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Dimsdale-Zucker HR, Montchal ME, Reagh ZM, Wang SF, Libby LA, Ranganath C. Representations of Complex Contexts: A Role for Hippocampus. J Cogn Neurosci 2023; 35:90-110. [PMID: 36166300 PMCID: PMC9832373 DOI: 10.1162/jocn_a_01919] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
Abstract
The hippocampus plays a critical role in supporting episodic memory, in large part by binding together experiences and items with surrounding contextual information. At present, however, little is known about the roles of different hippocampal subfields in supporting this item-context binding. To address this question, we constructed a task in which items were affiliated with differing types of context-cognitive associations that vary at the local, item level and membership in temporally organized lists that linked items together at a global level. Participants made item recognition judgments while undergoing high-resolution fMRI. We performed voxel pattern similarity analyses to answer the question of how human hippocampal subfields represent retrieved information about cognitive states and the time at which a past event took place. As participants recollected previously presented items, activity patterns in the CA23DG subregion carried information about prior cognitive states associated with these items. We found no evidence to suggest reinstatement of information about temporal context at the level of list membership, but exploratory analyses revealed representations of temporal context at a coarse level in conjunction with representations of cognitive contexts. Results are consistent with characterizations of CA23DG as a critical site for binding together items and contexts in the service of memory retrieval.
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Mızrak E, Bouffard NR, Libby LA, Boorman ED, Ranganath C. The hippocampus and orbitofrontal cortex jointly represent task structure during memory-guided decision making. Cell Rep 2021; 37:110065. [PMID: 34852232 PMCID: PMC8686644 DOI: 10.1016/j.celrep.2021.110065] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2019] [Revised: 07/23/2021] [Accepted: 11/05/2021] [Indexed: 11/28/2022] Open
Abstract
The hippocampus, well known for its role in episodic memory, might also be an important brain region for extracting structure from our experiences in order to guide future decisions. Recent evidence in rodents suggests that the hippocampus supports decision making by representing task structure in cooperation with the orbitofrontal cortex (OFC). Here, we examine how the human hippocampus and OFC represent task structure during an associative learning task that required learning of both context-determined and context-invariant probabilistic associations. We find that after learning, hippocampal and lateral OFC representations differentiated between context-determined and context-invariant task structures. The degree of this differentiation within the hippocampus and lateral OFC is highly correlated. These results advance our understanding of the hippocampus and suggest that the hippocampus and OFC support goal-directed behavior by representing information that guides the selection of appropriate decision strategies. Mizrak et al. use fMRI to demonstrate that hippocampus and orbitofrontal cortex generalize across decisions that share the same task sub-structure compared with different task sub-structures. Results show that the hippocampus, in coordination with OFC, supports decision making by extracting structure from past experiences.
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Affiliation(s)
- Eda Mızrak
- Center for Neuroscience, University of California, Davis, Davis, CA 95618, USA; Department of Psychology, University of Zürich, Zürich 8006, Switzerland.
| | - Nichole R Bouffard
- Department of Psychology, University of Toronto, Toronto, ON M5S 3G3, Canada
| | - Laura A Libby
- Center for Neuroscience, University of California, Davis, Davis, CA 95618, USA
| | - Erie D Boorman
- Center for Neuroscience, University of California, Davis, Davis, CA 95618, USA; Department of Psychology, University of California, Davis, Davis, CA 95618, USA; Center for Mind and Brain, University of California, Davis, Davis, CA 95618, USA
| | - Charan Ranganath
- Center for Neuroscience, University of California, Davis, Davis, CA 95618, USA; Department of Psychology, University of California, Davis, Davis, CA 95618, USA.
