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Stress-related disorders are among the biggest global health challenges. Despite significant progress in understanding their neurocognitive basis, the promise of applying insights from fundamental research to prevention and treatment remains largely unfulfilled. We argue that neurofeedback - a method for training voluntary control over brain activity - has the potential to fill this translational gap. We provide a contemporary perspective on neurofeedback as endogenous neuromodulation that can target complex brain network dynamics, is transferable to real-world scenarios outside a laboratory or treatment facility, can be trained prospectively, and is individually adaptable. This makes neurofeedback a prime candidate for a personalized preventive neuroscience-based intervention strategy that focuses on the ecological momentary neuromodulation of stress-related brain networks in response to actual stressors in real life., Competing Interests: Declaration of interests The authors declare no competing interests in relation to this work., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Human individuality is likely underpinned by the constitution of functional brain networks that ensure consistency of each person's cognitive and behavioral profile. These functional networks should, in principle, be detectable by noninvasive neurophysiology. We use a method that enables the detection of dominant frequencies of the interaction between every pair of brain areas at every temporal segment of the recording period, the dominant coupling modes (DoCM). We apply this method to brain oscillations, measured with magnetoencephalography (MEG) at rest in two independent datasets, and show that the spatiotemporal evolution of DoCMs constitutes an individualized brain fingerprint. Based on this successful fingerprinting we suggest that DoCMs are important targets for the investigation of neural correlates of individual psychological parameters and can provide mechanistic insight into the underlying neurophysiological processes, as well as their disturbance in brain diseases., (© 2023 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

Copy number variations (CNVs) are rare genomic deletions and duplications that can affect brain and behaviour. Previous reports of CNV pleiotropy imply that they converge on shared mechanisms at some level of pathway cascades, from genes to large-scale neural circuits to the phenome. However, existing studies have primarily examined single CNV loci in small clinical cohorts. It remains unknown, for example, how distinct CNVs escalate vulnerability for the same developmental and psychiatric disorders. Here we quantitatively dissect the associations between brain organization and behavioural differentiation across 8 key CNVs. In 534 CNV carriers, we explored CNV-specific brain morphology patterns. CNVs were characteristic of disparate morphological changes involving multiple large-scale networks. We extensively annotated these CNV-associated patterns with ~1,000 lifestyle indicators through the UK Biobank resource. The resulting phenotypic profiles largely overlap and have body-wide implications, including the cardiovascular, endocrine, skeletal and nervous systems. Our population-level investigation established brain structural divergences and phenotypical convergences of CNVs, with direct relevance to major brain disorders., (© 2023. The Author(s), under exclusive licence to Springer Nature Limited.)

Triple X syndrome is a sex chromosomal aneuploidy characterized by the presence of a supernumerary X chromosome, resulting in a karyotype of 47,XXX in affected females. It has been associated with a variable cognitive, behavioral, and psychiatric phenotype, but little is known about its effects on brain function. We therefore conducted 7 T resting-state functional magnetic resonance imaging and compared data of 19 adult individuals with 47,XXX and 21 age-matched healthy control women using independent component analysis and dual regression. Additionally, we examined potential relationships between social cognition and social functioning scores, and IQ, and mean functional connectivity values. The 47,XXX group showed significantly increased functional connectivity of the fronto-parietal resting-state network with the right postcentral gyrus. Resting-state functional connectivity (rsFC) variability was not associated with IQ and social cognition and social functioning deficits in the participants with 47,XXX. We thus observed an effect of a supernumerary X chromosome in adult women on fronto-parietal rsFC. These findings provide additional insight into the role of the X chromosome on functional connectivity of the brain. Further research is needed to understand the clinical implications of altered rsFC in 47,XXX., (© The Author(s) 2022. Published by Oxford University Press.)

The Enhancing NeuroImaging Genetics through Meta-Analysis copy number variant (ENIGMA-CNV) and 22q11.2 Deletion Syndrome Working Groups (22q-ENIGMA WGs) were created to gain insight into the involvement of genetic factors in human brain development and related cognitive, psychiatric and behavioral manifestations. To that end, the ENIGMA-CNV WG has collated CNV and magnetic resonance imaging (MRI) data from ~49,000 individuals across 38 global research sites, yielding one of the largest studies to date on the effects of CNVs on brain structures in the general population. The 22q-ENIGMA WG includes 12 international research centers that assessed over 533 individuals with a confirmed 22q11.2 deletion syndrome, 40 with 22q11.2 duplications, and 333 typically developing controls, creating the largest-ever 22q11.2 CNV neuroimaging data set. In this review, we outline the ENIGMA infrastructure and procedures for multi-site analysis of CNVs and MRI data. So far, ENIGMA has identified effects of the 22q11.2, 16p11.2 distal, 15q11.2, and 1q21.1 distal CNVs on subcortical and cortical brain structures. Each CNV is associated with differences in cognitive, neurodevelopmental and neuropsychiatric traits, with characteristic patterns of brain structural abnormalities. Evidence of gene-dosage effects on distinct brain regions also emerged, providing further insight into genotype-phenotype relationships. Taken together, these results offer a more comprehensive picture of molecular mechanisms involved in typical and atypical brain development. This "genotype-first" approach also contributes to our understanding of the etiopathogenesis of brain disorders. Finally, we outline future directions to better understand effects of CNVs on brain structure and behavior., (© 2021 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

The impact of human values on our choices depends on their nature. Self-Transcendence values motivate us to act for the benefit of others and care for the environment. Self-Enhancement values motivate us to act for our benefit. The present study examines differences in the neural processes underlying these two value domains. Extending our previous research, we used fMRI to explore first of all neural correlates of Self-Transcendence vs Self-Enhancement values, with a particular focus on the putative role of the medial prefrontal cortex (MPFC), which has been linked to a self-transcendent mind-set. Additionally, we investigated the neural basis of Openness to Change vs Conservation values. We asked participants to reflect on and rate values as guiding principles in their lives while undergoing fMRI. Mental processing of Self-Transcendence values was associated with higher brain activity in the dorsomedial (BA9, BA8) and ventromedial (BA10) prefrontal cortices, as compared to Self-Enhancement values. The former involved activation and the latter deactivation of those regions. We did not detect differences in brain activation between Openness to Change vs Conservation values. Self-Transcendence values thus shared brain regions with social processes that have previously been linked to a self-transcendent mind-set, and the "core self" representation.

