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27 Assessing Differences in Academic Achievement Among a National Sample of Children with Epilepsy Before and During the COVID-19 Pandemic
- Brandon Almy, Lauren Scimeca, David Marshall, Brittany L. Nordhaus, Erin Fedak Romanowski, Nancy McNamara, Elise Hodges, Madison M. Berl, Alyssa Ailion, Donald J. Bearden, Katrina Boyer, Crystal M. Cooper, Amanda M. Decrow, Priscilla H. Duong, Patricia Espe-Pfeifer, Marsha Gabriel, Jennifer I. Koop, Kelly A. McNally, Andrew Molnar, Emily Olsen, Kim E. Ono, Kristina E. Patrick, Brianna Paul, Jonathan Romain, Leigh N. Sepeta, Rebecca L.H. Stilp, Greta N. Wilkening, Mike Zaccariello, Frank Zelko
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- Journal:
- Journal of the International Neuropsychological Society / Volume 29 / Issue s1 / November 2023
- Published online by Cambridge University Press:
- 21 December 2023, pp. 28-29
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Objective:
The COVID-19 pandemic significantly disrupted schools and learning formats. Children with epilepsy are at-risk for generalized academic difficulties. We investigated the potential impact of COVID-19 on learning in those with epilepsy by comparing achievement on well-established academic measures among school-age children with epilepsy referred prior to the COVID-19 pandemic and those referred during the COVID-19 pandemic.
Participants and Methods:This study included 466 children [52% male, predominately White (76%), MAge=10.75 years] enrolled in the Pediatric Epilepsy Research Consortium Epilepsy (PERC) Surgery database project who were referred for surgery and seen for neuropsychological testing. Patients were divided into two groups based on a proxy measure of pandemic timing completed by PERC research staff at each site (i.e., “were there any changes to typical in-person administration [of the evaluation] due to COVID?”). 31% of the sample (N = 144) were identified as having testing during the pandemic (i.e., “yes” response), while 69% were identified as having testing done pre-pandemic (i.e., “no” response). Of the 31% who answered yes, 99% of administration changes pertained to in-person testing or other changes, with 1% indicating remote testing. Academic achievement was assessed by performance measures (i.e., word reading, reading comprehension, spelling, math calculations, and math word problems) across several different tests. T-tests compared the two groups on each academic domain. Subsequent analyses examined potential differences in academic achievement among age cohorts that approximately matched grade level [i.e., grade school (ages 5-10), middle school (ages 11-14), and high school (ages 15-18)].
Results:No significant differences were found between children who underwent an evaluation before the pandemic compared to those assessed during the pandemic based on age norms across academic achievement subtests (all p’s > .34). Similarly, there were no significant differences among age cohorts. The average performance for each age cohort generally fell in the low average range across academic skills. Performance inconsistently varied between age cohorts. The youngest cohort (ages 5-10) scored lower than the other cohorts for sight-word reading, whereas this cohort scored higher than the middle cohort (ages 11-14) for math word problems and reading comprehension. There were no significant differences between the two pandemic groups on demographic variables, intellectual functioning, or epilepsy variables (i.e., age of onset, number of seizure medications, seizure frequency).
Conclusions:Academic functioning was generally equivalent between children with epilepsy who underwent academic testing as part of a pre-surgical evaluation prior to the pandemic compared to those who received testing during the pandemic. Additionally, academic functioning did not significantly differ between age cohorts. Children with epilepsy may have entered the pandemic with effective academic supports and/or were accustomed to school disruptions given their seizure history. Replication is needed as findings are based on a proxy measure of pandemic timing and the extent to which children experienced in-person, remote, and hybrid learning is unknown. Children tested a year into the pandemic, after receiving instruction through varying educational methods, may score differently than those tested earlier. Future research can address these gaps. Although it is encouraging that academic functioning was not disproportionately impacted during the pandemic in this sample, children with epilepsy are at-risk for generalized academic difficulties and continued monitoring of academic functioning is necessary.
