Unlocking the neural mechanisms of consumer loan evaluations: an fNIRS and ML-based consumer neuroscience study.

Introduction: This study conducts a comprehensive exploration of the neurocognitive processes underlying consumer credit decision-making using cutting-edge techniques from neuroscience and machine learning (ML). Employing functional Near-Infrared Spectroscopy (fNIRS), the research examines the hemodynamic responses of participants while evaluating diverse credit offers. Methods: The experimental phase of this study investigates the hemodynamic responses collected from 39 healthy participants with respect to different loan offers. This study integrates fNIRS data with advanced ML algorithms, specifically Extreme Gradient Boosting, CatBoost, Extra Tree Classifier, and Light Gradient Boosted Machine, to predict participants' credit decisions based on prefrontal cortex (PFC) activation patterns. Results: Findings reveal distinctive PFC regions correlating with credit behaviors, including the dorsolateral prefrontal cortex (dlPFC) associated with strategic decision-making, the orbitofrontal cortex (OFC) linked to emotional valuations, and the ventromedial prefrontal cortex (vmPFC) reflecting brand integration and reward processing. Notably, the right dorsomedial prefrontal cortex (dmPFC) and the right vmPFC contribute to positive credit preferences. Discussion: This interdisciplinary approach bridges neuroscience, machine learning and finance, offering unprecedented insights into the neural mechanisms guiding financial choices regarding different loan offers. The study's predictive model holds promise for refining financial services and illuminating human financial behavior within the burgeoning field of neurofinance. The work exemplifies the potential of interdisciplinary research to enhance our understanding of human financial decision-making.

Analysis of the DOK1 gene in breast cancer.

Breast cancer, which is the most common type of cancer among women, is a heterogenous disease. It results from progressive accumulation of genetic and epigenetic alterations in different genes. The Dok1 protein has been identified as the major substrate of protein tyrosine kinases in hematopoietic cells. It is considered as a tumor suppressor due to the reports which describe its inhibitory effect on major oncogenic signaling pathways such as Mek/Erk/PI3k/Akt and Wnt/ß-catenin. In this study, we investigated the mutation frequency of the DOK1 gene in 118 breast tumors using Sanger sequencing and DOK1 mRNA expression level in 63 breast cancer samples using qRT-PCR methods. Although the mutation frequency was low DOK1 mRNA expression levels were significantly reduced (63.5%) in the tumors compared to adjacent non-cancerous tissue. We also correlated expression changes with clinicopathological characteristics. Low mRNA levels correlated with age (p = 0.01) and c-erbB-2 (p = 0.05). In most of the previous reports, down-regulation of DOK1 mRNA expression has been associated with promoter methylation. We identified four different coding sequence alterations in 5.1% (6/118) of the tumor samples. However, all of these alterations were located in the functional domains of the protein. Therefore, these mutations may affect the function and/or cellular localization of the protein and contribute to cancer progression by this way. In conclusion our data indicate that DOK1 acts as a tumor suppressor in breast cancer and association of Dok1 with the c-erbB-2 mediated mechanism of action in breast cancer needs to be investigated.