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Brain Effects of Cognitive Remediation Therapy in Schizophrenia: A Structural and Functional Neuroimaging Study

  • Rafael Penadés
    Correspondence
    Address correspondence to Rafael Penadés, Ph.D., Clinical Institute of Neurosciences, Hospital Clinic, C/Villarroel 170, 08036 Barcelona, Spain
    Affiliations
    Department of Psychiatry and Clinical Psychobiology, University of Barcelona, Spain

    Centro de Investigación Biomédica en Red de Salud Mental, Barcelona, Spain

    Institut Clínic de Neurociènces, Hospital Clinic, Barcelona, Spain
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  • Nuria Pujol
    Affiliations
    Department of Psychiatry and Clinical Psychobiology, University of Barcelona, Spain

    Institut d’Investigacions Biomèdiques August Pi i Sunyer, Barcelona, Spain
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  • Rosa Catalán
    Affiliations
    Department of Psychiatry and Clinical Psychobiology, University of Barcelona, Spain

    Centro de Investigación Biomédica en Red de Salud Mental, Barcelona, Spain

    Institut Clínic de Neurociènces, Hospital Clinic, Barcelona, Spain
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  • Guillem Massana
    Affiliations
    Institut d’Investigacions Biomèdiques August Pi i Sunyer, Barcelona, Spain

    Centro de Investigación Biomédica en Red de Salud Mental, Barcelona, Spain
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  • Giuseppina Rametti
    Affiliations
    Department of Psychiatry and Clinical Psychobiology, University of Barcelona, Spain
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  • Clemente García-Rizo
    Affiliations
    Institut Clínic de Neurociènces, Hospital Clinic, Barcelona, Spain
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  • Nuria Bargalló
    Affiliations
    Institut d’Investigacions Biomèdiques August Pi i Sunyer, Barcelona, Spain

    Centre de Diagnòstic per la Imatge, Hospital Clinic, Barcelona, Spain
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  • Cristóbal Gastó
    Affiliations
    Department of Psychiatry and Clinical Psychobiology, University of Barcelona, Spain

    Centro de Investigación Biomédica en Red de Salud Mental, Barcelona, Spain

    Institut Clínic de Neurociènces, Hospital Clinic, Barcelona, Spain
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  • Miquel Bernardo
    Affiliations
    Department of Psychiatry and Clinical Psychobiology, University of Barcelona, Spain

    Centro de Investigación Biomédica en Red de Salud Mental, Barcelona, Spain

    Institut Clínic de Neurociènces, Hospital Clinic, Barcelona, Spain
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  • Carme Junqué
    Affiliations
    Department of Psychiatry and Clinical Psychobiology, University of Barcelona, Spain

    Institut d’Investigacions Biomèdiques August Pi i Sunyer, Barcelona, Spain
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      Background

      Cognitive remediation therapy positively affects cognition and daily functioning in patients with schizophrenia. However, studies on the underlying neurobiological mechanisms of this treatment are scarce. The aim of the current study was to investigate functional and structural connectivity brain changes in schizophrenia patients after cognitive remediation therapy using a whole-brain approach that combined functional magnetic resonance imaging and diffusion tensor imaging.

      Methods

      A randomized controlled trial with 30 schizophrenia outpatients and 15 healthy volunteers. A strategy-learning-based treatment was used as a cognitive remediation therapy. A social skills training that provides useful information about illness management was used as an active control. We investigated changes in the pattern of functional connectivity assessed during an n-back task by tensorial independent component analysis as implemented in the multivariate exploratory linear decomposition into independent components and in the fractional anisotropy index of white matter integrity using tract-based spatial statistics.

      Results

      Brain networks activation pattern significantly changed in patients exposed to the cognitive treatment in the sense of normalizing toward the patterns observed in healthy control subjects. Additionally, in white matter, they showed an increase in fractional anisotropy index in the anterior part of the genu of the corpus callosum. Cognitive improvement, functional, and also structural changes showed statistically significant correlations.

      Conclusions

      Improvement in brain functioning detected after cognitive remediation therapy in schizophrenia patients might be based on an increase of the interhemispheric information transfer between the bilateral prefrontal cortexes via the corpus callosum.