Quality control of brain segmentation is a fundamental step to ensure data quality. Manual quality control strategies are the current gold standard, although these may be unfeasible for large neuroimaging samples. Several options for automated quality control have been proposed, providing potential time efficient and reproducible alternatives. However, those have never been compared side to side, which prevents consensus in the appropriate quality control strategy to use. This study aimed to elucidate the changes manual editing of brain segmentations produce in morphological estimates, and to analyze and compare the effects of different quality control strategies on the reduction of the measurement error. Structural brain MRI from 259 participants of The Maastricht Study were used. Morphological estimates were automatically extracted using FreeSurfer 6.0. Segmentations with inaccuracies were manually edited, and morphological estimates were compared before and after editing. In parallel, 12 quality control strategies were applied to the full sample. Those included: two manual strategies, in which images were visually inspected and either excluded or manually edited; five automated strategies, where outliers were excluded based on the tools "MRIQC" and "Qoala-T", and the metrics "morphological global measures", "Euler numbers" and "Contrast-to-Noise ratio"; and five semi-automated strategies, where the outliers detected through the mentioned tools and metrics were not excluded, but visually inspected and manually edited. In order to quantify the effects of each quality control strategy, the proportion of unexplained variance relative to the total variance was extracted after the application of each strategy, and the resulting differences compared. Manually editing brain surfaces produced particularly large changes in subcortical brain volumes and moderate changes in cortical surface area, thickness and hippocampal volumes. The performance of the quality control strategies depended on the morphological measure of interest. Overall, manual quality control strategies yielded the largest reduction in relative unexplained variance. The best performing automated alternatives were those based on Euler numbers and MRIQC scores. The exclusion of outliers based on global morphological measures produced an increase of relative unexplained variance. Manual quality control strategies are the most reliable solution for quality control of brain segmentation and parcellation. However, measures must be taken to prevent the subjectivity associated with these strategies. The detection of inaccurate segmentations based on Euler numbers or MRIQC provides a time efficient and reproducible alternative. The exclusion of outliers based on global morphological estimates must be avoided., Competing Interests: Declaration of Competing Interest None., (Copyright © 2021. Published by Elsevier Inc.)

Functional MRI neurofeedback (NF) allows humans to self-modulate neural patterns in specific brain areas. This technique is regarded as a promising tool to translate neuroscientific knowledge into brain-guided psychiatric interventions. However, its clinical implementation is restricted by unstandardized methodological practices, by clinical definitions that are poorly grounded in neurobiology, and by lack of a unifying framework that dictates experimental choices. Here we put forward a new framework, termed 'process-based NF', which endorses a process-oriented characterization of mental dysfunctions to form precise and effective psychiatric treatments. This framework relies on targeting specific dysfunctional mental processes by modifying their underlying neural mechanisms and on applying process-specific contextual feedback interfaces. Finally, process-based NF offers designs and a control condition that address the methodological shortcomings of current approaches, thus paving the way for a precise and personalized neuromodulation.

fMRI Neurofeedback research employs many different control conditions. Currently, there is no consensus as to which control condition is best, and the answer depends on what aspects of the neurofeedback-training design one is trying to control for. These aspects can range from determining whether participants can learn to control brain activity via neurofeedback to determining whether there are clinically significant effects of the neurofeedback intervention. Lack of consensus over criteria for control conditions has hampered the design and interpretation of studies employing neurofeedback protocols. This paper presents an overview of the most commonly employed control conditions currently used in neurofeedback studies and discusses their advantages and disadvantages. Control conditions covered include no control, treatment-as-usual, bidirectional-regulation control, feedback of an alternative brain signal, sham feedback, and mental-rehearsal control. We conclude that the selection of the control condition(s) should be determined by the specific research goal of the study and best procedures that effectively control for relevant confounding factors., (Copyright © 2018 Elsevier Inc. All rights reserved.)

Previous research has demonstrated that comparing two persons activates a frontoparietal network associated with numbers and nonsocial magnitudes. However, it is unclear whether this network is also recruited by comparisons involving the self. Self-reflection engages self-serving motivations (e.g., the maintenance of a positive self-image) and is associated with specific brain structures, such as the medial prefrontal cortex (MPFC), the anterior insula (AI) and the anterior cingulate cortex (ACC). Self-other comparisons may thus rely on distinct neural activity. To clarify this question, we used fMRI and asked female participants to compare their own attractiveness (or the attractiveness of a familiar woman) to pictures of unknown women. Participants were slower for comparisons with targets whose attractiveness was similar to their own (or their familiar other). Yet although this behavioral result resembles the distance effect reported for nonsocial magnitudes, at the brain level, it was linked to the activity of the AI, the ACC and the MPFC. The effect of distance in these regions was stronger for self-other than familiar-other comparisons. We interpret these results in relation to previous literature in social psychology and social neuroscience.

Functional magnetic resonance imaging neurofeedback (fMRI-NF) training of areas involved in emotion processing can reduce depressive symptoms by over 40% on the Hamilton Depression Rating Scale (HDRS). However, it remains unclear if this efficacy is specific to feedback from emotion-regulating regions. We tested in a single-blind, randomized, controlled trial if upregulation of emotion areas (NFE) yields superior efficacy compared to upregulation of a control region activated by visual scenes (NFS). Forty-three moderately to severely depressed medicated patients were randomly assigned to five sessions augmentation treatment of either NFE or NFS training. At primary outcome (week 12) no significant group mean HDRS difference was found (B = -0.415 [95% CI -4.847 to 4.016], p = 0.848) for the 32 completers (16 per group). However, across groups depressive symptoms decreased by 43%, and 38% of patients remitted. These improvements lasted until follow-up (week 18). Both groups upregulated target regions to a similar extent. Further, clinical improvement was correlated with an increase in self-efficacy scores. However, the interpretation of clinical improvements remains limited due to lack of a sham-control group. We thus surveyed effects reported for accepted augmentation therapies in depression. Data indicated that our findings exceed expected regression to the mean and placebo effects that have been reported for drug trials and other sham-controlled high-technology interventions. Taken together, we suggest that the experience of successful self-regulation during fMRI-NF training may be therapeutic. We conclude that if fMRI-NF is effective for depression, self-regulation training of higher visual areas may provide an effective alternative.

Human values guide behavior and the smooth functioning of societies. Schwartz's circumplex model of values predicts a sinusoidal waveform in relations between ratings of the importance of diverse human value types (e.g., achievement, benevolence) and any variables psychologically relevant to them. In this neuroimaging study, we examined these nonlinear associations between values types and brain structure. In 85 participants, we found the predicted sinusoidal relationship between ratings of values types and two measures of white matter (WM), volume and myelin volume fraction, as well as for grey matter (GM) parameters in several frontal regions. These effects reveal new functional associations for structural brain parameters and provide a novel cross-validation of Schwartz's model. Moreover, the sinusoidal waveform test can be applied to other circumplex models in social, affective and cognitive neuroscience.

