No Risk, No Differences. Neural Correlates of Temperamental Traits Revealed Using Naturalistic fMRI Method.

The main goal of this study was to identify the moderating role of temperamental traits, as defined by Strelau's Regulative Theory of Temperament (RTT), in explaining brain activity evoked by video stimuli of varying stimulatory value. fMRI scans were performed in a group of 61 young females in the luteal phase of the menstrual cycle. The validity of stimulus selection had been verified prior to the main study by collecting declarative measures of affective reactions, including valence, arousal, and basic emotions ratings. The choice of dynamic and complex video-stimuli allowed us to induce high levels of arousal effectively. Three categories of movies used in the experiment included neutral, low arousing, and highly arousing scenes. Movies classified into the last category depicted extreme-sport activities allowing us to confront the subjects with recordings potentially life-threatening situations. Results of the study revealed that activation of orbitofrontal cortex in highly arousing conditions is linked to the levels of activity, while traits of perseverance and emotional reactivity were negatively correlated with the BOLD signal in this structure. Low arousing movies evoked higher activation of the amygdala and left hippocampus in emotionally reactive subjects. Obtained results might be coherently interpreted in the light of RTT theory, therefore providing its first validation using functional brain imaging.

Effect of Frustration on Brain Activation Pattern in Subjects with Different Temperament.

In spite of the prevalence of frustration in everyday life, very few neuroimaging studies were focused on this emotional state. In the current study we aimed to examine effects of frustration on brain activity while performing a well-learned task in participants with low and high tolerance for arousal. Prior to the functional magnetic resonance imaging session, the subjects underwent 2 weeks of Braille reading training. Frustration induction was obtained by using a novel highly difficult tactile task based on discrimination of Braille-like raised dots patterns and negative feedback. Effectiveness of this procedure has been confirmed in a pilot study using galvanic skin response and questionnaires. Brain activation pattern during tactile discrimination task before and after frustration were compared directly. Results revealed changes in brain activity in structures mostly reported in acute stress studies: striatum, cingulate cortex, insula, middle frontal gyrus and precuneus and in structures engaged in tactile Braille discrimination: SI and SII. Temperament type affected activation pattern. Subjects with low tolerance for arousal showed higher activation in the posterior cingulate gyrus, precuneus, and inferior parietal lobule than high reactivity group. Even though performance in the discrimination trials following frustration was unaltered, we observed increased activity of primary and secondary somatosensory cortex processing the tactile information. We interpret this effect as an indicator of additional involvement required to counteract the effects of frustration.

Towards an optimization of stimulus parameters for brain-computer interfaces based on steady state visual evoked potentials.

Efforts to construct an effective brain-computer interface (BCI) system based on Steady State Visual Evoked Potentials (SSVEP) commonly focus on sophisticated mathematical methods for data analysis. The role of different stimulus features in evoking strong SSVEP is less often considered and the knowledge on the optimal stimulus properties is still fragmentary. The goal of this study was to provide insight into the influence of stimulus characteristics on the magnitude of SSVEP response. Five stimuli parameters were tested: size, distance, colour, shape, and presence of a fixation point in the middle of each flickering field. The stimuli were presented on four squares on LCD screen, with each square highlighted by LEDs flickering with different frequencies. Brighter colours and larger dimensions of flickering fields resulted in a significantly stronger SSVEP response. The distance between stimulation fields and the presence or absence of the fixation point had no significant effect on the response. Contrary to a popular belief, these results suggest that absence of the fixation point does not reduce the magnitude of SSVEP response. However, some parameters of the stimuli such as colour and the size of the flickering field play an important role in evoking SSVEP response, which indicates that stimuli rendering is an important factor in building effective SSVEP based BCI systems.

On the quantification of SSVEP frequency responses in human EEG in realistic BCI conditions.

This article concerns one of the most important problems of brain-computer interfaces (BCI) based on Steady State Visual Evoked Potentials (SSVEP), that is the selection of the a-priori most suitable frequencies for stimulation. Previous works related to this problem were done either with measuring systems that have little in common with actual BCI systems (e.g., single flashing LED) or were presented on a small number of subjects, or the tested frequency range did not cover a broad spectrum. Their results indicate a strong SSVEP response around 10 Hz, in the range 13-25 Hz, and at high frequencies in the band of 40-60 Hz. In the case of BCI interfaces, stimulation with frequencies from various ranges are used. The frequencies are often adapted for each user separately. The selection of these frequencies, however, was not yet justified in quantitative group-level study with proper statistical account for inter-subject variability. The aim of this study is to determine the SSVEP response curve, that is, the magnitude of the evoked signal as a function of frequency. The SSVEP response was induced in conditions as close as possible to the actual BCI system, using a wide range of frequencies (5-30 Hz, in step of 1 Hz). The data were obtained for 10 subjects. SSVEP curves for individual subjects and the population curve was determined. Statistical analysis were conducted both on the level of individual subjects and for the group. The main result of the study is the identification of the optimal range of frequencies, which is 12-18 Hz, for the registration of SSVEP phenomena. The applied criterion of optimality was: to find the largest contiguous range of frequencies yielding the strong and constant-level SSVEP response.