      Key Words

      Cognitive remediation therapy (CRT) is an evidence-based treatment that seems to improve neurocognition and positively affect daily functioning in patients with schizophrenia (
      • Krabbendam L.
      • Aleman A.
      Cognitive rehabilitation in schizophrenia: A quantitative analysis of controlled studies.
      ,
      • Twamley E.W.
      • Jeste D.V.
      • Bellack A.S.
      A review of cognitive training in schizophrenia.
      ,
      • McGurk S.R.
      • Twamley E.W.
      • Sitzer D.I.
      • McHugo G.J.
      • Mueser K.T.
      A meta-analysis of cognitive remediation in schizophrenia.
      ,
      • Wykes T.
      • Huddy V.
      • Cellard C.
      • McGurk S.R.
      • Czbor P.
      A meta-analysis of cognitive remediation for schizophrenia: Methodology and effect sizes.
      ). Unfortunately, the underlying neurobiological mechanisms of this treatment have scarcely been studied (
      • Holcomb H.
      Practice, learning, and the likelihood of making an error: How task experience shapes physiological response in patients with schizophrenia.
      ). Initially, Wykes (
      • Wykes T.
      What are we changing with neurocognitive rehabilitation? Illustrations from two single cases of changes in neuropsychological performance and brain systems as measured by SPECT.
      ) reported how two patients showed changes in frontal perfusion patterns after the cognitive treatment measured through single photon emission computed tomography (SPECT) procedures. Penadés et al. (
      • Penadés R.
      • Boget T.
      • Lomeña F.
      • Bernardo M.
      • Mateos J.J.
      • Laterza C.
      • et al.
      Brain perfusion and neuropsychological changes in schizophrenic patients after cognitive rehabilitation.
      ) also found an increase in prefrontal blood flow during task performance following cognitive treatment in a case report study. These results were replicated in a small sample of eight patients (
      • Penadés R.
      • Boget T.
      • Lomeña F.
      • Mateos J.J.
      • Catalán R.
      • Gastó C.
      • Salamero M.
      Could the hypofrontality pattern in schizophrenia be modified through neuropsychological rehabilitation?.
      ).
      Subsequently, using functional magnetic resonance imaging (fMRI) procedures, Wexler et al. (
      • Wexler B.E.
      • Anderson M.
      • Fulbright R.K.
      • Gore J.C.
      Preliminary evidence of improved verbal working memory performance and normalization of task-related frontal lobe activation in schizophrenia following cognitive exercises.
      ) found that verbal memory improvement after training was associated with increased task-related activation in the same brain region that was activated during memory tasks in healthy individuals. Unfortunately, these initial studies had small samples and lack of real placebo comparison groups. Wykes et al. (
      • Wykes T.
      • Brammer M.
      • Mellers J.
      • Bray P.
      • Reeder C.
      • Williams C.
      • Corner J.
      Effects on the brain of a psychological treatment: Cognitive remediation therapy functional magnetic resonance imaging in schizophrenia.
      ) conducted the first randomized, controlled study in which 12 patients were randomly assigned to control therapy or CRT. Only the group receiving CRT significantly increased their brain activation in regions associated with working memory, particularly the inferior frontal gyrus. Recently, Haut et al. (
      • Haut K.M.
      • Lim K.O.
      • MacDonald A.
      Prefrontal cortical changes following cognitive training in patients with chronic schizophrenia: Effects of practice, generalization, and specificity.
      ) conducted a quasi-randomized study with nine patients receiving CRT, nine patients receiving control therapy (social skills training), and nine healthy control (HC) subjects. Those patients receiving CRT showed increased activation in the dorsolateral prefrontal cortex, anterior cingulate, and frontopolar cortex. Finally, Bor et al. (
      • Bor J.
      • Brunelin J.
      • d’Amato T.
      • Costes N.
      • Suaud-Chagny M.F.
      • Saoud M.
      • Poulet E.
      How can cognitive remediation therapy modulate brain activations in schizophrenia? An fMRI study.
      ) explored the impact of CRT in 17 patients and 15 healthy volunteers with fMRI in a randomized controlled trial. Following treatment, the CRT group exhibited an increased ability to activate the prefrontal regions that could be subserving attention and working memory systems.
      Although these studies led the way in showing the possibility of concomitant changes in brain activity with CRT, they did not take into account the networks of activation involved in cognitive functioning. Thus, hypofrontality has been supported by meta-analysis (
      • Hill K.
      • Mann L.
      • Laws K.R.
      • Stephenson C.M.
      • Nimmo-Smith I.
      • McKenna P.J.
      Hypofrontality in schizophrenia: A meta-analysis of functional imaging studies.
      ), but there are some available data that could suggest prefrontal dysfunction in schizophrenia is more than the simple notion of hypofunction (
      • Meyer-Lindenberg A.
      • Poline J.B.
      • Kohn P.D.
      • Holt J.L.
      • Egan M.F.
      • Weinberger D.R.
      • Berman K.F.
      Evidence for abnormal cortical functional connectivity during working memory in schizophrenia.
      ). Interestingly, not only hypoactivation but also compensatory hyperactivation from other nonspecific prefrontal cortex areas such as the ventral regions have been described (
      • Callicott J.H.
      • Mattay V.S.
      • Verchinski B.A.
      • Marenco S.
      • Egan M.F.
      • Weinberger D.R.
      Complexity of prefrontal cortical dysfunction in schizophrenia: More than up or down.
      ). Notwithstanding, cognitive impairment in schizophrenia seems to be the consequence of widespread alterations of the connectivity between various brain networks and is not restricted to the dorsal prefrontal cortex (
      • Glahn D.C.
      • Ragland J.D.
      • Abramoff A.
      • Barrett J.
      • Laird A.R.
      • Bearden C.E.
      • Velligan D.I.
      Beyond hypofrontality: A quantitative meta-analysis of functional neuroimaging studies of working memory in schizophrenia.
      ,
      • Minzenberg M.J.
      • Laird A.R.
      • Thelen S.
      • Carter C.S.
      • Glahn D.C.
      Meta-analysis of 41 functional neuroimaging studies of executive function in schizophrenia.
      ). Moreover, recent studies suggest that patients show impairments not only in task-related performance but also in rest-related brain functioning (
      • Broyd S.J.
      • Demanuele C.
      • Debener S.
      • Helps S.K.
      • James C.J.
      • Sonuga-Barke E.J.
      Default-mode brain dysfunction in mental disorders: A systematic review.
      ). It is the so-called default mode network (DMN) that involves different interconnected regions that should be highly active at rest but that should be deactivated during performance of cognitive tasks (
      • Garrity A.G.
      • Pearlson G.D.
      • McKiernan K.
      • Lloyd D.
      • Kiehl K.A.
      • Calhoun V.D.
      Aberrant “default mode” functional connectivity in schizophrenia.
      ).
      Furthermore, only one study has tested the effects of CRT with structural neuroimaging methods showing compelling results. After a 2-year follow-up, Eack et al. (
      • Eack S.M.
      • Hogarty G.E.
      • Cho R.Y.
      • Prasad K.M.
      • Greenwald D.P.
      • Hogarty S.S.
      • Keshavan M.S.
      Neuroprotective effects of cognitive enhancement therapy against gray matter loss in early schizophrenia: Results from a 2-year randomized controlled trial.
      ) were able to demonstrate that patients following cognitive treatment showed better preservation of gray matter volumes in regions that are involved in cognitive impairment than the patients who did not. Despite these encouraging results, to date no study of CRT has been conducted to explore the impact of the CRT on structural connectivity that integrates structural and functional MRI techniques. Thus, we hypothesized that the use of a strategy-based CRT would improve efficiency in different functional networks and that it also would produce some changes in structural connectivity.

      Methods and Materials

      A controlled, randomized study was carried out with three groups: patients receiving cognitive treatment, patients receiving a different psychological intervention as an active control, and a HC group. Randomization was independently conducted by author C.G. He took no part in the implementation of assignments, the generation of the allocation sequence being his only role. On recruitment, patients were randomly assigned to either CRT or social skills training (SST) using computer-generated random numbers and treated for 4 months in their respective treatment condition. All were then assessed 2 to 3 days before the first treatment session and 2 to 3 days after the last session through neuropsychological battery and MRI. To identify functional and structural global changes related to CRT, a longitudinal analysis of patients and HC subjects pre- and posttreatment MRI data was carried out. In addition, preprocessing and analysis of cross-sectional fMRI data at baseline were performed using the same protocol. Researchers involved in those analyses were completely blinded to the treatment assignation.