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Abstract
The development and application of concepts is a critical component of cognition. Although concepts can be formed on the basis of simple perceptual or semantic features, conceptual representations can also capitalize on similarities across feature relationships. By representing these types of higher-order relationships, concepts can simplify the learning problem and facilitate decisions. Despite this, little is known about the neural mechanisms that support the construction and deployment of these kinds of higher-order concepts during learning. To address this question, we combined a carefully designed associative learning task with computational model-based functional magnetic resonance imaging (fMRI). Participants were scanned as they learned and made decisions about sixteen pairs of cues and associated outcomes. Associations were structured such that individual cues shared feature relationships, operationalized as shared patterns of cue pair-outcome associations. In order to capture the large number of possible conceptual representational structures that participants might employ and to evaluate how conceptual representations are used during learning, we leveraged a well-specified Bayesian computational model of category learning [1]. Behavioral and model-based results revealed that participants who displayed a tendency to link experiences in memory benefitted from faster learning rates, suggesting that the use of the conceptual structure in the task facilitated decisions about cue pair-outcome associations. Model-based fMRI analyses revealed that trial-by-trial integration of cue information into higher-order conceptual representations was supported by an anterior temporal (AT) network of regions previously implicated in representing complex conjunctions of features and meaning-based information.
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Affiliation(s)
- Marika C. Inhoff
- Department of Psychology, University of California at Davis, Davis, CA, United States of America
| | - Laura A. Libby
- Center for Neuroscience, University of California at Davis, Davis, CA, United States of America
| | - Takao Noguchi
- Department of Experimental Psychology, University College London, London, United Kingdom
| | - Bradley C. Love
- Department of Experimental Psychology, University College London, London, United Kingdom
- Alan Turing Institute, Kings Cross, London, United Kingdom
| | - Charan Ranganath
- Department of Psychology, University of California at Davis, Davis, CA, United States of America
- Center for Neuroscience, University of California at Davis, Davis, CA, United States of America
- * E-mail:
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Roberts BM, Libby LA, Inhoff MC, Ranganath C. Brain activity related to working memory for temporal order and object information. Behav Brain Res 2018; 354:55-63. [DOI: 10.1016/j.bbr.2017.05.068] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2017] [Accepted: 05/31/2017] [Indexed: 11/28/2022]
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Libby LA, Reagh ZM, Bouffard NR, Ragland JD, Ranganath C. The Hippocampus Generalizes across Memories that Share Item and Context Information. J Cogn Neurosci 2018; 31:24-35. [PMID: 30240315 DOI: 10.1162/jocn_a_01345] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
Episodic memory is known to rely on the hippocampus, but how the hippocampus organizes different episodes to permit their subsequent retrieval remains controversial. One major area of debate hinges on a discrepancy between two hypothesized roles of the hippocampus: differentiating between similar events to reduce interference and assigning similar representations to events that share overlapping items and contextual information. Here, we used multivariate analyses of activity patterns measured with fMRI to characterize how the hippocampus distinguishes between memories based on similarity at the level of items and/or context. Hippocampal activity patterns discriminated between events that shared either item or context information but generalized across events that shared similar item-context associations. The current findings provide evidence that, whereas the hippocampus can reduce mnemonic interference by separating events that generalize along a single attribute dimension, overlapping hippocampal codes may support memory for events with overlapping item-context relations. This lends new insights into the way the hippocampus may balance multiple mnemonic operations in adaptively guiding behavior.
