Cognitive Neuroscience Commons^™

A Bayesian Account Of Depth From Shadow, James Elder, Patrick Cavanagh, Roberto Casati

MODVIS Workshop

When an object casts a shadow on a background surface, the offset of the shadow can be a compelling cue to the relative depth between the object and the background (e.g., Kersten et al 1996, Fig. 1). Cavanagh et al (2021) found that, at least for small shadow offsets, perceived depth scales almost linearly with shadow offset. Here we ask whether this finding can be understood quantitatively in terms of Bayesian decision theory.

Estimating relative depth from shadow offset is complicated by the fact that the shadow offset is co-determined by the slant of the light source relative to the …

Identifying And Localizing Multiple Objects Using Artificial Ventral And Dorsal Visual Cortical Pathways, Zhixian Han, Anne Sereno

MODVIS Workshop

We concluded in our previous study that model cortical visual pathways actively retained information differently according to the different goals of the training tasks. One limitation of our study was that there was only one object in each input image whereas in reality there may be multiple objects in a scene. In our current study, we try to find a brain-like algorithm that can recognize and localize multiple objects.

Impact Of Brain State On Visual And Prefrontal Population Coding In Behaving Animals, Russell Milton

Dissertations and Theses (Open Access)

Patterns of neural activity in the brain constantly shift between different processing states. Earlier studies have established that the ongoing, spontaneous activity has major repercussions regarding how the brain processes incoming sensory stimuli. However, the interaction between behavioral activity and brain states throughout the cortical hierarchy of primates has not been understood. In particular, technical considerations have greatly limited the range of physical activities in which primate neuronal activity can be recorded. We have implemented two separate strategies to overcome these limitations. First, we have advanced wireless electrophysiological methodologies that enable recording high-yield neuronal data from animals as they freely …

Beyond Homogenous Decision-Making Models: Role Of Brain Areas Interaction And Heterogeneity, Mohsen Rakhshan

Dartmouth College Ph.D Dissertations

Most existing mechanistic models of decision making consider microcircuits within a homogenous brain area and fail to consider the distributed nature of this cognitive process. More specifically, these models do not take into account: a) how different types of information might influence choice in different stages of the process; and b) how interactions and the heterogeneity between circuits across different brain areas might be essential for the process. In this dissertation, I present a combination of experimental and modeling approaches to study distributed nature of the decision-making by examining both the distributed processing of information as well as the interaction …

The Neurological Asymmetry Of Self-Face Recognition, Aleksandra Janowska, Brianna Balugas, Matthew Pardillo, Victoria Mistretta, Katherine Chavarria, Janet Brenya, Taylor Shelansky, Vanessa Martinez, Kitty Pagano, Nathira Ahmad, Samantha Zorns, Abigail Straus, Sarah Sierra, Julian Keenan

Department of Biology Faculty Scholarship and Creative Works

While the desire to uncover the neural correlates of consciousness has taken numerous directions, self-face recognition has been a constant in attempts to isolate aspects of self-awareness. The neuroimaging revolution of the 1990s brought about systematic attempts to isolate the underlying neural basis of self-face recognition. These studies, including some of the first fMRI (functional magnetic resonance imaging) examinations, revealed a right-hemisphere bias for self-face recognition in a diverse set of regions including the insula, the dorsal frontal lobe, the temporal parietal junction, and the medial temporal cortex. In this systematic review, we provide confirmation of these data (which are …

Cortical Dynamics Of Language, Kiefer Forseth

Dissertations and Theses (Open Access)

The human capability for fluent speech profoundly directs inter-personal communication and, by extension, self-expression. Language is lost in millions of people each year due to trauma, stroke, neurodegeneration, and neoplasms with devastating impact to social interaction and quality of life. The following investigations were designed to elucidate the neurobiological foundation of speech production, building towards a universal cognitive model of language in the brain. Understanding the dynamical mechanisms supporting cortical network behavior will significantly advance the understanding of how both focal and disconnection injuries yield neurological deficits, informing the development of therapeutic approaches.

