Neurophysiological mechanisms underlying the distinction between automatic and controlled processes.

Automatic processes are fast, effortless, mostly unconscious, take very little capacity and are slowly changing. Controlled processes are much slower, require effort and attention, require capacity, are closely tied to consciousness but provide high behavioral adaptivity in unfamiliar situations. Because this distinction is fundamental for virtually all aspects of human cognition it is important to understand the difference in the neurophysiological mechanisms that underlie these two aspects of cognition. Through computer simulations we show that the neural computations that rely on oscillatory and synchronous neural activity share several fundamental properties with controlled processes. By accounting for several experiments that first established the distinction between automatic and controlled processes in visual perception, we show that synchrony-based computations observe limitations in capacity and that processing time depends on the task complexity. We also show that synchrony-based computations have an ability to handle new, not previously encountered computations. Finally, we show that a learning mechanism that employs synchrony-sensitive changes of synaptic efficacy provides a good tool for developing automaticity. In other words, the system learns to develop synchronous patterns faster and more reliably and thus increases the speed and accuracy and decrease the demands on limited attentional resources. In sum, controlled cognitive processes seem to rely heavily on synchronous neural activity while automatic processes seem to employ synchrony-based computations to a far lesser degree

Quickly fading afterimages: hierarchical adaptations in human perception

Afterimages result from a prolonged exposure to still visual stimuli. They are best detectable when viewed against uniform backgrounds and can persist for multiple seconds. Consequently, the dynamics of afterimages appears to be slow by their very nature. To the contrary, we report here that about 50% of an afterimage intensity can be erased rapidly--within less than a second. The prerequisite is that subjects view a rich visual content to erase the afterimage; fast erasure of afterimages does not occur if subjects view a blank screen. Moreover, we find evidence that fast removal of afterimages is a skill learned with practice as our subjects were always more effective in cleaning up afterimages in later parts of the experiment. These results can be explained by a tri-level hierarchy of adaptive mechanisms, as has been proposed by the theory of practopoiesis.Comment: 3 pages, 3 figure

Hemodinamika femoro-poplitealne by-pass hirurgije metodom analize konačnih elemenata

Objective. Femoropopliteal bypass is indicated in the advanced stage of peripheral arterial occlusive disease. The indications for surgical treatment are determined on the basis of a clinical exam, "ankle-brachial index" and angiographic findings. Using the finite element analysis method, three-dimensional models can be made based on angiography, and these models can be used to measure different physical quantities and calculate the value of the "ankle-brachial index". The aim of this paper is to show the hemodynamics of arteries by using the finite element analysis method based on preoperative and postoperative angiography, as well as physical quantities that can be measured in this way. Methods. This case shows the hemodynamics of femoropopliteal bypass in the preoperative and postoperative models. The models obtained by finite element analysis show: pressure, shear stress, velocities, and streamlines. The pressure, i.e. the "ankle-brachial index", was compared with the values measured on the patient, while the other three values were compared preoperatively and postoperatively. Results. Postoperatively, higher values of pressure and "ankle-brachial index" were measured on the patient and on the models. Wall shear stress and velocity values were reduced in postoperative models. The streamlines showed a dominant anterior tibial artery. Conclusion. The values of physical quantities measured on patient and on the models obtained by the finite element analysis method correlate significantly. Some physical quantities could indicate the "weak points" of a particular model.Publishe