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Publication Search Results

Now showing 1 - 10 of 17

Time-varying functional connectivity predicts fluctuations in sustained attention in a serial tapping task

(Georgia Institute of Technology, 2023-05-01) Seeburger, Dolly

There is ambiguity in the literature about how large-scale brain networks contribute to focused attention. Part of the problem comes from the methods of analyses that treat the correlates of attention as a static and discrete measure when in actuality, attention fluctuates from moment to moment. This continuous change in attention is consistent with the dynamic changes in functional connectivity between brain regions involved in the internal and external allocation of attention (Liu & Dyun, 2013). Namely, the default mode network (DMN) and the task positive network (TPN)(Fox et al., 2005). In this study, I investigated how brain network activity varied across different levels of attentional focus (e.g., “zones”). Participants performed a finger-tapping task and, guided by previous research (Esterman et al., 2013), in-the-zone was marked by low reaction time variability and out-of-the-zone as the inverse. Employing a novel method of time-varying functional connectivity, called the quasi-periodic pattern analysis (i.e., reliably observed spontaneous low-frequency fluctuations), I found that the activity between DMN and TPN was more anti-correlated during in-the-zone states versus out-of-the-zone states. Further investigation showed that it is the fronto-parietal control network (FPCN) of the TPN that drives the differentiation. During in-the-zone periods, FPCN synchronized with the dorsal attention network, while during out-of-the-zone periods, FPCN synchronized with DMN. In contrast, the ventral attention network synchronized more closely with DMN during in-the-zone periods compared to out-of-the-zone periods. These findings suggest that time-varying functional connectivity in the low-frequency can tell us how different networks of the brain work together during periods of sustained attention.
Improving Online Instructional Design using Memory, Attention, and Engagement

(Georgia Institute of Technology, 2022-05) Chanda, Ritika

Neuroscience research supports a relationship between the psychological constructions of attention and engagement. The level of selective attention and engagement present during the learning process correlates with increased memory and recall. With the recent rise in online learning, new questions regarding the improvement of educational design, teaching techniques, and learning have created a new avenue of investigation within the field of Neuroeducation. The objective of this study is to identify whether attentional brain networks related to Gagné’s Nine Events of Instruction and engagement can predict learning in an online setting by using fMRI and behavioral techniques. Overall, we found fMRI evidence of engagement, verified engagement’s role in memory and retrieval, and identified three Gagné events (Events 5, 6 and 7) that increase learning among students. This investigation allows for further advancements in online educational design as it will provide instructors with guidance on how to properly build their curriculum and modify the content structure of online classes to highlight techniques that promote successful learning.
Sleep and Quasi-Periodic Patterns During Rest

(Georgia Institute of Technology, 2022-05) Karkare, Maya C.

In this preliminary study, researchers attempted to determine the relationship between sleep and quasi-periodic pattern strength. Three participants wore actigraphy watches for three nights prior to a resting-state functional MRI (rs-fMRI) scan. Actigraphy data was analyzed using the Cole Kripke analysis method. Functional connectivity was analyzed for quasi-periodic patterns (QPPs) between the default mode network (DMN) and the task-positive network (TPN). Due to errors involving preprocessing of rs-fMRI data, proper QPP analyses were unable to be conducted as the QPP template was abnormal. Further analysis of the data collected in the future will yield more conclusive results.
The Impact of Sleep on Quasi-Periodic Patterns During Working Memory Tasks

(Georgia Institute of Technology, 2022-05) Huell, Derek Terrell

Quasi-periodic patterns (QPPs) are a form of low-frequency neural activity that include the interactions of both default mode and task positive networks. As this brain activity occurs constantly in our brains, they are suspected to contribute to the brain's functional connectivity. This is critical to our understanding understanding of the coordination of activity between multiple brain regions over time to accomplish tasks. Thus, this cognitive neuroscience study will seek to illuminate the effects of underlying brain mechanisms on QPPs, representing functional connectivity. Previous literature has shown that the pattern of QPPs may vary between individuals and with levels of sleep, and this variability may impact the brain's functional connectivity. In this study, we will analyze neural activity while participants complete 0-back, 2-back, and flanker tasks and a resting state fMRI scan, and pair these results with a wearable accelerometer to evaluate how sleep levels affect QPPs.
Integrating Neuroimaging and Behavioral Data Using The Multidimensional Generalized Graded Unfolding Model.