      Participants

      Patients (n = 35) were recruited by the Schizophrenia Unit at the Hospital Clinic, which serves part of the Barcelona area. The inclusion criteria were 1) age less than 55 years, 2) diagnosis of schizophrenia confirmed following the Structured Clinical Interview for DSM-IV Axis I Disorders (

      First MB, Spitzer RL, Gibbon M, Williams JB (1997): Structured Clinical Interview for DSM-IV Axis I Disorders—Clinician Version (SCID-CV) [Spanish Edition: Barcelona: Masson SA, 2001]. Washington, DC: American Psychiatric Press

      ), 3) prevalence of negative symptoms confirmed by the Positive and Negative Syndrome Scale (
      • Kay S.R.
      • Sevy S.
      Pyramidical model of schizophrenia.
      ), and 4) presence of cognitive impairments confirmed by a battery of neuropsychological tests. Exclusion criteria were 1) Vocabulary test of the Wechsler Adult Intelligence Scale—Third Edition below 4 (scaled score), 2) organic cerebral diseases or primary diagnosis of substance abuse, 3) psychotic exacerbation in the previous 6 months, and 4) plan to change medication during the treatment phase. Healthy control participants (n = 15) were screened for the presence of lifetime Axis I psychotic or mood disorders using the Structured Clinical Interview for DSM-IV (nonpatient version) and for the presence of a first-degree relative with schizophrenia. Following a complete description of the study to participants, written informed consent was obtained. There were no significant differences between groups for patients, but HC subjects performed significantly better in cognitive variables (Table 1).
      Table 1Demographic Clinical and Cognitive Variables
      CRT (n = 17)SST (n = 18)HC (n = 15)Testp Value
      Gender, n Male/Female12/515/310/5
      Age, Years36.35 (13.16)37.56 (8.99)34.75 (3.14)F2,47 = .320.728
      Years of Education11.59 (3.06)11.94 (3.02)16.50 (3.14)F2,47 = 12.87<.001
      Length of Illness, Years11.59 (9.79)14.19 (7.03)F1,34 = .736.397
      Hospitalizations1.76 (1.60)3.06 (2.62)F1,34 = 2.989.095
      Cumulative CDE270.65(121.72)268.31(148.265)F1,34 = .002.961
      Treatment
      Some patients were polymedicated, increasing the sample size for medication. Five patients were taking two antipsychotics, three of whom were from the CRT and 2 from the SST.
       Aripiprazole34
       Quetiapine12
       Olanzapine62
       Risperidone33
       Clozapine56
      PANSS Total66.00 (8.51)63.56 (8.93)F1,34 = .645.428
      PANSS Positive10.06 (1.78)10.25 (2.02)F1,34 = .083.775
      PANSS Negative19.24 (5.14)17.81 (1.60)F1,34 = .688.413
      PANSS General Pathology36.71 (4.41)35.50 (6.94)F1,34 = .359.554
      Data are mean (SD) except as noted.
      CDE, chlorpromazine daily equivalents; CRT, cognitive remediation therapy; HC, healthy controls subjects; PANSS, Positive and Negative Syndrome Scale; SST, social skills training.
      a Some patients were polymedicated, increasing the sample size for medication. Five patients were taking two antipsychotics, three of whom were from the CRT and 2 from the SST.

      Treatments

      CRT. CRT was applied according to the Wykes and Reeder manual (
      • Wykes T.
      • Reeder C.
      Cognitive Remediation Therapy for Schizophrenia: Theory and Practice.
      ). This program has been previously tested in various trials (
      • Wykes T.
      • Reeder C.
      • Corner J.
      • Williams C.
      • Everitt B.
      The effects of neurocognitive remediation on executive processing in patients with schizophrenia.
      ,
      • Penadés R.
      • Catalán R.
      • Salamero M.
      • Boget T.
      • Puig O.
      • Guarch J.
      • Gastó C.
      Cognitive remediation therapy for outpatients with chronic schizophrenia: A controlled and randomized study.
      ,
      • Wykes T.
      • Reeder C.
      • Landau S.
      • Everitt B.
      • Knapp M.
      • Patel A.
      • Romeo R.
      Cognitive remediation therapy in schizophrenia: Randomised controlled trial.
      ). It was implemented on an individual basis using mainly the paper-and-pencil tasks from the Spanish translation of the frontal/executive program (
      • Delahunty A.
      • Morice R.
      The Frontal Executive Program, A Neurocognitive Rehabilitation Program For Schizophrenia, 2nd ed.
      ) and is used to facilitate the strategy-learning in tasks of progressive complexity adopting an errorless learning approach. As much as possible, each task was set at the subject’s own pace with scaffolding as the main instructional technique. This involves an instructor extending a learner’s ability by providing support in those aspects of a task that the learner cannot accomplish, while removing assistance in those areas where competence has been achieved. The patients received 40 sessions: 1-hour sessions two or three times a week over 4 months. The Cognitive Shift Module aims to address flexibility in thinking and information-set maintenance, both of which presumably require the capacity to effectively engage and disengage activated neural network processing. The Working Memory Module aims to target the executive processes central to memory control and has patients work with as many as two to five information sets at a time. The primary target of the Planning Module is self-ordered, goal-oriented, set/schema formation and manipulation—that is, the application of the practiced processes, such as working memory, to tasks requiring planning.
      SST. Patients in the treatment control group received 40 hours of treatment based on a behaviorally oriented SST. The intervention was adapted from the manualized therapy protocol Symptom Management Module from the University of California—Los Angles skills training modules (
      • Liberman R.P.
      • Kopelowicz A.
      Basic elements in biobehavioral treatment and rehabilitation of schizophrenia.
      ). UCLA modules have shown positive results in symptom control (
      • Eckman T.A.
      • Wirshing W.C.
      • Marder S.R.
      • Liberman R.P.
      • Johnston-Cronk K.
      • Zimmermann K.
      • Mintz J.
      Technique for training schizophrenic patients in illness self-management: A controlled trial.
      ) but they are not expected to have any effects on neurocognition. The module provides information about schizophrenia and its treatment and trains the participants to identify and monitor warning signs of relapse, to manage warning signs by developing a crisis plan, to cope with persistent symptoms, and to avoid and refuse alcohol and nonmedication drugs. The role of the therapist was to inform the participant of the relevant skills and their benefits, to enhance skill acquisition by modeling and role-play exercises, to anticipate outcome problems that could interfere with the use of the skill, and to encourage the transfer of targeted skills into real-world settings by in vivo exercises and homework assignments.

