Constrained expectation maximisation algorithm for estimating ARMA models in state space representation

This paper discusses the fitting of linear state space models to given multivariate time series in the presence of constraints imposed on the four main parameter matrices of these models. Constraints arise partly from the assumption that the models have a block-diagonal structure, with each block corresponding to an ARMA process, that allows the reconstruction of independent source components from linear mixtures, and partly from the need to keep models identifiable. The first stage of parameter fitting is performed by the expectation maximisation (EM) algorithm. Due to the identifiability constraint, a subset of the diagonal elements of the dynamical noise covariance matrix needs to be constrained to fixed values (usually unity). For this kind of constraints, so far, no closed-form update rules were available. We present new update rules for this situation, both for updating the dynamical noise covariance matrix directly and for updating a matrix square-root of this matrix. The practical applicability of the proposed algorithm is demonstrated by a low-dimensional simulation example. The behaviour of the EM algorithm, as observed in this example, illustrates the well-known fact that in practical applications, the EM algorithm should be combined with a different algorithm for numerical optimisation, such as a quasi-Newton algorithm

Dynamic imaging of coherent sources reveals different network connectivity underlying the generation and perpetuation of epileptic seizures

The concept of focal epilepsies includes a seizure origin in brain regions with hyper synchronous activity (epileptogenic zone and seizure onset zone) and a complex epileptic network of different brain areas involved in the generation, propagation, and modulation of seizures. The purpose of this work was to study functional and effective connectivity between regions involved in networks of epileptic seizures. The beginning and middle part of focal seizures from ictal surface EEG data were analyzed using dynamic imaging of coherent sources (DICS), an inverse solution in the frequency domain which describes neuronal networks and coherences of oscillatory brain activities. The information flow (effective connectivity) between coherent sources was investigated using the renormalized partial directed coherence (RPDC) method. In 8/11 patients, the first and second source of epileptic activity as found by DICS were concordant with the operative resection site; these patients became seizure free after epilepsy surgery. In the remaining 3 patients, the results of DICS / RPDC calculations and the resection site were discordant; these patients had a poorer post-operative outcome. The first sources as found by DICS were located predominantly in cortical structures; subsequent sources included some subcortical structures: thalamus, Nucl. Subthalamicus and cerebellum. DICS seems to be a powerful tool to define the seizure onset zone and the epileptic networks involved. Seizure generation seems to be related to the propagation of epileptic activity from the primary source in the seizure onset zone, and maintenance of seizures is attributed to the perpetuation of epileptic activity between nodes in the epileptic network. Despite of these promising results, this proof of principle study needs further confirmation prior to the use of the described methods in the clinical praxis

The voxel-wise functional connectome can be efficiently derived from co-activations in a sparse spatio-temporal point-process

Large efforts are currently under way to systematically map functional connectivity between all pairs of millimeter-scale brain regions based on large neuroimaging databases. The exploratory unraveling of this "functional connectome" based on functional Magnetic Resonance Imaging (fMRI) can benefit from a better understanding of the contributors to resting state functional connectivity. In this work, we introduce a sparse representation of fMRI data in the form of a discrete point-process encoding high-amplitude events in the blood oxygenation level-dependent (BOLD) signal and we show it contains sufficient information for the estimation of functional connectivity between all pairs of voxels. We validate this method by replicating results obtained with standard whole-brain voxel-wise linear correlation matrices in two datasets. In the first one (n = 71), we study the changes in node strength (a measure of network centrality) during deep sleep. The second is a large database (n = 1147) of subjects in which we look at the age-related reorganization of the voxel-wise network of functional connections. In both cases it is shown that the proposed method compares well with standard techniques, despite requiring only data on the order of 1% of the original BOLD signal time series. Furthermore, we establish that the point-process approach does not reduce (and in one case increases) classification accuracy compared to standard linear correlations. Our results show how large fMRI datasets can be drastically simplified to include only the timings of large-amplitude events, while still allowing the recovery of all pair-wise interactions between voxels. The practical importance of this dimensionality reduction is manifest in the increasing number of collaborative efforts aiming to study large cohorts of healthy subjects as well as patients suffering from brain disease. Our method also suggests that the electrophysiological signals underlying the dynamics of fMRI time series consist of all-or-none temporally localized events, analogous to the avalanches of neural activity observed in recordings of local field potentials (LFP), an observation of potentially high neurobiological relevance.Fil: Tagliazucchi, Enzo. Christian Albrechts Universitat Zu Kiel.; Alemania. University Frankfurt am Main; AlemaniaFil: Siniatchkin, Michael. Christian Albrechts Universitat Zu Kiel.; AlemaniaFil: Laufs, Helmut. University Frankfurt am Main; Alemania. University Hospital Schleswig Holstein; AlemaniaFil: Chialvo, Dante Renato. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de San Martin. Escuela de Ciencia y Tecnologia. Centro de Estudios Multidisciplinarios En Sistemas Complejos y Ciencias del Cerebro.; Argentin