Motivational interdependence is an organizing principle in Schwartz's circumplex model of social values, which has received abundant cross-cultural support. We used fMRI to test whether motivational relations between social values predict different brain responses in a situation of choice between values. We hypothesized that differences in brain responses would become evident when the more important value had to be selected in pairs of congruent (e.g., wealth and success) as opposed to incongruent (e.g., curiosity and stability) values as they are described in Schwartz's model, because the former serve mutually facilitating motives, whereas the latter serve mutually inhibiting motives. Consistent with the model, choosing between congruent values led to longer response times and more activation in conflict-related brain regions (e.g., the supplementary motor area, dorsolateral prefrontal cortex) than selecting between incongruent values. These results provide novel neural evidence supporting the circumplex model's predictions about motivational interdependence between social values. In particular, our results show that the neural networks underlying social values are organized in a way that allows activation patterns related to motivational similarity between congruent values to be dissociated from those related to incongruent values.

FMRI-based neurofeedback transforms functional brain activation in real-time into sensory stimuli that participants can use to self-regulate brain responses, which can aid the modification of mental states and behavior. Emerging evidence supports the clinical utility of neurofeedback-guided up-regulation of hypoactive networks. In contrast, down-regulation of hyperactive neural circuits appears more difficult to achieve. There are conditions though, in which down-regulation would be clinically useful, including dysfunctional motivational states elicited by salient reward cues, such as food or drug craving. In this proof-of-concept study, 10 healthy females (mean age = 21.40 years, mean BMI = 23.53) who had fasted for 4 h underwent a novel 'motivational neurofeedback' training in which they learned to down-regulate brain activation during exposure to appetitive food pictures. FMRI feedback was given from individually determined target areas and through decreases/increases in food picture size, thus providing salient motivational consequences in terms of cue approach/avoidance. Our preliminary findings suggest that motivational neurofeedback is associated with functionally specific activation decreases in diverse cortical/subcortical regions, including key motivational areas. There was also preliminary evidence for a reduction of hunger after neurofeedback and an association between down-regulation success and the degree of hunger reduction. Decreasing neural cue responses by motivational neurofeedback may provide a useful extension of existing behavioral methods that aim to modulate cue reactivity. Our pilot findings indicate that reduction of neural cue reactivity is not achieved by top-down regulation but arises in a bottom-up manner, possibly through implicit operant shaping of target area activity.

Background: Real-time functional magnetic resonance imaging (rtfMRI) is used for neurofeedback training (NFT). Preliminary results suggest that it can help patients to control their symptoms. This study uses rtfMRI NFT for relapse prevention in alcohol dependence., Methods/design: Participants are alcohol-dependent patients who have completed a detoxification programme within the past 6 months and have remained abstinent. Potential participants are screened for eligibility, and those who are eligible are randomly assigned to the treatment group (receiving rtfMRI NFT in addition to treatment as usual) or the control group (receiving only treatment as usual). Participants in both groups are administered baseline assessments to measure their alcohol consumption and severity of dependence and a variety of psychological and behavioural characteristics that are hypothesised to predict success with rtfMRI NFT. During the following 4 months, experimental participants are given six NFT sessions, and before and after each session various alcohol-related measures are taken. Participants in the control group are given the same measures to coincide with their timing in the experimental group. Eight and 12 months after the baseline assessment, both groups are followed up with a battery of measures. The primary research questions are whether NFT can be used to teach participants to down-regulate their brain activation in the presence of alcohol stimuli or to up-regulate their brain activation in response to pictures related to healthy goal pursuits, and, if so, whether this translates into reductions in alcohol consumption. The primary outcome measures will be those derived from the functional brain imaging data. We are interested in improvements (i.e., reductions) in participants' alcohol consumption from pretreatment levels, as indicated by three continuous variables, not simply whether or not the person has remained abstinent. The indices of interest are percentage of days abstinent, drinks per drinking day, and percentage of days of heavy drinking. General linear models will be used to compare the NFT group and the control group on these measures., Discussion: Relapse in alcohol dependence is a recurring problem, and the present evaluation of the role of rtfMRI in its treatment holds promise for identifying a way to prevent relapse., Trial Registration: ClinicalTrials.gov Identifier: NCT02486900 , registered on 26 June 2015.

A substantial proportion of schizophrenia liability can be explained by additive genetic factors. Risk profile scores (RPS) directly index risk using a summated total of common risk variants weighted by their effect. Previous studies suggest that schizophrenia RPS predict alterations to neural networks that support working memory and verbal fluency. In this study, we apply schizophrenia RPS to fMRI data to elucidate the effects of polygenic risk on functional brain networks during a probabilistic-learning neuroimaging paradigm. The neural networks recruited during this paradigm have previously been shown to be altered to unmedicated schizophrenia patients and relatives of schizophrenia patients, which may reflect genetic susceptibility. We created schizophrenia RPS using summary data from the Psychiatric Genetic Consortium (Schizophrenia Working Group) for 83 healthy individuals and explore associations between schizophrenia RPS and blood oxygen level dependency (BOLD) during periods of choice behavior (switch-stay) and reflection upon choice outcome (reward-punishment). We show that schizophrenia RPS is associated with alterations in the frontal pole (PWHOLE-BRAIN-CORRECTED  = 0.048) and the ventral striatum (PROI-CORRECTED  = 0.036), during choice behavior, but not choice outcome. We suggest that the common risk variants that increase susceptibility to schizophrenia can be associated with alterations in the neural circuitry that support the processing of changing reward contingencies. Hum Brain Mapp 37:491-500, 2016. © 2015 Wiley Periodicals, Inc., (© 2015 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.)

An increasing number of studies using real-time fMRI neurofeedback have demonstrated that successful regulation of neural activity is possible in various brain regions. Since these studies focused on the regulated region(s), little is known about the target-independent mechanisms associated with neurofeedback-guided control of brain activation, i.e. the regulating network. While the specificity of the activation during self-regulation is an important factor, no study has effectively determined the network involved in self-regulation in general. In an effort to detect regions that are responsible for the act of brain regulation, we performed a post-hoc analysis of data involving different target regions based on studies from different research groups. We included twelve suitable studies that examined nine different target regions amounting to a total of 175 subjects and 899 neurofeedback runs. Data analysis included a standard first- (single subject, extracting main paradigm) and second-level (single subject, all runs) general linear model (GLM) analysis of all participants taking into account the individual timing. Subsequently, at the third level, a random effects model GLM included all subjects of all studies, resulting in an overall mixed effects model. Since four of the twelve studies had a reduced field of view (FoV), we repeated the same analysis in a subsample of eight studies that had a well-overlapping FoV to obtain a more global picture of self-regulation. The GLM analysis revealed that the anterior insula as well as the basal ganglia, notably the striatum, were consistently active during the regulation of brain activation across the studies. The anterior insula has been implicated in interoceptive awareness of the body and cognitive control. Basal ganglia are involved in procedural learning, visuomotor integration and other higher cognitive processes including motivation. The larger FoV analysis yielded additional activations in the anterior cingulate cortex, the dorsolateral and ventrolateral prefrontal cortex, the temporo-parietal area and the visual association areas including the temporo-occipital junction. In conclusion, we demonstrate that several key regions, such as the anterior insula and the basal ganglia, are consistently activated during self-regulation in real-time fMRI neurofeedback independent of the targeted region-of-interest. Our results imply that if the real-time fMRI neurofeedback studies target regions of this regulation network, such as the anterior insula, care should be given whether activation changes are related to successful regulation, or related to the regulation process per se. Furthermore, future research is needed to determine how activation within this regulation network is related to neurofeedback success., (Copyright © 2015 Elsevier Inc. All rights reserved.)

