Cognitive Training in Mental Disorders: Update and Future Directions
Publication: American Journal of Psychiatry
Abstract
Objective
This article reviews the conceptual basis, definitions, and evolution of cognitive training approaches for the treatment of mental disorders.
Method
The authors review the current state of the knowledge on cognitive training in psychiatric illnesses, and its neural and behavioral targets, and summarize the factors that appear to relate to a successful response, including learner characteristics that influence clinical outcome. They also discuss methodological issues relevant to the development and testing of cognitive training approaches, with the goal of creating maximally efficient and effective approaches to training. Finally, they identify gaps in existing knowledge and outline key research directions for the future.
Results
While much of the early research has been conducted in schizophrenia, cognitive training has more recently been applied to a widening range of neuropsychiatric illnesses, including attention deficit hyperactivity disorder, mood disorders, and substance use disorders. Cognitive training harnesses the inherent neuroplastic capacities of the brain, targeting neural system function across psychiatric disorders, thus improving the cognitive processes that play a role in emotion regulation, clinical symptoms, and adaptive community functioning.
Conclusions
Cognitive training offers considerable promise, especially given the limited efficacy of pharmacological interventions in ameliorating cognitive deficits. However, more research is needed to understand the mechanisms underlying cognitive training, predictors of response, generalization and real-world applicability, and approaches to dissemination in practice settings.
Introduction
On April 9 and 10, 2012, the National Institute of Mental Health convened a group of experts in cognitive training to review the current state of evidence for the efficacy of current and emerging cognitive training approaches for mental disorders, to identify challenges as well as research gaps, and to learn of efforts to adopt cognitive training interventions in clinical practice. Cognitive training methods that harness neuroplasticity mechanisms for cognitive enhancement in impaired neural systems show promise as evidence-based interventions in psychiatry. The meeting participants expressed optimism that one day in the not-too-distant future we will be able to identify the key neural system impairments unique to individual patients and prescribe personalized cognitive training programs in order to enhance cognition, improve community functioning, and optimize well-being.
Cognitive training is one of a range of behavioral interventions for cognitive enhancement (Figure 1) that also includes exercise, mindfulness-based meditation practice, and other approaches (including the more nonspecific cognitive and socio-affective engagement that can occur in psychotherapy). Cognitive training in psychiatry uses diverse approaches (paper and pencil, computer-administered exercises, or guided behavioral exercises) to enhance cognitive function and optimize well-being in mental disorders.
FIGURE 1. Taxonomy of Approaches to Cognitive Enhancements in Mental Illnessa
a Cognitive training is one of many potential interventions to enhance cognitive functioning.
How is Cognitive Training Defined?
The terms cognitive training, cognitive remediation, and cognitive rehabilitation are used both interchangeably and inconsistently in the literature and in clinical practice. We herein broadly define cognitive training as an intervention that uses specifically designed and behaviorally constrained cognitive or socio-affective learning events, delivered in a scalable and reproducible manner, to potentially improve neural system operations. The eventual goal of cognitive training is to target known neural mechanisms of behavioral impairment to affect clinical change.
Cognitive training aims to drive learning and adaptive neuroplastic changes in an individual’s neural representational systems through specifically defined, neuroscience-based, and controlled learning events. Specifically defined and controlled learning events that are delivered in cognitive training differ from the relatively unconstrained, uncontrolled, and unpredictable approaches to learning, e.g., those associated with cognitive-behavioral therapy or with the use of a psychoeducational video tutorial. We also distinguish cognitive training from the broad and nonspecific (although therapeutically important) forms of cognitive and socio-affective stimulation that occur, for example, from participating in a 12-step program or by joining a community organization such as a church group. Cognitive training as defined above is typically embedded in a larger therapeutic context that makes use of therapist and participant expectancy, the instillation of hope, and other psychosocial ingredients. These factors are themselves all potent agents of neurobehavioral change. Indeed, cognitive training, like many successful treatment programs (such as group therapies, vocational rehabilitation, and psychosocial skills training) explicitly harnesses multiple nonspecific and contextual therapeutic factors in order to maximize overall functional gains for participants.
Another term that is applied in the field is cognitive remediation, which the Cognitive Remediation Expert Working Group has defined as “a behavioral training-based intervention that aims to improve cognitive processes with the general aim of durability and generalization to community functioning” in Wykes et al. (1). In our article, we emphasize the term “training” as opposed to “remediation,” since the former carries less stigma and implies the improvement or restoration of physiological mechanisms in individuals at all levels of functioning, while the latter implies the correction of a fault or deficiency and may also include the development of compensatory or “work-around” skills.
Mental Illness, Neuroplasticity, and Cognitive Training
Clinical interest in “brain remediation” dates back to World War I (2) when methods were developed to treat war-related brain injuries in soldiers. However, emerging basic and clinical research has motivated a theory-driven design of cognitive training approaches, with an emphasis on harnessing the brain’s inherent capacities for change in order to promote or restore adaptive cognitive and socio-affective processes. How might this principle be applied in mental illnesses? First, mental illnesses can be broadly viewed as resulting from inefficient, maladaptive, or biased distributed neural representations underlying critical cognitive and emotional processes that are necessary for successful community functioning (Figure 2). Second, experimental neuroscience has unequivocally revealed that the brain changes with the introduction of new experiences and with the training of new perceptual, cognitive, or motor skills—a process termed neuroplasticity.
FIGURE 2. Translational Hierarchy of Outcomes With Cognitive Therapya
a Carefully targeted improvements in neural system function in mental illness should translate into better community functioning via their effects on cognition.
Neuroplasticity occurs in at least two (not mutually exclusive) developmental contexts (Figure 3). Very early in development, experience and its resulting neuronal activity can shape neuronal response properties irrespective of an organism’s attention to a stimulus. This process of experience-expectant neuroplasticity (3) shapes neural representations to reflect statistical regularities in inputs (e.g., from one eye versus another [4]) and in the environment (5). Such plasticity is often conceptualized to occur within a finite window, a so-called critical period. Maladaptive experiences or insults to the developing brain during these critical periods can have lasting behavioral consequences.
FIGURE 3. Critical Windows of Neuroplasticity During Human Lifea
a Cognitive training makes use of experience-dependent plasticity that is present throughout the human lifespan.
A qualitatively different process, experience-dependent neuroplasticity, occurs throughout development. Also termed “learning,” this process involves changes in neuronal activity that represents meaningful stimuli and behaviors, particularly those associated with reward; such activity in turn effects lasting neural representations (6–12). Maladaptive or distorted learning about behaviorally important events or stimuli (particularly during the extended critical period for socio-affective development), followed by enduring alterations in neural representations, can serve as a model for how psychiatric symptoms first emerge precipitously or insidiously, and then stabilize and become chronic.
Neuroplastic processes related to learning can be intentionally harnessed for therapeutic purposes across a wide range of disorders. Cognitive training focuses on identifying the impaired representational systems underlying critical cognitions and then training such processes via implicit or explicit learning mechanisms in order to improve the speed and accuracy of task-relevant information processing and distributed neural responses, thereby improving community functioning. Growing knowledge of the specific processing anomalies, developmental features, and distributed neural circuits that characterize various psychiatric illnesses will inform the next generation of cognitive training approaches, including their content and timing. This development will require a constant iterative process that bridges cognitive, affective, and developmental neuroscience with clinical treatment development.
