Brain rhythms regulate information processing in different states to enable learning and memory formation. The <1 Hz sleep slow oscillation hallmarks slow-wave sleep and is critical to memory consolidation. Here we show in sleeping humans that auditory stimulation in phase with the ongoing rhythmic occurrence of slow oscillation up states profoundly enhances the slow oscillation rhythm, phase-coupled spindle activity, and, consequently, the consolidation of declarative memory. Stimulation out of phase with the ongoing slow oscillation rhythm remained ineffective. Closed-loop in-phase stimulation provides a straight-forward tool to enhance sleep rhythms and their functional efficacy.
A neural network algorithm based on a soft-max adaptation rule is presented. This algorithm exhibits good performance in reaching the optimum minimization of a cost function for vector quantization data compression. The soft-max rule employed is an extension of the standard K-means clustering procedure and takes into account a neighborhood ranking of the reference (weight) vectors. It is shown that the dynamics of the reference (weight) vectors during the input-driven adaptation procedure are determined by the gradient of an energy function whose shape can be modulated through a neighborhood determining parameter and resemble the dynamics of Brownian particles moving in a potential determined by the data point density. The network is used to represent the attractor of the Mackey-Glass equation and to predict the Mackey-Glass time series, with additional local linear mappings for generating output values. The results obtained for the time-series prediction compare favorably with the results achieved by backpropagation and radial basis function networks.
How similar are the eye movement patterns of different subjects when free viewing dynamic natural scenes? We collected a large database of eye movements from 54 subjects on 18 high-resolution videos of outdoor scenes and measured their variability using the Normalized Scanpath Saliency, which we extended to the temporal domain. Even though up to about 80% of subjects looked at the same image region in some video parts, variability usually was much greater. Eye movements on natural movies were then compared with eye movements in several control conditions. "Stop-motion" movies had almost identical semantic content as the original videos but lacked continuous motion. Hollywood action movie trailers were used to probe the upper limit of eye movement coherence that can be achieved by deliberate camera work, scene cuts, etc. In a "repetitive" condition, subjects viewed the same movies ten times each over the course of 2 days. Results show several systematic differences between conditions both for general eye movement parameters such as saccade amplitude and fixation duration and for eye movement variability. Most importantly, eye movements on static images are initially driven by stimulus onset effects and later, more so than on continuous videos, by subject-specific idiosyncrasies; eye movements on Hollywood movies are significantly more coherent than those on natural movies. We conclude that the stimuli types often used in laboratory experiments, static images and professionally cut material, are not very representative of natural viewing behavior. All stimuli and gaze data are publicly available at http://www.inb.uni-luebeck.de/tools-demos/gaze.
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