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Objective: To assess the cost-effectiveness of intensive versus conventional therapy for 8 years as applied in the Steno-2 study in patients with type 2 diabetes and microalbuminuria.Research Design and Methods: A Markov model was developed to incorporate event and risk data from Steno-2 and account Danish-specific costs to project life expectancy, quality-adjusted life expectancy (QALE), and lifetime direct medical costs expressed in year 2005 Euros. Clinical and cost outcomes were projected over patient lifetimes and discounted at 3% annually. Sensitivity analyses were performed.Results: Intensive treatment was associated with increased life expectancy, QALE, and lifetime costs compared with conventional treatment. Mean +/- SD undiscounted life expectancy was 18.1 +/- 7.9 years with intensive treatment and 16.2 +/- 7.3 years with conventional treatment (difference 1.9 years). Discounted life expectancy was 13.4 +/- 4.8 years with intensive treatment and 12.4 +/- 4.5 years with conventional treatment. Lifetime costs (discounted) for intensive and conventional treatment were euro45,521 +/- 19,697 and euro41,319 +/- 27,500, respectively (difference euro4,202). Increased costs with intensive treatment were due to increased pharmacy and consultation costs. Discounted QALE was 1.66 quality-adjusted life-years (QALYs) higher for intensive (10.2 +/- 3.6 QALYs) versus conventional (8.6 +/- 2.7 QALYs) treatment, resulting in an incremental cost-effectiveness ratio of euro2,538 per QALY gained. This is considered a conservative estimate because accounting prescription of generic drugs and capturing indirect costs would further favor intensified therapy.Conclusions: From a health care payer perspective in Denmark, intensive therapy was more cost-effective than conventional treatment. Assuming that patients in both arms were treated in a primary care setting, intensive therapy became dominant (cost- and lifesaving). [ABSTRACT FROM AUTHOR]

The representation of intelligence is achieved by patterns of connections among neurons in brains and machines. Brains grow continuously, such that their patterns of connections develop through activity-dependent specification, with the continuing ontogenesis of individual experience. The theory of active inference proposes that the developmental organization of sentient systems reflects general processes of informatic self-evidencing, through the minimization of free energy. We interpret this theory to imply that the mind may be described in information terms that are not dependent on a specific physical substrate. At a certain level of complexity, self-evidencing of living (self-organizing) information systems becomes hierarchical and reentrant, such that effective consciousness emerges as the consequence of a good regulator. We propose that these principles imply that an adequate reconstruction of the computational dynamics of an individual human brain/mind is possible with sufficient neuromorphic computational emulation.

In previous papers, we proposed that the dorsal attention system's top-down control is regulated by the dorsal division of the limbic system, providing a feedforward or impulsive form of control generating expectancies during active inference. In contrast, we proposed that the ventral attention system is regulated by the ventral limbic division, regulating feedback constraints and error-correction for active inference within the neocortical hierarchy. Here, we propose that these forms of cognitive control reflect vertical integration of subcortical arousal control systems that evolved for specific forms of behavior control. The feedforward impetus to action is regulated by phasic arousal, mediated by lemnothalamic projections from the reticular activating system of the lower brainstem, and then elaborated by the hippocampus and dorsal limbic division. In contrast, feedback constraint-based on environmental requirements-is regulated by the tonic activation furnished by collothalamic projections from the midbrain arousal control centers, and then sustained and elaborated by the amygdala, basal ganglia, and ventral limbic division. In an evolutionary-developmental analysis, understanding these differing forms of active affordance-for arousal and motor control within the subcortical vertebrate neuraxis-may help explain the evolution of active inference regulating the cognition of expectancy and error-correction within the mammalian 6-layered neocortex., (© The Author(s) 2023. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

There is an apparent continuity in human neural development that can be traced to venerable themes of vertebrate morphogenesis that have shaped the evolution of the reptilian telencephalon (including both primitive three-layered cortex and basal ganglia) and then the subsequent evolution of the mammalian six-layered neocortex. In this theoretical analysis, we propose that an evolutionary-developmental analysis of these general morphogenetic themes can help to explain the embryonic development of the dual divisions of the limbic system that control the dorsal and ventral networks of the human neocortex. These include the archicortical (dorsal limbic) Papez circuits regulated by the hippocampus that organize spatial, contextual memory, as well as the paleocortical (ventral limbic) circuits that organize object memory. We review evidence that these dorsal and ventral limbic divisions are controlled by the differential actions of brainstem lemnothalamic and midbrain collothalamic arousal control systems, respectively, thereby traversing the vertebrate subcortical neuraxis. These dual control systems are first seen shaping the phyletic morphogenesis of the archicortical and paleocortical foundations of the forebrain in embryogenesis. They then provide dual modes of activity-dependent synaptic organization in the active (lemnothalamic) and quiet (collothalamic) stages of fetal sleep. Finally, these regulatory systems mature to form the major systems of memory consolidation of postnatal development, including the rapid eye movement (lemnothalamic) consolidation of implicit memory and social attachment in the first year, and then-in a subsequent stage-the non-REM (collothalamic) consolidation of explicit memory that is integral to the autonomy and individuation of the second year of life., (© 2023 Wiley Periodicals LLC.)