Neural Targets for Cognitive Training in Mental Illness
Cognitive or socio-affective deficits are found in all major neuropsychiatric disorders, often predate the symptoms, and may determine functional outcomes (13–15). Such disturbances may reflect aberrant neural representations involving affect regulation, motivation, incentive salience, self and other, and social perception (15). Emerging evidence shows that targeted intensive cognitive training can induce more normal and efficient neural system operations and can potentially harness inherent plasticity processes (16). Improving neural functioning at the macrocircuit level may de facto affect cellular and synaptic-level functioning at the microcircuit level, including the neurotransmitter and neurotrophin systems (17).
Relevant distributed neural system targets are being identified for such intensive cognitive training approaches in mental illness. Successful cognitive training can harness “bottom-up” or “feed-forward” processes (such as perception and preattentive perceptual biasing) and “top-down” or “feed-back” processes (e.g., attention, cognitive control, and metacognitive appraisal), as will be discussed later. In schizophrenia, for example, these targets range from impairments in sensory encoding to inefficient prefrontal operations that affect working memory, episodic memory, and social cognition (16). As observed in major depression, impairments in executive function and processing speed related to aberrant activity in prefrontal and limbic system networks are associated with affect dysregulation (18–20) and abnormal biasing of attention to negative cognitions (21). Thus, disorders are characterized by both distinct and cross-cutting patterns of neural dysfunction, offering unique combinations of cognitive and socio-affective targets for training. However, the ultimate goal is to identify target processes in which training will induce the widest range of generalized clinical and behavioral improvement. For example, inefficiencies or biases in prefrontal predictive and cognitive control operations may represent a fundamental or common denominator underlying a range of mental illnesses, resulting in disorder-specific or cross-diagnostic impairments or biases in perception, affect, and cognition (22). Such processes may represent promising cognitive training targets, not only as a treatment, but potentially as a preventive or preemptive intervention. However, challenges to this approach include the fact that no current assessment or intervention approaches address single neural system targets, nor is this likely to ever be the case; changes in one brain system (e.g., attention) inevitably affect other systems (such as working memory).
Current State of Knowledge
Cognitive training approaches have been applied across various mental illnesses and have used a variety of methods and study designs, making it currently difficult to integrate findings, draw definitive conclusions, or suggest best practices. Study outcomes have also revealed varying efficacy in targeted cognitive domains, while others have demonstrated generalization or transfer to untrained domains and to functional outcome; only a few studies have examined issues of durability beyond the end of treatment. We briefly review the current state of knowledge, beginning with the areas with the strongest evidence base.
Schizophrenia.
Several cognitive training approaches have been studied in schizophrenia, ranging from repetitive practice to therapist-guided strategy coaching. These approaches have targeted a wide range of cognitive processes, including perception, working memory, attention, and social cognition, or combinations of these functions. A meta-analysis of 40 studies conducted between 1973 and 2009 (1) found modest efficacy, with a mean effect size on cognition of 0.45; some cognitive training benefits appear durable after the end of treatment (23, 24). Functional outcomes were significantly better in studies where cognitive remediation was combined with other forms of rehabilitation and when it included strategy coaching. Age, pretreatment cognitive function, motivation, clinician expertise, therapeutic alliance, and measures of “brain reserve” may in certain cases be predictors of a positive treatment response (25–28). Initial neuroimaging findings suggest that cognitive training response is associated with structural and functional changes in key prefrontal brain regions (16, 26, 27, 29, 30). Overall, the evidence thus far supports the neurobiological rationale and the efficacy of cognitive training in schizophrenia, but replication of positive results is needed; many questions remain with regard to therapeutic mechanisms, key therapeutic ingredients, and approaches to dissemination in routine clinical settings.
Attention deficit hyperactivity disorder (ADHD).
Cognitive training, focused on executive functioning and working memory, may benefit individuals with ADHD (31–33). Klingberg et al. (34) demonstrated that cognitive training improved working memory as well as nontrained functions of response inhibition and reasoning; parent-rated inattention and hyperactivity/impulsivity symptoms also decreased after cognitive training, and the positive effects were maintained at 3 months. Such improvements appear to be related to increased activity in the frontoparietal and striatal regions mediating working memory functions in ADHD (35). In an open-label study of preschool-age children with ADHD and their parents, who participated in group sessions, Halperin et al. (36) used motor activities and games designed to enhance inhibitory control, working memory, attention, visuospatial abilities, planning, and motor skills. Parental involvement facilitated the implementation of this play-based intervention at home. Both parent and teacher ratings indicated significant improvement in ADHD symptoms. Similarly, an open trial of metacognitive executive function training for ADHD resulted in improved attention, working memory, and cognitive flexibility (37). Cognitive training targets for ADHD may need to be broadened to include self-control or delay aversion (38). Taken together, cognitive training appears effective in the treatment of ADHD, but well-powered and well-controlled randomized trials with precisely defined targets and outcome measures, as well as longitudinal follow-up to examine durability, are needed.
Anxiety disorders.
Anxiety disorders are characterized by implicit attentional biases to threat-related stimuli (39). This has led investigators to develop attention bias modification strategies, where response targets are repetitively presented at the location of neutral stimuli, rather than threat stimuli, with the goal of inducing an implicit bias away from threat in order to reduce overall anxiety levels. Two meta-analyses of attention bias modification training in adults with anxiety disorders (40, 41) revealed moderate to large effect sizes (0.8–1.4) for changes in attentional bias, and an effect size of 0.61 for clinical symptoms, comparable to what is seen with cognitive-behavioral therapy and selective serotonin reuptake inhibitors. Reductions in anxiety symptoms were also observed in a large randomized controlled trial of children with anxiety disorders (42). Critical next steps include determining the components of successful training (stimuli, optimal task design, and training duration) and the neural mechanisms that support behavioral change, demonstrating the robustness and durability of the effects of attention bias modification on subjective experiences and real-world functioning, and developing approaches to dissemination in routine clinical settings.
Mood disorders.
Emerging research indicates that major depressive disorder and bipolar disorder are both associated with persistent cognitive impairment in domains such as processing speed and executive functioning. In addition to these impairments in “cold” cognition (43–47), depression is associated with attentional bias to negative emotional stimuli, even at a level below awareness (40–43). Emerging evidence suggests (18) that cognitive training can be effective in mood disorders. Deckersbach et al. (48) found that a 14-session remediation program targeting residual depressive symptoms and cognitive functioning was associated with decreased ratings of depression and improved executive functioning scores that were related to better work functioning. A meta-analysis (49) found an effect size of 0.32 for cognitive training in studies with patients with affective or schizoaffective disorders. Attentional bias training in depression seems to potentially reduce relapse risk in depression (50). Further studies need to examine specificity, durability, mechanisms, and generalization of cognitive training effects in mood disorders.
Substance use disorders.