      MRI Scanning Protocol

      Functional and structural imaging data were acquired on a 3-T MRI scanner (Magnetom Trio Tim, Siemens Medical Systems, Germany). During fMRI a set of T2-weighted 280 volumes were acquired (repetition time [TR] = 2000 msec, echo time [TE] = 29 msec, slice thickness = 3 mm, distance factor = 25%, field of view [FOV] = 240 mm, matrix size = 128×128) providing whole brain coverage. A T1-weighted structural image was also acquired for each subject with magnetization prepared rapid acquisition gradient-echo three-dimensional protocol (TR = 2300 msec, TE = 2.98 msec, 240 slices, slice thickness = 1 mm, FOV = 256 mm, matrix size = 256 × 256). Finally, diffusion tensor imaging (DTI) was conducted in the same scanning session with single shot diffusion weighted echo-planar imaging in the axial plane with diffusion sensitization gradients applied in 60 noncolinear directions with a b value of 0 and 1000 s/mm2 (TR = 9300 msec, TE = 94 msec, 65 slices, slice thickness = 2 mm, FOV= 240, matrix size= 122×122). Image analysis was performed using Oxford Centre Functional MRI of the Brain software library (FSL version 4.1; http://www.fmrib.ox.ac.uk/fsl).

      fMRI Data

      Experimental Setup and N-back Paradigm. The task, adapted from Callicott et al. (
      • Callicott J.H.
      • Mattay V.S.
      • Bertolino A.
      • Finn K.
      • Coppola R.
      • Frank J.A.
      • et al.
      Physiological characteristics of capacity constraints in working memory as revealed by functional MRI.
      ), involved monitoring locations of dots (presentation time: 450 msec; interstimulus-interval: 500 msec) within a diamond-shaped box at a given delay from the original occurrence (0-back, or 2-back; Figure 1). During the 0-back test, participants identified the number currently seen. In the 2-back load, participants encoded the current stimulus while indicating the number seen two stimuli previously. Participants responded by pressing the appropriate button on a four-button box, which has the same configuration and position as the diamond. Short resting periods (in which a white cross was shown on a black screen) were introduced after each 2-back condition. Every block consisted of 18 trials (6×0-back, 6×2-back, and 6×rest) each of 90-second duration. The sequence consisted of a total of six blocks. Stimuli were presented inside the 3T magnetic resonance machine with Visual Stim Digital MRI Compatible High Resolution Stereo three-dimensional glasses (Resonance Technology, Northridge, California) and Presentation version 10.1 (Neurobehavioral Systems, Albany, California) running on Windows XP (Microsoft, Redmond, Washington).
      Figure thumbnail gr1
      Figure 1Illustration of 0-back and 2-back trials.
      Preprocessing and Analysis. For the functional data preprocessing, we applied motion correction using MCFLIRT (
      • Jenkinson M.
      • Bannister P.R.
      • Brady J.M.
      • Smith S.M.
      Improved optimisation for the robust and accurate linear registration and motion correction of brain images.
      ), removal of nonbrain structures from the echo-planar imaging volumes using the Brain Extraction tool (
      • Smith S.M.
      Fast robust automated brain extraction.
      ), spatial smoothing using a Gaussian kernel of 5 mm, mean-based intensity normalization of all volumes by the same factor (four-dimensional grand mean scaling), high pass temporal filtering (90 sec), and Gaussian low-pass temporal filtering (full width at half maximum = 2.8). The functional scans were registered to the Montreal Neurological Institute 152 standard space by using affine registration with FLIRT (
      • Jenkinson M.
      • Smith S.M.
      A global optimisation method for robust affine registration of brain images.
      ).
      After this preprocessing, fMRI analysis was carried out using tensorial independent component analysis (TICA) as implemented in the Multivariate Exploratory Linear Decomposition into Independent Components (MELODIC Version 3.1) (
      • Beckmann C.F.
      • Smith S.M.
      Tensorial extensions of independent component analysis for multisubject FMRI analysis.
      ) tool, part of FSL software. TICA is a data-driven approach that decomposes the data into a set of independent components (ICs). Model order was estimated using the Laplace approximation to the Bayesian evidence for a probabilistic principal component analysis model (
      • Beckmann C.F.
      • Smith S.M.
      Probabilistic independent component analysis for functional magnetic resonance imaging.
      ). Estimated component maps were divided by the standard deviation of the residual noise and thresholded by fitting a mixture model to the histogram of intensity values. Z (Gaussianized t/F) statistic images were thresholded using clusters determined by Z≥2.3 and a cluster significance threshold of p≤.05 corrected for multiple comparisons.
      DTI Preprocessing and Analysis. DTI preprocessing and analysis was performed using tools from FSL (
      • Ashburner J.
      • Friston K.
      Voxel-based morphometry—the methods.
      ,
      • Good C.
      • Johnsrude I.
      • Ashburner J.
      • Henson R.
      • Friston K.
      • Frackowiak R.
      A voxel-based morphometric study of ageing in 465 normal adult human brains.
      ). Image artifacts due to eddy current distortions were minimized by registering the diffusion images to the b0 images. The registered images were skull stripped using BET (
      • Douaud G.
      • Mackay C.
      • Anderson J.
      • James S.
      • Quested D.
      • Ray M.K.
      • et al.
      Schizophrenia delays and alters maturation of the brain in adolescence.
      ). Fractional anisotropy (FA) maps were obtained using the FDT tool (
      • Behrens T.E.J.
      • Woolrich M.W.
      • Jenkinson M.
      • Johansen-Berg H.
      • Nunes R.G.
      • Clare S.
      • et al.
      Characterization and propagation of uncertainty in diffusion-weighted MR imaging.
      ). After calculation of the FA map for each subject, we implemented a voxelwise statistical analysis of the FA data using Tract-Based Spatial Statistics v1.2 (TBSS) (
      • Smith S.M.
      • Jenkinson M.
      • Johansen-Berg H.
      • Rueckert D.
      • Nichols T.E.
      • Mackay C.E.
      • et al.
      Tract-based spatial statistics: Voxelwise analysis of multi-subject diffusion data.
      ). TBSS uses a carefully tuned nonlinear registration followed by the projection of the nearest maximum FA values onto a skeleton derived from a mean FA image to improve the sensitivity of the DTI analysis.

      Statistical Analysis

      For the neuropsychological outcomes an intent-to-treat analyses were first conducted with all participants who started the treatment sessions. A repeated-measures analysis of variance (ANOVA) design was used to test differences in cognitive variables between conditions at baseline and endpoint. Next, analyses of covariance comparing the two groups at baseline and endpoint assessments, including baseline as a covariate, were also performed.
      Regarding neuroimaging data, a longitudinal design included the three groups at two time points with the 30 patients (15 CRT and 15 SST) who finished the neuroimaging protocol and the 15 HC subjects. Longitudinal data were analyzed with a repeated-measures ANOVA, and cross-sectional fMRI data were analyzed with one-way ANOVA, using permutation-based nonparametric inference within the framework of the general linear model (5000 permutations) (
      • Nichols T.E.
      • Holmes A.T.
      Nonparametric permutation tests for functional neuroimaging: A primer with examples.
      ) as implemented in the FSL randomize tool. Results were considered significant at p < .05, family-wise error (FWE)-corrected, using threshold-free cluster (TFCE), a method which avoids using an arbitrary threshold for the initial cluster-formation (
      • Smith S.M.
      • Nichols T.E.
      Threshold-free cluster enhancement: Addressing problems of smoothing, threshold dependence and localization in cluster inference.
      ). Finally, motion parameters were extracted for every subject calculating the mean of displacement to establish a head movement correction. Then, a one-factor ANOVA was applied to test between-group differences. Finally, Pearson’s coefficients were calculated to determine the relationship between MRI changes and neuropsychological improvements.

