Scientific Understanding of Consciousness
Compendium of My Understanding of Consciousness
Our experience of consciousness is mediated by an ever-changing, widespread but sparse assemblage of neurons, dynamically connected via assemblages of active synapses. This dynamic core of neuron network assemblage is changing is ever-changing on the basis of about 10 ms.
Most of the neural network activity, both cortical and subcortical, is unconscious. Nearly all of the subcortical neural activity which includes both wake-time and sleep-time activities is unconscious.
Consciousness and the present state of science is undefined, and it should remain that way until the science of consciousness is much better understood. Understanding the minimal states of consciousness have obfuscated clinical medicine and the families of patients.
Consciousness can be parsed into human-type consciousness and core consciousness. Human-type consciousness is the consciousness we experience in our normal waketime activities. Dreaming during sleep time is a kind of unconsciousness we normally experience.
One researcher has posited that consciousness is a dream state modulated by the senses.
All of consciousness is based upon a sense of self, which is a background neural activity neural network activity that defines a person’s individual identity. The self is comprised of the entire network of neurons and synapses that were assembled by genetics and development and lifelong experiences in the world. The sense of self is an active network assemblage that interact with a sensory input image or with an imagining image.
The neural network must be understood of synaptically connected neurons. Although many types of neurons in the network they can generally be understood as projection neurons and interneurons. Typically, projection neurons can be understood as having a dendritic arbor of perhaps 10,000 input synapses and a number of axon collaterals with one major axon output with perhaps a number of collaterals. Neural network activity must be understood in terms of population statistics of active inputs on the dendritic axons exceeding the Byron threshold during an approximate 1 ms window 1 ms time window causing an action potential to be fired down the axon.
Limbic System and Emotions
Limbic system functionality is concentrated mainly around the brainstem beneath the frontal cortex.
Network memory is mediated by neurons and efficacious synapses on the dendritic tree. A pattern of input signals propagate’s in the neural network via efficacious synapses, activating a neuron-synapse pattern constituting a memory engraved via many similar activity patterns.
The memory in the neural network is based upon the efficacious pattern and neuron and synapses and the plasticity of synapses over a period of lifetime experience.
The associative functionality of memory causes in neural network pattern to the activated whenever a small snippet is activated as a cue.
Declarative Memory Is a Major Characteristic of Human Consciousness
Declarative memory as a major part of human consciousness. Declarative memory can be parsed into recall memory and recognition memory. Declarative memory includes semantic memory and episodic memory. The human brain contains a specialized area for the recognition and processing in the perception of human faces. The explicit functionality of human face processing can be compared with a different functionality that the brains of birding enthusiasts use to identify different bird species.
Resulting Function of Brain Activity is Movement Control
The resulting function of brain activity is movement control, which can include lips, tongue and throat movements of speaking; finger movements of playing the piano; eye movements of reading a book; as well as the highly visible movements of athletic sports. Movements are mediated by a hierarchy of FAPs, including a newborn baby’s sucking, crying and sneezing movements; along with FAPs for the learned movements of riding a bicycle or playing the piano.
Central Pattern Generators (CPGs) generate neuronal patterns of activity that drive FAPs such as the walking FAP. (Llinás; I of the Vortex, 134)
DNAand learned movements of control sequences form a part of procedural memory.
Cortex Is Heavily Involved with Sensory Input and Processing along with Movement Control
The posterior parts of the cortex are involved with sensory input and processing.
Visual input in the occipital cortex follows through association areas of the “what” pathway through the temporal cortex and it “where” pathway through the right parietal cortex.
Language Processed Mostly in the Left Cortex
Language and humans is typically processed in the left side of the cortex.
Plasticity of Neural Synaptic Connections
Short-term memory. Long-term memory. Consolidation of memory. Short-term based upon Ion concentrations and transfer and membranes. Long-term memory based upon gene expression and new protein molecules in membranes.
Neural Network Activity Produces a Wide Spectrum of Electrical Signals
The neural network’s huge number of asynchronous axon action potentials produce a wide spectrum of oscillations, which can be detected in the lectroencephalogram (EEG). Quiet waketime neural activity has a prominent frequency of about 10 Hz.
Short and long axon conduction produce a wide specs spectrum of oscillations. The spectrum has a 1/f distribution known as “Pink Noise.”
Unstructured Hierarchy of the Neural Network
The vast numbers of short and long term axon connections result in an unstructured hierarchy with many short interneurons interconnecting the dendritic trees of projection neurons, whose axons are both short, medium and longer range, including between cortices.
Recursive Functionality is a Ubiquitous Characteristic of Neural Circuitry
Bayesian Inference is a Result of the Recursive Functionality
Neural Representation of The Self
Sense of Self is a Neural Component of the Dynamic Core of Consciousness
A Mental Image is a Neural Component of the Dynamic Core of Consciousness
A mental image is ongoing recursive neural activity in a widespread but sparse neural network, representing a correspondence to an array of input sensory signals, or to an imagined thought queued by neural circuitry in the frontal cortex.