Auditory Cortical Specializations for Bat Echolocation

The vertebrate auditory system evolved to detect and encode a broad range of natural sounds. In mammals, the primary auditory cortex (A1) is the terminal stage of the ascending central auditory system and is comprised of specialized circuits for reconstructing spectrotemporal features of complex sounds such as those comprising human speech. Many studies have characterized the response properties of discrete populations of neurons to a wide variety of natural and artificial stimuli, yet the circuit mechanisms for representing complex sound patterns remain poorly understood. This is due to the technical challenges of reconstructing the real-time interactions of heterogenous neuronal populations in A1, and compounded by the broad range of sounds that mammals can discriminate. To circumvent this problem, this thesis investigated cortical neural networks in an auditory specialist, the echolocating bat. The auditory system of the Mexican Free-tailed bat, Tadarida brasiliensis follows the standard mammalian plan, but the neural circuits in A1 are highly stereotyped for processing echoes, providing an avenue for investigating fundamental questions about the functional organization of A1 in one uniquely important context. To do this, I used a combination of acoustics, neuroanatomy and electrophysiology to map the free-tailed bat A1. The results are not only original for free-tailed bats, but also provide the most updated and comprehensive description of A1 physiology for any bat species. The thesis is broken into three data chapters: chapter 2 describes key neuroanatomical features of the bat A1 and provides the stereotaxic basis for electrophysiological experiments in subsequent chapters. Chapter 3 utilizes multi-electrode arrays to characterize response properties of neurons located in cortical columnar layers which constitute the foundation for all mammalian cortical processes. Chapter 4 introduces for the first time in bats the use of a standardized complex auditory stimulus to generate an unbiased characterization of the spectrotemporal response properties of different neuronal subpopulations. Collectively, the data from chapters 2-4 are used to generate a computational model of the local circuits in Tadarida brasiliensis A1 that reproduces how the network captures echo sound features, and offers novel insight into how the mammalian cortex is wired to encode biologically-relevant sounds

Temporal coding of echo spectral shape in the bat auditory cortex.

Echolocating bats rely upon spectral interference patterns in echoes to reconstruct fine details of a reflecting object's shape. However, the acoustic modulations required to do this are extremely brief, raising questions about how their auditory cortex encodes and processes such rapid and fine spectrotemporal details. Here, we tested the hypothesis that biosonar target shape representation in the primary auditory cortex (A1) is more reliably encoded by changes in spike timing (latency) than spike rates and that latency is sufficiently precise to support a synchronization-based ensemble representation of this critical auditory object feature space. To test this, we measured how the spatiotemporal activation patterns of A1 changed when naturalistic spectral notches were inserted into echo mimic stimuli. Neurons tuned to notch frequencies were predicted to exhibit longer latencies and lower mean firing rates due to lower signal amplitudes at their preferred frequencies, and both were found to occur. Comparative analyses confirmed that significantly more information was recoverable from changes in spike times relative to concurrent changes in spike rates. With this data, we reconstructed spatiotemporal activation maps of A1 and estimated the level of emerging neuronal spike synchrony between cortical neurons tuned to different frequencies. The results support existing computational models, indicating that spectral interference patterns may be efficiently encoded by a cascading tonotopic sequence of neural synchronization patterns within an ensemble of network activity that relates to the physical features of the reflecting object surface