• 2014-2023close
• Open Access close
• Other research products close
• US close
• English close
• Neuroinformatics close

Human development is a dynamic, protracted process influenced by genetics, the environment, experience, and many other factors. During development, an individual develops an entirely unique neural architecture along with a unique set of cognitive skills and abilities. Through recent large-scale pediatric neuroimaging initiatives, we now have a better understanding of the protracted structural changes occurring in the developing brain. We are also beginning to map out relationships between developing brain structure and domain-specific cognition, although we haven’t fully characterized these relationships and their variability throughout typical development. The goal of this work is to assess how individual differences in regional cortical and subcortical brain structure are related to behavioral and cognitive variability in different domains during childhood and adolescence, which is a period of rapid dynamic change. This work also aims to investigate overlapping as well as distinguishing characteristics of the relationships between developing neural systems and domain-specific cognition. In this dissertation, I focus on three cognitive domains: phonological awareness, spatial working memory, and response inhibition. These three cognitive domains are thought to involve relatively distinct brain regions and networks, allowing us to investigate the specificity of associations between structure and function in the developing brain. In addition, these three domains have been well studied in pediatric, clinical, and adult populations in behavioral and functional neuroimaging studies, leading to relatively well-defined region-specific hypotheses. Utilizing three distinct cognitive domains also supports the investigation of domain-general aspects of cognitive development, such as latent factors or skills supporting multiple areas of cognitive development. In addition, studying multiple cognitive domains allows me to study the reflection of any shared features in the neural architecture. I will first address the region-specific associations between cortical and white matter regions thought to be principally related to each cognitive domain. Following that, I will carry out a more data-driven analysis aimed at exploring possible latent factors underlying the associations between these cognitive domains and structural regions. These results may provide insight into the neurobiological correlates of cognitive development and the nature of individual difference variability during development.

Mapping presents a compelling way to demystify complex data and concepts into useful visual information that most people can understand regardless of language, level of literacy, or culture. These maps can also be shared instantaneously with the world via the Internet. Interactive community mapping (ICM) is one method of information and communication technology (ICT)-enabled participatory mapping. In the development context, ICM can be a useful approach in helping community members, members of civil society organizations (CSOs), governments, and development partners to better picture and assess the needs and concerns of the mapped communities and adjust development plans, activities, and policies accordingly. This note is aimed at providing step-by-step guidance on the design and implementation of the ICM process to achieve an evidence-based and increasingly participatory decision-making approach for development projects. Relying on good practice examples from Kenya and Tanzania, this note seeks to provide a better understanding of how the potential benefits of ICM can be translated into tangible results. The note outlines some of the available ICM technology, delineate the enabling environment for ICM, and provide step-by-step guidance on how to effectively design and implement ICM in projects.

Timing is an essential component of human actions, and is the foundation of any sort of sequential behavior, from picking up a glass to playing an instrument or dancing. Because of this, our understanding of how we represent time in the brain (i.e., the human timing system) critically relies on basic research on simple behaviors. Perception of temporal regularities is central to a wide range of basic actions, but also underpins abilities unique to humans such as the creation of complex musical scores. This dissertation is an in-depth examination of endogenously and exogenously guided timing behavior, and how context is a critical component of understanding rhythmic entrainment in humans. We previously validated “gold standard” functional magnetic resonance imaging (fMRI) findings on action-based timing behavior using functional near infrared spectroscopy (fNIRS) (Rahimpour et al., 2020). In particular, we observed significant hemodynamic responses in cortical areas in direct relation to the complexity of the behavior being performed. To do so, we probed multiple levels of contextual influence on action-based timing behavior and patterns of cortical activation as measured using fNIRS. Our findings highlighted several distinct, context-dependent parameters of specific timing behaviors. Here we further interrogate human timing abilities by introducing variations of our original experimental design, observing that subtle contextual variations have a significant impact on the degree of rhythmic entrainment given the presence/absence of metronomic input. We used electroencephalogram (EEG) to further validate our fNIRS findings, demonstrating that single trial neurobiological activity can be used to predict whether behavior is exogenously or endogenously guided. We also found that patterns of neural activity correspond to differential use of the internal timing system, and that specific differences in neural activity correlate with accuracy of action-based timing behavior. These findings emerged from our use of a novel deep learning approach to extract person-specific, neural-based features as predictors of behavioral performance. Finally, we examined whether fNIRS and EEG produced similar localization information, finding that the influence of training factors on cortical localization must be accounted for to make such comparisons.

