Prior-guided individualized thalamic parcellation based on local diffusion characteristics.

Comprising numerous subnuclei, the thalamus intricately interconnects the cortex and subcortex, orchestrating various facets of brain functions. Extracting personalized parcellation patterns for these subnuclei is crucial, as different thalamic nuclei play varying roles in cognition and serve as therapeutic targets for neuromodulation. However, accurately delineating the thalamic nuclei boundary at the individual level is challenging due to intersubject variability. In this study, we proposed a prior-guided parcellation (PG-par) method to achieve robust individualized thalamic parcellation based on a central-boundary prior. We first constructed probabilistic atlas of thalamic nuclei using high-quality diffusion MRI datasets based on the local diffusion characteristics. Subsequently, high-probability voxels in the probabilistic atlas were utilized as prior guidance to train unique multiple classification models for each subject based on a multilayer perceptron. Finally, we employed the trained model to predict the parcellation labels for thalamic voxels and construct individualized thalamic parcellation. Through a test-retest assessment, the proposed prior-guided individualized thalamic parcellation exhibited excellent reproducibility and the capacity to detect individual variability. Compared with group atlas registration and individual clustering parcellation, the proposed PG-par demonstrated superior parcellation performance under different scanning protocols and clinic settings. Furthermore, the prior-guided individualized parcellation exhibited better correspondence with the histological staining atlas. The proposed prior-guided individualized thalamic parcellation method contributes to the personalized modeling of brain parcellation.

Evaluating the influence of anatomical accuracy and electrode positions on EEG forward solutions.

Generating realistic volume conductor models for forward calculations in electroencephalography (EEG) is not trivial and several factors contribute to the accuracy of such models, two of which are its anatomical accuracy and the accuracy with which electrode positions are known. Here, we investigate effects of anatomical accuracy by comparing forward solutions from SimNIBS, a tool which allows state-of-the-art anatomical modeling, with well-established pipelines in MNE-Python and FieldTrip. We also compare different ways of specifying electrode locations when digitized positions are not available such as transformation of measured positions from standard space and transformation of a manufacturer layout. Substantial effects of anatomical accuracy were seen throughout the entire brain both in terms of field topography and magnitude with SimNIBS generally being more accurate than the pipelines in MNE-Python and FieldTrip. Topographic and magnitude effects were particularly pronounced for MNE-Python which uses a three-layer boundary element method (BEM) model. We attribute these mainly to the coarse representation of the anatomy used in this model, in particular differences in skull and cerebrospinal fluid (CSF). Effects of electrode specification method were evident in occipital and posterior areas when using a transformed manufacturer layout whereas transforming measured positions from standard space generally resulted in smaller errors. We suggest modeling the anatomy of the volume conductor as accurately possible and we hope to facilitate this by making it easy to export simulations from SimNIBS to MNE-Python and FieldTrip for further analysis. Likewise, if digitized electrode positions are not available, a set of measured positions on a standard head template may be preferable to those specified by the manufacturer.

Dynamic involvement of premotor and supplementary motor areas in bimanual pinch force control.

Many activities of daily living require quick shifts between symmetric and asymmetric bimanual actions. Bimanual motor control has been mostly studied during continuous repetitive tasks, while little research has been carried out in experimental settings requiring dynamic changes in motor output generated by both hands. Here, we performed functional magnetic resonance imaging (MRI) while healthy volunteers performed a visually guided, bimanual pinch force task. This enabled us to map functional activity and connectivity of premotor and motor areas during bimanual pinch force control in different task contexts, requiring mirror-symmetric or inverse-asymmetric changes in discrete pinch force exerted with the right and left hand. The bilateral dorsal premotor cortex showed increased activity and effective coupling to the ipsilateral supplementary motor area (SMA) in the inverse-asymmetric context compared to the mirror-symmetric context of bimanual pinch force control while the SMA showed increased negative coupling to visual areas. Task-related activity of a cluster in the left caudal SMA also scaled positively with the degree of synchronous initiation of bilateral pinch force adjustments, irrespectively of the task context. The results suggest that the dorsal premotor cortex mediates increasing complexity of bimanual coordination by increasing coupling to the SMA while SMA provides feedback about motor actions to the sensory system.

Uncovering the genetic profiles underlying the intrinsic organization of the human cerebellum.