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Wang SF, Ritchey M, Libby LA, Ranganath C. Functional connectivity based parcellation of the human medial temporal lobe. Neurobiol Learn Mem 2016; 134 Pt A:123-134. [PMID: 26805590 DOI: 10.1016/j.nlm.2016.01.005] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2015] [Revised: 12/23/2015] [Accepted: 01/12/2016] [Indexed: 10/22/2022]
Abstract
Regional differences in large-scale connectivity have been proposed to underlie functional specialization along the anterior-posterior axis of the medial temporal lobe (MTL), including the hippocampus (HC) and the parahippocampal gyrus (PHG). However, it is unknown whether functional connectivity (FC) can be used reliably to parcellate the human MTL. The current study aimed to differentiate subregions of the HC and the PHG based on patterns of whole-brain intrinsic FC. FC maps were calculated for each slice along the longitudinal axis of the PHG and the HC. A hierarchical clustering algorithm was then applied to these data in order to group slices according to the similarity of their connectivity patterns. Surprisingly, three discrete clusters were identified in the PHG. Two clusters corresponded to the parahippocampal cortex (PHC) and the perirhinal cortex (PRC), and these regions showed preferential connectivity with previously described posterior-medial and anterior-temporal networks, respectively. The third cluster corresponded to an anterior PRC region previously described as area 36d, and this region exhibited preferential connectivity with auditory cortical areas and with a network involved in visceral processing. The three PHG clusters showed different profiles of activation during a memory-encoding task, demonstrating that the FC-based parcellation identified functionally dissociable sub-regions of the PHG. In the hippocampus, no sub-regions were identified via the parcellation procedure. These results indicate that connectivity-based methods can be used to parcellate functional regions within the MTL, and they suggest that studies of memory and high-level cognition need to differentiate between PHC, posterior PRC, and anterior PRC.
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Affiliation(s)
- Shao-Fang Wang
- Center for Neuroscience, University of California, Davis, CA 95618, USA.
| | - Maureen Ritchey
- Center for Neuroscience, University of California, Davis, CA 95618, USA
| | - Laura A Libby
- Center for Neuroscience, University of California, Davis, CA 95618, USA
| | - Charan Ranganath
- Center for Neuroscience, University of California, Davis, CA 95618, USA; Department of Psychology, University of California, Davis, CA 95616, USA
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7
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Cook PF, Reichmuth C, Rouse AA, Libby LA, Dennison SE, Carmichael OT, Kruse-Elliott KT, Bloom J, Singh B, Fravel VA, Barbosa L, Stuppino JJ, Van Bonn WG, Gulland FMD, Ranganath C. Algal toxin impairs sea lion memory and hippocampal connectivity, with implications for strandings. Science 2015; 350:1545-7. [PMID: 26668068 DOI: 10.1126/science.aac5675] [Citation(s) in RCA: 55] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2015] [Accepted: 11/09/2015] [Indexed: 01/07/2023]
Abstract
Domoic acid (DA) is a naturally occurring neurotoxin known to harm marine animals. DA-producing algal blooms are increasing in size and frequency. Although chronic exposure is known to produce brain lesions, the influence of DA toxicosis on behavior in wild animals is unknown. We showed, in a large sample of wild sea lions, that spatial memory deficits are predicted by the extent of right dorsal hippocampal lesions related to natural exposure to DA and that exposure also disrupts hippocampal-thalamic brain networks. Because sea lions are dynamic foragers that rely on flexible navigation, impaired spatial memory may affect survival in the wild.
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Affiliation(s)
- Peter F Cook
- Center for Neuropolicy, Emory University, Atlanta, GA 30322, USA. Pinniped Cognition and Sensory Systems Laboratory, Institute of Marine Sciences, University of California-Santa Cruz, Santa Cruz, CA 95060, USA.
| | - Colleen Reichmuth
- Pinniped Cognition and Sensory Systems Laboratory, Institute of Marine Sciences, University of California-Santa Cruz, Santa Cruz, CA 95060, USA
| | - Andrew A Rouse
- Pinniped Cognition and Sensory Systems Laboratory, Institute of Marine Sciences, University of California-Santa Cruz, Santa Cruz, CA 95060, USA
| | - Laura A Libby
- Dynamic Memory Lab, Center for Neuroscience, University of California-Davis, Davis, CA 95618, USA
| | | | | | | | - Josh Bloom
- AnimalScan Advanced Veterinary Imaging, Redwood City, CA 94063, USA
| | - Baljeet Singh
- Dynamic Memory Lab, Center for Neuroscience, University of California-Davis, Davis, CA 95618, USA
| | | | | | - Jim J Stuppino
- AnimalScan Advanced Veterinary Imaging, Redwood City, CA 94063, USA
| | | | | | - Charan Ranganath
- Dynamic Memory Lab, Center for Neuroscience, University of California-Davis, Davis, CA 95618, USA
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Abstract
The entorhinal cortex (EC) is the primary site of interactions between the neocortex and hippocampus. Studies in rodents and nonhuman primates suggest that EC can be divided into subregions that connect differentially with perirhinal cortex (PRC) vs parahippocampal cortex (PHC) and with hippocampal subfields along the proximo-distal axis. Here, we used high-resolution functional magnetic resonance imaging at 7 Tesla to identify functional subdivisions of the human EC. In two independent datasets, PRC showed preferential intrinsic functional connectivity with anterior-lateral EC and PHC with posterior-medial EC. These EC subregions, in turn, exhibited differential connectivity with proximal and distal subiculum. In contrast, connectivity of PRC and PHC with subiculum followed not only a proximal-distal but also an anterior-posterior gradient. Our data provide the first evidence that the human EC can be divided into functional subdivisions whose functional connectivity closely parallels the known anatomical connectivity patterns of the rodent and nonhuman primate EC.