3 Latent Wechsler Profiles in Presurgical Pediatric Epilepsy
- Madison M Berl, Erin T Kaseda, Jennifer I Koop, Brandon Almy, Alyssa Ailion, Donald J Bearden, Katrina Boyer, Crystal M Cooper, Amanda M DeCrow, Priscilla H Duong, Patricia Espe-Pfeifer, Marsha Gabriel, Elise Hodges, David Marshall, Kelly A McNally, Andrew Molnar, Emily Olsen, Kim E Ono, Kristina E Patrick, Brianna Paul, Jonathan Romain, Leigh N Sepeta, Rebecca LH Stilp, Greta Wilkening, Michael Zaccariello, Frank Zelko, PERC Epilepsy Surgery Database Project
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- Journal:
- Journal of the International Neuropsychological Society / Volume 29 / Issue s1 / November 2023
- Published online by Cambridge University Press:
- 21 December 2023, pp. 308-310
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Objective:
The Pediatric Epilepsy Research Consortium (PERC) Epilepsy Surgery Database Project is a multisite collaborative that includes neuropsychological evaluations of children presenting for epilepsy surgery. There is some evidence for specific neuropsychological phenotypes within epilepsy (Hermann et al, 2016); however, this is less clear in pediatric patients. As a first step, we applied an empirically-based subtyping approach to determine if there were specific profiles using indices from the Wechsler scales [Verbal IQ (VIQ), Nonverbal IQ (NVIQ), Processing Speed Index (PSI), Working Memory Index (WMI)]. We hypothesized that there would be at least four profiles that are distinguished by slow processing speed and poor working memory as well as profiles with significant differences between verbal and nonverbal reasoning abilities.
Participants and Methods:Our study included 372 children (M=12.1 years SD=4.1; 77.4% White; 48% male) who completed an age-appropriate Wechsler measure, enough to render at least two index scores. Epilepsy characteristics included 84.4% with focal epilepsy (evenly distributed between left and right focus) and 13.5% with generalized or mixed seizure types; mean age of onset = 6.7 years, SD = 4.5; seizure frequency ranged from daily to less than monthly; 53% had structural etiology; 71% had an abnormal MRI; and mean number of antiseizure medications was two. Latent profile analysis was used to identify discrete underlying cognitive profiles based on intellectual functioning. Demographic and epilepsy characteristics were compared among profiles.
Results:Based on class enumeration procedures, a 3-cluster solution provided the best fit for the data, with profiles characterized by generally Average, Low Average, or Below Average functioning. 32.8% were in the Average profile with mean index scores ranging from 91.7-103.2; 47.6% were in the Low Average profile with mean index ranging from 80.7 to 84.5; and 19.6% were in the Below Average profile with mean index scores ranging from 55.0-63.1. Across all profiles, the lowest mean score was the PSI, followed by WMI. VIQ and NVIQ represented relatively higher scores for all three profiles. Mean discrepancy between indices within a profile was as large as 11.5 IQ points. No demographics or epilepsy characteristics were significantly different across cognitive phenotypes.
Conclusions:Latent cognitive phenotypes in a pediatric presurgical cohort were differentiated by general level of functioning; however, across profiles, processing speed was consistently the lowest index followed by working memory. These findings across phenotypes suggest a common relative weakness which may result from a global effect of antiseizure medications and/or the widespread impact of seizures on neural networks even in a largely focal epilepsy cohort; similar to adult studies with temporal lobe epilepsy (Hermann et al, 2007). Future work will use latent profile analysis to examine phenotypes across other domains relevant to pediatric epilepsy including attention, naming, motor, and memory functioning. These findings are in line with collaborative efforts towards cognitive phenotyping which is the aim of our PERC Epilepsy Surgery Database Project that has already established one of the largest pediatric epilepsy surgery cohorts.
26 The Importance of Executive Functioning for Academic Achievement Among a National Sample of Children with Epilepsy
- Brandon Almy, David Marshall, Brittany L. Nordhaus, Erin Fedak Romanowski, Nancy McNamara, Elise Hodges, Madison M. Berl, Alyssa Ailion, Donald J. Bearden, Katrina Boyer, Crystal M. Cooper, Amanda M. Decrow, Priscilla H. Duong, Patricia Espe-Pfeifer, Marsha Gabriel, Jennifer I. Koop, Kelly A. McNally, Andrew Molnar, Emily Olsen, Kim E. Ono, Kristina E. Patrick, Brianna Paul, Jonathan Romain, Leigh N. Sepeta, Rebecca L.H. Stilp, Greta N. Wilkening, Mike Zaccariello, Frank Zelko
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- Journal:
- Journal of the International Neuropsychological Society / Volume 29 / Issue s1 / November 2023
- Published online by Cambridge University Press:
- 21 December 2023, pp. 26-27
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Objective:
Children with epilepsy are at greater risk of lower academic achievement than their typically developing peers (Reilly and Neville, 2015). Demographic, social, and neuropsychological factors, such as executive functioning (EF), mediate this relation. While research emphasizes the importance of EF skills for academic achievement among typically developing children (e.g., Best et al., 2011; Spiegel et al., 2021) less is known among children with epilepsy (Ng et al., 2020). The purpose of this study is to examine the influence of EF skills on academic achievement in a nationwide sample of children with epilepsy.
