Blind method for discovering number of clusters in multidimensional datasets by regression on linkage hierarchies generated from random data.

Determining intrinsic number of clusters in a multidimensional dataset is a commonly encountered problem in exploratory data analysis. Unsupervised clustering algorithms often rely on specification of cluster number as an input parameter. However, this is typically not known a priori.

Response evaluation after stereotactic ablative radiotherapy for localised non-small-cell lung cancer: an equipoise of available resource and accuracy.

There is growing evidence supporting the use of stereotactic ablative radiotherapy (SABR) on the treatment of localised stage non-small-cell lung cancer (NSCLC). Distinctive imaging challenges are posed post-SABR treatment. Thus, it is imperative to provide guidance on assessing treatment response, especially for new adopters.

Mapping the coherence of ictal high frequency oscillations in human extratemporal lobe epilepsy.

Objective: High frequency oscillations (HFOs) have recently been recorded in epilepsy patients and proposed as possible novel biomarkers of epileptogenicity. Investigation of additional HFO characteristics that correlate with the clinical manifestation of seizures may yield additional insights for delineating epileptogenic regions. To that end, this study examined the spatiotemporal coherence patterns of HFOs (80-400 Hz) so as to characterize the strength of HFO interactions in the epileptic brain.

Synthesis of high-complexity rhythmic signals for closed-loop electrical neuromodulation.

We propose an approach to synthesizing high-complexity rhythmic signals for closed-loop electrical neuromodulation using cognitive rhythm generator (CRG) networks, wherein the CRG is a hybrid oscillator comprised of (1) a bank of neuronal modes, (2) a ring device (clock), and (3) a static output nonlinearity (mapper). Networks of coupled CRGs have been previously implemented to simulate the electrical activity of biological neural networks, including in silico models of epilepsy, producing outputs of similar waveform and complexity to the biological system. This has enabled CRG network models to be used as platforms for testing seizure control strategies.

Markers of pathological excitability derived from principal dynamic modes of hippocampal neurons.

Transformation of principal dynamic modes (PDMs) under epileptogenic conditions was investigated by computing the Volterra kernels in a rodent epilepsy model derived from a mouse whole hippocampal preparation, where epileptogenesis was induced by altering the concentrations of Mg(2 +) and K(+) of the perfusate for different levels of excitability. Both integrating and differentiating PDMs were present in the neuronal dynamics, and both of them increased in absolute magnitude for increased excitability levels. However, the integrating PDMs dominated at all levels of excitability in terms of their relative contributions to the overall response, whereas the dominant frequency responses of the differentiating PDMs were shifted to higher ranges under epileptogenic conditions, from ripple activities (75-200 Hz) to fast ripple activities (200-500 Hz).

Spectral features of electroencephalogram in characterizing various brain states under anesthesia.

The administration of the anesthetic agents is known to alter the electroencephalogram (EEG) signal significantly with the brain being their primary target. In this study, we analyzed the EEG recorded from six ASA I/II patients undergoing a 1-2 hour surgery. The EEG was collected before and during induction, maintenance and recovery of anesthesia using the 10/20 lead-system.

Responsive neuromodulators based on artificial neural networks used to control seizure-like events in a computational model of epilepsy.

Deep brain stimulation (DBS) has been noted for its potential to suppress epileptic seizures. To date, DBS has achieved mixed results as a therapeutic approach to seizure control. Using a computational model, we demonstrate that high-complexity, biologically-inspired responsive neuromodulation is superior to periodic forms of neuromodulation (responsive and non-responsive) such as those implemented in DBS, as well as neuromodulation using random and random repetitive-interval stimulation.

Complexity in neuronal noise depends on network interconnectivity.

"Noise," or noise-like activity (NLA), defines background electrical membrane potential fluctuations at the cellular level of the nervous system, comprising an important aspect of brain dynamics. Using whole-cell voltage recordings from fast-spiking stratum oriens interneurons and stratum pyramidale neurons located in the CA3 region of the intact mouse hippocampus, we applied complexity measures from dynamical systems theory (i.e.

System characterization of neuronal excitability in the hippocampus and its relevance to observed dynamics of spontaneous seizure-like transitions.

Most forms of epilepsy are marked by seizure episodes that arise spontaneously. The low-magnesium/high-potassium (low-Mg(2+)/high-K(+)) experimental model of epilepsy is an acute model that produces spontaneous, recurring seizure-like events (SLEs). To elucidate the nature of spontaneous seizure transitions and their relationship to neuronal excitability, whole-cell recordings from the intact hippocampus were undertaken in vitro, and the response of hippocampal CA3 neurons to Gaussian white noise injection was obtained before and after treatment with various concentrations of low-Mg(2+)/high-K(+) solution.

Transformation of neuronal modes associated with low-Mg2+/high-K+ conditions in an in vitro model of epilepsy.

Nonparametric system modeling constitutes a robust method for the analysis of physiological systems as it can be used to identify nonlinear dynamic input-output relationships and facilitate their description. First- and second-order kernels of hippocampal CA3 pyramidal neurons in an in vitro slice preparation were computed using the Volterra-Wiener approach to investigate system changes associated with epileptogenic low-magnesium/high-potassium (low-Mg(2+)/high-K(+)) conditions. The principal dynamic modes (PDMs) of neurons were calculated from the first- and second-order kernel estimates in order to characterize changes in neural coding functionality.

Theta phase precession and phase selectivity: a cognitive device description of neural coding.

Information in neural systems is carried by way of phase and rate codes. Neuronal signals are processed through transformative biophysical mechanisms at the cellular and network levels. Neural coding transformations can be represented mathematically in a device called the cognitive rhythm generator (CRG).

A wavelet packet-based algorithm for the extraction of neural rhythms.

Neural rhythms are associated with different brain functions and pathological conditions. These rhythms are often clinically relevant for purposes of diagnosis or treatment, though their complex, time-varying features make them difficult to isolate. The wavelet packet transform has proven itself to be versatile and effective with respect to resolving signal features in both time and frequency.

Mapped clock oscillators as ring devices and their application to neuronal electrical rhythms.

The mapped clock oscillator (MCO) is a second-order, Winfree-type oscillator generating two instantaneous clock variables (amplitude and phase) that are mapped to an observable output variable (voltage) via a static nonlinearity. Two fundamental classes of ring devices are presented. Their respective dynamics give rise to two oscillator forms--the labile clock and the clock--which can be coupled together in various configurations to create higher-order systems with sufficient complexity to capture the dynamics of neuronal assemblies.

Simulated mossy fiber associated feedforward circuit functioning as a highpass filter.

Learning and memory rely on the strict regulation of communication between neurons in the hippocampus. The mossy fiber (MF) pathway connects the dentate gyrus to the auto-associative CA3 network, and the information it carries is controlled by a feedforward circuit combining disynaptic inhibition with monosynaptic excitation. Analysis of the MF associated circuit using a mapped clock oscillator (MCO) model reveals the circuit to be a highpass filter.