The origin of orientation selectivity in the responses of simple cells in cat visual cortex serves as a model problem for understanding cortical circuitry and computation. The feed-forward model posits that this selectivity arises simply from the arrangement of thalamic inputs to a simple cell. Much evidence, including a number of recent intracellular studies, supports a primary role of the tha...

We study the problem of computing the rate-distortion function of sources with feed-forward and the capacity of channels with feedback. The formulas (involving directed information) for the optimal feed-forward rate-distortion function and the feedback channel capacity are multi-letter expressions and cannot be computed easily in general. In this work, we derive conditions under which these can...

Functionally similar pathways are often seen in biological systems, forming feed-forward controls. The robustness in network motifs such as feed-forward loops (FFLs) has been reported previously. In this work, we studied noise propagation in a development network that has multiple interlinked FFLs. A FFL has the potential of asymmetric noise-filtering (i.e., it works at either the "ON" or the "...

One-shot learning is usually tackled by using generative models or discriminative embeddings. Discriminative methods based on deep learning, which are very effective in other learning scenarios, are ill-suited for one-shot learning as they need large amounts of training data. In this paper, we propose a method to learn the parameters of a deep model in one shot. We construct the learner as a se...

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In this paper, we propose four techniques for extraction of facial features namely 2DPCA, LDA, KPCA and KFA. The purpose of face feature extraction is to capture certain discriminative features that are unique for a person. In the previous works that uses PCA for face feature extraction involves merging the features and reducing the dimensions that results in some information loss. To overcome ...

Neurons receive a large number of excitatory and inhibitory synaptic inputs whose temporal interplay determines the spiking behavior. On average, excitation and inhibition balance each other, such that spikes are elicited by fluctuations [1]. In addition, it has been shown in vivo that excitation and inhibition are correlated, with inhibition lagging excitation only by few milliseconds (∼6 ms),...

The temporal features of tactile stimuli are faithfully represented by the activity of neurons in the somatosensory cortex. However, the cellular mechanisms that enable cortical neurons to report accurate temporal information are not known. Here, we show that in the rodent barrel cortex, the temporal window for integration of thalamic inputs is under the control of thalamocortical feed-forward ...

Multilayered feed-forward neural networks trained with back-propagation algorithm are one of the most popular “online” artificial neural networks. These networks are showing strong inherit parallelism because of the influence of high number of simple computational elements. So it is natural to try to implement this kind of parallelism on parallel computer architecture. The Parallel Hybrid Ring ...

The temporal resolution of neuronal integration depends on the time window within which excitatory inputs summate to reach the threshold for spike generation. Here, we show that in rat hippocampal pyramidal cells this window is very narrow (less than 2 milliseconds). This narrowness results from the short delay with which disynaptic feed-forward inhibition follows monosynaptic excitation. Simul...