Tag Archives: neurons
31 Jan Feature Selectivity in Vision
This post is another in the series on specialization, in which the author stresses the need for very heterogeneous models for imitating brain capabilities with computers. An important discovery of neurophysiological and cybernetic research is that many neurons, particularly those in areas of the brain that specialize in processing perceptual data, are feature selective. Vision processing is […]
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 […]
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. […]
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 […]
29 Oct DNA and Biocomplexity
Bio-Complexity Before I can feel comfortable designing a machine or software that can perform brain-like tasks, I want to understand the brain and the broader context in which it develops and operates. The last thing I want to do is over-simplify my assumptions and fail in my design. Nor do I want to over-complexify. I don’t […]
25 Aug Learning from Brain Disorders
Serotonin Imbalance I am possessed of an orderly disorder. My “Obsessive-Compulsive Disorder” (OCD) compels me to make sure everything is lined up nicely. Do good managers benefit from a little OCD? Today’s post is about what we can learn about the brain from observing what happens when something isn’t exactly right. Collette Bouchez, on WebMD, tells us […]
31 Mar Asymmetrical Balance, True Love and Chaos
Inequality is the Pattern Unequal distributions characterize everything in the universe from subatomic particles to galaxies. In fact the whole idea of “equality” in the physical universe seems at least a tiny bit sketchy. At the extreme end of unequal distributions is chaos. On the near end are things that approximate equality: balance, parity, equal opportunity, symmetry […]
19 Mar Neural Networks – Section 3 Intro
It’s all in your head My posts on Brains and Neurons show us there is a sense of structure and order in the brain. By looking at the brain’s areas, we see how each plays a special role in processing the information necessary to support human cognition and other activities. We’ve looked at neurons and learned that each type has its own components, […]