Dynamics of the Hippocampus During Encoding and Retrieval of Face-Name Pairs

Zeineh, Michael; Engel, Stephen A.; Thompson, Paul M.; Bookheimer, Susan Y.

doi:10.1126/science.1077775

Cited by 458 publications

(504 citation statements)

References 28 publications

Supporting

Mentioning

431

Contrasting

Unclassified

Order By: Relevance

“…Nonetheless, the automated partitioning of the hippocampal surface was performed consistently across all subjects because the diffeomorphic transformations from the template ensured reliable registration across subjects, thus allowing for the examination of the different zones on the hippocampal surface in all subjects based the zones predefined on the surface of the provisory hippocampal template. Similar strategies have been employed by others to examine functions within hippocampal subfields in high-resolution MR scans (Zeineh et al, 2003).…”

Section: Discussionmentioning

confidence: 96%

Abnormalities of hippocampal surface structure in very mild dementia of the Alzheimer type

et al. 2006

View full text Add to dashboard Cite

To better define the pattern of hippocampal deformity early in the course of Alzheimer's disease, we compared the pattern of hippocampal surface variation in subjects with very mild dementia of the Alzheimer type (DAT) and nondemented subjects. The surface of the hippocampus was divided a priori on a neuroanatomical template into three zones approximating the locations of underlying subfields [Csernansky, J.G., Wang, L., Swank, J., Miller, J.P., Gado, M., McKeel, D., Miller, M.I., Morris, J.C., 2005. Preclinical detection of Alzheimer's disease: hippocampal shape and volume predict dementia onset in the elderly. NeuroImage 25, 783-792]; i.e., a lateral zone (LZ) approximating the CA1 subfield, a superior zone (SZ) approximating the combined CA2, CA3, CA4 subfields and the gyrus dentatus (GD), and an inferior-medial zone (IMZ) approximating the subiculum. Large-deformation high-dimensional brain mapping (HDBM-LD) was used to generate the hippocampal surfaces of all subjects and to register the surface zones across subjects. Average variations within each zone were calculated for the subjects with very mild DAT as compared to the average of the nondemented subjects. After correcting for multiple comparisons, the very mild DAT subjects showed significant inward variation in the left and right LZ, the left and right IMZ, but not in the left and right SZ as compared to nondemented subjects. In logistic regression analyses, inward variation of the left and right LZ or IMZ by 0.1 mm relative to the average of the nondemented subjects increased the odds of the subject being a very mild DAT subject (range-1.18 to 1.57) rather than being a nondemented subject. The odds ratios for the left and right SZ were not significant. These results represent a replication of our previous findings [Csernansky, J.G., Wang, L., Joshi, S., Miller, J.P., Gado, M., Kido, D., McKeel, D., Morris, J.C., Miller, M.I., 2000. Early DAT is distinguished from aging by high-dimensional mapping of the hippocampus. Neurology 55, 1636-1643.] and suggest that inward deformities of the hippocampal surface in proximity to the CA1

show abstract

Section: Discussionmentioning

confidence: 96%

Abnormalities of hippocampal surface structure in very mild dementia of the Alzheimer type

et al. 2006

View full text Add to dashboard Cite

show abstract

“…These data may include information on cortical thickness, gray matter density, functional MRI signals (Rasser et al, in press;Zeineh et al, 2003), or many other cortical measures. Fig.…”

Section: Statistical Maps On the Cortexmentioning

confidence: 99%

“…Ongoing work aims to better understand these deficits by determining whether they are found in genetically at-risk relatives of patients , whether they represent an acceleration of normally occurring brain changes (Gogtay et al, 2004), and whether they are differentially modulated by different types of antipsychotic drugs. The cortical pattern matching approach has also been used to correlate gray matter differences with fMRI measures in tasks that recruit the frontal lobes (Rasser et al, in press) and can be applied to functional imaging data with minor modifications (Zeineh et al, 2003).…”

