Migraine and motion sickness: what is the link?

The brainstem is a structurally complex region, containing numerous ascending and descending fibres that converge on centres that regulate bodily functions essential to life. Afferent input from the cranial tissues and the special senses is processed, in part, in brainstem nuclei. In addition, brainstem centres modulate the flow of pain messages and other forms of sensory information to higher regions of the brain, and influence the general excitability of these cortical regions. Thus, disruptions in brainstem processing might evoke a complex range of unpleasant symptoms, vegetative changes and neurovascular disturbances and that, together, form attacks of migraine. Migraine is linked with various co-morbid conditions, the most prominent being motion sickness. Symptoms such as nausea, dizziness and headache are common to motion sickness and migraine; moreover, migraine sufferers have a heightened vulnerability to motion sickness. As both maladies involve reflexes that relay in the brainstem, symptoms may share the same neural circuitry. In consequence, subclinical interictal persistence of disturbances in these brainstem pathways could not only increase vulnerability to recurrent attacks of migraine but also increase susceptibility to motion sickness. Mechanisms that mediate symptoms of motion sickness and migraine are explored in this paper. The physiology of motion sickness and migraine is discussed, and neurotransmitters that may be involved in the manifestation of symptoms are reviewed. Recent findings have shed light on the relationship between migraine and motion sickness, and provide insights into the generation of migraine attacks

An error estimate of Gaussian Recursive Filter in 3Dvar problem

Computational kernel of the three-dimensional variational data assimilation (3D-Var) problem is a linear system, generally solved by means of an iterative method. The most costly part of each iterative step is a matrix-vector product with a very large covariance matrix having Gaussian correlation structure. This operation may be interpreted as a Gaussian convolution, that is a very expensive numerical kernel. Recursive Filters (RFs) are a well known way to approximate the Gaussian convolution and are intensively applied in the meteorology, in the oceanography and in forecast models. In this paper, we deal with an oceanographic 3D-Var data assimilation scheme, named OceanVar, where the linear system is solved by using the Conjugate Gradient (GC) method by replacing, at each step, the Gaussian convolution with RFs. Here we give theoretical issues on the discrete convolution approximation with a first order (1st-RF) and a third order (3rd-RF) recursive filters. Numerical experiments confirm given error bounds and show the benefits, in terms of accuracy and performance, of the 3-rd RF.Comment: 9 page

Computation of the inverse Laplace Transform based on a Collocation method which uses only real values

We develop a numerical algorithm for inverting a Laplace transform (LT), based on Laguerre polynomial series expansion of the inverse function under the assumption that the LT is known on the real axis only. The method belongs to the class of Collocation methods (C-methods), and is applicable when the LT function is regular at infinity. Difficulties associated with these problems are due to their intrinsic ill-posedness. The main contribution of this paper is to provide computable estimates of truncation, discretization, conditioning and roundoff errors introduced by numerical computations. Moreover, we introduce the pseudoaccuracy which will be used by the numerical algorithm in order to provide uniform scaled accuracy of the computed approximation for any x with respect to ex . These estimates are then employed to dynamically truncate the series expansion. In other words, the number of the terms of the series acts like the regularization parameter which provides the trade-off between errors. With the aim to validate the reliability and usability of the algorithm experiments were carried out on several test functions

Exploring treatment strategies for mood stabilization in patients with major depressive disorder and mixed features

We discuss strategies for mood stabilization in patients with major depressive disorder (MDD) and mixed features, challenging traditional paradigms and calling for a reevaluation of current diagnostic classifications. The DSM-5 "mixed features specifier" applies to several mood disorders, including MDD. In patients with MDD, this specifier blurs the traditional distinctions between depression and mania by introducing criteria that include symptoms such as elevated, expansive mood, inflated self-esteem, increased talkativeness, flight of ideas, increased energy, involvement in activities with potentially painful consequences, and decreased need for sleep. According to the DSM, when 3 of the above 7 symptoms are present during a major depressive episode, the episode may be characterized by the specifier "with mixed features". Despite the relatively high prevalence of mixed features in patients with MDD, no specific pharmacological treatments have been approved for these cases. We propose a treatment approach that includes: 1) initiating treatment with an antimanic agent (e.g., a mood stabilizer or a new-generation antipsychotic); 2) considering adjunctive low-dose serotonergic antidepressants; and then 3) considering discontinuation of the antimanic agent once the acute episode has resolved. We emphasize the lack of adequate studies of maintenance treatment with mood stabilizers and antipsychotics in patients with MDD and mixed features and the need for further research to improve our mood stabilization strategies for these patients

Unraveling the Boundaries, Overlaps, and Connections between Schizophrenia and Obsessive–Compulsive Disorder (OCD)

Schizophrenia (SCZ) and obsessive-compulsive disorder (OCD) typically have distinct diagnostic criteria and treatment approaches. SCZ is characterized by delusions, hallucinations, disorganized speech, and cognitive impairments, while OCD involves persistent, intrusive thoughts (obsessions) and repetitive behaviors (compulsions). The co-occurrence of these disorders increases clinical complexity and poses significant challenges for diagnosis and treatment. Epidemiological studies indicate a significant overlap, with prevalence rates of comorbid OCD in SCZ patients ranging from 12% to 25%, which is higher than in the general population. Etiological hypotheses suggest shared genetic, neurobiological, and environmental factors, with genetic studies identifying common loci and pathways, such as glutamatergic and dopaminergic systems. Neuroimaging studies reveal both overlapping and distinct neural abnormalities, indicating shared and unique neurobiological substrates. Environmental factors, like early life stressors and urbanicity, also contribute to the comorbidity. The overlapping clinical features of both disorders complicate diagnosis. Treatment approaches include combining SSRIs with antipsychotics and cognitive behavioral therapy (CBT). The complexity of SCZ and OCD comorbidity underscores the need for a dimensional, spectrum-based perspective on psychiatric disorders, alongside traditional categorical approaches, to improve diagnosis and treatment outcomes