Power spectrum stability in resting state: a reliability study with Magnetoencephalography

Este trabajo ha sido publicado en: Martín-Buro, María Carmen ; Garcés, Pilar ; Maestú, Fernando Test-retest reliability of resting-state magnetoencephalography power in sensor and source space Human brain mapping. Vol: 37, 1 : 179-190. Versión online: 14 octubre 2015DOI: 10.1002/hbm.23027La sincronización de las oscilaciones cerebrales se produce incluso en ausencia de tarea, por eso, el resting state está aportando interesantes vías de estudio de los procesos normales y patológicos. Dada la creciente necesidad por utilizar las medidas derivadas de las señales MEG en resting state como biomarcadores clínicos o en la evaluación de tratamientos, es necesario garantizar su fiabilidad. En este estudio se ha investigado por primera vez la fiabilidad de la las medidas espectrales derivadas de registros MEG explorando la estabilidad en resting state de la potencia de 10 sujetos sanos en tres sesiones con un intervalo test-retest de 7 días. A partir de las señales MEG de cada sujeto y sesión se calculó el espectro de potencia de 1 a 100Hz en cada sensor, y como medida de fiabilidad se utilizó el coeficiente de correlación intraclase (ICC). Para explorar cómo afecta la intensidad de la señal a la estabilidad, se registró la señal de la cámara vacía en cada sesión de registro y se calculó la relación señal/ruido (SNR). La potencia espectral en MEG es muy estable en las bandas de frecuencia α, β y θ, y menos estable en δ y γ-2. Con respecto a la distribución de la estabilidad, la señal capturada en la zona frontal del equipo MEG fue la menos estable a través de todas las bandas de frecuencia. La estabilidad mostró cierta tendencia a disminuir conforme disminuye la SNR; este efecto es parcial, ya que los ritmos cerebrales estables mostraron un alto ICC incluso con baja SNR. En conjunto, estos resultados sugieren que las medidas espectrales en resting state con MEG son suficientemente fiables para ser consideradas en futuros estudios longitudinales sobre cambios en la actividad cerebral.The synchronization of cerebral oscillations takes place even in the absence of task, for that reason, resting state provides interesting lines of study of normal and pathological processes. Given the increasing necessity to use the measures derived from MEG signals in resting state as clinical biomarkers or in the evaluation of treatments, it is necessary to guarantee its reliability. In this study, the reliability of spectral measures derived from MEG recordings is investigated for the first time by means of exploring resting state stability of the power spectrum of 10 healthy subjects in three sessions with 7 days test-retest interval. The power spectrum from 1 to 100Hz was calculated for each subject, session and sensor, and intraclass correlation coefficient (ICC) was used as a measure of test-retest reliability. In order to explore how intensity of the signal affects to the reliability, empty room was recorded in each session, and the signal-to-noise ratio (SNR) was calculated. Spectral power in MEG was very reliable in α, β and θ frequency bands, and less reliable in δ and γ-2. With regard to reliability distribution, sensors covering the frontal area of the scalp were less stable in all frequency bands. The reliability showed a certain trend to fall as the SNR diminishes; this effect was partial, since stable cerebral rhythms show high ICC values even with very low SNR. Overall, these results suggest that spectral measures in resting state with MEG are sufficiently reliable to be considered for future longitudinal studies of brain activity changes.Depto. de Psicología Experimental, Procesos Cognitivos y LogopediaFac. de PsicologíaTRUEsubmitte

Test-Retest Reliability of Resting-State Magnetoencephalography Power in Sensor and Source Space

Several studies have reported changes in spontaneous brain rhythms that could be used asclinical biomarkers or in the evaluation of neuropsychological and drug treatments in longitudinal studies using magnetoencephalography (MEG). There is an increasing necessity to use these measures in early diagnosis and pathology progression; however, there is a lack of studies addressing how reliable they are. Here, we provide the first test-retest reliability estimate of MEG power in resting-state at sensor and source space. In this study, we recorded 3 sessions of resting-state MEG activity from 24 healthy subjects with an interval of a week between each session. Power values were estimated at sensor and source space with beamforming for classical frequency bands: delta (2–4 Hz), theta (4–8 Hz), alpha (8–13 Hz), low beta (13–20 Hz), high beta (20–30 Hz), and gamma (30–45 Hz). Then, test-retest reliability was evaluated using the intraclass correlation coefficient (ICC). We also evaluated the relation between source power and the within-subject variability. In general, ICC of theta, alpha, and low beta power was fairly high (ICC > 0.6) while in delta and gamma power was lower. In source space, fronto-posterior alpha, frontal beta, and medial temporal theta showed the most reliable profiles. Signal-to-noise ratio could be partially responsible for reliability as low signal intensity resulted inhigh within-subject variability, but also the inherent nature of some brain rhythms in resting-state might be driving these reliability patterns. In conclusion, our results described the reliability of MEG power estimates in each frequency band, which could be considered in disease characterization or clinical trials