Substance use disorders are associated with a range of cognitive impairments, particularly in attention, working memory, response inhibition, and delay discounting (i.e., preference for immediate versus delayed rewards), which predict poor outcome and adherence to treatment. Although the nature, course, and significance of these deficits are unclear at present, cognitive training is under active investigation in this field. For instance, cognitive training on computerized working memory tasks has been shown to reduce impulsivity and delay discounting among stimulant users (51). Cognitive bias modification (brief training to automatically avoid alcohol cues) has also shown promise in treating alcohol addiction patients during a 1-year follow-up (52). While promising, the field is in its early stages and many questions still need to be addressed. For example, it remains unclear whether cognitive training approaches might work generally for individuals with substance use disorders, or whether they need to be reserved for those with demonstrable cognitive impairments (53). In addition, the cognitive targets that will result in the highest yield clinical outcomes are as of yet unknown.
Autism spectrum disorders (ASDs).
There is an emerging trend toward the use of social cognition training in ASDs, although the field is in its infancy (54). Eack et al. (55) observed significant improvement (effect size >1) in cognition, social cognition, and overall functioning in a preliminary study of individuals with ASDs treated with cognitive enhancement therapy, which combines computerized neurocognitive and social-cognitive remediation with social skills group therapy. Another approach has focused on computerized methods that promote a holistic approach to face processing, which is known to be abnormal in ASDs (56). Overall, cognitive training research in children and adults with ASDs is currently very limited and needs to capitalize on emerging findings of neurocognitive and neural system impairments in these illnesses.
Other disorders.
Cognitive training applications in other brain disorders will be briefly mentioned here, but the details are beyond the scope of this review. Cognitive training directed at enhancing phonological awareness and auditory processing, related to impaired left parietotemporal cortex engagement, is effective in the treatment of dyslexia (57). Several studies have examined the effects of cognitive training interventions in mild cognitive impairments in older adults and have found promising but inconclusive results; it is unclear if cognitive training interventions affect the conversion rates from mild cognitive impairment to dementia (58). There is also evidence for the benefits of cognitive training in traumatic brain injury and stroke (59); however, overall the current evidence on the efficacy and utility of cognitive training approaches in stroke and other acquired brain disease remains insufficient (60).
Predictors and Moderators of Response to Cognitive Training
Learner Characteristics
Age and neurodevelopmental effects.
Few studies have systematically examined the effects of age or neurodevelopmental stage on the response to cognitive training. “Sensitive periods,” when specific neural systems are undergoing rapid change, may provide windows of opportunity during which cognitive training could have a particularly potent effect. Early adolescence, characterized by a heightened sensitivity to reward and the rapid development of cognitive control systems, may be one such period.
Cognitive training delivered as a preventive or preemptive intervention may diminish the cascading effects of psychopathology, at both the neural and environmental levels; such an intervention could potentially be used to prevent increasing deterioration in role functioning as well as the development of comorbidities. Such potential effects have been shown with early (childhood) interventions in anxiety (42), ADHD (61), and depression (62). This view is being tested in animal models as well; a study (63) showed that “adolescent” cognitive training in juvenile rats prevented adult cognitive control impairment in rats with neonatal ventral hippocampus lesions, an established neurodevelopmental model of schizophrenia. Clearly, once effective cognitive training approaches have been developed, they will prove highly useful if delivered preemptively across a broad range of psychopathologies.
Genotype.
Given that genetic factors regulate plasticity and cognition, genotype will likely moderate response to cognitive training in people with mental illnesses. Genetic variability related to the catechol O-methyltransferase (COMT) gene (Val158Met polymorphism), a gene regulating prefrontal dopamine levels, has been investigated as one such factor. Bosia et al. (64) reported a greater response to cognitive training in schizophrenia patients who were COMT Met carriers, although no such relationship was observed by Greenwood et al. (65). However, using an intensive computerized cognitive training paradigm in schizophrenia patients, Panizzutti et al. (66) showed an association between eight single nucleotide polymorphisms at the 3′ end of the COMT gene and global cognition improvement (66). Brain-derived neurotrophic factor (BDNF) polymorphisms have been associated with greater gains in response to cognitive training in older adults (67). Genetic factors may interact with one another; in healthy adults, the interaction of BDNF with COMT polymorphisms demonstrates a clear role in human cortical plasticity, and genotype-related differences in neurophysiology translate into behavioral differences (68). Given the large sample sizes needed from well-defined clinical trials to determine the relationship of genotype to behavioral outcome, it will be many years before we have definitive answers on the role of specific genes and gene interactions in cognitive training response.
Cognitive function and brain reserve.
Baseline cognitive function may be a moderator of outcome with cognitive training (69, 70). Keshavan et al. (28) demonstrated that pretreatment neurobiological reserve, operationalized as whole-brain surface area and gray matter volume, significantly moderated the effects of cognitive enhancement therapy (computerized cognitive training plus group-based social skills practice) in early-course schizophrenia. Greater reserve predicted a more rapid social-cognitive response to cognitive enhancement therapy in the first year of treatment, while individuals with less reserve responded at a slower rate. The lower gray matter volume at baseline may itself reflect an underlying pathophysiological process with an adverse impact on plasticity or previous environmental insults and stressors that have affected neural substrates. The ability to improve basic auditory processing speed during cognitive training in schizophrenia may be related to the overall cognitive gains made by individuals (71), suggesting that an inherent psychophysical learning capacity influences the response to training. Baseline cognitive and neuroplastic potential may thus predict treatment response; lower reserve may require adjunctive physical exercise interventions, pharmacological enhancement (72), or neuromodulation (73), as discussed below.
Motivation and emotional state.
Factors linked to motivation, self-efficacy, and emotional state clearly play an important role in treatment response to cognitive training. For example, in healthy individuals motivational state exerts both local and global neural effects on cognitive control operations, while a positive mood enhances prefrontal activation and facilitates creative problem solving (74). Intrinsic motivation can best be fostered by providing a personalized context that links cognitive training to goals of everyday life and by promoting autonomy so that aspects of the training can be tailored to the learning style and goals of each participant (75). In addition, internalized beliefs influence cortical responses to feedback during learning (76) and are likely to moderate response to cognitive training. Finally, interindividual variations in reward sensitivity predict rates of learning, and will need to be the focus of future studies (77).
Features of Training
Training approaches.
The field is barely at the threshold of understanding the key “active ingredients” for the development of training methods that maximize cognitive and functional gains in patients with mental illness. As discussed earlier, cognitive training involves varying combinations of top-down or feed-back approaches (training of higher-order metacognitive skills, executive functioning, or strategic techniques) and bottom-up or feed-forward approaches (training of perceptual and attentional skills) (Figure 4). Neurocognitive operations rely on both feed-forward and feed-back operations in the brain, as these processes may not be as distinct as was once thought; their synergistic interactions may be especially critical in impaired brains (e.g., impaired perception can influence higher-order cognition, as degraded bottom-up sensory representations may lead to increased competition for attentional resources) (78). Thus, the field may benefit from describing cognitive training methods in terms of their relative emphasis on these levels of operations as well as their emphasis on implicit versus explicit learning methods (15). “Bridge” groups (19) are an example of a top-down approach that is often combined with computerized cognitive training in order to help patients apply newly acquired cognitive skills to real-world situations and promote socialization. As the field moves forward in developing targeted cognitive training methods, the key challenges will be to identify and engineer precisely defined learning trials relevant to the neural system impairments of interest, and to elucidate their behavioral and neural effects in both healthy and impaired brains.
