Simultaneous functional magnetic resonance imaging and electrophysiological recordings : practical application and methodological approach /
Abstract: The present work investigated two distinct analytical approaches to simultaneous EEG/fMRI data. In the first part, functional connectivity analysis was applied to simultaneous EEG/fMRI data to study cerebral networks and hemodynamic correlates of sleep specific EEG features as well as t...
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| Principais autores: | , , |
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| Formato: | Dissertação |
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| Endereço do item: | https://app.bczm.ufrn.br/home/#/item/233024 |
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| Resumo: | Abstract:
The present work investigated two distinct analytical approaches to
simultaneous EEG/fMRI data. In the first part, functional connectivity analysis was applied to simultaneous EEG/fMRI data to study cerebral networks and
hemodynamic correlates of sleep specific EEG features as well as their functional significance during human sleep. In the second part, methodological aspects were addressed, evaluating the potential of a non-linear analysis method called recurrence quantification analysis (RQA) to extract rapidly changing dynamic features of electrophysiological data, which may be used to improve fMRI models of brain behaviour.
According to the standard model of memory consolidation, memory formation
initially occurs in the hippocampus and the medial temporal lobe, where new
experiences are temporarily stored. Long-term memory storage relies on off-line transfer to and consolidation in the neocortex. This information transfer between the hippocampus and the neocortex is believed to benefit from sleep. The goal of the first study was to determine spontaneous functional connectivity maps of subregions of the hippocampal formation (HF) with the rest of the brain in humans, and to evaluate their alteration throughout non rapid eye movement (NREM) sleep. We provided first evidence of changes in human hippocampal connectivity patterns from wakefulness to NREM sleep. The strongest functional connectivity between the HF, especially the
subiculum output region, and neocortex was observed in sleep stage 2, while
weakest connectivity was found in slow wave sleep. Increased connectivity between HF and neocortical regions in sleep stage 2 further appears associated to the presence of fast sleep spindle activity in concurrent electrophysiological recordings. This suggests an increased capacity for possible global information transfer, while reduced long-range connectivity in slow wave sleep may reflect a functional system optimal for segregated information reprocessing. Our data may be relevant to differentiating sleep stage specific contributions to neural plasticity as proposed in sleep dependent memory consolidation.
Simultaneous EEG/fMRI recording allow to combine the high EEG temporal
resolution with the unmatched fMRI spatial resolution and the flexibility of fMRI to explore brain behaviour in various sensoric, cognitive and emotional paradigms. Today, analysis of event related potentials (ERP) is usually performed by an averaging of multiple EEG trials, in order to increase the signal-to-noise ratio. Thus, the temporal resolution of the EEG is partially lost, and averaging does not consider response changes across trials. This variability can, however, represent changes in subject's performance or fluctuations in attention, arousal, habituation or other cognitive features. In the second part of this thesis, we evaluated the potential of a nonlinear signal analysis method, recurrence quantification analysis (RQA), to improve the characterization of single trial EEG responses. This analysis showed that
RQA is not significantly superior to conventional amplitude analysis. Despite equal discrimination power, RQA measures were only weakly correlated with ERP amplitudes, suggesting that additional information on single trials may be extracted by RQA. Therefore, RQA may be used as an additional tool to obtain new insights about the neurophysiology of the brain. |
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