Predicting single-neuron activity in locally connected networks

An Adaptive-PSO-Based Self-Organizing RBF Neural Network

In this paper, a self-organizing radial basis function (SORBF) neural network is designed to improve both accuracy and parsimony with the aid of adaptive particle swarm optimization (APSO). In the proposed APSO algorithm, to avoid being trapped into local optimal values, a nonlinear regressive function is developed to adjust the inertia weight. Furthermore, the APSO algorithm can optimize both the network size and the parameters of an RBF neural network simultaneously. As a result, the proposed APSO-SORBF neural network can effectively generate a network model with a compact structure and high accuracy. Moreover, the analysis of convergence is given to guarantee the successful application of the APSO-SORBF neural network. Finally, multiple numerical examples are presented to illustrate the effectiveness of the proposed APSO-SORBF neural network. The results demonstrate that the proposed method is more competitive in solving nonlinear problems than some other existing SORBF neural networks.

Simultaneous Recording of Single-Neuron Activities and Broad-Area Intracranial Electroencephalography: Electrode Design and Implantation Procedure

BACKGROUND:

There has been growing interest in clinical single-neuron recording to better understand epileptogenicity and brain function. It is crucial to compare this new information, single-neuronal activity, with that obtained from conventional intracranial electroencephalography during simultaneous recording. However, it is difficult to implant microwires and subdural electrodes during a single surgical operation because the stereotactic frame hampers flexible craniotomy.

OBJECTIVE:

To describe newly designed electrodes and surgical techniques for implanting them with subdural electrodes that enable simultaneous recording from hippocampal neurons and broad areas of the cortical surface.

METHODS:

We designed a depth electrode that does not protrude into the dura and pulsates naturally with the brain. The length and tract of the depth electrode were determined preoperatively between the lateral subiculum and the lateral surface of the temporal lobe. A frameless navigation system was used to insert the depth electrode. Surface grids and ventral strips were placed before and after the insertion of the depth electrodes, respectively. Finally, a microwire bundle was inserted into the lumen of the depth electrode. We evaluated the precision of implantation, the recording stability, and the recording rate with microwire electrodes.

RESULTS:

Depth-microwire electrodes were placed with a precision of 3.6 mm. The mean successful recording rate of single- or multiple-unit activity was 14.8%, which was maintained throughout the entire recording period.

CONCLUSION:

We achieved simultaneous implantation of microwires, depth electrodes, and broad-area subdural electrodes. Our method enabled simultaneous and stable recording of hippocampal single-neuron activities and multichannel intracranial electroencephalography.