The functional diversity of the human cerebellum is largely believed to be derived more from its extensive connections rather than being limited to its mostly invariant architecture. However, whether and how the determination of cerebellar connections in its intrinsic organization interact with microscale gene expression is still unknown. Here we decode the genetic profiles of the cerebellar functional organization by investigating the genetic substrates simultaneously linking cerebellar functional heterogeneity and its drivers, i.e., the connections. We not only identified 443 network-specific genes but also discovered that their co-expression pattern correlated strongly with intra-cerebellar functional connectivity (FC). Ninety of these genes were also linked to the FC of cortico-cerebellar cognitive-limbic networks. To further discover the biological functions of these genes, we performed a "virtual gene knock-out" by observing the change in the coupling between gene co-expression and FC and divided the genes into two subsets, i.e., a positive gene contribution indicator (GCI+) involved in cerebellar neurodevelopment and a negative gene set (GCI-) related to neurotransmission. A more interesting finding is that GCI- is significantly linked with the cerebellar connectivity-behavior association and many recognized brain diseases that are closely linked with the cerebellar functional abnormalities. Our results could collectively help to rethink the genetic substrates underlying the cerebellar functional organization and offer possible micro-macro interacted mechanistic interpretations of the cerebellum-involved high order functions and dysfunctions in neuropsychiatric disorders.

The Myelin Content of the Human Precentral Hand Knob Reflects Interindividual Differences in Manual Motor Control at the Physiological and Behavioral Level.

The primary motor cortex hand area (M1HAND) and adjacent dorsal premotor cortex (PMd) form the so-called motor hand knob in the precentral gyrus. M1HAND and PMd are critical for dexterous hand use and are densely interconnected via corticocortical axons, lacking a sharp demarcating border. In 24 young right-handed volunteers, we performed multimodal mapping to delineate the relationship between structure and function in the right motor hand knob. Quantitative structural magnetic resonance imaging (MRI) at 3 tesla yielded regional R1 maps as a proxy of cortical myelin content. Participants also underwent functional MRI (fMRI). We mapped task-related activation and temporal precision, while they performed a visuomotor synchronization task requiring visually cued abduction movements with the left index or little finger. We also performed sulcus-aligned transcranial magnetic stimulation of the motor hand knob to localize the optimal site (hotspot) for evoking a motor evoked potential (MEP) in two intrinsic hand muscles. Individual motor hotspot locations varied along the rostrocaudal axis. The more rostral the motor hotspot location in the precentral crown, the longer were corticomotor MEP latencies. "Hotspot rostrality" was associated with the regional myelin content in the precentral hand knob. Cortical myelin content also correlated positively with task-related activation of the precentral crown and temporal precision during the visuomotor synchronization task. Together, our results suggest a link among cortical myelination, the spatial cortical representation, and temporal precision of finger movements. We hypothesize that the myelination of cortical axons facilitates neuronal integration in PMd and M1HAND and, hereby, promotes the precise timing of movements.SIGNIFICANCE STATEMENT Here we used magnetic resonance imaging and transcranial magnetic stimulation of the precentral motor hand knob to test for a link among cortical myelin content, functional corticomotor representations, and manual motor control. A higher myelin content of the precentral motor hand knob was associated with more rostral corticomotor presentations, with stronger task-related activation and a higher precision of movement timing during a visuomotor synchronization task. We propose that a high precentral myelin content enables fast and precise neuronal integration in M1 (primary motor cortex) and dorsal premotor cortex, resulting in higher temporal precision during dexterous hand use. Our results identify the degree of myelination as an important structural feature of the neocortex that is tightly linked to the function and behavior supported by the cortical area.

Accessibility of cortical regions to focal TES: Dependence on spatial position, safety, and practical constraints.

