Transcranial direct current stimulation (tDCS) is a promising method for altering the function of neural systems, cognition, and behavior. Evidence is emerging that it can also influence psychiatric ...symptomatology, including major depression and schizophrenia. However, there are many open questions regarding how the method might have such an effect, and uncertainties surrounding its influence on neural activity, and human cognition and functioning. In the present critical review, we identify key priorities for future research into major depression and schizophrenia, including studies of the mechanism(s) of action of tDCS at the neuronal and systems levels, the establishment of the cognitive impact of tDCS, as well as investigations of the potential clinical efficacy of tDCS. We highlight areas of progress in each of these domains, including data that appear to favor an effect of tDCS on neural oscillations rather than spiking, and findings that tDCS administration to the prefrontal cortex during task training may be an effective way to enhance behavioral performance. Finally, we provide suggestions for further empirical study that will elucidate the impact of tDCS on brain and behavior, and may pave the way for efficacious clinical treatments for psychiatric disorders.
The dorsal anterior cingulate cortex (ACC) and associated regions of the medial frontal wall have often been hypothesized to play an important role in cognitive control. We have proposed that the ...ACC's specific role in cognitive control is to detect conflict between simultaneously active, competing representations and to engage the dorsolateral prefrontal cortex (DLPFC) to resolve such conflict. Here we review some of the evidence supporting this theory, from event-related potential (ERP) and fMRI studies. We focus on data obtained from interference tasks, such as the Stroop task, and review the evidence that trial-to-trial changes in control engagement can be understood as driven by conflict detection; the data suggest that levels of activation of the ACC and the DLPFC in such tasks do indeed reflect conflict and control, respectively. We also discuss some discrepant results in the literature that highlight the need for future research.
Kraepelin, in his early descriptions of schizophrenia (SZ), characterized the illness as having "an orchestra without a conductor." Kraepelin further speculated that this "conductor" was situated in ...the frontal lobes. Findings from multiple studies over the following decades have clearly implicated pathology of the dorsolateral prefrontal cortex (DLPFC) as playing a central role in the pathophysiology of SZ, particularly with regard to key cognitive features such as deficits in working memory and cognitive control. Following an overview of the cognitive mechanisms associated with DLPFC function and how they are altered in SZ, we review evidence from an array of neuroscientific approaches addressing how these cognitive impairments may reflect the underlying pathophysiology of the illness. Specifically, we present evidence suggesting that alterations of the DLPFC in SZ are evident across a range of spatial and temporal resolutions: from its cellular and molecular architecture, to its gross structural and functional integrity, and from millisecond to longer timescales. We then present an integrative model based upon how microscale changes in neuronal signaling in the DLPFC can influence synchronized patterns of neural activity to produce macrocircuit-level alterations in DLPFC activation that ultimately influence cognition and behavior. We conclude with a discussion of initial efforts aimed at targeting DLPFC function in SZ, the clinical implications of those efforts, and potential avenues for future development.
Modafinil (2-(Diphenylmethyl) sulfinyl acetamide, Provigil) is an FDA-approved medication with wake-promoting properties. Pre-clinical studies of modafinil suggest a complex profile of neurochemical ...and behavioral effects, distinct from those of amphetamine. In addition, modafinil shows initial promise for a variety of off-label indications in psychiatry, including treatment-resistant depression, attention-deficit/hyperactivity disorder, and schizophrenia. Cognitive dysfunction may be a particularly important emerging treatment target for modafinil, across these and other neuropsychiatric disorders. We aimed to comprehensively review the empirical literature on neurochemical actions of modafinil, and effects on cognition in animal models, healthy adult humans, and clinical populations. We searched PubMed with the search term 'modafinil' and reviewed all English-language articles for neurochemical, neurophysiological, cognitive, or information-processing experimental measures. We additionally summarized the pharmacokinetic profile of modafinil and clinical efficacy in psychiatric patients. Modafinil exhibits robust effects on catecholamines, serotonin, glutamate, gamma amino-butyric acid, orexin, and histamine systems in the brain. Many of these effects may be secondary to catecholamine effects, with some selectivity for cortical over subcortical sites of action. In addition, modafinil (at well-tolerated doses) improves function in several cognitive domains, including working memory and episodic memory, and other processes dependent on prefrontal cortex and cognitive control. These effects are observed in rodents, healthy adults, and across several psychiatric disorders. Furthermore, modafinil appears to be well-tolerated, with a low rate of adverse events and a low liability to abuse. Modafinil has a number of neurochemical actions in the brain, which may be related to primary effects on catecholaminergic systems. These effects are in general advantageous for cognitive processes. Overall, modafinil is an excellent candidate agent for remediation of cognitive dysfunction in neuropsychiatric disorders.