When The Brain Plays A Game: Neural Responses To Visual Dynamics During Naturalistic Visual Tasks, Jason Ki

Dissertations and Theses

Many day-to-day tasks involve processing of complex visual information in a continuous stream. While much of our knowledge on visual processing has been established from reductionist approaches in lab-controlled settings, very little is known about the processing of complex dynamic stimuli experienced in everyday scenarios. Traditional investigations employ event-related paradigms that involve presentation of simple stimuli at select locations in visual space and discrete moments in time. In contrast, visual stimuli in real-life are highly dynamic, spatially-heterogeneous, and semantically rich. Moreover, traditional experiments impose unnatural task constraints (e.g., inhibited saccades), thus, it is unclear whether theories developed under the reductionist …

Investigating The Role Of Attention And Memory In Visual Exploration, Jacob E. Suffridge

Graduate Theses, Dissertations, and Problem Reports (ETD)

This research investigates the role that attention and memory plays in visual exploration through a comprehensive analysis of eye movement and behavioral data, alongside incorporation of a computational saliency model. The purpose of this project is to quantify differences in visual attention over repeated viewings of natural scene images by employing a free viewing task that contains a memory component. In Chapter 2, we explore the task’s behavioral data showing that participants generally memorize our images well before we investigate the effect of numerous object and individual feature inclusion. In Chapter 3, we develop four primary methods to quantify visual …

Exploring Effects Of Background Music In A Serious Game On Attention By Means Of Eeg Signals In Children, Fettah Kiran

LSU Master's Theses

Music and Serious Games are separately useful alternative therapy methods for helping people with a cognitive disorder, including Attention Deficit Hyperactivity Disorder (ADHD). The goal of this thesis is to explore the effect of background music on children with and without ADHD. In this study, a simple Tetris game is designed with Beethoven, Mozart music, and no-music. There are different brainwave techniques for recording; among others, the electroencephalography (EEG) allows for the most efficient use of BCI. We recorded the EEG brain signals of the regular and ADHD subjects who played the Tetris we designed according to our protocol that …

Using Machine Learning To Conduct A Detailed Behavioral Analysis In An Appetitive Social Learning Task, Thomas Shao

Honors Scholar Theses

Learning by watching others, or observational learning, is important for social development and survival. However, not much is known about the brain mechanisms underlying this type of learning. Since the 1960s, observational learning has been widely studied in humans, but developing and analyzing experiments for animals has been challenging. Here, I explore observational learning using a novel paradigm while performing an analysis that involves tracking the rats using an active learning paradigm called DeepLabCut. In this novel paradigm, customized operant conditioning chambers are used for the rats to observe and learn from another animal repeatedly on multiple trials each day. …

Serum-Based Biomarkers And Magnetic Resonance Imaging Following Mild Traumatic Brain Injury In Collegiate Athletes Post Return-To-Play, Taylor R. Susa

All NMU Master's Theses

Recently there has been an increase in the use of MRI (Magnetic Resonance Imaging), to measure the effects of traumatic brain injury (TBI). Proteins such as BDNF, S100B, UCH-L1, and Tau have been found to have altered levels in blood serum after TBI. However, there is limited knowledge about the relationship between serum-based and MRI-based biomarkers in concussed athletes post return-to-play. This study aimed to bridge this gap by collecting serum samples from 42 participants across two groups. The first group (n = 21) consisted of recently cleared to return-to-play collegiate athletes after experiencing a sports-related concussion. The second group …

Mechanisms Of Value-Biased Prioritization In Fast Sensorimotor Decision Making, Kivilcim Afacan-Seref

Dissertations and Theses

In dynamic environments, split-second sensorimotor decisions must be prioritized according to potential payoffs to maximize overall rewards. The impact of relative value on deliberative perceptual judgments has been examined extensively, but relatively little is known about value-biasing mechanisms in the common situation where physical evidence is strong but the time to act is severely limited. This research examines the behavioral and electrophysiological indices of how value biases split-second perceptual decisions and the possible mechanisms underlying the process. In prominent decision models, a noisy but statistically stationary representation of sensory evidence is integrated over time to an action-triggering bound, and value-biases …

What Makes An Image Memorable? Effects Of Encoding On The Mechanism Of Recognition, Asiya Gul

Theses and Dissertations (Comprehensive)

Memory is undoubtedly one of the most important processes of human cognition. A long line of research suggests that recognition relies on the assessment of two explicit memory phenomena: familiarity and recollection. Researchers who support the Dual Process Signal Detection (DPSD) model of recognition memory link the FN400 component (a negative ERP deflection peaking around 400 ms at frontal electrodes) with familiarity; however, it is currently unclear whether the FN400 reflects familiarity or implicit memory. Three event-related potentials (ERP) studies were conducted to determine whether implicit memory plays a role in setting up encoding strategies, and how these encoding strategies …

Variance Partitioning Reveals Consistent Representation Of Object Boundary Contours In Lo Across Different Datasets, Mark D. Lescroart, Utkarsh Singhal

MODVIS Workshop

No abstract provided.