Intensity and progression of training.
Several principles for achieving robust and specific integration of neural representations have been proposed and supported (15). A desired skill has to be practiced through repetitive trials on an intensive and frequent schedule. Close engagement of attention and reward systems is needed; with a high proportion of the learning trials being attended to, performed correctly, and immediately rewarded. Individualized adaptation of task difficulty helps to drive learning, so that accurate performance on initial “easy” trials is gradually led toward accurate performance on systematically more difficult trials (scaffolding), while maintaining a high trial-by-trial reward schedule. Learning tasks should drive progressively refined and detailed neural representations of task-relevant stimuli. Finally, learning approaches need to support generalization of improved function to real-world environments (such as through the use of bridging groups) (19). Learning-driven improvements in cognitive and socio-affective operations must generalize to untrained stimuli, tasks, and, most importantly, to cognitively demanding real-world situations.
Adjunctive Cognitive-Enhancing Interventions
Physical exercise.
Physical exercise has important benefits for patients with mental disorders (79). In addition to its important metabolic effects, aerobic exercise has been associated with increased neurogenesis, angiogenesis, and the production of neurotrophic factors such as BDNF involved in neuroprotection and synaptic plasticity (80). One study (81) reported increased hippocampal volume in schizophrenia patients and healthy individuals following 3 months of aerobic exercise (cycling) with no change in a control condition (table football). Schizophrenia patients, but not healthy comparison subjects, exhibited a corresponding increase in hippocampal N-acetylaspartate, a marker of neuronal integrity. Physical exercise may also promote neurocognitive function and development in ADHD (82). Combining cognitive training with physical exercise programs may particularly help psychiatric patients who have been sedentary. However, the field needs a more precise understanding of the effects of specific types of exercise on cognition in mental illness and its potential interactive effects with cognitive training.
Pharmacological agents.
In schizophrenia, the field now agrees that procognitive agents need to be developed and tested in combination with cognitive training in order to obtain maximal behavioral effects (83); these issues also apply to other psychiatric disorders. Examples of procognitive agents include the glycine agonist d-serine, the GlyT1 inhibitor sarcosine, ampakines (84), metabotropic mGlu2/3 agonists, the GABAergic agent MK-0777 (85), modafinil (which has complex effects on multiple neurotransmitter systems), and d-amphetamine (86, 87). Given these various mechanisms of action, drugs with different molecular targets may potentiate cognitive training effects in diverse clinical populations. For example, cholinergic enhancement with donepezil has been found to improve perceptual learning in healthy individuals (88), but its effects in clinical groups are unknown. Dopaminergic and cholinergic agents may potentially enhance reward-related learning and thereby augment cognitive enhancement (89). A great deal of preclinical and clinical work lies ahead.
Brain neuromodulation.
Neuromodulation approaches, such as transcranial magnetic stimulation, transcranial direct current stimulation, and vagal nerve stimulation, can potentially enhance cognition by modulating neuronal excitability (90). The effects of brain stimulation may be determined by the initial neural activation state (91); thus, manipulating neural activation states may allow one to selectively enhance activity in a given neural circuit. Andrews et al. (92) demonstrated that in healthy individuals, transcranial direct current stimulation applied while performing an n-back working memory task resulted in better performance, compared with sham transcranial direct current stimulation and stimulation applied while at rest. Ditye et al. (93) reported that anodal transcranial direct current stimulation combined with cognitive training was able to improve performance on the stop signal task. Animal research indicates that pairing vagal nerve stimulation with specific learning events increases the cortical representations of those events (94). Systematic studies of specific neuromodulatory interventions combined with cognitive training are needed in various clinical populations. It is unclear whether adjunctive neuromodulation will be most useful in illnesses characterized by widespread neural deficits and cortical inefficiency (e.g., schizophrenia) or as a “learning accelerator” in illnesses characterized by more circumscribed representational impairments (e.g., ADHD or anxiety disorders).
Trial Design Issues
Several critical methodological issues must be addressed as the field moves forward in the development and testing of cognitive training approaches for psychiatric illness (Table 1) (95).
| Item | Description |
|---|---|
| Participant characterization | Are potential predictors/moderators (e.g., baseline cognitive function, psychopathology, and neural reserve) assessed? |
| Are inclusion/exclusion criteria (e.g., presence of targeted cognitive capacity/deficits) justified? | |
| Intervention targets | Are cognitive targets (deficits/capacities) linked to clinical status and functioning? |
| Do the cognitive training interventions match the perceptual/cognitive/affective processes that characterize the disorder and/or neural circuits implicated? | |
| Is the hypothesized therapeutic mechanism supported by research and theory? | |
| Outcome assessment | Are potential predictors/moderators (e.g., medications, therapist engagement) of outcomes considered? |
| Do assessments provide for the elucidation of intervention mechanisms (e.g., temporal precedence between putative mediators/mechanisms and target outcomes)? | |
| Are retention/completion rates assessed and reported? | |
| Are cognitive/functional outcomes distinguishable from practice effects? | |
| Are valid measures of proximal (e.g., performance on training tasks, neurocognitive measures) and more distal outcomes (clinical status, functioning, adverse effects, durability, generalization of cognitive and affective outcomes distinct from training tasks) included? | |
| Does the plan include measures at multiple levels of analysis (e.g., genes, molecules, cells, circuits, physiology, behavior, and self-report) as appropriate (64). | |
| Concomitant treatments | Is cognitive training intended as a monotherapy or as an adjunctive treatment? Are concomitant treatments considered in the assessment and analysis plan? |
| How might the proposed concomitant therapies potentiate (e.g., promoting plasticity; generalization of skills) or interfere with (e.g., medication side effects) cognitive training effects? | |
| Are concomitant treatments held constant across treatment conditions and/or quantified and considered in analyses? | |
| Comparison condition | Is the comparison condition justified in terms of the research question and stage of intervention development/testing? |
| Does the comparison condition control for attention, expectations, and potential practice effects associated with training/assessment protocols, as appropriate? | |
| Scalability/potential for dissemination | Are all relevant stakeholders considered (i.e., patients/families [e.g., acceptability], clinicians [availability of an appropriately trained workforce], and policymakers [competing demands, therapist time/involvement, and other costs])? |
| What are the implementation strategies (e.g., delivery within existing services, such as employment training; use of Internet or other facilitative technology for conducting assessments and delivering the intervention; provisions to facilitate motivation/engagement)? | |
| Design considerations | Are randomization procedures clearly detailed and justified? |
| Are intervention protocols standardized and manualized? | |
| Are there plans to monitor fidelity and operationalize the delivery of the experimental and comparison conditions? | |
| Are statistical approaches state of the art and appropriately matched to the research question and data structure? |
First, the etiological and phenotypic heterogeneity of mental disorders makes it unlikely that particular domain-specific neurocognitive deficits will be universal to all individuals within a diagnostic category. Different cognitive phenotypes may have a similar clinical presentation; not all individuals will demonstrate specific cognitive deficits of interest, and specific cognitive deficits may cut across disorders and healthy states (96). This raises the question of how to operationally define caseness in selecting individuals for intervention studies. Thus, if the entry criteria consider only diagnostic criteria without addressing baseline neurocognitive heterogeneity, individuals for whom the proposed cognitive training intervention is not relevant could inadvertently be included in the sample.
