Zhiyao Gao

Forward reactivation in human hippocampal CA1 supports repetition learning and is preserved in the aging brain

The paper uses fMRI and representational similarity analysis to show that forward reactivation in hippocampal CA1 supports repetition learning and is preserved in aging.

Functional deficits of the inhibitory control system in children with ADHD: A task-based fMRI meta-analysis

This study identifies reduced preSMA activation in children with ADHD during inhibitory control tasks using fMRI meta-analysis.

Protracted Maturation of Proactive and Reactive Systems Predicts Cognitive Stability and Psychopathology : A longitudinal multi-cohort study

The paper uses longitudinal fMRI data to show that proactive and reactive control networks stabilize after mid-adolescence, predicting cognitive stability and psychopathology.

Nonergodicity and Simpson's paradox in neurocognitive dynamics of cognitive control

The paper investigates nonergodicity and Simpson's paradox in cognitive control dynamics using brain imaging and behavioral data from over 4,000 children, revealing brain-behavior associations that reverse between between-subjects and within-subjects analyses.

Latent brain state dynamics predict early amyloid accumulation and cognitive impairment

This study uses brain state dynamics to predict early amyloid accumulation and cognitive impairment in older adults.

Shared and distinct neural signatures of inhibitory control deficits in attention-deficit/hyperactivity disorder and autism

This study identifies shared and distinct neural patterns in inhibitory control deficits between ADHD and ASD using fMRI data.

Reduced temporal and spatial stability of neural activity patterns predict cognitive control deficits in children with ADHD

This study identifies increased temporal variability and reduced spatial stability in neural activity patterns in children with ADHD, correlating with cognitive control deficits and symptom severity.

Visual to default network pathways: A double dissociation between semantic and spatial cognition

The paper identifies two distinct pathways between visual and default mode networks that support semantic and spatial cognition, showing their dissociation in functional connectivity and task responses.

Hippocampal contributions to novel spatial learning are both age-related and age-invariant

This study examines age-related changes in neural representations of spatial environments using fMRI, finding both age-dependent and independent factors affecting spatial memory performance.

Flexing the principal gradient of the cerebral cortex to suit changing semantic task demands

The paper uses fMRI data to show how the principal gradient of connectivity in the cerebral cortex changes during semantic tasks, revealing how strong conceptual links are associated with separation of DMN from sensory-motor systems.

Creativity in Verbal Associations is Linked to Semantic Control

The paper investigates how semantic control relates to creativity in verbal associations by analyzing neural networks involved in retrieving strongly and weakly related word pairs.

Context Free and Context-Dependent Conceptual Representation in the Brain

This study investigates how conceptual representations in the brain change with context, finding distinct brain regions involved in maintaining individual word meaning versus context-dependent meaning.

A tale of two gradients: Differences between the left and right hemispheres predict semantic cognition and visual reasoning

This study identifies hemispheric differences in a principal gradient of brain connectivity and links these differences to semantic cognition and visual reasoning.

Distinct and Common Neural Coding of Semantic and Non-semantic Control Demands

The paper examines neural coding of semantic and non-semantic control demands using fMRI and finds distinct and common patterns in semantic and multiple-demand networks.

Both default and multiple-demand regions represent semantic goal information

The paper investigates the role of default mode and multiple-demand networks in semantic goal information using multivoxel pattern decoding in a semantic feature matching task.