      Results

      Neuropsychological Outcomes

      The result of the overall intent-to-treat analysis with the addition of baseline covariates was significant for time by condition (F2,47 = 3.918; p = .029; effect size .175) and also for different cognitive measures (Table 2). Additionally, univariate analyses showed a beneficial effect of CRT on different cognitive tests and cognitive domains (Figure 2), particularly for executive function (F2,47 = 8.469; p = .001; effect size .314), Verbal Memory (F2,47 = 6.029; p = .005; effect size .236) and Nonverbal Memory (F2,47 = 10.418; p<.001; effect size .348). Changes on working memory and psychomotor speed were not significant. More to the point, performances during scanning in the n-back task were similar at baseline and the endpoint for the three groups with no change after treatment.
      Table 2Neuropsychological Outcomes
      Pre Mean (SD)Baseline Between GroupsBaseline CRT vs. SSTPost Mean (SD)Time×GroupTime×Group CRT vs. SST
      0-Back Correct Hits
       CRT70.8 (.4)F2,42 = 1.875F1,29 = 1.87570.6 (.1)F2,42 = 1.875
       SST70.7 (.4)p = .247p = .24770.8 (.4)p = .247
       HC71.0 (1.5)70.8 (.3)
      2-Back Correct Hits
       CRT39.2 (6.2)F2,42 = 1.709F1,29 = 1.70942.2 (5.2)F2,42 = 1.433
       SST43.5 (1.2)p = .227p = .24948.5 (2.1)p = .227
       HC43.1 (1.9)47.3 (6.8)
      WAIS-III, Digit Span
       CRT12.53 (9.77)F2,47 = 9.089F1,34 = 2.72014.29 (3.06)F2,47 = .653
       SST14.38 (2.91)p<.001p = .10916.69 (11.8)p = .216
       HC18.01 (4.63)16.13 (7.71)
      WAIS-III, Arithmetic
       CRT7.82 (2.16)F2,47 = 33.47F1,34 = 5.35111.24 (7.12)F2,47 = 1.465
       SST9.56 (2.16)p<.001p = .02811.81 (10.3)p = .242
       HC14.81 (3.19)13.77 (3.78)
      WAIS-III, L-Number
       CRT6.94 (2.19)F2,47 = 18.08F1,34 = 1.6078.76 (2.41)F2,47 = .812
       SST7.88 (2.03)p<.00111.69 (11.2)p = .431
       HC11.88 (3.12)p = .21413.31 (2.65)
      WAIS-III, Symbol Coding
       CRT50.76 (22.04)F2,47 = 30.13F1,34 = .11160.47 (17.14)F2,47 = .761
       SST52.94 (14.30)p<.001p = .74159.56 (13.67)p = .474
       HC91.25 (11.51)93.23 (14.32)
      WMS-III, Logical Memory
       CRT25.29 (9.48)F2,47 = 19.97F1,34 = 6.56834.29 (11.11)F2,47 = 4.006F1,34 = 5.174
       SST24.75 (11.6)p<.001p = .01537.51 (10.82)p = .025p = .030
       HC47.08 (9.05)49.77 (7.81)
      WMS-III, Faces
       CRT31.82 (5.26)F2,47 = 10.35F1,34 = 13.2836.29 (4,96)F2,47 = 3.065F1,34 = 4.9
       SST32.75 (11.6)p<.002p = .00137.81 (5.63)p = .047p = .034
       HC40.46 (4.77)43.31 (3.37)
      RAVLT
       CRT41.88 (9.84)F2,47 = 11.15F1,34 = 1.11545.41 (11.6)F2,47 = 1.925
       SST45.31 (8.75)p<.001p = .29943.31 (9.98)p = .158
       HC56.44 (8.93)59.31 (8.07)
      TMT-A
       CRT42.53 (31.96)F2,47 = 5.197F1,34 = .93233.82 (11.8)F2,47 = 2.033
       SST42.09 (13.48)p<.001p = .34236.38 (15.2)p = .143
       HC24.38 (13.55)21.23 (6.04)
      TMT-B
       CRT128.41 (52.4)F2,47 = 12.89F1,34 = 1.80187.71 (43.66)F2,47 = 4.698F1,34 = 1.584
       SST123.44 (54.4)p<.001p = .18981.19 (28.81)p = .014p = .218
       HC50.63 (15.36)57.61 (16.73)
      TOL, Total Score
       CRT45.53 (16.24)F2,47 = 19.19F1,34 = 3.42928.29 (13.74)F2,47 = 19.193F1,34 = 28.91
       SST43.41 (18.54)p<.001p = .07433.56 (17.28)p<.001p<.001
       HC12.62 (12.02)11.77 (14.18)
      WCST, No. of Categories
       CRT2.82 (2.24)F2,47 = 51.01F1,34 = 3.7825.06 (1.88)F2,47 = 19.193F1,34 = 15.37
       SST2.25 (1.9)p<.001p = .0614.25 (2.14)p<.001p<.001
       HC9.19 (1.76)8.77 (1.36)
      WCST, Perseverations
       CRT24.21 (12.79)F2,47 = 36.29F1,34 = .84324.41 (8.21)F2,47 = 10.697F1,34 = 10.68
       SST27.51 (10.3)p<.001p = .41327.13 (8.81)p<.002p<.003
       HC1.33 (1.76)1.56 (1.93)
      CRT, cognitive remediation therapy; HC, healthy control subjects; RAVLT, Rey Auditory Verbal Learning Test; SST, social skills training; WAIS-III, Wechsler Adult Intelligence Scale—Third Edition; WMS-III, Wechsler Memory Scale—Third Edition Alternative versions (list A and B) were used in pre- and postassessments; TMT-A, Trail Making Test, part A; TMT-B, Trail Making Test, part B; TOL, Tower of London; WCST, Wisconsin Card Sorting Test.
      Figure thumbnail gr2
      Figure 2Endpoint-baseline differences through different cognitive domains for each group. The increment was calculated subtracting the baseline scores from the endpoint scores of each cognitive domain. Cognitive domain scores were obtained by calculating the mean of the standardized t scores (mean: 50; SD: 10) from the respective subtests of each cognitive domain as follows: Digit Span, Letter-Number Sequencing and Arithmetic (Wechsler Adult Intelligence Scale-Third Revision). Psychomotor speed (PS): Digit Symbol-Coding (Wechsler Adult Intelligence Scale-Third Revision) and Trail Making Test-A. Verbal memory (VM): Rey Auditory Verbal Learning Test and Logical Memory I and II (Wechsler Memory Scale-Third Edition). Nonverbal memory (NVM): Visual Reproduction I and II and Faces I and II (Wechsler Memory Scale-Third Edition). Executive function (EF): Wisconsin Card Sorting Test Categories and perseverations, Trail Making Test-B, Tower of London. CRT, cognitive remediation therapy; HC, healthy control subjects; SST, social skills training; WM, working memory.

