Search

BackgroundAdverse childhood experiences (ACEs) increase the risk of mental health difficulties in general, but the link to panic disorder (PD) has received comparatively little attention. There are no data for the magnitudes between ACEs and PD. This systematic review and meta-analysis estimated the overall, as well as the subgroups, odds ratio of having PD in adults who report ACEs, compared to adults who do not.MethodsThe study was pre-registered on PROSPERO [CRD42018111506] and the database was searched in June 2021. In order to overcome the violation of independent assumptions due to multiple estimations from the same samples, we utilized a robust variance estimation model that supports meta-analysis for clustered estimations. Accordingly, an advanced method relaxing the distributional and asymptotic assumptions was used to assess publication bias and sensitivity.ResultsThe literature search and screening returned 34 final studies, comprising 192,182 participants. Ninety-six estimations of 20 types of ACEs were extracted. Pooled ORs are: overall 2.2, CI (1.82–2.58), sexual abuse 1.92, CI (1.37–2.46), physical abuse 1.71, CI (1.37–2.05), emotional abuse 1.61, CI (0.868–2.35), emotional neglect 1.53, CI (0.756–2.31), parental alcoholism 1.83, CI (1.24–2.43), and parental separation/loss 1.82, CI (1.14–2.50). No between-group difference was identified by either sociolegal classification (abuse, neglect, household dysfunction) or threat-deprivation dimensions (high on threat, high on deprivation and mixed).ConclusionsThere are links of mild to medium strength between overall ACEs and PD as well as individual ACEs. The homogeneous effect sizes across ACEs either suggest the effects of ACEs on PD are comparable, or raised the question whether the categorical or dimensional approaches to classifying ACEs are the definitive ways to conceptualize the impact of ACEs on later mental health.

Background/Aims Chronic pain is highly prevalent and a leading cause of disability worldwide with a crippling socioeconomic cost. Current non-pharmacological management of conditions including Fibromyalgia Syndrome (FMS) are labour intensive to implement and not widely available. There is an urgent need to develop accessible, innovative treatments for pain cohorts. Virtual reality (VR) is a modern technology that immerses users within a three-dimensional, interactive virtual environment delivered through a head-mounted display. VR is widely used for acute pain, following multiple randomised controlled trials showing efficacy. Despite growing numbers of feasibility studies and a handful of larger clinical trials, robust evidence within chronic pain cohorts including FMS is still limited. Through the VIPA Study, we investigated the impact of different VR characteristics on acceptability and pain using multiple feasibility studies in patients with FMS. Methods Patients with FMS were recruited through outpatient clinics at the Norfolk and Norwich University Hospital. We investigated four VR systems representing the spectrum of commercially available technologies. Participants used each system in a random order for five minutes. The interactive VR program experienced with each headset was co-developed alongside industry partners specifically for patients with chronic pain. Baseline questionnaires included the McGill pain questionnaire short form (MPQ-SF; total score: 0-45), pain visual analogue scale (VAS; 0-10) and Revised Fibromyalgia Impact Questionnaire (FIQR; total score: 0-100). MPQ-SF and VAS data were also collected approximately 15 minutes after use of the fourth headset (post-intervention). Questionnaires collected acceptability data using 7-point Likert scale rating questions (1=strongly disagree to 7=strongly agree). The VR sickness questionnaire (VRSQ) gained side-effect data (total severity score: 0-100). Results 26 participants with FMS were included (mean (SD) age 48 ±14yrs, 88% female). Disease severity ranged from moderate to extreme (mean FIQR 65 ±16). Following use of all headsets, a 40% reduction in mean MPQ-SF total scores from baseline were reported (baseline 24 ±9, post-intervention 15 ±9, p = Conclusion Patients with FMS can experience large reductions in pain following VR, find the technology acceptable with limited side effects, and are open to home use for pain management. VR has enormous potential as an accessible, home-based treatment for chronic pain. VIPA provides strong justification for future RCTs investigating efficacy and dose-response. Disclosure J. Tsigarides: Grants/research support; J.T. has received a small amount of funding from Orbital Global Ltd to support research equipment purchase for The VIPA Study. V. Grove: None. N. Shenker: None. J. Dainty: None. J. Chipping: None. S. Miles: None. S. Sami: None. A. MacGregor: None.