Transcranial electric stimulation (TES) can modulate intrinsic neural activity in the brain by injecting weak currents through electrodes attached to the scalp. TES has been widely used as a neuroscience tool to investigate how behavioural and physiological variables of brain function are modulated by electric stimulation of specific brain regions. For an unambiguous interpretation of TES experiments, it is important that the electric fields can be steered towards one or several brain regions-of-interest. However, the conductive proprieties of the human head impose inherent physical limitations on how focal the electric fields in the brain produced by multi-electrode TES can be. As a rule of thumb, it is not feasible to selectively target deep brain areas with TES, although focusing the field in some specific deeper locations might be possible due to favourable conductive properties in the surrounding tissue. In the present study, we first propose a computationally efficient method for the automatic determination of electrode placements and stimulation intensities to optimally affect a given target position. We provide a robust implementation of the optimization procedure that is able to adhere to safety constraints, while explicitly controlling both the number of active electrodes and the angular deviation of the field in the target area relative to the desired field direction. Leveraging the high computational efficiency of our method, we systematically assess the achievable focality of multi-electrode TES for all cortex positions, thereby investigating the dependence on the chosen constraints. Our results provide comprehensive insight into the limitations regarding the achievable TES dose and focality that are imposed by the biophysical constraints and the safety considerations of TES.

Getting to grips with endoscopy - Learning endoscopic surgical skills induces bi-hemispheric plasticity of the grasping network.

Endoscopic surgery requires skilled bimanual use of complex instruments that extend the peri-personal workspace. To delineate brain structures involved in learning such surgical skills, 48 medical students without surgical experience were randomly assigned to five training sessions on a virtual-reality endoscopy simulator or to a non-training group. Brain activity was probed with functional MRI while participants performed endoscopic tasks. Repeated task performance in the scanner was sufficient to enhance task-related activity in left ventral premotor cortex (PMv) and the anterior Intraparietal Sulcus (aIPS). Simulator training induced additional increases in task-related activation in right PMv and aIPS and reduced effective connectivity from left to right PMv. Skill improvement after training scaled with stronger task-related activation of the lateral left primary motor hand area (M1-HAND). The results suggest that a bilateral fronto-parietal grasping network and left M1-HAND are engaged in bimanual learning of tool-based manipulations in an extended peri-personal space.

Searchlight classification based on Amplitude of Low Frequency Fluctuation and functional connectivity in individuals with obsessive-compulsive symptoms.

INTRODUCTION: Investigating obsessive-compulsive symptoms in subclinical populations provides a useful framework for understanding the early development of obsessive-compulsive spectrum disorders. The present study aimed to apply searchlight classification analysis on resting-state functional magnetic resonance imaging data to identify potential brain markers in subclinical individuals with obsessive-compulsive symptoms. METHODS: In this observational study, 40 college students with high obsessive-compulsive symptom scores and 40 with low obsessive-compulsive symptom scores were recruited from universities in China. We conducted searchlight classification and comparison analysis between the two groups based on Amplitude of Low Frequency Fluctuation (ALFF), fraction ALFF (fALFF) and resting-state functional connectivity using searchlight classification. RESULTS: We found that the highest accuracy rate in differentiating between the two groups was 85.00%. Significant discriminating features included the ALFF of the left medial superior frontal gyrus and the functional connectivity between the right thalamus and the bilateral medial superior frontal gyrus, and the right putamen, as well as the functional connectivity between the left caudate and the right insula. CONCLUSIONS: These findings highlight the specific and distinguishing brain functional abnormalities associated with obsessive-compulsive symptoms.

Tuning the Brake While Raising the Stake: Network Dynamics during Sequential Decision-Making.

UNLABELLED: When gathering valued goods, risk and reward are often coupled and escalate over time, for instance, during foraging, trading, or gambling. This escalating frame requires agents to continuously balance expectations of reward against those of risk. To address how the human brain dynamically computes these tradeoffs, we performed whole-brain fMRI while healthy young individuals engaged in a sequential gambling task. Participants were repeatedly confronted with the option to continue with throwing a die to accumulate monetary reward under escalating risk, or the alternative option to stop to bank the current balance. Within each gambling round, the accumulation of gains gradually increased reaction times for "continue" choices, indicating growing uncertainty in the decision to continue. Neural activity evoked by "continue" choices was associated with growing activity and connectivity of a cortico-subcortical "braking" network that positively scaled with the accumulated gains, including pre-supplementary motor area (pre-SMA), inferior frontal gyrus, caudate, and subthalamic nucleus (STN). The influence of the STN on continue-evoked activity in the pre-SMA was predicted by interindividual differences in risk-aversion attitudes expressed during the gambling task. Furthermore, activity in dorsal anterior cingulate cortex (ACC) reflected individual choice tendencies by showing increased activation when subjects made nondefault "continue" choices despite an increasing tendency to stop, but ACC activity did not change in proportion with subjective choice uncertainty. Together, the results implicate a key role of dorsal ACC, pre-SMA, inferior frontal gyrus, and STN in computing the trade-off between escalating reward and risk in sequential decision-making. SIGNIFICANCE STATEMENT: Using a paradigm where subjects experienced increasing potential rewards coupled with increasing risk, this study addressed two unresolved questions in the field of decision-making: First, we investigated an "inhibitory" network of regions that has so far been investigated with externally cued action inhibition. In this study, we show that the dynamics in this network under increasingly risky decisions are predictive of subjects' risk attitudes. Second, we contribute to a currently ongoing debate about the anterior cingulate cortex's role in sequential foraging decisions by showing that its activity is related to making nondefault choices rather than to choice uncertainty.