Since its inception, the international quality standard ISO/IEC 17025 has been revised twice. The most recent edition adopted a new structure to align with other conformity assessment and quality management standards, harmonized the terminology with the International Vocabulary of Metrology and introduced the concept of risk-based thinking. This paper disseminates the experience of the IAEA Radiation Safety Technical Services Laboratory in successful transition and re-accreditation to ISO/IEC 17025:2017. It covers all stages of the transition cycle: from conducting a gap analysis between the existing quality system and the requirements in the revised standard, updating the corresponding quality documents, developing training and communication plans for laboratory personnel, to monitoring the changes and improving the system through auditing, management review and participation in proficiency testing schemes. Lessons learned about building operational resilience and maintaining a business continuity management system to prepare for, respond to, and recover from disruptions are considered., (© The Author(s) 2023. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

The connectional anatomy of the primate cortex is now well-defined by the Structural Model, in which adjacent cortical areas are interconnected in an organized network hierarchy of communication and control. The computational theory of "active inference" can be aligned with this architecture, proposing that predictions descend from higher association areas to be updated by ascending prediction errors from lower (i.e. primary) sensory and motor areas. Given the connectivity, the limbic networks at the apex of the cerebral hierarchy must then be responsible for the most general expectancies, which are propagated through the hierarchy to organize the multiple component network levels of experience and behavior. Anatomical evidence suggests that there are dual limbic divisions, reflecting archicortical (dorsal) and paleocortical (ventral) derivations, resulting in fundamentally different neural mechanisms for managing expectancies across the corticolimbic hierarchy. In the functional connectivity literature, the dorsal attention network is seen to provide top-down or endogenous control of attention, whereas the ventral attention network provides stimulus bound or exogenous attentional control. We review evidence indicating that the dorsal, archicortical division of the limbic system provides a feedforward, impulsive, endogenous mode of motive control, whereas the ventral, paleocortical limbic division provides feedback constraint linked to exogenous events., (© The Author(s) 2023. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Neurophysiological mechanisms are increasingly understood to constitute the foundations of human conscious experience. These include the capacity for ongoing memory, achieved through a hierarchy of reentrant cross-laminar connections across limbic, heteromodal, unimodal, and primary cortices. The neurophysiological mechanisms of consciousness also include the capacity for volitional direction of attention to the ongoing cognitive process, through a reentrant fronto-thalamo-cortical network regulation of the inhibitory thalamic reticular nucleus. More elusive is the way that discrete objects of subjective experience, such as the color of deep blue or the sound of middle C, could be generated by neural mechanisms. Explaining such ineffable qualities of subjective experience is what Chalmers has called "the hard problem of consciousness," which has divided modern neuroscientists and philosophers alike. We propose that insight into the appearance of the hard problem can be gained through integrating classical phenomenological studies of experience with recent progress in the differential neurophysiology of consolidating explicit versus implicit memory. Although the achievement of consciousness, once it is reflected upon, becomes explicit, the underlying process of generating consciousness, through neurophysiological mechanisms, is largely implicit. Studying the neurophysiological mechanisms of adaptive implicit memory, including brain stem, limbic, and thalamic regulation of neocortical representations, may lead to a more extended phenomenological understanding of both the neurophysiological process and the subjective experience of consciousness. NEW & NOTEWORTHY The process of consciousness, generating the qualia that may appear to be irreducible qualities of experience, can be understood to arise from neurophysiological mechanisms of memory. Implicit memory, organized by the lemnothalamic brain stem projections and dorsal limbic consolidation in REM sleep, supports the unconscious field and the quasi-conscious fringe of current awareness. Explicit memory, organized by the collothalamic midbrain projections and ventral limbic consolidation of NREM sleep, supports the focal objects of consciousness.

Current computational models of neocortical processing, described as predictive coding theory, are providing new ways of understanding Helmholtz's classical insight that perception cannot proceed in a data-driven fashion, but instead requires unconscious inference based on prior experience. Predictive coding is a Bayesian process, in which the operations at each lower level of the cortical hierarchy are predicted by prior projections of expectancies from a higher level, and are then updated by error-correction with lower level evidence. To generalize the predictive coding model to the human neocortex as a whole requires aligning the Bayesian negotiation of prior expectancies with sensory and motor evidence not only within the connectional architecture of the neocortex (primary sensory/motor, unimodal association areas, and heteromodal association areas) but also with the limbic cortex that forms the base for the adaptive control of the heteromodal areas and thereby the cerebral hemisphere as a whole. By reviewing the current evidence on the anatomy of the human corticolimbic connectivity (now formalized as the Structural Model) we address the problem of how limbic cortex resonates to the homeostatic, personal significance of events to provide Bayesian priors to organize the operations of predictive coding across the multiple levels of the neocortex. By reviewing both classical evidence and current models of control exerted between limbic and neocortical networks, we suggest a neuropsychological theory of human cognition, the adaptive Bayes process model, in which prior expectancies are not simply rationalized propositions, but rather affectively-charged expectancies that bias the interpretation of sensory data and action affordances to support allostasis, the motive control of expectancies for future events., (Copyright © 2021 Brain Electrophysiology Laboratory Company LLC. Published by Elsevier Ltd.. All rights reserved.)

Background: Initial observations with the human electroencephalogram (EEG) have interpreted slow oscillations (SOs) of the EEG during deep sleep (N3) as reflecting widespread surface-negative traveling waves that originate in frontal regions and propagate across the neocortex. However, mapping SOs with a high-density array shows the simultaneous appearance of posterior positive voltage fields in the EEG at the time of the frontal-negative fields, with the typical inversion point (apparent source) around the temporal lobe., Methods: Overnight 256-channel EEG recordings were gathered from 10 healthy young adults. Individual head conductivity models were created using each participant's own structural MRI. Source localization of SOs during N3 was then performed., Results: Electrical source localization models confirmed that these large waves were created by focal discharges within the ventral limbic cortex, including medial temporal and caudal orbitofrontal cortex., Conclusions: Although the functional neurophysiology of deep sleep involves interactions between limbic and neocortical networks, the large EEG deflections of deep sleep are not created by distributed traveling waves in lateral neocortex but instead by relatively focal limbic discharges., (Copyright © 2021 Brain Electrophysiology Laboratory Company. Published by Elsevier B.V. All rights reserved.)