Alpha Rhythms Reveal When and Where Item and Associative Memories Are Retrieved

Memories for past experiences can range from vague recognition to full-blown recall of associated details. Electroencephalography has shown that recall signals unfold a few hundred milliseconds after simple recognition, but has only provided limited insights into the underlying brain networks. Functional magnetic resonance imaging (fMRI) has revealed a “core recollection network” (CRN) centered on posterior parietal and medial temporal lobe regions, but the temporal dynamics of these regions during retrieval remain largely unknown. Here we used Magnetoencephalography in a memory paradigm assessing correct rejection (CR) of lures, item recognition (IR) and associative recall (AR) in human participants of both sexes. We found that power decreases in the alpha frequency band (10–12 Hz) systematically track different mnemonic outcomes in both time and space: Over left posterior sensors, alpha power decreased in a stepwise fashion from 500 ms onward, first from CR to IR and then from IR to AR. When projecting alpha power into source space, the CRN known from fMRI studies emerged, including posterior parietal cortex (PPC) and hippocampus. While PPC showed a monotonic change across conditions, hippocampal effects were specific to recall. These region-specific effects were corroborated by a separate fMRI dataset. Importantly, alpha power time courses revealed a temporal dissociation between item and associative memory in hippocampus and PPC, with earlier AR effects in hippocampus. Our data thus link engagement of the CRN to the temporal dynamics of episodic memory and highlight the role of alpha rhythms in revealing when and where different types of memories are retrieved

Alpha Rhythms Reveal When and Where Item and Associative Memories Are Retrieved.

Memories for past experiences can range from vague recognition to full-blown recall of associated details. Electroencephalography has shown that recall signals unfold a few hundred milliseconds after simple recognition, but has only provided limited insights into the underlying brain networks. Functional magnetic resonance imaging (fMRI) has revealed a "core recollection network" (CRN) centered on posterior parietal and medial temporal lobe regions, but the temporal dynamics of these regions during retrieval remain largely unknown. Here we used Magnetoencephalography in a memory paradigm assessing correct rejection (CR) of lures, item recognition (IR) and associative recall (AR) in human participants of both sexes. We found that power decreases in the alpha frequency band (10-12 Hz) systematically track different mnemonic outcomes in both time and space: Over left posterior sensors, alpha power decreased in a stepwise fashion from 500 ms onward, first from CR to IR and then from IR to AR. When projecting alpha power into source space, the CRN known from fMRI studies emerged, including posterior parietal cortex (PPC) and hippocampus. While PPC showed a monotonic change across conditions, hippocampal effects were specific to recall. These region-specific effects were corroborated by a separate fMRI dataset. Importantly, alpha power time courses revealed a temporal dissociation between item and associative memory in hippocampus and PPC, with earlier AR effects in hippocampus. Our data thus link engagement of the CRN to the temporal dynamics of episodic memory and highlight the role of alpha rhythms in revealing when and where different types of memories are retrieved.SIGNIFICANCE STATEMENT Our ability to remember ranges from the vague feeling of familiarity to vivid recollection of associated details. Scientific understanding of episodic memory thus far relied upon separate lines of research focusing on either temporal (via electroencephalography) or spatial (via functional magnetic resonance imaging) dimensions. However, both techniques have limitations that have hindered understanding of when and where memories are retrieved. Capitalizing on the enhanced temporal and spatial resolution of magnetoencephalography, we show that changes in alpha power reveal both when and where different types of memory are retrieved. Having access to the temporal and spatial characteristics of successful retrieval provided new insights into the cross-regional dynamics in the hippocampus and parietal cortex