Previous work using logistic regression suggests that cognitive control‐related frontoparietal activation in early psychosis can predict symptomatic improvement after 1 year of coordinated specialty ...care with 66% accuracy. Here, we evaluated the ability of six machine learning (ML) algorithms and deep learning (DL) to predict “Improver” status (>20% improvement on Brief Psychiatric Rating Scale BPRS total score at 1‐year follow‐up vs. baseline) and continuous change in BPRS score using the same functional magnetic resonance imaging‐based features (frontoparietal activations during the AX‐continuous performance task) in the same sample (individuals with either schizophrenia (n = 65, 49M/16F, mean age 20.8 years) or Type I bipolar disorder (n = 17, 9M/8F, mean age 21.6 years)). 138 healthy controls were included as a reference group. “Shallow” ML methods included Naive Bayes, support vector machine, K Star, AdaBoost, J48 decision tree, and random forest. DL included an explainable artificial intelligence (XAI) procedure for understanding results. The best overall performances (70% accuracy for the binary outcome and root mean square error = 9.47 for the continuous outcome) were achieved using DL. XAI revealed left DLPFC activation was the strongest feature used to make binary classification decisions, with a classification activation threshold (adjusted beta = .017) intermediate to the healthy control mean (adjusted beta = .15, 95% CI = −0.02 to 0.31) and patient mean (adjusted beta = −.13, 95% CI = −0.37 to 0.11). Our results suggest DL is more powerful than shallow ML methods for predicting symptomatic improvement. The left DLPFC may be a functional target for future biomarker development as its activation was particularly important for predicting improvement.
The performance of shallow machine learning algorithms was compared to deep learning when predicting symptomatic improvement in early psychosis using frontoparietal activation data from a cognitive control task. Deep learning outperformed all shallow algorithms for both binary and continuous classifiers. Explainable artificial intelligence (XAI) methods suggested the deep learner primarily used left dorsolateral prefrontal cortex activation to predict clinical improvement, providing an example of how XAI can be used to "demystify" the "black box" problem inherent in all machine learning algorithms.
Cognitive control (with the closely related concepts of attention control and executive function) encompasses the collection of processes that are involved in generating and maintaining appropriate ...task goals and suppressing task goals that are no longer relevant, as well as the way in which current goal representations are used to modify attentional biases to improve task performance. Here, we provide a comprehensive but nonexhaustive review of this complex literature, with an emphasis on the contributions made by techniques for studying human brain function. The review is divided into five sections: (a) overview and historical perspective of cognitive control, its subcomponent processes, and its neural substrate; (b) most common types of tasks used to assess and/or manipulate the level of control; (c) main research findings obtained with various imaging methodologies, with a focus on ERP data, and briefer overviews of oscillatory (event‐related spectral perturbations) and fMRI data; (d) major theories of cognitive control; and (e) discussion of open questions regarding how to integrate the various dimensions of control, as well as the faster versus slower temporal dynamics informing this complex and multifaceted concept.
Magnetic resonance spectroscopy studies measuring brain glutamate separately from glutamine are helping elucidate schizophrenia pathophysiology. An expanded literature and improved methodologies ...motivate an updated meta-analysis examining effects of measurement quality and other moderating factors in characterizing abnormal glutamate levels in schizophrenia.