Participants and Methods:Participants included 427 children with epilepsy (52% male; MAge= 10.71), enrolled in the Pediatric Epilepsy Research Consortium (PERC) Epilepsy Surgery Database who had been referred for surgery and underwent neuropsychological testing. Academic achievement was assessed by performance measures (word reading, reading comprehension, spelling, and calculation and word-based mathematics) and parent-rating measures (Adaptive Behavior Assessment System (ABAS) Functional Academics and Child Behavior Checklist (CBCL) School Performance). EF was assessed by verbal fluency measures, sequencing, and planning measures from the Delis Kaplan Executive Function System (DKEFS), NEPSY, and Tower of London test. Rating-based measures of EF included the 'Attention Problems’ subscale from the CBCL and 'Cognitive Regulation’ index from the Behavior Rating Inventory of Executive Function (BRIEF-2). Partial correlations assessed associations between EF predictors and academic achievement, controlling for fullscale IQ (FSIQ; A composite across intelligence tests). Significant predictors of each academic skill or rating were entered into a two-step regression that included FSIQ, demographics, and seizure variables (age of onset, current medications) in the first step with EF predictors in the second step.
Results:Although zero-order correlations were significant between EF predictors and academic achievement (.29 < r’s < .63 for performance; -.63 < r’s < -.50 for rating measures), partial correlations controlling for FSIQ showed fewer significant relations. For performance-based EF, only letter fluency (DKEFS Letter Fluency) and cognitive flexibility (DKEFS Trails Condition 4) demonstrated significant associations with performance-based academic achievement (r’s > .29). Regression models for performance-based academic achievement indicated that letter fluency (ß = .22, p = .017) and CBCL attention problems (ß = -.21, p =.002) were significant predictors of sight-word reading. Only letter fluency (ß = .23, p =.006) was significant for math calculation. CBCL Attention Problems were a significant predictor of spelling performance (ß = -.21, p = .009) and reading comprehension (ß = -.18, p =.039). CBCL Attention Problems (ß = -.38, p <.001 for ABAS; ß = -.34, p =.002 for CBCL School) and BRIEF-2 Cognitive Regulation difficulties (ß = -.46, p < .001 for ABAS; ß = -.46, p =.013 for CBCL School) were significant predictors of parent-rated ABAS Functional Academics and CBCL School Performance.
Conclusions:Among a national pediatric epilepsy dataset, performance-based and ratings-based measures of EF predicted performance academic achievement, whereas only ratings-based EF predicted parent-rated academic achievement, due at least in part to shared method variance. These findings suggest that interventions that increase cognitive regulation, reduce symptoms of attention dysfunction, and promote self-generative, flexible thinking, may promote academic achievement among children with epilepsy.
38 Fine Motor Skills in Pediatric Frontal Lobe Epilepsy are Associated with Executive Dysfunction and ADHD Symptomatology
- Moshe Maiman, Madison Berl, Jennifer I Koop, Donald J Bearden, Katrina Boyer, Crystal M Cooper, Amanda M Decrow, Priscilla H. Duong, Patricia Espe-Pfeifer, Marsha Gabriel, Elise Hodges, Kelly A McNally, Andrew Molnar, Emily Olsen, Kim E Ono, Kristina E Patrick, Brianna Paul, Jonathan Romain, Leigh N Sepeta, Rebecca LH Stilp, Greta N Wilkening, Mike Zaccariello, Frank Zelko, Clemente Vega, Trey Moore, Szimonetta Mulati, Phillip Pearl, Jeffrey Bolton, Alyssa Ailion
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- Journal:
- Journal of the International Neuropsychological Society / Volume 29 / Issue s1 / November 2023
- Published online by Cambridge University Press:
- 21 December 2023, pp. 37-38
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Objective:
Pediatric patients with frontal lobe epilepsy (FLE) have higher rates of attention deficit hyperactivity disorder (ADHD), as well as executive functioning (EF) and fine motor (FM) challenges. Relations between these constructs have been established in youth with ADHD and are supported by FM and EF skill involvement in frontal-subcortical systems. Still, they are not well understood in pediatric FLE. We hypothesized that poorer FM performance would be related to greater executive dysfunction and ADHD symptomatology in this group.
