Biology subjects

Giampietro, V.

Publications and source records attributed to Giampietro, V..

5 recordsLinked to original sources

bioRxiv2023

Anhedonia severity mediates the relationship between attentional networks recruitment and emotional blunting during music listening

Recent studies have reported atypical emotional processing in individuals with greater levels of anhedonic depressive symptoms. However, the relationship between brain networks dynamics and moment-to-moment affective responses to naturalistic paradigms, as emotions are unfolding, remains unclear. In this study, we used the unique temporal characteristics of music to investigate behavioural and brain network dynamics as a function of anhedonic depressive symptoms severity in healthy adults during an emotionally provocative music listening task. Thirty-one neurotypical participants aged 18-30 years were required to continuously rate happy, neutral and sad pieces of music whilst undergoing MRI scanning. They were also asked to fill in questionnaires assessing their levels of anhedonic depressive symptoms. Using a novel fMRI analysis method called Leading Eigenvector Dynamics Analysis (LEiDA), we found an increased probability of occurrence of attentional networks and a blunted emotional response to both happy and sad pieces of music in participants with greater levels of anhedonic depressive symptoms. More specifically, anhedonic depressive symptoms mediated the relationship between attentional networks recruitment and emotional blunting. Furthermore, the elevated recruitment of attentional networks during emotional pieces of music carried over into subsequent neutral music. Future studies are needed to investigate whether these findings could be generalised to a clinical population (i.e., Major Depressive Disorder).

neuroscience↗

bioRxiv2022

Tissue volume estimation and age prediction using rapid structural brain scans

The multicontrast EPImix sequence generates 6 contrasts, including a T1-weighted scan, in [~]1 minute. EPImix shows comparable diagnostic performance to conventional scans under qualitative clinical evaluation, and similarities in simple quantitative measures including contrast intensity. However, EPImix scans have not yet been compared to standard MRI scans using established quantitative measures. In this study, we compared conventional and EPImix-derived T1-weighted scans of 64 healthy participants using tissue volume estimates and predicted brain-age. All scans were pre-processed using the SPM12 DARTEL pipeline, generating measures of grey matter, white matter and cerebrospinal fluid volume. Brain-age was predicted using brainageR, a Gaussian process regression model previously trained on a large sample of standard T1-weighted scans. Estimates of both global and voxel-wise tissue volume showed significantly similar results between standard and EPImix-derived T1-weighted scans. Brain-age estimates from both sequences were significantly correlated, although EPImix T1-weighted scans showed a systematic offset in predictions of chronological age. Supplementary analyses suggest that this is likely caused by the reduced field of view of EPImix scans, and the use of a brain-age model trained using conventional T1-weighted scans. However, this systematic error can be corrected using additional regression of T1-predicted brain-age onto EPImix-predicted brain-age. Finally, retest EPImix scans acquired for 10 participants demonstrated high test-retest reliability in all evaluated quantitative measurements. Quantitative analysis of EPImix scans holds potential to reduce scanning time, increasing participant comfort and reducing cost, as well as to support automation of scanning, utilising active learning for faster and individually-tailored (neuro)imaging.

neuroscience↗

bioRxiv2021

Epigenetic mediation of AKT1 rs1130233 s effect on delta-9-tetrahydrocannabinol-induced medial temporal function during fear processing

High doses of delta-9-tetrahydrocannabinol (THC), the main psychoactive component of cannabis, have been shown to have anxiogenic effects. Also, THC effects have been shown to be modulated by genotype, including the single nucleotide polymorphism (SNP) rs1130233 at the protein kinase AKT1 gene, a key component of the dopamine signaling cascade. As such, it is likely that epigenetic methylation around this SNP may affect AKT gene expression, which may in turn impact on the acute effects of THC on brain function. We investigated the genetic (AKT1 rs1130233) and epigenetic modulation of brain function during fear processing in a 2-session, double-blind, cross-over, randomized placebo-controlled THC administration, in 36 healthy males. Fear processing was assessed using an emotion (fear processing) paradigm, under functional magnetic resonance imaging (fMRI). Complete genetic and fMRI data was available for 34 participants. THC caused an increase in anxiety and transient psychotomimetic symptoms and para-hippocampal gyrus/ amygdala activation. Number of A alleles at the AKT1 rs1130233 SNP, and percentage methylation at the CpG11-12 site, were independently associated with a greater effect of THC on activation in a network of brain regions including left and right parahippocampal gyri, respectively. AKT1 rs1130233 moderation of the THC effect on left parahippocampal activation persisted after covarying for methylation percentage, and was partially mediated in sections of the left parahippocampal gyrus/ hippocampus by methylation percentage. These results may offer an example of how genetic and epigenetic variations influence the psychotomimetic and neurofunctional effects of THC.

