Biology subjects

Dobryakova, E.

Publications and source records attributed to Dobryakova, E..

6 recordsLinked to original sources

bioRxiv2025

Resting-state Functional Connections with the Hippocampus and with the Caudate Nucleus Predict Working Memory Performance in Multiple Sclerosis

Episodic memory (EM) dysfunction is a common symptom of multiple sclerosis (MS). A related process, working memory (WM), supports long-term EM and is often also impaired. Functional connectivity (FC) between the hippocampus and caudate nucleus supports EM performance. However, this connectivitys specific influences on WM performance in MS is relatively unknown. Resting-state FC (RSFC) possesses clinical utility, including predicting cognitive impairments before they are captured by assessment. The present study tested whether RSFC with the hippocampus and caudate could predict WM performance in people with MS and in healthy individuals (HC). In a secondary analysis of 78 participants (42 MS, 36 HC), RSFC between the hippocampus, caudate nucleus, and other regions was quantified. These connections predictive influence on WM performance was then examined using a global WM performance measure for a subset with available neuropsychological data (26 MS, 15 HC). Across the entire sample (N=78), MS participants displayed stronger coupling between the right hippocampus and left dorsomedial prefrontal cortex, compared to HC participants. Within MS participants, stronger coupling between the left hippocampus (LHipp) and left ventral anterior cingulate (LvACC), and between the left caudate (LCaud) and right insula, were observed. Stronger decoupling between the LHipp and left supramarginal gyrus (LSMG) also emerged. Stronger LHipp-LvACC connectivity predicted worse WM performance, whereas stronger LHipp-LSMG connectivity and LCaud-RInsula connectivity each predicted better performance. The hippocampal connections were also inversely correlated. Findings identify a caudate circuit and potential hippocampal network whose aberrant, intrinsic activity could serve as neural markers for WM dysfunction in MS.

neuroscience↗

bioRxiv2023

Bypassing Striatal Learning Mechanisms Using Delayed Feedback to Circumvent Learning Deficits in TBI

ObjectiveFeedback facilitates learning by guiding and modifying behaviors through an action-outcome contingency. As the majority of existing studies have focused on immediate presentation of feedback, the impact of delayed feedback on learning is understudied. Prior work demonstrated that learning from immediate and delayed feedback employed distinct brain regions in healthy individuals, and compared to healthy individuals, individuals with traumatic brain injury (TBI) are impaired in learning from immediate feedback. The goal of the current investigation was to assess the effects of delayed vs. immediate feedback on learning in individuals with TBI and examine brain networks associated with delayed and immediate feedback processing. SettingNon-profit research organization. ParticipantsTwenty-eight individuals with moderate-to-severe TBI. DesignParticipants completed a paired-associate word learning task while undergoing MRI. During the task, feedback was presented either immediately, after a delay, or not at all (control condition). Main measuresLearning performance accuracy; confidence ratings; post-task questionnaire, blood-oxygen-level dependent signal. ResultsBehavioral data showed that delayed feedback resulted in better learning performance than immediate feedback and no feedback. In addition, participants reported higher confidence in their performance during delayed feedback trials. During delayed vs. immediate feedback processing, greater activation was observed in the superior parietal and angular gyrus. Activation in these areas has been previously associated with successful retrieval and greater memory confidence. ConclusionThe observed results might be explained by delayed feedback processing circumventing the striatal dopaminergic regions responsible for learning from immediate feedback that are impaired in TBI. Additionally, delayed feedback evokes less of an affective reaction than immediate feedback, which likely benefited memory performance. Indeed, compared to delayed feedback, positive or negative immediate feedback was more likely to be rated as rewarding or punishing, respectively. Findings have significant implications for TBI rehabilitation and suggest that delaying feedback during rehabilitation might recruit brain regions that lead to better functional outcomes.

neuroscience↗

bioRxiv2023

Accelerated Aging after Traumatic Brain Injury: an ENIGMA Multi-Cohort Mega-Analysis