Background many medications possess anticholinergic activity. Their use is associated with a number of serious adverse effects including cognitive effects. The cumulative anticholinergic effect of medications as assessed by tools such as the anticholinergic burden scale (AchB) can identify people particularly at risk of anticholinergic side-effects. Currently, >20 tools are available for clinicians to use, but there is no consensus on the most appropriate tool. Methods a newly created online tool—International Anticholinergic Cognitive Burden Tool (IACT)—based on natural language processing and chemical structure analysis, was developed and made available for clinicians to test its functions. We carried out a survey (between 8th of February and 31st of March 2021) to assess the overall need for an assessment tool as well as the usability of the IACT. Results a total of 110 responses were received from different countries and practitioners’ groups. The majority of the participants (86.11%) stated they would use a tool for AchB assessment if available and when they were asked to rate the IACT against other tools, amongst 34 responders, 20.59% rated it better and 8.82% rated it significantly better, 44.12% rated it neither better, nor worse, 14.71% rated it worse and 11.76% somewhat worse. Conclusion there is a need for an anticholinergic burden calculator to assess the anticholinergicity of medications. Tools such as the IACT potentially could meet this demand due to its ability to assign scores to current and new medications appearing on the market based both on their chemical structure and reported adverse pharmacological effects.

Background: Loss of smell or olfactory dysfunction (OD)s a common yet under- addressed problem with an estimated 5% of the general population having no functioning sense of smell. OD secondary to viral infections (eg: Covid-19) is one of the leading causes. Isolation, depression, anxiety, risk of danger from hazards such as toxic gas and spoiled food, weight loss/ gain secondary to loss of appetite are all prevalent negative impacts associated with OD. Various treatment options have been tried to treat smell loss after viral infection. Smell training has been tried with good results in the immediate post-viral phase. Evidence behind treatment with steroids has not shown to have proven effectiveness. With this, a key problem for patients and their clinicians is the lack of proven an effective therapeutic treatment option. Based on previous studies, there is some evidence supporting the regenerative potential of retinoic acid, the metabolically active form of Vitamin A in regeneration of olfactory receptor neurons. It is based on this concept that we have chosen Vitamin A as our study comparator in this two-arm randomised trial to determine proof of conceptMethods/Design: The study will compare 10,000 IU once daily Vitamin A self-administered intranasal drops versus peanut oil drops (placebo) delivered over 12 weeks in patients with post viral olfactory loss. Eligible patients will be recruited from the Smell & Taste Clinic and randomised to receive vitamin A drops or placebo in a 2:1 ratio. They will then be invited to attend the Brain Imaging Centre at the University of East Anglia on two occasions, 3 months apart, Serial MRI scanning will enable volumetric measurement of the OB and ROS; fMRI will then be conducted using an olfactometer to deliver pulsed odours – phenethylalcohol (rose-like) and hydrogen sulphide (rotten eggs). Participants will also undergo a standard smell test at both visits as well as complete a quality-of-life questionnaire. Change in OB volume on MRI will be the primary outcome measure.Discussion: We expect the outputs of this study to enable a subsequent randomised controlled trial of Vitamin A versus placebo. With PPI input we will make the outputs publicly available using journals, conferences and social media via Fifth Sense. We have already prepared a draft RCT proposal in partnership with the Norwich Clinical Trials Unit and would plan to develop this further considering the findings.Trial registration: ISRCTN registry 39523. Date of registration in primary registry: 23rd February 2021