(Georgia Institute of Technology, 2021-04-26) Barrett, Matthew E.

A study investigating the relationship between two distinct data structures resulting from the same stimulus was examined. Participants made attractiveness judgments to computer generated models in two phases. Phase 1 of the study was conducted in the laboratory (behavioral) while phase 2 was conducted in the fMRI scanner (neuroimaging). Data from the behavioral component was composed of attractiveness ratings for computer generated models, whereas the neuroimaging component was composed of signal change in five pre-specified ROIs when responding to the identical stimulus. It was hypothesized that both of these outcomes were a function of the distance between a subject’s ideal point and the stimulus location in a latent multidimensional preference space. The attractiveness ratings were modeled with the multidimensional generalized graded unfolding model (MGGUM), which is an item response theory model for proximity-based data presumed to underlie the general preference ratings. The signal change data was simultaneously modeled as a function of the estimated distance between a subject and stimulus derived from the MGGUM. Estimation of models for both types of data was conducted simultaneously using a system of two simultaneous equations with parameters that are updated using a Markov chain Monte Carlo procedure. Information about signal change and its relationship to person-stimulus distances (i.e., idealness) in the multidimensional latent space was utilized to update estimates of the individual’s location in that space and this, in turn, lead to updated predictions of signal change in each ROI. This project was predicated on the notion that both behavioral and neural signal data are a function of the proximity between a given individual and stimulus, and was the first study to integrate models for neural signal into an item response theory framework.
Broad Effects of Arousal on Quasi-Periodic Patterns of Brain Activity

(Georgia Institute of Technology, 2020-12) Humm, Erek Matthew

Quasi Periodic Patterns (QPPs) are recurring patterns of brain activity found in brain imaging data that last approximately 20 seconds and occur at no regular interval. In this experiment, researchers aim to establish a link between the level of mental arousal and the strength and frequency of QPPs. It was thought that increased levels of arousal would result in an increase in the strength and frequency of QPPs. To test this, subjects from three different contrasting experimental groups conducted tasks while in a functional magnetic resonance imaging (fMRI) scanner: (1) young subjects vs. old subjects, (2) task-engaged vs. resting-state, and (3) sleep disorder vs. no disorder. QPPs were regressed from the fMRI scans using an extensive processing and analysis pipeline. It was generally found that increased arousal levels led to an increase in the incidence and strength of QPPs. Increased arousal is present in young subjects, task-engaged subjects, and subjects without sleeping disorders. These results open the door for future experiments to quantify the link between arousal and QPPs. Establishing a link between these two can be vital to future research involving therapeutic devices, diagnostic tools, and even human-computer interfaces.
Neural Activation During Dual-task Processing with Simultaneous Stimulus Presentation

(Georgia Institute of Technology, 2019-08) Alfonso, Juliana

Despite extensive literature regarding response time cost in dual-task processing, the predominant procedures do not isolate task-processing from stimulus processing. The purpose of this study was to investigate the neural correlates of motor learning and dual-task processing using a procedure in which stimulus processing was held constant. Participants learned to make bimanual or unimanual hand responses to indicate the individual or associated pairs of stimuli in two types of tasks. In the independent task (two-set task), participants made a response with the left hand corresponding to the left image shown on the screen and a response with the right hand based on the right image, simultaneously. In the relational task (one-set task), the individuals respond with button-presses to the pair of images shown. Subjects performed an equal number of trials per condition and neural activation during each trial was recorded using fMRI. Preliminary behavioral results showed that there was a significant interaction between task condition and response type, as well as a greater response time-cost for bimanual responses in the independent condition. Imaging analysis suggests significantly greater neural activation in the inferior frontal sulcus (IFS) during the independent task (p<0.01). These preliminary results seem to support the behavioral findings of Schumacher et al. (2018) and implicate, at a neural activation level, a dissociation in the location of task-processing between the independent and relational tasks.
Multimodal investigation of mind wandering and attention lapses

(Georgia Institute of Technology, 2019-07-24) Godwin, Christine A.

