Migraine as dysfunctional drive reduction: Insight from electrophysiology

The missing N1 or jittered P2: Electrophysiological correlates of pattern glare in the time and frequency domain

Excessive sensitivity to certain visual stimuli (cortical hyperexcitability) is associated with a number of neurological disorders including migraine, epilepsy, multiple sclerosis, autism and possibly dyslexia. Others show disruptive sensitivity to visual stimuli with no other obvious pathology or symptom profile (visual stress) which can extend to discomfort and nausea. We used event‐related potentials (ERPs) to explore the neural correlates of visual stress and headache proneness. We analysed ERPs in response to thick (0.37 cycles per degree [c/deg]), medium (3 c/deg) and thin (12 c/deg) gratings, using mass univariate analysis, considering three factors in the general population: headache proneness, visual stress and discomfort. We found relationships between ERP features and the headache and discomfort factors. Stimulus main effects were driven by the medium stimulus regardless of participant characteristics. Participants with high discomfort ratings had larger P1 components for the initial presentation of medium stimuli, suggesting initial cortical hyperexcitability that is later suppressed. The participants with high headache ratings showed atypical N1‐P2 components for medium stripes relative to the other stimuli. This effect was present only after repeated stimulus presentation. These effects were also explored in the frequency domain, suggesting variations in intertrial theta band phase coherence. Our results suggest that discomfort and headache in response to striped stimuli are related to different neural processes; however, more exploration is needed to determine whether the results translate to a clinical migraine population.

Neuropsychiatric Disorders as Erratic Attention Regulation - Lessons from Electrophysiology

Attention related electrophysiological waves, such as P300, often deviate from norm in various populations of neuropsychiatric patients. For example, the amplitude is often smaller and the latency is often longer in major depressive disorder, in bipolar disorder and in schizophrenia. On the other hand, in other neuropsychiatric populations, it is often possible to note the opposite phenomena of larger P300 amplitude and shorter latency in comparison with norm, but only for a specific subset of stimuli. This is often reported in various anxiety disorders, substance abuse and various chronic pain syndromes. These findings in the various clinical populations, on their commonalities and differences, are presented in this work. The prevalence of these two types of deviations in the electrophysiological markers of attention, shared by multiple neuropsychiatric populations, raise interesting questions regarding the role of attention deviation and regulation in neuropsychiatry. We present these questions and outline a possible hypothesis in this regard. Furthermore, such potential sensitivity of the attention-related markers to clinical dynamics suggests they could be candidates for monitoring and, potentially, early-sensing of clinical dynamics. Therefore, we discuss the potential usability of such markers.

Monitoring Migraine Cycle Dynamics with an Easy-to-Use Electrophysiological Marker-A Pilot Study

Migraine attacks can cause significant discomfort and reduced functioning for days at a time, including the pre-ictal and post-ictal periods. During the inter-ictsal period, however, migraineurs seem to function normally. It is puzzling, therefore, that event-related potentials of migraine patients often differ in the asymptomatic and inter-ictal period. Part of the electrophysiological dynamics demonstrated in the migraine cycle are attention related. In this pilot study we evaluated an easy-to-use new marker, the Brain Engagement Index (BEI), for attention monitoring during the migraine cycle. We sampled 12 migraine patients for 20 days within one calendar month. Each session consisted of subjects’ reports of stress level and migraine-related symptoms, and a 5 min EEG recording, with a 2-electrode EEG device, during an auditory oddball task. The first minute of the EEG sample was analyzed. Repetitive samples were also obtained from 10 healthy controls. The brain engagement index increased significantly during the pre-ictal (p ≈ 0.001) and the ictal (p ≈ 0.020) periods compared with the inter-ictal period. No difference was observed between the pre-ictal and ictal periods. Control subjects demonstrated intermediate Brain Engagement Index values, that is, higher than inter-ictal, yet lower than pre-ictal. Our preliminary results demonstrate the potential advantage of the use of a simple EEG system for improved prediction of migraine attacks. Further study is required to evaluate the efficacy of the Brain Engagement Index in monitoring the migraine cycle and the possible effects of interventions.

A Possible Common Neurophysiologic Basis for MDD, Bipolar Disorder, and Schizophrenia: Lessons from Electrophysiology

There is ample electrophysiological evidence of attention dysfunction in the EEG/ERP signal of major depressive disorder (MDD), bipolar disorder, and schizophrenia. The reduced attention-related ERP waves show much similarity between MDD, bipolar disorder, and schizophrenia, raising the question whether there are similarities in the neurophysiologic process that underlies attention dysfunction in these pathologies. The present work suggests that there is such a unified underlying neurophysiologic process, which results in reduced attention in the three pathologies. Naturally, as these pathologies involve different clinical manifestations, we expect differences in their underlying neurophysiology. These differences and their subtle manifestation in the ERP marker for attention are also discussed. MDD, bipolar disorder, and schizophrenia are just three of multiple neuropsychiatric disorders, which involve changes in the EEG/ERP manifestations of attention. Further work should expand the basic model presented here to offer comprehensive modeling of these multiple disorders and to emphasize similarities and dissimilarities of the underlying neurophysiologic processes.