Applied Neurosciences

A framework combining delta event related oscillations (EROs) and synchronisation effects (ERD/ERS) to study emotional processing

2009-05-04T18:31:00.004+02:00

Manousos A. Klados, Christos Frantzidis, Ana Vivas, Christos Papadelis, Chrysa Lithari, Costas Pappas, Panagiotis D. Bamidis

Abstract:

The amount of literature investigating the neuronal mechanisms involved in emotional processing has been growing recently. This has been partly due to the availability of standardized databases like the International Affective Pictures System (IAPS), with pictures of emotional content. Event-Related Potentials (ERPs) or Event-Related Oscillations (EROs) have been widely used to this end, mainly on the theta and gamma frequency bands. However, the role of the slow (delta) waves has been largely ignored. The aim of this study is to provide a framework that combines EROs with Event Related Desynchronization (ERD) / Event Related Synchronization (ERS) and peak amplitude analysis of delta activity, evoked by the passive viewing of emotionally evocative pictures. Results showed that this kind of approach is sensitive to the effects of gender, valence and arousal, as well as, the study of inter-hemispherical disparity, as the two brain hemispheres interplay roles in the detailed discrimination of gender. Valence effects are recovered in both the central electrodes as well as in the hemisphere interactions. These findings suggest that the temporal patterns of delta activity and the alterations of delta energy may contribute to the study of emotional processing. Finally the results depict the improved sensitivity of the proposed framework in comparison to the traditional ERP techniques, thereby delineating the need for further development of new methodologies to study slow brain frequencies.

O εγκέφαλος, το μέτρο και το ενόραμα της ζωής που μας δημιουργεί

2009-01-09T01:12:00.003+01:00

To εργαστήριο Ιατρικής Πληροφορικής του Α.Π.Θ. και πιο συγκεκριμένα η Ομάδα Εφαρμοσμένων Νευροεπιστημών σας καλέι την Δευτέρα στις 12.00 μμ να παρακολουθήσετε την διάλεξη από τον κ. Ιωαννίδης Ανδρέα με θέμα "O εγκέφαλος, το μέτρο και το ενόραμα της ζωής που μας δημιουργεί". Η διάλεξη θα λάβει χώρα στην κεντρική βιβλιοθήκη του Α.Π.Θ.

Affective computing in the era of contemporary neurophysiology and health informatics

2008-12-09T01:55:00.002+01:00

Panagiotis D. Bamidis, Christos Papadelis, Chrysoula Kourtidou-Papadeli, Costas Pappas and Ana B. Vivas

Abstract:

This commentary is a response to Interacting with Computers (Vol 14)—[Interacting Comput. 14 (2002) 119], [Interacting with Comput. 14 (2002) 141], [Interacting Comput. 14 (2002) 93]. Its aim is to discuss the role that neurophysiological measurements, such as EEG and MEG, may play in affective computing. The discussion is drawn upon the light of current experience and practice, as well as, advances envisaged in the fields of health informatics, telecommunications and biomedical engineering. It is explained why HCI research into interface evaluation and affective computing may be greatly enhanced by exploiting the underlying information of neurophysiological recordings.

Full Article in here

Quantitative multichannel EEG measure predicting the optimal weaning from ventilator in ICU patients with acute respiratory failure

2008-12-09T01:50:00.003+01:00

Christos Papadelis, Nikos Maglaveras, Chrysoula Kourtidou-Papadeli, Panagiotis Bamidis, Maria Albani, Kyriazis Chatzinikolaou and Konstantinos Pappas

Abstract

Objective

The objective of this study was to develop a novel quantitative multichannel EEG (qEEG) based analysis method, called Global Field Damping Time (GFDT), in order to detect potential EEG changes of patients admitted to the ICU with acute respiratory failure, and correlate them to the patients' recovery outcome predicting the optimal time-point to disconnect the patient from mechanical ventilation.

Methods

Twenty-nine adult patients with acute respiratory failure out of 98 admitted to the Intensive Care Unit of Saint Paul General Hospital were enrolled, and among them only 15 completed the study. The patients were classified in 3 groups according to their outcome after 3 months follow-up. The patients were intubated with fraction of inspired oxygen (FiO₂) of 100%. Neurological Deficit Scores (NDS) were measured 24 h after intubation to assess patients' neurological condition. Twenty-four hours after patient's intubation, FiO₂ was decreased to 40% (weaning session), followed by a 5 min early recovery session, a 5 min recovery 1 session and a 5 min recovery 2 session. EEG recordings were performed during this experimental procedure. Multichannel EEG segments were processed and fitted into a multivariate autoregressive (mAR) model, and single channel EEG segments into a scalar autoregressive (sAR) model. The mAR and the sAR models of arbitrary order p were decomposed into mp and p oscillators and relaxators, respectively. Damping time of each oscillator and each relaxator, and the Global Field Damping Time (GFDT) as a weighted damping time were estimated for both mAR and sAR models.