How to target inter-regional phase synchronization with dual-site Transcranial Alternating Current Stimulation.

Large-scale synchronization of neural oscillations is a key mechanism for functional information exchange among brain areas. Dual-site Transcranial Alternating Current Stimulation (ds-TACS) has been recently introduced as non-invasive technique to manipulate the temporal phase relationship of local oscillations in two connected cortical areas. While the frequency of ds-TACS is matched, the phase of stimulation is either identical (in-phase stimulation) or opposite (anti-phase stimulation) in the two cortical target areas. In-phase stimulation is thought to synchronize the endogenous oscillations and hereby to improve behavioral performance. Conversely, anti-phase stimulation is thought to desynchronize neural oscillations in the two areas, which is expected to decrease performance. Critically, in- and anti-phase ds-TACS should only differ with respect to temporal phase, while all other stimulation parameters such as focality and stimulation intensity should be matched to enable an unambiguous interpretation of the behavioral effects. Using electric field simulations based on a realistic head geometry, we tested how well this goal has been met in studies, which have employed ds-TACS up to now. Separating the induced electrical fields in their spatial and temporal components, we investigated how the chosen electrode montages determined the spatial field distribution and the generation of phase variations in the injected electric fields. Considering the basic physical mechanisms, we derived recommendations for an optimized stimulation montage. The latter allows for a principled design of in- and anti-phase ds-TACS conditions with matched spatial distributions of the electric field. This knowledge will help cognitive neuroscientists to design optimal ds-TACS configurations, which are suited to probe unambiguously the causal contribution of phase coupling to specific cognitive processes in the human brain.

Individualized brain mapping for navigated neuromodulation.

ABSTRACT: The brain is a complex organ that requires precise mapping to understand its structure and function. Brain atlases provide a powerful tool for studying brain circuits, discovering biological markers for early diagnosis, and developing personalized treatments for neuropsychiatric disorders. Neuromodulation techniques, such as transcranial magnetic stimulation and deep brain stimulation, have revolutionized clinical therapies for neuropsychiatric disorders. However, the lack of fine-scale brain atlases limits the precision and effectiveness of these techniques. Advances in neuroimaging and machine learning techniques have led to the emergence of stereotactic-assisted neurosurgery and navigation systems. Still, the individual variability among patients and the diversity of brain diseases make it necessary to develop personalized solutions. The article provides an overview of recent advances in individualized brain mapping and navigated neuromodulation and discusses the methodological profiles, advantages, disadvantages, and future trends of these techniques. The article concludes by posing open questions about the future development of individualized brain mapping and navigated neuromodulation.

Spatio-molecular profiles shape the human cerebellar hierarchy along the sensorimotor-association axis.

Cerebellar involvement in both motor and non-motor functions manifests in specific regions of the human cerebellum, revealing the functional heterogeneity within it. One compelling theory places the heterogeneity within the cerebellar functional hierarchy along the sensorimotor-association (SA) axis. Despite extensive neuroimaging studies, evidence for the cerebellar SA axis from different modalities and scales was lacking. Thus, we establish a significant link between the cerebellar SA axis and spatio-molecular profiles. Utilizing the gene set variation analysis, we find the intermediate biological principles the significant genes leveraged to scaffold the cerebellar SA axis. Interestingly, we find these spatio-molecular profiles notably associated with neuropsychiatric dysfunction and recent evolution. Furthermore, cerebello-cerebral interactions at genetic and functional connectivity levels mirror the cerebral cortex and cerebellum's SA axis. These findings can provide a deeper understanding of how the human cerebellar SA axis is shaped and its role in transitioning from sensorimotor to association functions.

