MS-DOS | EPFL Graph Search

MS-DOS (abréviation de Microsoft Disk Operating System) est le système d'exploitation de type DOS développé par Microsoft pour l'IBM PC d'abord, puis les compatibles PC. Il s'agit d'un système fonctionnant en mode réel, monotâche et mono-utilisateur, et équipé par défaut d'une interface en ligne de commande. Des années 1980 au début des années 1990, il a été le système le plus utilisé sur compatible PC, avant d'être progressivement remplacé par des systèmes d'exploitation plus évolués, notamment Windows. Son développement est maintenant arrêté. Il est encore présent sur les ordinateurs modernes fonctionnant sous Windows via l'invite de commande. Histoire vignette|Écran de démarrage MS-DOS en allemand. Après avoir conclu son « deal » historique avec IBM, Bill Gates s'est mis à la recherche d'un système d'exploitation qu'il pourrait effectivement fournir à IBM pour le lancement de l'IBM PC. Selon lui-même, l'objectif de Microsoft était que MS-DOS soit aussi compatible avec C

The Spike Response Model: A Framework to Predict Neuronal Spike Trains

Wulfram Gerstner, Renaud Jolivet

We propose a simple method to map a generic threshold model, namely the Spike Response Model, to artificial data of neuronal activity using a minimal amount of a priori information. Here, data are generated by a detailed mathematical model of neuronal activity. The model neuron is driven with in-vivo-like current injected, and we test to which extent it is possible to predict the spike train of the detailed neuron model from that of the Spike Response Model. In particular, we look at the number of spikes correctly predicted within a biologically relevant time window. We find that the Spike Response Model achieves prediction of up to

80\%

of the spikes with correct timing (

\pm2

ms). Other characteristics of activity, such as mean rate and coefficient of variation of spike trains, are predicted in the correct range as well.

Springer-Verlag2003

Single trial prediction of self-paced reaching directions from EEG signals

Ricardo Andres Chavarriaga Lozano, Eileen Lew Yi Lee

Early detection of movement intention could possibly minimize the delays in the activation of neuroprosthetic devices. As yet, single trial analysis using non-invasive approaches for understanding such movement preparation remains a challenging task. We studied the feasibility of predicting movement directions in self-paced upper limb center-out reaching tasks, i.e., spontaneous movements executed without an external cue that can better reflect natural motor behavior in humans. We reported results of non-invasive electroencephalography (EEG) recorded from mild stroke patients and able-bodied participants. Previous studies have shown that low frequency EEG oscillations are modulated by the intent to move and therefore, can be decoded prior to the movement execution. Motivated by these results, we investigated whether slow cortical potentials (SCPs) preceding movement onset can be used to classify reaching directions and evaluated the performance using 5-fold cross-validation. For able-bodied subjects, we obtained an average decoding accuracy of 76% (chance level of 25%) at 62.5ms before onset using the amplitude of on-going SCPs with above chance level performances between 875ms to 437.5ms prior to onset. The decoding accuracy for the stroke patients was on average 47% with their paretic arms. Comparison of the decoding accuracy across different frequency ranges (i.e., SCPs, delta, theta, alpha and gamma) yielded the best accuracy using SCPs filtered between 0.1 to 1 Hz. Across all the subjects, including stroke subjects, the best selected features were obtained mostly from the fronto-parietal regions, hence consistent with previous neurophysiological studies on arm reaching tasks. In summary, we concluded that SCPs allow the possibility of single trial decoding of reaching directions at least 312.5ms before onset of reach.

Frontiers Research Foundation2014