Results

A statistically significant increase of mAR model's GFDT during the weaning session was observed in the subjects of all groups. Comparing the 3 patients' groups, statistically significant differences for mAR model's GFDT were observed for the weaning and early recovery session. Linear regression analysis between NDS and mean mAR model's GFDT showed statistical significance during weaning session, early recovery session, and recovery 1 session. There was no statistical significance for SaO₂ in the regression analysis with NDS. The sAR model's GFDT presented worst results in comparison with the mAR modelling GFDT in the identification of hypoxic conditions during weaning session and in the discrimination of patients with acute respiratory failure according to their neurological outcome.

Conclusions

Global Field Damping Time as correlated to the patients' neurological outcome appears to be a simple, compact, and substantial novel indicator of cerebral hypoxia and a potential predictor of the optimal time-point to disconnect the patient from the ventilator.

Significance

Quantitative EEG seems to be an important tool for ICU clinicians assisting them to decide for the patients' optimal time-point to disconnect the patient from the ventilator.

Full Article availiable here

Effects of imagery training on cognitive performance and use of physiological measures as an assessment tool of mental effort

2008-12-09T01:47:00.002+01:00

Christos Papadelis, Chrysoula Kourtidou-Papadeli, Panagiotis Bamidis and Maria Albani

Abstract:

The effectiveness of motor imagery training on cognitive performance was examined and the physiological mechanisms involved in the contribution of mental practice to motor learning were considered. The subject’s mental effort during motor imagery was assessed by using psychophysiological measures and particularly eye blink activity as an ‘indirect’ measurement of subjects’ attention. An electronic flight simulation program (Multiple Attribute Task Battery—MATB) was used to assess performance. Twenty healthy volunteers participated in the study divided in two groups: the control group and the imagery-training group. The subjects of the imagery group were asked for additional imagery training. The subjects of the actual performing group were asked additionally to passively observe the task in order to have equal time of exposure to the task. Performance scores and physiological parameters such as heart rate, respiratory rate, eye blinking activity and muscular activity were recorded during all sessions. The results revealed significantly higher performance level of the imagery-training group than the control group. Heart rate and respiratory rate significantly increased during imagery sessions compared to rest. A slight electromyographic activity was observed during the imagination of movement. Our findings support the notion that mental practice improves motor performance in a task where spatiotemporal or dynamic control of the action is highly required. The effects of mental practice on motor performance could be explained by the existence of a top–down mechanism based on the activation of a central representation of the movements, since the vegetative activation during motor imagery seems to be centrally controlled.

Full Article availiable in here

G.A.N. Posters

2008-12-08T11:46:00.006+01:00

Event Related Potentials from Affective Pictures

Emotion Recognition and Oscillatory Patterns for IAPS pictures

Removal of Ocular Artifacts from EEG Signals: A Comparison of Thechniques

SAN & COST TRAINING COURSES & SYMPOSIUM

2008-12-08T11:40:00.001+01:00

SAN & COST TRAINING COURSES & SYMPOSIUM

NEUROFEEDBACK : ADHD

Dubrovnik President Hotel, 15th – 22nd, April, 2009

SAN: Symposium, Neurofeedback, ADHD, 18,19th April

Introduction to Neurofeedback, COST Training School, 15-17th April

Introduction to ADHD, COST Training School, 20-22rd April

The following will depend on demand:

SAN Neurofeedback Education Training Track, 15-17th April

SAN Neurofeedback Clinical Training Track, 20-22nd April

SAN Neurofeedback Training Modules 15-22nd April

The President Hotel will offer special rates for attendees.
COST will offer sponsorship, by application, for COST training schools for young scientists and for continuing education.

Full details together with early bird registration and COST application forms will be posted in October.

More Informations>>

About G.A.N.

2008-12-07T13:29:00.001+01:00

Meet us...Meet the group...

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G.A.N.