Second, if we are to develop prescriptive, personalized intervention strategies, we must design cognitive training studies that include dense multimodal baseline assessments of participants so that we can determine both predictors of treatment response and factors associated with successful target engagement. In this manner, the feasibility of assessing putative moderators, as suggested by theory and research, could be explored in pilot studies. These putative moderators could then be examined in formal moderator analyses in subsequent studies with larger samples. Robust moderators thus identified could then be used as tailoring variables for more prescriptive treatment assignment. For example, neurobiological measures derived from imaging, electrophysiology, or transcranial magnetic stimulation (97) may be used to assess neural reserve or neuroplastic capacity. Genotype, reward sensitivity, motivational state, and internalized beliefs may also be important baseline predictive factors.
Third, understanding the mechanisms driving behavioral change requires us to define the treatment target of the cognitive training intervention under study and to demonstrate target engagement. Accordingly, preliminary proof of concept studies would seek to demonstrate that the intervention results in predicted changes in the hypothesized proximal target (e.g., a specific brain circuit or a psychological process, such as working memory or attention bias). Larger studies would then formally interrogate mediational pathways and examine whether changes in the presumed target mediate or translate into clinical benefit.
We must also control for nonspecific factors such as concomitant therapies that can influence behavioral outcomes unrelated to cognitive training. In schizophrenia (1), meta-analyses suggest that adjunctive psychosocial rehabilitation enhances cognitive training’s impact on functional outcomes, but the specificity of this effect is unclear. Future studies need to quantify extra-protocol interventions and assess outcomes to identify synergistic benefits and develop optimized interventions.
A final but highly important consideration involves the dissemination of cognitive training into practice. Many factors contribute to delays in the research-to-practice translation (98), including fundamental differences between efficacy studies and the usual care context. This research-to-practice gap has prompted calls to rethink the intervention development and testing process. For example, a deployment-focused model of intervention development and testing (99) emphasizes incorporating information from different stakeholder perspectives (e.g., patients, consumers, family members, providers, administrators, insurers, and payers) much earlier in the intervention testing process. Careful consideration of patient characteristics (e.g., common comorbidities), candidate interventions (e.g., scalability, complexity, patient burden, and costs), potential providers (e.g., current competencies and training needs) and settings (e.g., capacity, competing demands, supervision infrastructure, and reimbursement structure) will also likely facilitate the development of more practice-ready, scalable, cost-efficient interventions.
Conclusions and Future Directions
Current evidence indicates that cognitive training interventions can result in significant, albeit modest, improvements in specific cognitive functions (e.g., memory, attention, and problem solving) across a range of mental illnesses. In parallel, the mechanisms underlying neuroplasticity as well as neural circuitry alterations in psychiatric disorders are increasingly well understood. These developments are promising, especially given the limited efficacy of pharmacological interventions in improving cognitive and socio-affective processing. However, the durability and effects of cognitive training (as currently studied) on symptoms and everyday functioning vary across clinical populations and need further study.
The field is in its infancy, and rigorously designed, adequately powered, randomized controlled trials are needed that investigate variability of treatment response, in addition to testing efficacy, and determine mediators and moderators of cognitive training effects. Future studies must also incorporate measures of the hypothesized mechanisms of action and of target engagement, as well as determine the time course and time scale of exposure needed for enduring changes in neurocognition and functioning. The synergistic effects of combining cognitive training with other interventions are another highly promising area of inquiry (e.g., cognitive training plus physical exercise in ADHD or cognitive training plus group social skills training for schizophrenia and autism).
Cognitive training’s promise as a safe, preventive, and early intervention for individuals at younger ages and at earlier stages of illness highlights the need to design engaging and developmentally appropriate methods, which may or may not be computer based. Even more compelling is the prospect of early prodromal detection and intervention for impaired neural systems in order to preempt the onset of full-blown illness. There may even be the possibility of primary prevention of mental disorders if neural biomarkers of vulnerability can be found and improved through cognitive training, although ethical issues related to labeling individuals without overt symptoms will need to be addressed. Finally, our field must develop models to disseminate efficacious cognitive training approaches into community settings, and to emphasize deployment-focused models of intervention development.
Footnote
The opinions and assertions contained in this article are the private views of the authors and are not to be considered as official or as reflecting the views of the Department of Health and Human Services, NIH, or NIMH.
References
1.
Wykes T, Huddy V, Cellard C, McGurk SR, Czobor P: A meta-analysis of cognitive remediation for schizophrenia: methodology and effect sizes. Am J Psychiatry 2011; 168:472–485
2.
Boake C: History of cognitive rehabilitation following head injury, in Cognitive Rehabilitation for Persons With Traumatic Brain Injury: A Functional Approach. Edited by, Kreutzer JS, Wehman PH. Baltimore, Paul H Brookes Pub Co, 1991
3.
Greenough WT, Black JE, Wallace CS: Experience and brain development. Child Dev 1987; 58:539–559
4.
Shatz CJ, Stryker MP: Ocular dominance in layer IV of the cat’s visual cortex and the effects of monocular deprivation. J Physiol 1978; 281:267–283
5.
Coppola DM, Purves HR, McCoy AN, Purves D: The distribution of oriented contours in the real world. Proc Natl Acad Sci USA 1998; 95:4002–4006
6.
Jenkins WM, Merzenich MM, Ochs MT, Allard T, Guíc-Robles E: Functional reorganization of primary somatosensory cortex in adult owl monkeys after behaviorally controlled tactile stimulation. J Neurophysiol 1990; 63:82–104
7.
Recanzone GH, Merzenich MM, Jenkins WM, Grajski KA, Dinse HR: Topographic reorganization of the hand representation in cortical area 3b owl monkeys trained in a frequency-discrimination task. J Neurophysiol 1992; 67:1031–1056
8.
Recanzone GH, Schreiner CE, Merzenich MM: Plasticity in the frequency representation of primary auditory cortex following discrimination training in adult owl monkeys. J Neurosci 1993; 13:87–103
9.
Wang X, Merzenich MM, Sameshima K, Jenkins WM: Remodelling of hand representation in adult cortex determined by timing of tactile stimulation. Nature 1995; 378:71–75
10.
Nudo RJ, Milliken GW, Jenkins WM, Merzenich MM: Use-dependent alterations of movement representations in primary motor cortex of adult squirrel monkeys. J Neurosci 1996; 16:785–807
11.
Cruikshank SJ, Weinberger NM: Evidence for the Hebbian hypothesis in experience-dependent physiological plasticity of neocortex: a critical review. Brain Res Brain Res Rev 1996; 22:191–228
12.
Buonomano DV, Merzenich MM: Cortical plasticity: from synapses to maps. Annu Rev Neurosci 1998; 21:149–186
13.
Spaulding WD, Reed D, Sullivan M, Richardson C, Weiler M: Effects of cognitive treatment in psychiatric rehabilitation. Schizophr Bull 1999; 25:657–676
14.
Kleim JA, Jones TA: Principles of experience-dependent neural plasticity: implications for rehabilitation after brain damage. J Speech Lang Hear Res 2008; 51:S225–S239
15.
