3. D. G. MacKay et al., “H.M. Revisited: Relations between Language Comprehension, Memory, and the Hippocampus System,” Journal of Cognitive Neuroscience 10 (1998): 377–94.
4. Kensinger et al., “Bilateral Medial Temporal Lobe Damage Does Not Affect Lexical or Grammatical Processing.”
5. Ibid.
6. Ibid.
7. A. D. Friederici, “The Brain Basis of Language Processing: From Structure to Function,” Physiological Review 92 (2011): 1357–92; C. J. Price, “A Review and Synthesis of the First 20 Years of PET and fMRI Studies of Heard Speech, Spoken Language, and reading,” Neuroimage 62 (2012): 816–47.
8. D. C. Park and P. Reuter-Lorenz, “The Adaptive Brain: Aging and Neurocognitive Scaffolding,” Annual Review of Psychology 60 (2009): 173–96.
9. Kensinger et al., “Bilateral Medial Temporal Lobe Damage Does Not Affect Lexical or Grammatical Processing.”
10. E. K. Warrington and L. Weiskrantz, “Amnesic Syndrome: Consolidation or Retrieval?,” Nature 228 (1970): 628–30; W. D. Marslen-Wilson and H.-L. Teuber, “Memory for Remote Events in Anterograde Amnesia: Recognition of Public Figures from Newsphotographs,” Neuropsychologia 13 (1975): 353–64.
11. M. Kinsbourne and F. Wood, “Short-Term Memory Processes and the Amnesic Syndrome,” in Short-Term Memory, eds, D. Deutsch et al. (San Diego, CA: Academic Press, 1975), 258–93; M. Kinsbourne, “Brain Mechanisms and Memory,” Human Neurobiology 6 (1987): 81–92.
12. J. D. Gabrieli et al., “The Impaired Learning of Semantic Knowledge Following Bilateral Medial Temporal-Lobe Resection,” Brain Cognition 7 (1988): 157–77.
13. Ibid.
14. F. B. Wood et al., “The Episodic-Semantic Memory Distinction in Memory and Amnesia: Clinical and Experimental Observations,” in Human Memory and Amnesia, eds, L. S. Cermak (Hillsdale, NJ: Erlbaum, 1982), 167–94.
15. J. D. Gabrieli et al., “The Impaired Learning of Semantic Knowledge.”
16. Ibid.
17. Ibid.
18. Ibid.
19. B. R. Postle and S. Corkin, “Impaired Word-Stem Completion Priming but Intact Perceptual Identification Priming with Novel Words: Evidence from the Amnesic Patient H.M.,” Neuropsychologia 36 (1998): 421–40.
20. Ibid.
21. Ibid.
22. Ibid.
23. Ibid.
24. Ibid.
25. Ibid.
26. E. Tulving et al., “Long-Lasting Perceptual Priming and Semantic Learning in Amnesia: A Case Experiment,” Journal of Experimental Psychology: Human Learning and Memory 17 (1991): 595–617; P. J. Bayley and L. R. Squire, “Medial Temporal Lobe Amnesia: Gradual Acquisition of Factual Information by Nondeclarative Memory,” Journal of Neuroscience 22 (2002): 5741-8.
27. G. O’Kane et al., “Evidence for Semantic Learning in Profound Amnesia: An Investigation with Patient H.M.,” Hippocampus 14 (2004); 417–25.
28. Ibid.
29. Ibid.
30. Ibid.
31. Ibid.
32. Ibid.
33. Ibid.
34. Ibid.
35. Ibid.
36. B. G. Skotko et al., ““Puzzling Thoughts for H.M.: Can New Semantic Information Be Anchored to Old Semantic Memories?,” Neuropsychology 18 (2004): 756–69.
37. Ibid.
38. Ibid.
39. F. C. Bartlett, Remembering: A Study in Experimental and Social Psychology (Cambridge: University Press, 1932).
40. D. Tse et al., “Schemas and Memory Consolidation,” Science 316 (2007): 76–82.
41. Ibid.
Chapter Twelve: Rising Fame and Declining Health
1. W. B. Scoville and B. Milner, “Loss of Recent Memory after Bilateral Hippocampal Lesions,” Journal of Neurology, Neurosurgery, and Psychiatry 20 (1957): 11–21.
