Wyniki wyszukiwania - Biblioteka Nauki

1

General intelligence and temporal control of motor tasks

100%

Dreszer J. , Szelag E. , Osinski G. , Gorski D.

Acta Neurobiologiae Experimentalis

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2007

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tom 67

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nr 3

2

Dynamical proprieties of "internal clock" as neural basis of individual differences in the level of intelligence

100%

Dreszer J. , Szelag E. , Osinski G.

Acta Neurobiologiae Experimentalis

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2009

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tom 69

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nr 3

EN

Neuropsychological evidence has suggested that both intelligence and temporal resolution in information processing may be determined by similar neural mechanisms, related to internal timing mechanism. Personal tapping tempo (PTT) can be considered as a promising measure of such “internal clock” properties, as it refl ects spontaneous tempo in human motor activity. As the existing studies do not provide detailed description of temporal characteristics of PTT, conclusions on temporal control underling timing and intelligence are still not clear. The present study investigated in 55 highly intelligent and 50 average intelligent students dynamical properties of temporal control of repetitive fi nger movements in PTT. Nonlinear elements for reconstruction of dynamical properties of PTT were performed. We found fractal properties of tapping performance. Additionally, advanced mathematical analyzes showed grouping in frequencies of PTT, which constituted characteristic optima of subjects’ performance. In these optima intelligence-related differences were revealed. These fi ndings supported the notion that ’internal clock system’ in the brain could be fractal in its nature which has a different structure in highly and average intelligent individuals. The study was supported by Grant N N106 109636 from Ministry of National Education and Science.

3

Cognitive robots in the development and rehabilitation of children with developmental disorders

88%

Komendziński T. , Mikołajewska E. , Mikołajewski D. , Dreszer J. , Bałaj B.

Bio-Algorithms and Med-Systems

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2016

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tom Vol. 12, no. 3

93--98

EN

Cognitive robots constitute a highly interdisciplinary approach to the issue of therapy of children with developmental disorders. Cognitive robots become more popular, especially in action and language integration areas, joining the experience of psychologists, neuroscientists, philosophers, and even engineers. The concept of a robot as a cognitive companion for humans may be very useful. The interaction between humans and cognitive robots may be a mediator of movement patterns, learning behaviors from demonstrations, group activities, and social behaviors, as far as higher-order concepts such as symbol manipulation capabilities, words acquisition, and sensorimotor knowledge organization. Moreover there is an occupation to check many theories, such as transferring the knowledge and skills between humans and robots. Although several robotic solutions for children have been proposed the diffusion of aforementioned ideas is still limited. The review summarizes the current.

4

Role of the music therapy in neurorehabilitation of patients with disorders of consciousness – looking for rules of evidence based practice

88%

Komendziński T. , Mikołajewska E. , Mikołajewski D. , Dreszer J. , Bałaj B.

Progress in Health Sciences

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2016

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tom 6(2)

21-28

EN

Neurological early and long-term rehabilitation plays a crucial role in the therapy of patients with disorders of consciousness (DOC) such as unresponsive wakefulness syndrome or minimally conscious state. Neuroscience tries to explain the effect of music therapy on all levels of the nervous system = activity in patients with DOC, but full understanding is still incomplete. This paper attempts to answer how current clinical outcomes may reflect the influence of various factors including music's capacity. Based on their interdisciplinary perspective and previous experiences, the authors try to investigate the extent to which current occupations have been explored. The authors analyzed the literature data concerning the results of the studies published until the first half of 2016, to sum up the current state of research. Research in the main databases: PubMed, PEDro, Health Source: Nursing/Academic Edition was made using specified keywords and inclusion and exclusion criteria. Next, the authors sorted them all out into a coherent view of the current state. Music listening may constitute a part of an enriched environment setting. However, due to weak evidence, the therapeutic value of music-based interventions in patients with DOC is uneven or limited. The role of music therapy is thus complementary. Standardized clinical settings, protocols, and behavioral measures should be developed to increase its clinical validity, reliability, sensitivity, and objectivity. There is a reasonable hypothesis that music may produce a high level of diagnostic and therapeutic outcomes as stimuli usually reflecting strong personal meaning in patients with DOC.

5

EEG spectral fingerprints as a method for classifying different regions of the human brain - initial results

75%

Komorowski M. , Wojciechowski J. , Nikadon J. , Piotrowski T. , Dreszer J. , Duch W.

Acta Neurobiologiae Experimentalis

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2018

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tom 78

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nr Suppl.1

EN

During rest different brain structures are connected into distinguishable networks. Each region of interest (ROI) tends to preserve its own natural frequency. A long term goal of our team is to develop a reliable method which al‑ lows us to access milliseconds-level dynamic features of brain networks from EEG signal, so called EEG brain finger‑ print. In 2016, Dr. Anne Keitel and Professor Joachim Gross proposed a method of clustering each ROI MEG source-re‑ constructed activity. 116 ROIs were selected according to the Automated Anatomic Labeling Atlas. As a result, they obtained a group-level spectral representation (referred to as “spectral fingerprints”) of dynamic behavior of the hu‑ man cortex and deep sources. It turned out that spectral fingerprint representation enables accurate ROI classifica‑ tions. Moreover, using only functional data, the algorithm linked ROIs to clusters that correspond well to large-scale anatomical parcellations of the cortex. We have recreat‑ ed and adapted this method to analyse resting-state EEG signal. We tested this approach on resting-state EEG data and compared with original results obtained on MEG data. Results show that, despite the difficulty of differentiating between ROIs using EEG data, performance was well above the chance level. Each ROI EEG activity was characterized by fewer numbers of clusters than ROI MEG activity and ROI similarities formed less clear images of brain networks. Nevertheless, the method is still promising and further de‑ velopment could lead us to identify new and reliable tools useful in scientific and clinical practice.