Participants and Methods:47 children and adolescents with FLE (AgeM=12.47, SD=5.18; IQM=84.07; SD=17.56; Age of Seizure OnsetM=6.85, SD=4.64; right-handed: n=34; left-handed: n=10; Unclear: n=3) were enrolled in the Pediatric Epilepsy Research Consortium dataset as part of their phase I epilepsy surgical evaluation. Participants were selected if they had unifocal FLE and completed the Lafayette Grooved Pegboard (GP). Seizure lateralization (left-sided: n=19; right-sided: n=26; bilateral: n=2) and localization were established via data (e.g., EEG, MRI) presented at a multidisciplinary team case conference. Patients completed neuropsychological measures of FM, attention, and EF. Parents also completed questionnaires inquiring about their child’s everyday EF and ADHD symptomatology. Correlational analyses were conducted to examine FM, EF, and ADHD relations.
Results:Dominant hand (DH) manual dexterity (GP) was related to parent-reported EF (Behavior Rating Inventory of Executive Function, Second Edition [BRIEF-2]-Global Executive Composite [GEC]: r(15) =-.70, p<.01, d=1.96). While not statistically significant, medium to large effect sizes were found for GP DH and parent-reported inattention (Behavior Assessment System for Children, Third Edition [BASC-3]-Attention Problems: r(12)=-.39, p=.17, d=.85) and hyperactivity/impulsivity (BASC-3-Hyperactivity: r(11)= -.44, p=.13, d=.98), as well as performance-based attention (Conners Continuous Performance Test, Third Edition -Omission Errors: r(12)=-.35, p=.22, d=.41), working memory (Wechsler Intelligence Scale for Children - Fifth Edition [WISC-V]-Digit Span [DS]: r(19)=.38, p=.09, d=.82) and cognitive flexibility (Delis-Kaplan Executive Function System (D-KEFS) Verbal Fluency Category Switching: r(13)=.46, p=.08, d=1.04); this suggests that these relations may exist but that our study was underpowered to detect them. Non-dominant hand (NDH) manual dexterity was related to performance-based working memory (WISC-V-DS: r(19)=.50, p<.01, d=1.12) and cognitive flexibility (D-KEFS-Trails Making Test Number-Letter Switching: r(17)=.64, p<.01, d=1.67). Again, while underpowered, medium to large effect sizes were found for GP NDH and parent-reported EF (BRIEF-2 GEC: r(15) =-.45, p=.07, d=1.01) and performance-based phonemic fluency (D-KEFS-Letter Fluency: r(13)=.31, p=.20, d=.65).
Conclusions:Our findings suggest that FM, EF, and ADHD are related in youth with FLE; however, these relations appear to vary by skill and hand. We posit that our findings are due in part to the frontal-cerebellar networks given their anatomic proximity between frontal motor areas and the dorsolateral prefrontal cortex - as well as their shared functional involvement in these networks. Future studies should evaluate the predictive validity of initial FM skills for later executive dysfunction and ADHD symptomatology in FLE. If such relations emerge, contributions of early FM interventions on EF development should be examined. Further replication of these findings with a larger sample is warranted.
Exploration of baseline and early changes in neurocognitive characteristics as predictors of treatment response to bupropion, sertraline, and placebo in the EMBARC clinical trial
- Yuen-Siang Ang, Gerard E. Bruder, John G. Keilp, Ashleigh Rutherford, Daniel M. Alschuler, Pia Pechtel, Christian A. Webb, Thomas Carmody, Maurizio Fava, Cristina Cusin, Patrick J. McGrath, Myrna Weissman, Ramin Parsey, Maria A. Oquendo, Melvin G. McInnis, Crystal M. Cooper, Patricia Deldin, Madhukar H. Trivedi, Diego A. Pizzagalli
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- Psychological Medicine / Volume 52 / Issue 13 / October 2022
- Published online by Cambridge University Press:
- 20 November 2020, pp. 2441-2449
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Background
Treatment for major depressive disorder (MDD) is imprecise and often involves trial-and-error to determine the most effective approach. To facilitate optimal treatment selection and inform timely adjustment, the current study investigated whether neurocognitive variables could predict an antidepressant response in a treatment-specific manner.
