Biology subjects

Silveri, M. M.

Publications and source records attributed to Silveri, M. M..

3 recordsLinked to original sources

bioRxiv2022

Anterior cingulate metabolite levels, memory, and inhibitory control in abstinent men and women with Alcohol Use Disorder

AimsAlcohol use disorder (AUD), has been shown to have harmful cognitive and physiological effects, including altered brain chemistry. Further, although men and women may differ in vulnerability to the neurobiological effects of AUD, results of existing studies have been conflicting. Brain metabolite levels and cognitive functions were examined in a cross section of men with AUD (AUDm) and women with AUD (AUDw) to determine degree of abnormalities after extended periods of abstinence (mean, six years), and to evaluate gender differences in cognitive and metabolite measures. MethodsParticipants were 40 abstinent individuals with AUD (22 AUDw, 18 AUDm) and 50 age-equivalent non-AUD comparison participants (26 NCw, 24 NCm). Proton magnetic resonance spectroscopy (MRS) was employed at 3 Tesla to acquire metabolite spectra from the dorsal anterior cingulate cortex (dACC). Brain metabolites N-acetylaspartate (NAA), choline (Cho), myo-Inositol (mI), and glutamate & glutamine (Glx) were examined relative to measures of memory and inhibitory control. ResultsMetabolite levels in the AUD group showed no significant differences from the NC group. Memory and inhibitory-control impairments were observed in the AUD group. There also were significant group-specific associations between metabolite ratios and measures of inhibitory control. There were no Group-by-Gender interactions for the four metabolite ratios. ConclusionsThese findings demonstrate that brain metabolite levels in men and women with AUD, following long-term abstinence, do not differ from individuals without AUD. The data also provide evidence of associations between metabolite levels and measures of inhibitory control, a functional domain important for curtailing harmful drinking.

neuroscience↗

bioRxiv2019

Too much, too young? Altered corticolimbic axonal innervation and resting state functional connectivity suggests sex-dependent outcomes in a rat model of early life adversity

Adverse early experiences significantly alter behavioral and neural trajectories via aberrant brain maturation. Children with a history of early life stress (ELS) exhibit maladaptive behaviors and increased risk of mental illness later in life. Evidence in ELS-exposed humans identifies a role of atypical corticolimbic development; specifically, within amygdala-prefrontal cortex (PFC) circuits, and show precocially mature task-based corticolimbic functional connectivity (FC). However, the neurobiological substrates of such ELS-driven developmental changes remain unknown. Here, we identify putative neurobiological changes to determine the timeline of developmental perturbations following ELS in rats. Anterograde axonal tracing from basolateral amygdala (BLA) to pre- and infralimbic (PL, IL) PFC was quantified at postnatal days (PD)28, 38, and 48, along with anxiety-like behavior, in maternally separated (ELS) or control reared (CON) male and female rats. Resting state (rs)FC was assessed at PD28 and PD48 in a separate cohort. We report that ELS-exposed female rats show early maturation of BLA-PFC innervation at PD28, with ELS-related changes in males not appearing until PD38. ELS disrupted the maturation of rsFC from PD28 to PD48 in females, with enduring relationships between early rsFC and later anxiety-like behavior. Only transient ELS-related changes in rsFC were seen in male PL. Together, these data provide evidence that female rats may be more vulnerable to the effects of ELS via precocial BLA-PFC innervation, which may drive altered corticolimbic rsFC. These data also provide evidence that increased BLA-IL rsFC is associated with behavioral resiliency following ELS in female rats, providing mechanistic insight into the underlying etiology of adversity-induced vulnerability and resiliency.

neuroscience↗

bioRxiv2018

Combining Multi-Site/Multi-Study MRI Data: Linked-ICA Denoising for Removing Scanner and Site Variability from Multimodal MRI Data

Large multi-site studies that pool magnetic resonance imaging (MRI) data across research sites or studies, or that utilize shared data from imaging repositories, present exceptional opportunities to advance neuroscience and enhance reproducibility of neuroimaging research. However, both scanner and site variability are confounds that hinder pooling data collected across different sites or across different operating systems on the same scanner, even when all acquisition protocols are harmonized. These confounds degrade statistical analyses and can lead to spurious findings. Unfortunately, methods to address this problem are scant. In this study, we propose a novel denoising approach for multi-site multimodal MRI data that implements a data-driven linked independent component analysis (LICA) to efficiently identify scanner/site-related effects for removal. Removing these effects results in denoised data that can then be combined across sites/studies to improve modality-specific statistical processing. We use data from six different studies collected on the same scanner across major hardware (gradient and head coil) and software upgrades to demonstrate our LICA-based denoising approach. The proposed method is superior compared to the existing methods we tested and has great potential for large-scale multi-site studies to produce combined data free from study/site confounds.

neuroscience↗