Limbic System & Social Media Influence - The limbic system, described as a set of brain structures translating experiences into emotions, impulses, and decisions, significantly influences human behavior before conscious thought [2] - Social media platforms and algorithms can manipulate the limbic system, affecting how individuals feel and act [3][6] - Algorithms filter information, prioritizing responses that evoke strong emotions, subtly shaping user experiences [6] - Social media leverages sensationalism to activate the amygdala, prompting reactions before reflection, potentially leading to impulsive behavior [8] - Constant exposure to diverse content on social media can overwhelm the limbic system, hindering its ability to process information effectively [10] - The rapid pace of information on social media reduces the time available for the cingulate gyrus to moderate emotions, potentially leading to flawed judgment [12] - Algorithms exploit user history to trigger specific emotions repeatedly, creating cycles of emotional response [15] Limbic System Components & Functions - The thalamus filters sensory information, prioritizing relevant stimuli and sending urgent signals to the amygdala for rapid responses [5][6] - The amygdala triggers fight-or-flight responses in perceived danger, prioritizing survival over nuanced assessment [8] - The cingulate gyrus moderates emotions, evaluating the severity of situations and regulating emotional responses [11][12] - The hippocampus stores past experiences, influencing current reactions based on pleasant or painful associations [14] - The insula translates bodily sensations into emotional arguments, highlighting the physical component of decision-making [17][18] - The hypothalamus directs physiological responses, such as heart rate and hormone release, in reaction to stimuli [20]

Artificial Intelligence Efficiency & Brain-Inspired Computing - Artificial intelligence currently consumes 20,000 W of power, while the human brain only consumes 20 W for similar operations, highlighting the inefficiency of current AI systems [1] - The industry is studying the brain to transfer its mechanisms to artificial intelligence, using a scientific method of hypothesis testing based on animal behavior [2] - Engineers use differential equations and neuronal models to study emergent properties, which are then tested in animals to refine the models [3][4] Reward Systems & Learning in AI - Current artificial intelligence lacks a reward system, which is present even in phylogenetically distant species through dopamine receptors [5] - Dopamine release in the ventral tegmental area reinforces connections between stimuli and predicted rewards, accelerating learning and increasing the signal-to-noise ratio [8][9][10] - Experiments with rats showed that neuronal activity in the frontal cortex anticipates rewards as dopamine release intensifies, improving aspects of neural network learning [11][12] Perception & Consciousness Studies - Perception is subjective and crucial for survival, guiding behavior towards rewards or away from threats [13][14] - Studies on epileptic patients with implanted electrodes allow for in-vivo study of the human brain and consciousness during seizures [15] - Measuring integrated information in the brain correlates with consciousness scores measured by doctors during epileptic seizures [18]