Background: Youth receiving medical care for injury are at risk of PTSD. Therefore, accurate prediction of chronic PTSD at an early stage is needed. Machine learning (ML) offers a promising approach to precise prediction and interpretation. Aims: The study proposes a clinically useful predictive model for PTSD 6–12 months after injury, analyzing the relationship among predictors, and between predictors and outcomes. Methods: A ML approach was utilized to train models based on 1167 children and adolescents of nine perspective studies. Demographics, trauma characteristics and acute traumatic stress (ASD) symptoms were used as initial predictors. PTSD diagnosis at six months was derived using DSM-IV PTSD diagnostic criteria. Models were validated on external datasets. Shapley value and partial dependency plot (PDP) were applied to interpret the final model. Results: A random forest model with 13 predictors (age, ethnicity, trauma type, intrusive memories, nightmares, reliving, distress, dissociation, cognitive avoidance, sleep, irritability, hypervigilance and startle) yielded F-scores of.973,0.902 and.961 with training and two external datasets. Shapley values were calculated for individual and grouped predictors. A cumulative effect for intrusion symptoms was observed. PDP showed a non-linear relationship between age and PTSD, and between ASD symptom severity and PTSD. A 43 % difference in the risk between non-minority and minority ethnic groups was detected. Conclusions: A ML model demonstrated excellent classification performance and good potential for clinical utility, using a few easily obtainable variables. Model interpretation gave a comprehensive quantitative analysis on the operations among predictors, in particular ASD symptoms.

Background: Anticholinergic medications have been associated with accelerated memory and language deterioration with increased risk of Mild Cognitive Impairment (MCI), particularly in older people. Accurate quantification of total anticholinergic burden (ACB) is a critical first step to prevent cognitive decline in the geriatric population. Whilst there are at least 16 different anticholinergic burden scales available, inconsistency exists between these scales due to the methods employed in their development and the different interests and expertise of developers with regard to outcomes. We aimed to develop a universal ACB scoring system using machine learning techniques for a fully automated model accessible through a web-based portal. Methods: A novel machine learning system was developed using textual samples from published sources describing medications scored on previously established anticholinergic burden scales which were well validated against several health outcomes. Our semi-supervised approach ensures that maximal information from these scales is utilized. The algorithm provides the ability to rapidly classify existing medications and maintain surveillance of new emerging medications. In order to validate the approach, a chemical structure based analysis was performed to explore homogeneity between innate chemical structure and the new ACB scoring system. Findings: Usage of the newly created International Anticholinergic Burden Scale (IACB) significantly improves the ACB scale accuracy compared to previous scales (AUC $0\cdot91$). An analysis of chemical structure found a stronger correlation between the IACB and the underlying chemical structure of medications when compared to 6 currently used scoring systems. To increase accessibility to this newly created scale, a web portal was developed to provide clinicians and patients with accurate information on their current total anticholinergic burden. Interpretation: Usage of Machine Learning can potentially build upon previous attempts at anticholinergic burden quantification, overcoming language barriers and aligning closely with innate medication structure allowing for a more accurate, up-to-date scoring system. Funding: UEA impact fund 192008. Conflicts of Interest: These author declare no conflict of interest.