Recent research has shown that visual short-term memory (VSTM) can substantially be improved when the to-be-remembered objects are split in 2 half-arrays (i.e., sequenced) or the entire array is shown twice (i.e., repeated), rather than presented simultaneously. Here we investigate the hypothesis that sequencing and repeating displays overcomes attentional "bottlenecks" during simultaneous encoding. Using functional magnetic resonance imaging, we show that sequencing and repeating displays increased brain activation in extrastriate and primary visual areas, relative to simultaneous displays (Study 1). Passively viewing identical stimuli did not increase visual activation (Study 2), ruling out a physical confound. Importantly, areas of the frontoparietal attention network showed increased activation in repetition but not in sequential trials. This dissociation suggests that repeating a display increases attentional control by allowing attention to be reallocated in a second encoding episode. In contrast, sequencing the array poses fewer demands on control, with competition from nonattended objects being reduced by the half-arrays. This idea was corroborated by a third study in which we found optimal VSTM for sequential displays minimizing attentional demands. Importantly these results provide support within the same experimental paradigm for the role of stimulus-driven and top-down attentional control aspects of biased competition theory in setting constraints on VSTM., (© The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.)

Polygenic risk scores, based on risk variants identified in genome-wide-association-studies (GWAS), explain a considerable portion of the heritability for schizophrenia (SZ) and bipolar disorder (BD). However, little is known about the combined effects of these variants, although polygenic neuroimaging has developed into a powerful tool of translational neuroscience. In this study, we used genome wide significant SZ risk variants to test the predictive capacity of the polygenic model and explored potential associations with white matter volume, a key candidate in imaging phenotype for psychotic disorders. By calculating the combined additive schizophrenia risk of seven SNPs (significant hits from a recent schizophrenia GWAS study), we show that increased additive genetic risk for SZ was associated with reduced white matter volume in a group of participants (n = 94) consisting of healthy individuals, SZ first-degree relatives, SZ patients and BD patients. This effect was also seen in a second independent sample of healthy individuals (n = 89). We suggest that a moderate portion of variance (~4%) of white matter volume can be explained by the seven hits from the recent schizophrenia GWAS. These results provide evidence for associations between cumulative genetic risk for schizophrenia and intermediate neuroimaging phenotypes in models of psychosis. Our work contributes to a growing body of literature suggesting that polygenic risk may help to explain white matter alterations associated with familial risk for psychosis.

We tested the effects of variation of stimulus onset asynchrony (SOA) on visual working memory (WM) performance across different load levels and the underlying brain activation patterns using functional magnetic resonance imaging (fMRI) in 48 healthy participants. Participants were instructed to memorise arrays of coloured squares and had to perform a match/non-match judgement on a probe stimulus after a jittered delay. We presented visual pattern masks at four SOAs after the offset of the memory array (100 ms, 200 ms, 400 ms, and 800 ms). Memory performance decreased with increased load and shortened SOA. Brain activation data showed significant effects of load (during encoding and retrieval), SOA (retrieval) and an interaction of load by SOA (encoding), mainly in frontal and parietal areas. There was also a direct relationship between successfully stored items and activation in the right inferior parietal lobule and the left middle frontal gyrus. The neurobehavioral results suggest that the frontal regions, together with the inferior parietal lobe, are associated with successful WM performance, especially under the most challenging conditions of high load and short SOAs., (Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.)

Objectives: We combined multimodal functional magnetic resonance imaging (fMRI) and structural magnetic resonance imaging to probe abnormalities in brain circuits underpinning episodic memory performance deficits in patients with bipolar disorder (BD)., Methods: We acquired whole-brain fMRI data in 21 patients with BD and a matched group of 20 healthy controls during a non-verbal episodic memory task, using abstract shapes. We also examined density of gray matter, using voxel-based morphometry (VBM), and integrity of connecting fiber tracts, using diffusion tensor imaging (DTI) and tract-based spatial statistics, for areas with significant activation differences., Results: Patients with BD remembered less well than controls which shapes they had seen and had lower activation levels during the encoding stage of the task in the anterior cingulate gyrus, the precuneus/cuneus bilaterally, and the left lingual gyrus, and higher activation levels during the retrieval stage in the left temporo-parietal junction. Patients with BD showed reduced gray matter volumes in the left anterior cingulate, the precuneus/cuneus bilaterally, and the left temporo-parietal region in comparison with controls. DTI revealed increased radial, axial, and mean diffusivity in the left superior longitudinal fascicle in patients with BD compared with controls., Conclusions: Changes in task-related activation in frontal and parietal areas were associated with poorer episodic memory in patients with BD. Compared with data from single imaging modalities, integration of multimodal neuroimaging data enables the building of more complete neuropsychological models of mental disorders., (© 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

Whenever we interact with others, we judge them and whenever we make such judgments, we compare them with ourselves, other people, or internalized standards. Countless social psychological experiments have shown that comparative thinking plays a ubiquitous role in person perception and social cognition as a whole. The topic of social comparison has recently aroused the interest of social neuroscientists, who have begun to investigate its neural underpinnings. The present article provides an overview of these neuroimaging and electrophysiological studies. We discuss recent findings on the consequences of social comparison on the brain processing of outcomes and highlight the role of the brain's reward system. Moreover, we analyze the relationship between the brain networks involved in social comparisons and those active during other forms of cognitive and perceptual comparison. Finally, we discuss potential future questions that research on the neural correlates of social comparison could address.

