International journal of neural systems
May 15, 2018
Brain function has been proposed to arise as a result of the coordinated activity between distributed brain areas. An important issue in the study of brain activity is the characterization of the synchrony among these areas and the resulting complexi...
Contemporary cognitive neuroscience recognises unconstrained processing varies across individuals, describing variation in meaningful attributes, such as intelligence. It may also have links to patterns of on-going experience. This study examined whe...
The International journal of neuroscience
Apr 23, 2018
Functioning, but injured cerebral connections are hypothesized to inhibit cortical plasticity. Study of neural networks can validate this hypothesis, and provide further practical clues for clinical and surgical options to restore function in eloque...
OBJECTIVE: A growing literature indicates that unipolar depression and bipolar depression are associated with alterations in grey matter volume. However, it is unclear to what degree these patterns of morphometric change reflect symptom dimensions. H...
Electrocorticography (ECoG), electrophysiological recording from the pial surface of the brain, is a critical measurement technique for clinical neurophysiology, basic neurophysiology studies, and demonstrates great promise for the development of neu...
International journal of neural systems
Apr 11, 2018
Functional brain network (FBN) has become very popular to analyze the interaction between cortical regions in the last decade. But researchers always spend a long time to search the best way to compute FBN for their specific studies. The purpose of t...
Proceedings of the National Academy of Sciences of the United States of America
Mar 12, 2018
A hallmark of cortical circuits is their versatility. They can perform multiple fundamental computations such as normalization, memory storage, and rhythm generation. Yet it is far from clear how such versatility can be achieved in a single circuit, ...
To develop a new method for measuring Alzheimer's disease (AD)-specific similarity of cortical atrophy patterns at the individual-level, we employed an individual-level machine learning algorithm. A total of 869 cognitively normal (CN) individuals an...
OBJECTIVE: We investigated the potential of computer-based models to decode diagnosis and lifetime consumption in alcohol dependence (AD) from grey-matter pattern information. As machine-learning approaches to psychiatric neuroimaging have recently c...
The activities of groups of neurons in a circuit or brain region are important for neuronal computations that contribute to behaviors and disease states. Traditional extracellular recordings have been powerful and scalable, but much less is known abo...
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