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White Matter Connectivity

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The applications of diffusion tensor imaging (DTI) have increased considerably among both normal and diverse neuropsychiatric populations in recent years. In this chapter, the authors examine the contributions of DTI in identifying profiles of trait-specific connectivity in several groups defined in terms of gender, age, handedness, and general intelligence. Additionally, the DTI literature is reviewed across a range of neurodegenerative disorders including Alzheimer’s disease, mild cognitive impairment, frontotemporal dementia, Parkinson disease, multiple sclerosis, and acquired neurological disorders resulting from neuronal injury such as traumatic brain injury, aphasia, agnosia, amnesia, and apraxia. DTI metrics sensitive to psychiatric disorders encompassing obsessive-compulsive disorder, depression, bipolar disorder, schizophrenia, and alcoholism are reviewed. Future uses of DTI as a promising means of confirming diagnoses and identifying in vivo early microstructural changes of patients’ clinical symptoms are discussed.
Title: White Matter Connectivity
Description:
The applications of diffusion tensor imaging (DTI) have increased considerably among both normal and diverse neuropsychiatric populations in recent years.
In this chapter, the authors examine the contributions of DTI in identifying profiles of trait-specific connectivity in several groups defined in terms of gender, age, handedness, and general intelligence.
Additionally, the DTI literature is reviewed across a range of neurodegenerative disorders including Alzheimer’s disease, mild cognitive impairment, frontotemporal dementia, Parkinson disease, multiple sclerosis, and acquired neurological disorders resulting from neuronal injury such as traumatic brain injury, aphasia, agnosia, amnesia, and apraxia.
DTI metrics sensitive to psychiatric disorders encompassing obsessive-compulsive disorder, depression, bipolar disorder, schizophrenia, and alcoholism are reviewed.
Future uses of DTI as a promising means of confirming diagnoses and identifying in vivo early microstructural changes of patients’ clinical symptoms are discussed.

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