Berj L. Bardakjian

256-Channel Neural Recording and Delta Compression Microsystem With 3D Electrodes

A 3D microsystem for multi-site penetrating extracellular neural recording from the brain is presented. A 16 times 16-channel neural recording interface integrated prototype fabricated in 0.35 mum CMOS occupies 3.5 mm times 4.5 mm area. Each recording channel dissipates 15 muW of power with input-referred noise of 7 muVrms over 5 kHz bandwidth. A switched-capacitor delta read-out data compression circuit trades recording accuracy for the output data rate. An array of 1.5 mm platinum-coated microelectrodes is bonded directly onto the die. Results of in vitro experimental recordings from intact mouse hippocampus validate the circuit design and the on-chip electrode bonding technology.

Increased high-frequency oscillations precede in vitro low-Mg2+ seizures

Summary:  Purpose: High‐frequency oscillations (HFOs) in the range of ≥80 Hz have been recorded in neocortical and hippocampal brain structures in vitro and in vivo and have been associated with physiologic and epileptiform neuronal population activity. Frequencies in the fast‐ripple range (>200 Hz) are believed to be exclusive to epileptiform activity and have been recorded in vitro, in vivo, and in epilepsy patients. Although the presence of HFOs is well characterized, their temporal evolution in the context of transition to seizure activity is not well understood.

The origin of segmentation motor activity in the intestine

The segmentation motor activity of the gut that facilitates absorption of nutrients, was first described in the late 19th century but the fundamental mechanisms underlying it remain poorly understood. The dominant theory suggests alternate excitation and inhibition from the enteric nervous system. Here we demonstrate that typical segmentation can occur after total nerve blockade. The segmentation motor pattern emerges when the amplitude of the dominant pacemaker, the slow wave generated by ICC associated with the myenteric plexus (ICC-MP), is modulated by the phase of induced lower frequency rhythmic transient depolarizations, generated by ICC associated with the deep muscular plexus (ICC-DMP), resulting in a waxing and waning of the amplitude of the slow wave and a rhythmic checkered pattern of segmentation motor activity. Phase amplitude modulation of the slow waves points to an underlying system of coupled nonlinear oscillators originating in ICC.

Brain–Silicon Interface for High-Resolution in vitro Neural Recording

A 256-channel integrated interface for simultaneous recording of distributed neural activity from acute brain slices is presented. An array of 16 times 16 Au recording electrodes are fabricated directly on the die. Each channel implements differential voltage acquisition, amplification and band-pass filtering. In-channel analog memory stores an electronic image of neural activity. A 3 mm times 4.5 mm integrated prototype fabricated in a 0.35-mum CMOS technology is experimentally validated in single-channel extracellular in vitro recordings from the hippocampus of mice and in multichannel simultaneous recordings in a controlled environment

Type III intermittency in human partial epilepsy

A rigorous characterization of the dynamic regimes underlying human seizures is needed to understand, and possibly control, the transition to seizure. Intra‐ or extracranial brain electrical activity was recorded in five patients with partial epilepsy, and the interictal and ictal activity analysed to determine the dynamics of seizures. We constructed first‐return one‐dimensional maps by fitting the scatter plots of interpeak intervals. The features of the mapping indicated that type III intermittency is the dynamic charateristic of the ictal events. This was confirmed using histograms of the durations of the regular phases during seizures. The intermittent regime explains the abrupt transitions observed during ictal events in terms of transient stabilization of the unstable steady state.

Daily Rhythmic Behaviors and Thermoregulatory Patterns Are Disrupted in Adult Female MeCP2-Deficient Mice

Mutations in the X-linked gene encoding Methyl-CpG-binding protein 2 (MECP2) have been associated with neurodevelopmental and neuropsychiatric disorders including Rett Syndrome, X-linked mental retardation syndrome, severe neonatal encephalopathy, and Angelman syndrome. Although alterations in the performance of MeCP2-deficient mice in specific behavioral tasks have been documented, it remains unclear whether or not MeCP2 dysfunction affects patterns of periodic behavioral and electroencephalographic (EEG) activity. The aim of the current study was therefore to determine whether a deficiency in MeCP2 is sufficient to alter the normal daily rhythmic patterns of core body temperature, gross motor activity and cortical delta power. To address this, we monitored individual wild-type and MeCP2-deficient mice in their home cage environment via telemetric recording over 24 hour cycles. Our results show that the normal daily rhythmic behavioral patterning of cortical delta wave activity, core body temperature and mobility are disrupted in one-year old female MeCP2-deficient mice. Moreover, female MeCP2-deficient mice display diminished overall motor activity, lower average core body temperature, and significantly greater body temperature fluctuation than wild-type mice in their home-cage environment. Finally, we show that the epileptiform discharge activity in female MeCP2-deficient mice is more predominant during times of behavioral activity compared to inactivity. Collectively, these results indicate that MeCP2 deficiency is sufficient to disrupt the normal patterning of daily biological rhythmic activities.