Background: Researchers have proposed that impaired sleep may be a causal link in the progression from Mild Cognitive Impairment (MCI) to Alzheimer's Disease (AD). Several recent findings suggest that enhancing deep sleep (N3) may improve neurological health in persons with MCI, and buffer the risk for AD. Specifically, Transcranial Electrical Stimulation (TES) of frontal brain areas, the inferred source of the Slow Oscillations (SOs) of N3 sleep, can extend N3 sleep duration and improve declarative memory for recently learned information. Recent work in our laboratory using dense array Electroencephalography (dEEG) localized the sources of SOs to anterior limbic sites - suggesting that targeting these sites with TES may be more effective for enhancing N3., Methods: For the present study, we recruited 13 healthy adults (M = 42 years) to participate in three all-night sleep EEG recordings where they received low level (0.5 mA) TES designed to target anterior limbic areas and a sham stimulation (placebo). We used a convolutional neural network, trained and tested on professionally scored EEG sleep staging, to predict sleep stages for each recording., Results: When compared to the sham session, limbic-targeted TES significantly increased the duration of N3 sleep. TES also significantly increased spectral power in the 0.5-1 Hz frequency band (relative to pre-TES epochs) in left temporoparietal and left occipital scalp regions compared to sham., Conclusion: These results suggest that even low-level TES, when specifically targeting anterior limbic sites, can increase deep (N3) sleep and thereby contribute to healthy sleep quality., (Copyright © 2021 The Authors. Published by Elsevier B.V. All rights reserved.)

Performance evaluation is typically assessed as part of the approval procedure to verify that a dosimetry system fulfils specified national or international type-test requirements under representative exposure conditions that are expected to mimic workplace fields from the radiological activities being monitored. The International Atomic Energy Agency Radiation Safety Technical Services Laboratory has recently implemented an integrated radiophotoluminescence (RPL) personal dosimetry system developed by Chiyoda Technol Corporation. This paper reports on the successful verification of dosimetric performance properties of the RPL dosimetry system to IEC 62387:2020, in which the badges were exposed to a range of radiation energies and angles of incidence as well as other influence parameters. Characteristics under test included the coefficient of variation, non-linearity of response due to dose dependence as well as the energy and angular response to photon and beta radiation., (© The Author(s) 2020. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

We examined the effects of slow-pulsed transcranial electrical stimulation (TES) in suppressing epileptiform discharges in seven adults with refractory epilepsy. An MRI-based realistic head model was constructed for each subject and co-registered with 256-channel dense EEG (dEEG). Interictal spikes were localized, and TES targeted the cortical source of each subject's principal spike population. Targeted spikes were suppressed in five subject's (29/35 treatment days overall), and nontargeted spikes were suppressed in four subjects. Epileptiform activity did not worsen. This study suggests that this protocol, designed to induce long-term depression (LTD), is safe and effective in acute suppression of interictal epileptiform discharges., (© 2019 The Authors. Annals of Clinical and Translational Neurology published by Wiley Periodicals, Inc on behalf of American Neurological Association.)

Surgical resection of the seizure onset zone (SOZ) requires that this region of the cortex is accurately localized. The onset of a seizure may be marked by transient discharges, but it also may be accompanied by oscillatory, sinusoidal electrographic activity, such as the EEG theta rhythm. However, because of the superposition of the seizure signal with other electrical signals, including noise artifacts and non-seizure brain activity, noninvasive Electrical Source Imaging (ESI) of the ictal EEG activity at seizure onset remains a challenging task for surgical planning. In the present study, we localize the SOZ from oscillatory features of the EEG at the ictal onset using 256-channel high density electroencephalography (HD-EEG), exact sensor positions, and individual electrical head models constructed from the patient's T1 magnetic resonance image (MRI). Epileptic activities at the seizure onset were characterized with joint time-frequency analysis and source estimated by standardized low resolution electromagnetic tomography (sLORETA) inverse method. The consistency of this localization was examined across multiple seizures for individual patients. For validation, results were compared to three clinical criteria: (1) epileptogenic lesions, (2) seizure onset observed in intracranial EEG, and (3) successful surgical outcomes. In this set of 84 seizures, the onsets of 56 seizures could be localized. For the lateralization measure, the results from HD-EEG with interictal spikes (8/10) and with ictal onset (10/10) were more accurate than international 10-20 EEG for interictal spikes (5/10) and ictal onset (5/10). ESI from HD-EEG with ictal onset (9/10) had greater concordance to the clinical criteria than HD-EEG with interictal spikes (6/10). Noninvasive ESI of oscillatory features at ictal onset using 256-channel HD-EEG and high-resolution individual head models can make a useful contribution to the clinical localization of the SOZ in presurgical planning., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Adolescence is a sensitive period for the development of romantic relationships. During this period the maturation of frontolimbic networks is particularly important for the capacity to regulate emotional experiences. In previous research, both functional magnetic resonance imaging (fMRI) and dense array electroencephalography (dEEG) measures have suggested that responses in limbic regions are enhanced in adolescents experiencing social rejection. In the present research, we examined social acceptance and rejection from romantic partners as they engaged in a Chatroom Interact Task. Dual 128-channel dEEG systems were used to record neural responses to acceptance and rejection from both adolescent romantic partners and unfamiliar peers ( N = 75). We employed a two-step temporal principal component analysis (PCA) and spatial independent component analysis (ICA) approach to statistically identify the neural components related to social feedback. Results revealed that the early (288 ms) discrimination between acceptance and rejection reflected by the P3a component was significant for the romantic partner but not the unfamiliar peer. In contrast, the later (364 ms) P3b component discriminated between acceptance and rejection for both partners and peers. The two-step approach (PCA then ICA) was better able than either PCA or ICA alone in separating these components of the brain's electrical activity that reflected both temporal and spatial phases of the brain's processing of social feedback.