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Affiliation(s)
- Anne Maass
- Institute of Cognitive Neurology and Dementia Research, Otto-von-Guericke University Magdeburg, Magdeburg, Germany
| | - David Berron
- Institute of Cognitive Neurology and Dementia Research, Otto-von-Guericke University Magdeburg, Magdeburg, Germany
| | - Laura A Libby
- Center for Neuroscience, University of California at Davis, Davis, United States
| | - Charan Ranganath
- Department of Psychology, University of California at Davis, Davis, United States
| | - Emrah Düzel
- German Center for Neurodegenerative Diseases, Magdeburg, Germany
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Yushkevich PA, Amaral RSC, Augustinack JC, Bender AR, Bernstein JD, Boccardi M, Bocchetta M, Burggren AC, Carr VA, Chakravarty MM, Chételat G, Daugherty AM, Davachi L, Ding SL, Ekstrom A, Geerlings MI, Hassan A, Huang Y, Iglesias JE, La Joie R, Kerchner GA, LaRocque KF, Libby LA, Malykhin N, Mueller SG, Olsen RK, Palombo DJ, Parekh MB, Pluta JB, Preston AR, Pruessner JC, Ranganath C, Raz N, Schlichting ML, Schoemaker D, Singh S, Stark CEL, Suthana N, Tompary A, Turowski MM, Van Leemput K, Wagner AD, Wang L, Winterburn JL, Wisse LEM, Yassa MA, Zeineh MM. Quantitative comparison of 21 protocols for labeling hippocampal subfields and parahippocampal subregions in in vivo MRI: towards a harmonized segmentation protocol. Neuroimage 2015; 111:526-41. [PMID: 25596463 PMCID: PMC4387011 DOI: 10.1016/j.neuroimage.2015.01.004] [Citation(s) in RCA: 226] [Impact Index Per Article: 25.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2014] [Revised: 11/25/2014] [Accepted: 01/01/2015] [Indexed: 11/16/2022] Open
Abstract
OBJECTIVE An increasing number of human in vivo magnetic resonance imaging (MRI) studies have focused on examining the structure and function of the subfields of the hippocampal formation (the dentate gyrus, CA fields 1-3, and the subiculum) and subregions of the parahippocampal gyrus (entorhinal, perirhinal, and parahippocampal cortices). The ability to interpret the results of such studies and to relate them to each other would be improved if a common standard existed for labeling hippocampal subfields and parahippocampal subregions. Currently, research groups label different subsets of structures and use different rules, landmarks, and cues to define their anatomical extents. This paper characterizes, both qualitatively and quantitatively, the variability in the existing manual segmentation protocols for labeling hippocampal and parahippocampal substructures in MRI, with the goal of guiding subsequent work on developing a harmonized substructure segmentation protocol. METHOD MRI scans of a single healthy adult human subject were acquired both at 3 T and 7 T. Representatives from 21 research groups applied their respective manual segmentation protocols to the MRI modalities of their choice. The resulting set of 21 segmentations was analyzed in a common anatomical space to quantify similarity and identify areas of agreement. RESULTS The differences between the 21 protocols include the region within which segmentation is performed, the set of anatomical labels used, and the extents of specific anatomical labels. The greatest overall disagreement among the protocols is at the CA1/subiculum boundary, and disagreement across all structures is greatest in the anterior portion of the hippocampal formation relative to the body and tail. CONCLUSIONS The combined examination of the 21 protocols in the same dataset suggests possible strategies towards developing a harmonized subfield segmentation protocol and facilitates comparison between published studies.