Rescue of behavioral and EEG deficits in male and female Mecp2-deficient mice by delayed Mecp2 gene reactivation

Mutations of the X-linked gene encoding methyl CpG binding protein type 2 (MECP2) are the predominant cause of Rett syndrome, a severe neurodevelopmental condition that affects primarily females. Previous studies have shown that major phenotypic deficits arising from MeCP2-deficiency may be reversible, as the delayed reactivation of the Mecp2 gene in Mecp2-deficient mice improved aspects of their Rett-like phenotype. While encouraging for prospective gene replacement treatments, it remains unclear whether additional Rett syndrome co-morbidities recapitulated in Mecp2-deficient mice will be similarly responsive to the delayed reintroduction of functional Mecp2. Here, we show that the delayed reactivation of Mecp2 in both male and female Mecp2-deficient mice rescues established deficits in motor and anxiety-like behavior, epileptiform activity, cortical and hippocampal electroencephalogram patterning and thermoregulation. These findings indicate that neural circuitry deficits arising from the deficiency in Mecp2 are not engrained, and provide further evidence that delayed restoration of Mecp2 function can improve a wide spectrum of the Rett-like deficits recapitulated by Mecp2-deficient mice.

System identification of electrically coupled smooth muscle cells: the passive electrical properties

A system model approach based on a network model is used to investigate the passive electrical properties of coupled smooth muscle cells. This approach makes use of a gradient method of optimization to estimate the passive electrical parameters directly from the magnitude of the input impedance or voltage transfer function of the network model. The need for subjective measurements of parameters and many of the intermediate steps involved in the analysis using the conventional signal model approach are eliminated. The coupling resistance and capacitance are estimated with sound theoretical and mathematical analysis directly from experimental data. The coupling impedance is estimated directly from experimental data. The sensitivities of the network with respect to the resistances, capacitances, and time constants can readily be found. This should provide insight into the passive electrical properties of smooth muscle.<<ETX>>

Passive Neuronal Membrane Parameters: Comparison of Optimization and Peeling Methods

The passive membrane properties of neurons allow characterization of neurons. This paper deals with comparison of optimization and peeling methods for passive membrane parameter estimation. Examples using computer-generated test data as well as biological data are used to illustrate the use of these two methods, showing that optimization methods are more accurate than peeling methods.

Prediction of seizure onset in an in-vitro hippocampal slice model of epilepsy using Gaussian-based and wavelet-based artificial neural networks.

We propose that artificial neural networks (ANNs) can be used to predict seizure onsets in an in-vitro hippocampal slice model capable of generating spontaneous seizure-like events (SLEs) in their extracellular field recordings. This paper assesses the effectiveness of two ANN prediction schemes: Gaussian-based artificial neural network (GANN) and wavelet-based artificial neural network (WANN). The GANN prediction system consists of a recurrent network having Gaussian radial basis function (RBF) nonlinearities capable of extracting the estimated manifold of the system. It is able to classify the underlying dynamics of spontaneous in-vitro activities into interictal, preictal and ictal modes. It is also able to successfully predict the onsets of SLEs as early as 60 s before. Improvements can be made to the overall seizure predictor design by incorporating time-varying frequency information. Consequently, the idea of WANN is considered. The WANN design entails the assumption that frequency variations in the extracellular field recordings can be used to compute the times at which onsets of SLEs are most likely to occur in the future. Progressions of different frequency components can be captured by the ANN using appropriate frequency band adjustments via pruning, after the initial wavelet transforms. In the off-line processing comprised of 102 spontaneous SLEs generated from 14 in-vitro rat hippocampal slices, with half of them used for training and the other half for testing, the WANN is able to predict the forecoming ictal onsets as early as 2 min prior to SLEs with over 75% accuracy within a 30 s precision window.