Variation in the CACNA1C gene has consistently been associated with psychosis in genome wide association studies. We have previously shown in a sample of n=110 healthy subjects that carriers of the CACNA1C rs1006737 risk variant exhibit hippocampal and perigenual anterior cingulate dysfunction (pgACC) during episodic memory recall. Here, we aimed to replicate our results, by testing for the effects of the rs1006737 risk variant in a new large cohort of healthy controls. We furthermore sought to refine these results by identifying the impact of a CACNA1C specific, gene-wide risk score in the absence of clinical pathology. An independent sample of 179 healthy subjects genotyped for rs1006737 underwent functional magnetic resonance imaging (fMRI) while performing an associative episodic memory task and underwent psychological testing similar to the discovery sample. The effect of gene-wide risk scores was analyzed in the combined sample of 289 subjects. We replicated our discovery findings of hippocampal and pgACC dysfunction in carriers of the rs1006737 risk variant. Additionally, we observed diminished activation of the dorsolateral prefrontal cortex, in the replication sample. Our replicated results as well as this new effect were also observable in the combined sample. Moreover, the same system-level phenotypes were significantly associated with the individual gene-based genetic risk score. Our findings suggest that altered hippocampal and frontolimbic function is associated with variants in the CACNA1C gene. Since CACNA1C variants have been associated repeatedly with psychosis at a genome-wide level, and preclinical data provide convergent evidence for the relevance of the CACNA1C gene for hippocampal and frontolimbic plasticity and adaptive regulation of stress, our data suggest a potential pathophysiological mechanism conferred by CACNA1C variants that may mediate risk for symptom dimensions shared among bipolar disorder, major depression, and schizophrenia., (Copyright © 2014 Elsevier Inc. All rights reserved.)

Beauty is in the eye of the beholder. How attractive someone is perceived to be depends on the individual or cultural standards to which this person is compared. But although comparisons play a central role in the way people judge the appearance of others, the brain processes underlying attractiveness comparisons remain unknown. In the present experiment, we tested the hypothesis that attractiveness comparisons rely on the same cognitive and neural mechanisms as comparisons of simple nonsocial magnitudes such as size. We recorded brain activity with functional magnetic resonance imaging (fMRI) while participants compared the beauty or height of two women or two dogs. Our data support the hypothesis of a common process underlying these different types of comparisons. First, we demonstrate that the distance effect characteristic of nonsocial comparisons also holds for attractiveness comparisons. Behavioral results indicated, for all our comparisons, longer response times for near than far distances. Second, the neural correlates of these distance effects overlapped in a frontoparietal network known for its involvement in processing simple nonsocial quantities. These results provide evidence for overlapping processes in the comparison of physical attractiveness and nonsocial magnitudes.

Recent advances in imaging technology and in the understanding of neural circuits relevant to emotion, motivation, and depression have boosted interest and experimental work in neuromodulation for affective disorders. Real-time functional magnetic resonance imaging (fMRI) can be used to train patients in the self regulation of these circuits, and thus complement existing neurofeedback technologies based on electroencephalography (EEG). EEG neurofeedback for depression has mainly been based on models of altered hemispheric asymmetry. fMRI-based neurofeedback (fMRI-NF) can utilize functional localizer scans that allow the dynamic adjustment of the target areas or networks for self-regulation training to individual patterns of emotion processing. An initial application of fMRI-NF in depression has produced promising clinical results, and further clinical trials are under way. Challenges lie in the design of appropriate control conditions for rigorous clinical trials, and in the transfer of neurofeedback protocols from the laboratory to mobile devices to enhance the sustainability of any clinical benefits.

In patients with attention deficit hyperactivity disorder (ADHD), quantitative neuroimaging techniques have revealed abnormalities in various brain regions, including the frontal cortex, striatum, cerebellum, and occipital cortex. Nonlinear signal processing techniques such as sample entropy have been used to probe the regularity of brain magnetoencephalography signals in patients with ADHD. In the present study, we extend this technique to analyse the complex output patterns of the 4 dimensional resting state functional magnetic resonance imaging signals in adult patients with ADHD. After adjusting for the effect of age, we found whole brain entropy differences (P=0.002) between groups and negative correlation (r=-0.45) between symptom scores and mean whole brain entropy values, indicating lower complexity in patients. In the regional analysis, patients showed reduced entropy in frontal and occipital regions bilaterally and a significant negative correlation between the symptom scores and the entropy maps at a family-wise error corrected cluster level of P<0.05 (P=0.001, initial threshold). Our findings support the hypothesis of abnormal frontal-striatal-cerebellar circuits in ADHD and the suggestion that sample entropy is a useful tool in revealing abnormalities in the brain dynamics of patients with psychiatric disorders., (© 2013 Elsevier Ireland Ltd. All rights reserved.)

Adolescence is a period of profound change, which holds substantial developmental milestones, but also unique challenges to the individual. In this opinion paper, we highlight the potential of combining two recently developed behavioural and neural training techniques (cognitive bias modification and functional magnetic neuroimaging-based neurofeedback) into a research approach that could help make the most of increased levels of plasticity during childhood and adolescence. We discuss how this powerful combination could be used to explore changing brain-behaviour relationships throughout development in the context of emotion processing, a cognitive domain that exhibits continuous development throughout the second decade of life. By targeting both behaviour and brain response, we would also be in an excellent position to define sensible time windows for enhancing plasticity, thereby allowing for targeted intervention approaches that can help improve emotion processing in both typically and atypically developing populations., (© 2013 John Wiley & Sons Ltd.)

Background: People with Alzheimer disease (AD) are capable of new learning when cognitive support is provided, suggesting that there is plasticity even in a degenerating brain. However, it is unclear how a cognition-focused intervention operates on a neural level., Objective: The present study examined the effects of cognitive rehabilitation (CR) on memory-related brain activation in people with early-stage AD, as measured by functional magnetic resonance imaging (fMRI)., Methods: A total of 19 participants either received 8 weeks of CR treatment (n = 7) or formed a control group (n = 12). We scanned participants pretreatment and posttreatment while they learned and recognized unfamiliar face-name pairs., Results: Following treatment, the CR group showed higher brain activation during recognition of face-name pairs in the left middle and inferior frontal gyri, the left insula, and 2s regions in the right medial parietal cortex. The control group showed decreased activation in these areas during recognition after the intervention period. Neither group showed an activation change during encoding. Behavioral performance on face-name learning did not improve for either group., Conclusions: We suggest that CR may have operated on the process of recognition through partial restoration of function in frontal brain areas that are less compromised in early-stage AD and that physiological markers may be more sensitive indicators of brain plasticity than behavioral performance.

Social comparison, that is, the process of comparing oneself to other people, is a ubiquitous social cognitive mechanism; however, so far its neural correlates have remained unknown. The present study tested the hypothesis that social comparisons are supported by partly dissociated networks, depending on whether the dimension under comparison concerns a physical or a psychological attribute. We measured brain activity with functional MRI, whereas participants were comparing their own height or intelligence to that of individuals they personally know. Height comparisons were associated with higher activity in a frontoparietal network involved in spatial and numerical cognition. Conversely, intelligence comparisons recruited a network of midline areas that have been previously implicated in the attribution of mental states to oneself and others (Theory of mind). These findings suggest that social comparisons rely on diverse domain-specific mechanisms rather than on one unitary process.