Vinogradov S, Fisher M, de Villers-Sidani E: Cognitive training for impaired neural systems in neuropsychiatric illness. Neuropsychopharmacology 2012; 37:43–76
16.
Subramaniam K, Luks TL, Fisher M, Simpson GV, Nagarajan S, Vinogradov S: Computerized cognitive training restores neural activity within the reality monitoring network in schizophrenia. Neuron 2012; 73:842–853
17.
McNab F, Varrone A, Farde L, Jucaite A, Bystritsky P, Forssberg H, Klingberg T: Changes in cortical dopamine D1 receptor binding associated with cognitive training. Science 2009; 323:800–802
18.
Bowie CR, Gupta M, Holshausen K: Cognitive remediation therapy for mood disorders: rationale, early evidence, and future directions. Can J Psychiatry 2013; 58:319–325
19.
Medalia A, Choi J: Cognitive remediation in schizophrenia. Neuropsychol Rev 2009; 19:353–364
20.
Rive MM, van Rooijen G, Veltman DJ, Phillips ML, Schene AH, Ruhé HG: Neural correlates of dysfunctional emotion regulation in major depressive disorder: a systematic review of neuroimaging studies. Neurosci Biobehav Rev 2013; 37:2529–2553
21.
Etkin A, Schatzberg AF: Common abnormalities and disorder-specific compensation during implicit regulation of emotional processing in generalized anxiety and major depressive disorders. Am J Psychiatry 2011; 168:968–978
22.
Arguello PA, Gogos JA: Genetic and cognitive windows into circuit mechanisms of psychiatric disease. Trends Neurosci 2012; 35:3–13
23.
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. Schizophr Res 2003; 61:163–174
24.
Eack SM, Greenwald DP, Hogarty SS, Keshavan MS: One-year durability of the effects of cognitive enhancement therapy on functional outcome in early schizophrenia. Schizophr Res 2010; 120:210–216
25.
Kurtz MM: Cognitive remediation for schizophrenia: current status, biological correlates and predictors of response. Expert Rev Neurother 2012; 12:813–821
26.
Huddy V, Reeder C, Kontis D, Wykes T, Stahl D: The effect of working alliance on adherence and outcome in cognitive remediation therapy. J Nerv Ment Dis 2012; 200:614–619
27.
Kontis D, Huddy V, Reeder C, Landau S, Wykes T: Effects of age and cognitive reserve on cognitive remediation therapy outcome in patients with schizophrenia. Am J Geriatr Psychiatry 2013; 21:218–230
28.
Keshavan MS, Eack SM, Wojtalik JA, Prasad KMR, Francis AN, Bhojraj TS, Greenwald DP, Hogarty SS: A broad cortical reserve accelerates response to cognitive enhancement therapy in early-course schizophrenia. Schizophr Res 2011; 130:123–129
29.
Eack SM, Hogarty GE, Cho RY, Prasad KMR, Greenwald DP, Hogarty SS, Keshavan MS: Neuroprotective effects of cognitive enhancement therapy against gray matter loss in early schizophrenia: results from a 2-year randomized controlled trial. Arch Gen Psychiatry 2010; 67:674–682
30.
Haut KM, Lim KO, MacDonald A: Prefrontal cortical changes following cognitive training in patients with chronic schizophrenia: effects of practice, generalization, and specificity. Neuropsychopharmacology 2010; 35:1850–1859
31.
Beck SJ, Hanson CA, Puffenberger SS, Benninger KL, Benninger WB: A controlled trial of working memory training for children and adolescents with ADHD. J Clin Child Adolesc Psychol 2010; 39:825–836
32.
Holmes J, Gathercole SE, Dunning DL: Adaptive training leads to sustained enhancement of poor working memory in children. Dev Sci 2009; 12:F9–F15
33.
Karbach J, Kray J: How useful is executive control training? age differences in near and far transfer of task-switching training. Dev Sci 2009; 12:978–990
34.
Klingberg T, Fernell E, Olesen PJ, Johnson M, Gustafsson P, Dahlström K, Gillberg CG, Forssberg H, Westerberg H: Computerized training of working memory in children with ADHD: a randomized, controlled trial. J Am Acad Child Adolesc Psychiatry 2005; 44:177–186
35.
Klingberg T: Training and plasticity of working memory. Trends Cogn Sci 2010; 14:317–324
36.
Halperin JM, Marks DJ, Bedard AC, Chacko A, Curchack JT, Yoon CA, Healey DM: Training executive, attention, and motor skills: a proof-of-concept study in preschool children with ADHD. J Atten Disord 2013; 17:711–721
37.
Tamm L, Epstein JN, Peugh JL, Nakonezny PA, Hughes CW: Preliminary data suggesting the efficacy of attention training for school-aged children with ADHD. Dev Cogn Neurosci 2013; 4:16–28
38.
Rutledge KJ, van den Bos W, McClure SM, Schweitzer JB: Training cognition in ADHD: current findings, borrowed concepts, and future directions. Neurotherapeutics 2012; 9:542–558
39.
Bar-Haim Y, Lamy D, Pergamin L, Bakermans-Kranenburg MJ, van IJzendoorn MH: Threat-related attentional bias in anxious and nonanxious individuals: a meta-analytic study. Psychol Bull 2007; 133:1–24
40.
Hakamata Y, Lissek S, Bar-Haim Y, Britton JC, Fox NA, Leibenluft E, Ernst M, Pine DS: Attention bias modification treatment: a meta-analysis toward the establishment of novel treatment for anxiety. Biol Psychiatry 2010; 68:982–990
41.
Beard C, Sawyer AT, Hofmann SG: Efficacy of attention bias modification using threat and appetitive stimuli: a meta-analytic review. Behav Ther 2012; 43:724–740
42.
Eldar S, Apter A, Lotan D, Edgar KP, Naim R, Fox NA, Pine DS, Bar-Haim Y: Attention bias modification treatment for pediatric anxiety disorders: a randomized controlled trial. Am J Psychiatry 2012; 169:213–220
43.
Bowie CR, McGurk SR, Mausbach B, Patterson TL, Harvey PD: Combined cognitive remediation and functional skills training for schizophrenia: effects on cognition, functional competence, and real-world behavior. Am J Psychiatry 2012; 169:710–718
44.
Lee RSC, Hermens DF, Porter MA, Redoblado-Hodge MA: A meta-analysis of cognitive deficits in first-episode major depressive disorder. J Affect Disord 2012; 140:113–124
45.
Xu G, Lin K, Rao D, Dang Y, Ouyang H, Guo Y, Ma J, Chen J: Neuropsychological performance in bipolar I, bipolar II and unipolar depression patients: a longitudinal, naturalistic study. J Affect Disord 2012; 136:328–339
46.
Yang W, Zhu X, Wang X, Wu D, Yao S: Time course of affective processing bias in major depression: an ERP study. Neurosci Lett 2011; 487:372–377
47.
Victor TA, Furey ML, Fromm SJ, Bellgowan PSF, Öhman A, Drevets WC: The extended functional neuroanatomy of emotional processing biases for masked faces in major depressive disorder. PLoS ONE 2012; 7:e46439
48.
