Digital Commons Network^™

Physiological Rationale For Fixation Eye-Movements, Qasim Zaidi

MODVIS Workshop

No abstract provided.

Are Microsaccades The Cause Of Attention-Related Modulation In Visual Circuits?, Richard Krauzlis, Gongchen Yu, James Herman, Leor Katz

MODVIS Workshop

No abstract provided.

Task-Driven Influences On Fixational Eye Movements, Jonathan Victor, Yen-Chu Lin, Michele Rucci

MODVIS Workshop

There is now compelling evidence that the spatiotemporal remapping carried out by fixational eye movements (FEMs) is an essential step in visual processing. Moreover, the overall Brownian-like statistics of FEMs are calibrated to map fine spatial detail into the temporal frequency range to which retinal circuitry is tuned. Here, we tested the hypothesis that the detailed spatial characteristics of FEMs can be adjusted to task demands via cognitive influences that operate even in the absence of a visual stimulus. We examined FEMs in a task that required subjects (N=6) to report which of two letters was displayed. Trials were blocked; …

Active Encoding Of Space Through Time, Michele Rucci, Jonathan D. Victor

MODVIS Workshop

No abstract provided.

Extracting Edges In Space And Time During Visual Fixations, Lynn Schmittwilken, Marianne Maertens

MODVIS Workshop

No abstract provided.

A Signal Detection Model For The Analysis Of Continuous Response Gradients And An Application To Confidence Rating Data, Fabian A. Soto

MODVIS Workshop

see attached

Modelling Pairwise Comparisons For Thurstonian Scaling And Kendall Rank Correlation, Maarten Wijntjes

MODVIS Workshop

Pairwise comparisons are a simple and effective way to measure the relative ordering of two samples. For more than two samples, a global ordering can be constructed and with sufficient data it is possible to construct a metric scale, for example by using Thurstonian scaling. We will discuss the concept of Number of Distinguishable Levels (NDLs) that emerges from a Thurstonian scaling procedure. The NDL is the attribute range in terms of Just Noticeable Differences (JNDs), for example the number of grayscale values. The NDL is either limited by the visual system or by the range of stimuli. The latter …

The Model 2.0 And Friends: An Interim Report, Garrison W. Cottrell, Martha Gahl, Shubham Kulkarni, Shashank Venkatramani, Yash Shah, Keyu Long, Xuzhe Zhi, Shivaank Agarwal, Cody Li, Jingyuan He, Thomas Fischer

MODVIS Workshop

Last year, I reported on preliminary results of an anatomically-inspired deep learning model of the visual system and its role in explaining the face inversion effect. This year, I will report on new results and some variations on network architectures that we have explored, mainly as a way to generate discussion and get feedback. This is by no means a polished, final presentation!

We look forward to the group’s suggestions for these projects.

Automated Delineation Of Visual Area Boundaries And Eccentricities By A Cnn Using Functional, Anatomical, And Diffusion-Weighted Mri Data, Noah C. Benson, Bogeng Song, Toshikazu Miyata, Hiromasa Takemura, Jonathan Winawer

MODVIS Workshop

Delineating visual field maps and iso-eccentricities from fMRI data is an important but time-consuming task for many neuroimaging studies on the human visual cortex because the traditional methods of doing so using retinotopic mapping experiments require substantial expertise as well as scanner, computer, and human time. Automated methods based on gray-matter anatomy or a combination of anatomy and functional mapping can reduce these requirements but are less accurate than experts. Convolutional Neural Networks (CNNs) are powerful tools for automated medical image segmentation. We hypothesize that CNNs can define visual area boundaries with high accuracy. We trained U-Net CNNs with ResNet18 …

Comprehensive Analysis Of The Retinal Cell Contributions To The Human Erg, Christopher W. Tyler

MODVIS Workshop

Purpose. Standard electroretinogram (ERG) protocols are largely designed to isolate the responses of the rod and cone retinal pathways, including the use of adapting backgrounds to suppress unwanted off-pathway responses. Here, we record spectral ERGs in the low-to-high mesopic sensitivity range in the absence of any adapting background in order to assess interactions between the pathways.