Brain stimulation with 40 Hz heterochromatic flicker extended beyond red, green, and blue.

Alzheimer's disease (AD) is associated with electrophysiological changes in the brain. Pre-clinical and early clinical trials have shown promising results for the possible therapy of AD with 40 Hz neurostimulation. The most notable findings used stroboscopic flicker, but this technique poses an inherent barrier for human applications due to its visible flickering and resulting high level of perceived discomfort. Therefore, alternative options should be investigated for entraining 40 Hz brain activity with light sources that appear less flickering. Previously, chromatic flicker based on red, green, and blue (RGB) have been studied in the context of brain-computer interfaces, but this is an incomplete representation of the colours in the visual spectrum. This study introduces a new kind of heterochromatic flicker based on spectral combinations of blue, cyan, green, lime, amber, and red (BCGLAR). These combinations are investigated by the steady-state visually evoked potential (SSVEP) response from the flicker with an aim of optimising the choice of 40 Hz light stimulation with spectrally similar colour combinations in BCGLAR space. Thirty healthy young volunteers were stimulated with heterochromatic flicker in an electroencephalography experiment with randomised complete block design. Responses were quantified as the 40 Hz signal-to-noise ratio and analysed using mixed linear models. The size of the SSVEP response to heterochromatic flicker is dependent on colour combinations and influenced by both visual and non-visual effects. The amber-red flicker combination evoked the highest SSVEP, and combinations that included blue and/or red consistently evoked higher SSVEP than combinations only with mid-spectrum colours. Including a colour from either extreme of the visual spectrum (blue and/or red) in at least one of the dyadic phases appears to be more important than choosing pairs of colours that are far from each other on the visual spectrum. Spectrally adjacent colour pairs appear less flickering to the perceiver, and thus the results motivate investigations into the limits for how alike the two phases can be and still evoke a 40 Hz response. Specifically, combining a colour on either extreme of the visual spectrum with another proximal colour might provide the best trade-off between flickering sensation and SSVEP magnitude.

End-to-end volumetric segmentation of white matter hyperintensities using deep learning.

BACKGROUND AND OBJECTIVES: Reliable detection of white matter hyperintensities (WMH) is crucial for studying the impact of diffuse white-matter pathology on brain health and monitoring changes in WMH load over time. However, manual annotation of 3D high-dimensional neuroimages is laborious and can be prone to biases and errors in the annotation procedure. In this study, we evaluate the performance of deep learning (DL) segmentation tools and propose a novel volumetric segmentation model incorporating self-attention via a transformer-based architecture. Ultimately, we aim to evaluate diverse factors that influence WMH segmentation, aiming for a comprehensive analysis of the state-of-the-art algorithms in a broader context. METHODS: We trained state-of-the-art DL algorithms, and incorporated advanced attention mechanisms, using structural fluid-attenuated inversion recovery (FLAIR) image acquisitions. The anatomical MRI data utilized for model training was obtained from healthy individuals aged 62-70 years in the Live active Successful Aging (LISA) project. Given the potential sparsity of lesion volume among healthy aging individuals, we explored the impact of incorporating a weighted loss function and ensemble models. To assess the generalizability of the studied DL models, we applied the trained algorithm to an independent subset of data sourced from the MICCAI WMH challenge (MWSC). Notably, this subset had vastly different acquisition parameters compared to the LISA dataset used for training. RESULTS: Consistently, DL approaches exhibited commendable segmentation performance, achieving the level of inter-rater agreement comparable to expert performance, ensuring superior quality segmentation outcomes. On the out of sample dataset, the ensemble models exhibited the most outstanding performance. CONCLUSIONS: DL methods generally surpassed conventional approaches in our study. While all DL methods performed comparably, incorporating attention mechanisms could prove advantageous in future applications with a wider availability of training data. As expected, our experiments indicate that the use of ensemble-based models enables the superior generalization in out-of-distribution settings. We believe that introducing DL methods in the WHM annotation workflow in heathy aging cohorts is promising, not only for reducing the annotation time required, but also for eventually improving accuracy and robustness via incorporating the automatic segmentations in the evaluation procedure.

