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The MindWave is a commercial EEG device and a second-generation BCI headset. Its producer NeuroSky claims the device measures and secondly can be used to enhance attention and concentration through biofeedback training. The MindWave is also frequently advertised as a ready-for-research utility. However, not a lot of independent research paradigms seem to have investigated the claims of the NeuroSky Company. Can the device really measure attention by means of a single frontal sensor? And secondly, does the MindWave provide the opportunity to actually improve attention? In this study we primarily focused on the validation of the MindWave device as a measurement tool for attention. The study also investigated the possible enhancement of attention by means of the MindWave device. Several validated psychological tests measuring attention were compared with measurements provided by the MindWave to establish concurrent validity. A sample of 61 participants ran through the constructed test battery, which included the ZVAH, IRT, FDS and d2. In between the psychological tasks and questionnaire, the participants were introduced to the MindWave by playing three sessions of the Blink/Zone, a game provided with the purchase of the MindWave. Additionally, the MindWave was used to collect a measure of attention during the FDS. We found that attention as measured by the MindWave decreased with the addition of more digits during the FDS. Nevertheless, this relation explained only a small part of the overall variability in attention measures. In addition, we found that the scores linked to attention during the Blink/Zone game did not increase over the three sessions. Moreover, the relation with well-validated psychological tests was typically poor. Together, these results do not offer much validation for the MindWave as a consistent measurement tool for attention. These outcomes were in part explained by the chosen research paradigm.

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Categorization is a cognitive process or skill found in both humans and animals. It allows us to simplify and structure our environment. This is necessary to survive in a world that is never exactly the same. After all, where would we be, if we could not distinguish predator from prey? We master this skill very well and often categorize without any conscious thought. However, despite its crucial role for our survival and despite much extensive research on this topic, many questions about categorization still remain. A behavioural animal model would allow a more detailed investigation of neural basis of categorization. We conducted a pilot study to develop such a behavioural animal model. In this study 24 rats were trained in a visual water task. The animals were trained to categorize sine-wave gratings into artificially created categories, by focusing either on the orientation of the sine-wave gratings or the direction of movement. The knowledge that could be derived from this was also applied on new, unseen stimuli. After the behavioural task, a neurobiological analyses was done on the visual cortex (striate and extrastriate) and the prefrontal cortex. The activation in these two regions was mapped and compared between the different conditions. We were interested in both the behavioural and neurobiological effects resulting from training in this task. Would the rats be able to learn the artificial categories and generalize this knowledge to new, unseen stimuli? Which resulting activation could be observed in the neurobiological analysis? Would there be differences between the conditions based on manipulations of the stimuli? The rats were able to learn the behavioural task in both conditions, but the animals showed a preference for orientation over direction of movement. Activity in the visual cortex was found for all animals, but there were also differences between the conditions. These could be due to the nature of the stimuli. The prefrontal activation seemed to correspond to the position of the subject in the learning curve.

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Memory alters the way humans perceive, behave and predict and are thus essential processes to survive in an ever-changing environment. During memorization, a process of learning occurs which is accompanied by its underlying process of neuroplasticity. Hereby refers the concept of Long-Term Potentiation (LTP) to a strengthened connection and Long-Term Depression (LTD) to a weakened connection between synapses. Research showed that passive visual stimulation with low-level stimuli can evoke a comparable learning effect within visual guided behaviour. Applying the stimulation protocol with a slightly adapted paradigm to high-level stimuli (faces) a short-term frequency-dependent effect was found but no long-term effect (one hour). In this paper, the same slightly adapted paradigm had been used, but with low-level stimuli (bars). We investigated the long-term effect of the frequency-dependent stimulation on a change-detection task. Fundamental research demonstrated long-term effects of a frequency-dependent stimulation in a change-detection task with low-level stimuli. Therefore, in our paper it is questioned, if either the frequency-dependent effect of passive stimulation is limited to low-level stimuli or if the slightly adapted paradigm in our laboratory is suboptim attempted to understand the critical factors to induce long-term LTD/LTP-like effects through visual stimulation. We applied a change-detection task before and after a passive stimulation protocol and a one-hour break, to test for potential long-term changes in visual guided performance. During the change-detection task the participants had to indicate on which side of the screen a luminance change (relevant change) of the two presented bars occurred. The visual stimulation was either a 10 Hz LTP-like high-frequency stimulation, a 20 Hz LTP-like high-frequency stimulation or a 1 Hz LTD-like low-frequency stimulation for the relevant change of the stimuli; alongside a control group. Moreover, questionnaires were enclosed to measure several personality and physiological features of the participants and their possible influences on the learning effect. A positive correlation towards sleep quality had been found. The long-term effect of LTP-/LTD-like stimulation could not be replicated for low-level stimuli. It can be assumed that the paradigm of the studies conducted in our laboratory was suboptimal and consequently no long-term effects could be found. Since no frequency-dependent long-term effect through passive visual stimulation with low-level and high-level stimuli had been found in our laboratory, future research should focus on the detection of its critical factors. In case of a well-defined paradigm, it could have far-reaching possibilities for clinical interventions (e.g. to improve or impair specific parts of face processing in clinical populations). It could be applied in a wide range of therapeutic settings, mainly due to its simple implementation and the passive role of the patient.

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Worldwide, roughly one in twenty human beings experience difficulties solving basic arithmetic problems. These people are diagnosed with developmental dyscalculia, and it is hypothesized that their calculation difficulties originate from an impairment in processing numerical quantities. However, it is not entirely clear which deficit at the level of the brain gives rise to the arithmetic impairment. Some theoretical proposals focus upon a difference in precision of underlying neural representations of symbolic (e.g. Arabic digits) and non-symbolic (e.g. dots) number magnitudes in the intraparietal sulcus (IPS). However, there is very little agreement on whether both formats or only one format is impaired in individuals with dyscalculia. This inconsistency is largely due to less direct analyses. In particular, several previous studies applied univariate fMRI analyses (i.e. contrast mean activation between two groups in brain regions), which in turn were not able to pinpoint differences in spatial patterns. Accordingly, this dissertation contrasted the neural underpinnings of symbolic and non-symbolic numerical magnitudes between adults with and without dyscalculia, by means of multi-voxel pattern analysis (MVPA). MVPA is a machine learning analysis by which we can directly test how distinct underlying number magnitudes are in the brain regions of interest. This study comprised a behavioural and a neuroimaging session. Throughout the first session, the participants' mathematical and reading performance was assessed to ascertain whether both groups only differed by means of mathematical performance. Additionally, a diagnostic interview was conducted to confirm whether a participant belonged to the dyscalculia or control group. Lastly, participants completed a number comparison task to determine the underlying precision of numerical representations, at the behavioural level. For the second session, participants performed a number comparison task during a fMRI scan session to determine the neural underpinnings of numerical cognition. To summarize the results of this study, behavioural results showed slower reaction times and decreased accuracy scores in individuals with dyscalculia, irrespective of the format. In line with this, neuroimaging findings did reveal less precise non-symbolic neural representations in adults with dyscalculia in the IPS. There is a clear connection between behavioural number comparison performance and neuroimaging findings: an impaired numerical comparison performance is associated with fewer neural precision in the IPS.