      fMRI: TICA Results

      Between-Group Comparison. At baseline, whole-group analysis through IC MELODIC produced 22 ICs: 20 were shared with all groups, and 2 evidenced significant differences between groups. Cluster size, Montreal Neurological Institute coordinates, and Z values of the areas with significant differences between groups are described in Table 3. A detailed description of selection the whole independent component analysis results and the selection criteria used to identify significant independent components are provided in Supplement 1. Specifically, the CRT group showed increased independent component (IC)1 task positive component when compared with HC (z = 1.69; p<.04). IC1-related to the central executive network (CEN), showed increased activations in the bilateral middle and inferior frontal gyrus, left medial frontal gyrus, bilateral inferior and superior parietal lobule, bilateral precuneus, and bilateral middle occipital gyrus, compared with HC participants. IC1 time course fitted the time series task (F = 425.14, p < .000001) and was significant for all the contrasts, 2-back>0-back (z = 10.03, p < .000001), 2-back > rest (z = 21.37, p < .000001), and 0-back>rest (z = 16.46, p<.000001). Compared with SST, the CRT group also exhibited increased activation in the IC8 at rest related to the DMN (z = 1.76; p<.03) in the bilateral anterior cingulate, left middle temporal gyrus, bilateral cingulate gyrus, bilateral precuneus, bilateral inferior occipital gyrus, and bilateral lingual gyrus and its time course fitted the time series task (F = 203.47, p<.000001), being significant for both contrasts; rest>0-back (z = 17.40, p<.000001) and rest>2-back (z = 13.15, p<.000001).
      Table 3Peak Activation/Deactivation of Independent Component Analysis Cross-Sectional and Longitudinal Results
      Anatomic LocationCluster SizeMNI CoordinatesZ
      x, y, z
      Baseline: Cross-sectional Data
      IC1 CEN, CRT>HC
      Task-related activation
      L superior parietal lobe147,597116, 60, 1246.37
      R middle frontal gyrus37,66648, 164, 965.82
      Medial frontal gyrus (BA 6)11,46192, 144, 1165.29
      Task-related deactivation
      R parietal lobe28,22668, 92, 144−4.27
      Anterior cingulate (BA 32)15,10184, 172, 60−3.89
      L inferior occipital gyrus5243120, 28, 68−4.34
      R inferior occipital gyrus306460, 32, 68−4.15
      IC8 DMN, CRT>SST
      Rest-related activation89,92680, 60, 1005.77
      R precuneus9739120, 28, 725.34
      L inferior occipital gyrus (BA 18)920864, 28, 685.02
      R inferior occipital gyrus (BA 18)
      Rest-related deactivation
      L inferior parietal lobe39,774136, 88, 128−5.03
      R inferior parietal lobe359744, 84, 124−3.53
      R middle frontal gyrus340860, 128, 132−3.46
      Effect Time×Treatment: Longitudinal Data
      IC1 CEN, CRT group
      Baseline>Posttreatment
      Task-related activation
      L superior parietal lobule70,128116, 64, 1245.4
      L middle frontal gyrus11,764124, 176, 883.51
      R middle frontal gyrus960148, 168, 924.79
      Task-related deactivation
      L posterior cingulate713990, 69, 88−3.33
      Medial frontal gyrus703888, 164, 52−3.53
      L inferior occipital gyrus1725120, 28, 68−3.13
      IC2 DMN, CRT group
      Baseline>Posttreatment
      Rest-related activation
      L precuneus62,54892, 70, 1086.04
      L middle temporal gyrus53,598136, 56, 1005.58
      Rest-related deactivation
      L lingual gyrus63,88593, 38, 72−7.7
      L precentral gyrus51,364128, 108, 132−7.79
      R superior parietal lobe18,55968, 60, 132−6.22
      R middle frontal gyrus16,03560, 124, 120−4.91
      BA, Brodmann area; CEN, central executive network; CRT, cognitive remediation therapy; DMN, default mode network; HC, healthy control subjects; IC, independent component; L, left; MNI, Montreal Neurological Institute; R, right; SST, social skills training; TR, repetition time.
      With regard to longitudinal results, after treatment, the CRT group showed decreased activation in the IC1 CEN in regions that had shown overactivation at baseline (z = 2.89; p<.001): the bilateral middle and inferior frontal gyrus, anterior cingulate, bilateral inferior and superior parietal lobe, and bilateral precuneus. IC1 time course fitted the time series task (F = 335.07, p = .000001) and was significant for all the contrasts, 2-back>0-back (z = 10.03, p<.000001), 2-back>rest (z = 21.37, p<.000001) and 0-back>rest (z = 16.46, p<.000001). Compared with baseline, the CRT group also exhibited decreased DMN activation after treatment (z = 2.15, p<.015) in the anterior cingulate, cingulate gyrus, bilateral precuneus and cuneus, left middle temporal gyrus, and left supramarginal gyrus (Table 3), and its time course fitted the time series task (F = 405.86, p = .000001), being significant for all the contrasts, rest>0-back (z = 19.09, p<.000001) and rest>2-back (z = 20.71, p<.000001). No significant changes were observed for the HC and SST groups at endpoint. In addition, comparing the pattern of changes between CRT and SST, the CRT group had decreased IC1 CEN activation (z = 1.78, p<.03) indicating a significant between-group interaction (Figure 3). IC1 time course fitted the task; F = 335.07 and p = .000001, and was significant for 2-back>0-back contrast (z = 10.51, p<.00001), 2-back>rest (z = 20.04, p<.00001), and 0-back>rest (z = 14.15, p<.00001).
      Figure thumbnail gr3
      Figure 3Tensor independent component analysis showing functional changes in the cognitive remediation therapy group after treatment. Changes include a decreased activation of the central executive network (hot colors) and default mode network deactivation (cold colors) during the 2-back task (z = 2.89; p< .001).
      Endpoint cross-sectional analysis: neither differences between groups emerged on task-related activation or in the task-related deactivation of the IC1 CEN component at the endpoint. Similarly, IC2 DMN rest-related activation and rest-related deactivation did not show differences between groups on the participants-mode vectors (Supplement 1).
      DTI Results. For longitudinal results, by using the TFCE method and p<.05 (FWE corrected), we found that the CRT group showed increase FA values after treatment in the genu and body of the CC, and in the right posterior thalamic radiation (Table 4; Figure S2 in Supplement 1). Conversely, SST showed decreased FA in bilateral superior longitudinal fasciculus, left inferior longitudinal fasciculus (Table 3). No significant changes in FA emerged in the HC group between baseline and after treatment. Moreover, FA changes observed in the CRT group were also significant compared with changes in the SST group (t = 3.27; p<.05). To check that treatment-related changes in FA were not due only to baseline differences, a region of interest analysis between groups was also carried out. A mask based on TBSS longitudinal results was created and mean FA values were extracted from each participants’ FA skeletonized region of interest. Using the TFCE method (p<.05; FWE corrected) a t test between CRT and SST groups with the extracted FA values at baseline was then performed and results showed no significant differences between groups (t = –1.131, df = 28, p = .268).
      Table 4Changes in the FA Index in the Patient Groups After Psychological Treatments
      Cluster SizeTalairach Coordinatest
      x, y, z
      CRT: Increased FA
      Genu of CC619−5, 23, 153.11
      Body of CC12211 13 241.67
      Posterior thalamic radiation1029, −66, 134.11
      SST: Decreased FA
      Right superior LF11,17329, −58, 253.29
      Left superior LF6444−35, −31, 341.74
      Left inferior LF125−38, −48, −53.85
      All provided results were obtained after being corrected (p< .05).
      CC, corpus callosum; CRT, cognitive remediation therapy; FA, fractional anisotropy; LF, longitudinal fasciculus; SST, social skills training.
      Structural-Functional Performance Relationship. After treatment, reduction of overactivation in IC1 CEN was found to be associated with improvement in total cognition score (r2 = –.479; p<.03). Moreover, increment in FA was also associated with total cognition score (r2=.442; p<.04), being the executive function domain (r2=.359; p<.029) significantly correlated, but not to the level of the multiple comparisons correction. The association between anatomic and functional changes observed in the CRT group, a posterior analysis was investigated by introducing the IC1 CEN longitudinal subject mode as a covariate in the FA longitudinal analysis. The result, FWE corrected (p<.05), using TFCE showed a negative relationship between increased FA in the CC and decreased CEN overactivation after treatment, suggesting that the white matter integrity increment was associated with normalization of the functional activation pattern during the task.