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Affiliation(s)
- Paul A Yushkevich
- Penn Image Computing and Science Laboratory, Department of Radiology, University of Pennsylvania, USA.
| | - Robert S C Amaral
- Cerebral Imaging Centre, Douglas Mental Health University Institute, McGill University, Canada
| | - Jean C Augustinack
- A.A. Martinos Center for Biomedical Imaging, Department of Radiology, Harvard Medical School, Massachusetts General Hospital, USA
| | | | - Jeffrey D Bernstein
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, USA; Stanford Center for Memory Disorders, USA
| | - Marina Boccardi
- LENITEM (Laboratory of Epidemiology, Neuroimaging and Telemedicine), IRCCS Centro S. Giovanni di Dio Fatebenefratelli, Italy
| | - Martina Bocchetta
- LENITEM (Laboratory of Epidemiology, Neuroimaging and Telemedicine), IRCCS Centro S. Giovanni di Dio Fatebenefratelli, Italy; Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy
| | - Alison C Burggren
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, USA
| | | | - M Mallar Chakravarty
- Cerebral Imaging Centre, Douglas Mental Health University Institute, McGill University, Canada; Department of Psychiatry, Department of Biomedical Engineering, McGill University, Canada
| | - Gaël Chételat
- INSERM U1077, Universitè de Caen Basse-Normandie, UMR-S1077, Ecole Pratique des Hautes Etudes, CHU de Caen, U1077, Caen, France
| | - Ana M Daugherty
- Institute of Gerontology, Wayne State University, USA; Psychology Department, Wayne State University, USA
| | - Lila Davachi
- Department of Psychology, New York University, USA; Center for Neural Science, New York University, USA
| | | | - Arne Ekstrom
- Center for Neuroscience, University of California, Davis, USA; Department of Psychology, University of California, Davis, USA
| | - Mirjam I Geerlings
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Netherlands
| | - Abdul Hassan
- Center for Neuroscience, University of California, Davis, USA
| | - Yushan Huang
- Department of Biomedical Engineering, University of Alberta, Edmonton, Alberta, Canada
| | - J Eugenio Iglesias
- A.A. Martinos Center for Biomedical Imaging, Department of Radiology, Harvard Medical School, Massachusetts General Hospital, USA; Basque Center on Cognition, Brain and Language (BCBL), Donostia-San Sebastian, Spain
| | - Renaud La Joie
- INSERM U1077, Universitè de Caen Basse-Normandie, UMR-S1077, Ecole Pratique des Hautes Etudes, CHU de Caen, U1077, Caen, France
| | - Geoffrey A Kerchner
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, USA; Stanford Center for Memory Disorders, USA
| | | | - Laura A Libby
- Center for Neuroscience, University of California, Davis, USA
| | - Nikolai Malykhin
- Department of Biomedical Engineering, University of Alberta, Edmonton, Alberta, Canada; Centre for Neuroscience, University of Alberta, Edmonton, Alberta, Canada
| | - Susanne G Mueller
- Department of Radiology, University of California, San Francisco, USA; Center for Imaging of Neurodegenerative Diseases, San Francisco VA Medical Center, USA
| | | | | | | | - John B Pluta
- Penn Image Computing and Science Laboratory, Department of Radiology, University of Pennsylvania, USA; Department of Biostatistics, University of Pennsylvania, USA
| | - Alison R Preston
- Department of Psychology, The University of Texas at Austin, USA; Center for Learning and Memory, The University of Texas at Austin, USA; Department of Neuroscience, The University of Texas at Austin, USA
| | - Jens C Pruessner
- McGill Centre for Studies in Aging, Faculty of Medicine, McGill University, Canada; Department of Psychology, McGill University, Canada
| | - Charan Ranganath
