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Pouretemad, H.

Publications and source records attributed to Pouretemad, H..

2 recordsLinked to original sources

Electrophysiological markers of fairness and selfishness revealed by a combination of Dictator and Ultimatum Games

AO_SCPLOWBSTRACTC_SCPLOWEvent Related Potentials (ERPs) were recorded from 39 participants who played the role of Allocators in a Dictator Game (DG) and Responders in an Ultimatum Game (UG). Most participants expressed very low levels of altruistic decision making, and two homogeneous groups could be identified, one formed by fair (N = 10) individuals and another by selfish (N = 8) individuals. At fronto-central cortical sites, the ERP early negativity (N1) was reduced in selfish participants with a latency about 10 ms earlier than in fair participants. In fair DG players, the features of the subsequent positive wave P2 suggested that more cognitive resources were required when they allocated the least gains to the other party. P2 latency and amplitude in the selfish group supported the hypothesis that these participants tended to maximize their profit, as expected by a rational Homo economicus. During UG, we observed that a medial frontal negativity (MFN) occurred earlier and with greater amplitude when selfish participants rejected less favorable endowment shares. In this case, all players received zero payoffs, which showed that MFN in selfish participants was associated with a spiteful punishment. At posterior-parietal sites we found that the greater the selfishness, the greater the amplitude of the late positive component (LPC). Our results bring new evidence to the existence of specific somatic markers associated with the activation of distinct cerebral circuits by the evaluation of fair and unfair proposals in participants characterized by different expressions of perceived fairness, thus suggesting that particular brain dynamics could be associated with moral decisions.

neuroscience↗

Amygdalar atrophy as the genetically mediated hub of limbic degeneration in Alzheimer’s disease

Pharmacological progress, basic science and medical practice can benefit from objective biomarkers that assist in early diagnosis and prognostic stratification of diseases. In the field of Alzheimers disease (AD), the clinical presentation of early stage dementia may not fulfill any diagnostic criteria for years, and quantifying structural brain changes by magnetic resonance imaging (MRI) has shown promise in the discovery of sensitive biomarkers. Although hippocampal atrophy is often used as an in vivo measure of AD, data-driven neuroimaging has revealed complex patterns of regional brain vulnerability that may not perfectly map to anatomical boundaries. In addition to aiding diagnosis, decoding genetic influences on neuroimaging measures of the disease can enlighten molecular mechanisms of the underlying pathology in living patients and guide the therapeutic design.\n\nHere, we aimed to extract a data-driven MRI feature of brain atrophy in AD by decomposing structural neuroimages using independent component analysis (ICA), a method for performing unbiased computational search in high dimensional data spaces. Our study of the AD Neuroimaging Initiative dataset (n=1,100 subjects) revealed a disease-vulnerable feature with a network-like topology, comprising amygdala, hippocampus, fornix and the inter-connecting white-matter tracts of the limbic system. Whole-genome sequencing identified a nonsynonymous variant (rs34173062) in SHARPIN, a gene coding for a synaptic protein, as a significant modifier of this new MRI feature (p=2.1x10-10). The risk variant was brought to replication in the UK Biobank dataset (n=8,428 subjects), where it was associated with reduced cortical thickness in areas co-localizing with those of the discovery sample (left entorhinal cortex p=0.002, right entorhinal cortex p=8.6x10-4; same direction), as well as with the history of AD in both parents (p=2.3x10-6; same direction).\n\nIn conclusion, our study shows that ICA can transform voxel-wise volumetric measures of the brain into a data-driven feature of neurodegeneration in AD. Structure of the limbic system, as the most vulnerable focus of brain atrophy in AD, is affected by genetic variability of SHARPIN. The elevated risk of dementia in carriers of the minor allele supports engagement of SHARPIN in the disease pathways, and its role in neurotransmitter receptor scaffolding and integrin signaling may inform on new molecular mechanisms of AD pathophysiology.\n\nAbbreviationsAlzheimers disease (AD), genome-wide association study (GWAS), independent component analysis (ICA), mild cognitive impairment (MCI), medial temporal circuit (MTC), single-nucleotide polymorphism (SNP), tensor-based morphometry (TBM)

neuroscience↗