Cortico-cortical transfer of socially derived information gates emotion recognition

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...

Cortical Networks Relating to Arousal Are Differentially Coupled to Neural Activity and Hemodynamics

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...

Subthalamic Nucleus-Language Network Connectivity Predicts Dopaminergic Modulation of Speech Function in Parkinson’s Disease

Subthalamic Nucleus-Language Network Connectivity Predicts Dopaminergic Modulation of Speech Function in Parkinson’s Disease

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...

Motor Cortex Retains and Reorients Neural Dynamics During Motor Imagery

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...

Using Deep Neural Networks to Disentangle Visual and Semantic Information in Human Perception and Memory

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...