Intermittent spike-wave dynamics in a heterogeneous, spatially extended neural mass model

Generalised epileptic seizures are frequently accompanied by sudden, reversible transitions from low amplitude, irregular background activity to high amplitude, regular spike-wave discharges (SWD) in the EEG. The underlying mechanisms responsible for SWD generation and for the apparently spontaneous transitions to SWD and back again are still not fully understood. Specifically, the role of spatial cortico-cortical interactions in ictogenesis is not well studied. We present a macroscopic, neural mass model of a cortical column which includes two distinct time scales of inhibition. This model can produce both an oscillatory background and a pathological SWD rhythm. We demonstrate that coupling two of these cortical columns can lead to a bistability between out-of-phase, low amplitude background dynamics and in-phase, high amplitude SWD activity. Stimuli can cause state-dependent transitions from background into SWD. In an extended local area of cortex, spatial heterogeneities in a model parameter can lead to spontaneous reversible transitions from a desynchronised background to synchronous SWD due to intermittency. The deterministic model is therefore capable of producing absence seizure-like events without any time dependent adjustment of model parameters. The emergence of such mechanisms due to spatial coupling demonstrates the importance of spatial interactions in modelling ictal dynamics, and in the study of ictogenesis.

Cortical local and long-range synchronization interplay in human absence seizure initiation

Brain activity relies on transient, fluctuating interactions between segregated neuronal populations. Synchronization within a single and between distributed neuronal clusters reflects the dynamics of these cooperative patterns. Thus absence epilepsy can be used as a model for integrated, large-scale investigation of the emergence of pathological collective dynamics in the brain. Indeed, spike-wave discharges (SWD) of an absence seizure are thought to reflect abnormal cortical hypersynchronization. In this paper, we address two questions: how and where do SWD arise in the human brain? Therefore, we explored the spatio-temporal dynamics of interactions within and between widely distributed cortical sites using magneto-encephalographic recordings of spontaneous absence seizures. We then extracted, from their time-frequency analysis, local synchronization of cortical sources and long-range synchronization linking distant sites. Our analyses revealed a reproducible sequence of 1) long-range desynchronization, 2) increased local synchronization and 3) increased long-range synchronization. Although both local and long-range synchronization displayed different spatio-temporal profiles, their cortical projection within an initiation time window overlap and reveal a multifocal fronto-central network. These observations contradict the classical view of sudden generalized synchronous activities in absence epilepsy. Furthermore, they suggest that brain states transition may rely on multi-scale processes involving both local and distant interactions.

Surface-acoustic-wave counterflow micropumps for on-chip liquid motion control in two-dimensional microchannel arrays

Fully controlled liquid injection and flow in hydrophobic polydimethylsiloxane (PDMS) two-dimensional microchannel arrays based on on-chip integrated, low-voltage-driven micropumps are demonstrated. Our architecture exploits the surface-acoustic-wave (SAW) induced counterflow mechanism and the effect of nebulization anisotropies at crossing areas owing to lateral propagating SAWs. We show that by selectively exciting single or multiple SAWs, fluids can be drawn from their reservoirs and moved towards selected positions of a microchannel grid. Splitting of the main liquid flow is also demonstrated by exploiting multiple SAW beams. As a demonstrator, we show simultaneous filling of two orthogonal microchannels. The present results show that SAW micropumps are good candidates for truly integrated on-chip fluidic networks allowing liquid control in arbitrarily shaped two-dimensional microchannel arrays.

Learning Spike-Based Population Codes by Reward and Population Feedback

We investigate a recently proposed model for decision learning in a population of spiking neurons where synaptic plasticity is modulated by a population signal in addition to reward feedback. For the basic model, binary population decision making based on spike/no-spike coding, a detailed computational analysis is given about how learning performance depends on population size and task complexity. Next, we extend the basic model to n-ary decision making and show that it can also be used in conjunction with other population codes such as rate or even latency coding.