2. D. H. Salat et al., “Neuroimaging H.M.: A 10-Year Follow-up Examination,” Hippocampus 16 (2006): 936–45.
3. Our brains house billions of individual nerve cells or neurons, with thousands of distinct types already identified and others still unknown. Neurons are dedicated to information processing—receiving, conducting, and transmitting electrical and chemical signals. The standard neuron has a nerve-cell body, numerous dendrites, and a single axon that branches out. The dendrites receive signals from other cells and deliver them to the cell body, while the axon carries signals away from the cell body to activate other neurons. Clusters of nerve-cell bodies are called gray matter, and collections of axons are referred to as white matter. The cerebral cortex is made up of gray matter, while the short and long fiber pathways that allow information to flow from one area to another are white matter. With MRI, we have been able to observe the effects of brain aging in both gray matter and white matter in healthy older people and in Henry (E. Diaz, “A Functional Genomics Guide to the Galaxy of Neuronal Cell Types,” Nature Neuroscience 9 (2006): 10–12; K. Sugino et al., “Molecular Taxonomy of Major Neuronal Classes in the Adult Mouse Forebrain,” Nature Neuroscience 9 (2006): 99–107).
One autopsy study of older adults who were not demented found that the gray matter in the cortex became much thinner with increasing age, but cortical thickness did not correlate with performance on a cognitive test that estimated the individual’s overall mental capacity just before death. This finding suggested that cognition in aging might be more closely linked to the loss of white matter than gray matter. If that were the case, then what would be the consequence of white-matter breakdown? When the white matter is intact, the transmission of neural information is fast and on course, a river flowing swiftly with no obstacles in the way. But when minute structures in the white matter are compromised, this river is cluttered with dams, rocks, trees, and a partially submerged boat. Neural transmission becomes obstructed and inefficient, slowing neural and cognitive processing. (S. H. Freeman et al., “Preservation of Neuronal Number Despite Age-Related Cortical Brain Atrophy in Elderly Subjects without Alzheimer Disease,” Journal of Neuropathology and Experimental Neurology 67 (2008): 1205–12; T. A. Salthouse, “The Processing-Speed Theory of Adult Age Differences in Cognition,” Psychological Review 103 (1996): 403–28).
Although white-matter changes are more conspicuous than gray-matter changes in older brains, mapping out these networks in the living brain was difficult until recently. An advanced type of MRI, diffusion-tensor imaging, can now measure and map white-matter tissue integrity in living individuals in health and disease. With this tool, our collaborators at Mass General Martinos Center found erosion of white matter not only in older participants but also in middle-aged individuals, reinforcing that age-related decline in memory may also begin in middle age, even in perfectly healthy people.
In 2008, my lab members and I asked two key questions: are white matter and gray matter affected differently by aging, and are measures of cognitive performance more closely linked to alterations in white matter or to alterations in gray matter? We used advanced MRI techniques to measure gray matter thickness and subtle changes in white matter across the entire brain in young and older participants. The imaging data provided information about the integrity of brain areas that mediated three kinds of abilities: episodic memory, delayed recall of word lists and stories; semantic memory, naming objects and vocabulary; and cognitive control processes—paying attention, overriding dominant responses, and achieving goals. On the cognitive tests, the young adults outperformed the older adults on measures of episodic memory and cognitive control, but, as is often the case, the older adults performed better than the young on the semantic memory tasks, which probed their general knowledge about the world. As we age, our vocabulary and pool of information grow and become more sophisticated.
Consistent with previous studies, we found that healthy aging is accompanied by deterioration of gray and white matter. A further analysis of the MRI images revealed new insights. When we correlated these measures of brain structure with the older adults’ cognitive-test scores, we found that cortical thickness—the indicator of gray matter—was unrelated to perform
ance on the cognitive tests. Instead, our results confirmed the speculation that white-matter damage is largely responsible for the cognitive deficits that characterize healthy aging. We found region-specific correlations between cognitive-test scores and measures of white matter. Cognitive-control processes correlated with the integrity of frontal-lobe white matter, whereas episodic memory was related to the integrity of temporal- and parietal-lobe white matter. Our experiment sent the important message that scientists who want to understand the neural underpinnings of cognitive loss should examine not just gray matter, but white matter as well. This suggestion applies not just to experiments on aging and diseases of aging, but also to research on participants of all ages. (D. A. Ziegler et al., “Cognition in Healthy Aging Is Related to Regional White Matter Integrity, but Not Cortical Thickness,” Neurobiology of Aging 31 (2010): 1912–26); D. H. Salat et al., “Age-Related Alterations in White Matter Microstructure Measured by Diffusion Tensor Imaging,” Neurobiology of Aging 26 (2005): 1215–27.