Highlights • We compared cerebellar grey matter loss in Alzheimer’s disease and normal aging. • Posterior cerebellum was affected by both healthy aging and Alzheimer’s disease. • Healthy aging showed bilateral grey matter loss, while AD was right lateralized. • Affected regions participate in default, frontoparietal and attention networks. • AD and aging show partly divergent and convergent cerebellar functional profiles., Recent findings challenge the prior notion that the cerebellum remains unaffected by Alzheimer’s disease (AD). Yet, it is unclear whether AD exacerbates age-related cerebellar grey matter decline or engages distinct structural and functional territories. We performed a meta-analysis of cerebellar grey matter loss in normal ageing and AD. We mapped voxels with structural decline onto established brain networks, functional parcellations, and along gradients that govern the functional organisation of the cerebellum. Importantly, these gradients track continuous changes in cerebellar specialisation providing a more nuanced measure of the functional profile of regions vulnerable to ageing and AD. Gradient 1 progresses from motor to cognitive territories; Gradient 2 isolates attentional processing; Gradient 3 captures lateralisation differences in cognitive functions. We identified bilateral and right-lateralised posterior cerebellar atrophy in ageing and AD, respectively. Age- and AD-related structural decline only showed partial spatial overlap in right lobule VI/Crus I. Despite the seemingly distinct patterns of AD- and age-related atrophy, the functional profiles of these regions were similar. Both participate in the same macroscale networks (default mode, frontoparietal, attention), support executive functions and language processing, and did not exhibit a difference in relative positions along Gradients 1 or 2. However, Gradient 3 values were significantly different in ageing vs. AD, suggesting that the roles of left and right atrophied cerebellar regions exhibit subtle functional differences despite their membership in similar macroscale networks. These findings provide an unprecedented characterisation of structural and functional differences and similarities in cerebellar grey matter loss between normal ageing and AD.

SEE SCHMAHMANN DOI101093/BRAIN/AWW064 FOR A SCIENTIFIC COMMENTARY ON THIS ARTICLE: Neurodegenerative diseases are associated with distinct and distributed patterns of atrophy in the cerebral cortex. Emerging evidence suggests that these atrophy patterns resemble intrinsic connectivity networks in the healthy brain, supporting the network-based degeneration framework where neuropathology spreads across connectivity networks. An intriguing yet untested possibility is that the cerebellar circuits, which share extensive connections with the cerebral cortex, could be selectively targeted by major neurodegenerative diseases. Here we examined the structural atrophy in the cerebellum across common types of neurodegenerative diseases, and characterized the functional connectivity patterns of these cerebellar atrophy regions. Our results showed that Alzheimer's disease and frontotemporal dementia are associated with distinct and circumscribed atrophy in the cerebellum. These cerebellar atrophied regions share robust and selective intrinsic connectivity with the atrophied regions in the cerebral cortex. These findings for the first time demonstrated the selective vulnerability of the cerebellum to common neurodegenerative disease, extending the network-based degeneration framework to the cerebellum. Our work also has direct implications on the cerebellar contribution to the cognitive and affective processes that are compromised in neurodegeneration as well as the practice of using the cerebellum as reference region for ligand neuroimaging studies.

Human spatial ability is modulated by a number of factors, including age [1, 2, 3] and gender [4, 5]. Although a few studies showed that culture influences cognitive strategies [6, 7, 8, 9, 10, 11, 12, 13], the interaction between these factors has never been globally assessed as this requires testing millions of people of all ages across many different countries in the world. Since countries vary in their geographical and cultural properties, we predicted that these variations give rise to an organized spatial distribution of cognition at a planetary-wide scale. To test this hypothesis, we developed a mobile-app-based cognitive task, measuring non-verbal spatial navigation ability in more than 2.5 million people and sampling populations in every nation state. We focused on spatial navigation due to its universal requirement across cultures. Using a clustering approach, we find that navigation ability is clustered into five distinct, yet geographically related, groups of countries. Specifically, the economic wealth of a nation was predictive of the average navigation ability of its inhabitants, and gender inequality was predictive of the size of performance difference between males and females. Thus, cognitive abilities, at least for spatial navigation, are clustered according to economic wealth and gender inequalities globally, which has significant implications for cross-cultural studies and multi-center clinical trials using cognitive testing.