neuroscience↗

bioRxiv2021

Rapid processing and quantitative evaluation of multicontrast EPImix scans for adaptive multimodal imaging

Current neuroimaging acquisition and processing approaches tend to be optimised for quality rather than speed. However, rapid acquisition and processing of neuroimaging data can lead to novel neuroimaging paradigms, such as adaptive acquisition, where rapidly processed data is used to inform subsequent image acquisition steps. Here we first evaluate the impact of several processing steps on the processing time and quality of registration of manually labelled T1-weighted MRI scans. Subsequently, we apply the selected rapid processing pipeline both to rapidly acquired multicontrast EPImix scans of 95 participants (which include T1-FLAIR, T2, T2*, T2-FLAIR, DWI & ADC contrasts, acquired in [~]1 minute), as well as to slower, more standard single-contrast T1-weighted scans of a subset of 66 participants. We quantify the correspondence between EPImix and single-contrast T1-weighted scans, using correlations between voxels and regions of interest across participants, measures of within- and between-participant identifiability as well as regional structural covariance networks. Furthermore, we explore the use of EPImix for the rapid construction of morphometric similarity networks. Finally, we quantify the reliability of EPImix-derived data using test-retest scans of 10 participants. Our results demonstrate that quantitative information can be derived from a neuroimaging scan acquired and processed within minutes, which could further be used to implement adaptive multimodal imaging and tailor neuroimaging examinations to individual patients. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=77 SRC="FIGDIR/small/430956v1_ufig1.gif" ALT="Figure 1"> View larger version (33K): org.highwire.dtl.DTLVardef@3ae0e9org.highwire.dtl.DTLVardef@1840d39org.highwire.dtl.DTLVardef@80339borg.highwire.dtl.DTLVardef@bc16cf_HPS_FORMAT_FIGEXP M_FIG Graphical abstract. C_FIG

neuroscience↗

bioRxiv2019

The heterogeneous functional architecture of the posteromedial cortex is associated with selective functional connectivity differences in Alzheimer’s disease

The posteromedial cortex (PMC) is a key region involved in the development and progression of Alzheimers disease (AD). Previous studies have demonstrated a heterogenous functional architecture of the region, with different subdivisions reflecting distinct connectivity profiles. However, little is understood about PMC functional connectivity and its differential vulnerability to AD pathogenesis. Using a data-driven approach, we applied a constrained independent component analysis (ICA) on healthy adults from the Human Connectome Project (HCP) to characterise the distinct functional subdivisions and unique functional-anatomic connectivity patterns of the PMC. These connectivity profiles were subsequently quantified in the Alzheimers Disease Neuroimaging Initiative (ADNI) study, to examine functional connectivity differences in (1) AD patients and cognitively normal (CN) participants and (2) the entire AD pathological spectrum, ranging from CN participants and participants with subjective memory complaints (SMC), through to those with mild cognitive impairment (MCI), and finally, patients diagnosed with AD. Our findings revealed decreased functional connectivity in the anterior precuneus, dorsal posterior cingulate cortex, and the central precuneus in AD patients compared to CN participants. Functional abnormalities in these subdivisions were also related to high amyloid burden and lower hippocampal volumes. Across the entire AD spectrum, functional connectivity of the central precuneus was associated with disease progression and specific deficits in memory and executive function. These findings provide new evidence showing that specific vulnerabilities in PMC functional connectivity are associated with large-scale network disruptions in AD and that these patterns may be useful for elucidating potential biomarkers for measuring disease progression in future work.

neuroscience↗