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Individual Alpha Peak Frequency Moderates Transfer of Learning in Cognitive Remediation of Schizophrenia

Published online by Cambridge University Press:  27 January 2020

B.C. Castelluccio Open the ORCID record for B.C. Castelluccio [Opens in a new window] ,
J.G. Kenney  and
J.K. Johannesen Open the ORCID record for J.K. Johannesen [Opens in a new window]
B.C. Castelluccio
Affiliation:
Department of Psychiatry and Human Behavior, Brown University Alpert Medical School, Providence, RI 02903, USA
J.G. Kenney
Affiliation:
Psychology Service, VA Connecticut Healthcare System, West Haven, CT 06516, USA Department of Psychiatry, Yale University School of Medicine, New Haven, CT 06510, USA
J.K. Johannesen*
Affiliation:
Psychology Service, VA Connecticut Healthcare System, West Haven, CT 06516, USA Department of Psychiatry, Yale University School of Medicine, New Haven, CT 06510, USA
*
*Correspondence and reprint requests to: Jason K. Johannesen, VA Connecticut Health Care System, Psychology Service 116-B, 950 Campbell Ave, West Haven, CT 06516, USA. E-mail: jason.johannesen@yale.edu
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Abstract

Objective:

Meta-analyses report moderate effects across cognitive remediation (CR) trials in schizophrenia. However, individual responses are variable, with some participants showing no appreciable gain in cognitive performance. Furthermore, reasons for heterogeneous outcome are undetermined. We examine the extent to which CR outcome is attributable to near learning—direct gains in trained cognitive tasks—while also exploring factors influencing far transfer of gains during training to external cognitive measures.

Method:

Thirty-seven schizophrenia outpatients were classified as CR responders and non-responders according to change in MATRICS Consensus Cognitive Battery composite score following 20 sessions of computer-based training. Metrics of near learning during training, as well as baseline demographic, clinical, cognitive, and electroencephalographic (EEG) measures, were examined as predictors of responder status.

Results:

Significant post-training improvement in cognitive composite score (Cohen’s d = .41) was observed across the sample, with n = 21 and n = 16 classified as responders and non-responders, respectively. Near learning was evidenced by significant improvement on each training exercise with practice; however, learning did not directly predict responder status. Group-wise comparison of responders and non-responders identified two factors favoring responders: higher EEG individual alpha frequency (IAF) and lower antipsychotic dosing. Tested in moderation analyses, IAF interacted with learning to predict improvement in cognitive outcome.

Conclusion:

CR outcome in schizophrenia is not directly explained by learning during training and appears to depend on latent factors influencing far transfer of trained abilities. Further understanding of factors influencing transfer of learning is needed to optimize CR efficacy.

Keywords

PlasticityNeuronalLearningCognitive neuroscienceElectroencephalographyDrugsAntipsychoticCognitive dysfunction
Type
Regular Research
Information
Journal of the International Neuropsychological Society , Volume 26 , Special Issue 1: Rehabilitation , January 2020 , pp. 19 - 30
Copyright
Copyright © INS. Published by Cambridge University Press, 2020. 

