Exploring alterations in sensory pathways in migraine

Background Migraine is a neurological disorder characterized by intense, debilitating headaches, often coupled with nausea, vomiting and sensitivity to light and sound. Whilst changes in sensory processes during a migraine attack have been well-described, there is growing evidence that even between migraine attacks, sensory abilities are disrupted in migraine. Brain imaging studies have investigated altered coupling between areas of the descending pain modulatory pathway but coupling between somatosensory processing regions between migraine attacks has not been properly studied. The aim of this study was to determine if ongoing functional connectivity between visual, auditory, olfactory, gustatory and somatosensory cortices are altered during the interictal phase of migraine. Methods To explore the neural mechanisms underpinning interictal changes in sensory processing, we used functional magnetic resonance imaging to compare resting brain activity patterns and connectivity in migraineurs between migraine attacks (n = 32) and in healthy controls (n = 71). Significant differences between groups were determined using two-sample random effects procedures (p < 0.05, corrected for multiple comparisons, minimum cluster size 10 contiguous voxels, age and gender included as nuisance variables). Results In the migraine group, increases in infra-slow oscillatory activity were detected in the right primary visual cortex (V1), secondary visual cortex (V2) and third visual complex (V3), and left V3. In addition, resting connectivity analysis revealed that migraineurs displayed significantly enhanced connectivity between V1 and V2 with other sensory cortices including the auditory, gustatory, motor and somatosensory cortices. Conclusions These data provide evidence for a dysfunctional sensory network in pain-free migraine patients which may be underlying altered sensory processing between migraine attacks.

Aging-Related Changes in Cortical Sources of Sleep Oscillatory Neural Activity Following Motor Learning Reflect Contributions of Cortical Thickness and Pre-sleep Functional Activity

Oscillatory neural activity during sleep, such as that in the delta and sigma bands, is important for motor learning consolidation. This activity is reduced with typical aging, and this reduction may contribute to aging-related declines in motor learning consolidation. Evidence suggests that brain regions involved in motor learning contribute to oscillatory neural activity during subsequent sleep. However, aging-related differences in regional contributions to sleep oscillatory activity following motor learning are unclear. To characterize these differences, we estimated the cortical sources of consolidation-related oscillatory activity using individual anatomical information in young and older adults during non-rapid eye movement sleep after motor learning and analyzed them in light of cortical thickness and pre-sleep functional brain activation. High-density electroencephalogram was recorded from young and older adults during a midday nap, following completion of a functional magnetic resonance imaged serial reaction time task as part of a larger experimental protocol. Sleep delta activity was reduced with age in a left-weighted motor cortical network, including premotor cortex, primary motor cortex, supplementary motor area, and pre-supplementary motor area, as well as non-motor regions in parietal, temporal, occipital, and cingulate cortices. Sleep theta activity was reduced with age in a similar left-weighted motor network, and in non-motor prefrontal and middle cingulate regions. Sleep sigma activity was reduced with age in left primary motor cortex, in a non-motor right-weighted prefrontal-temporal network, and in cingulate regions. Cortical thinning mediated aging-related sigma reductions in lateral orbitofrontal cortex and frontal pole, and partially mediated delta reductions in parahippocampal, fusiform, and lingual gyri. Putamen, caudate, and inferior parietal cortex activation prior to sleep predicted frontal and motor cortical contributions to sleep delta and theta activity in an age-moderated fashion, reflecting negative relationships in young adults and positive or absent relationships in older adults. Overall, these results support the local sleep hypothesis that brain regions active during learning contribute to consolidation-related neural activity during subsequent sleep and demonstrate that sleep oscillatory activity in these regions is reduced with aging.

Active Role of Self-Sustained Neural Activity on Sensory Input Processing: A Minimal Theoretical Model