4. J. W. Rowe and R. L. Kahn, “Human Aging: Usual and Successful,” Science 237 (1987): 143–9.
5. Salat et al., “Neuroimaging H.M.”
6. Ibid.
Chapter Thirteen: Henry’s Legacy
1. I had long believed that it would be essential to study Henry’s brain after his death to take full advantage of the wealth of information that evolved from his research participation. My view about brain donation stemmed partly from recognizing the value of information that had been gained from previous autopsy studies in Parkinson and Alzheimer disease. In 1960, a neuroscientist at the University of Vienna conducted autopsies of patients with Parkinson disease, and found that they had lower than normal levels of dopamine in their brain. This major discovery spurred treatments to replace dopamine function and thereby relieve the abnormal movements that characterize Parkinson disease.
In Alzheimer disease, we can know for sure that a patient had the disease only by looking for pathological markers in the brain at autopsy. Even in the early stages of the disorder, neurofibrillary tangles and amyloid plaques are abundant, and cell death is significant.
Examining brains after death also enlightens scientists who study cognitive functions in other manifestations of brain damage, although autopsies on such cases are rare. In this book, I have emphasized how much we have learned about the roles of different brain circuits by studying patients who had the misfortune of losing function in those areas; Henry was just one outstanding example. In most of our research, we make guesses about the actual brain damage. When I studied brain injuries in military veterans, for instance, I had to infer the location and extent of their brain lesions based on the wounds in their skulls. Recent imaging advances have made it possible to see brain anatomy in much more detail, but MRI is still imperfect. The only way to truly see brain abnormalities is to look directly at the brain, which is possible only after death. Postmortem studies of these patients tell us, in a more detailed and complete way, what brain damage led to their cognitive deficits, and they could inform scientific debates about the role of specific brain structures in memory and other capacities.
2. “H.M., an Unforgettable Amnesiac, Dies at 82”; www.nytimes.com/2008/12/05/us/05hm.html?pagewanted=all (accessed December 2012).
Epilogue
1. Experimental surgeries have been practiced since antiquity and have been the bedrock of many treatment advances. A startling twenty-first-century example is natural-orifice surgery. Several years ago, a Mass General surgeon extracted a woman’s gallbladder via her vagina. This kind of surgery, unpleasant as it sounds, offers several advantages over time-honored methods. These procedures do not require an incision because they are carried out through a natural opening in the body—the mouth, anus, vagina, or urethra. As a result, they do not leave a scar, and the recovery time is much faster—days instead of weeks, in the case of gallbladder removal. Although natural-orifice surgery seems safe and effective, we cannot draw firm conclusions about the experiments until each procedure and its specialized new tools have been tested in clinical trials. In contrast, Henry’s experimental operation immediately gave a strong directive to other surgeons—never perform this operation. Sacha Pfeiffer, “You Want to Take My What Out of My Where? Hospitals Experiment with Orifice Surgery,” WBUR / NPR News, June 22, 2009, www.wbur.org/2009/06/22/orifice-surgery (accessed December 2012).
2. B. Milner and W. Penfield, “The Effect of Hippocampal Lesions on Recent Memory,” Transactions of the American Neurological Association (1955–56): 42–48; W. B. Scoville, “World Neurosurgery: A Personal History of a Surgical Specialty,” International Surgery 58 (1973): 526–35.
3. S. Tigaran et al., “Evidence of Cardiac Ischemia during Seizures in Drug Refractory Epilepsy Patients,” Neurology 60 (2003): 492–95.