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References

REFERENCES

Anokhin, A. & Vogel, F. (1996). EEG Alpha rhythm frequency and intelligence in normal adults. Intelligence, 23(1), 1–14. doi:10.1016/S0160-2896(96)80002-X CrossRefGoogle Scholar
Best, M.W. & Bowie, C.R. (2017). A review of cognitive remediation approaches for schizophrenia: From top-down to bottom-up, brain training to psychotherapy. Expert Review of Neurotherapeutics, 17(7), 713–723. doi:10.1080/14737175.2017.1331128 CrossRefGoogle Scholar
Buchanan, R.W., Freedman, R., Javitt, D.C., Abi-Dargham, A., & Lieberman, J.A. (2007). Recent advances in the development of novel pharmacological agents for the treatment of cognitive impairments in schizophrenia. Schizophrenia Bulletin, 33(5), 1120–1130. doi:10.1093/schbul/sbm083 CrossRefGoogle Scholar
Clark, C.R., Veltmeyer, M.D., Hamilton, R.J., Simms, E., Paul, R., Hermens, D., & Gordon, E. (2004). Spontaneous alpha peak frequency predicts working memory performance across the age span. International Journal of Psychophysiology, 53(1), 1–9. doi:10.1016/J.IJPSYCHO.2003.12.011 CrossRefGoogle Scholar
Davidson, C.A., Johannesen, J.K., & Fiszdon, J.M. (2016). Role of learning potential in cognitive remediation: Construct and predictive validity. Schizophrenia Research, 171(1–3), 117–124. doi:10.1016/j.schres.2016.01.044 CrossRefGoogle Scholar
DeTore, N.R., Mueser, K.T., Byrd, J.A., & McGurk, S.R. (2019). Cognitive functioning as a predictor of response to comprehensive cognitive remediation. Journal of Psychiatric Research, 113(March), 117–124. doi:10.1016/j.jpsychires.2019.03.012 CrossRefGoogle Scholar
Doppelmayr, M., Klimesch, W., Sauseng, P., Hödlmoser, K., Stadler, W., & Hanslmayr, S. (2005). Intelligence related differences in EEG-bandpower. Neuroscience Letters, 381(3), 309–313. doi:10.1016/J.NEULET.2005.02.037 CrossRefGoogle Scholar
D’Souza, D.C., Carson, R.E., Driesen, N., Johannesen, J., Ranganathan, M., Krystal, J.H., Ahn, K.H., Bielen, K., Carbuto, M., Deaso, E. Naganawa, M., & Pittman, B. (2018). Dose-related target occupancy and effects on circuitry, behavior, and neuroplasticity of the glycine transporter-1 inhibitor PF-03463275 in healthy and schizophrenia subjects. Biological Psychiatry, 84(6), 413–421. doi:10.1016/j.biopsych.2017.12.019 CrossRefGoogle Scholar
Élie, D., Poirier, M., Chianetta, J., Durand, M., Grégoire, C., & Grignon, S. (2010). Cognitive effects of antipsychotic dosage and polypharmacy: A study with the BACS in patients with schizophrenia and schizoaffective disorder. Journal of Psychopharmacology, 24(7), 1037–1044. doi:10.1177/0269881108100777 CrossRefGoogle Scholar
First, M.B., Spitzer, R.L., Gibbon, M., & Williams, J.B.W. (2002). Structured Clinical Interview for DSM-IV-TR Axis I Disorders (Research Version, Patient Edition (SCID-I/P)). New York: Biometrics Research: New York State Psychiatric Institute.Google Scholar
Fisher, M., Loewy, R., Carter, C., Lee, A., Ragland, J.D., Niendam, T., Schlosser, D., Pham, L., Miskovich, T., & Vinogradov, S. (2015). Neuroplasticity-based auditory training via laptop computer improves cognition in young individuals with recent onset schizophrenia. Schizophrenia Bulletin, 41(1), 250–258. doi:10.1093/schbul/sbt232 CrossRefGoogle Scholar
Fiszdon, J.M. & Johannesen, J.K. (2010). Comparison of computational methods for the evaluation of learning potential in schizophrenia. Journal of the International Neuropsychological Society, 16(4), 613–620. doi:10.1017/S1355617710000317 CrossRefGoogle Scholar
