Gender Differences in EEG Responses to Color and Black-White Images: Implications for Neuromarketing Strategies

Analyzing the decision of different genders during shopping is an interesting topic in the neuromarketing industry. This study explores the EEG signal acquisition of twenty subjects in response to Color and Black-White (CL/BW) images and analysis both linear and nonlinear features in different brain regions. The Wilcoxon Rank Sum statistical test was utilized to determine the significance of features in identifying discriminative channels and frequency bands. The results show that the activation of different bands and regions are dependent on the subject’s preference and the color of stimuli which are evaluated by spectral scalp map and power spectral density analysis on the the regions. Then, random forest, support vector machine, k-nearest neighbors, and linear discriminant analysis classifiers were also employed to identify the most significant active regions of different brain lobes in both human genders. For the female group in the Like task with CL/BW stimuli images, the classification accuracy significantly increased to 96.47% by combining all frequency bands in the random forest algorithm. On the other hand, for the male group, using the gamma frequency band in the k-nearest neighbors algorithm led to a notable improvement in classification accuracy, reaching 95.32% for the Like task with CL/BW stimuli images. The study provides insights into the influence of black-white colors on marketing products and neuromarketing strategies. The research also revealed differences in the time taken for males and females to make Like and Dislike decisions, as well as the decision-making time for Like and Dislike CL/BW images. The female group took approximately 2.5 seconds to choose an image of a product, whilst the male group took 2.5-3 seconds. The study’s findings have significant implications for the field of neuromarketing, emphasizing the importance of careful stimulus selection and classifier choice for classification tasks

The impact of selective and non-selective medial septum stimulation on hippocampal neuronal oscillations: A study based on modeling and experiments

Alzheimer's disease (AD) is a neurodegenerative disorder with a rising socioeconomic impact on societies. The hippocampus (HPC), which plays an important role in AD, is affected in the early stages. The medial septum (MS) in the forebrain provides major cholinergic input to the HPC and has been shown to play a significant role in generating oscillations in hippocampal neurons. Cholinergic neurons in the basal forebrain are particularly vulnerable to neurodegeneration in AD. To better understand the role of MS neurons including the cholinergic, glutamatergic, and GABAergic subpopulations in generating the well-known brain rhythms in HPC including delta, theta, slow gamma, and fast gamma oscillations, we designed a detailed computational model of the septohippocampal pathway. We validated the results of our model, using electrophysiological recordings in HPC with and without stimulation of the cholinergic neurons in MS using designer receptors exclusively activated by designer drugs (DREADDs) in healthy male ChAT-cre rats. Then, we eliminated 75% of the MS cholinergic neurons in the model to simulate degeneration in AD. A series of selective and non-selective stimulations of the remaining MS neurons were performed to understand the dynamics of oscillation regulation in the HPC during the degenerated state. In this way, appropriate stimulation strategies able to normalize the aberrant oscillations are proposed. We found that selectively stimulating the remaining healthy cholinergic neurons was sufficient for network recovery and compare this to stimulating other subpopulations and a non-selective stimulation of all MS neurons. Our data provide valuable information for the development of new therapeutic strategies in AD and a tool to test and predict the outcome of potential theranostic manipulations

Additional file 1 of Anodal HD-tDCS on the dominant anterior temporal lobe and dorsolateral prefrontal cortex: clinical results in patients with mild cognitive impairment

Additional file 1: Figure A1. In both left DLPFC and DATL groups, the achieved MoCA scores in two weeks, one, and three months after the intervention were statistically higher than the baseline score (p-value≤0.05). There was no significant difference in the achieved MoCA scores for patients in the Sham group during the same time intervals with respect to the study baseline. “*” shows the statistically significant cases regarding the baseline. The data are presented using mean ± SD (Standard Deviation). (MoCA: Montreal Cognitive Assessment, Left DLPFC: Left Dorsolateral prefrontal cortex, DATL: Dominant anterior temporal lobe). Table A1. Comparison of MoCA sub-scale mean scores between groups. Table A2. The Bonferroni post hoc tests of MoCA sub-scale mean scores during different time intervals between groups. Table A3. The results of Bonferroni post hoc test of MOCA sub-scale mean scores in different groups