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The next step in modern brain lesion analysis: multivariate pattern analysis

Hans-Otto Karnath, David V. Smith
DOI: http://dx.doi.org/10.1093/brain/awu180 2405-2407 First published online: 14 August 2014

This scientific commentary refers to ‘Human brain lesion-deficit inference remapped’, by Y.-H. Mah et al. (doi: 10.1093/brain/awu164).

A cardinal goal in neuroscience relates to mapping brain circuits to specific functions. Although progress towards this goal has been made using a range of measurement techniques applicable in healthy human subjects, the brain circuits that are necessary for a given function can only be ascertained by observing the behavioural consequences of brain injury (Rorden and Karnath, 2004). In the evolution of this domain, voxel-wise lesion symptom mapping (VLSM; Bates et al., 2003) represents a tremendous step forward. This statistical approach, as well as other inferential methods (e.g. Rorden et al., 2007), controls for regions that are not critical for the behavioural deficit under consideration; i.e. VLSM rules out regions of the brain that are simply vulnerable to damage and thus commonly damaged in stroke patients.

However, a limitation of this mass univariate approach is that it typically does not consider how multiple regions interact to produce a behavioural deficit. Indeed, in cases where function is tied to a distributed network of regions, two patients with the same symptom and with damage to the same functional network may have damage to distinct parts of the network, thus appearing as statistical counter examples to each other [cf. the ‘partial injury problem’ (Rorden and Karnath, 2004)]. To overcome this problem, Smith et al. (2013) used multivariate pattern analysis (MVPA) for lesion analysis, which uses machine learning algorithms (e.g. support vector machines) to train and then test predictive models based on the pattern of damage to multiple regions (Fig. 1). This seminal application of MVPA to lesion data addressed the multivariate patterns of damage predictive of spatial neglect. In a large sample of 140 patients with acute right brain damage, MVPA …

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