This paper reports on an investigation of mathematics anxiety (MA) among 40 Korean undergraduate students, using cognitive neuroscience. In Spring 2015, we collected data on correct response rates and reaction times from computer-based activities related to quadratic functions. We also measured brain response through event related potentials (ERP). Results demonstrate that students with higher mathematics anxiety (HMA) took more time than students with lower mathematics anxiety (LMA), both in translating equations to graphs and in translating graphs to equations. Moreover, based on analysis of ERP, brain waves of the HMA group recorded higher amplitude. In specific, both groups showed higher amplitude in translation from graphs to equation than vice versa. Higher amplitudes indicate greater demands on working memory, which we discuss in the concluding section, especially with regard to MA.

Degenerative cervical myelopathy (DCM) is a chronic, progressive disorder characterized by the age-related degeneration of osseocartilaginous structures within the cervical spine resulting in narrowing of the spinal canal and chronic compression of the spinal cord. Chronic spinal cord compression can result in persisting neck pain and neurological deficits including loss of fine motor skills, weakness or numbness in the upper limbs, and gait abnormalities and imbalance, ultimately requiring surgical intervention to relieve cord compression. DCM is the most common form of spinal cord injury in adults and as the elderly population continues to grow, incidence of DCM will rise alongside an increased demand on healthcare resources. Further investigation into the neural response to chronic spinal cord compression may not only inform disease progression and prognosis but may benefit patient monitoring and treatment planning.This dissertation aims to elucidate how symptom presentation, degree of spinal compression, microstructural and cellular integrity of the affected cord, and sex impact supraspinal structure and function in patients with DCM. To address the goals of the dissertation, we implemented a multimodal neuroimaging approach including anatomical, functional, and diffusion imaging of the brain and T2-weighted, diffusion, and metabolic imaging of the spine. First, we characterized and compared spinal cord compression induced alterations in cerebral morphometry and functional connectivity between symptomatic DCM and asymptomatic spinal cord compression (ASCC) patients to further uncover potential compensatory neural mechanisms driving symptom presentation and disease progression. Because the degree of cervical cord compression is not strongly linked to symptom severity, we investigated whether macrostructural, microstructural, and metabolic properties of the cervical spinal cord result in conventional anatomical and functional alterations within the brains of patients with DCM. Lastly, we identified sex-specific differences on cerebral structure and functional connectivity in patients with DCM. In summary, the dissertation revealed unique cerebral signatures between symptomatic and asymptomatic patients, novel insights into the interrelationship between spinal and supraspinal alterations, and sex-specific supraspinal reorganization in patients with DCM. Findings from this work contribute to our knowledge of disease characteristics and compensatory neural mechanisms; and may benefit future development of non-invasive imaging biomarkers, more precise predicative models to inform disease progression, and novel pharmacological strategies to enhance neuroprotective mechanisms and functional recovery in patients with DCM.

In daily life, moral judgments are embedded in dynamic, complex, and contextualized environments. As we reason about morally right or wrong behaviors, our personal history shapes how we judge who did what to whom, where, when, and why. Yet, surprisingly little is known about how individual differences in moral dispositions modulate shared neural response patterns when processing increasingly complex moral scenarios. Consequently, we herein examine brain-behavior-trait coherence in moral cognition across three datasets of increasing naturalistic complexity. Applying intersubject representational similarity analysis, we demonstrate how between-subject variability in moral dispositions modulates similarity in neural responses when processing decontextualized moral vignettes, auditory movie summaries, political attack advertisement, soap opera clips, and full-length movies. Our approach highlights how brain-behavior-trait relationships during moral cognition are shaped by paradigm choice, and provides a reference for conducting research at the intersection of socio-moral cognition, communication science, and naturalistic neuroimaging.

Information processing in the brain is orchestrated across multiple spatial and temporal scales. Given a vast array of possible interactions between highly interconnected neurons, the brain must develop efficient mechanisms for limiting and selectively engaging interactions among subsets of neurons to meet specific computational needs. Neural oscillations provide a mechanism for selective processing by creating temporal windows for effectively integrating or ignoring inputs. In addition, it is hypothesized that there are optimal frequencies for entraining neurons and network activity, termed neural resonance. However, the effect of oscillations upon neuronal network activity is often not clearly understood. There is thus a growing need to characterize the range of oscillatory patterns that networks can manifest, and relationships between oscillatory patterns, spiking activity, and changing processing demands. In this dissertation, I present tools for quantifying neuronal entrainment in rhythms and uncovering neural resonance in networks of interacting neurons. Specifically, in Chapter 1, I present a modeling approach for characterizing relationships between neural spiking activity and the phase of neural oscillations in the local field potential (LFP). This method enables the characterization of complex spiking relationships to the phase of multiple simultaneously ongoing oscillations, or the extent of neuronal engagement in multiple possible rhythmic circuit interactions. In Chapter 2, I examine optimal frequencies for communication between the lateral entorhinal cortex (LEC) and area CA1 of the hippocampus. I demonstrate that LEC input frequency can powerfully determine CA1 entrainment to LEC inputs and shift CA1 neuron engagement in distinct local rhythms. In Chapter 3, I characterize the rodent auditory steady state response (ASSR) at both mesoscopic LFP and macroscopic electroencephalography (EEG) scales. I show that a resonant response at 40Hz in the rat primary auditory cortex is due to greater response consistency across cortical layers, and that superficial and deep layers of cortex predict distinct phases of the EEG signal. Taken together, this body of work expands our knowledge of how neural oscillations and resonance impact neuronal spiking activity and larger network responses. Further, it provides tools that future studies can leverage to gain a more comprehensive understanding of their influence across different neural systems.