In pain management as well as other clinical applications of neuromodulation, it is important to consider the timing parameters influencing activity-dependent plasticity, including pulsed versus sustained currents, as well as the spatial action of electrical currents as they polarize the complex convolutions of the cortical mantle. These factors are of course related; studying temporal factors is not possible when the spatial resolution of current delivery to the cortex is so uncertain to make it unclear whether excitability is increased or decreased with anodal vs. cathodal current flow. In the present study we attempted to improve the targeting of specific cortical locations by applying current through flexible source-sink configurations of 256 electrodes in a geodesic array. We constructed a precision electric head model for 12 healthy individuals. Extraction of the individual's cortical surface allowed computation of the component of the induced current that is normal to the target cortical surface. In an effort to replicate the long-term depression (LTD) induced with pulsed protocols in invasive animal research and transcranial magnetic stimulation studies, we applied 100 ms pulses at 1.9 s intervals either in cortical-surface-anodal or cortical-surface-cathodal directions, with a placebo (sham) control. The results showed significant LTD of the motor evoked potential as a result of the cortical-surface-cathodal pulses in contrast to the placebo control, with a smaller but similar LTD effect for anodal pulses. The cathodal LTD after-effect was sustained over 90 min following current injection. These results support the feasibility of pulsed protocols with low total charge in non-invasive neuromodulation when the precision of targeting is improved with a dense electrode array and accurate head modeling.

Negative self-evaluation is an important psychological characteristic of depression. In order to study the underlying neural mechanisms, we examined event-related potentials (ERPs) during a self-evaluation task in a community sample (N = 150) of adults reporting a range of depressive symptoms. Principal components analysis (PCA) was used to separate processes that overlap in the average ERP, and neural source analysis was applied to localize the ERP components, with a particular focus on the frontal networks that are thought to be critical to affective self-regulation in depression. Consistent with previous research, individuals reporting greater depression showed enhanced negativity over medial frontal regions as well as attenuation of the late positive potential over parietal regions. Examining loadings of frontal sources on the ERP components showed that activity in the right inferior frontal region may be particularly important for depressed individuals: activity in this region declined as symptoms became more severe. Characterizing brain mechanisms of self-evaluation on the timescale of cognitive events may provide insight into the neural mechanisms of self-regulation that are important in cognitive therapy, and that could be made more amenable to change through increasing neuroplasticity with targeted non-invasive neuromodulation., (© The Author (2016). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.)

Background: Multiple noncephalic electrical sources superpose with brain signals in the recorded EEG. Blind source separation (BSS) methods such as independent component analysis (ICA) have been shown to separate noncephalic artifacts as unique components. However, robust and objective identification of artifact components remains a challenge in practice. In addition, with high dimensional data, ICA requires a large number of observations for stable solutions. Moreover, using signals from long recordings to provide the large observation set might violate the stationarity assumption of ICA due to signal changes over time., New Method: Instead of decomposing all channels simultaneously, subsets of channels are randomly selected and decomposed with ICA. With reduced dimensionality of the subsets, much less amount of data is required to derive stable components. To characterize each independent component, an artifact relevance index (ARI) is calculated by template matching each component with a model of the artifact. Automatic artifact identification is then implemented based on the statistical distribution of ARI of the numerous components generated., Results: The proposed permutation resampling for identification matching (PRIM) method effectively removed eye blink artifacts from both simulated and real EEG., Comparison With Existing Method: The average topomap correlation coefficient between the cleaned EEG and the ground truth is 0.89±0.01 for PRIM, compared with 0.64±0.05 for conventional ICA based method. The average relative root-mean-square error is 0.40±0.01 for PRIM, compared with 0.66±0.10 for conventional method., Conclusions: The proposed method overcame limitations of conventional ICA based method and succeeded in removing eye blink artifacts automatically., (Copyright © 2016 Elsevier B.V. All rights reserved.)

Learning is not a unitary phenomenon. Rather, learning progresses through stages, with the stages reflecting different challenges that require the support of specific cognitive processes that reflect the functions of different brain networks. A theory of general learning proposes that learning can be divided into early and late stages controlled by corticolimbic networks located in frontal and posterior brain regions, respectively. Recent human studies using dense-array EEG (dEEG) support these results by showing progressive increases in P3b amplitude (an Event Related Potential with estimated sources in posterior cingulate cortex and hippocampus) as participants acquire a new visuomotor skill. In the present study, the P3b was used to track the learning and performance of participants as they identify defensive football formations and make an appropriate response. Participants acquired the task over three days, and P3b latency and amplitude significantly changed when participants learned the task. As participants demonstrated further proficiency with extensive training, amplitude and latency changes in the P3b continued to closely mirror performance improvements. Source localization results across all days suggest that an important source generator of the P3b is located in the posterior cingulate cortex. Results from the study support prior findings and further suggest that the careful analysis of covert learning mechanisms and their underlying electrical signatures are a robust index of task competency.

