Egocentric memory impaired and allocentric memory intact as assessed by virtual reality in subjects with unilateral parietal cortex lesions
- PMID: 18789955
- DOI: 10.1016/j.neuropsychologia.2008.08.018
Egocentric memory impaired and allocentric memory intact as assessed by virtual reality in subjects with unilateral parietal cortex lesions
Abstract
Present evidence suggests that medial temporal cortices subserve allocentric representation and memory, whereas egocentric representation and memory mainly depends on inferior and superior parietal cortices. Virtual reality environments have a major advantage for the assessment of spatial navigation and memory formation, as computer-simulated first-person environments can simulate navigation in a large-scale space. However, virtual reality studies on allocentric memory in subjects with cortical lesions are rare, and studies on egocentric memory are lacking. Twenty-four subjects with unilateral parietal cortex lesions due to infarction or intracerebral haemorrhage (14 left-sided, 10 right-sided) were compared with 36 healthy matched control subjects on two virtual reality tasks affording to learn a virtual park (allocentric memory) and a virtual maze (egocentric memory). Subjects further received a comprehensive clinical and neuropsychological investigation, and MRI lesion assessment using T(1), T(2) and FLAIR sequences as well as 3D MRI volumetry at the time of the assessment. Results indicate that left- and right-sided lesioned subjects did not differ on task performance. Compared with control subjects, subjects with parietal cortex lesions were strongly impaired learning the virtual maze. On the other hand, performance of subjects with parietal cortex lesions on the virtual park was entirely normal. Volumes of the right-sided precuneus of lesioned subjects were significantly related to performance on the virtual maze, indicating better performance of subjects with larger volumes. It is concluded that parietal cortices support egocentric navigation and imagination during spatial learning in large-scale environments.
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