A growing body of work has demonstrated the importance of ongoing oscillatory neural activity in sensory processing and the generation of sensorimotor behaviors. It has been shown, for several different brain areas, that sensory-evoked neural oscillations are generated from the modulation by sensory inputs of inherent self-sustained neural activity (SSA). This letter contributes to that strand of research by introducing a methodology to investigate how much of the sensory-evoked oscillatory activity is generated by SSA and how much is generated by sensory inputs within the context of sensorimotor behavior in a computational model. We develop an abstract model consisting of a network of three Kuramoto oscillators controlling the behavior of a simulated agent performing a categorical perception task. The effects of sensory inputs and SSAs on sensory-evoked oscillations are quantified by the cross product of velocity vectors in the phase space of the network under different conditions (disconnected without input, connected without input, and connected with input). We found that while the agent is carrying out the task, sensory-evoked activity is predominantly generated by SSA (93.10%) with much less influence from sensory inputs (6.90%). Furthermore, the influence of sensory inputs can be reduced by 10.4% (from 6.90% to 6.18%) with a decay in the agent's performance of only 2%. A dynamical analysis shows how sensory-evoked oscillations are generated from a dynamic coupling between the level of sensitivity of the network and the intensity of the input signals. This work may suggest interesting directions for neurophysiological experiments investigating how self-sustained neural activity influences sensory input processing, and ultimately affects behavior.

Keeping time and rhythm by replaying a sensory-motor engram

Imagine practicing a piece of music, or a speech, solely within the mind, without any sensory input or motor output. Our ability to implement dynamic internal representations is key for successful behavior, yet how the brain achieves this is not fully understood. Here we trained primates to perceive, and internally maintain, rhythms of different tempos and performed large-scale recordings of neuronal activity across multiple areas spanning the sensory-motor processing hierarchy. Results show that perceiving and maintaining rhythms engage multiple brain areas, including visual, parietal, premotor, prefrontal, and hippocampal regions. Each area displayed oscillatory activity that reflected the temporal and spatial characteristics of an internal metronome which flexibly encoded fast, medium, and slow tempos on a trial-by-trial basis. The presence of widespread metronome-related activity across the brain, in the absence of stimuli and overt actions, is consistent with the idea that time and rhythm are maintained by a mechanism that internally replays the stimuli and actions that define well-timed behavior.

Evidence for Three Subgroups of Female FMR1 Premutation Carriers Defined by Distinct Neuropsychiatric Features: A Pilot Study

Over 200 Cytosine-guanine-guanine (CGG) trinucleotide repeats in the 5′ untranslated region of the Fragile X mental retardation 1 (FMR1) gene results in a “full mutation,” clinically Fragile X Syndrome (FXS), whereas 55 – 200 repeats result in a “premutation.” FMR1 premutation carriers (PMC) are at an increased risk for a range of psychiatric, neurocognitive, and physical conditions. Few studies have examined the variable expression of neuropsychiatric features in female PMCs, and whether heterogeneous presentation among female PMCs may reflect differential presentation of features in unique subgroups. In the current pilot study, we examined 41 female PMCs (ages 17–78 years) and 15 age-, sex-, and IQ-matched typically developing controls (TDC) across a battery of self-report, eye tracking, expressive language, neurocognitive, and resting state EEG measures to determine the feasibility of identifying discrete clusters. Secondly, we sought to identify the key features that distinguished these clusters of female PMCs. We found a three cluster solution using k-means clustering. Cluster 1 represented a psychiatric feature group (27% of our sample); cluster 2 represented a group with executive dysfunction and elevated high frequency neural oscillatory activity (32%); and cluster 3 represented a relatively unaffected group (41%). Our findings indicate the feasibility of using a data-driven approach to identify naturally occurring clusters in female PMCs using a multi-method assessment battery. CGG repeat count and its association with neuropsychiatric features differ across clusters. Together, our findings provide important insight into potential diverging pathophysiological mechanisms and risk factors for each female PMC cluster, which may ultimately help provide novel and individualized targets for treatment options.

Neurological Markers of Maladaptive Brain Activity in Fibromyalgia and their Relationship with Treatment Effectiveness

Chronic pain (CP) is estimated to affect at least one-third of the population in the United Kingdom. Fibromyalgia (FM) is one of the most disabling CP conditions. Epidemiological research suggests its global prevalence to be between 2-8%. The unknown pathogenesis, lack of biological markers to monitor its development, and lack of successful treatment make FM a crucial target of pre-clinical research.The goal of this project is twofold. The project aims to 1) identify robust neurological markers (i.e., electrochemical brain activity) by applying a combination of advanced electroencephalography (EEG) signal processing (i.e., functional connectivity of oscillatory activity) and neuroinflammatory (NI) responses (i.e., estimation of pro-inflammatory cytokines intake), through which 2) characterizing successfully and unsuccessfully treated FM patients (compared to age-matched healthy controls). These measures, seldom combined, have been successfully applied to the study of psychiatric conditions and sleep. Crucially, the identification of neurological markers at rest and during arousing sensory stimulation will allow us to estimate the relationship between these neurological markers and treatment effectiveness. This proposal is important because it aims to generate a robust pre-clinical neurological tool to identify FM and its relationship with measures of treatment effectiveness. The successful identification of neurological markers will improve the assessment of the development of maladaptive changes in FM and will kick-start further research on treatment effectiveness.This project is of great medical relevance as it will identify pathological signatures of FM that can then inform research on etiology and treatment of this condition.

