The Neural Basis for Category-Specific Knowledge: An fMRI Study
| Autor: | John A. Detre, Murray Grossman, James C. Gee, David C. Alsop, Christian DeVita, Phyllis Koenig, Guila Glosser |
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| Rok vydání: | 2002 |
| Předmět: |
Adult
Male Cognitive Neuroscience Prefrontal Cortex Lateralization of brain function Functional neuroimaging Cortex (anatomy) Noun Image Processing Computer-Assisted medicine Humans Semantic memory Attention Problem Solving Temporal cortex Brain Mapping Motivation Fourier Analysis Verbal Learning Magnetic Resonance Imaging Paired-Associate Learning Temporal Lobe Frontal Lobe Comprehension medicine.anatomical_structure Neurology Mental Recall Female Arousal Consumer neuroscience Psychology Cognitive psychology |
| Zdroj: | NeuroImage. 15:936-948 |
| ISSN: | 1053-8119 |
| Popis: | Functional neuroimaging studies of healthy adults have associated different categories of knowledge with distinct activation patterns. The basis for these recruitment patterns has been controversial, due in part to the limited range of categories that has been studied. We used fMRI to monitor regional cortical recruitment patterns while subjects were exposed to printed names of Animals, Implements, and Abstract nouns. Both Implements and Abstract nouns were related to recruitment of left posterolateral temporal cortex and left prefrontal cortex, and Abstract nouns additionally recruited posterolateral temporal and prefrontal regions of the right hemisphere. Animals were associated with activation of ventral-medial occipital cortex in the left hemisphere at a level that approaches significance. These findings are not consistent with the “sensory–motor” model proposed to explain the neural representation of word knowledge. We suggest instead a neural model of semantic memory that reflects the processes common to understanding Implements and Abstract nouns and a selective sensitivity, possibly evolving from adaptive pressures, to the overlapping, intercorrelated visual characteristics of Animals. |
| Databáze: | OpenAIRE |
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