MethodsIn the two-stage Establishing Moderators and Biosignatures of Antidepressant Response for Clinical Care (EMBARC) trial, outpatients with non-psychotic recurrent MDD were first randomized to an 8-week course of sertraline selective serotonin reuptake inhibitor or placebo. Behavioral measures of reward responsiveness, cognitive control, verbal fluency, psychomotor, and cognitive processing speeds were collected at baseline and week 1. Treatment responders then continued on another 8-week course of the same medication, whereas non-responders to sertraline or placebo were crossed-over under double-blinded conditions to bupropion noradrenaline/dopamine reuptake inhibitor or sertraline, respectively. Hamilton Rating for Depression scores were also assessed at baseline, weeks 8, and 16.
ResultsGreater improvements in psychomotor and cognitive processing speeds within the first week, as well as better pretreatment performance in these domains, were specifically associated with higher likelihood of response to placebo. Moreover, better reward responsiveness, poorer cognitive control and greater verbal fluency were associated with greater likelihood of response to bupropion in patients who previously failed to respond to sertraline.
ConclusionThese exploratory results warrant further scrutiny, but demonstrate that quick and non-invasive behavioral tests may have substantial clinical value in predicting antidepressant treatment response.
Personalized prediction of antidepressant v. placebo response: evidence from the EMBARC study
- Christian A. Webb, Madhukar H. Trivedi, Zachary D. Cohen, Daniel G. Dillon, Jay C. Fournier, Franziska Goer, Maurizio Fava, Patrick J. McGrath, Myrna Weissman, Ramin Parsey, Phil Adams, Joseph M. Trombello, Crystal Cooper, Patricia Deldin, Maria A. Oquendo, Melvin G. McInnis, Quentin Huys, Gerard Bruder, Benji T. Kurian, Manish Jha, Robert J. DeRubeis, Diego A. Pizzagalli
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- Psychological Medicine / Volume 49 / Issue 7 / May 2019
- Published online by Cambridge University Press:
- 02 July 2018, pp. 1118-1127
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Background
Major depressive disorder (MDD) is a highly heterogeneous condition in terms of symptom presentation and, likely, underlying pathophysiology. Accordingly, it is possible that only certain individuals with MDD are well-suited to antidepressants. A potentially fruitful approach to parsing this heterogeneity is to focus on promising endophenotypes of depression, such as neuroticism, anhedonia, and cognitive control deficits.
MethodsWithin an 8-week multisite trial of sertraline v. placebo for depressed adults (n = 216), we examined whether the combination of machine learning with a Personalized Advantage Index (PAI) can generate individualized treatment recommendations on the basis of endophenotype profiles coupled with clinical and demographic characteristics.
ResultsFive pre-treatment variables moderated treatment response. Higher depression severity and neuroticism, older age, less impairment in cognitive control, and being employed were each associated with better outcomes to sertraline than placebo. Across 1000 iterations of a 10-fold cross-validation, the PAI model predicted that 31% of the sample would exhibit a clinically meaningful advantage [post-treatment Hamilton Rating Scale for Depression (HRSD) difference ⩾3] with sertraline relative to placebo. Although there were no overall outcome differences between treatment groups (d = 0.15), those identified as optimally suited to sertraline at pre-treatment had better week 8 HRSD scores if randomized to sertraline (10.7) than placebo (14.7) (d = 0.58).
ConclusionsA subset of MDD patients optimally suited to sertraline can be identified on the basis of pre-treatment characteristics. This model must be tested prospectively before it can be used to inform treatment selection. However, findings demonstrate the potential to improve individual outcomes through algorithm-guided treatment recommendations.