In this paper we present a web-based software solution to the problem of implementing real-time collaborative neuroimage visualization. In both clinical and research settings, simple and powerful access to imaging technologies across multiple devices is becoming increasingly useful. Prior technical solutions have used a server-side rendering and push-to-client model wherein only the server has the full image dataset. We propose a rich client solution in which each client has all the data and uses the Google Drive Realtime API for state synchronization. We have developed a small set of reusable client-side object-oriented JavaScript modules that make use of the XTK toolkit, a popular open-source JavaScript library also developed by our team, for the in-browser rendering and visualization of brain image volumes. Efficient realtime communication among the remote instances is achieved by using just a small JSON object, comprising a representation of the XTK image renderers' state, as the Google Drive Realtime collaborative data model. The developed open-source JavaScript modules have already been instantiated in a web-app called MedView, a distributed collaborative neuroimage visualization application that is delivered to the users over the web without requiring the installation of any extra software or browser plugin. This responsive application allows multiple physically distant physicians or researchers to cooperate in real time to reach a diagnosis or scientific conclusion. It also serves as a proof of concept for the capabilities of the presented technological solution.

There are many instances in life when a person wants or needs to forget a memory. These unwanted memories can range from something that is simply now irrelevant such as an outdated fact, to something as serious as a traumatic experience. In extreme cases such as post-traumatic stress disorder, the benefit of forgetting becomes obvious. As such, it is important that we understand not only how our brain is able to remember, but also how it is able to forget. Unlike the traditional view of incidental forgetting, recent studies have shown that forgetting can be a strategic and active process. However, the mechanisms by which we can intentionally suppress our memories are not fully understood. Moreover, most of the directed forgetting research has focused on suppressing visual memories. A more complete understanding of the way we can exert inhibitory control over our memories should include all sensory modalities. To address this issue, we examined whether similar electrophysiological findings, as reported in visual electroencephalography (EEG) studies of directed forgetting, would be observed in the auditory domain. Additionally, the role of the prefrontal cortex in this higher-order process was investigated. Here, we utilized the Think/No-Think paradigm to examine the neural correlates of the cognitive control of memory in three studies. First, we compared findings from healthy young adults in two tasks that varied in the number of to-be-remembered and to-be-forgotten repetitions, and found that behavioral and electrophysiological evidence points to similar effects using auditory stimuli, but that it may be more difficult to achieve than the inhibition of visual memories. Second, we extended those findings to older adults, and found that they too showed behavioral and EEG evidence of successful suppression of unwanted auditory memories. Third, we determined that prefrontal cortex plays a causal role in the ability to actively inhibit auditory memories by examining the behavioral and EEG effects of unilateral frontal lesions in a patient cohort. The behavioral evidence for the inhibition of auditory memory and the corresponding electrophysiology is a step toward a more complete picture of how we intentionally suppress unwanted memories.

Many studies have provided evidence that the medial temporal lobes of the brain are involved in memory for everyday life experiences (episodic memory). Episodic memory has several components: the event itself (what), where the event took place, and when the event took place. The goal of this dissertation was to understand how the brain supports memory for when events occur (temporal memory). We showed participants an episode of Curb Your Enthusiasm inside of the MRI scanner, to monitor task-related changes in relevant brain regions. Then, we tested participants’ memory for when events in the episode occurred. We found that a network of brain regions, including the hippocampus, lateral entorhinal cortex (LEC), and perirhinal cortex (PRC) were preferentially activated when participants were closest to the correct answer. This suggests that memory for time may have different neurobiological correlates than memory for spatial information. Cortical regions, such as medial prefrontal cortex, angular gyrus, and posterior cingulate cortex were also activated when participants responded most precisely, indicating that they may also support temporal memory precision. We found no evidence that scene changes (event boundaries) had an effect on temporal memory performance in this task. A cluster in the superior temporal gyrus was preferentially activated at event boundaries while participants watched the episode, which could reflect changes occurring at boundaries, music during the episode, or both. We also tested older adults on this task and their performance correlated with a neuropsychological test of memory involving remembering words over a delay. Future studies of memory for time involving more naturalistic stimuli will provide additional information on brain-behavior relationships critical for remembering when events occurred.