BrainK is a set of automated procedures for characterizing the tissues of the human head from MRI, CT, and photogrammetry images. The tissue segmentation and cortical surface extraction support the primary goal of modeling the propagation of electrical currents through head tissues with a finite difference model (FDM) or finite element model (FEM) created from the BrainK geometries. The electrical head model is necessary for accurate source localization of dense array electroencephalographic (dEEG) measures from head surface electrodes. It is also necessary for accurate targeting of cerebral structures with transcranial current injection from those surface electrodes. BrainK must achieve five major tasks: image segmentation, registration of the MRI, CT, and sensor photogrammetry images, cortical surface reconstruction, dipole tessellation of the cortical surface, and Talairach transformation. We describe the approach to each task, and we compare the accuracies for the key tasks of tissue segmentation and cortical surface extraction in relation to existing research tools (FreeSurfer, FSL, SPM, and BrainVisa). BrainK achieves good accuracy with minimal or no user intervention, it deals well with poor quality MR images and tissue abnormalities, and it provides improved computational efficiency over existing research packages.

Research on neurobiological development is providing insight into the nature and mechanisms of human neural plasticity. These mechanisms appear to support two different forms of developmental learning. One form of learning could be described as externalizing, in which neural representations are highly responsive to environmental influences, as the child typically operates under a mode of hedonic approach. A second form of learning supports internalizing, in which motive control separates attention and self-regulation from the immediate influences of the context, particularly when the child faces conditions of avoidance and threat. The dorsal cortical networks of externalizing are organized around dorsal limbic (cingulate, septal, lateral hypothalamic, hippocampal, and ventral striatal) circuits. In contrast, the ventral cortical networks of internalizing are organized around ventral limbic (anterior temporal and orbital cortex, extended amygdala, dorsal striatal, and mediodorsal thalamic) circuits. These dual divisions of the limbic system in turn self-regulate their arousal levels through different brain stem and forebrain neuromodulator projection systems, with dorsal corticolimbic networks regulated strongly by locus coeruleus norepinephrine and brain stem raphe nucleus serotonin projection systems, and ventral corticolimbic networks regulated by ventral tegmental dopamine and forebrain acetylcholine projections. Because the arousal control systems appear to regulate specific properties of neural plasticity in development, an analysis of these systems explains differences between externalizing and internalizing at multiple levels of neural and psychological self-regulation. In neuroscience, the concept of critical periods has been applied to times when experience is essential for the maturation of sensory systems. In a more general neuropsychological analysis, certain periods of the child's development require successful self-regulation through the differential capacities for externalizing and internalizing.

The field of transcranial electrical stimulation (tES) has experienced significant growth in the past 15 years. One of the tES techniques leading this increased interest is transcranial direct current stimulation (tDCS). Significant research efforts have been devoted to determining the clinical potential of tDCS in humans. Despite the promising results obtained with tDCS in basic and clinical neuroscience, further progress has been impeded by a lack of clarity on international regulatory pathways. We therefore convened a group of research and clinician experts on tDCS to review the research and clinical use of tDCS. In this report, we review the regulatory status of tDCS, and we summarize the results according to research, off-label and compassionate use of tDCS in the following countries: Australia, Brazil, France, Germany, India, Iran, Italy, Portugal, South Korea, Taiwan and United States. Research use, off label treatment and compassionate use of tDCS are employed in most of the countries reviewed in this study. It is critical that a global or local effort is organized to pursue definite evidence to either approve and regulate or restrict the use of tDCS in clinical practice on the basis of adequate randomized controlled treatment trials.

Background: Root system architecture is important for water acquisition and nutrient acquisition for all crops. In soybean breeding programs, wild soybean alleles have been used successfully to enhance yield and seed composition traits, but have never been investigated to improve root system architecture. Therefore, in this study, high-density single-feature polymorphic markers and simple sequence repeats were used to map quantitative trait loci (QTLs) governing root system architecture in an inter-specific soybean mapping population developed from a cross between Glycine max and Glycine soja., Results: Wild and cultivated soybean both contributed alleles towards significant additive large effect QTLs on chromosome 6 and 7 for a longer total root length and root distribution, respectively. Epistatic effect QTLs were also identified for taproot length, average diameter, and root distribution. These root traits will influence the water and nutrient uptake in soybean. Two cell division-related genes (D type cyclin and auxin efflux carrier protein) with insertion/deletion variations might contribute to the shorter root phenotypes observed in G. soja compared with cultivated soybean. Based on the location of the QTLs and sequence information from a second G. soja accession, three genes (slow anion channel associated 1 like, Auxin responsive NEDD8-activating complex and peroxidase), each with a non-synonymous single nucleotide polymorphism mutation were identified, which may also contribute to changes in root architecture in the cultivated soybean. In addition, Apoptosis inhibitor 5-like on chromosome 7 and slow anion channel associated 1-like on chromosome 15 had epistatic interactions for taproot length QTLs in soybean., Conclusion: Rare alleles from a G. soja accession are expected to enhance our understanding of the genetic components involved in root architecture traits, and could be combined to improve root system and drought adaptation in soybean.

Electroencephalographic (EEG) oscillations in multiple frequency bands can be observed during functional activity of the cerebral cortex. An important question is whether activity of focal areas of cortex, such as during finger movements, is tracked by focal oscillatory EEG changes. Although a number of studies have compared EEG changes to functional MRI hemodynamic responses, we can find no previous research that relates the fMRI hemodynamic activity to localization of the multiple EEG frequency changes observed in motor tasks. In the present study, five participants performed similar thumb and finger movement tasks in parallel EEG and functional MRI studies. We examined changes in five frequency bands (from 5-120 Hz) and localized them using 256 dense-array EEG (dEEG) recordings and high-resolution individual head models. These localizations were compared with fMRI localizations in the same participants. Results showed that beta-band (14-30 Hz) desynchronizations (power decreases) were the most robust effects, appearing in all individuals, consistently localized to the hand region of the primary motor cortex, and consistently aligned with fMRI localizations.