Methods. We have developed a comprehensive neuroanalytic model of the component structure of the ERG driven by knowledge of the underlying retinal physiology, to enhance its power as a critical diagnostic tool for a broad range of both retinal and systemic dysfunctions. The ERG …

Toward A Manifold Encoding Neural Responses, Luciano Dyballa, Andra M. Rudzite, Mahmood S. Hoseini, Mishek Thapa, Michael P. Stryker, Greg D. Field, Steven W. Zucker

MODVIS Workshop

Understanding circuit properties from physiological data presents two challenges: (i) recordings do not reveal connectivity, and (ii) stimuli only exercise circuits to a limited extent. We address these challenges for the mouse visual system with a novel neural manifold obtained using unsupervised algorithms. Each point in our manifold is a neuron; nearby neurons respond similarly in time to similar parts of a stimulus ensemble. This ensemble includes drifting gratings and flows, i.e., patterns resembling what a mouse would “see” running through fields.

Regarding (i), our manifold differs from the standard practice in computational neuroscience: embedding trials in neural coordinates. Topology …

How Object Segmentation And Perceptual Grouping Emerge In Noisy Variational Autoencoders, Ben Lonnqvist, Zhengqing Wu, Michael H. Herzog

MODVIS Workshop

Many animals and humans can recognize and segment objects from their backgrounds. Whether object segmentation is necessary for object recognition has long been a topic of debate. Deep neural networks (DNNs) excel at object recognition, but not at segmentation tasks - this has led to the belief that object recognition and segmentation are separate mechanisms in visual processing. Here, however, we show evidence that in variational autoencoders (VAEs), segmentation and faithful representation of data can be interlinked. VAEs are encoder-decoder models that learn to represent independent generative factors of the data as a distribution in a very small bottleneck layer; …

Constraining The Binding Problem Using Maps, Zhixian Han, Anne Sereno

MODVIS Workshop

We constrained the binding problem by creating maps of different attributes. We compared the performance of different models with different maps in our current study. Our preliminary results showed that the performance of the model is the highest when location maps were used. These results suggest that the optimal way to constrain the binding problem is to create location maps of different attributes.

From Image Gradients To A Perceptual Metric Space, Alan Johnston

MODVIS Workshop

How do we achieve a sense of spatial dimension from a sense of location? There are three predominant ideas about how we achieve this; spatial isomorphism, in which what we see reflects differences in distance or size in the brain; that spatial extent depends upon motor sensations or intentions related to eye movements; and that distance is computed from the degree of correlation in neural activity between adjacent locations, with distance inversely proportional to the correlation. There are problems with each of these approaches, for example, neural correlation may depend more on image structure than adjacency - consider the case …

Evaluating Models Of Scanpath Prediction, Matthias Kümmerer, Matthias Bethge

MODVIS Workshop

No abstract provided.

Modeling The Spread Of Object-Based Attention During Free Viewing, Nicolas Roth, Olga Shurygina, Flora Marleen Muscinelli, Klaus Obermayer, Martin Rolfs

MODVIS Workshop

No abstract provided.

V1 Saliency Hypothesis And Central-Peripheral Dichotomy (Cpd), Li Zhaoping Prof. Dr.

MODVIS Workshop

No abstract provided.

A Dynamical Model Of Binding In Visual Cortex During Incremental Grouping And Search, Daniel Schmid, Daniel A. Braun, Heiko Neumann

MODVIS Workshop

Binding of visual information is crucial for several perceptual tasks. To incrementally group an object, elements in a space-feature neighborhood need to be bound together starting from an attended location (Roelfsema, TICS, 2005). To perform visual search, candidate locations and cued features must be evaluated conjunctively to retrieve a target (Treisman&Gormican, Psychol Rev, 1988). Despite different requirements on binding, both tasks are solved by the same neural substrate. In a model of perceptual decision-making, we give a mechanistic explanation for how this can be achieved. The architecture consists of a visual cortex module and a higher-order thalamic module. While the …

Object Rigidity: Competition And Cooperation Between Motion-Energy And Feature- Tracking Mechanisms And Shape-Based Priors, Akihito Maruya, Qasim Zaidi Dr.