Fiszdon, J.M., McClough, J.F., Silverstein, S.M., Bell, M.D., Jaramillo, J.R., & Smith, T.E. (2006). Learning potential as a predictor of readiness for psychosocial rehabilitation in schizophrenia. Psychiatry Research, 143(2–3), 159–166. doi:10.1016/j.psychres.2005.09.012 CrossRefGoogle Scholar
Foxe, J.J. & Snyder, A.C. (2011). The role of alpha-band brain oscillations as a sensory suppression mechanism during selective attention. Frontiers in Psychology, 2, 1–13. doi:10.3389/fpsyg.2011.00154 CrossRefGoogle Scholar
Giannitrapani, D. & Kayton, L. (1974). Schizophrenia and EEG spectral analysis. Electroencephalography and Clinical Neurophysiology, 36, 377–386. doi:10.1016/0013-4694(74)90187-4 CrossRefGoogle Scholar
Grandy, T.H., Werkle-Bergner, M., Chicherio, C., Lövdén, M., Schmiedek, F., & Lindenberger, U. (2013). Individual alpha peak frequency is related to latent factors of general cognitive abilities. NeuroImage, 79, 10–18. doi:10.1016/J.NEUROIMAGE.2013.04.059 CrossRefGoogle Scholar
Grandy, T.H., Werkle-Bergner, M., Chicherio, C., Schmiedek, F., Lövdén, M., & Lindenberger, U. (2013). Peak individual alpha frequency qualifies as a stable neurophysiological trait marker in healthy younger and older adults. Psychophysiology, 50(6), 570–582. doi:10.1111/psyp.12043 CrossRefGoogle Scholar
Gratton, G., Coles, M.G., & Donchin, E. (1983). A new method for off-line removal of ocular artifact. Electroencephalography and Clinical Neurophysiology, 55(4), 468–84.CrossRefGoogle Scholar
Green, M.F., Kern, R.S., Braff, D.L., & Mintz, J. (2000). Neurocognitive deficits and functional outcome in schizophrenia: Are we measuring the “Right Stuff”? Schizophrenia Bulletin, 26(1), 119–136. doi:10.1093/oxfordjournals.schbul.a033430 CrossRefGoogle Scholar
Grynszpan, O., Perbal, S., Pelissolo, A., Fossati, P., Jouvent, R., Dubal, S., & Perez-Diaz, F. (2011). Efficacy and specificity of computer-assisted cognitive remediation in schizophrenia: A meta-analytical study. Psychological Medicine, 41(1), 163–173. doi:10.1017/S0033291710000607 CrossRefGoogle Scholar
Harris, A., Melkonian, D., Williams, L., & Gordon, E. (2006). Dynamic spectral analysis findings in first episode and chronic schizophrenia. International Journal of Neuroscience, 116(3), 223–246. doi:10.1080/00207450500402977 CrossRefGoogle Scholar
Hayes, A.F. (2013). Methodology in the Social Sciences. Introduction to Mediation, Moderation, and Conditional Process Analysis: A Regression-Based Approach. New York, NY: Guilford Press.Google Scholar
Hegerl, U., Sander, C., Ulke, C., Böttger, D., Hensch, T., Huang, J., Mauche, N., & Olbrich, S. (2016). Vigilance Algorithm Leipzig (VIGALL) Version 2.1 Manual.Google Scholar
Hill, S.K., Bishop, J.R., Palumbo, D., & Sweeney, J.A. (2010). Effect of second-generation antipsychotics on cognition: Current issues and future challenges. Expert Review of Neurotherapeutics, 10(1), 43–57. doi:10.1586/ern.09.143 CrossRefGoogle Scholar
Ho, B.-C., Andreasen, N.C., Ziebell, S., Pierson, R., & Magnotta, V. (2011). Long-term antipsychotic treatment and brain volumes: A longitudinal study of first-episode schizophrenia. Archives of General Psychiatry, 68(2), 128–37. doi:10.1001/archgenpsychiatry.2010.199 CrossRefGoogle Scholar
Hochberger, W.C., Joshi, Y.B., Thomas, M.L., Zhang, W., Bismark, A.W., Treichler, E.B.H., Tarasenko, M, Nungaray, J, Sprock, J, Cardoso, L, Swerdlow, N, & Light, G.A. (2018). Neurophysiologic measures of target engagement predict response to auditory-based cognitive training in treatment refractory schizophrenia. Neuropsychopharmacology, 44, 606–612. (October 2018). doi:10.1038/s41386-018-0256-9 CrossRefGoogle Scholar