In this study, we investigate whether aberrant integrity of white matter (WM) fiber tracts represents a genetically determined biological marker of schizophrenia (SZ), and its relation with clinical symptoms. We collected brain DTI data from 28 SZ patients, 18 first-degree relatives and 22 matched controls and used voxel-based analysis with tract-based spatial statistics (TBSS) in order to compare fractional anisotropy (FA) between groups. Mean voxel-based FA values from the entire skeleton of each group were compared. We did a multiple regression analysis, followed by single post-hoc contrasts between groups. FA values were extracted from the statistically significant areas. The results showed significantly smaller FA values for SZ patients in comparison with controls in cortico-spinal tracts, in commissural fibers, in thalamic projections, in association fibers and in cingulum bundles. A significant increase of FA in SZ patients in comparison with healthy controls was only found in the arcuate fasciculus. Relatives had intermediate values between patients and controls which were deemed significant in the comparison to patients and controls in association fibers, arcuate fasciculus and cingulum bundles. Lower FA values in association fibers were significantly associated with predisposition toward hallucinations (in SZ patients and relatives), with higher PANSS scores of positive symptoms and with duration of illness (SZ patients). Our results suggest that clinical and subclinical presentations of psychotic symptoms are associated with aberrant integrity of multiple WM tracts. This association may represent an endophenotype of schizophrenia, since it is present in unaffected relatives as well. Such endophenotypes may serve as quantitative traits for future genetic studies and as candidate markers for early and preclinical identification of subjects at risk., (Copyright © 2012 Elsevier B.V. All rights reserved.)

How is working memory for different visual categories supported in the brain? Do the same principles of cortical specialization that govern the initial processing and encoding of visual stimuli also apply to their short-term maintenance? We investigated these questions with a delayed discrimination paradigm for faces, bodies, flowers, and scenes and applied both univariate and multivariate analyses to functional magnetic resonance imaging (fMRI) data. Activity during encoding followed the well-known specialization in posterior areas. During the delay interval, activity shifted to frontal and parietal regions but was not specialized for category. Conversely, activity in visual areas returned to baseline during that interval but showed some evidence of category specialization on multivariate pattern analysis (MVPA). We conclude that principles of cortical activation differ between encoding and maintenance of visual material. Whereas perceptual processes rely on specialized regions in occipitotemporal cortex, maintenance involves the activation of a frontoparietal network that seems to require little specialization at the category level. We also confirm previous findings that MVPA can extract information from fMRI signals in the absence of suprathreshold activation and that such signals from visual areas can reflect the material stored in memory.

The ability to integrate different types of information (e.g., object identity and spatial orientation) and maintain or manipulate them concurrently in working memory (WM) facilitates the flow of ongoing tasks and is essential for normal human cognition. Research shows that object and spatial information is maintained and manipulated in WM via separate pathways in the brain (object/ventral versus spatial/dorsal). How does the human brain coordinate the activity of different specialized systems to conjoin different types of information? Here we used functional magnetic resonance imaging to investigate conjunction- versus single-task manipulation of object (compute average color blend) and spatial (compute intermediate angle) information in WM. Object WM was associated with ventral (inferior frontal gyrus, occipital cortex), and spatial WM with dorsal (parietal cortex, superior frontal, and temporal sulci) regions. Conjoined object/spatial WM resulted in intermediate activity in these specialized areas, but greater activity in different prefrontal and parietal areas. Unique to our study, we found lower temporo-occipital activity and greater deactivation in temporal and medial prefrontal cortices for conjunction- versus single-tasks. Using structural equation modeling, we derived a conjunction-task connectivity model that comprises a frontoparietal network with a bidirectional DLPFC-VLPFC connection, and a direct parietal-extrastriate pathway. We suggest that these activation/deactivation patterns reflect efficient resource allocation throughout the brain and propose a new extended version of the biased competition model of WM., (Copyright © 2010 Wiley-Liss, Inc.)

The course to alcohol dependence often starts with a preclinical period of heavy drinking. The present article reports functional magnetic resonance imaging data showing that even this pattern of alcohol consumption is associated with maladaptive neural responses to alcohol and other stimuli. When participants were confronted with visual cues related to alcohol, heavy drinkers showed amplified blood oxygen level-dependent signal responses in specific emotional areas (insular cortex) and in parts of the brain's reward circuitry (ventral striatum). This neuronal amplification was not present in light drinkers. Crucially, at the same time heavy drinkers showed reduced responses in frontal areas to pictures related to higher order life goals and in the cingulate cortex to appetitive food stimuli, suggesting that they have difficulty finding alternative, socially desirable goals. Using discriminant function analysis, we demonstrate that the combination of alcohol-related overactivation and underactivation to alternative goals allows heavy and light drinkers to be differentiated with a high degree of precision. Our findings highlight the diagnostic value of functional brain mapping of cue reactivity. Imaging measures may help to identify addictive dispositions in preclinical stages and to clarify the mechanisms that underlie the development and maintenance of alcohol dependence.

Background: Dysfunctional working memory (WM) has been recognized as one of the most consistent deficits in schizophrenia. Studies that investigated the neural correlates of WM-related pathology by comparing patients with schizophrenia and control participants have produced controversial results, reporting task-related hyper- or hypoactivity in frontoparietal networks., Method: We addressed this question by comparing BOLD signals for accurate responses during a WM task for emotional faces between a homogeneous group of high-performing patients and a control group., Results: Our results confirm previous findings of left prefrontal hyperactivity contrasted with hypoactivity in right prefrontal cortex to support WM performance. We also extend previous work by reporting enhanced activity in higher visual areas of patients during encoding and maintenance., Conclusion: Our findings and those of the literature can be integrated into a model, where preserved visual cognition in high-functioning patients with hypofrontality is explained by activation of contralateral homologue areas combined with enhanced recruitment of sensory areas., (Copyright © 2011 S. Karger AG, Basel.)

Laterality is a characteristic principle of the organization of the brain systems for language, and reduced hemispheric asymmetry has been considered a risk factor for schizophrenia. Here we sought support for the risk factor hypothesis by investigating whether reduced asymmetry of temporal lobe structure and function is also present in unaffected relatives. Sixteen schizophrenia patients, 16 age-matched first-degree relatives, and 15 healthy controls underwent high-resolution three-dimensional anatomical imaging and functional magnetic resonance imaging during auditory stimulation. Both the overall auditory cortex and planum temporale volumes and the lateralization to the left hemisphere were markedly reduced in patients. The decrease of lateralization correlated with increased severity of symptoms. In addition, both the overall functional activation in response to auditory stimulation and its asymmetry were reduced in the patients. Relatives had intermediate values between patients and controls on both structural and functional measures. This study provides added support for the idea that reduced hemispheric asymmetry is a biological risk factor for schizophrenia.

