Evidence for vibration coding of sliding tactile textures in auditory cortex.

Introduction: Psychophysical studies suggest texture perception is mediated by spatial and vibration codes (duplex theory). Vibration coding, driven by relative motion between digit and stimulus, is involved in the perception of very fine gratings whereas coarse texture perception depends more on spatial coding, which does not require relative motion. Methods: We examined cortical activation, using functional Magnetic Resonance Imaging associated with fine and coarse tactile spatial gratings applied by sliding or touching (sliding vs. static contact) on the index finger pad. Results: We found regions, contralateral to the stimulated digit, in BA1 in S1, OP1, OP3, and OP4 in S2, and in auditory cortex, which were significantly more activated by sliding gratings but did not find this pattern in visual cortex. Regions in brain areas activated by vibrotactile stimuli (including auditory cortex) were also modulated by whether or not the gratings moved. In a control study we showed that this contrast persisted when the salience of the static condition was increased by using a double touch. Discussion: These findings suggest that vibration from sliding touch invokes multisensory cortical mechanisms in tactile processing of roughness. However, we did not find evidence of a separate visual region activated by static touch nor was there a dissociation between cortical response to fine vs. coarse gratings as might have been expected from duplex theory.

Intelligent model-based advisory system for the management of ventilated intensive care patients. Part II: Advisory system design and evaluation.

The optimisation of ventilatory support is a crucial issue for the management of respiratory failure in critically ill patients, aiming at improving gas exchange while preventing ventilator-induced dysfunction of the respiratory system. Clinicians often rely on their knowledge/experience and regular observation of the patient's response for adjusting the level of respiratory support. Using a similar data-driven decision-making methodology, an adaptive model-based advisory system has been designed for the clinical monitoring and management of mechanically ventilated patients. The hybrid blood gas patient model SOPAVent developed in Part I of this paper and validated against clinical data for a range of patients lung abnormalities is embedded into the advisory system to predict continuously and non-invasively the patient's respiratory response to changes in the ventilator settings. The choice of appropriate ventilator settings involves finding a balance among a selection of fundamentally competing therapeutic decisions. The design approach used here is based on a goal-directed multi-objective optimisation strategy to determine the optimal ventilator settings that effectively restore gas exchange and promote improved patient's clinical conditions. As an initial step to its clinical validation, the advisory system's closed-loop stability and performance have been assessed in a series of simulations scenarios reconstructed from real ICU patients data. The results show that the designed advisory system can generate good ventilator-setting advice under patient state changes and competing ventilator management targets.

Robust emergence of small-world structure in networks of spiking neurons.

Spontaneous activity in biological neural networks shows patterns of dynamic synchronization. We propose that these patterns support the formation of a small-world structure-network connectivity optimal for distributed information processing. We present numerical simulations with connected Hindmarsh-Rose neurons in which, starting from random connection distributions, small-world networks evolve as a result of applying an adaptive rewiring rule. The rule connects pairs of neurons that tend fire in synchrony, and disconnects ones that fail to synchronize. Repeated application of the rule leads to small-world structures. This mechanism is robustly observed for bursting and irregular firing regimes.

Time-based prediction in motor control: evidence from grip force response to external load perturbations.

An object held in precision grip creates predictable load forces on the hand during voluntary hand movement and these are associated with anticipatory modulation of grip force. Conflicting results have been obtained over whether predictable external load perturbations result in anticipatory grip force responses (e.g. Blakemore et al. in J Neurosci 18(18):7511-7518, 1998; Weeks et al. in Exp Brain Res 132:404-410, 2000). This paper investigated whether the discrepancies reflect differences in the methods used in estimating the time delay. Subjects held a manipulandum that delivered load force perturbations in the form of pulses of variable duration and interval or periodic 0.5 and 1 Hz square waves or sinusoids. The grip forces exerted by the subjects were measured. Two methods were used to assess the time delay of the grip force in relation to the load force: (1) cross-spectral analysis, (2) a single threshold method applied on time-locked averaged data. Despite a phase lag shown by the cross-spectral analysis, the threshold method revealed grip force increased 264.8+/-40.2 ms before the onset of the load force when 0.5 Hz square waves were used as the load force perturbation and 70.2+/-17.0 ms before the load force when 1 Hz square waves were used. Computer simulations indicated that the single threshold method gives a more sensitive estimate of the onset time than the cross-spectral analysis. We conclude that discrepancies in previous studies reflect differences in the methods used to assess the time-delay and that there is an anticipatory component in the grip force response to predictable external load perturbation.

Neurophysiology of implicit timing in serial choice reaction-time performance.

Neural representations of time for the judgment of temporal durations are reflected in electroencephalographic (EEG) slow brain potentials, as established in time production and perception tasks. Here, we investigated whether anticipatory processes in reaction-time procedures are governed by similar mechanisms of interval timing. We used a choice reaction task with two different, temporally regular stimulus presentation regimes, both with occasional deviant interstimulus intervals. Temporal preparation was shown in the form of adjustments in time course of slow brain potentials, such that they reached their maximum amplitude just before a new trial, independent of the duration of the interstimulus interval. Preparation was focused on a brief time window, demonstrated by a drop in amplitude of slow potentials as the standard interval had elapsed in deviant interstimulus intervals. Implicit timing influencing perceptual processing was shown in reduced visual-evoked responses to delayed stimuli after a deviant interstimulus interval and in a reduction of EEG alpha power over the visual cortex at the time when the standard interval had elapsed. In contrast to explicit timing tasks, the slow brain potential manifestations of implicit timing originated in the lateral instead of the medial premotor cortex. Together, the results show that temporal regularities set up a narrow time window of motor and sensory attention, demonstrating the operation of interval timing in reaction time performance. The divergence in slow brain potential distribution between implicit and explicit timing tasks suggests that interval timing for different behaviors relies on qualitatively similar mechanisms implemented in distinct cortical substrates.

SIVA: a hybrid knowledge-and-model-based advisory system for intensive care ventilators.

The Sheffield Intelligent Ventilator Advisor is a hybrid knowledge-and-model-based advisory system designed for intensive care ventilator management. It consists of a top-level fuzzy rule-based module to give the qualitative component of the advice, and a lower-level model-based module to give the quantitative component of the advice. It is structured to offer adaptive patient-specific decision support. It can be operated in either invasive or noninvasive modes depending on the availability of data from invasive clinical measurements. The user can choose between the full-advisory mode and the clinician-directed mode. The advice given by the top-level module has been validated against retrospective real patient data and compared with intensivists expertise and performance under simulation conditions. Closed-loop simulations were performed assuming various clinical scenarios including sudden changes in the patient parameters such as the shunt or deadspace with noise and disturbances. They have shown that the advice given was appropriate and the blood gases resulting from the closed-loop decision support were acceptable. The system was also shown to be tolerant to noise and disturbances. It is implemented in MATLAB/SIMULINK and LabVIEW.