The structure of frontoparallel haptic space is task dependent

In three experiments, we investigated the structure of frontoparallel haptic space. In the first experiment, we asked blindfolded participants to rotate a matching bar so that it felt parallel to the reference bar, the bars could be at various positions in the frontoparallel plane. Large systematic errors were observed, in which orientations that were perceived to be parallel were not physically parallel. In two subsequent experiments, we investigated the origin of these errors. In Experiment 2, we asked participants to verbally report the orientation of haptically presented bars. In this task, participants made errors that were considerably smaller than those made in Experiment 1. In Experiment 3, we asked participants to set bars in a verbally instructed orientation, and they also made errors significantly smaller than those observed in Experiment 1. The data suggest that the errors in the matching task originate from the transfer of the reference orientation to the matching-bar position

Time-Integrated Position Error Accounts for Sensorimotor Behavior in Time-Constrained Tasks

Several studies have shown that human motor behavior can be successfully described using optimal control theory, which describes behavior by optimizing the trade-off between the subject's effort and performance. This approach predicts that subjects reach the goal exactly at the final time. However, another strategy might be that subjects try to reach the target position well before the final time to avoid the risk of missing the target. To test this, we have investigated whether minimizing the control effort and maximizing the performance is sufficient to describe human motor behavior in time-constrained motor tasks. In addition to the standard model, we postulate a new model which includes an additional cost criterion which penalizes deviations between the position of the effector and the target throughout the trial, forcing arrival on target before the final time. To investigate which model gives the best fit to the data and to see whether that model is generic, we tested both models in two different tasks where subjects used a joystick to steer a ball on a screen to hit a target (first task) or one of two targets (second task) before a final time. Noise of different amplitudes was superimposed on the ball position to investigate the ability of the models to predict motor behavior for different levels of uncertainty. The results show that a cost function representing only a trade-off between effort and accuracy at the end time is insufficient to describe the observed behavior. The new model correctly predicts that subjects steer the ball to the target position well before the final time is reached, which is in agreement with the observed behavior. This result is consistent for all noise amplitudes and for both tasks

Dynamica van het brein

Een van de standaard procedures op een afdeling Klinische Neurofysiologie is het meten van een Elektro-EncefaloGram (EEG). In Nederland worden naar schatting ruim 150-duizend EEG’s per jaar gemaakt om eventuele afwijkingen in hersenfuncties te kunnen vaststellen. Bij een gewone EEG-registratie worden 21 elektroden op de schedel aangebracht, waarmee op de schedelhuid elektrische signalen van ongeveer 10-100 μV gemeten kunnen worden, maar voor sommige indicaties is het aantal elektroden groter dan honder

Modeling Kinematics and Dynamics of Human Arm Movements

A central problem in motor control relates to the coordination of the arm's many degrees of freedom. This problem concerns the many arm postures (kinematics) that correspond to the same hand position in space and the movement trajectories between begin and end position (dynamics) that result in the same arm postures. The aim of this study was to compare the predictions for arm kinematics by various models on human motor control with experimental data and to study the relation between kinematics and dynamics. Goal-directed arm movements were measured in 3-D space toward far and near targets. The results demonstrate that arm postures for a particular target depend on previous arm postures, contradicting Donders's law. The minimum-work and minimumtorque-change models, on the other hand, predict a much larger effect of initial posture than observed. These data suggest that both kinematics and dynamics affect postures and that their relative contribution might depend on instruction and task complexity

The response of a classical Hodgkin–Huxley neuron to an inhibitory input pulse

A population of uncoupled neurons can often be brought close to synchrony by a single strong inhibitory input pulse affecting all neurons equally. This mechanism is thought to underlie some brain rhythms, in particular gamma frequency (30–80 Hz) oscillations in the hippocampus and neocortex. Here we show that synchronization by an inhibitory input pulse often fails for populations of classical Hodgkin–Huxley neurons. Our reasoning suggests that in general, synchronization by inhibitory input pulses can fail when the transition of the target neurons from rest to spiking involves a Hopf bifurcation, especially when inhibition is shunting, not hyperpolarizing. Surprisingly, synchronization is more likely to fail when the inhibitory pulse is stronger or longer-lasting. These findings have potential implications for the question which neurons participate in brain rhythms, in particular in gamma oscillations

Biased competition through variations in amplitude of γ-oscillations

Experiments in visual cortex have shown that the firing rate of a neuron in response to the simultaneous presentation of a preferred and non-preferred stimulus within the receptive field is intermediate between that for the two stimuli alone (stimulus competition). Attention directed to one of the stimuli drives the response towards the response induced by the attended stimulus alone (selective attention). This study shows that a simple feedforward model with fixed synaptic conductance values can reproduce these two phenomena using synchronization in the gamma-frequency range to increase the effective synaptic gain for the responses to the attended stimulus. The performance of the model is robust to changes in the parameter values. The model predicts that the phase locking between presynaptic input and output spikes increases with attention

Validity of TAP equations in neural networks.

Contains fulltext : 112663.pdf (preprint version ) (Open Access)ICAN

Hippocampal theta modulation of neocortical spike times and gamma rhythm: A biophysical model study

Contains fulltext : 103419.pdf (publisher's version ) (Open Access

Gamma oscillations as a mechanism for selective information transmission

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