The Gating Role of Cortical Transfer of Socially Derived Information in Emotion Recognition Background Introduction Emotion recognition and the subsequent responses are crucial for survival and maintaining social functions. However, how social information is processed to reliably recognize emotions remains unclear. In this new study, the authors re...
Differences in Coupling Between Cortical Networks Related to Arousal in Neural Activity and Hemodynamics Academic Background In the absence of specific sensory inputs or behavioral tasks, the brain generates structured activity patterns. This organized activity is modulated by the state of arousal. The relationship between arousal and cortical acti...
Using Monotonicity-Constrained Deep Geometric Learning to Predict Alzheimer’s Disease Progression Background Introduction Alzheimer’s Disease (AD) is a devastating neurodegenerative disorder that gradually leads to irreversible cognitive decline, eventually resulting in dementia. Early identification and progression prediction of this disease are c...
Parkinson’s Disease Research Report: Subthalamic Nucleus–Language Network Functional Connectivity Predicts Dopaminergic Modulation of Speech Function Background Parkinson’s disease (PD) is primarily characterized by motor impairments, but it also involves non-motor symptoms including speech disorders, severely affecting patients’ quality of life. A...
Academic News Report Background The motor cortex has long been the focus of research on motor control, mainly studying its role in active motor execution. However, even in the absence of actual motor output, the motor cortex also activates during motor imagery. Previous behavioral and imaging studies have confirmed this phenomenon, but how the spec...
Background Introduction Over the long term, normative and descriptive models have been trying to explain and predict human decision-making behavior in the face of risk choices such as products or gambling. A recent study discovered a more accurate human decision model by training Neural Networks (NNs) on a new large-scale online dataset called choi...
Languages with Higher Information Density Exhibit Faster Communication but Lower Conversational Breadth Background Human languages exhibit extensive differences in encoding information. These differences have been studied extensively within certain semantic domains, such as time, space, color, human body parts, and activities. However, there has be...
Differentiating Visual and Semantic Information in Human Perception and Memory Using Deep Neural Networks Introduction In cognitive science, the study of how humans recognize individuals and objects during perception and memory processes has long been of interest. Successful recognition of people and objects relies on matching representations gener...
Academic News Report: Revealing Effector-Independent Evidence Accumulation Dynamics from Intracranial Electrophysiological Recordings Research Background The neural mechanisms underlying the decision-making process have long been a significant topic in neuroscience. Previous studies have indicated that it is possible to identify neural signals rela...
Background Introduction In contemporary neuroscience research, dopamine and serotonin are hypothesized to be crucial neuromodulators guiding social behavior. However, there is a significant lack of understanding regarding the dynamic changes of these neuromodulators during social interactions. Although non-invasive functional neuroimaging methods (...