of these signals in coding the salience of a sound. Preliminary data of recordings in awake barn owls show increased power of gamma range brain oscillations and correlation with response levels, corresponding with results obtained in anesthetized animals.] A critical open question in sound localization is the interplay of midbrain and forebrain areas displaying seemingly different coding schemes of sound localization, which we will address in Aim 3. [We will conduct simultaneous population recordings across brain regions in anesthetized and awake birds to elucidate the routing of neural activity across areas by analyzing pairwise correlation structure and trial-to-trial variability.] Previous studies by our group have shown important differences in correlation structure between midbrain and forebrain regions involved in sound localization, supporting the potential significance of investigating the bases of those results in simultaneous recordings of these brain areas and feasibility of this unprecedented approach. Thus, this project will assess the higher-order dynamics and interplay of midbrain and forebrain neural populations involved in sound localization to investigate mechanisms underlying vital functions that operate across species. [A new approach of in vivo recording in awake barn owls was recently developed by the group to validate functional significance of results across aims.] The contribution of this research to understanding central auditory processing underlying sound localization will lead to more accurate interpretations of auditory perception and its disruption in hearing disorders, with potential for improving treatments.

DESCRIPTION (provided by applicant): Capturing nature's statistical structure in the neural coding is essential for optimal adaptation to the environment. This proposal investigates this issue by asking how the brain can approach statistical optimality in the sound localization system of barn owls. A Bayesian theoretical framework will be used to describe how sensory and a priori information can be combined optimally to guide orienting behavior. Specifically, we seek to demonstrate that sensory reliability and a priori information are represented in the response properties and topography of the neural population that represents auditory space. The first aim studies how sensory cue reliability is represented in the brain. Optimal use of sensory information requires that the statistical reliability of sensory cues is accessible from neural responses. Previous theories have suggested that cue reliability is encoded in the gain of neural responses or alternatively the selectivity of neural responses but how reliability is represented is not known. In the owl, changes in the statistical reliability of spatial cues resultin changes in sound localization behavior consistent with a Bayesian model. Our model predicts that the reliability is encoded in the tuning curve widths of space-specific neurons located in the owl's midbrain. We will manipulate tuning-curve widths and firing rates independently to test this hypothesis and test the model with behavior. The second aim will study whether the integration of spatial cues for sound localization follows the rules of statistical optimality. Perception in natural environments often depends on the integration of multiple cues, both within modalities and across modalities. Here, whether the integration is linear or nonlinear is crucial, as extending a Bayesian model from one to two dimensions indicates that optimal combination of conditionally independent sensory cues should be nonlinear. In the owl's brain, the spatial cues used to determine elevation and azimuth are processed independently and combined nonlinearly in the midbrain to form spatial receptive fields. However, whether or not sound localization cues are conditionally independent is unknown. This aim will demonstrate why nonlinear operations are essential for optimal cue combination and how they arise. We will perform in vivo intracellular recording and behavioral tests to address these questions. This will provide an experimental test of the prediction that optimal combination of conditionally independent cues is nonlinear. The third aim will extend the model to coding dynamic auditory scenes; the time dimension will be incorporated into the Bayesian model of sound localization. We will use a population vector model to determine how a neural system can achieve predictive power in auditory space through Bayesian inference. We will measure receptive fields of midbrain neurons in space and time to test the hypothesis that the owl has a bias for sources moving toward the center of gaze. We will use behavioral tests to measure detection thresholds for moving sound sources. Finally, we will study whether a dynamic gain control in a non-uniform network can account for Bayesian predictive coding of sound motion with a bias for sources moving toward the center of gaze. Broader Impacts: Outstanding open questions of how statistics of natural scenes are captured by neural coding include how reliability of sensory information is represented and combined with prior probabilistic knowledge, and how sensory cues are integrated to optimally guide behavior. This project addresses these questions in the heterogeneous representation of space of the owl's auditory midbrain. Whether non-uniform representations can be decoded using a population vector to perform Bayesian inference and that this mechanism works in multiple dimensions transcends sound localization in barn owls, becoming of general interest to neural coding. The PIs involved in this project, one of them a junior researcher, gather complementary expertise in modeling, physiology and behavioral approaches allowing for a truly interdisciplinary approach. This project will thus consolidate a powerful collaboration while providing groundbreaking information on outstanding questions in Neuroscience. The three institutions involved are committed to the training of underrepresented groups. The location of the Albert Einstein College of Medicine in the Bronx, makes it a pole of development in one of the most diverse and poor counties in the country and provides the potential for direct access to translational research. The inclusion of the Department of Mathematics at Seattle University, ranked among the top ten universities in the West for undergraduate programs, and the University of Oregon will ensure that this project will enhance training from the undergraduate to postdoctoral levels.