Representation and propagation of epileptic activity in absences and generalized photoparoxysmal responses

Although functional imaging studies described networks associated with generalized epileptic activity, propagation patterns within these networks are not clear. In this study, electroencephalogram (EEG)-based coherent source imaging dynamic imaging of coherent sources (DICS) was applied to different types of generalized epileptiform discharges, namely absence seizures (10 patients) and photoparoxysmal responses (PPR) (eight patients) to describe the representation and propagation of these discharges in the brain. The results of electrical source imaging were compared to EEG-functional magnetic resonance imaging (fMRI) which had been obtained from the same data sets of simultaneous EEG and fMRI recordings. Similar networks were described by DICS and fMRI: (1) absence seizures were associated with thalamic involvement in all patients. Concordant results were also found for brain areas of the default mode network and the occipital cortex. (2) Both DICS and fMRI identified the occipital, parietal, and the frontal cortex in a network associated with PPR. (3) However, only when PPR preceded a generalized tonic-clonic seizure, the thalamus was involved in the generation of PPR as shown by both imaging techniques. Partial directed coherence suggested that during absences, the thalamus acts as a pacemaker while PPR could be explained by a cortical propagation from the occipital cortex via the parietal cortex to the frontal cortex. In conclusion, the electrical source imaging is not only able to describe similar neuronal networks as revealed by fMRI, including deep sources of neuronal activity such as the thalamus, but also demonstrates interactions interactions within these networks and sheds light on pathogenetic mechanisms of absence seizures and PPR. Hum Brain Mapp, 2013

Identifying the origin of the source in multi-focal epilepsy patients [Poster]

The aim of this study, was firstly to identify the two neuronal sources in the brain which show the highest dipole strength; caused by the multi-focal epileptic activity using the Minimum-norm (MN) inverse solution technique on a realistic head model. The second aim was to study the dynamics of these two source signals so as to identify which part of the brain is activated first and which part follows, using time-frequency analysis. 1. The source analysis revealed the first two neuronal networks, which showed the highest dipolar strength, in each patient. 2. The power dynamics over the whole time duration and frequency gives valuable information in identifying the region of the brain which is activated first for each patient before the surgical procedure

Unmet Needs in Children With Attention Deficit Hyperactivity Disorder—Can Transcranial Direct Current Stimulation Fill the Gap? Promises and Ethical Challenges

Attention deficit hyperactivity disorder (ADHD) is a disorder most frequently diagnosed in children and adolescents. Although ADHD can be effectively treated with psychostimulants, a significant proportion of patients discontinue treatment because of adverse events or insufficient improvement of symptoms. In addition, cognitive abilities that are frequently impaired in ADHD are not directly targeted by medication. Therefore, additional treatment options, especially to improve cognitive abilities, are needed. Because of its relatively easy application, well-established safety, and low cost, transcranial direct current stimulation (tDCS) is a promising additional treatment option. Further research is needed to establish efficacy and to integrate this treatment into the clinical routine. In particular, limited evidence regarding the use of tDCS in children, lack of clear translational guidelines, and general challenges in conducting research with vulnerable populations pose a number of practical and ethical challenges to tDCS intervention studies. In this paper, we identify and discuss ethical issues related to research on tDCS and its potential therapeutic use for ADHD in children and adolescents. Relevant ethical issues in the tDCS research for pediatric ADHD center on safety, risk/benefit ratio, information and consent, labeling problems, and nonmedical use. Following an analysis of these issues, we developed a list of recommendations that can guide clinicians and researchers in conducting ethically sound research on tDCS in pediatric ADHD

Multimodal alterations of directed connectivity profiles in patients with attention-deficit/hyperactivity disorders