Deckersbach T, Nierenberg AA, Kessler R, Lund HG, Ametrano RM, Sachs G, Rauch SL, Dougherty D: RESEARCH: Cognitive rehabilitation for bipolar disorder: an open trial for employed patients with residual depressive symptoms. CNS Neurosci Ther 2010; 16:298–307
49.
Anaya C, Martinez Aran A, Ayuso-Mateos JL, Wykes T, Vieta E, Scott J: A systematic review of cognitive remediation for schizo-affective and affective disorders. J Affect Disord 2012; 142:13–21
50.
Browning M, Grol M, Ly V, Goodwin GM, Holmes EA, Harmer CJ: Using an experimental medicine model to explore combination effects of pharmacological and cognitive interventions for depression and anxiety. Neuropsychopharmacology 2011; 36:2689–2697
51.
Bickel WK, Yi R, Landes RD, Hill PF, Baxter C: Remember the future: working memory training decreases delay discounting among stimulant addicts. Biol Psychiatry 2011; 69:260–265
52.
Wiers RW, Eberl C, Rinck M, Becker ES, Lindenmeyer J: Retraining automatic action tendencies changes alcoholic patients’ approach bias for alcohol and improves treatment outcome. Psychol Sci 2011; 22:490–497
53.
Sofuoglu M, DeVito EE, Waters AJ, Carroll KM: Cognitive enhancement as a treatment for drug addictions. Neuropharmacology 2013; 64:452–463
54.
Bishop-Fitzpatrick L, Minshew NJ, Eack SM: A systematic review of psychosocial interventions for adults with autism spectrum disorders. J Autism Dev Disord 2013; 43:687–694
55.
Eack SM, Greenwald DP, Hogarty SS, Bahorik AL, Litschge MY, Mazefsky CA, Minshew NJ: Cognitive enhancement therapy for adults with autism spectrum disorder: results of an 18-month feasibility study. J Autism Dev Disord 2013; 43:2866–2877
56.
Damiano C, Churches O, Ring H, Baron-Cohen S: The development of perceptual expertise for faces and objects in autism spectrum conditions. Autism Res 2011; 4:297–301
57.
Gabrieli JDE: Dyslexia: a new synergy between education and cognitive neuroscience. Science 2009; 325:280–283
58.
Huckans M, Hutson L, Twamley E, Jak A, Kaye J, Storzbach D: Efficacy of cognitive rehabilitation therapies for mild cognitive impairment (MCI) in older adults: working toward a theoretical model and evidence-based interventions. Neuropsychol Rev 2013; 23:63–80
59.
Cicerone KD, Langenbahn DM, Braden C, Malec JF, Kalmar K, Fraas M, Felicetti T, Laatsch L, Harley JP, Bergquist T, Azulay J, Cantor J, Ashman T: Evidence-based cognitive rehabilitation: updated review of the literature from 2003 through 2008. Arch Phys Med Rehabil 2011; 92:519–530
60.
Chung CSY, Pollock A, Campbell T, Durward BR, Hagen S: Cognitive rehabilitation for executive dysfunction in adults with stroke or other adult non-progressive acquired brain damage. Cochrane Database Syst Rev 2013; 4:CD008391
61.
Klingberg T: Computerized training of working memory in children with ADHD. Eur Neuropsychopharmacol 2007; 17:S192–S193
62.
Browning M, Holmes EA, Charles M, Cowen PJ, Harmer CJ: Using attentional bias modification as a cognitive vaccine against depression. Biol Psychiatry 2012; 72:572–579
63.
Lee H, Dvorak D, Kao H-Y, Duffy ÁM, Scharfman HE, Fenton AA: Early cognitive experience prevents adult deficits in a neurodevelopmental schizophrenia model. Neuron 2012; 75:714–724
64.
Bosia M, Bechi M, Marino E, Anselmetti S, Poletti S, Cocchi F, Smeraldi E, Cavallaro R: Influence of catechol-O-methyltransferase Val158Met polymorphism on neuropsychological and functional outcomes of classical rehabilitation and cognitive remediation in schizophrenia. Neurosci Lett 2007; 417:271–274
65.
Greenwood K, Hung C-F, Tropeano M, McGuffin P, Wykes T: No association between the Catechol-O-Methyltransferase (COMT) val158met polymorphism and cognitive improvement following cognitive remediation therapy (CRT) in schizophrenia. Neurosci Lett 2011; 496:65–69
66.
Panizzutti R, Hamilton SP, Vinogradov S: Genetic correlate of cognitive training response in schizophrenia. Neuropharmacology 2013; 64:264–267
67.
Colzato LS, van Muijden J, Band GPH, Hommel B: Genetic modulation of training and transfer in older adults: BDNF ValMet polymorphism is associated with wider useful field of view. Front Psychol 2011; 2:199
68.
Witte AV, Kürten J, Jansen S, Schirmacher A, Brand E, Sommer J, Flöel A: Interaction of BDNF and COMT polymorphisms on paired-associative stimulation-induced cortical plasticity. J Neurosci 2012; 32:4553–4561
69.
Kurtz MM, Wexler BE, Fujimoto M, Shagan DS, Seltzer JC: Symptoms versus neurocognition as predictors of change in life skills in schizophrenia after outpatient rehabilitation. Schizophr Res 2008; 102:303–311
70.
Fiszdon JM, Cardenas AS, Bryson GJ, Bell MD: Predictors of remediation success on a trained memory task. J Nerv Ment Dis 2005; 193:602–608
71.
Fisher M, Holland C, Merzenich MM, Vinogradov S: Using neuroplasticity-based auditory training to improve verbal memory in schizophrenia. Am J Psychiatry 2009; 166:805–811
72.
Floel A, Garraux G, Xu B, Breitenstein C, Knecht S, Herscovitch P, Cohen LG: Levodopa increases memory encoding and dopamine release in the striatum in the elderly. Neurobiol Aging 2008; 29:267–279
73.
Hummel F, Cohen LG: Improvement of motor function with noninvasive cortical stimulation in a patient with chronic stroke. Neurorehabil Neural Repair 2005; 19:14–19
74.
Subramaniam K, Kounios J, Parrish TB, Jung-Beeman M: A brain mechanism for facilitation of insight by positive affect. J Cogn Neurosci 2009; 21:415–432
75.
Medalia A, Saperstein A: The role of motivation for treatment success. Schizophr Bull 2011; 37(suppl 2):S122–S128
76.
Mangels JA, Butterfield B, Lamb J, Good C, Dweck CS: Why do beliefs about intelligence influence learning success? a social cognitive neuroscience model. Soc Cogn Affect Neurosci 2006; 1:75–86
77.
Flagel SB, Clark JJ, Robinson TE, Mayo L, Czuj A, Willuhn I, Akers CA, Clinton SM, Phillips PE, Akil H: A selective role for dopamine in stimulus-reward learning. Nature 2011; 469:53–57
78.
Adcock RA, Dale C, Fisher M, Aldebot S, Genevsky A, Simpson GV, Nagarajan S, Vinogradov S: When top-down meets bottom-up: auditory training enhances verbal memory in schizophrenia. Schizophr Bull 2009; 35:1132–1141
79.
Knöchel C, Oertel-Knöchel V, O’Dwyer L, Prvulovic D, Alves G, Kollmann B, Hampel H: Cognitive and behavioural effects of physical exercise in psychiatric patients. Prog Neurobiol 2012; 96:46–68
80.