Looking Backward, Looking Forward: MLA Members Speak
- April Alliston, Elizabeth Ammons, Jean Arnold, Nina Baym, Sandra L. Beckett, Peter G. Beidler, Roger A. Berger, Sandra Bermann, J.J. Wilson, Troy Boone, Alison Booth, Wayne C. Booth, James Phelan, Marie Borroff, Ihab Hassan, Ulrich Weisstein, Zack Bowen, Jill Campbell, Dan Campion, Jay Caplan, Maurice Charney, Beverly Lyon Clark, Robert A. Colby, Thomas C. Coleman III, Nicole Cooley, Richard Dellamora, Morris Dickstein, Terrell Dixon, Emory Elliott, Caryl Emerson, Ann W. Engar, Lars Engle, Kai Hammermeister, N. N. Feltes, Mary Anne Ferguson, Annie Finch, Shelley Fisher Fishkin, Jerry Aline Flieger, Norman Friedman, Rosemarie Garland-Thomson, Sandra M. Gilbert, Laurie Grobman, George Guida, Liselotte Gumpel, R. K. Gupta, Florence Howe, Cathy L. Jrade, Richard A. Kaye, Calhoun Winton, Murray Krieger, Robert Langbaum, Richard A. Lanham, Marilee Lindemann, Paul Michael Lützeler, Thomas J. Lynn, Juliet Flower MacCannell, Michelle A. Massé, Irving Massey, Georges May, Christian W. Hallstein, Gita May, Lucy McDiarmid, Ellen Messer-Davidow, Koritha Mitchell, Robin Smiles, Kenyatta Albeny, George Monteiro, Joel Myerson, Alan Nadel, Ashton Nichols, Jeffrey Nishimura, Neal Oxenhandler, David Palumbo-Liu, Vincent P. Pecora, David Porter, Nancy Potter, Ronald C. Rosbottom, Elias L. Rivers, Gerhard F. Strasser, J. L. Styan, Marianna De Marco Torgovnick, Gary Totten, David van Leer, Asha Varadharajan, Orrin N. C. Wang, Sharon Willis, Louise E. Wright, Donald A. Yates, Takayuki Yokota-Murakami, Richard E. Zeikowitz, Angelika Bammer, Dale Bauer, Karl Beckson, Betsy A. Bowen, Stacey Donohue, Sheila Emerson, Gwendolyn Audrey Foster, Jay L. Halio, Karl Kroeber, Terence Hawkes, William B. Hunter, Mary Jambus, Willard F. King, Nancy K. Miller, Jody Norton, Ann Pellegrini, S. P. Rosenbaum, Lorie Roth, Robert Scholes, Joanne Shattock, Rosemary T. VanArsdel, Alfred Bendixen, Alarma Kathleen Brown, Michael J. Kiskis, Debra A. Castillo, Rey Chow, John F. Crossen, Robert F. Fleissner, Regenia Gagnier, Nicholas Howe, M. Thomas Inge, Frank Mehring, Hyungji Park, Jahan Ramazani, Kenneth M. Roemer, Deborah D. Rogers, A. LaVonne Brown Ruoff, Regina M. Schwartz, John T. Shawcross, Brenda R. Silver, Andrew von Hendy, Virginia Wright Wexman, Britta Zangen, A. Owen Aldridge, Paula R. Backscheider, Roland Bartel, E. M. Forster, Milton Birnbaum, Jonathan Bishop, Crystal Downing, Frank H. Ellis, Roberto Forns-Broggi, James R. Giles, Mary E. Giles, Susan Blair Green, Madelyn Gutwirth, Constance B. Hieatt, Titi Adepitan, Edgar C. Knowlton, Jr., Emanuel Mussman, Sally Todd Nelson, Robert O. Preyer, David Diego Rodriguez, Guy Stern, James Thorpe, Robert J. Wilson, Rebecca S. Beal, Joyce Simutis, Betsy Bowden, Sara Cooper, Wheeler Winston Dixon, Tarek el Ariss, Richard Jewell, John W. Kronik, Wendy Martin, Stuart Y. McDougal, Hugo Méndez-Ramírez, Ivy Schweitzer, Armand E. Singer, G. Thomas Tanselle, Tom Bishop, Mary Ann Caws, Marcel Gutwirth, Christophe Ippolito, Lawrence D. Kritzman, James Longenbach, Tim McCracken, Wolfe S. Molitor, Diane Quantic, Gregory Rabassa, Ellen M. Tsagaris, Anthony C. Yu, Betty Jean Craige, Wendell V. Harris, J. Hillis Miller, Jesse G. Swan, Helene Zimmer-Loew, Peter Berek, James Chandler, Hanna K. Charney, Philip Cohen, Judith Fetterley, Herbert Lindenberger, Julia Reinhard Lupton, Maximillian E. Novak, Richard Ohmann, Marjorie Perloff, Mark Reynolds, James Sledd, Harriet Turner, Marie Umeh, Flavia Aloya, Regina Barreca, Konrad Bieber, Ellis Hanson, William J. Hyde, Holly A. Laird, David Leverenz, Allen Michie, J. Wesley Miller, Marvin Rosenberg, Daniel R. Schwarz, Elizabeth Welt Trahan, Jean Fagan Yellin
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- Journal:
- PMLA / Publications of the Modern Language Association of America / Volume 115 / Issue 7 / December 2000
- Published online by Cambridge University Press:
- 23 October 2020, pp. 1986-2078
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- December 2000
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