Safety, Feasibility, and Potential Clinical Efficacy of 40 Hz Invisible Spectral Flicker versus Placebo in Patients with Mild-to-Moderate Alzheimer's Disease: A Randomized, Placebo-Controlled, Double-Blinded, Pilot Study.

BACKGROUND: Recent studies suggested induction of 40 Hz neural activity as a potential treatment for Alzheimer's disease (AD). However, prolonged exposure to flickering light raises adherence and safety concerns, encouraging investigation of tolerable light stimulation protocols. OBJECTIVE: To investigate the safety, feasibility, and exploratory measures of efficacy. METHODS: This two-stage randomized placebo-controlled double-blinded clinical trial, recruited first cognitive healthy participants (n = 3/2 active/placebo), and subsequently patients with mild-to-moderate AD (n = 5/6, active/placebo). Participants were randomized 1:1 to receive either active intervention with 40 Hz Invisible Spectral Flicker (ISF) or placebo intervention with color and intensity matched non-flickering white light. RESULTS: Few and mild adverse events were observed. Adherence was above 86.1% of intended treatment days, with participants remaining in front of the device for >51.3 min (60 max) and directed gaze >34.9 min. Secondary outcomes of cognition indicate a tendency towards improvement in the active group compared to placebo (mean: -2.6/1.5, SD: 6.58/6.53, active/placebo) at week 6. Changes in hippocampal and ventricular volume also showed no tendency of improvement in the active group at week 6 compared to placebo. At week 12, a potential delayed effect of the intervention was seen on the volume of the hippocampus in the active group compared to placebo (mean: 0.34/-2.03, SD: 3.26/1.18, active/placebo), and the ventricular volume active group (mean: -0.36/2.50, SD: 1.89/2.05, active/placebo), compared to placebo. CONCLUSION: Treatment with 40 Hz ISF offers no significant safety or adherence concerns. Potential impact on secondary outcomes must be tested in larger scale clinical trials.

Study on the effect of 40 Hz non-invasive light therapy system. A protocol for a randomized, double-blinded, placebo-controlled clinical trial.

Introduction: With no cure or effective treatment, the prevalence of patients with Alzheimer's disease (AD) is expected to intensify, thereby increasing the social and financial burden on society. Light-based 40 Hz brain stimulation is considered a novel treatment strategy for patients with AD that may alleviate some of this burden. The clinical trial ALZLIGHT will utilize a novel Light Therapy System (LTS). The LTS uses Invisible Spectral Flicker for non-invasive induction of 40 Hz neural activity. This protocol describes a trial evaluating the efficacy and safety of a light-based 40 Hz brain stimulation in patients with mild-to-moderate AD. Methods: 62 patients with mild-to-moderate AD will participate in a randomized, double-blinded, placebo-controlled, parallel-group, and single-center trial. The participants will partake in an enrollment period of 1 month, an intervention period of 6 months, and a 1.5-month post-interventional follow-up period. Prior to the baseline measurement (week 0), the patients will be randomized to either active or placebo intervention from baseline (week 0) to post-intervention follow-up (week 26). Discussion: This protocol describes a randomized, double-blinded, placebo-controlled clinical trial that may increase the understanding of the effect of gamma oscillations in the human brain and how it could be utilized as a novel and important tool for the treatment of AD. The effect is measured through a large, multidisciplinary assessment battery.Clinical trial registration:www.ClinicalTrials.gov, (NCT05260177). Registered on March 2, 2022.

Executive Control and Associated Brain Activity in Children With Familial High-Risk of Schizophrenia or Bipolar Disorder: A Danish Register-based Study.