The 5-Ht1a-R Knockout Mouse As A Model Of Later Life Anxiety Disorders: Implications For Sex Differences, Tatyana Budylin

Dissertations, Theses, and Capstone Projects

Anxiety affects nearly twice as many women as it affects men across all cultures and economic groups. Importantly, girls have a higher chance of inheriting anxiety disorders than boys, and many anxiety disorders appear at a very young age. However, little is known about sex differences in brain and behavioral development and how they relate to anxiety in adulthood. Serotonin 1A receptor (5-HT_1A-R) mediated signaling has been implicated in depression and anxiety, however most studies that focus on the involvement of the 5-HT_1A-R have been conducted in adults. Little is known about how the 5-HT_{1A …}

The Characterization Of Alzheimer’S Disease And The Development Of Early Detection Paradigms: Insights From Nosology, Biomarkers And Machine Learning, Isabel Milano

CMC Senior Theses

Alzheimer’s Disease (AD) is the only condition in the top ten leading causes of death for which we do not have an effective treatment that prevents, slows, or stops its progression. Our ability to design useful interventions relies on (a) increasing our understanding of the pathological process of AD and (b) improving our ability for its early detection. These goals are impeded by our current reliance on the clinical symptoms of AD for its diagnosis. This characterizations of AD often falsely assumes a unified, underlying AD-specific pathology for similar presentations of dementia that leads to inconsistent diagnoses. It also hinges …

Temporal Information Guides Prefrontal Preparatory Activity, Jacqueline R. Janowich

Shared Knowledge Conference

Proactive preparation for an upcoming goal differs from last-minute reactive adaptation, but it is unclear how preparatory mechanisms change based on when in the future a goal needs to be executed. To assess how timing information is integrated into preparatory control, we designed a novel variant of the Dot Pattern Expectancy task, where each cue signaled both task rule and delay duration (known short, known long, or unknown) between cue and probe. We recorded EEG while healthy young adult participants (n=36) performed this task, and found that delay demands elicited distinct prefrontal preparatory activities. Medial prefrontal amplitude was sensitive to …

Population Codes And Their Correlates In Decision Making, Neda Shahidi

Dissertations and Theses (Open Access)

This dissertation was organized in two parts: in part 1, we discussed Neural Correlates of Perceptual Accuracy” and in part 2 we discussed “Strategy encoding in Prefrontal Cortex”.

Abstract of part 1_The accurate transmission of electrical signals within neocortex is central to sensory perception and cognition. Theoretical studies have long proposed that the temporal coordination of cortical spiking activity controls signal transmission and cognitive function. In reality, whether and how the precise temporal coordination in neuronal populations during wakefulness influences perception remains a mystery. Here, we simultaneously recorded populations of neurons in early and mid-level visual cortex (areas V1 …

Linking Signal Detection Theory And Encoding Models To Reveal Independent Neural Representations From Neuroimaging Data, Fabian A. Soto

MODVIS Workshop

No abstract provided.

A Feature-Based Model Of Visually Perceiving Deformable Objects, Vivian C. Paulun, Filipp Schmidt, Roland W. Fleming

MODVIS Workshop

No abstract provided.

Effect Of Noise On Mutually Inhibiting Pyramidal Cells In Visual Cortex: Foundation Of Stochasticity In Bi-Stable Perception, Naoki Kogo, Felix Kern, Thomas Nowotny, Raymond Van Ee, Richard Van Wezel, Takeshi Aihara

MODVIS Workshop

Bi-stable perception has been an important tool to investigate how visual input is interpreted and how it reaches consciousness. To explain the mechanisms of this phenomenon, it has been assumed that a mutual inhibition circuit plays a key role. It is possible that this circuit functions to resolve ambiguity of input image by quickly shifting the balance of competing signals in response to conflicting features. Recently we established an in vitro neural recording system combined with computerized connections mediated by model neurons and synapses (“dynamic clamp” system). With this system, mutual inhibition circuit between two pyramidal cells from primary visual …

Why Latent Representations In Convolutional Neural Networks Fall Outside Visual Space, Katerina Malakhova

MODVIS Workshop

It is common to compare properties of visual information processing by artificial neural networks and the primate visual system.

Some remarkable similarities were observed in the responses of neurons in IT cortex and units in higher layers of CNNs. Here I show that latent representations formed by weights in convolutional layers do not necessarily reflect visual domain. Instead they are strongly dependent on a choice of training set and cost function.

The most striking example is when an individual unit, which is highly selective to some members of a category is, nevertheless, inhibited by visually similar objects of the same …

The Rhetoric Of Science Education And Technology, Iwasan D. Kejawa

School of Computing: Faculty Publications

Nearly thousands of science experiments are performed both on humans and animals every year in the United States (Gregory, 1999). Does Science enormously play a role in the well-beings of individual in the society? Research has found that science education is through motivation and satisfying the needs of humans. The scientific world is part of an elongated human development. This can be substantiated with the use and evolution of TECHNOLOGY and SCIENCE (Minton, 2004). Education of the entities that comprise the need to achieve the goal of TECHNOLOGY and SCIENCE which are important issues of today. Research has shown that …

Central And Peripheral Difference In Perceptual Bias In Ambiguous Perception Using Dichoptic Stimuli --- Implications For The Analysis-By-Synthesis Process In Visual Recognition, Li Zhaoping Prof

MODVIS Workshop

No abstract provided.