ObjectiveThe long-term consequences of traumatic brain injury (TBI) on brain structure remain uncertain. In light of current evidence that even a single significant brain injury event increases the risk of dementia, brain-age estimation could provide a novel and efficient indexing of the long-term consequences of TBI. Brain-age procedures use predictive modeling to calculate brain-age scores for an individual using MRI data. Complicated mild, moderate and severe TBI (cmsTBI) is associated with a higher predicted (brain) age difference (PAD), but the progression of PAD over time remains unclear. Here we sought to examine whether PAD increases as a function of time since injury (TSI). MethodsAs part of the ENIGMA Adult Moderate and Severe (AMS)-TBI working group, we examine the largest TBI sample to date (n=343), along with controls, for a total sample size of 540, to reproduce and extend prior findings in the study of TBI brain age. T1w-MRI data were aggregated across 7 cohorts and brain age was established using a similar brain age algorithm to prior work in TBI. ResultsFindings show that PAD widens with longer TSI, and there was evidence for differences between sexes in PAD, with men showing more advanced brain age. We did not find evidence supporting a link between PAD and cognitive performance. InterpretationThis work provides evidence that changes in brain structure after cmsTBI are dynamic, with an initial period of change, followed by relative stability, eventually leading to further changes in the decades after a single cmsTBI.

neuroscience↗

bioRxiv2023

Bridging Big Data: Procedures for Combining Non-equivalent Cognitive Measures from the ENIGMA Consortium

Investigators in neuroscience have turned to Big Data to address replication and reliability issues by increasing sample sizes, statistical power, and representativeness of data. These efforts unveil new questions about integrating data arising from distinct sources and instruments. We focus on the most frequently assessed cognitive domain - memory testing - and demonstrate a process for reliable data harmonization across three common measures. We aggregated global raw data from 53 studies totaling N = 10,505 individuals. A mega-analysis was conducted using empirical bayes harmonization to remove site effects, followed by linear models adjusting for common covariates. A continuous item response theory (IRT) model estimated each individuals latent verbal learning ability while accounting for item difficulties. Harmonization significantly reduced inter-site variance while preserving covariate effects, and our conversion tool is freely available online. This demonstrates that large-scale data sharing and harmonization initiatives can address reproducibility and integration challenges across the behavioral sciences. TeaserWe present a global effort to devise harmonization procedures necessary to meaningfully leverage big data.

neuroscience↗

bioRxiv2022

ALFF Response Interaction With Learning During Feedback in Individuals With Multiple Sclerosis

Amplitude of low-frequency fluctuations (ALFF) is defined as changes of BOLD signal during resting state (RS) brain activity. Previous studies identified differences in RS activation between healthy and multiple sclerosis (MS) participants. However, no research has investigated the relationship between ALFF and learning in MS. We thus examine this here. Twenty-five MS and 19 healthy participants performed a paired-associate word learning task where participants were presented with extrinsic or intrinsic performance feedback. Compared to healthy participants, MS participants showed higher local brain activation in the right thalamus. We also observed a positive correlation in the MS group between ALFF and extrinsic feedback within the left inferior frontal gyrus, and within the left superior temporal gyrus in association with intrinsic feedback. Healthy participants showed a positive correlation in the right fusiform gyrus between ALFF and extrinsic feedback. Findings suggest that while MS participants do not show a feedback learning impairment compared to the healthy participants, ALFF differences might suggest a general maladaptive pattern of task unrelated thalamic activation and adaptive activation in frontal and temporal regions. Results indicate that ALFF can be successfully used at capturing pathophysiological changes in local brain activation in MS in association with learning through feedback.

neuroscience↗

bioRxiv2021

Reward Enhances Connectivity between the Ventral Striatum and the Default Mode Network

The default mode network (DMN) has been theorized to participate in a range of social, cognitive, and affective functions. Yet, previous accounts do not consider how the DMN contributes to other brain regions depending on psychological context, thus rendering our understanding of DMN function incomplete. We addressed this gap by applying a novel network-based psychophysiological interaction (nPPI) analysis to the reward task within the Human Connectome Project. We first focused on the task-evoked responses of the DMN and other networks involving the prefrontal cortex, including the executive control network (salience network) and the left and right frontoparietal networks. Consistent with a host of prior studies, the DMN exhibited a relative decrease in activation during the task, while the other networks exhibited a relative increase during the task. Next, we used nPPI analyses to assess whether these networks exhibit task-dependent changes in connectivity with other brain regions. Strikingly, we found that the experience of reward enhances task-dependent connectivity between the DMN and the ventral striatum, an effect that was specific to the DMN. Surprisingly, the strength of DMN-VS connectivity was correlated with personality characteristics relating to openness. Taken together, these results advance models of DMN by demonstrating how it contributes to other brain systems during task performance and how those contributions relate to individual differences.

neuroscience↗