Construction of human 3D striato-nigral assembloids to recapitulate medium spiny neuronal projection defects in Huntington’s disease

Construction of human 3D striato-nigral assembloids to recapitulate medium spiny neuronal projection defects in Huntington’s disease

Constructing Human 3D Striatum-Substantia Nigra Organoids to Model Medium Spiny Neuron Projection Deficits in Huntington’s Disease Background Introduction Huntington’s Disease (HD) is a neurodegenerative disorder leading to significant deterioration of the motor system, primarily characterized by defects in medium spiny neurons (MSNs) that project ...

APOE4 Homozygosity Represents a Distinct Genetic Form of Alzheimer’s Disease

APOE4 Homozygotes Represent a Unique Genotypic Subset of Alzheimer’s Disease Introduction Alzheimer’s disease (AD) is one of the neurodegenerative diseases that modern medicine has yet to conquer, usually with a complex genetic background. While mutations in three genes (APP, PSEN1, and PSEN2) lead to early-onset autosomal dominant Alzheimer’s dise...

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...

Deep Geometric Learning with Monotonicity Constraints for Alzheimer’s Disease Progression

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...

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...

Intracranial electroencephalography reveals effector-independent evidence accumulation dynamics in multiple human brain regions

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...

Prediction of tumor origin in cancers of unknown primary origin with cytology-based deep learning

Prediction of tumor origin in cancers of unknown primary origin with cytology-based deep learning

Background Introduction Cancer of Unknown Primary (CUP) is a type of malignant disease that is confirmed to be metastatic through histopathology but whose primary site cannot be identified using conventional baseline diagnostic methods. CUP presents significant diagnostic and therapeutic challenges in clinical practice and is believed to account fo...