The neuroscience of mind wandering has advanced appreciably over the past decade. By applying convergent methods that span self-reports, behavioral indexes, and neuroimaging, researchers have been able to gain an understanding of how the brain supports ongoing mentation that is unrelated to other tasks at hand. However, despite the complex processes that attention lapses can take, research in this field has often focused on simply dichotomizing mind wandering as either on-task or off-task. Furthermore, repeated use of tasks such as the sustained attention to response task (SART) to study mind wandering has constrained research and hampered generalizability. The current work addresses these issues by presenting a novel series of thought prompts that query several attention states and dynamics as participants perform the metronome response task (Seli et al., 2013). In Study 1, simultaneous recording of behavioral performance, fMRI, and pupil diameter allowed for a multimodal investigation of the neural correlates of attention lapses. In Study 2, task difficulty was manipulated in order to test the effect of cognitive load on attention lapses and performance. Results indicated unique behavioral and neural profiles for several attention states and found subtle but consistent differences between self-reported attention state and performance variability. In addition, cognitive load modulated task performance and, to a lesser extent, the frequency of dynamic states (e.g., spontaneous versus constrained attention) in manners consistent with previous theorizing (e.g., the context regulation hypothesis). However, not all measures dissociated across attention states. The results are discussed from the perspectives of mind wandering theories and frameworks, the function of the default mode network, and the importance of task context in the study of attention lapses.
Cognitive adjustments & network interactions

(Georgia Institute of Technology, 2019-03-26) Smith, Derek M.

Our understanding of the neural substrates of cognitive adjustments is fairly limited. Given the growing body of work showing that brain connectivity network interactions are behaviorally relevant, more attention should be paid to network interactions when studying adjustments of cognitive control. Both the Frontoparietal Network (FPN) and the Cingulo-Opercular Network (CON) have been associated with elements of cognitive control. The aim of this study was to gain a better understanding of how these networks contribute to cognitive adjustments, specifically the congruency sequence effect, by testing the hypothesis that increased coupling between these networks is associated with more adjustment in behavior. Additionally, it was predicted that CON activity over and above FPN activity would predict both the neural response in the FPN and behavior on the subsequent trial. A significant congruency sequence effect was not observed in this data set. Inter-network connectivity was shown to be greater prior to relatively fast trials for a subset of subjects. In addition, significant negative modulation of current trial FPN was observed but this modulation could not be clearly linked to behavioral adjustments. Overall, the findings suggest that interactions between these networks have some role to play in performance but the primary hypotheses were not supported.
Investigating the sub-regional organization of the prefrontal cortex

(Georgia Institute of Technology, 2016-11-15) Cookson, Savannah L.

The prefrontal cortex (PFC) is involved in many cognitive processes important for complex, flexible human behavior (e.g., Duncan & Owen, 2000). Recent research has posited at least two axes of functional organization in PFC: a rostrocaudal axis, along which the PFC processes tasks of varying abstractness or complexity (e.g., Badre 2008); and a dorsoventral axis, along which the PFC handles various modes of task-related information (e.g., Goldman-Rakic, 1995; O’Reilly, 2010; Petrides, 1995). However, it remains unclear how these two axes may interact with one another, as well as with other known organizational principles in PFC (viz., lateralization of motor control). The present experiment aimed to address these questions using a novel “hierarchical precuing” task that combined a traditional cuing procedure with a hierarchical mapping structure in an event-related functional magnetic resonance imaging (fMRI) design. Participants made one of four possible judgments about pairs of stimuli based on simple characteristics shared by the pair. Two judgments related to spatial features of the stimuli (viz., left/right or above/below fixation), and two to nonspatial features (viz., color or shape of stimulus). One spatial judgment and one nonspatial judgment are mapped to each hand. Cues presented at the start of each trial allowed participants to prepare response sets based on whether they received information about the upcoming judgment type, response hand, both, or neither. The cues produced a stair-step effect on reaction time as a function of the amount of information presented a priori; that is, as the amount of information contained in the cue increased, reaction time decreased, regardless of the exact information contained in the cue. The fMRI data demonstrated segregation of activity in PFC at the cue time point for the main effects of each factor: a rostrocaudal distribution as a function of cue content; a dorsoventral distribution according to judgment domain; and lateralization of activity as a function of response hand. We then investigated how different combinations of cue content, processing domain, and response hand interact to influence the distribution of activity within these regions of interest (ROIs). These results demonstrate how the functional structure of the PFC integrates these different axes across the cortex and validate the hierarchical precuing task as a procedure for integrating multiple cognitive factors into a single event-related task design.