Dhanesh Solanki

Neurons or nerve cells are electrically excitable cells in the nervous system. The main tasks of a nervous system are collecting information, processing information and eliciting a response to the information. In order to ful ll these functions, a huge number of linked neurons are essential. Alone the human brain,being one of the two part in central nervous system, has about 100 billions neurons, which are highly connected with each other. Neuronal cells consists of a cell body, the so-called soma, furthermore of dendrites, axon and the axon foot. The dendrites receive the chemical messages from other neuronal cells. The axon transmits the electro-chemical signal, the action potential, to other neurons. If the action potential reached the axon foot, the electro-chemical message will be again transformed into a chemical message. We will only focus on the electro-chemical signal, the action potential. Nerve signals are changes in membrane voltage, also called membrane potential, wh...

Encoding --- is the crucial first step to creating a new memory. It allows the perceived item of interest to be converted into a construct that can be stored within the brain, and then recalled later from short-term or long-term memory. Encoding is a biological event beginning with perception through the senses. The process of laying down a memory begins with attention (regulated by the thalamus and the frontal lobe ), in which a memorable event causes neurons to fire more frequently, making the experience more intense and increasing the likelihood that the event is encoded as a memory. Emotion tends to increase attention, and the emotional element of an event is processed on an unconscious pathway in the brain leading to the amygdala . Only then are the actual sensations derived from an event processed. The perceived sensations are decoded in the various sensory areas of the cortex, and then combined in the brain’s hippocampus into one single experience. The hippocam...

Question 1:- Identifying Synapses, Reconstructing neurons involves tracing their branches, which are like the “wires” of the retina. This by itself is not enough for finding connectomes; we also need to identify synapses. This kind of image analysis will be accomplished through another game that will be introduced on this website in the near future. The identification of synapses will involve subtleties. A neuron receives input from other neurons (typically many thousands). Inputs sum (approximately). Once input exceeds a critical level, the neuron discharges a spike - an electrical pulse that travels from the body, down the axon, to the next neuron(s) (or other receptors). This spiking event is also called depolarization , and is followed by a refractory period , during which the neuron is unable to fire. The axon endings (Output Zone) almost touch the dendrites or cell body of the next neuron. Transmission of an electrical signal from one neuron to the next is effected by ...

The nervous system manages dynamic recognition. The recognition of an odor identifies a single entity among millions. But, animals also use this ability for time dimensioned recognition. Dogs can quickly sniff a sequence of footprints of a person and determine accurately which way the person is walking. The animal's nose can detect the relative odor strength difference between footprints only a few feet apart, to determine the direction of a trail. The somesthetic association region of the brain enables you to recognize a pair of scissors, with your eyes closed. If this region is damaged, you will be able to feel the scissors, but you will not be able identify it. This recognition process is also dynamic. An instant touch cannot identify a pair of scissors. You have to run your fingers over it. A sequence of touches recognizes a single object.

The human mind deals comfortably with sequences of millions of such matrices. People are reported to be able to remember and recognize any one of 10,000 images displayed to him at one second intervals. Each image is a matrix of millions of pixels. The mind has the ability to remember and recognize images in huge sequences of massive matrices. Combinatorial codes enable matrices to record, interact and recall the patterns of other matrices. This ability to identify the unique qualities of matrices over time enables behavior pattern recognition by the mind. That process can identify events the way a movie subtitle identifies a sequence of film images. If a recording iterates the subtitle across the length of an activity, then any individual frame of the movie will identify the action through the subtitle. In such matrices, an iterating pattern can recognize a sequential activity.

Here we discuss two potential algorithms that can perform clustering extremely fast, on big data sets, as well as the graphical representation of such complex clustering structures. By extremely fast, we mean a computational complexity of order   O(n) and even faster such as   O(n/log n) . This is much faster than good Hierarchical Agglomerative Clustering   which are typically O(n^2 log n) . By big data, we mean several millions, possibly a billion observations. Potential applications : Creating a keyword taxonomy to categorize the entire universe of cleaned (standardized), valuable English keywords. We are talking of about 10 million keywords made up of one, two or three tokens, that is, about 300 times the number of keywords found in a good English dictionary. The purpose might be to categorize all bid keywords that could be purchased by eBay and Amazon on Google (for pay-per-click ad campaigns), to better price them. This is the application discussed in this art...