Kramer AF, Erickson KI: Capitalizing on cortical plasticity: influence of physical activity on cognition and brain function. Trends Cogn Sci 2007; 11:342–348
81.
Pajonk FG, Wobrock T, Gruber O, Scherk H, Berner D, Kaizl I, Kierer A, Müller S, Oest M, Meyer T, Backens M, Schneider-Axmann T, Thornton AE, Honer WG, Falkai P: Hippocampal plasticity in response to exercise in schizophrenia. Arch Gen Psychiatry 2010; 67:133–143
82.
Berwid OG, Halperin JM: Emerging support for a role of exercise in attention-deficit/hyperactivity disorder intervention planning. Curr Psychiatry Rep 2012; 14:543–551
83.
Chou H-H, Twamley E, Swerdlow NR: Towards medication-enhancement of cognitive interventions in schizophrenia. Handb Exp Pharmacol 2012; 213:81–111
84.
Arai AC, Kessler M: Pharmacology of ampakine modulators: from AMPA receptors to synapses and behavior. Curr Drug Targets 2007; 8:583–602
85.
Buchanan RW, Keefe RSE, Lieberman JA, Barch DM, Csernansky JG, Goff DC, Gold JM, Green MF, Jarskog LF, Javitt DC, Kimhy D, Kraus MS, McEvoy JP, Mesholam-Gately RI, Seidman LJ, Ball MP, McMahon RP, Kern RS, Robinson J, Marder SR: A randomized clinical trial of MK-0777 for the treatment of cognitive impairments in people with schizophrenia. Biol Psychiatry 2011; 69:442–449
86.
Minzenberg MJ, Carter CS: Developing treatments for impaired cognition in schizophrenia. Trends Cogn Sci 2012; 77:35–42
87.
Barch DM, Carter CS: Amphetamine improves cognitive function in medicated individuals with schizophrenia and in healthy volunteers. Schizophr Res 2005; 77:43–58
88.
Rokem A, Silver MA: Cholinergic enhancement augments magnitude and specificity of visual perceptual learning in healthy humans. Curr Biol 2010; 20:1723–1728
89.
Acheson DT, Twamley EW, Young JW: Reward learning as a potential target for pharmacological augmentation of cognitive remediation for schizophrenia: a roadmap for preclinical development. Front Neurosci 2013; 7:103
90.
Miniussi C, Cappa SF, Cohen LG, Floel A, Fregni F, Nitsche MA, Oliveri M, Pascual-Leone A, Paulus W, Priori A, Walsh V: Efficacy of repetitive transcranial magnetic stimulation/transcranial direct current stimulation in cognitive neurorehabilitation. Brain Stimulat 2008; 1:326–336
91.
Silvanto J, Muggleton N, Walsh V: State-dependency in brain stimulation studies of perception and cognition. Trends Cogn Sci 2008; 12:447–454
92.
Andrews SC, Hoy KE, Enticott PG, Daskalakis ZJ, Fitzgerald PB: Improving working memory: the effect of combining cognitive activity and anodal transcranial direct current stimulation to the left dorsolateral prefrontal cortex. Brain Stimulat 2011; 4:84–89
93.
Ditye T, Jacobson L, Walsh V, Lavidor M: Modulating behavioral inhibition by tDCS combined with cognitive training. Exp Brain Res 2012; 219:363–368
94.
Porter BA, Khodaparast N, Fayyaz T, Cheung RJ, Ahmed SS, Vrana WA, Rennaker RL, Kilgard MP: Repeatedly pairing vagus nerve stimulation with a movement reorganizes primary motor cortex. Cereb Cortex 2012; 22:2365–2374
95.
Sherrill JT, Sommers DI, Nierenberg AA, Leon AC, Arndt S, Bandeen-Roche K, Greenhouse J, Guthrie D, Normand SL, Phillips KA, Shear MK, Woolson R: Integrating statistical and clinical research elements in intervention-related grant applications: summary from an NIMH workshop. Acad Psychiatry 2009; 33:221–228
96.
Constantino JN, Todd RD: Autistic traits in the general population: a twin study. Arch Gen Psychiatry 2003; 60:524–530
97.
Pascual-Leone A, Freitas C, Oberman L, Horvath JC, Halko M, Eldaief M, Bashir S, Vernet M, Shafi M, Westover B, Vahabzadeh-Hagh AM, Rotenberg A: Characterizing brain cortical plasticity and network dynamics across the age-span in health and disease with TMS-EEG and TMS-fMRI. Brain Topogr 2011; 24:302–315
98.
Balas EA, Weingarten S, Garb CT, Blumenthal D, Boren SA, Brown GD: Improving preventive care by prompting physicians. Arch Intern Med 2000; 160:301–308
99.
Weisz JR, Ugueto AM, Cheron DM, Herren J: Evidence-based youth psychotherapy in the mental health ecosystem. J Clin Child Adolesc Psychol 2013; 42:274–286
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Received: 13 August 2013
Revision received: 22 November 2013
Accepted: 19 December 2013
Published online: 1 May 2014
Published in print: May 2014
Authors
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Dr. Keshavan has received grant funding from Sunovion. Dr. Vinogradov has received consulting fees from AmGen, Brain Plasticity Institute, EnVivo, Genentech, and Hoffman La Roche. The other authors report no financial relationships with commercial interests.Dr. Keshavan has been supported by NIH grants MH092440 and MH060902. Dr. Vinogradov has been supported by NIH grants MH068725, MH082818, MH068725, MH081051, and MH081807 and the Stanley Medical Research Institute.This research is based on a workshop sponsored by NIMH that was held on April 9 and 10, 2012. The workshop participants were Matcheri Keshavan, Harvard University (co-chair); Ann Wagner, NIMH (co-chair); Yair Bar-Haim, Tel Aviv University; Cameron Carter, University of California Davis; David Chambers, NIMH; Bruce Cuthbert, NIMH; Daniel Dickstein, Bradley Hospital/Brown University; Amy Dorin, FEGS Health and Human Services System, New York; Shaun Eack, University of Pittsburgh; Amit Etkin, Stanford University; Adam Gazzaley, University of California San Francisco; Russ Glasgow, National Cancer Institute; Adam Haim, NIMH; Jeffrey Halperin, Queens College; Courtenay Harding, The Coalition of Behavioral Health Agencies, New York; Robert Heinssen, NIMH; Thomas Insel, NIMH; Wendy Kates, SUNY Upstate Medical Center; Ellen Leibenluft, NIMH; Susan McGurk, Boston University; Alice Medalia, Columbia University; Sarah Morris, NIMH; Alvaro Pascual-Leone, Harvard Medical School; Daniel Pine, NIMH; Judith Rumsey, NIMH; Christopher Sarampote, NIMH; Suzy Scherf, Pennsylvania State University; Joel Sherrill, NIMH; David Sommers, NIMH; Leanne Tamm, Cincinnati Children’s Hospital Medical Center; Carol Tamminga, University of Texas Southwestern Medical Center; Sophia Vinogradov, University of California San Francisco; Bruce Wexler, Yale University; Til Wykes, University of London Institute of Psychiatry.
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