Browsing by Author "Matyi, Melanie A."
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Item Assessing the utility of a novel cortical marker of delay discounting (C-DD) in two independent samples of early adolescents: Links with externalizing pathology(PLoS ONE, 2023-09-27) Bounoua, Nadia; Church, Leah D.; Matyi, Melanie A.; Rudoler, Jeremy; Wieand, Kaleigh; Spielberg, Jeffrey M.Delay discounting is a well-established risk factor for risky behaviors and the development of externalizing spectrum disorders. Building upon recent work that developed a novel cortical marker of delay discounting (C-DD) in adult samples, the objective of this study was to test whether the C-DD relates to delay discounting and subsequently externalizing pathology in adolescent samples. The current study used two samples: 9992 early adolescents participating in the ABCD study (Mage = 9.93 years old, 48.7% female), and 56 early adolescents recruited from the community (Mage = 12.27 years old, 55.4% female). Cortical thickness was estimated using the FreeSurfer standard pipeline, and the cortical marker of delay discounting (C-DD) was calculated based on procedures outlined by the initial validation study. All data are cross-sectional in nature. As expected, C-DD was positively related to delay discounting in the ABCD sample, even after accounting for age, biological sex, collection site and data quality indicators. Moreover, results showed that C-DD was discriminately associated with externalizing, but not internalizing, symptoms in both samples of young adolescents. Findings replicate those found in adult samples, suggestive that C-DD may be a useful neuroanatomical marker of youth delay discounting. Replication of findings in other samples will be needed to determine whether C-DD has translational relevance to understanding externalizing psychopathology in adolescent samples.Item Classification of mood disorders from functional brain network topology: a latent profile analysis(University of Delaware, 2020) Matyi, Melanie A.Differentiation of Bipolar Disorder I (BPI), Bipolar Disorder II (BPII), and Major Depressive Disorder (MDD) is difficult due to the episodic nature of these disorders and their phenotypic and genetic overlap. This results in frequent misdiagnosis of MDD in BP patients which can have devastating real-world consequences as MDD treatments (e.g., selective serotonin reuptake inhibitors) can precipitate the onset of mania in some depressed individuals. Additionally, the current diagnostic system relies solely upon either self-reported or observable symptoms, which can be problematic as more than one pathway may lead to the same presentation. Thus, inclusion of additional data sources (e.g., neural metrics) may help refine diagnostic categories. However, extant neuroscience research has almost uniformly focused on differentiating between disorders using the current nosology. In a sample of patients (BPI, BPII, and MDD) and healthy controls, we addressed this gap in the literature by deriving latent classes from emergent brain network attributes in a manner that was blind to diagnostic group. In particular, we entered three global metrics of functional brain network organization (assortativity, algebraic connectivity, and total clustering coefficient) as indicators into a latent profile analysis. We examined models with 2 to 4 classes and found a 3-class model to be superior. Next, we examined the extent to which these 3 classes mapped onto existing DSM diagnostic groupings. Findings demonstrated that these classes were related to, but did not match, diagnostic groupings. In particular, the functional brain network organization of individuals with BPII appeared to be particularly distinct from that of the other patient groups (i.e., BPI, MDD) and HC. This also appeared to be the case for MDD, although the evidence was less definitive.Item Identifying brain regions supporting amygdalar functionality: Application of a novel graph theory technique(NeuroImage, 2021-09-25) Matyi, Melanie A.; Cioaba, Sebastian M.; Banich, Marie T.; Spielberg, Jeffrey M.Effective amygdalar functionality depends on the concerted activity of a complex network of regions. Thus, the role of the amygdala cannot be fully understood without identifying the set of brain structures that allow the processes performed by the amygdala to emerge. However, this identification has yet to occur, hampering our ability to understand both normative and pathological processes that rely on the amygdala. We developed and applied novel graph theory methods to diffusion-based anatomical networks in a large sample (n = 1,052, 54.28% female, mean age=28.75) to identify nodes that critically support amygdalar interactions with the larger brain network. We examined three graph properties, each indexing a different emergent aspect of amygdalar network communication: current-flow betweenness centrality (amygdalar influence on information flowing between other pairs of nodes), node communicability (clarity of communication between the amygdala