Hori, H., Noguchi, H., Hashimoto, R., Nakabayashi, T., Omori, M., Takahashi, S., Tsukue, R., Anami, K., Hirabayashi, N., Harada, S., Saitoh, O., & Kunugi, H. (2006). Antipsychotic medication and cognitive function in schizophrenia. Schizophrenia Research, 86(1–3), 138–146. doi:10.1016/j.schres.2006.05.004 CrossRefGoogle Scholar
Joshi, Y.B., Thomas, M.L., Hochberger, W.C., Bismark, A.W., Treichler, E.B.H., Molina, J., Nungaray, J., Cardoso, L., Sprock, J., Swerdlow, N.R., & Light, G.A. (2019). Verbal learning deficits associated with increased anticholinergic burden are attenuated with targeted cognitive training in treatment refractory schizophrenia patients. Schizophrenia Research, 208, 384–389. doi:10.1016/j.schres.2019.01.016 CrossRefGoogle Scholar
Karson, C.N., Coppola, R., & Daniel, D.G. (1988). Alpha frequency in schizophrenia: An association with enlarged cerebral ventricles. American Journal of Psychiatry, 145, 861–864. doi:10.1176/ajp.145.7.861 Google Scholar
Klimesch, W., Schimke, H., & Pfurtscheller, G. (1993). Alpha frequency, cognitive load and memory performance. Brain Topography, 5(3), 241–251. doi:10.1007/BF01128991 CrossRefGoogle Scholar
Lindenmayer, J.P., Ozog, V.A., Khan, A., Ljuri, I., Fregenti, S., & McGurk, S.R. (2017). Predictors of response to cognitive remediation in service recipients with severe mental illness. Psychiatric Rehabilitation Journal, 40(1), 61–69. doi:10.1037/prj0000252 CrossRefGoogle Scholar
McGurk, S.R. & Mueser, K.T. (2017). Introduction to special issue on cognitive remediation. Psychiatric Rehabilitation Journal, 40(1), 1–3. doi:10.1037/prj0000263 CrossRefGoogle Scholar
McGurk, S.R., Twamley, E.W., Sitzer, D.I., McHugo, G.J., & Mueser, K.T. (2007). A meta-analysis of cognitive remediation in schizophrenia. American Journal of Psychiatry, 164, 1791–1802.CrossRefGoogle Scholar
Medalia, A. & Richardson, R. (2005). What predicts a good response to cognitive remediation interventions? Schizophrenia Bulletin, 31(4), 942–953. doi:10.1093/schbul/sbi045 CrossRefGoogle Scholar
Murthy, N.V., Mahncke, H., Wexler, B.E., Maruff, P., Inamdar, A., Zucchetto, M., Lund, J., Shabbir, S., Shergill, S., Keshavan, M., Kapur, S., Laruelle, M., & Alexander, R. (2012). Computerized cognitive remediation training for schizophrenia: An open label, multi-site, multinational methodology study. Schizophrenia Research, 139(1–3), 87–91. doi:10.1016/j.schres.2012.01.042 CrossRefGoogle Scholar
Nuechterlein, K.H., Barch, D.M., Gold, J.M., Goldberg, T.E., Green, M.F., & Heaton, R.K. (2004). Identification of separable cognitive factors in schizophrenia. Schizophrenia Research, 72(1), 29–39. doi:10.1016/j.schres.2004.09.007 CrossRefGoogle Scholar
Nuechterlein, K.H., Green, M.F., Kern, R.S., Baade, L.E., Barch, D.M., Cohen, J.D., Essock, S., Fenton, W.S., Frese, FJ 3rd, Gold, J.M., Goldberg, T., Heaton, R.K., Keefe, R.S., Kraemer, H., Mesholam-Gately, R., Seidman, L.J., Stover, E., Weinberger, D.R., Young, A.S., Zalcman, S., & Marder, S.R. (2008). The MATRICS consensus cognitive battery, Part 1: Test selection, reliability, and validity. American Journal of Psychiatry, 165(2), 203–213. doi:10.1176/appi.ajp.2007.07010042 CrossRefGoogle Scholar
Perez, V.B., Tarasenko, M., Miyakoshi, M., Pianka, S.T., Makeig, S.D., Braff, D.L., Swerdlow, N.R., & Light, G.A. (2017). Mismatch negativity is a sensitive and predictive biomarker of perceptual learning during auditory cognitive training in schizophrenia. Neuropsychopharmacology, 42(11), 2206–2213. doi:10.1038/npp.2017.25 CrossRefGoogle Scholar