- Department of Psychology, University of California, Davis, USA; Center for Neuroscience, University of California, Davis, USA
| | - Naftali Raz
- Institute of Gerontology, Wayne State University, USA; Psychology Department, Wayne State University, USA
| | - Margaret L Schlichting
- Department of Psychology, The University of Texas at Austin, USA; Center for Learning and Memory, The University of Texas at Austin, USA
| | - Dorothee Schoemaker
- McGill Centre for Studies in Aging, Faculty of Medicine, McGill University, Canada; Department of Psychology, McGill University, Canada
| | - Sachi Singh
- Department of Psychiatry and Behavioral Sciences, Northwestern University Feinberg School of Medicine, USA
| | - Craig E L Stark
- Department of Neurobiology and Behavior, University of California, Irvine, USA
| | - Nanthia Suthana
- Department of Neurosurgery, University of California, Los Angeles, USA
| | | | - Marta M Turowski
- Department of Psychiatry and Behavioral Sciences, Northwestern University Feinberg School of Medicine, USA
| | - Koen Van Leemput
- A.A. Martinos Center for Biomedical Imaging, Department of Radiology, Harvard Medical School, Massachusetts General Hospital, USA; Department of Applied Mathematics and Computer Science, Technical University of Denmark, Denmark
| | - Anthony D Wagner
- Department of Psychology, Stanford University, USA; Neurosciences Program, Stanford University, USA
| | - Lei Wang
- Department of Psychiatry and Behavioral Sciences, Northwestern University Feinberg School of Medicine, USA; Department of Radiology, Northwestern University Feinberg School of Medicine, USA
| | - Julie L Winterburn
- Cerebral Imaging Centre, Douglas Mental Health University Institute, McGill University, Canada
| | - Laura E M Wisse
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Netherlands
| | - Michael A Yassa
- Department of Neurobiology and Behavior, University of California, Irvine, USA
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Libby LA, Yonelinas AP, Ranganath C, Ragland JD. Recollection and familiarity in schizophrenia: a quantitative review. Biol Psychiatry 2013; 73:944-50. [PMID: 23245761 PMCID: PMC3609900 DOI: 10.1016/j.biopsych.2012.10.027] [Citation(s) in RCA: 49] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/31/2012] [Revised: 10/26/2012] [Accepted: 10/31/2012] [Indexed: 11/27/2022]
Abstract
Recognition memory judgments can be based on recollection of qualitative information about an earlier study event or on assessments of stimulus familiarity. Schizophrenia is associated with pronounced deficits in overall recognition memory, and these deficits are highly predictive of global functioning. However, the extent to which these deficits reflect impairments in recollection or familiarity is less well understood. In the current article, we reviewed studies that used remember-know-new, process dissociation, and receiver operating characteristic procedures to investigate recollection and familiarity in schizophrenia. We also performed a quantitative reanalysis of these study results to obtain recollection and familiarity estimates that account for methodological differences between studies. Contrary to previous conclusions that recollection is selectively impaired in schizophrenia, we found evidence for both familiarity and recollection deficits across studies, suggesting multi-focal medial temporal lobe and/or prefrontal cortex dysfunction. The familiarity deficits were more variable with frequent small-to-medium rather than medium-to-large effect sizes, suggesting that familiarity could be potentially used as a compensatory ability, whereas recollection is conceptualized as a therapeutic target for new treatment development.
