Tag Archives: neural network
25 Jan The Chromophore as Digital Bit
I have opined in prior posts that the skeletal components that give structure to axons and dendrites, especially microtubules, may play a larger role in cognition than previously thought. The illustration of microtubule structure at right shows how the alpha and beta tubulin dimers string themselves together to make protofilaments, which further join one another […]
18 Jan Multi-Layered Perceptron
Multi-Layered Perceptron In prior posts we introduced the concept of the artificial neural network and the perceptron model as a simple implementation of a neural network. We showed the structure, including an input layer and an output layer. Let’s look at one of the typical approaches for processing input to derive the output. The net output of […]
17 Jan Perceptrons and Weighted Schemes
Perceptrons In the late 1600’s, John Locke expounded an associationist theory in which neurons or “bundles” of neurons came to represent certain ideas and associations between ideas. Rosenblatt‘s work seems a logical extension of associationist theory. Perceptrons can perform linear discrimination, thus enabling them to model the cognitive function of recognition (or, in computational terms, pattern classification). […]
14 Jan Timing is Everything: Asynchronicity of E/I
Time marches straight on in a never-ending rhythm, never stopping to rest – never missing a beat. After memory fails, and all the mainsprings unwind, time strides forward. Coincidence and synchronicity of events in the physical universe are time bound, but not necessarily meaning bound. In the human brain, time loses relevance and thought flows in lesser […]
09 Jan What of Perception
Questions Cognitive Modelers Might Ask The biological and chemical processes associated with brain activity are the foundation on which our exploration of the cognitive mind is built. Yet the physiological underpinnings are not sufficient, in themselves, to lead us to the next cybernetic level. Too many questions are left unanswered. In this section of Understanding […]
08 Jan E/I Electric Potential Curve
Challenge I’ve noticed two phenomena in computing that have often been compared to brain activity even though they don’t significantly resemble the behavior of electrical potential changes between neurons: Flip-Flop (the changing of a “register” from 0 to 1 Node Firing (The activation of a node in an artificial neural network) In this section of Understanding Context, I’ve been trying to […]
06 Jan Excitation and Inhibition
Most, if not all, neural information-processing functions involve the flow of action potential. Impulses in the nervous system are changes in the action potential or electrical charge of membranes. It is possible that, in addition to the membranes, the potential within the cytoplasm of the cell changes as a result of electrical flow in neurons. […]
02 Jan Synapse Formation
Many neurons have only a few synapses. Others, like giant pyramidal and Purkinje cells, may have tens or even hundreds of thousands of synapses. At the conclusion of the complex growth process, called synaptogenesis, in which growth cones at the tips of spines, axons, and dendrites propel or draw the fiber through the crowded gray and white matter […]
31 Dec Signal Transduction in Neurons
Wires in the Brain Electrical impulses jump from neuron to neuron in the brain through their branching nerve fibers. This movement of electrical potentials is called signal transduction, and significantly resembles the process of electrical flow in printed circuit boards and semiconductor chips. Nerve fibers (axons and dendrites) are filled with a fluid called axoplasm. […]
30 Dec Aristotle and von Neumann
In the 1950’s, John von Neumann compared the computer to the brain. Scientific inquiry that laid the foundation for that comparison, however, had begun long before. The influence of the Greek philosopher Aristotle’s association theory (metaphysics), for example, is evident in neural net theory. In The Computer and the Brain, Dr. von Neumann describes how […]