Mecanismos cognitivos y neurales de la reactivación de la memoria episódica: de la consolidación a la recuperación

Tesis de la Universidad Complutense de Madrid, Facultad de Psicología, leída el 22/03/2019Introduction: Episodic memory is the result of highly dynamic processing. After encoding, the memory trace undergoes a set of transformations that range from the unconscious replay during waking rest periods to the full-blown reactivation that gives rise to our experience of recollection. The literature review reveals that, despite our knowledge of the neocorticalhippocampal circuits involved, their brain oscillatory mechanisms remain unclear. Objective: The main goal of this doctoral thesis is to track episodic memory reactivation during consolidation and retrieval by means of its oscillatory signatures. Explicitly, we aim to unveil how their underlying neural mechanisms unfold over time and space to coordinate behaviour...Introducción: La memoria episódica es el resultado de un procesamiento altamente dinámico. Tras la codificación, el recuerdo sufre una serie de transformaciones que abarcan desde la reactivación (replay) inconsciente durante los periodos de reposo en vigilia, hasta la reactivación íntegra que da lugar a nuestra experiencia subjetiva de ‘recordar’ (vs. reconocer). A pesar de que conocemos las regiones cerebrales implicadas, sus mecanismos neurales oscilatorios siguen sin conocerse adecuadamente. Objetivo: El objetivo principal de esta tesis es rastrear la reactivación de la memoria episódica durante la consolidación y la recuperación a través de sus perfiles de actividad oscilatoria. En concreto, a partir de registros de Magnetoencefalografía (MEG) con participantes sanos, se pretende desvelar cómo se despliegan los mecanismos neurales subyacentes en el tiempo y el espacio para coordinar el comportamiento...Fac. de PsicologíaTRUEunpu

Functional Connectivity Disruption in Subjective Cognitive Decline and Mild Cognitive Impairment: A Common Pattern of Alterations

Functional connectivity (FC) alterations represent a key feature in Alzheimer's Disease (AD) and provide a useful tool to characterize and predict the course of the disease. Those alterations have been also described in Mild Cognitive Impairment (MCI), a prodromal stage of AD. There is a growing interest in detecting AD pathology in the brain in the very early stages of the disorder. Subjective Cognitive Decline (SCD) could represent a preclinical asymptomatic stage of AD but very little is known about this population. In the present work we assessed whether FC disruptions are already present in this stage, and if they share any spatial distribution properties with MCI alterations (a condition known to be highly related to AD). To this end, we measured electromagnetic spontaneous activity with MEG in 39 healthy control elders, 41 elders with SCD and 51 MCI patients. The results showed FC alterations in both SCD and MCI compared to the healthy control group. Interestingly, both groups exhibited a very similar spatial pattern of altered links: a hyper-synchronized anterior network and a posterior network characterized by a decrease in FC. This decrease was more pronounced in the MCI group. These results highlight that elders with SCD present FC alterations. More importantly, those disruptions affected AD typically related areas and showed great overlap with the alterations exhibited by MCI patients. These results support the consideration of SCD as a preclinical stage of AD and may indicate that FC alterations appear very early in the course of the disease

The hippocampus as the switchboard between perception and memory.

Adaptive memory recall requires a rapid and flexible switch from external perceptual reminders to internal mnemonic representations. However, owing to the limited temporal or spatial resolution of brain imaging modalities used in isolation, the hippocampal–cortical dynamics supporting this process remain unknown. We thus employed an object-scene cued recall paradigm across two studies, including intracranial electroencephalography (iEEG) and high-density scalp EEG. First, a sustained increase in hippocampal high gamma power (55 to 110 Hz) emerged 500 ms after cue onset and distinguished successful vs. unsuccessful recall. This increase in gamma power for successful recall was followed by a decrease in hippocampal alpha power (8 to 12 Hz). Intriguingly, the hippocampal gamma power increase marked the moment at which extrahippocampal activation patterns shifted from perceptual cue toward mnemonic target representations. In parallel, source-localized EEG alpha power revealed that the recall signal progresses from hippocampus to posterior parietal cortex and then to medial prefrontal cortex. Together, these results identify the hippocampus as the switchboard between perception and memory and elucidate the ensuing hippocampal–cortical dynamics supporting the recall process.post-print1844 K