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The technique of clinical-pathological correlations is the oldest method for understanding the neural basis of cognitive function and has been a mainstay of neurology and neurosurgery for more than a century. A major advantage of this approach is that if damage to a brain area or system disrupts a cognitive function, it is likely that the damaged region is involved in some critical way in the performance of that function. This approach was first accomplished by correlating a patient’s signs, symptoms, and behavior during life with the location of brain lesions discovered upon autopsy. Brain lesions can arise from a stroke that damages a particular region of cortex, from traumatic injury, from a tumor, or from various brain diseases. Many examples of clinical-pathological correlations are considered in later chapters, including the seminal work that associated language functions with specific regions in the left hemisphere (see Chapter 12); studies that associated frontal lobe damage with deficits in planning and judgment (see Chapter 14); and studies that have provided fundamental insights into the neural basis of perception (see Chapters 3 and 4), attentional control (see Chapter 7), memory (see Chapters 8 and 9), and emotion (see Chapter 10). A major limitation of clinical-pathological correlations in humans, however, is that the brain damage is the result of many factors that are not under the control of the experimenter. In the case of strokes, for example, these factors include which specific artery was blocked, which brain area(s) that artery supplied, whether other arteries were still able to supply some blood to the affected area, and how long ago the stroke occurred. Although stroke-induced lesions can be relatively focal, they follow vascular-supply boundaries rather than being restricted to functional brain regions, and thus a single lesion can have diverse effects on cognitive functions. Moreover, the distribution of brain regions supporting cognitive functions varies among individuals, making it difficult to generalize results. This variability can be addressed to some degree by combining information about the