NCA changes our perspectives on emotional processing

Brain systems supporting the processing of emotion involve deep brain structures (amygdala, thalamus, insula, anterior cingulate cortex, and cerebellum) and fairly superficial cortical areas (prefrontal cortex, temporal and visual cortices). The cerebellum is a recent addition to our view of the emotion-related distributed circuitry. NCA’s very recent findings provide for the first time the temporal component of emotional processing within the cerebellum. It is indicated that: (i) arousal, valence, and their interaction are processed in parallel within anatomically distinct cerebellar lobules, (ii) these processes unfold at well-defined latencies relative to stimulus onset following a temporal hierarchy, and (iii) cerebellar responses are organized into an early prioritization of high arousal, followed by an unpleasant valence effect, and later a pleasant valence by high arousal interaction (Styliadis et al., 2015a).

Distinct cerebellar lobules process arousal, valence and their interaction in parallel following a temporal hierarchy (Styliadis et al., 2015a)

NCA’s research focuses on understanding the functions of the individual amygdala sub-divisions by unmasking their contributions to the processing of valence, arousal or their interaction effect. The results reveal contrasting though parallel roles for laterobasal (LB) and centromedial (CM) sub-divisions of human amygdala in mediating the effects of unpleasant stimuli and for interweaving the effects of pleasure by high arousal respectively. It is indicated that there exists a distinct functional specificity of amygdala anatomical sub-divisions in the emotional processing (Styliadis et al., 2014).

Amygdala responses to valence and its interaction by arousal (Styliadis et al., 2014)

NCA’s research demonstrates evidence for gender differences in the way pleasant and unpleasant stimuli of high and low arousal are processed. Females show greater negativity than males on negative components (N100 and N200) upon viewing emotional stimuli. This effect is further modulated by a gender by valence interaction on the N100 of Pz electrode; females exhibit greater negativity than males but only for the unpleasant stimuli. Arousal effects are observed early on in the processing (N100) on frontal and central electrodes, and these effects are also modulated by gender; high arousing pictures evoke more negative response in females as compared to males (Lithari et al., 2010).

Gender differences across arousal and valence dimensions (Lithari et al., 2010)

NCA develops a hybrid methodology for the rejection of ocular artifacts

The NCA team proposes a hybrid methodology that combines the main advantages of regression and Blind Source Separation (BSS) techniques for rejecting ocular artifacts from electroencephalographic (EEG) and magnetoencephalographic (MEG) signals. Given that the artifactual independent components (ICs) extracted by a BSS method include more ocular and less cerebral activity than the contaminated EEG signals, a regression algorithm is applied to the ICs rather than directly to the recorded signals. The performance of the proposed technique was compared with two automatic techniques; a regression technique based on Least Mean Square (LMS) algorithm and a BSS-based artifact rejection technique called wavelet-ICA (W-ICA) on the artificially contaminated data. For comparison, two metrics were used to assess the different methods’ performance: the first quantified how successful each technique was in removing the ocular artifacts from the EEG recordings, and the second one quantified how much each technique distorted the ongoing brain activity in both time and frequency domains. Confirming our main hypothesis, results have shown that the artifactual ICs contained more ocular and less cerebral activity (p < 0.04) (artifact to signal ratio (ASR) = 1.83 ± 3.65) in contrast to the contaminated electrode signals (ASR = 0.69 ± 3.40). Our results reveal that NCA’s REG-ICA removes the ocular artifacts more successfully than the BSS-based artifact rejection technique called wavelet-ICA (W-ICA) (p < 0.01) or the regression technique based on Least Mean Square (LMS) algorithm (p < 0.01). It also distorts less the brain activity in the time domain when compared to W-ICA and LMS. In the frequency domain, it distorts the brain activity less than the W-ICA in all frequency bands, and less than the LMS for the delta, beta, and gamma bands.