Emotion-Aware Natural Interaction

2008-12-06T21:30:00.003+01:00

Rosalind Picard defined affective computing as “computing that relates to, arises from, or deliberately influences emotions.” Along with the more recent introduction of neighboring terms such as “human centered” or “anthropocentric,” “pervasive” and “ubiquitous” computing, computers are no longer deemed as number-crunching machines, but are approached as intelligent and adaptive tools or interfaces within our habitat, helping perform everyday tasks in a more intuitive and yet robust manner. In most cases, paralinguistic concepts such as mood, attitude, traits, and expressivity can adapt the user experience and present flexible and, therefore, more suitable results.

From an engineering point of view, researchers have been investigating different modalities and combinations to provide emotion or affect recognition components. The mapping of raw signals and related features to high-level concepts has been mainly driven from claims such as Ekman's who states that specific facial expressions can be universally recognized across cultures and ages. This claim lends itself well to the existing algorithms which classify content into discrete categories, and as a result pushed the area into creating training and testing data sets containing only the aforementioned expressions. In addition to this, these data sets usually contain cases of extreme expressivity, since these can be distinguished more easily and make it quite difficult to extend. However, everyday human-human and human-computer interactions hardly ever contain cases of extreme expressivity or clear occurrences of expressivity ranging from a neu-tral state to the visual, aural, or physiological apexes of an expression.

The proposed Special Issue aims to present state-of-the-art approaches in the fields of unimodal and multimodal affect analysis, and combine these with techniques that utilize a priori or just-in-time knowledge about the user, environment, or task contexts. Papers on emotion- and affect-aware applications are strongly encouraged, especially those discussing issues related to natural interaction and/or the tradeoff between unconstrained expressivity and robustness.

Topics of interest include, but are not limited to:

* Acoustic and linguistic analysis/feature extraction and recognition
* Visual (face, body, hand) analysis/feature extraction and recognition
* Uni/multimodal recognition/sensing of (blended) emotion, affect, and behavior
* Dynamic, temporal concepts, turn-taking
* Bridging feature extraction and recognition with knowledge sources and context
* Novel modalities for HCI (biosignals, haptics, etc.)
* Affect analysis “in the wild” (e.g., public spaces, groups, etc.)
* Protocols for evaluation of affect-aware systems
* Affect- and emotion-aware applications: design and implementation

Before submission authors should carefully read over the journal'sAuthor Guidelines, which are located at http://www.hindawi.com/journals/ahci/guidelines.html. Authors should follow the Advances in Human-Computer Interaction manuscript format described at the journal site http://www.hindawi.com/journals/ahci/. Prospective authors should submit an electronic copy of their complete manuscript through the Journal Manuscript Tracking System at http://www.hindawi.com/mts/, according to the following timetable:

Manuscript Due April 1, 2009

First Round of Reviews July 1, 2009

Publication Date October 1, 2009

Lead Guest Editor

o Kostas Karpouzis, Institute of Communication and Computer Systems, National Technical University of Athens, 15780 Zographou, Athens, Greece; kkarpou@cs.ntua.gr

Guest Editors

o Elisabeth Andre, Multimedia Concepts and Applications, Institute of Computer Science, University of Augsburg, 86135 Augsburg, Germany; andre@informatik.uni-augsburg.de
o Anton Batliner, Computer Science Department 5, Friedrich Alexander University, Erlangen-Nuremberg, 91058 Erlangen, Germany; batliner@informatik.uni-erlangen.de

Group of Applied Neurosciences

2008-12-06T14:30:00.000+01:00

This is the offcial blog of Group of Applied Neurosciences.

The Group of Applied Neurosciences started the scientific research as a team during 2008. The Group is conducting research on basic and applied neurosciences (both theoretical and experimental), especially the involvement of Information Technology (I.T.) in studying the Human Brain

Area of Interest

IT Applications of Neurosciences and Neurophysiology
Neuroscience and Human Computer Interaction (HCI)
Affective Computing and Emotional Intelligence
EEG/MEG Signal Processing Methods
Independent Component Analysis (ICA) - Blind Source Separation Techniques (BSS) and Artifact Rejection
Intensive Care Unit (ICU) Monitoring
Biosensor Technology (wireless and wearable)
Elderly Care Applications
ADHD, Autism and related Disorders research
Attention and Emotion Studies

Group of Applied Neurosciences

Group of Applied Neurosciences
Lab of Medical Informatics
School of Medicine
Aristotle University of Thessaloniki
P.O. Box 323 54124 Thessaloniki
e-mail: gan.lomi.auth@gmail.com
website: http://lomiweb.med.auth.gr/gan/

Τel: 2310-999332

Fax: 2310-999263

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