Functional and effective connectivity measures for tracking brain region interactions that have been investigated using both electroencephalography (EEG) and magnetoencephalography (MEG) bringing up new insights into clinical research. However, the differences between these connectivity methods, especially at the source level, have not yet been systematically studied. The dynamic characterization of coherent sources and temporal partial directed coherence, as measures of functional and effective connectivity, were applied to multimodal resting EEG and MEG data obtained from 11 young patients (mean age 13.2 ± 1.5 years) with attention-deficit/hyperactivity disorder (ADHD) and age-matched healthy subjects. Additionally, machine-learning algorithms were applied to the extracted connectivity features to identify biomarkers differentiating the two groups. An altered thalamo-cortical connectivity profile was attested in patients with ADHD who showed solely information outflow from cortical regions in comparison to healthy controls who exhibited bidirectional interregional connectivity in alpha, beta, and gamma frequency bands. We achieved an accuracy of 98% by combining features from all five studied frequency bands. Our findings suggest that both types of connectivity as extracted from EEG or MEG are sensitive methods to investigate neuronal network features in neuropsychiatric disorders. The connectivity features investigated here can be further tested as biomarkers of ADHD

Mobile applications in adolescent psychotherapy during the COVID-19 pandemic: a systematic review

BackgroundTo bridge the gap in adolescent psychotherapy created by the increasing need for mental health interventions and the limited possibilities of in-person treatment during the pandemic, many health care providers opted to offer online mental health care programs. As a result, the number of mental health apps available in app stores experienced a sharp increase during the COVID-19 pandemic.ObjectiveThe aim of the current review is to provide an overview of feasibility and effectiveness studies testing mobile applications in adolescent psychotherapy during the peak phase of the COVID-19 pandemic.MethodsWe conducted a literature search in Pubmed, PsychInfo, Google Scholar, OpenSIGLE and OpenGREY for papers published from June 2020 to June 2023. Studies were included if they evaluated app-based interventions intended for psychotherapeutic treatment and targeted adolescents between 12 and 27 years of age with symptoms of psychological disorders. The quality of each study was assessed using the Systematic Assessment of Quality in Observational Research (SAQOR). Effectiveness outcomes were analyzed by vote counting and calculating a binomial probability test.ResultsThe search yielded 31 relevant studies that examined 27 different apps with a total of 1,578 adolescent participants. Nine articles were primary effectiveness studies and 22 focused on feasibility measures as primary outcome. There was evidence that mental health apps influenced adolescents' psychotherapy, with 83% of the studies with effectiveness outcomes favoring the intervention (p = 0.002). Sixty-one percent of the included studies were rated at low or very low quality.ConclusionsThe pandemic has given apps a firm and important role in healthcare that will probably continue to expand in the future. To ensure that mental health apps are truly effective and beneficial for adolescents' psychotherapy, we need a standardized measurement of quality features of mental health apps and higher quality app evaluation studies.Systematic review registrationhttps://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=406455, PROSPERO International Prospective Register of Systematic Reviews [CRD42023406455]

V5. Dynamic imaging of coherent sources in continues spikes and waves during slow sleep [Abstract]

The network of sources involved in the frequency oscillations of continuous spikes and waves during slow wave sleep and their causal architecture is still lacking in the current literature. In a couple of studies the network and causal connectivity was studied using fMRI by concentrating the analysis on the spikes and not on the background oscillations. In a number of studies the connectivity and the network of sources were studied during normal subjects sleep using fMRI. However, the earlier estimations do not directly relate to the background oscillations present during the interictal epileptiform patterns during sleep. In contrast the dynamic source coherence method is a tool to study the causality on the cortical and sub-cortical source level. In this study we measured the functional and directed connectivity with renormalized partial directed coherence during continuous spikes and waves during slow wave sleep EEG recordings from 12 patients. The network of sources involved was premotor cortex, posterior cingulate cortex, dorsolateral prefrontal cortex, middle temporal gyrus, medial thalamus and cerebellum. The cerebellum, thalamus and the posterior cingulate cortex showed significant bi-directional causality whereas all the other the sources showed uni-directional causality. Our results suggest that the mean source coherence could be an early biomarker for onset and severity of the disease. In addition we show the source network and the directed connectivity of the background frequency oscillations for continuous spikes and waves during slow wave sleep