Section: Schizophreniamentioning

confidence: 99%

Mapping cortical change in Alzheimer's disease, brain development, and schizophrenia

et al. 2004

Self Cite

View full text Add to dashboard Cite

This paper describes algorithms that can identify patterns of brain structure and function associated with Alzheimer's disease, schizophrenia, normal aging, and abnormal brain development based on imaging data collected in large human populations. Extraordinary information can be discovered with these techniques: dynamic brain maps reveal how the brain grows in childhood, how it changes in disease, and how it responds to medication. Genetic brain maps can reveal genetic influences on brain structure, shedding light on the nature-nurture debate, and the mechanisms underlying inherited neurobehavioral disorders. Recently, we created time-lapse movies of brain structure for a variety of diseases. These identify complex, shifting patterns of brain structural deficits, revealing where, and at what rate, the path of brain deterioration in illness deviates from normal. Statistical criteria can then identify situations in which these changes are abnormally accelerated, or when medication or other interventions slow them. In this paper, we focus on describing our approaches to map structural changes in the cortex. These methods have already been used to reveal the profile of brain anomalies in studies of dementia, epilepsy, depression, childhoodand adult-onset schizophrenia, bipolar disorder, attention-deficit/ hyperactivity disorder, fetal alcohol syndrome, Tourette syndrome, Williams syndrome, and in methamphetamine abusers. Specifically, we describe an image analysis pipeline known as cortical pattern matching that helps compare and pool cortical data over time and across subjects. Statistics are then defined to identify brain structural differences between groups, including localized alterations in cortical thickness, gray matter density (GMD), and asymmetries in cortical organization. Subtle features, not seen in individual brain scans, often emerge when population-based brain data are averaged in this way. Illustrative examples are presented to show the profound effects of development and various diseases on the human cortex. Dynamically spreading waves of gray matter loss are tracked in dementia and schizophrenia, and these sequences are related to normally occurring changes in healthy subjects of various ages. D 2004 Published by Elsevier Inc.

show abstract

“…Aiming to detect substructural changes within the hippocampus, our research group reported a technique for unfolding of the hippocampal gray matter sheet with subsequent alignment of the hippocampal subfields. 62 Another research group delineated the hippocampal subfields on T2-weighted MRI data obtained at 4 T on three hippocampal slices and studied the effects of aging on the derived partial subfield volumes. 63 Ultimately, the best approach to delineate hippocampal subfields in vivo may require higher-field MRI-at field strengths as high as 7 T-in which the layers of the entorhinal cortex can be visualized.…”

Section: Brain Mapping In Neurodegenerative Dementiasmentioning

confidence: 99%

Brain Mapping as a Tool to Study Neurodegeneration

Apostolova

Thompson

2007

Neurotherapeutics

Self Cite

View full text Add to dashboard Cite

Summary: Alzheimer's disease (AD) is the most common neurodegenerative disorder for those 65 years or older; it currently affects 4.5 million in the United States and is predicted to rise to 13.2 million by the year 2050. Neuroimaging and brain mapping techniques offer extraordinary power to understand AD, providing spatially detailed information on the extent and trajectory of the disease as it spreads in the living brain. Computational anatomy techniques, applied to large databases of brain MRI scans, reveal the dynamic sequence of cortical and hippocampal changes with disease progression and how these relate to cognitive decline and future clinical outcomes. People who are mildly cognitively impaired, in particular, are at a fivefold increased risk of imminent conversion to dementia, and they show specific structural brain changes that are predictive of imminent disease onset. We review the principles and key findings of several new methods for assessing brain degeneration, including voxel-based morphometry, tensor-based morphometry, cortical thickness mapping, hippocampal atrophy mapping, and automated methods for mapping ventricular anatomy. Applications to AD and other dementias are discussed, with a brief review of related findings in other neurological and neuropsychiatric illnesses, including epilepsy, HIV/AIDS, schizophrenia, and disorders of brain development.

show abstract

Dynamics of the Hippocampus During Encoding and Retrieval of Face-Name Pairs

Cited by 458 publications

References 28 publications

Abnormalities of hippocampal surface structure in very mild dementia of the Alzheimer type

Abnormalities of hippocampal surface structure in very mild dementia of the Alzheimer type

Mapping cortical change in Alzheimer's disease, brain development, and schizophrenia

Brain Mapping as a Tool to Study Neurodegeneration

Contact Info

Product

Resources

About