A multimodal investigation of dynamic face perception using functional magnetic resonance imaging and magnetoencephalography

Motion is an important aspect of face perception that has been largely neglected to date. Many of the established findings are based on studies that use static facial images, which do not reflect the unique temporal dynamics available from seeing a moving face. In the present thesis a set of naturalistic dynamic facial emotional expressions was purposely created and used to investigate the neural structures involved in the perception of dynamic facial expressions of emotion, with both functional Magnetic Resonance Imaging (fMRI) and Magnetoencephalography (MEG). Through fMRI and connectivity analysis, a dynamic face perception network was identified, which is demonstrated to extend the distributed neural system for face perception (Haxby et al.,2000). Measures of effective connectivity between these regions revealed that dynamic facial stimuli were associated with specific increases in connectivity between early visual regions, such as inferior occipital gyri and superior temporal sulci, along with coupling between superior temporal sulci and amygdalae, as well as with inferior frontal gyri. MEG and Synthetic Aperture Magnetometry (SAM) were used to examine the spatiotemporal profile of neurophysiological activity within this dynamic face perception network. SAM analysis revealed a number of regions showing differential activation to dynamic versus static faces in the distributed face network, characterised by decreases in cortical oscillatory power in the beta band, which were spatially coincident with those regions that were previously identified with fMRI. These findings support the presence of a distributed network of cortical regions that mediate the perception of dynamic facial expressions, with the fMRI data providing information on the spatial co-ordinates paralleled by the MEG data, which indicate the temporal dynamics within this network. This integrated multimodal approach offers both excellent spatial and temporal resolution, thereby providing an opportunity to explore dynamic brain activity and connectivity during face processing

A multimodal investigation of dynamic face perception using functional magnetic resonance imaging and magnetoencephalography

Motion is an important aspect of face perception that has been largely neglected to date. Many of the established findings are based on studies that use static facial images, which do not reflect the unique temporal dynamics available from seeing a moving face. In the present thesis a set of naturalistic dynamic facial emotional expressions was purposely created and used to investigate the neural structures involved in the perception of dynamic facial expressions of emotion, with both functional Magnetic Resonance Imaging (fMRI) and Magnetoencephalography (MEG). Through fMRI and connectivity analysis, a dynamic face perception network was identified, which is demonstrated to extend the distributed neural system for face perception (Haxby et al.,2000). Measures of effective connectivity between these regions revealed that dynamic facial stimuli were associated with specific increases in connectivity between early visual regions, such as inferior occipital gyri and superior temporal sulci, along with coupling between superior temporal sulci and amygdalae, as well as with inferior frontal gyri. MEG and Synthetic Aperture Magnetometry (SAM) were used to examine the spatiotemporal profile of neurophysiological activity within this dynamic face perception network. SAM analysis revealed a number of regions showing differential activation to dynamic versus static faces in the distributed face network, characterised by decreases in cortical oscillatory power in the beta band, which were spatially coincident with those regions that were previously identified with fMRI. These findings support the presence of a distributed network of cortical regions that mediate the perception of dynamic facial expressions, with the fMRI data providing information on the spatial co-ordinates paralleled by the MEG data, which indicate the temporal dynamics within this network. This integrated multimodal approach offers both excellent spatial and temporal resolution, thereby providing an opportunity to explore dynamic brain activity and connectivity during face processing.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Modulation of Neural Oscillatory Activity during Dynamic Face Processing

Various neuroimaging and neurophysiological methods have been used to examine neural activation patterns in response to faces. However, much of previous research has relied on static images of faces, which do not allow a complete description of the temporal structure of face-specific neural activities to be made. More recently, insights are emerging from fMRI studies about the neural substrates that underpin our perception of naturalistic dynamic face stimuli, but the temporal and spectral oscillatory activity associated with processing dynamic faces has yet to be fully characterized. Here, we used MEG and beamformer source localization to examine the spatiotemporal profile of neurophysiological oscillatory activity in response to dynamic faces. Source analysis revealed a number of regions showing enhanced activation in response to dynamic relative to static faces in the distributed face network, which were spatially coincident with regions that were previously identified with fMRI. Furthermore, our results demonstrate that perception of realistic dynamic facial stimuli activates a distributed neural network at varying time points facilitated by modulations in low-frequency power within alpha and beta frequency ranges (8-30 Hz). Naturalistic dynamic face stimuli may provide a better means of representing the complex nature of perceiving facial expressions in the real world, and neural oscillatory activity can provide additional insights into the associated neural processes

Developing and piloting a resource for training assessors in use of the Mini-CEX (mini clinical evaluation exercise).

The assessment of undergraduate medical students in the clinical setting has become a key priority for medical educators. Facilitating the successful translation of undergraduate theoretical knowledge into safe and appropriate postgraduate clinical practice represents a challenge in medical education [1]. Poor clinical performance of newly qualified doctors has been highlighted as a major issue relating to patient safety [2]. Performance based assessment in the undergraduate setting may assist in addressing this issue by assessing ‘doing’ rather than ‘knowing’. The mini clinical evaluation exercise (Mini-CEX) is a formative assessment used to assess the performance of medical students in a clinical context. It incorporates assessment by, and feedback from, an assessor, based on the direct observation of a student–patient consultation [3]. Conducted in a series of stages, the Mini-CEX allows focused assessment of key competencies (see Box 1) [3]

Dynamic facial expressions evoke distinct activation in the face perception network:a connectivity analysis study