      Discussion

      Patients exposed to the treatment showed a reduction in overactivation of the CEN during task-related responses and also in the deactivation of its anticorrelated DMN suggesting an improvement in the efficiency of both networks. On the other hand, an increase in white matter integrity in the genu of the corpus callosum was found in the CRT group after treatment. Functional and structural changes were correlated in the CRT group participants.
      Previous studies have already shown a reduction in initial hypofrontality after CRT in patients with schizophrenia following drill-and-practice approaches (
      • Haut K.M.
      • Lim K.O.
      • MacDonald A.
      Prefrontal cortical changes following cognitive training in patients with chronic schizophrenia: Effects of practice, generalization, and specificity.
      ,
      • Bor J.
      • Brunelin J.
      • d’Amato T.
      • Costes N.
      • Suaud-Chagny M.F.
      • Saoud M.
      • Poulet E.
      How can cognitive remediation therapy modulate brain activations in schizophrenia? An fMRI study.
      ). Additionally, enhancement of activation in prefrontal regions subserving working memory (WM) has also been demonstrated with strategy-based programs that help patients to develop compensatory strategies for learning, remembering, and processing information actively (
      • Wykes T.
      • Brammer M.
      • Mellers J.
      • Bray P.
      • Reeder C.
      • Williams C.
      • Corner J.
      Effects on the brain of a psychological treatment: Cognitive remediation therapy functional magnetic resonance imaging in schizophrenia.
      ). Nonetheless, functional neuroimaging studies showing activation changes in the frontal lobe (
      • Wykes T.
      • Brammer M.
      • Mellers J.
      • Bray P.
      • Reeder C.
      • Williams C.
      • Corner J.
      Effects on the brain of a psychological treatment: Cognitive remediation therapy functional magnetic resonance imaging in schizophrenia.
      ,
      • Haut K.M.
      • Lim K.O.
      • MacDonald A.
      Prefrontal cortical changes following cognitive training in patients with chronic schizophrenia: Effects of practice, generalization, and specificity.
      ,
      • Bor J.
      • Brunelin J.
      • d’Amato T.
      • Costes N.
      • Suaud-Chagny M.F.
      • Saoud M.
      • Poulet E.
      How can cognitive remediation therapy modulate brain activations in schizophrenia? An fMRI study.
      ) are not easy to directly integrate with the one structural study that has found reductions in loss of gray matter volume in the temporal lobes (
      • Eack S.M.
      • Hogarty G.E.
      • Cho R.Y.
      • Prasad K.M.
      • Greenwald D.P.
      • Hogarty S.S.
      • Keshavan M.S.
      Neuroprotective effects of cognitive enhancement therapy against gray matter loss in early schizophrenia: Results from a 2-year randomized controlled trial.
      ). It needs to be stressed that structural deficits can produce functional deficits at distant regions forming part of the same circuitry.
      Conceivably, working memory abnormalities cannot be understood exclusively in terms of the hypofunctioning or hyperfunctioning of the prefrontal areas (
      • Manoach D.S.
      Prefrontal cortex dysfunction during working memory performance in schizophrenia: Reconciling discrepant findings.
      ). Inefficiency of more complex neural networks has been postulated for a more descriptive and clarifying framework in which WM abnormalities in schizophrenia are the consequence of an inefficient neural strategy in different areas mediated by the dorsolateral prefrontal cortex (
      • Meyer-Lindenberg A.S.
      • Olsen R.K.
      • Kohn P.D.
      • Brown T.
      • Egan M.F.
      • Weinberger D.R.
      • Berman K.F.
      Regionally specific disturbance of dorsolateral prefrontal-hippocampal functional connectivity in schizophrenia.
      ). Thus, when patients perform WM tasks they use greater prefrontal resources than HC subjects despite lower accuracy (
      • Tan H.Y.
      • Sust S.
      • Buckholtz J.W.
      • Mattay V.S.
      • Meyer-Lindenberg A.
      • Egan M.F.
      • et al.
      Dysfunctional prefrontal regional specialization and compensation in schizophrenia.
      ). Our results can be interpreted in this framework because an initial overactive CEN became more similar to HC participants as a result of the cognitive treatment. On the other hand, normalization of DMN deactivation after treatment might be interpreted in the same context. The DMN is not only important as a resting state; it also seems to have an important role in the performance of cognitive tasks (
      • Kim D.I.
      • Manoach D.S.
      • Mathalon D.H.
      • Turner J.A.
      • Mannell M.
      • Brown G.G.
      • et al.
      Dysregulation of working memory and default-mode networks in schizophrenia using independent component analysis, an fBIRN and MCIC study.
      ,
      • Salgado-Pineda P.
      • Fakra E.
      • Delaveau P.
      • McKenna P.J.
      • Pomarol-Clotet E.
      • Blin O.
      Correlated structural and functional brain abnormalities in the default mode network in schizophrenia patients.
      ). Our study is the first to show that the anomalies in DMN in schizophrenia patients can be ameliorated to some extent with CRT. Although the therapeutic effects on DMN functioning have hardly been studied, at least one previous work showed that treatment with olanzapine was associated with the modulation of DMN connectivity in schizophrenia but not with other prefrontal networks (
      • Sambataro F.
      • Blasi G.
      • Fazio L.
      • Caforio G.
      • Taurisano P.
      • Romano R.
      • et al.
      Treatment with olanzapine is associated with modulation of the default mode network in patients with Schizophrenia.
      ). Furthermore, our findings add some evidence to the suggested complementary role of CEN and DMN networks in WM functioning (
      • Repovs G.
      • Csernansky J.G.
      • Barch D.M.
      Brain network connectivity in individuals with schizophrenia and their siblings.
      ,
      • Hasenkamp W.
      • James G.A.
      • Boshoven W.
      • Duncan E.