Similarity-Based Fusion Of Meg And Fmri Discerns Early Feedforward And Feedback Processing In The Ventral Stream, Yalda Mohsenzadeh Dr., Radoslaw Martin Cichy Dr., Aude Oliva Dr., Dimitrios Pantazis Dr.

MODVIS Workshop

Successful models of vision, such as DNNs and HMAX, are inspired by the human visual system, relying on a hierarchical cascade of feedforward transformations akin to the ventral stream. Despite these advances, the human visual cortex remains unique in complexity, with feedforward and feedback pathways characterized by rapid spatiotemporal dynamics as visual information is transformed into semantic content. Thus, a systematic characterization of the spatiotemporal and representational space of the ventral visual pathway can offer novel insights in the duration and sequencing of cognitive processes, suggesting computational constraints and new architectures for computer vision models.

To discern the feedforward and …

On The Origin Of Sensory Errors, Jonathan R. Flynn

Dissertations and Theses (Open Access)

Estimation of perceptual variables is imprecise and prone to errors. Although the properties of these perceptual errors are well characterized, the physiological basis for these errors is unknown. One previously proposed explanation for these errors is the trial-by-trial variability of the responses of sensory neurons that encode the percept. Initially, it would seem that a complicated electrophysiological experiment would need to be performed to test this hypothesis. However, using a strong theoretical framework, I demonstrate that it is possible to determine statistical characteristics of the physiological mechanism responsible for perceptual errors solely from a behavioral experiment. The basis for this …

Rules And Mechanisms For Efficient Two-Stage Learning In Neural Circuits, Tiberiu Teşileanu, Bence Ölveczky, Vijay Balasubramanian

Publications and Research

Trial-and-error learning requires evaluating variable actions and reinforcing successful variants. In songbirds, vocal exploration is induced by LMAN, the output of a basal ganglia-related circuit that also contributes a corrective bias to the vocal output. This bias is gradually consolidated in RA, a motor cortex analogue downstream of LMAN. We develop a new model of such two-stage learning. Using stochastic gradient descent, we derive how the activity in ‘tutor’ circuits (e.g., LMAN) should match plasticity mechanisms in ‘student’ circuits (e.g., RA) to achieve efficient learning. We further describe a reinforcement learning framework through which the tutor can build its teaching …

The Impact Of Cortical State On Neural Coding And Behavior, Charles Beaman

Dissertations and Theses (Open Access)

The brain is never truly silent – up to 80% of its energy budget is expended during ongoing activity in the absence of sensory input. Previous research has shown that sensory neurons are not exclusively influenced by external stimuli but rather reflect interactions between sensory inputs and the ongoing activity of the brain. Yet, whether fluctuations in the state of cortical networks influence sensory coding in neural circuits and the behavior of the animal are unknown. To shed light on this issue, we conducted multi-unit electrophysiology experiments in visual areas V1 and V4 of behaving monkeys. First, we studied the …

Parametrically Constrained Lightness Model Incorporating Edge Classification And Increment-Decrement Neural Response Asymmetries, Michael E. Rudd

MODVIS Workshop

Lightness matching data from disk-annulus experiments has the form of a parabolic (2^nd-order polynomial) function when matches are plotted against annulus luminance on log-log axes. Rudd (2010) has proposed a computational cortical model to account for this fact and has subsequently (Rudd, 2013, 2014, 2015) extended the model to explain data from other lightness paradigms, including staircase-Gelb and luminance gradient illusions (Galmonte, Soranzo, Rudd, & Agostini, 2015). Here, I re-analyze parametric lightness matching data from disk-annulus experiments by Rudd and Zemach (2007) and Rudd (2010) for the purpose of further testing the model and to try to constrain …

Identifying Falsifiable Predictions Of The Divisive Normalization Model Of V1 Neurons, Tadamasa Sawada, Alexander A. Petrov

MODVIS Workshop

The divisive normalization model (DNM, Heeger, 1992) accounts successfully for a wide range of phenomena observed in single-cell physiological recordings from neurons in primary visual cortex (V1). The DNM has adjustable parameters to accommodate the diversity of V1 neurons, and is quite flexible. At the same time, in order to be falsifiable, the model must be rigid enough to rule out some possible data patterns. In this study, we discuss whether the DNM predicts any physiological result of the V1 neurons based on mathematical analysis and computational simulations. We identified some falsifiable predictions of the DNM. The main idea is …