Seidman, L.J., Cherkerzian, S., Goldstein, J.M., Agnew-Blais, J., Tsuang, M.T., & Buka, S.L. (2013). Neuropsychological performance and family history in children at age 7 who develop adult schizophrenia or bipolar psychosis in the New England Family Studies. Psychological Medicine, 43(1), 119–31. doi:10.1017/S0033291712000773 CrossRefGoogle Scholar
Shamsi, S., Lau, A., Lencz, T., Burdick, K.E., DeRosse, P., Brenner, R., Lindenmayer, J.P., & Malhotra, A.K. (2011). Cognitive and symptomatic predictors of functional disability in schizophrenia. Schizophrenia Research, 126, 257–264. doi:10.1109/TMI.2012.2196707.Separate CrossRefGoogle Scholar
Simons, D.J., Boot, W.R., Charness, N., Gathercole, S.E., Chabris, C.F., Hambrick, D.Z., & Stine-Morrow, E.A.L. (2016). Do “brain-training” programs work? Psychological Science in the Public Interest, 17(3), 103–186. doi:10.1177/1529100616661983 CrossRefGoogle Scholar
Smit, C.M., Wright, M.J., Hansell, N.K., Geffen, G.M., & Martin, N.G. (2006). Genetic variation of individual alpha frequency (IAF) and alpha power in a large adolescent twin sample. International Journal of Psychophysiology, 61(2), 235–243. doi:10.1016/J.IJPSYCHO.2005.10.004 CrossRefGoogle Scholar
Steiger, J.H. (1980). Tests for comparing elements of a correlation matrix. Psychological Bulletin, 87(2), 245–251. doi:10.1037/0033-2909.87.2.245 CrossRefGoogle Scholar
Tarasenko, M., Perez, V.B., Pianka, S.T., Vinogradov, S., Braff, D.L., Swerdlow, N.R., & Light, G.A. (2016). Measuring the capacity for auditory system plasticity: An examination of performance gains during initial exposure to auditory-targeted cognitive training in schizophrenia. Schizophrenia Research, 172(2), 123–130. doi:10.1016/j.schres.2016.01.019 CrossRefGoogle Scholar
Tsang, H.W.H., Leung, A.Y., Chung, R.C.K., Bell, M., & Cheung, W.M. (2010). Review on vocational predictors: A systematic review of predictors of vocational outcomes among individuals with schizophrenia: An update since 1998. Australian and New Zealand Journal of Psychiatry, 44(6), 495–504 doi:10.3109/00048671003785716 Google Scholar
Vita, A., Deste, G., De Peri, L., Barlati, S., Poli, R., Cesana, B.M., & Sacchetti, E. (2013). Predictors of cognitive and functional improvement and normalization after cognitive remediation in patients with schizophrenia. Schizophrenia Research, 150(1), 51–7. doi:10.1016/j.schres.2013.08.011 CrossRefGoogle Scholar
Watzke, S., Brieger, P., Kuss, O., Schoettke, H., & Wiedl, K.H. (2008). A longitudinal study of learning potential and rehabilitation outcome in schizophrenia. Psychiatric Services, 59(3), 248–255. doi:10.1176/ps.2008.59.3.248 CrossRefGoogle Scholar
Wechsler, D. (2001). Wechsler Test of Adult Reading (WTAR). San Antonio, TX: Harcourt Assessment.Google Scholar
Wiedl, K.H. & Wienobst, J. (1999). Interindividual differences in cognitive remediation research with schizophrenic patients—indicators of rehabilitation potential? International Journal of Rehabilitation Research, 22(1), 55–59 doi:10.1097/00004356-199903000-00007 CrossRefGoogle Scholar
Wright, B.A., Wilson, R.M., & Sabin, A.T. (2010). Generalization lags behind learning on an auditory perceptual task. Journal of Neuroscience, 30(35), 11635–11639. doi:10.1523/JNEUROSCI.1441-10.2010 CrossRefGoogle Scholar
Wykes, T., Huddy, V., Cellard, C., McGurk, S.R., & Czobor, P. (2011). A meta-analysis of cognitive remediation for schizophrenia: Methodology and effect sizes. American Journal of Psychiatry, 168(5), 472–485. doi:10.1176/appi.ajp.2010.10060855 CrossRefGoogle Scholar