Introduction The cerebellum has strong cortical and subcortical connectivity, but is rarely taken into account for clinical diagnosis in many neurodegenerative conditions, particularly in the absence of clinical ataxia. The current meta-analysis aims to assess patterns of cerebellar grey matter atrophy in seven neurodegenerative conditions (Alzheimer’s disease (AD), Parkinson’s disease (PD) and Huntington’s disease (HD), frontotemporal dementia (FTD), amyotrophic lateral sclerosis (ALS), multiple system atrophy (MSA), progressive supranuclear palsy (MSP)). Methods We carried out a systematic search in PubMed (any date: 14 July 2016) and a hand search of references from pertinent articles according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The authors were contacted to provide missing coordinate data. Peer-reviewed studies with direct comparison of patient and control groups, and availability of coordinate data of grey matter cerebellar atrophy in patients were included. These coordinates were used in an anatomical likelihood estimation meta-analysis. Results Across 54 studies, clusters of cerebellar atrophy were found for AD, ALS, FTD, MSA, and PSP. Atrophy patterns were largely disease-specific, with overlap in certain areas of the cerebellar hemisphere, which showed marked atrophy in AD, ALS, FTD and PSP (Crus I/II), and MSA and PSP (lobules I–IV), respectively. Atrophy colocated with cerebellar areas implicated for motor (PSP, MSA) or cognitive symptoms (FTD, ALS, PSP) in the diseases. Discussion Our findings suggest that cerebellar changes are largely disease-specific and correspond to cortical or subcortical changes in neurodegenerative conditions. High clinical variability in PD and HD samples may explain the absence of findings for consistent grey matter loss across studies. Our results have clinical implications for diagnosis and cerebellar neuroimaging referencing approaches.

The ability to assess the distribution and extent of tau pathology in Alzheimer's disease and progressive supranuclear palsy in vivo would help to develop biomarkers for these tauopathies and clinical trials of disease-modifying therapies. New radioligands for positron emission tomography have generated considerable interest, and controversy, in their potential as tau biomarkers. We assessed the radiotracer 18F-AV-1451 with positron emission tomography imaging to compare the distribution and intensity of tau pathology in 15 patients with Alzheimer's pathology (including amyloid-positive mild cognitive impairment), 19 patients with progressive supranuclear palsy, and 13 age- and sex-matched controls. Regional analysis of variance and a support vector machine were used to compare and discriminate the clinical groups, respectively. We also examined the 18F-AV-1451 autoradiographic binding in post mortem tissue from patients with Alzheimer's disease, progressive supranuclear palsy, and a control case to assess the 18F-AV-1451 binding specificity to Alzheimer's and non-Alzheimer's tau pathology. There was increased 18F-AV-1451 binding in multiple regions in living patients with Alzheimer's disease and progressive supranuclear palsy relative to controls [main effect of group, F(2,41) = 17.5, P < 0.0001; region of interest × group interaction, F(2,68) = 7.5, P < 0.00001]. More specifically, 18F-AV-1451 binding was significantly increased in patients with Alzheimer's disease, relative to patients with progressive supranuclear palsy and with control subjects, in the hippocampus and in occipital, parietal, temporal, and frontal cortices (t's > 2.2, P's < 0.04). Conversely, in patients with progressive supranuclear palsy, relative to patients with Alzheimer's disease, 18F-AV-1451 binding was elevated in the midbrain (t = 2.1, P < 0.04); while patients with progressive supranuclear palsy showed, relative to controls, increased 18F-AV-1451 uptake in the putamen, pallidum, thalamus, midbrain, and in the dentate nucleus of the cerebellum (t's > 2.7, P's < 0.02). The support vector machine assigned patients' diagnoses with 94% accuracy. The post mortem autoradiographic data showed that 18F-AV-1451 strongly bound to Alzheimer-related tau pathology, but less specifically in progressive supranuclear palsy. 18F-AV-1451 binding to the basal ganglia was strong in all groups in vivo. Postmortem histochemical staining showed absence of neuromelanin-containing cells in the basal ganglia, indicating that off-target binding to neuromelanin is an insufficient explanation of 18F-AV-1451 positron emission tomography data in vivo, at least in the basal ganglia. Overall, we confirm the potential of 18F-AV-1451 as a heuristic biomarker, but caution is indicated in the neuropathological interpretation of its binding. Off-target binding may contribute to disease profiles of 18F-AV-1451 positron emission tomography, especially in primary tauopathies such as progressive supranuclear palsy. We suggest that 18F-AV-1451 positron emission tomography is a useful biomarker to assess tau pathology in Alzheimer's disease and to distinguish it from other tauopathies with distinct clinical and pathological characteristics such as progressive supranuclear palsy.

