Cortical language activation in aphasia: a functional MRI study

Background Functional neuroimaging has been used in neurolinguistic research on normal subjects and on patients with brain damage. This study was designed to investigate the differences of the neural basis underlying language processing between normal subjects and aphasics.Methods Functional magnetic resonance imaging (fMRI) was used to map the language network in 6 normal subjects and 3 patients with aphasia who were in the stage of recovery from acute stroke. The participants performed a word generation task during multi-slice functional scanning for the measurement of signal change associated with regional neural activity induced by the task. Results In normal subjects, a distributed language network was activated. Activations were present in the frontal, temporal, parietal and occipital regions. In the patient group, however, no activation was detected in the left inferior frontal gyrus whether the patient had a lesion in the left frontal lobe or not. Two patients showed activations in some right hemisphere regions where no activation appeared in normal subjects. Conclusions fMRI with word generation task is feasible for evaluating language function in aphasic patients. Remote effect of focal lesion and functional redistribution or reorganisation can be found in aphasic patients.

Clinical applications of neurolinguistics in neurosurgery

The protection of language function is one of the major challenges of brain surgery.Over the past century,neurosurgeons have attempted to seek the optimal strategy for the preoperative and intraoperative identification of language-related brain regions.Neurosurgeons have investigated the neural mechanism of language,developed neurolinguistics theory,and provided unique evidence to further understand the neural basis of language functions by using intraoperative cortical and subcortical electrical stimulation.With the emergence of modern neuroscience techniques and dramatic advances in language models over the last 25 years,novel language mapping methods have been applied in the neurosurgical practice to help neurosurgeons protect the brain and reduce morbidity.The rapid advancements in brain-computer interface have provided the perfect platform for the combination of neurosurgery and neurolinguistics.In this review,the history of neurolinguistics models,advancements in modern technology,role of neurosurgery in language mapping,and modern language mapping methods(including noninvasive neuroimaging techniques and invasive cortical electroencephalogram)are presented.

The Semantic Data Dictionary-An Approach for Describing and Annotating Data

It is common practice for data providers to include text descriptions for each column when publishing data sets in the form of data dictionaries.While these documents are useful in helping an end-user properly interpret the meaning of a column in a data set,existing data dictionaries typically are not machine-readable and do not follow a common specification standard.We introduce the Semantic Data Dictionary,a specification that formalizes the assignment of a semantic representation of data,enabling standardization and harmonization across diverse data sets.In this paper,we present our Semantic Data Dictionary work in the context of our work with biomedical data;however,the approach can and has been used in a wide range of domains.The rendition of data in this form helps promote improved discovery,interoperability,reuse,traceability,and reproducibility.We present the associated research and describe how the Semantic Data Dictionary can help address existing limitations in the related literature.We discuss our approach,present an example by annotating portions of the publicly available National Health and Nutrition Examination Survey data set,present modeling challenges,and describe the use of this approach in sponsored research,including our work on a large National Institutes of Health(NIH)-funded exposure and health data portal and in the RPI-IBM collaborative Health Empowerment by Analytics,Learning,and Semantics project.