MODVIS Workshop

No abstract provided.

Efficient Perception Of Physical Object Properties With Visual Heuristics, Vivian C. Paulun, Florian S. Bayer, Joshua B. Tenenbaum, Roland W. Fleming

MODVIS Workshop

No abstract provided.

Efficient Coding Of Local 2d Shape, James Elder, Timothy D. Oleskiw, Ingo Fruend, Gerick M. Lee, Andrew Sutter, Anitha Pasupathy, Eero Simoncelli, J Anthony Movshon, Lynne Kiorpes, Najib Majaj

MODVIS Workshop

Efficient coding provides a concise account of key early visual properties, but can it explain higher-level visual function such as shape perception? If curvature is a key primitive of local shape representation, efficient shape coding predicts that sensitivity of visual neurons should be determined by naturally-occurring curvature statistics, which follow a scale-invariant power-law distribution. To assess visual sensitivity to these power-law statistics, we developed a novel family of synthetic maximum-entropy shape stimuli that progressively match the local curvature statistics of natural shapes, but lack global structure. We find that humans can reliably identify natural shapes based on 4^th and …

Simulating Electrified Powertrain Noise And Vibration Measurement Signals For Machine Learning Based Fault Diagnosis Applications, Joohyun Lee, Yangfan Liu, J Stuart Bolton, Patricia Davies

Publications of the Ray W. Herrick Laboratories

Machine learning classification is a common method for vehicle noise and vibration (N&V) fault diagnosis which helps improve vehicle safety, comfort, and reduce maintenance cost. To improve the accuracy of classification, the model requires sufficient training data which is often expensive and time-consuming to acquire. A possible solution to resolve this limitation is to extract representative features from measurement signals and generate realistic simulated signals based on a smaller set of high-quality N&V measurement signals. A method to simulate N&V measurement signals of rotating machineries such as electrified powertrains is proposed. In its feature extraction process, tonal and broadband components …

Leveraging Mathematical Modeling To Analyze Nonadherence For Hydroxyurea Therapy In Sickle Cell Disease, Akancha Pandey, Rubesh Raja, Jeremie H. Estepp, Doraiswami Ramkrishna

Purdue University Libraries Open Access Publishing Fund

Nonadherence is common in individuals with sickle cell disease (SCD) on hydroxyurea therapy and can be observed with waning improvements in hematologic parameters or biomarkers like mean cell volume and fetal hemoglobin level over time. We modeled the impact of hydroxyurea nonadherence on longitudinal biomarker profiles. We estimated the potential nonadherent days in individuals exhibiting a drop in biomarker levels by modifying the dosing profile using a probabilistic approach. Incorporating additional nonadherence using our approach besides existing ones in the dosing profile improves the model fits. We also studied how different patterns in adherence give rise to various physiological profiles …

Frequency Reduction And Attenuation Of The Tire Air Cavity Mode Due To A Porous Lining, Kyosung Choo, Won Hong Choi, Guochenhao Song, J Stuart Bolton

Publications of the Ray W. Herrick Laboratories

The tire air cavity mode is known to be a significant source of vehicle structure-borne road noise near 200 Hz. A porous lining placed on the inner surface of a tire is an effective countermeasure to attenuate that resonance. The two noticeable effects of such a lining are the reduction in the cavity resonance frequency and the attenuation of the air cavity mode. In this paper, through both theoretical and numerical analysis, the mechanisms underlyiing the effects of a porous lining were studied. A two-dimensional duct-shaped theoretical model and a torus-shaped numerical model were created to investigate the lined tire …

A Transfer-Matrix-Based Approach To Predicting Acoustic Properties Of A Layered System In A General, Efficient, And Stable Way, Guochenhao Song, Zhuang Mo, J Stuart Bolton