Index
Adaptation, 88, 165–167, 334
Akkadian Empire, 6–7
Altruism, Henry’s, xv, 207–208, 311
Alzheimer disease, 47, 69, 83, 196–198, 280, 282–283, 302, 324, 326, 334, 339, 344–345
Ambiguities, lexical, 238–241
American Neurological Association, 44–45
Amnesia
animal models, 46, 89, 324, 327–328
anterograde amnesia, 81–82, 213–214, 218, 222, 313, 338–339
defining, xii
dementia and, 218, 223, 269, 278
retrograde amnesia, 213–215, 218, 222–224, 340–341
See also Memory
Amygdala
bilateral medial temporal-lobe resection, 17, 30–31
bioethical questions about psychosurgery, 309–312
emotions, 101, 103, 107, 111, 228
Henry’s operation, 17, 30–31
long-term effect of removal, 103, 107, 209–213, 231, 233
MRI of Henry’s postoperative brain, 80–81
olfaction, 87–88
operation on D.C., 45
operation on F.C. and P.B., 42
postmortem research, 301–302
temporal lobe seizures, 9, 311
Ancient civilizations, 6–7, 10
Anesthesia, 8, 19, 39, 274
Animal models of amnesia, 46, 89, 324, 327–328
Animal research
chimpanzee memory experiments, 22–23
encoding information, 126–127, 133–134, 262
information reconsolidation, 141–143
long-term potentiation, 131–134
Pavlov’s classical conditioning in dogs, 182
place cells, 135–137
schema learning, 262–263
sleep, 135–139
Animals, Henry’s love for, 269–270
Annese, Jacopo, 288, 294–295, 297–301
Digital Brain Laboratory Project (UCSD), 302
Anterograde amnesia, 81–82, 213–214, 218, 222, 313
Antibodies, 302
Aplysia (sea snail), 56–57
Appetite, 10, 85, 111, 209–212, 275, 282
Applied mathematics, 69–70, 116
Art and theater, 308
Aspiration, 30–31
Associations, formation of, 122, 126–130, 150, 195–196, 199, 224, 262–263, 272
Associativity, 133
Atkinson, Richard, 70–71, 146
Auditory cortex, 186
Autobiographical memory, 215, 217–237, 313
Automobile accident, 108–110
Autopsy. See Postmortem research
Awareness, 82, 92, 94, 152, 160, 185–187, 196, 198–199, 246, 256, 258, 313
Axonal varicosities, 131
Axons, 130–132
Baddeley, Alan, 71–72
Balance, 80, 151–152
Ballantine, H. Thomas, 26
Bartlett, Sir Frederic, 41, 261
Berger, Hans, 9
Bickford, Ken, 205
Bickford, Rose, 205
Bickford Health Care Center, 84, 149–150, 205–206, 219, 263, 265, 267–276, 281, 283, 285, 287, 291, 305–307
Bil
ateral medial temporal-lobe resection, xii, 17, 45–46, 212, 240, 258, 309, 311
psychiatric results, 16
Bimanual tracking, 157–159, 171, 175, 177
Bioethics, 267, 309–312
Bit, 116
Blasko, Lucille Taylor, 11–12
Blogging, 309
Brain function model, 9
Brain imaging, xviii, xx, 77, 79–82, 118, 123–124, 148, 176–177, 187–188, 241–242, 276, 279–281, 288, 290, 292–293, 295, 297–298, 302–303, 306
Brain stem, 80
Brown, John, 64
Brown-Peterson distractor task, 63–65
Buckler, Arthur, 103–104, 112
Bullemer, Peter, 163, 178
Burckhardt, Gottlieb, 22
Card-sorting task, 66–67, 70
Carey, Benedict J., 297, 300
Caudate nucleus, 161–162, 164, 168, 242
Celebrities, knowledge of, 82, 189, 216, 248–249, 254–261, 264
Central executive subsystem, 71
Cerebellum
classical conditioning, 182–183, 185
Henry’s atrophied brain, 79–80, 302
internal models, 170–171
motor-skill learning, 151, 161, 165–168, 170–171, 176–177, 179
Cerebral cortex
communication with hippocampus, 77–78, 92–93, 110, 127, 129–130, 137–139, 224–230
depth of processing effect, 120
first recorded psychosurgery in, 22
neural location of short-term memory, 61–62
See also Frontal lobe, Occipital lobe, Parietal lobe, Temporal lobe
Cerebral hemispheres, 28, 49, 239, 242
Chaplin, Charlie, 184, 260
Childhood, xii, xiv, 3–6, 84, 139, 173, 214, 221, 225–226, 234, 260, 300
Chimpanzee experiments, 22–23
Churchland, Patricia, 300
Churchland, Paul, 300
Cingulate cortex, 93, 101, 124, 210, 236
Claparède, Édouard, 153
Classical conditioning, 153, 181–186, 199
Cognitive map, 89, 92–96
Cognitive processes, xvi, 8, 46, 62, 65, 67, 70, 72, 94, 116–118, 123–124, 146–147, 156, 163, 175, 178, 197, 199, 242, 277, 314
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