BACKGROUND AND HYPOTHESES: Impaired executive control is a potential prognostic and endophenotypic marker of schizophrenia (SZ) and bipolar disorder (BP). Assessing children with familial high-risk (FHR) of SZ or BP enables characterization of early risk markers and we hypothesize that they express impaired executive control as well as aberrant brain activation compared to population-based control (PBC) children. STUDY DESIGN: Using a flanker task, we examined executive control together with functional magnetic resonance imaging (fMRI) in 11- to 12-year-old children with FHR of SZ (FHR-SZ) or FHR of BP (FHR-BP) and PBC children as part of a register-based, prospective cohort-study; The Danish High Risk and Resilience study-VIA 11. STUDY RESULTS: We included 85 (44% female) FHR-SZ, 63 (52% female) FHR-BP and 98 (50% female) PBC in the analyses. Executive control effects, caused by the spatial visuomotor conflict, showed no differences between groups. Bayesian ANOVA of reaction time (RT) variability, quantified by the coefficient of variation (CVRT), revealed a group effect with similarly higher CVRT in FHR-BP and FHR-SZ compared to PBC (BF10 = 6.82). The fMRI analyses revealed no evidence for between-group differences in task-related brain activation. Post hoc analyses excluding children with psychiatric illness yielded same results. CONCLUSION: FHR-SZ and FHR-BP at age 11-12 show intact ability to resolve a spatial visuomotor conflict and neural efficacy. The increased variability in RT may reflect difficulties in maintaining sustained attention. Since variability in RT was independent of existing psychiatric illness, it may reflect a potential endophenotypic marker of risk.

Nonlinear denoising and analysis of neuroimages with kernel principal component analysis and pre-image estimation.

We investigate the use of kernel principal component analysis (PCA) and the inverse problem known as pre-image estimation in neuroimaging: i) We explore kernel PCA and pre-image estimation as a means for image denoising as part of the image preprocessing pipeline. Evaluation of the denoising procedure is performed within a data-driven split-half evaluation framework. ii) We introduce manifold navigation for exploration of a nonlinear data manifold, and illustrate how pre-image estimation can be used to generate brain maps in the continuum between experimentally defined brain states/classes. We base these illustrations on two fMRI BOLD data sets - one from a simple finger tapping experiment and the other from an experiment on object recognition in the ventral temporal lobe.

Monocular visual deprivation suppresses excitability in adult human visual cortex.

The adult visual cortex maintains a substantial potential for plasticity in response to a change in visual input. For instance, transcranial magnetic stimulation (TMS) studies have shown that binocular deprivation (BD) increases the cortical excitability for inducing phosphenes with TMS. Here, we employed TMS to trace plastic changes in adult visual cortex before, during, and after 48 h of monocular deprivation (MD) of the right dominant eye. In healthy adult volunteers, MD-induced changes in visual cortex excitability were probed with paired-pulse TMS applied to the left and right occipital cortex. Stimulus-response curves were constructed by recording the intensity of the reported phosphenes evoked in the contralateral visual field at range of TMS intensities. Phosphene measurements revealed that MD produced a rapid and robust decrease in cortical excitability relative to a control condition without MD. The cortical excitability returned to preinterventional baseline levels within 3 h after the end of MD. The results show that in contrast to the excitability increase in response to BD, MD acutely triggers a reversible decrease in visual cortical excitability. This shows that the pattern of visual deprivation has a substantial impact on experience-dependent plasticity of the human visual cortex.

Get to grips with motivation: Slipping and gripping movements are biased by approach-avoidance context.

People are better at approaching appetitive cues signaling reward and avoiding aversive cues signaling punishment than vice versa. This action bias has previously been shown in approach-avoidance tasks involving arm movements in response to appetitive or aversive cues. It is not known whether appetitive or aversive stimuli also bias more distal dexterous actions, such as gripping and slipping, in a similar manner. To test this hypothesis, we designed a novel task involving grip force control (gripping and slipping) to probe gripping-related approach and avoidance behavior. 32 male volunteers, aged 18-40 years, were instructed to either grip ("approach") or slip ("avoid") a grip-force device with their right thumb and index finger at the sight of positive or negative images. In one version of this pincer grip task, participants were responding to graspable objects and in another version of the task they were responding to happy or angry faces. Bayesian repeated measures Analysis of variance revealed extreme evidence for an interaction between response type and cue valence (Bayes factor = 296). Participants were faster to respond in affect-congruent conditions ("approach appetitive," "avoid aversive") than in affect-incongruent conditions ("approach aversive," "avoid appetitive"). This bias toward faster response times for affect-congruent conditions was present regardless of whether it was a graspable object or a face signaling valence. Since our results mirror the approach and avoidance effects previously observed for arm movements, we conclude that a tendency favoring affectively congruent cue-response mappings is an inherent feature of motor control and thus also includes precision grip.