Very little is known about the neural structures involved in the perception of realistic dynamic facial expressions. In the present study, a unique set of naturalistic dynamic facial emotional expressions was created. Through fMRI and connectivity analysis, a dynamic face perception network was identified, which is demonstrated to extend Haxby et al.'s [Haxby, J. V., Hoffman, E. A., & Gobbini, M. I. The distributed human neural system for face perception. Trends in Cognitive Science, 4, 223–233, 2000] distributed neural system for face perception. This network includes early visual regions, such as the inferior occipital gyrus, which is identified as insensitive to motion or affect but sensitive to the visual stimulus, the STS, identified as specifically sensitive to motion, and the amygdala, recruited to process affect. Measures of effective connectivity between these regions revealed that dynamic facial stimuli were associated with specific increases in connectivity between early visual regions, such as the inferior occipital gyrus and the STS, along with coupling between the STS and the amygdala, as well as the inferior frontal gyrus. These findings support the presence of a distributed network of cortical regions that mediate the perception of different dynamic facial expressions

Establishing a Developmentally Appropriate fMRI Paradigm Relevant to Presurgical Mapping of Memory in Children

Functional magnetic resonance imaging (fMRI) is an established eloquent cortex mapping technique that is now an integral part of the pre-operative work-up in candidates for epilepsy surgery. Emerging evidence in adults with epilepsy suggests that material-specific fMRI paradigms can predict postoperative memory outcomes, however these paradigms are not suitable for children. In pediatric age, the use of memory fMRI paradigms designed for adults is complicated by the effect of developmental stages in cognitive maturation, the impairment experienced by some people with temporal lobe epilepsy (TLE) and the normal representation of memory function during development, which may differ from adults. We present a memory fMRI paradigm designed to activate mesial temporal lobe structures that is brief, independent of reading ability, and therefore a novel candidate for use in children. Data from 33 adults and 19 children (all healthy controls) show that the paradigm captures the expected leftward asymmetry of mesial temporal activation in adults. A more symmetrical pattern was observed in children, consistent with the progressive emergence of hemispheric specialisation across childhood. These data have important implications for the interpretation of presurgical memory fMRI in the pediatric setting. They also highlight the need to carefully consider the impact of cognitive development on fMRI tools used in clinical practice

Impairment in Theory of Mind in Parkinson’s Disease Is Explained by Deficits in Inhibition

Objective. Several studies have reported that people with Parkinson's disease (PD) perform poorly on tests of 'Theory of Mind' (ToM), suggesting impairment in the ability to understand and infer other people's thoughts and feelings. However, few studies have sought to separate the processes involved in social reasoning from those involved in managing the inhibitory demands on these tests. In this study, we investigated the contribution of inhibition to ToM performance in PD. Methods. 18 PD patients and 22 age-matched healthy controls performed a ToM test that separates the ability to infer someone else's perspective from the ability to inhibit one's own. Participants also completed a battery of standard measures of social and executive functioning, including measures of inhibition. Results. The PD patients performed worse on the ToM test only when the inhibitory demands were high. When the level of inhibition required was reduced, there were no significant group differences. Furthermore, executive impairments in PD patients were limited to measures of inhibition, with disadvantages associated with poorer ToM performance in this group. Conclusions. This study provides convincing evidence that the apparent impairment observed on ToM tests in PD is explained by deficits in inhibition

EPINETLAB:a software for seizure-onset zone identification from intracranial EEG signal in epilepsy

The pre-operative workup of patients with drug-resistant epilepsy requires in some candidates the identification from intracranial EEG (iEEG) of the seizure-onset zone (SOZ), defined as the area responsible of the generation of the seizure and therefore candidate for resection. High-frequency oscillations (HFOs) contained in the iEEG signal have been proposed as biomarker of the SOZ. Their visual identification is a very onerous process and an automated detection tool could be an extremely valuable aid for clinicians, reducing operator-dependent bias and computational time. In this manuscript we present the EPINETLAB software, developed as a collection of routines integrated in the EEGLAB framework that aim to provide clinicians with a structured analysis pipeline for HFOs detection and SOZ identification. The tool implements an analysis strategy developed by our group and underwent a preliminary clinical validation that identifies the HFOs area by extracting the statistical properties of HFOs signal and that provides useful information for a topographic characterization of the relationship between clinically defined SOZ and HFO area. Additional functionalities such as inspection of spectral properties of ictal iEEG data and import and analysis of source-space MEG data were also included. EPINETLAB was developed with user-friendliness in mind to support clinicians in the identification and quantitative assessment of HFOs in iEEG and source space MEG data and aid the evaluation of the SOZ for pre-surgical assessment

An evaluation of kurtosis beamforming in magnetoencephalography to localize the epileptogenic zone in drug resistant epilepsy patients

OBJECTIVE: Kurtosis beamforming is a useful technique for analysing magnetoencephalograpy (MEG) data containing epileptic spikes. However, the implementation varies and few studies measure concordance with subsequently resected areas. We evaluated kurtosis beamforming as a means of localizing spikes in drug-resistant epilepsy patients. METHODS: We retrospectively applied kurtosis beamforming to MEG recordings of 22 epilepsy patients that had previously been analysed using equivalent current dipole (ECD) fitting. Virtual electrodes were placed in the kurtosis volumetric peaks and visually inspected to select a candidate source. The candidate sources were compared to the ECD localizations and resection areas. RESULTS: The kurtosis beamformer produced interpretable localizations in 18/22 patients, of which the candidate source coincided with the resection lobe in 9/13 seizure-free patients and in 3/5 patients with persistent seizures. The sublobar accuracy of the kurtosis beamformer with respect to the resection zone was higher than ECD (56% and 50%, respectively), however, ECD resulted in a higher lobar accuracy (75%, 67%). CONCLUSIONS: Kurtosis beamforming may provide additional value when spikes are not clearly discernible on the sensors and support ECD localizations when dipoles are scattered. SIGNIFICANCE: Kurtosis beamforming should be integrated with existing clinical protocols to assist in localizing the epileptogenic zone