Inaug.-Diss.--Bern.

Thesis (Ph. D.)--University of Wisconsin--Madison, 1937. / Typescript. Includes abstract and vita. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaves 47-48).

Thesis (Ph. D.)--University of Wisconsin--Madison, 1976. / Typescript. Vita. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaves 134-142).

published_or_final_version / Medical Sciences / Master / Master of Medical Sciences

Title from PDF of title page (University of Missouri--Columbia, viewed on Feb 26, 2010). The entire thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file; a non-technical public abstract appears in the public.pdf file. Dissertation advisor: Dr. Gang Yao. Vita. Includes bibliographical references.

Thesis (M.Med.Sc.)--University of Hong Kong, 2004. / Also available in print.

The sensitivity of pupillary responses (PR) to emotional states brought on by psychological state of deception was explored. Utilizing a combination of guilty person and guilty knowledge techniques, 16 male and 14 female Ss were presented with neutral and relevant names, with relevant names involving deception. Half of the Ss were presented with one relevant name and the other half were presented with two. The lists of five names were presented on three trials during which PR and GSR were monitored. Pupiliary responses and GSRs to relevant names were significantly different than PRs and GSRs to neutral names. There were no significant effects with respect to the number of relevant names and trials. In terms of detection rates, GSR yielded higher rates than PR. The correlational tests indicated no significant relationship between PR and GSR under the experimental conditions employed.

Engagement with educational instruction and related materials is an important part of learning and contributes to test performance. There are various measures of engagement including self-reports, observations, pupil diameter, and posture. With the challenges associated with obtaining accurate engagement levels, such as difficulties with measuring variations in engagement, the present study used a novel approach to predict engagement from posture by using deep learning. Deep learning was used to analyze a labeled outline of the participants and extract key points that are expected to predict engagement. In the first experiment two short lectures were presented and participants were tested on a lecture to motivate engagement. The next experiment had videos that varied in interest to understand whether a more interesting presentation engages participants more, therefore helping participants achieve higher comprehension scores. In a third experiment, one video was presented to attempt to use posture to predict comprehension rather than engagement. The fourth experiment had videos that varied in level of difficulty to determine whether a challenging topic versus an easier topic affects engagement. T-tests revealed that the more interesting Ted Talk was rated as more engaging, and for the fourth study, the more difficult video was rated as more engaging. Comparing average pupil sizes did not reveal significant differences that would relate to differences in the engagement scores, and average pupil dilation did not correlate with engagement. Analyzing posture through deep learning resulted in three accurate predictive models and a way to predict comprehension. Since engagement relates to learning, researchers and educators can benefit from accurate engagement measures. / Includes bibliography. / Dissertation (Ph.D.)--Florida Atlantic University, 2020. / FAU Electronic Theses and Dissertations Collection

The overarching purpose of this work is to investigate the effect of pupil-linked arousal systems and heart rate-linked arousal systems on behavior and the use of pupil dynamics as an index for adaptive behavior. These arousal systems are correlated with behavior states which have modulatory effects on perception and neural coding and are therefore integral in carrying out complex behaviors, such as decision-making. Additionally, cholinergic transmission is proposed to be critical for adaptive behavior via its modulation of thalamic neurons. While the first two chapters focus on the behavior output and the non-invasive ways to index arousal and behavior, the third aim attempts to investigate the neural circuits that underlie arousal’s effect on adaptive behavior by studying the pattern of cholinergic axons between brainstem nuclei and the thalamus, opening avenues for future investigation of their mechanistic impact on adaptive behavior. For characterization of the influence of arousal indexed by pupil dynamics and heartbeat dynamics, we simultaneously recorded electrocardiogram (ECG) and pupil size in head-fixed rats performing tactile discrimination tasks. We found both heartbeat dynamics and pupil size co-varied with behavioral outcomes, indicating behavior was dependent upon arousal indexed by both physiological signals. The potential difference between the effects of pupil-linked arousal and heart-rate linked arousal on behavior were estimated by constructing a Bayesian decoder predicting animals’ behavior from both signals prior to stimulus presentation. The decoder performed significantly better when using both physiological signals as inputs, suggesting both arousal systems, pupil-linked and heart rate-linked are not completely redundant. Additionally, the pupil size-based decoder failed to correctly predict animals’ behavior on a substantial portion of trials correctly predicted by the heart rate-based decoder, furthermore suggesting that both arousal systems exert different influences on animals’ behavior (Y.Liu, S. Narasimhan, B.J.Schriver, & Q.Wang, 2021). For characterization of how adaptive behavior in response to changing sensory environments depends on pupil-linked arousal, we recorded pupil size and behavioral output simultaneously during a similar tactile Go/No-Go discrimination task while systematically varying the statistics of the sensory environment. For each session, the probability of the presence of reward linked-stimuli (S+/Go) was randomly set at 80%, 50% or 20%. Animals adapted their behavioral responses and the task evoked pupil responses were bigger when the probability of S+ was lower. Impulsive licking (pre-stimulus response) decreased as the probability of S+ was lower. Animals became more liberal as the probability of S+ increased, in line with signal detection theory, indexed by a decrease in the decision criterion. We additionally found that reaction time decreased as the probability of S+ increased. A hierarchical drift diffusion model (HDDM) was used to model the decision-making process in these paradigms. We found the drift rate to monotonically vary with task difficulty. Animals performed sub-optimally to adaptively change their action in response to changes in the sensory environment and this adaptive adjustment in decision-making was indexed by their pupil dynamics. For studying the pattern of cholinergic axons between brainstem nuclei and the thalamus, we used two different AAV-retrograde constructs with two different reporters (mCherry and GFP) injected in the left and right hemisphere of the ventral-posterior-medial (VPM) thalamic nucleus of recombinant ChAT-cre mice. In agreement with previous studies done with conventional tracing methods, labelled projecting cells were traced to the LDT and PPN in the brainstem. Labelled cells were found in a clustered area of the LDT, suggesting a topographic distribution of the projections between the LDT and the VPM. A larger quantity of labelled cells was found in the PPN than the LDT. Additionally, bilateral injections with double reporters enabled us to find that a majority of cells project from the brainstem to the VPM project ipsilaterally while still displaying lateralization. This work provides methods and tools for future investigation of the functional impact of these projections between LDT, PPN and the VPM.