REG-ICA: A hybrid methodology combining Blind Source Separation and regression techniques for the rejection of ocular artifacts (Klados et al., 2011)

NCA implements a framework for emotional detection

The NCA team proposes a novel architecture for the robust discrimination of emotional physiological signals evoked upon viewing pictures selected from the International Affective Picture System (IAPS). The emotion detection is performed through neurophysiological sensing (electroencephalographic, (EEG) & skin conductance responses, (SCR)). The valence-arousal emotional theory that derives from evolutionary processes is employed. The emotion detection is performed through data mining (decision trees) and pattern recognition techniques (Mahalanobis distance classifier). The results are encouraging since the proposed framework detects four emotional states (in terms of high/low valence/arousal) with recognition rate reaching 77.68%. Results are described in terms of Extensible Markup Language (XML) format towards the facilitation of platform independency, easy interconnectivity and information exchange (Frantzidis et al., 2010a).

The aforementioned architecture is further extended regarding its emotion recognition accuracy by employing gender-specific analysis and contemporary pattern recognition techniques such as Support Vector Machines (SVMs). The improved recognition rate reached 81.3%, which may facilitate numerous applications within the sphere of human-computer interaction.

Toward Emotion Aware Computing: An Integrated Approach Using Multichannel Neurophysiological Recordings and Affective Visual Stimuli (Frantzidis et al., 2010b).

NCA investigates lifelong development, not just old age

NCA’s research takes a lifespan perspective to understand the way the brain develops across the adult lifespan in order to preserve cognitive function and emotional wellbeing and age healthily. Intervention schemes of combined physical and cognitive training as well as unobtrusive monitoring in our Active and Health Aging Living Lab/e-home offer a great way to investigate the everyday cognitive abilities (memory, attention, emotion, and action) that enable individuals to function efficiently as well as understand how these abilities can be retained into old age. This research includes participants across the adult lifespan; young (18-39 years old), middle-life (40-59 years old), and elderly (60+) individuals.

NCA’s very recent research demonstrates that after an eight-week long intervention of combined physical activity and cognitive training a resting state change of EEG showing that: (i) combined training significantly decreases delta, theta and beta rhythms, (ii) PCu/PCC activity decrease implies functional plasticity, (iii) the greater the delta and theta decrease of activity the higher the improvement in the MMSE, (iv) short-term interventions of both physical and cognitive training can significantly tap into brain plasticity, and (v) physical activity may play a crucial role in transferring the combined training effects (Styliadis et al., 2015b).

Neuroplastic effects of combined computerized physical and cognitive training in MCI individuals (Styliadis et al., 2015b)

Regarding neuropathology of aging, the NCA team approaches healthy and pathological aging from the perspective of an altered co-operative capacity between neuronal populations. This also opens the door for neuroplasticity-based training through coherent interaction between distant brain regions and concomitantly improving cognition. This study posits that in order to assess the efficacy of potential interventions neurophysiological synchronization is a valid outcome index. Towards this purpose, an objective, synchronization-based tool (Relative Wavelet Entropy) is proposed in the form of a parameter-free synchronization metric. Empirical support was forthcoming from an elderly group receiving combined physical and cognitive training when compared with an active control intervention group. This is a first demonstration of enhanced function in the elderly with a synchronization outcome measure (Frantzidis et al., 2014a).

A recent work of the NCA group employs brain network analysis in order to investigate whether functional disorganization is already evident in the aMCI phase and if the network architecture could be correlated with cognitive functioning. The study also investigates the existence of compensatory mechanisms that occur prior to the onset of the clinical dementia phase.

Functional disorganization of small-world brain networks in mild Alzheimer’s disease (MD) and aMCI (Frantzidis et al., 2014b).

NCA reveals a cortical response identifying abstract audiovisual incongruences, extending the MMN in other modalities

Research conducted by NCA reveals that a fronto-temporal network of sources generates an audiovisual incongruency response with similar characteristics as the Mismatch Negativity (MMN). This response is generated when the judgment regarding the congruency (or incongruency) of the stimuli does not rely on physical characteristics of the stimulation, such as temporal synchronization, but on an abstract convention such as the rule behind musical reading: “the higher the pitch of the tone, the higher the position of the circle”. In addition, cross-sectional studies using musicians and non-musicians, as well as short-term training studies conducted by members of NCA, indicate that musical expertise induces neuroplastic changes of multisensory nature in the frontal pole that are functionally related with the identification of abstract audiovisual incongruences (Paraskevopoulos et al., 2014).

Cortical responses underlying magnitude comparisons of multisensory stimuli and the effect of musical training (Paraskevopoulos et al., 2014)