Impacts of population structure on the evaluation of genomic heritability and prediction were investigated and quantified using high-density markers in diverse panels in rice and maize. Population structure is an important factor affecting estimation of genomic heritability and assessment of genomic prediction in stratified populations. In this study, our first objective was to assess effects of population structure on estimations of genomic heritability using the diversity panels in rice and maize. Results indicate population structure explained 33 and 7.5% of genomic heritability for rice and maize, respectively, depending on traits, with the remaining heritability explained by within-subpopulation variation. Estimates of within-subpopulation heritability were higher than that derived from quantitative trait loci identified in genome-wide association studies, suggesting 65% improvement in genetic gains. The second objective was to evaluate effects of population structure on genomic prediction using cross-validation experiments. When population structure exists in both training and validation sets, correcting for population structure led to a significant decrease in accuracy with genomic prediction. In contrast, when prediction was limited to a specific subpopulation, population structure showed little effect on accuracy and within-subpopulation genetic variance dominated predictions. Finally, effects of genomic heritability on genomic prediction were investigated. Accuracies with genomic prediction increased with genomic heritability in both training and validation sets, with the former showing a slightly greater impact. In summary, our results suggest that the population structure contribution to genomic prediction varies based on prediction strategies, and is also affected by the genetic architectures of traits and populations. In practical breeding, these conclusions may be helpful to better understand and utilize the different genetic resources in genomic prediction.

Working memory (WM) is one of the most studied cognitive constructs. Although many neuroimaging studies have identified brain networks involved in WM, the time course of these networks remains unclear. In this paper we use dense-array electroencephalography (dEEG) to capture neural signals during performance of a standard WM task, the n-back task, and a blend of principal components analysis and independent components analysis (PCA/ICA) to statistically identify networks of WM and their time courses. Results reveal a visual cortex centric network, that also includes the posterior cingulate cortex, that is active prior to stimulus onset and that appears to reflect anticipatory, attention-related processes. After stimulus onset, the ventromedial prefrontal cortex, lateral prefrontal prefrontal cortex, and temporal poles become associated with the prestimulus network. This second network appears to reflect executive control processes. Following activation of the second network, the cortices of the temporo-parietal junction with the temporal lobe structures seen in the first and second networks re-engage. This third network appears to reflect activity of the ventral attention network involved in control of attentional reorientation. The results point to important temporal features of network dynamics that integrate multiple subsystems of the ventral attention network with the default mode network in the performance of working memory tasks.

[This corrects the article on p. 42 in vol. 4, PMID: 23717298.].

We examined brain mechanisms of self-evaluation in a sample of adolescents using dense array EEG (dEEG), neural source analysis, and a novel psychometric weighting method. Each trial of the self-evaluation task was weighted according to its correlation with negative affect and positive affect, such that unique ERP averages were constructed for each mood dimension. Results support the hypothesis that the emotional influence on self-appraisal is dimension specific. Negative affect was associated with more robust ERP responses 300 ms into the decision-making epoch. Affect-weighted source analyses further differentiated dorsal-posterior and ventral-anterior features of brain activity. The integration of psychometric weights and dEEG neural source analysis may provide new clues to the neural mechanisms of affective influence on self-evaluative cognition., (Copyright © 2013 Society for Psychophysiological Research.)

Epilepsy may reflect a focal abnormality of cerebral tissue, but the generation of seizures typically involves propagation of abnormal activity through cerebral networks. We examined epileptiform discharges (spikes) with dense array electroencephalography (dEEG) in five patients to search for the possible engagement of pathological networks. Source analysis was conducted with individual electrical head models for each patient, including sensor position measurement for registration with MRI with geodesic photogrammetry; tissue segmentation and skull conductivity modeling with an atlas skull warped to each patient's MRI; cortical surface extraction and tessellation into 1 cm(2) equivalent dipole patches; inverse source estimation with either minimum norm or cortical surface Laplacian constraints; and spectral coherence computed among equivalent dipoles aggregated within Brodmann areas with 1 Hz resolution from 1 to 70 Hz. These analyses revealed characteristic source coherence patterns in each patient during the pre-spike, spike, and post-spike intervals. For one patient with both spikes and seizure onset localized to a single temporal lobe, we observed a cluster of apparently abnormal coherences over the involved temporal lobe. For the other patients, there were apparently characteristic coherence patterns associated with the discharges, and in some cases these appeared to reflect abnormal temporal lobe synchronization, but the coherence patterns for these patients were not easily related to an unequivocal epileptogenic zone. In contrast, simple localization of the site of onset of the spike discharge, and/or the site of onset of the seizure, with non-invasive 256 dEEG was useful in predicting the characteristic site of seizure onset for those cases that were verified by intracranial EEG and/or by surgical outcome.

Rationale: Dense array EEG (dEEG) evenly covers the whole head surface with over 100 channels contributing to more accurate electrical source imaging due to the higher spatial and temporal resolution. Several studies have shown the clinical utility of dEEG in presurgical clinical evaluation of epilepsy. However validation studies measuring the accuracy of dEEG source imaging are still needed. This can be achieved through simultaneously recording both scalp dEEG with intracranial electrodes (icEEG), which is considered as the true measure of cortical activity at the source. The purpose of this study is to evaluate the accuracy of 256-channel dEEG electrical source estimation for interictal spikes., Methods: Four patients with medically refractory neocortical epilepsy, all surgical candidates, underwent subdural electrode implantation to determine ictal onset and define functional areas. One patient showed a lesion on the magnetic resonance imaging in the right parietal lobe. The patient underwent simultaneous recording of interictal spikes by both scalp 256-channelsvdEEG and icEEG. The dEEG was used to non-invasively estimate the source of the interictal spikes detected by the 256-channel dEEG array, which was then compared to the activity measured directly at the source by the icEEG., Results: From the four patients, a total of 287 interictal spikes were measured with the icEEG. One hundred fifty-five of the 287 spikes (54%) were visually detected by the dEEG upon examination of the 256 channel head surface array. The spike amplitudes detected by the 256-channel dEEG correlated with icEEG spike amplitudes (p < 0.01). All spikes detected in dEEG were localized to the same lobe correctly., Conclusion: Our study demonstrates that 256-channel dEEG can reliably detect interictal spikes and localize them with reasonable accuracy. Two hundred fifty-six-channel dEEG may be clinically useful in the presurgical workup for epilepsy and also reduce the need for invasive EEG evaluation.