Transcranial stimulation of alpha oscillations up-regulates the default mode network

The default mode network (DMN) is the most-prominent intrinsic connectivity network, serving as a key architecture of the brain’s functional organization. Conversely, dysregulated DMN is characteristic of major neuropsychiatric disorders. However, the field still lacks mechanistic insights into the regulation of the DMN and effective interventions for DMN dysregulation. The current study approached this problem by manipulating neural synchrony, particularly alpha (8 to 12 Hz) oscillations, a dominant intrinsic oscillatory activity that has been increasingly associated with the DMN in both function and physiology. Using high-definition alpha-frequency transcranial alternating current stimulation (α-tACS) to stimulate the cortical source of alpha oscillations, in combination with simultaneous electroencephalography and functional MRI (EEG-fMRI), we demonstrated that α-tACS (versus Sham control) not only augmented EEG alpha oscillations but also strengthened fMRI and (source-level) alpha connectivity within the core of the DMN. Importantly, increase in alpha oscillations mediated the DMN connectivity enhancement. These findings thus identify a mechanistic link between alpha oscillations and DMN functioning. That transcranial alpha modulation can up-regulate the DMN further highlights an effective noninvasive intervention to normalize DMN functioning in various disorders.

Electroencephalography Correlates of Well-Being Using a Low-Cost Wearable System

Electroencephalography (EEG) alpha asymmetry is thought to reflect crucial brain processes underlying executive control, motivation, and affect. It has been widely used in psychopathology and, more recently, in novel neuromodulation studies. However, inconsistencies remain in the field due to the lack of consensus in methodological approaches employed and the recurrent use of small samples. Wearable technologies ease the collection of large and diversified EEG datasets that better reflect the general population, allow longitudinal monitoring of individuals, and facilitate real-world experience sampling. We tested the feasibility of using a low-cost wearable headset to collect a relatively large EEG database (N = 230, 22–80 years old, 64.3% female), and an open-source automatic method to preprocess it. We then examined associations between well-being levels and the alpha center of gravity (CoG) as well as trait EEG asymmetries, in the frontal and temporoparietal (TP) areas. Robust linear regression models did not reveal an association between well-being and alpha (8–13 Hz) asymmetry in the frontal regions, nor with the CoG. However, well-being was associated with alpha asymmetry in the TP areas (i.e., corresponding to relatively less left than right TP cortical activity as well-being levels increased). This effect was driven by oscillatory activity in lower alpha frequencies (8–10.5 Hz), reinforcing the importance of dissociating sub-components of the alpha band when investigating alpha asymmetries. Age was correlated with both well-being and alpha asymmetry scores, but gender was not. Finally, EEG asymmetries in the other frequency bands were not associated with well-being, supporting the specific role of alpha asymmetries with the brain mechanisms underlying well-being levels. Interpretations, limitations, and recommendations for future studies are discussed. This paper presents novel methodological, experimental, and theoretical findings that help advance human neurophysiological monitoring techniques using wearable neurotechnologies and increase the feasibility of their implementation into real-world applications.

Theta oscillations in the prefrontal-hippocampal circuit do not couple to respiration-related oscillations

Oscillatory activity is thought to coordinate neural computations across brain regions, and theta oscillations are critical for learning and memory. Because the frequency of respiratory-related oscillations (RROs) in rodents can overlap with the frequency of theta in the prefrontal cortex (PFC) and the hippocampus, we asked whether odor-cued working memory may be supported by coupling between these two oscillations. We first confirmed that RROs are propagated to the hippocampus and PFC and that RRO frequency overlaps with canonical theta frequency. However, we found low coherence between RROs and local theta oscillations in the hippocampus-PFC network when the two types of oscillations overlapped in frequency. This effect was observed during all behavioral phases including during movement and while odors were actively sampled when stationary. Despite the similarity in frequency, RROs and theta oscillations therefore appear to be limited to supporting computation in distinct networks, which suggests that sustained long-range coordination between oscillation patterns that depend on separate pacemakers is not necessary to support at least one type of working memory.