The lesion method, which identifies consistent relationships between sites of brain damage and acquired impairments of cognition and behavior, continues to be an indispensable approach in neuroscience for identifying the neural basis of higher function. The overall goal of this project is to put the lesion method on a rigorous, quantitative footing, and to determine and extend its limits, especially with respect to the specificity and interpretability of localization. We will introduce methods for formally integrating connectivity information, from diffusion tensor imaging, into group-level voxel-based lesion-deficit analyses. We will investigate the validity, reliability, and anatomic accuracy of existing and new methods, with particular attention to the impact of the subject group, non-uniform lesion coverage, and the different roles of gray and white matter damage. We will validate voxel-based statistical methods for lesion studies in two ways: 1) with simulations based on a large set of real brain lesions, that capture the effects of the complex structure of the natural lesion sample;and 2) in a well characterized database of lesions in the retinotopically organized visual system, for which there will be multispectral MRI data and extensive functional assessment (retinotopic fMRI, multifocal visual evoked potentials, quantitative visual fields, and metabolic PET data). Another overarching goal is to determine best practices for the lesion method, including identification of the optimal (efficient, sensitive, valid) forms of analysis and generation of resources for evaluating future improvements in the methods. Finally, we will disseminate methods, software, validation data sets, and performance benchmarks generated in this Project to the brain mapping community. The work proposed here will enable the lesion method to be used with unprecedented confidence to identify the essential components of neural systems for normal cognition and behavior.
Studying the behavioral and cognitive consequences of focal brain damage provides information about the brain basis of cognitive abilities that can be gained from no other source. The proposed work will help establish best practices for the lesion method, making it easier to study and understand the impairments that result from stroke and other neurologic diseases.
| Mehta, Sonya; Inoue, Kayo; Rudrauf, David et al. (2016) Segregation of anterior temporal regions critical for retrieving names of unique and non-unique entities reflects underlying long-range connectivity. Cortex 75:1-19 |
| Inoue, Kayo; Madhyastha, Tara; Rudrauf, David et al. (2014) What affects detectability of lesion-deficit relationships in lesion studies? Neuroimage Clin 6:388-97 |
| Philippi, Carissa L; Mehta, Sonya; Grabowski, Thomas et al. (2009) Damage to association fiber tracts impairs recognition of the facial expression of emotion. J Neurosci 29:15089-99 |