Most of previous empirical studies with genome-wide prediction were focused on within-environment prediction based on a single-environment (SE) model. In this study, we evaluated accuracy improvements of across-environment prediction by using genetic and residual covariance across correlated environments. Predictions with a multienvironment (ME) model were evaluated for two corn polygenic leaf structure traits, leaf length and leaf width, based on within-population (WP) and across-population (AP) experiments using a large maize nested association mapping data set consisting of 25 populations of recombinant inbred-lines. To make our study more applicable to plant breeding, two cross-validation schemes were used by evaluating accuracies of (CV1) predicting unobserved phenotypes of untested lines and (CV2) predicting unobserved phenotypes of lines that have been evaluated in some environments but not others. We concluded that (1) genome-wide prediction provided greater prediction accuracies than traditional quantitative trait loci-based prediction in both WP and AP and provided more advantages over quantitative trait loci -based prediction for WP than for AP. (2) Prediction accuracy with ME was significantly greater than that attained by SE in CV1 and CV2, and gains with ME over SE were greater in CV2 than in CV1. These gains were also greater in WP than in AP in both CV1 and CV2. (3) Gains with ME over SE attributed to genetic correlation between environments, with little effect from residual correlation. Impacts of marker density on predictions also were investigated in this study.

Objective: Dense-array EEG recordings are now commonplace in research and gaining acceptance in clinical settings. Application of many sensors with traditional electrolytes is time consuming. Saline electrolytes can be used to minimize application time but recording duration is limited due to evaporation. In the present study, we evaluate a NIPAm (N-isopropyl acrylamide:acrylic acid) base electrolyte extender for use with saline electrolytes., Methods: Sensor-scalp impedances and EEG data quality acquired with the electrolyte extender are compared with those obtained for saline and an EEG electrolyte commonly used in clinical exams (Elefix)., Results: The results show that when used in conjunction with saline, electrode-scalp impedances and data across the EEG spectrum are comparable with those obtained using Elefix EEG paste., Conclusions: When used in conjunction with saline, the electrolyte extender permits rapid application of dense-sensor arrays and stable, high-quality EEG data to be obtained for at least 4.5 h., Significance: This is an enabling technology that will make benefits of dense-array EEG recordings practical for clinical applications., (Copyright © 2011 Elsevier B.V. All rights reserved.)

In comparison to conventional marker-assisted selection (MAS), which utilizes only a subset of genetic markers associated with a trait to predict breeding values (BVs), genome-wide selection (GWS) improves prediction accuracies by incorporating all markers into a model simultaneously. This strategy avoids risks of missing quantitative trait loci (QTL) with small effects. Here, we evaluated the accuracy of prediction for three corn flowering traits days to silking, days to anthesis, and anthesis-silking interval with GWS based on cross-validation experiments using a large data set of 25 nested association mapping populations in maize (Zea mays). We found that GWS via ridge regression-best linear unbiased prediction (RR-BLUP) gave significantly higher predictions compared to MAS utilizing composite interval mapping (CIM). The CIM method may be selected over multiple linear regression to decrease over-estimations of the efficiency of GWS over a MAS strategy. The RR-BLUP method was the preferred method for estimating marker effects in GWS with prediction accuracies comparable to or greater than BayesA and BayesB. The accuracy with RR-BLUP increased with training sample proportion, marker density, and heritability until it reached a plateau. In general, gains in accuracy with RR-BLUP over CIM increased with decreases of these factors. Compared to training sample proportion, the accuracy of prediction with RR-BLUP was relatively insensitive to marker density.

Purpose: To evaluate the clinical utility of dense array electroencephalography (dEEG) for the detection yield and localization of interictal spikes in mesial temporal lobe epilepsy., Methods: We simultaneously recorded 256-channel dEEG and intracranial electroencephalography (icEEG) implanted over the lateral and mesial temporal lobe in patients with intractable epilepsy. We calculated the dEEG spike detection rate for mesial temporal spikes which were confirmed by icEEG and applied source estimation to dEEG to compare noninvasive localization to the invasive recordings., Results: 339 of 760 interictal spikes (45%) were detected by dEEG examining the 256-channel head surface array. The average icEEG amplitude of dEEG detectable spikes was 1083 μV, and that of dEEG undetectable spikes was 780 μV (P<0.05). All spikes detected in dEEG were localized to the temporal lobe. 295 of 339 spikes (87%) were well localized in mesial temporal lobe, close to the position confirmed by subdural electrodes., Significance: 256-channel dEEG may provide more precise information for the localization of interictal epileptiform discharges than conventional EEG or MEG in patients with deep spike foci. 256-channel dEEG may be clinically useful in the presurgical work-up for epilepsy, providing accurate noninvasive guidance for the placement of intracranial electrodes., (Copyright © 2011 Elsevier B.V. All rights reserved.)

