Efficient Encoding Of Vocalizations In The Auditory Midbrain

Abstract

An important question in sensory neuroscience is what coding strategies and mechanisms are used by the brain to detect and discriminate among behaviorally relevant stimuli. To address the noisy response properties of individual neurons, sensory systems often utilize broadly tuned neurons with overlapping receptive fields at the system's periphery, resulting in homogeneous responses among neighboring populations of neurons. It has been hypothesized that progressive response heterogeneity in ascending sensory pathways is evidence of an efficient encoding strategy that minimizes the redundancy of the peripheral neural code and maximizes information throughput for higher level processing. This hypothesis has been partly supported by the documentation of neural heterogeneity in various cortical structures.This dissertation examines whether selective and sensitive responses to behaviorally relevant stimuli contribute to a heterogeneous and efficient encoding in the auditory midbrain. Prior to this study, no compelling experimental framework ex- My parents, for their support throughout all of my education. Not only did they instill in me a confidence that I could take on any educational challenge, but they supported me when I chose not to take these challenges on. I'm sure they worried about me when I dropped out of college in 1993, but their trust in my own decision making process was a better lesson for me to learn at the time.My sister, for teaching me how to fight for the important things in life.My entire committee, for challenging me to push my limits (which I discovered on many occasions). I have leaned on each and every one of them at different times through this process. I am very grateful to have had access to a group so diverse in their specialties, yet so consistent in their kindness, approachability, depth of knowledge, and eagerness to share this knowledge. I couldn't have done this without a single one of them.Lonneke Eeuwes, for all of the long hours she spent collecting data for our experiii iments and carefully reading through my manuscripts.Sunghan Kim, for working with me through the technical details of our state space frequency tracking methods. My research was made possible by your work.Roberto Santiago, for taking me under his wing as a fresh graduate student and imbuing me with a sense of adventure about research. He taught me that the challenges inherent in science are not a chore, but a privilege to be relished.John Vasallo, for setting time aside for our weekly musical catharsis and for being flexible with respect to my constantly shifting schedule. He almost single handedly ensured that playing music will continue to be an important part of my life.Todd Haynes, for his roving intellect and dedication to the creative process. I can only hope that I can tap into a similar wellspring of enthusiasm, kindness, and vision.

Spectral summation and facilitation in on‐ and off‐responses for optimized representation of communication calls in mouse inferior colliculus

“…Therefore, the responsiveness of a neuron to all the signal types ( Fig. 2) relative to the responsiveness to the natural wriggling call was expressed by the selectivity index as used by others (Wang & Kadia, 2001;Holmstrom et al, 2010) d = (n 0 À n)/ (n 0 + n) with n 0 equal to the number of spikes to 19 repetitions of the natural wriggling call and n to the number of spikes to 19 repetitions of a given signal type. d was calculated separately for on-responses and, if applying, offresponses of a given unit.…”

“…Off-responses in addition to on-responses to single tones at the CF of a neuron have been observed in mouse IC neurons before at rates of 3-12% depending on the SPL of the stimulus (Ehret & Moffat, 1985;Egorova, 2008a, b;Kasai et al, 2012). Off-responses in the IC to mouse ultrasonic vocalizations have been recorded but not separated from and quantified in addition to on-responses (Holmstrom et al, 2010). Similarly, on-and off-responses to vocalizations have been recorded from the guinea pig IC but not analyzed further ( Suta et al, 2003).…”

BOLD fMRI study of ultrahigh frequency encoding in the inferior colliculus

“…It is likely that the involvement of multiple neural mechanisms enables the IC to encode UHFs and process complex sounds that contain them (e.g., vocalizations) more accurately (Holmstrom et al, 2010). It is plausible that the combination (i.e., summation) and distortion (i.e., difference) of two UHFs contain complementary signals, with which the IC can fully decode and extract information conveyed in both frequency channels.…”

“…For example, in the primary auditory nucleus in the midbrain, called the inferior colliculus (IC), which is a compulsory relay for all ascending auditory projections (Malmierca, 2003) and a region that efficiently encodes vocalizations (Holmstrom et al, 2010), the tonotopic organization is a basic feature in its central nucleus (CNIC), where the CFs of neurons run from low to high along the dorsolateralventromedial dimension (Cheung et al, 2012a(Cheung et al, , 2012bDe Martino et al, 2013;Malmierca et al, 2008;Ress and Chandrasekaran, 2013;Schreiner and Langner, 1997;Yu et al, 2005). In the cortical regions of the IC, the frequency organization is usually non-tonotopic, with neurons showing complex frequency tuning properties, such as broadband or multipeak receptive fields (Duque et al, 2012;Hernandez et al, 2005;Malmierca et al, 2011;Stebbings et al, 2014).…”

Neural Heterogeneity and Efficient Population Codes for Communication Signals

“…In particular, it has been shown that the heterogeneity in firing patterns of MT neurons in the visual cortex of primates leads to an increase in information coding (Osborne et al 2008). Another study showed that heterogeneity of the population response of neurons in the inferior colliculus of mammals permits the discrimination of different vocalizations (Holmstrom et al 2010). Sensory coding is often referred to as sparse in higher brain areas because only a few neurons respond to a given feature of the sensory signal so that these features are not redundantly encoded in a large population of neurons (Olshausen and Field 2004).…”