Motor adaptation is impaired by the performance of a secondary task which divides cognitive resources. Additionally, we previously reported slowed adaptation when participants were required to switch from one visual displacement adaptation task to another. Here, we examined whether a dividing secondary task had a similar effect on adaptation as switching between opposing visual displacements. The resource-dividing task involved simultaneously adapting to a step-visual displacement whilst vocally shadowing an auditory stimulus. The switching task required participants to adapt to opposing visual displacements in an alternating manner with the left and right hands. We found that both manipulations had a detrimental effect on adaptation rate. We then integrated these tasks and found the combination caused a greater decrease in adaptation rate than either manipulation in isolation. A second set of experiments showed that adaptation to a gradually imposed visual displacement was influenced in a similar manner to step adaptation. In summary, step adaptation slows the learning rate of gradual adaptation to a large degree, whereas gradual adaptation only slightly slows the learning rate of step adaptation. Therefore, although gradual adaptation involves minimal awareness it can still be disrupted with a cognitively demanding secondary task. We propose that awareness and cognitive resource can be regarded as qualitatively different, but that awareness may be a marker of the amount of resource required. For example, large errors are both noticed and require substantial cognitive resource. However, a lack of awareness does not mean an adaptation task will be resistant to interference from a resource-consuming secondary task.

Cognitive impairment is common in Parkinson's disease (PD), but often not improved by dopaminergic treatment. New treatment strategies targeting other neurotransmitter deficits are therefore of growing interest. Imaging the brain at rest (‘task-free') provides the opportunity to examine the impact of a candidate drug on many of the brain networks that underpin cognition, while minimizing task-related performance confounds. We test this approach using atomoxetine, a selective noradrenaline reuptake inhibitor that modulates the prefrontal cortical activity and can facilitate some executive functions and response inhibition. Thirty-three patients with idiopathic PD underwent task-free fMRI. Patients were scanned twice in a double-blind, placebo-controlled crossover design, following either placebo or 40-mg oral atomoxetine. Seventy-six controls were scanned once without medication to provide normative data. Seed-based correlation analyses were used to measure changes in functional connectivity, with the right inferior frontal gyrus (IFG) a critical region for executive function. Patients on placebo had reduced connectivity relative to controls from right IFG to dorsal anterior cingulate cortex and to left IFG and dorsolateral prefrontal cortex. Atomoxetine increased connectivity from the right IFG to the dorsal anterior cingulate. In addition, the atomoxetine-induced change in connectivity from right IFG to dorsolateral prefrontal cortex was proportional to the change in verbal fluency, a simple index of executive function. The results support the hypothesis that atomoxetine may restore prefrontal networks related to executive functions. We suggest that task-free imaging can support translational pharmacological studies of new drug therapies and provide evidence for engagement of the relevant neurocognitive systems.

The present paper asks whether the motor cortex contributes to prediction-based guidance of target selection. This question was inspired by recent evidence that suggests (i) recurrent connections from the motor system into the attentional system may extract movement-relevant perceptual information and (ii) that the motor cortex cannot only generate predictions of the sensory consequences of movements but may also operate as predictor of perceptual events in general. To test this idea we employed a choice reaching task requiring participants to rapidly reach and touch a predictable or unpredictable colour target. Motor cortex activity was modulated via transcranial direct current stimulation (tDCS). In Experiment 1 target colour repetitions were predictable. Under such conditions anodal tDCS facilitated selection versus sham and cathodal tDCS. This improvement was apparent for trajectory curvature but not movement initiation. Conversely, where no predictability of colour was embedded reach performance was unaffected by tDCS. Finally, the results of a key-press experiment suggested that motor cortex involvement is restricted to tasks where the predictable target colour is movement-relevant. The outcomes are interpreted as evidence that the motor system contributes to the top-down guidance of selective attention to movement targets.