Classification of brain images obtained through functional magnetic resonance imaging (fMRI) poses a serious challenge to pattern recognition and machine learning due to the extremely large feature-to-instance ratio. This calls for revision and adaptation of the current state-of-the-art classification methods. We investigate the suitability of the random subspace (RS) ensemble method for fMRI classification. RS samples from the original feature set and builds one (base) classifier on each subset. The ensemble assigns a class label by either majority voting or averaging of output probabilities. Looking for guidelines for setting the two parameters of the method-ensemble size and feature sample size-we introduce three criteria calculated through these parameters: usability of the selected feature sets, coverage of the set of "important" features, and feature set diversity. Optimized together, these criteria work toward producing accurate and diverse individual classifiers. RS was tested on three fMRI datasets from single-subject experiments: the Haxby data (Haxby, 2001.) and two datasets collected in-house. We found that RS with support vector machines (SVM) as the base classifier outperformed single classifiers as well as some of the most widely used classifier ensembles such as bagging, AdaBoost, random forest, and rotation forest. The closest rivals were the single SVM and bagging of SVM classifiers. We use kappa-error diagrams to understand the success of RS.

Structural brain changes in schizophrenia are well documented in the neuroimaging literature. The classical morphometric analyses of magnetic resonance imaging (MRI) data have recently been supplemented by diffusion tensor imaging (DTI), which mainly assesses changes in white matter (WM). DTI increasingly provides evidence for abnormal anatomical connectivity in schizophrenia, most often using fractional anisotropy (FA) as an indicator of the integrity of WM tracts. To better understand the clinical significance of such anatomical changes, we studied FA values in a whole-brain analysis comparing paranoid schizophrenic patients with a history of auditory hallucinations and matched healthy controls. The relationship of WM changes to psychopathology was assessed by correlating FA values with PANSS scores (positive symptoms and severity of auditory hallucinations) and with illness duration. Schizophrenic patients showed FA reductions indicating WM integrity disturbance in the prefrontal regions, external capsule, pyramidal tract, occipitofrontal fasciculus, superior and inferior longitudinal fasciculi, and corpus callosum. The arcuate fasciculus was the only tract which showed increased FA values in patients. Increased FA values in this region correlated with increased severity of auditory hallucinations and length of illness. Our results suggest that local changes in anatomical integrity of WM tracts in schizophrenia may be related to patients' clinical presentation.

An individual, goal-oriented cognitive rehabilitation intervention was conducted with AB, a 77-year-old woman with MCI. Outcomes were evaluated using a client-centred measure of goal achievement and an experimental associative learning task testing a skill practised in the intervention. Pre- and post-intervention fMRI scans were compared to examine changes in brain activation. Following intervention, AB showed improved performance on rehabilitation goals and on the associative learning task. There were significant decreases in brain activation in sensory areas and significant increases in memory-related areas. Both client-centred measures and fMRI may assist in detecting clinically-meaningful changes resulting from cognitive rehabilitation interventions.

Impairments in working memory (WM) are a core cognitive deficit in schizophrenia. Neurophysiological models suggest that deficits during WM maintenance in schizophrenia may be explained by abnormalities in the GABAergic system, which will lead to deficits in high-frequency oscillations. However, it is not yet clear which of the three WM phases (encoding, maintenance, retrieval) are affected by dysfunctional oscillatory activity. We investigated the relationship between impairments in oscillatory activity in a broad frequency range (3-100 Hz) and WM load in the different phases of WM in 14 patients with early-onset schizophrenia and 14 matched control participants using a delayed matching to sample paradigm. During encoding, successful memorization was predicted by evoked theta, alpha, and beta oscillatory activity in controls. Patients showed severe reductions in the evoked activity in these frequency bands. During early WM maintenance, patients showed a comparable WM load-dependent increase in induced alpha and gamma activity to controls. In contrast, during the later maintenance phase, patients showed a shift in the peak of induced gamma activity to the lower WM load conditions. Finally, induced theta and gamma activity were reduced in patients during retrieval. Our findings suggest that the WM deficit in schizophrenia is associated with impaired oscillatory activity during all phases of the task and that the cortical storage system reaches its capacity limit at lower loads. Inability to maintain oscillatory activity in specific frequency bands could thus result in the information overload that may underlie both cognitive deficits and psychopathological symptoms of schizophrenia.

Purpose: This review considers the application of functional magnetic resonance imaging (fMRI) to identify treatment effects and brain plasticity in cognition-focused interventions aimed at people with Alzheimer's disease (AD). At present there is little evidence available that bears directly on this question. Associative memory function is affected in the early stages of AD and also deteriorates disproportionately in comparison to other types of memory in healthy ageing., Methods: We review paradigms from the literature on face-name learning in fMRI in three groups (AD, mild cognitive impairment, and healthy ageing) with the aim of developing a paradigm to measure treatment effects and functional plasticity following cognitive intervention., Results: Previous studies have commonly selected participants with high levels of education, and have generally used challenging tasks, with considerable variations in level of task performance across studies. The findings of the review indicate that there is a need a simple face-name learning paradigm that can be used with people with AD, and which can be applied either as a single assessment tool to compare various subject groups or as an outcome tool to assess functional changes following a period of cognitive intervention., Conclusions: We make recommendations for such a paradigm and discuss pilot data showing the successful application of our paradigm in an individual with MCI.

The development of psychotherapy has been based on psychological theories and clinical effects. However, an investigation of the neurobiological mechanisms of psychological interventions is also needed in order to improve indication and prognosis, inform the choice of parallel pharmacotherapy, provide outcome measures and potentially even aid the development of new treatment protocols. This neurobiological investigation can be informed by animal models, for example of learning and conditioning, but will essentially need the non-invasive techniques of functional neuroimaging in order to assess psychotherapy effects on patients' brains, which will be reviewed here. Most research so far has been conducted in obsessive compulsive disorder (OCD), anxiety disorders and depression. Effects in OCD were particularly exciting in that both cognitive behavioural therapy and medication with a selective serotonin inhibitor led to a reduction in blood flow in the caudate nucleus. In phobia, brief courses of behavioural therapy produced marked reductions of paralimbic responses to offensive stimuli in line with the clinical improvement. Findings in depression are less consistent, with both increases and decreases in prefrontal metabolism being reported. However, they are important in pointing to different mechanisms for the clinical effects of pharmacotherapy (more "bottom up") and psychotherapy (more "top down"). For the future it would be desirable if the findings of psychotherapy changes to brain activation patterns were confirmed in larger groups with homogenous imaging protocols. Functional imaging has already made great contributions to the understanding of the neural correlates of psychopathology. For example, evidence converges to suggest that the subgenual cingulate is crucial for mood regulation. One current clinical application of these findings is deep brain stimulation in areas highlighted by such imaging studies. I will discuss their initial application in depression and OCD, and suggest potential alternative options based on recent developments in neurofeedback technology.