Searching previous meta-analyses and the MEDLINE database identified 83 proton magnetic resonance spectroscopy datasets published through March 25, 2020. Three quality metrics were extracted—Cramér–Rao lower bound (CRLB), line width, and coefficient of variation. Pooled effect sizes (Hedges’ g) were calculated with random-effects, inverse variance-weighted models. Moderator analyses were conducted using quality metrics, field strength, echo time, medication, age, and stage of illness.
Across 36 datasets (2086 participants), medial prefrontal cortex glutamate was significantly reduced in patients (g = −0.19, confidence interval CI = −0.07 to −0.32). CRLB and coefficient of variation quality subgroups significantly moderated this effect. Glutamate was significantly more reduced in studies with lower CRLB or coefficient of variation (g = −0.44, CI = −0.29 to −0.60, and g = −0.43, CI = −0.29 to −0.57, respectively). Studies using echo time ≤20 ms also showed significantly greater reduction in glutamate (g = −0.41, CI = −0.26 to −0.55). Across 11 hippocampal datasets, group differences and moderator effects were nonsignificant. Group effects in thalamus and dorsolateral prefrontal cortex were also nonsignificant.
High-quality measurements reveal consistently reduced medial prefrontal cortex glutamate in schizophrenia. Stricter CRLB criteria and reduced nuisance variance may increase the sensitivity of future studies examining additional regions and the pathophysiological significance of abnormal glutamate levels in schizophrenia.
Classic cognitive theory conceptualizes executive functions as involving multiple specific domains, including initiation, inhibition, working memory, flexibility, planning, and vigilance. Lesion and ...neuroimaging experiments over the past two decades have suggested that both common and unique processes contribute to executive functions during higher cognition. It has been suggested that a superordinate fronto–cingulo–parietal network supporting cognitive control may also underlie a range of distinct executive functions. To test this hypothesis in the largest sample to date, we used quantitative meta-analytic methods to analyze 193 functional neuroimaging studies of 2,832 healthy individuals, ages 18–60, in which performance on executive function measures was contrasted with an active control condition. A common pattern of activation was observed in the prefrontal, dorsal anterior cingulate, and parietal cortices across executive function domains, supporting the idea that executive functions are supported by a superordinate cognitive control network. However, domain-specific analyses showed some variation in the recruitment of anterior prefrontal cortex, anterior and midcingulate regions, and unique subcortical regions such as the basal ganglia and cerebellum. These results are consistent with the existence of a superordinate cognitive control network in the brain, involving dorsolateral prefrontal, anterior cingulate, and parietal cortices, that supports a broad range of executive functions.
Although schizophrenia is an illness that has been historically characterized by the presence of positive symptomatology, decades of research highlight the importance of cognitive deficits in this ...disorder. This review proposes that the theoretical model of cognitive control, which is based on contemporary cognitive neuroscience, provides a unifying theory for the cognitive and neural abnormalities underlying higher cognitive dysfunction in schizophrenia. To support this model, we outline converging evidence from multiple modalities (eg, structural and functional neuroimaging, pharmacological data, and animal models) and samples (eg, clinical high risk, genetic high risk, first episode, and chronic subjects) to emphasize how dysfunction in cognitive control mechanisms supported by the prefrontal cortex contribute to the pathophysiology of higher cognitive deficits in schizophrenia. Our model provides a theoretical link between cellular abnormalities (eg, reductions in dentritic spines, interneuronal dysfunction), functional disturbances in local circuit function (eg, gamma abnormalities), altered inter-regional cortical connectivity, a range of higher cognitive deficits, and symptom presentation (eg, disorganization) in the disorder. Finally, we discuss recent advances in the neuropharmacology of cognition and how they can inform a targeted approach to the development of effective therapies for this disabling aspect of schizophrenia.
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