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Affiliation(s)
- Laura A. Libby
- Department of Psychology, University of California at Davis, Davis, CA
| | | | - Charan Ranganath
- Department of Psychology, University of California at Davis, Davis, CA
| | - John D. Ragland
- Department of Psychiatry and Behavioral Sciences, University of California at Davis, Sacramento, CA
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Coleman PJ, Brashear KM, Hunt CA, Hoffman WF, Hutchinson JH, Breslin MJ, McVean CA, Askew BC, Hartman GD, Rodan SB, Rodan GA, Leu CT, Prueksaritanont T, Fernandez-Metzler C, Ma B, Libby LA, Merkle KM, Stump GL, Wallace AA, Lynch JJ, Lynch R, Duggan ME. Non-peptide alpha(v)beta(3) antagonists. Part 3: identification of potent RGD mimetics incorporating novel beta-amino acids as aspartic acid replacements. Bioorg Med Chem Lett 2002; 12:31-4. [PMID: 11738567 DOI: 10.1016/s0960-894x(01)00666-7] [Citation(s) in RCA: 17] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Potent non-peptidic alpha(v)beta(3) antagonists have been prepared incorporating various beta-amino acids as aspartic acid mimetics. Modification of the beta-alanine 3-substituents alters the potency and physicochemical properties of these receptor antagonists and in some cases provides orally bioavailable alpha(v)beta(3) inhibitors.
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Affiliation(s)
- Paul J Coleman
- Department of Medicinal Chemistry, Merck Research Laboratories, West Point, PA 19486, USA.
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Egbertson MS, Cook JJ, Bednar B, Prugh JD, Bednar RA, Gaul SL, Gould RJ, Hartman GD, Homnick CF, Holahan MA, Libby LA, Lynch JJ, Lynch RJ, Sitko GR, Stranieri MT, Laura M. Vasallo. Non-Peptide GPIIb/IIIa Inhibitors. 20. Centrally Constrained Thienothiophene α-Sulfonamides Are Potent, Long Acting in Vivo Inhibitors of Platelet Aggregation. J Med Chem 1999. [DOI: 10.1021/jm990405y] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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Egbertson MS, Cook JJ, Bednar B, Prugh JD, Bednar RA, Gaul SL, Gould RJ, Hartman GD, Homnick CF, Holahan MA, Libby LA, Lynch JJ, Lynch RJ, Sitko GR, Stranieri MT, Vassallo LM. Non-peptide GPIIb/IIIa inhibitors. 20. Centrally constrained thienothiophene alpha-sulfonamides are potent, long acting in vivo inhibitors of platelet aggregation. J Med Chem 1999; 42:2409-21. [PMID: 10395482 DOI: 10.1021/jm980722p] [Citation(s) in RCA: 43] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
The synthesis and pharmacology of 4, a potent thienothiophene non-peptide fibrinogen receptor antagonist, are reported. Compound 4 inhibited the aggregation of human gel-filtered platelets with an IC50 of 8 nM and demonstrated an 8-fold improvement in affinity for isolated GPIIb/IIIa receptors over analogues possessing an isoindolinone backbone. Flow cytometry studies revealed that the binding of 4 to resting platelets is a diffusion-controlled process (kon = 3.3 x 10(6) M-1 s-1) and that 4 binds to dog and human platelets with comparable affinity (Kd = 0.04 and 0.07 nM, respectively). Ex vivo platelet aggregation in dogs was completely inhibited by an iv dose of 5 microg/kg [corrected], and an oral dose of 50-90 microg/kg [corrected] followed by low daily doses of 10 microg/kg [corrected] was sufficient to maintain approximately 80% inhibition of ex vivo platelet aggregation over several days. Inhibition of ADP-induced platelet aggregation in anesthetized dogs at 77 +/- 7% resulted in a moderate 2.5-fold increase in bleeding time, while complete inhibition (100%) resulted in an approximately 10-min bleeding time. Additional doses were required to increase the bleeding time to the maximum time allowed in the protocol (15 min), thus indicating a potentially useful and safe separation of efficacy and bleeding time.
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Affiliation(s)
- M S Egbertson
- Departments of Medicinal Chemistry and Pharmacology, Merck Research Laboratories, West Point, Pennsylvania 19486, USA
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