Person comparison is pervasive in social judgment and human decision making and yet its neural substrate is poorly explored. We measured brain activity when participants compared psychological (intelligence) and physical (height) characteristics of famous people and found activation of medial frontal, orbitofrontal and limbic areas and the temporoparietal junction. This network was largely driven by the psychological comparison, with activity being higher for intelligence than height comparison in several areas in medial prefrontal cortex, suggesting that their activation scales with the demand on person comparison. The person comparison network overlaps strikingly with that commonly described for classic theory of mind tasks. We interpret this overlap as indexing the use of perspective taking common to person comparison and theory of mind.

We investigated a 27-year old patient with paranoid schizophrenia. Brain activity related to visual hallucinations was found in higher visual areas corresponding to the content of the hallucinations (faces, bodies, scenes) and the hippocampus. We assume that the hippocampal activity is related to the retrieval of visual images from memory and that sensory cortex activity is related to the vividness of the perceptual experience.

Working memory and short-term memory are closely related in their cognitive architecture, capacity limitations, and functional neuroanatomy, which only partly overlap with those of long-term memory. The author reviews the functional neuroimaging literature on the commonalities and differences between working memory and short-term memory and the interplay of areas with modality-specific and supramodal representations in the brain networks supporting these fundamental cognitive processes. Sensory stores in the visual, auditory, and somatosensory cortex play a role in short-term memory, but supramodal parietal and frontal areas are often recruited as well. Classical working memory operations such as manipulation, protection against interference, or updating almost certainly require at least some degree of prefrontal support, but many pure maintenance tasks involve these areas as well. Although it seems that activity shifts from more posterior regions during encoding to more anterior regions during delay, some studies reported sustained delay activity in sensory areas as well. This spatiotemporal complexity of the short-term memory/working memory networks is mirrored in the activation patterns that may explain capacity constraints, which, although most prominent in the parietal cortex, seem to be pervasive across sensory and premotor areas. Finally, the author highlights open questions for cognitive neuroscience research of working memory, such as that of the mechanisms for integrating different types of content (binding) or those providing the link to long-term memory.

Whether the human brain is equipped with a special neural substrate for numbers, or rather with a common neural substrate for processing of several types of magnitudes, has been the topic of a long-standing debate. The present study addressed this question by using functional magnetic resonance imaging (fMRI) and event-related potentials (ERPs) together with the size-congruity paradigm, a Stroop-like task in which numerical values and physical sizes were varied independently. In the fMRI experiment, a region-of-interest analysis of the primary motor cortex revealed interference effects in the hemisphere ipsilateral to the response hand, indicating that the stimulus-stimulus conflict between numerical and physical magnitude is not completely resolved until response initiation. This result supports the assumption of distinct comparison mechanisms for physical size and numerical value. In the ERP experiment, the cognitive load was manipulated in order to probe the degree to which information processing is shared across cognitive systems. As in the fMRI experiment, we found that the stimulus-stimulus conflict between numerical and physical magnitude is not completely resolved until response initiation. However, such late interaction was found only in the low cognitive load condition. In contrast, in the high load condition, physical and numerical dimensions interacted only at the comparison stage. We concluded that the processing of magnitude can be subserved by shared or distinct neural substrates, depending on task requirements.

Most models of information processing in the brain assume that cognitive tasks can be broken down into components that are solved in sequential steps, from perception through a number of cognitive comparisons (e.g., memory) or transformations (e.g., language) to the preparation and execution of a motor response. The relative and absolute timing of these stages and the degree to which they occur parallel or in serial order has traditionally been investigated with behavioural methods, mainly reaction times. This classical mental chronometry has over the past decades been complemented with neurophysiological approaches, using event-related potentials (ERPs), functional magnetic resonance imaging (fMRI) and transcranial magnetic stimulation (TMS). This review highlights the contributions and limitations of these techniques and focuses on recent advances in the combination of ERPs and fMRI to elucidate working memory and number processing. It will be argued that similar design principles as established for behavioural studies of mental chronometry should apply to neurophysiological investigations as well.

Recent theoretical and empirical research on schizophrenia converges on the notion that core aspects of the pathophysiology of the disorder may arise from a dysfunction in the coordination of distributed neural activity. Synchronization of neural responses in the beta-band (15-30 Hz) and gamma-band range (30-80 Hz) has been implicated as a possible neural substrate for dysfunctional coordination in schizophrenia. To test this hypothesis, we examined the electroencephalography (EEG) activity in 19 patients with a Diagnostic and Statistical Manual of Mental Disorder, edition IV criteria, diagnosis of schizophrenia and 19 healthy control subjects during a Gestalt perception task. EEG data were analyzed for phase synchrony and induced spectral power as an index of neural synchronization. Schizophrenia patients were impaired significantly in the detection of images that required the grouping of stimulus elements into coherent object representations. This deficit was accompanied by longer reaction times in schizophrenia patients. Deficits in Gestalt perception in schizophrenia patients were associated with reduced phase synchrony in the beta-band (20-30 Hz), whereas induced spectral power in the gamma-band (40-70 Hz) was mainly intact. Our findings suggest that schizophrenia patients are impaired in the long-range synchronization of neural responses, which may reflect a core deficit in the coordination of neural activity and underlie the specific cognitive dysfunctions associated with the disorder.

Intracranial recordings, lesion studies, and the combination of functional imaging with source analysis have produced a solid body of evidence about the generators of the P300 event-related potential. Although it is impossible to square all findings obtained across and within methodologies, a consistent pattern of generators has emerged, with target-related responses in the parietal cortex and the cingulate and novelty-related activations mainly in the inferior parietal and prefrontal regions. Stimulus modality-specific contributions come from the inferior temporal and superior parietal cortex for the visual and from the superior temporal cortex for the auditory modality. The P300 continues to be an important signature of cognitive processes such as attention and working memory and of its dysfunction in neurologic and mental disorders. It is increasingly being investigated as a potential genetic marker of mental disorders. Knowledge about the generators of the P300 will be crucial for a better understanding of its cognitive significance and its continuing clinical application.

With life expectancy increasing continuously, the effects of neurodegeneration on brain function are a topic of ever increasing importance. Thus there is a need for tools and models that probe both the functional consequences of neurodegenerative processes and compensatory mechanisms that might occur. As neurodegenerative burden and compensatory mechanisms may change over time, these tools will ideally be applied multiple times over the lifespan. Specifically, in order to elucidate whether brain-activation patterns in Alzheimer's disease (AD) and in healthy aging follow general rules in the context of degeneration and compensation, it is necessary to compare functional brain-activation patterns during different states of neurodegeneration. This article integrates the findings of functional activation studies at different stages of neurodegeneration: in healthy aging, in subjects at high risk of developing dementia, in subjects with mild cognitive impairment (MCI), and in patients suffering from AD. We review existing theoretical models that aim to explain the underlying mechanisms of functional activation changes in aging and dementia, and we propose an integrative account, which allows for different neural response patterns depending on the amount of neuronal damage and the recruitment of compensatory pathways.