and other nodes), and subgraph centrality (amygdalar influence over local network processing). Findings demonstrate that each of these aspects of amygdalar communication is associated with separable sets of regions and, in some cases, these sets map onto previously identified sub-circuits. For example, betweenness and communicability were each associated with different sub-circuits that have been identified in previous work as supporting distinct aspects of memory-guided behavior. Other regions identified span basic (e.g., visual cortex) to higher-order (e.g., insula) sensory processing and executive functions (e.g., dorsolateral prefrontal cortex). Present findings expand our current understanding of amygdalar function by showing that there is no single ‘amygdala network’, but rather multiple networks, each supporting different modes of amygdalar interaction with the larger brain network. Additionally, our novel method allowed for the identification of how such regions support the amygdala, which has not been previously explored.Item The structural brain network topology of episodic memory(PLoS ONE, 2022-06-24) Matyi, Melanie A.; Spielberg, Jeffrey M.Episodic memory is supported by a distributed network of brain regions, and this complex network of regions does not operate in isolation. To date, neuroscience research in this area has typically focused on the activation levels in specific regions or pairwise connectivity between such regions. However, research has yet to investigate how the complex interactions of structural brain networks influence episodic memory abilities. We applied graph theory methods to diffusion-based anatomical networks in order to examine the structural architecture of the medial temporal lobe needed to support effective episodic memory functioning. We examined the relationship between performance on tests of verbal and non-verbal episodic memory with node strength, which indexes how well connected a brain region is in the network. Findings mapped onto the Posterior Medial memory system, subserved by the parahippocampal cortex and overlapped with findings of previous studies of episodic memory employing different methodologies. This expands our current understanding by providing independent evidence for the importance of identified regions and suggesting the particular manner in which these regions support episodic memory.Item Understanding the mechanisms of emotion differentiation(University of Delaware, 2023) Matyi, Melanie A.Emotion differentiation (ED) is the ability to make fine-grained distinctions between relatively similar internal emotional experiences. Deficits in the capacity to differentiate negative emotions (NED) have been linked to poorer mental health. However, much remains unknown regarding the mechanisms of NED, including the specific processes that lead to low NED, how NED is implemented in the brain, and the intermediate mechanisms by which NED confers vulnerability for pathology during adolescence. ☐ To provide crucial insights into how low NED emerges, Studies 1 and 2 examined the neural correlates of NED using a novel fMRI task that simulated different components of NED in a sample of young adults. Study 1 examined the relationship between neural activation in regions supporting generation of affective experiences and labeling/recognizing these experiences and a behavioral measure of NED. Study 2 examined how task-dependent changes in the connectivity of brain regions associated with affective experience and those linked to labeling/recognizing relate to a behavioral measure of NED. Study 3 further probed the neural processes supporting NED using metrics of white matter microstructure derived from diffusion-weighted imaging. Lastly, Study 4 investigated the manner in which NED ability is related to internalizing pathology in adolescence by examining the relationships between NED, emotion regulation, and psychopathology in an early adolescent sample. ☐ In Studies 1 and 2 we found that NED is related to activation and connectivity, respectively, of dorsomedial prefrontal cortex and anterior insula. In Study 3, we found that white matter microstructure of right anterior thalamic radiation, inferior fronto-occipital fasciculus, and peri-genual cingulum is related to NED. Although we did not detect any significant associations among NED, emotion regulation, and psychopathology in Study 4, we suggest that these associations do not develop until later in adolescence. ☐ Results across Studies 1-3 indicated that NED relies on the context-based generation and modulation of emotion, the ability to compare/predict and become aware of feeling states, the extent to which affective information is integrated with self-referential meaning of the emotional experience, and the integrity of white matter pathways subserving these functions (i.e., affective experience, memory, and semantics). Together, the findings from these studies suggest mechanisms that explain how NED emerges and have implications for intervention targets to increase NED capacity.