324,262 research outputs found
Coelli, C, 2789115
No full textThis record was harvested from a previous catalogue system and will be withdrawn in 2025. Information in this record may be superseded or incomplete. Visit this record in UMA's new catalogue at: https://archives.library.unimelb.edu.au/nodes/view/377867Surname: COELLI
Given Name(s) or Initials: C
Military Service Number or Last Known Location: 2789115
Missing, Wounded and Prisoner of War Enquiry Card Index Number: SEA-3775191681
Item: [2016.0049.10162] "Coelli, C, 2789115
Automatic artifacts correction: improving on-line EEG analysis
No full textIn this paper an automatic ocular artifacts management procedure for EEG analysis on-line is proposed, composed of a detection algorithm followed by a correction which is based on canonical correlation analysis (CCA). The accuracy of the whole method is tested on simulated signals and its capability of recovering the original signals is shown to be comparable with non-automatic ‘gold standard’ procedure (independent component analysis - ICA). The method is implemented to be suitable for fast EEG processing to improve on-line signal interpretation. An example on real data is also provided
Electrophysiological and neuroimaging approaches for the investigation of functional brain networks
No full textDespite the continuous advances in brain imaging and signaling techniques, our knowledge of the human brain remains incomplete. In the study of the fascinating yet complex brain connectome, only the integration of complementary techniques can provide a more complete view and extend the spatio-temporal domain coverage. Likely, multiple analytical frameworks are required to comprehensively unravel the brain’s interaction patterns. The aim of this talk is to provide an overview of the areas of integration of neuroimaging and electrophysiological techniques and processing pipelines that are relevant for the study of functional brain networks. We will describe the principles, advantages, and drawbacks of techniques such as functional magnetic resonance imaging (fMRI) and electroencephalography (EEG), as well as unimodal and multimodal analysis approaches for the study of functional brain networks. Finally, we will present exemplary applications of these approaches in the study of neuropsychiatric disorders for which a dysconnectivity hypothesis has been proposed
Handedness-Dependent Brain Networks Re-organization During Visuo-Motor Task Execution
No full textThe aim of the present study was to investigate handedness-dependent organization and functioning of brain networks during visuomotor integration processes. Specifically, a connectivity study was conducted on EEG traces acquired on a group of healthy volunteers during a resting (baseline) condition and the execution of a visuomotor task with the dominant and non-dominant hands. Our results showed that an enhanced network reorganization is observed in the mu band during the movement performed with the right hand with respect to the baseline condition. Conversely, more evident reorganization was observed for the movement performed with the non-dominant hand when dealing with the beta band. These results suggest that different brain functional reorganization strategies are used to accomplish motor tasks with the two body sides. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG
L'elaborazione dei segnali biomedici per ottenere parametri vitali significativi per il benessere e l'invecchiamento attivo
No full textAssociation Between Variations in Kinematic Indexes of Manual Dexterity and Mu Rhythm Desynchronization Changes After Action Observation and Motor Imagery
No full textThe Mirror Neuron System functioning have enabled the development of Action Observation and Motor Imagery (AOMI) as effective approaches to enhance manual dexterity. Improvements in manual dexterity can be quantified using kinematic indexes during the execution of clinical and functional tests, and neurodynamical correlates of such changes may also be investigated through EEG recording. The current study aimed at investigating (1) kinematic and EEG mu rhythm desynchronization changes after an AOMI-training in healthy subjects and (2) the association between variations in kinematic indexes of manual dexterity and mu rhythm desynchronization changes induced by AOMI. Thirty healthy subjects performed a 3-week AOMI intervention consisting of the observation and motor imagery of transitive manual dexterity tasks. Manual dexterity assessed through the analysis of kinematic indexes and EEG mu rhythm desynchronizations were analyzed before and after the training. Results showed that AOMI improved kinematic indexes of manual dexterity and induced an increase in murhythm desynchronizations during motor performance. Furthermore, improvements in kinematic indexes of manual dexterity were related to mu rhythm desynchronization changes in central and parietal cortical areas during the execution of NHPT with the left hand. These findings are explanatory of parameters of human movements subtended to sensorimotor system activity changes induced by AOMI and may provide useful information for planning AOMI interventions aimed at enhancing manual dexterity. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG
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