Chest pulse-wave velocity: a novel approach to assess arterial stiffness

Pulse-wave velocity (PWV) is considered as the gold-standard method to assess arterial stiffness, an independent predictor of cardiovascular morbidity and mortality. Current available devices that measure PWV need to be operated by skilled medical staff, thus, reducing the potential use of PWV in the ambulatory setting. In this paper, we present a new technique allowing continuous, unsupervised measurements of pulse transit times (PTT) in central arteries by means of a chest sensor. This technique relies on measuring the propagation time of pressure pulses from their genesis in the left ventricle to their later arrival at the cutaneous vasculature on the sternum. Combined thoracic impedance cardiography and phonocardiography are used to detect the opening of the aortic valve, from which a pre-ejection period (PEP) value is estimated. Multichannel reflective photoplethysmography at the sternum is used to detect the distal pulse-arrival time (PAT). A PTT value is then calculated as PTT = PAT - PEP. After optimizing the parameters of the chest PTT calculation algorithm on a nine-subject cohort, a prospective validation study involving 31 normo- and hypertensive subjects was performed. 1/chest PTT correlated very well with the COMPLIOR carotid to femoral PWV (r = 0.88, p < 10 (-9)). Finally, an empirical method to map chest PTT values onto chest PWV values is explored.

Assessment of right ventricular systolic function: Comparison between cardiac magnetic resonance derived ejection fraction and pulsed-wave tissue Doppler imaging of the tricuspid annulus

Systolic right ventricular (RV) function is an important predictor in the course of various congenital and acquired heart diseases. Its practical determination by echocardiography remains challenging. We compared routine assessment of lateral tricuspid annular systolic motion velocity (TV(lat), cm/s) using pulsed-wave tissue Doppler imaging from the apical 4-chamber view with cardiac magnetic resonance (CMR) as reference method.

Excitability and recruitment patterns of spinal motoneurons in human sleep as assessed by F-wave recordings

This study examines the excitability and recruitment of spinal motoneurons in human sleep. The main objective was to assess whether supraspinal inhibition affects the different subpopulations of the compound spinal motoneuron pool in the same way or rather in a selective fashion in the various sleep stages. To this end, we studied F-conduction velocities (FCV) and F-tacheodispersion alongside F-amplitudes and F-persistence in 22 healthy subjects in sleep stages N2, N3 (slow-wave sleep), REM and in wakefulness. Stimuli were delivered on the ulnar nerve, and F-waves were recorded from the first dorsal interosseus muscle. Repeated sets of stimuli were stored to obtain at least 15 F-waves for each state of vigilance. F-tacheodispersion was calculated based on FCVs using the modified Kimura formula. Confirming the only previous study, excitability of spinal motoneurons was generally decreased in all sleep stages compared with wakefulness as indicated by significantly reduced F-persistence and F-amplitudes. More importantly, F-tacheodispersion showed a narrowed range of FCV in all sleep stages, most prominently in REM. In non-REM, this narrowed range was associated with a shift towards significantly decreased maximal FCV and mean FCV as well as with a trend towards lower minimal FCV. In REM, the lowering of mean FCV was even more pronounced, but contrary to non-REM sleep without a shift of minimal and maximal FCV. Variations in F-tacheodispersion between sleep stages suggest that different supraspinal inhibitory neuronal circuits acting on the spinal motoneuron pool may contribute to muscle hypotonia in human non-REM sleep and to atonia in REM sleep.

A triplet spike-timing–dependent plasticity model generalizes the Bienenstock–Cooper–Munro rule to higher-order spatiotemporal correlations

Synaptic strength depresses for low and potentiates for high activation of the postsynaptic neuron. This feature is a key property of the Bienenstock–Cooper–Munro (BCM) synaptic learning rule, which has been shown to maximize the selectivity of the postsynaptic neuron, and thereby offers a possible explanation for experience-dependent cortical plasticity such as orientation selectivity. However, the BCM framework is rate-based and a significant amount of recent work has shown that synaptic plasticity also depends on the precise timing of presynaptic and postsynaptic spikes. Here we consider a triplet model of spike-timing–dependent plasticity (STDP) that depends on the interactions of three precisely timed spikes. Triplet STDP has been shown to describe plasticity experiments that the classical STDP rule, based on pairs of spikes, has failed to capture. In the case of rate-based patterns, we show a tight correspondence between the triplet STDP rule and the BCM rule. We analytically demonstrate the selectivity property of the triplet STDP rule for orthogonal inputs and perform numerical simulations for nonorthogonal inputs. Moreover, in contrast to BCM, we show that triplet STDP can also induce selectivity for input patterns consisting of higher-order spatiotemporal correlations, which exist in natural stimuli and have been measured in the brain. We show that this sensitivity to higher-order correlations can be used to develop direction and speed selectivity.