Purpose. To evaluate the clinical utility of dense array electroencephalography (dEEG) for detecting and localizing interictal spikes in temporal lobe epilepsy. Methods. Simultaneous invasive and noninvasive recordings were performed across two different groups. (1) The first group underwent both noninvasive recording with 128 channels of (scalp) dEEG and invasive sphenoidal electrode recording. (2) The second group underwent both noninvasive recording with 256 channels of (scalp) dEEG and invasive intracranial EEG (icEEG) involving coverage with grids and strips over the lateral and mesial temporal lobe. A noninvasive to noninvasive comparison was made comparing the overall spike detection rate of the dEEG to that of conventional 10/20 EEG. A noninvasive to invasive comparison was made comparing the spike detection rate of dEEG to that of conventional 10/20 EEG plus sphenoidal electrodes. And finally, a noninvasive to invasive evaluation measuring the source localization ability of the dEEG using the icEEG as validation. Results. In the 128-channel dEEG study (1), 90.4% of the interictal spikes detected by the dEEG were not detected in the 10/20 montage. 91% of the dEEG-detected spikes were accurately localized to the medial temporal lobe. In the 256-channel dEEG study (2), 218 of 519 interictal spikes (42%) were detected by dEEG. 85% of these spikes were accurately localized to the medial temporal lobe, close to the position confirmed by subdural electrodes. Conclusion. Dense array EEG may provide more precise information than conventional EEG and has a potential for providing an alternative to sphenoidal electrode monitoring in patients with temporal lobe epilepsy.

In event-related potential (ERP) research, the average potential over many trials is a useful measure, but it obscures temporal variability across trials that may be functionally significant. Familiar ERP components have been shown to reflect the phase shifting of oscillatory activity that is present in varying degrees before the event. Even with single trials, understanding the underlying neural activity may require methods of dealing with the spatial superposition of neural signals at the head surface electrodes. We conclude with an illustration in which the modulation of averaged ERPs by trait anxiety may be related to underlying sources of theta oscillations.

Neurophysiological evidence from animal studies suggests that frontal corticolimbic systems support early stages of learning, whereas later stages involve context representation formed in hippocampus and posterior cingulate cortex. In dense-array EEG studies of human learning, we observed brain activity in medial prefrontal cortex (the medial frontal negativity or MFN) was not only observed in early stages, but, surprisingly, continued to increase as learning progressed. In the present study we investigated this finding by examining MFN amplitude as participants learned an arbitrary associative learning task over three sessions. On the fourth session the same task with new stimuli was presented to assess changes in MFN amplitude. The results showed that MFN amplitude continued to increase with practice over the first three sessions, in contrast to P3 amplitudes. Even when participants were presented with new stimuli in session 4, MFN amplitude was larger than that observed in the first session. Furthermore, MFN activity from the third session predicted learning rate in the fourth session. The results point to an interaction between early and late stages in which learning results in corticolimbic consolidation of cognitive context models that facilitate new learning in similar contexts.

Aim: To synthesise key outcomes data from cost-effectiveness studies in diabetes, in the UK setting, and describe a narrative for the evidence-base, in order to understand the direction that future health economics research in this field could be heading., Methods: The peer-reviewed literature was searched at http://www.pubmed.com for health economics analyses in diabetes in the UK setting published between 1995 and 2008, using the keywords: "costs", "cost-effectiveness", "diabetes", "UK". Studies on screening for diabetes or prevention of diabetes were excluded, along with studies that looked purely at cost of diabetes treatment or monitoring., Results: There were over 350 hits on MEDLINE. A total of 23 articles were identified and reviewed. 18 studies were in type 2, two in type 1 and three studies in both types 1 and type 2 diabetes. All studies evaluated treatment from the perspective of the NHS, with the time horizons varying from 12 months to patient lifetimes. 13 studies estimated quality-adjusted life expectancy (QALE). The majority of studies used health economics modelling techniques to project clinical benefit and cost outcomes beyond the context of clinical trials, with Markov-type models predominating. The United Kingdom Prospective Study of Diabetes was the most frequently cited source of clinical effectiveness and cost data. Most studies were funded by the pharmaceutical industry and evaluated more expensive products, rather than cheaper generic therapies such as human insulin and metformin monotherapy., Conclusion: Treatment-to-target in patients with diabetes in the UK is generally cost-effective and sometimes cost-saving vs. standard care. Ongoing health economics analysis in diabetes is essential as new clinical data are published. Future analysis of clinical and cost outcomes in diabetes could be expected to look beyond the impact of interventions on HbA1c in isolation, as manufacturers seek to differentiate innovative products in the market. Furthermore, it is anticipated that the competitiveness in the market for interventions in diabetes will lead to future cost-effectiveness analysis taking more interest in comparisons of off-patent medication and generic, fixed-dose combination therapies., (Copyright © 2010 Primary Care Diabetes Europe. Published by Elsevier Ltd. All rights reserved.)

The present paper proposes that four neuromodulator systems underpin highly generalized behavioral sets, but each targets either dorsomedial or ventrolateral cortical systems, where it produces its effects in either a proactive or reactive orientation to the environment. This way systems are discriminated that control reactive approach (dopaminergic), reactive avoidance (cholinergic), proactive behavior (noradrenergic), and withdrawal (serotonergic). This model is compared with models of temperament, affect, personality, and so-called two-system models from psychology. Although the present model converges with previous models that point to a basic scheme underlying temperamental and affective space, at the same time it suggest that specific additional discriminations are necessary to improve descriptive fit to data and solve inconsistencies and confusions. We demonstrate how proactive and reactive actions and controls can be confused, and that this has many potential implications for psychology and neurobiology. We uncover conceptual problems regarding constructs such as effortful control, positive affect, approach-avoidance, extraversion, impulsivity, impulse-control, and goal-directedness of behavior. By delineating those problems, our approach also opens up ways to tackle them.