<p>Persistent and maladaptive fear in the absence of a threat can be disruptive because it decreases an organism’s opportunity to seek life-sustaining substances. Learned safety signaling can suppress fear and encourage reward-seeking behavior, thus freeing the organism from fear induced immobilization. The infralimbic (IL) region of the prefrontal cortex is important for recalling fear extinction memories and for suppressing fear via learned safety signals. Neurons in the IL show an excitatory response to an extinguished fear cue. We thus hypothesized that neurons in the IL would encode safety by showing an excitatory response during active fear suppression to a learned safety signal. </p> <p>To assess global changes in IL activity, we monitored IL multi-unit activity to different cues while training animals in a fear-reward-safety discrimination task (Sangha, Chadick, & Janak, 2013). During the discrimination task, male rats learned that the reward cue predicted liquid sucrose, the fear cue predicted footshock and the joint presentation of both the fear and safety cues resulted in no footshock. We also counterbalanced the modality of fear and safety cues (auditory vs visual) with two separate groups of animals to control for potential sensory modality effects. Male rats showed high levels of freezing to the fear cue, and significantly reduced levels of freezing to the combined fear+safety cue. Male rats also showed high levels of port activity to the reward cue. There was no significant difference in the learning rate between the two counterbalanced conditions. </p> <p>Our multi-unit-data showed an increase in IL neuronal firing to the fear+safety cue across training sessions. This effect was consistent between the two counterbalanced conditions. We also examined single-unit activity from all animals that received light as the safety cue (n=8). This allowed us to examine the population response profile with a subset of the total animals. Although not statistically significant, our preliminary single-unit data demonstrated a decrease in the percentage of neurons that showed an inhibitory response to the fear+safety cue, but no change in the percentage of neurons that showed an excitatory response to the fear+safety cue. There was also no change in the magnitude of averaged firing rate in fear+safety excitatory or inhibitory neurons across training. Taken together, the decreased inhibition of single-unit activity in the IL may drive the increased excitation in multi-unit activity in the IL during behavioral fear suppression to a safety signal. </p>

<p>This thesis aims to investigate how one fundamental component of the inner-ear (cochlear) response to all sounds, the temporal fine structure (TFS), is used by the auditory system in everyday hearing. Although it is well known that neurons in the cochlea encode the TFS through exquisite phase locking, how this initial/peripheral temporal code contributes to everyday hearing and how its degradation contributes to perceptual deficits are foundational questions in auditory neuroscience and clinical audiology that remain unresolved despite extensive prior research. This is largely because the conventional approach to studying the role of TFS involves performing perceptual experiments with acoustic manipulations of stimuli (such as sub-band vocoding), rather than direct physiological or behavioral measurements of TFS coding, and hence is intrinsically limited. The present thesis addresses these gaps in three parts: 1) developing assays that can quantify TFS coding at the individual level 2) comparing individual differences in TFS coding to differences in speech-in-noise perception across a range of real-world listening conditions, and 3) developing deep neural network (DNN) models of speech separation/enhancement to complement the individual-difference approach. By comparing behavioral and electroencephalogram (EEG)-based measures, Part 1 of this work identified a robust test battery that measures TFS processing in individual humans. Using this battery, Part 2 subdivided a large sample of listeners (N=200) into groups with “good” and “poor” TFS sensitivity. A comparison of speech-in-noise scores under a range of listening conditions between the groups revealed that good TFS coding reduces the negative impact of reverberation on speech intelligibility, and leads to reduced reaction times suggesting lessened listening effort. These results raise the possibility that cochlear implant (CI) sound coding strategies could be improved by attempting to provide usable TFS information, and that these individualized TFS assays can also help predict listening outcomes in reverberant, real-world listening environments. Finally, the DNN models (Part 3) introduced significant improvements in speech quality and intelligibility, as evidenced by all acoustic evaluation metrics and test results from CI listeners (N=8). These models can be incorporated as “front-end” noise-reduction algorithms in hearing assistive devices, as well as complement other approaches by serving as a research tool to help generate and rapidly sub-select the most viable hypotheses about the role of TFS coding in complex listening scenarios.</p>