Previous studies have reported functionally localized changes in resting-state brain activity following a short period of motor learning, but their relationship with memory consolidation and their dependence on the form of learning is unclear. We investigate these questions with implicit or explicit variants of the serial reaction time task (SRTT). fMRI resting-state functional connectivity was measured in human subjects before the tasks, and 0.1, 0.5, and 6 h after learning. There was significant improvement in procedural skill in both groups, with the group learning under explicit conditions showing stronger initial acquisition, and greater improvement at the 6 h retest. Immediately following acquisition, this group showed enhanced functional connectivity in networks including frontal and cerebellar areas and in the visual cortex. Thirty minutes later, enhanced connectivity was observed between cerebellar nuclei, thalamus, and basal ganglia, whereas at 6 h there was enhanced connectivity in a sensory-motor cortical network. In contrast, immediately after acquisition under implicit conditions, there was increased connectivity in a network including precentral and sensory-motor areas, whereas after 30 min a similar cerebello-thalamo-basal ganglionic network was seen as in explicit learning. Finally, 6 h after implicit learning, we found increased connectivity in medial temporal cortex, but reduction in precentral and sensory-motor areas. Our findings are consistent with predictions that two variants of the SRTT task engage dissociable functional networks, although there are also networks in common. We also show a converging and diverging pattern of flux between prefrontal, sensory-motor, and parietal areas, and subcortical circuits across a 6 h consolidation period.

Correction to: Neuropsychopharmacology advance online publication, 2 March 2016; doi:10.1038/npp.2016.18 Following the publication of this paper, the authors have changed the Funding and Disclosure section to read as follows: This work was funded by the Wellcome trust (103838), Parkinson’s UK, National Institute for Health Research’s Cambridge Biomedical Research Centre and the Medical Research Council (MC_US_A060_0016 and RG62761), and the James F McDonnell Foundation (21st century science initiative on Understanding Human Cognition).

We investigated which evoked response component occurring in the first 800 ms after stimulus presentation was most suitable to be used in a classical P300-based brain-computer interface speller protocol. Data was acquired from 275 Magnetoencephalographic sensors in two subjects and from 61 Electroencephalographic sensors in four. To better characterize the evoked physiological responses and minimize the effect of response overlap, a 1000 ms Inter Stimulus Interval was preferred to the short (400 ms) trial length traditionally used in this class of BCIs. To investigate which scalp regions conveyed information suitable for BCI, a stepwise linear discriminant analysis classifier was used. The method iteratively analyzed each individual sensor and determined its performance indicators. These were then plotted on a 2-D topographic head map. Preliminary results for both EEG and MEG data suggest that components other than the P300 maximally represented in the occipital region, could be successfully used to improve classification accuracy and finally drive this class of BCIs.

Combining information present in multiple datasets is one of the key challenges to fully benefit from the increasing availability of data in a variety of fields. Coupled tensor factorization aims to address this challenge by performing a simultaneous decomposition of different tensors. However, tensor factorization tends to suffer from a lack of robustness as the number of components affects the results to a large extent. In this work, a general framework for coupled tensor factorization is built to extract reliable components. Results from both individual and coupled decompositions are compared and divergence measures are used to adapt the number of components. It results in a joint decomposition method with (i) a variable number of components, (ii) shared and unshared components among tensors and (iii) robust components. Results on simulated data show a better modelling of the sources composing the datasets and an improved evaluation of the number of shared sources.