This award will provide support to US-based students and post-doctoral fellows and junior scientists to attend the 2016 International Congress on Neuroethology. This conference is recognized as the major, mid-size meeting in Neuroethology, bringing together outstanding senior and junior scientists for discussions of the recent advances in the field. Invited speakers across many areas of neuroethology, will present their findings on how the activity of animal brains give rise to natural behaviors. The meeting feature sessions that will showcase how biological solutions inform new conceptual and technological advances in bio-inspired robotics, smart machines and neural modeling. The results presented at the meeting will have the potential to guide future developments in multiple areas, including neurally inspired design of engineered systems that will have considerable societal benefits.

The intellectual merit of this meeting derives from its small size, which promotes interactions between participants, and the assembly of many top scientists whose research spans neurobiology, engineering and neuroethology. It spans a wide variety of experimental systems and focuses on areas of exceptional activity or promise. This combination leads to fruitful comparative analyses, raises new questions about underlying mechanisms and often leads to new collaborations. By maximizing both formal discussion and informal interactions, the meeting will highlight exciting new developments in neuroethology and engineering approaches in neurobiology. With respect to broader impacts, this meeting will benefit the larger community in multiple ways. First, it will help train and inspire the next generation of scientists, by exposing students and postdoctoral fellows to exciting science and scientists. Second, special mentoring sessions will be organized to help junior researchers make informed choices about scientific careers in academia and beyond. Finally, a concerted effort will be made to recruit scientists from under-represented groups.

Abstract This study aims to understand how the ensemble activity and network architecture of a neuronal population guides natural and learned behavior. The model system is the midbrain localization pathway of the owl. Ensemble recordings, microcircuit analysis, behavioral measurements and computational modeling will be used to analyze the neural representation of auditory space and the head-orienting movement driven by it. The compact volume of tissue commanding this behavior makes a complete understanding of information processing tractable with high-throughput electrophysiological and microanatomical methods. How information about sound location is readout to guide orienting behaviors has not been demonstrated in any species. This project has the potential to fill this gap. Aim 1 will investigate the relationship between orienting behavior and activity in the neuronal population representing auditory space, in which frontal space is overrepresented. The hypothesis is based on recent work showing that sound localization can be explained by statistical inference, computed by integrating activity across the entire population. Microelectrode arrays (MEAs) will be used to map the activity of the population upon presentation of sounds. Population decoders will be constructed to determine how the population activity is readout to drive behavior. In Aim 2, the network architecture supporting the activity pattern will be studied with light and electron microscopy. Network models will combine the data to explain how connectivity and cellular computations result in the population activity and correlated firing that drives behavior. When auditory-visual cues are modified, the midbrain representation of auditory space adapts over time, and consequently drives a learned behavior. Aim 3 will directly examine this link. MEA recordings, microcircuit analysis and behavioral measurements will be made in owls adapted to prismatic spectacles. Population decoders will be used to test the hypothesis that population activity in the learned condition maintains a non-uniform population code with an overrepresentation of frontal space. Network models will be used to examine how local re-wiring may explain changes in the distribution of activity across the population. This would be the first time that neural activity and network architecture underlying sound localization are approached from the complete-population down to single-cell level, before and after learning. This integrative approach holds potential for understanding principles of population coding, plasticity and learning that operate across species and brain circuits.

This award will provide support to US-based students and post-doctoral fellows and junior scientists to attend the 2016 International Congress on Neuroethology. This conference is recognized as the major, mid-size meeting in Neuroethology, bringing together outstanding senior and junior scientists for discussions of the recent advances in the field. Invited speakers across many areas of neuroethology, will present their findings on how the activity of animal brains give rise to natural behaviors. The meeting feature sessions that will showcase how biological solutions inform new conceptual and technological advances in bio-inspired robotics, smart machines and neural modeling. The results presented at the meeting will have the potential to guide future developments in multiple areas, including neurally inspired design of engineered systems that will have considerable societal benefits.

The intellectual merit of this meeting derives from its small size, which promotes interactions between participants, and the assembly of many top scientists whose research spans neurobiology, engineering and neuroethology. It spans a wide variety of experimental systems and focuses on areas of exceptional activity or promise. This combination leads to fruitful comparative analyses, raises new questions about underlying mechanisms and often leads to new collaborations. By maximizing both formal discussion and informal interactions, the meeting will highlight exciting new developments in neuroethology and engineering approaches in neurobiology. With respect to broader impacts, this meeting will benefit the larger community in multiple ways. First, it will help train and inspire the next generation of scientists, by exposing students and postdoctoral fellows to exciting science and scientists. Second, special mentoring sessions will be organized to help junior researchers make informed choices about scientific careers in academia and beyond. Finally, a concerted effort will be made to recruit scientists from under-represented groups.