Publications of the Ray W. Herrick Laboratories

Layered materials are one of the most commonly used acoustical treatments in the automotive industry, and have gained increased attention, especially owing to the popularity of electric vehicles. Here, a method to model and couple layered systems with various layer types (i.e., poro-elastic layers, solid-elastic layers, stiff panels, and fluid layers) is derived that makes it possible to stably predict their acoustical properties. In contrast with most existing methods, in which an equation system is constructed for the whole structure, the present method involves only the topmost layer and its boundary conditions at two interfaces at a time, which are …

Force Amplification At The Wheel Hub Due To The Split In The Air-Cavity Mode For A Rolling Tire, Won Hong Choi, Kyosung Choo, J Stuart Bolton

Publications of the Ray W. Herrick Laboratories

Reduction of tire/road noise has become an important issue for EVs since powertrain noise has largely been eliminated. A tire’s air-cavity mode is known to be a significant contributor to increased forces at the wheel hub, which can result in significant interior noise levels near 200 Hz. Moreover, the single natural frequency of a static, undeformed tire can separate into two neighboring frequencies for a rolling, deformed tire due to the combination of the tire’s asymmetry, and the Doppler effect resulting from the tire’s rotation. In this study, the evolution of the Doppler-related frequency split with increasing speed was observed …

Downstream Effects: Impact Of Antibiotic Pollution On An Aquatic Host-Parasite Interaction, Hannah G. Melchiorre, Stephanie O. Gutierrez, Dennis J. Minchella, Jing Trevor Vannatta

Purdue University Libraries Open Access Publishing Fund

The global increase in antibiotic use has led to contamination of freshwater environments. Despite the identified impacts of antibiotics on humans and wildlife, the effect of antibiotics on host–parasite life cycles in freshwater is relatively unexplored. In the current study, we utilize the trematode parasite Schistosoma mansoni, and its snail intermediate host, Biomphalaria glabrata, to investigate the influence of an ecologically relevant antibiotic concentration on the life history characteristics of both parasite and host. Our results demonstrate that antibiotics not only accelerate parasite development time, but also increase host reproduction and delay parasite-induced host castration. Using a mathematical …

The Role Of Community Healthcare Professionals In Discussing Sexual Assault Experiences During Obstetrics And Gynecological Healthcare Appointments, Andrea L. Demaria, Stephanie Meier, Hannah King, Haley Sidorowicz, Kathryn C. Siegfried-Spellar, Laura M. Schwab-Reese

Purdue University Libraries Open Access Publishing Fund

Background

Nearly half of adult women in the US report experiencing sexual assault, with almost one-fifth reporting rape. For many sexual assault survivors, healthcare professionals are the first point of contact and disclosure. This study aimed to understand how healthcare professionals working in community settings perceived their role in discussing sexual violence experiences with women during obstetrical and gynecological healthcare appointments. The secondary purpose was to compare healthcare professionals’ perspectives with the patients’ to determine how sexual violence conversations should occur in these environments.

Methods

Data were collected in two phases. Phase 1 consisted of 6 focus groups (Sept-Dec, 2019) …

Iodinated Non-Ionic Contrast Medium Does Not Inhibit E. Coli Growth In Ex Vivo Inoculated Canine Urine, Maxime G. Derre, Sarah M. Steinbach, Gena K. Hendrix, Meggan Stanton, Larry G. Adams

Purdue University Libraries Open Access Publishing Fund

OBJECTIVE

To investigate the effect of iohexol on standardized quantitative urine culture results in dogs. The authors hypothesized that the presence of iohexol in inoculated urine samples would result in lower bacterial concentrations (CFU/mL) and, therefore, decrease culture sensitivity.

SAMPLE

Urine samples were aseptically collected during cystoscopy from a single client-owned dog untreated with antimicrobials.

PROCEDURES

An experimental controlled study. The urine sample was divided into 38 aliquots (0.5 mL each) that were used as negative controls or inoculated with an equal amount of Escherichia coli (105 CFU/mL). Different volumes (0.1 and 0.5 mL) of contrast or saline were added …

Closing Thoughts, Mark Lundstrom

American Journal of Rising Scholar Activities

No abstract provided.