Information coding via spontaneous oscillations in neural ensembles.

Title Information coding via spontaneous oscillations in neural ensembles

A neural coding scheme formed by the combined function of gamma and theta oscillations.

Brain oscillations are important in controlling the timing of neuronal firing. This process has been extensively analyzed in connection with gamma frequency oscillations and more recently with respect to theta frequency oscillations. Here we review evidence that theta and gamma oscillations work together to form a neural code. This coding scheme provides a way for multiple neural ensembles to r...

Spatial pattern coding of sensory information by climbing-fiber evoked calcium signals in networks of neighboring cerebellar Purkinje cells Abbreviated Title: Spatial pattern coding in cerebellar microzones

Climbing fiber input produces complex spike synchrony across populations of cerebellar Purkinje cells oriented in the parasagittal axis. Elucidating the fine spatial structure of this synchrony is crucial for understanding its role in the encoding and processing of sensory information within the olivocerebellar cortical circuit. We investigated these issues using in vivo multineuron two-photon ...

Optimal synchrony state for maximal information transmission.

This work investigated the roles of spontaneous synchronized rhythmic oscillations in information processing in a globally coupled neural network. We found that in the encoding of input aperiodic signals, there exists a range of optimal synchronous states in the network, where the information transmission rate and coding efficiency of the network are maximized. Our results indicate that it is n...

Ensemble strategies to build neural network to facilitate decision making

There are three major strategies to form neural network ensembles. The simplest one is the Cross Validation strategy in which all members are trained with the same training data. Bagging and boosting strategies pro-duce perturbed sample from training data. This paper provides an ideal model based on two important factors: activation function and number of neurons in the hidden layer and based u...