      Altered engagement of attention and default networks during target detection in schizophrenia.
      ) and shed new light on their potential role in cognitive improvement following CRT in schizophrenia. It is conceivable that CRT could have had played a role in cases in which patients who initially were more self-referential (
      • van Buuren M.
      • Gladwin T.E.
      • Zandbelt B.B.
      • Kahn R.S.
      • Vink M.
      Reduced functional coupling in the default-mode network during self-referential processing.
      ,
      • van Buuren M.
      • Vink M.
      • Kahn R.S.
      Default-mode network dysfunction and self-referential processing in healthy siblings of schizophrenia patients.
      ,
      • Mannell M.V.
      • Franco A.R.
      • Calhoun V.D.
      • Cañive J.M.
      • Thoma R.J.
      • Mayer A.R.
      Resting state and task-induced deactivation: A methodological comparison in patients with schizophrenia and healthy controls.
      ) in their information processing style had become more task-oriented after the treatment.
      Little is known about the potential effects of CRT in schizophrenia patients in terms of neural plasticity at the structural level (
      • Klingberg T.
      Training and plasticity of working memory.
      ). Nonetheless, Vinogradov et al. (
      • Vinogradov S.
      • Fisher M.
      • Holland C.
      • Shelly W.
      • Wolkowitz O.
      • Mellon S.H.
      Is serum brain-derived neurotrophic factor a biomarker for cognitive enhancement in schizophrenia?.
      ) provided some early evidence on the neurotrophin response induced by neuroplasticity-based CRT. Schizophrenia participants who followed the computerized cognitive training showed a significant increase in serum brain-derived neurotrophic factor compared with matched control participants. Furthermore, the impact of CRT on structural connectivity over working memory–related networks has never been tested before in patients with schizophrenia, although changes in white matter connectivity have been already described in healthy people after cognitive training. Takeuchi et al. (
      • Takeuchi H.
      • Sekiguchi A.
      • Taki Y.
      • Yokoyama S.
      • Yomogida Y.
      • Komuro N.
      • et al.
      Training of working memory impacts structural connectivity.
      ) demonstrated that working memory training was associated with increases in white matter structural integrity adjacent to the anterior part of the body of the corpus callosum in healthy people. The anterior part of the corpus callosum connects the dorsolateral prefrontal cortex between both hemispheres, and the whole network is a key element of the working memory system (
      • Kennedy K.M.
      • Raz N.
      Aging white matter and cognition: differential effects of regional variations in diffusion properties on memory, executive functions, and speed.
      ). Those improvements will lead to an increase of interhemispheric information transfer between the bilateral prefrontal cortices. Surprisingly, our findings showed similar results on the same brain structure with schizophrenia patients, suggesting a common underlying mechanism for the induced neural plasticity. It has been speculated that cognitive training could be facilitating specific neural activity that would eventually cause increased myelination in fiber tracts (
      • Charlton R.A.
      • Barrick T.R.
      • Lawes I.N.
      • Markus H.S.
      • Morris R.G.
      White matter pathways associated with working memory in normal aging.
      ).
      In summary, our results show that there are detectable effects on functional and structural connectivity after CRT in patients with schizophrenia. Despite the beneficial effects demonstrated in this study, these findings need to be interpreted in the context of a number of important limitations. In all likelihood, the current pretest/posttest design is, unfortunately, too weak to fully characterize the dynamics of change over time. Moreover, the version of the cognitive task we used in the scanning (0-back vs. 2-back comparison) has not allowed us to characterize properly the clinical improvement due to CRT. Other obvious problem is the role of pharmacologic treatment in cognitive improvement. An important challenge for clinical research will be to investigate combinations of cognitive training with specific pharmacologic treatments (
      • Swerdlow N.R.
      Are we studying and treating schizophrenia correctly?.
      ,
      • Swerdlow N.R.
      Beyond antipsychotics: Pharmacologically-augmented cognitive therapies (PACTs) for schizophrenia.
      ). Furthermore, although there is some evidence of the durability of the effects of CRT (
      • Wykes T.
      • Reeder C.
      • Williams C.
      • Corner J.
      • Rice C.
      • Everitt B.
      Are the effects of cognitive remediation therapy (CRT) durable? Results from an exploratory trial in schizophrenia.
      ,
      • Fisher M.
      • Holland C.
      • Subramaniam K.
      • Vinogradov S.
      Neuroplasticity-based cognitive training in schizophrenia: An interim report on the effects 6 months later.
      ), it is unclear from this study what the long-term consequences of training in brain functions might be.
      This study was supported by Fondo de Investigación sanitaria (FIS) Grant No. PI 07/0258 (to RP) and Rio Hortega Institut d'Investigació Biomèdica Agust Pi i Sunyer (IDIBAPS) (NP) from the Instituto de Salud Carlos III.
      The authors report no biomedical financial interests or potential conflicts of interest.
      Clinicaltrials.gov: Effects of Cognitive Remediation Therapy on Schizophrenia Patients Through Functional Magnetic Resonance Imaging; http://clinicaltrials.gov/ct2/show/NCT01318850; NCT01318850.

      Appendix A. Supplementary material

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      • Erratum
        Biological PsychiatryVol. 75Issue 5
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          Erratum to: “Brain Effects of Cognitive Remediation Therapy in Schizophrenia: A Structural and Functional Neuroimaging Study” by Penadés et al. which appeared in Biological Psychiatry (2013;73:1015–1023).
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