Tag Archives: thought
27 Jan Go With the Flow
Modeling Neural Electrical Flow Patterns From looking at possible mechanisms for information storage, we move back to its movement. It may be important to understand the patterns of electrical flow in the brain to define good models for artificial systems that attempt to match human competence in cognitive processing tasks. This is what neural network and […]
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 […]
16 Jan Roots of Neural Nets
Roots of Neural Nets The concept of the modern Artificial Neural Systems (ANS) has its roots in the work of psychologists and philosophers as well as computer scientists. As mentioned in prior posts, Aristotelian theories on cognition and logic influenced the development of automata theory and associationism, spawning connectionism or parallel distributed processing (PDP) theory. Connectionism is the […]
13 Jan Harmonic Convergence of Light
Light waves diverge and converge and bend on their journey to places where they are perceived. We choose to focus, perceived light waves enter us through the portals of our eyes, then flow through the visual cortex and resonate in the brain until they trigger recognition, often very quickly. The illustration shows a lens that […]
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 […]
01 Jan Axon and Dendrite Growth
Link Formation in a Bio-Network It was once believed that the link structure of the nervous system was formed randomly during embryogenesis and remained static after maturation – sometime between early development and adolescence (except for regeneration after injury). Due to improved imaging resolutions and preparation techniques, we now know that axon termini, dendrites, and spines […]
31 Oct Modeling Biological Systems
Possible Mechanisms of Learning, Memory and Cognition In the first section of this blog, I talked about the brain, as a whole, to establish a framework for the discussion of natural intelligence. In this section, I have delved into the inner workings of neurons, themselves to ensure we understand how complex they are, and where we […]
17 Mar Intro to Cybernetic Models
Are you my Motherboard? From Eliza to Watson, Jeeves, Siri and Alfred, people have been naming their computers. Some systems are named after their inventors – like Wolfram Alpha and its siblings. Who is JARVIS? Just Another Rather Very Intelligent System? These attempts have, in their own little ways, touched our lives. But we are still waiting on the cusp of an innovation that will […]
06 Mar Correlation in Neuroeconomics
I find that driving when my body is tense, especially on slick roads or in poor visibility, is uncomfortable to the point of danger. Stress is a killer. I found, as a student, that relaxing at the piano just before going in to the test helped me perform better (on the test). I think many […]