FF -> raw sensory input (nerve endings) -> brainstem (routing) -> thalamus (screening and routing) ->
PRIMARY SENSORY ROUTING : SPECIALIZED, MULTI-THREADED, PARALELL
FF <-> temporal lobe (audio cortex) ->
FF <-> occipital lobe (visual cortex) ->
FF <-> parietal lobe (sensory cortex) ->
PRIMARY SENSORY ANALYSIS : INTRACORTICAL FEEDBACK, RESOLUTION
<-> Layers 4-6: Bottom-up construction <-> Layers 1-3: Top-down re-construction
SECONDARY SENSORY ANALYSIS : CONTEXTUAL, MULTI-THREADED
FF <-> parietal lobe (spatial cortex, location) ->
FF <-> temporal lobe (pattern matching cortex) <-> hippocampus (memory)
FF <-> amygdala (immediate emotional response) <-> hippocampus (memory)
TERTIARY SENSORY ANALYSIS : RATIONAL, MULTI-THREADED
FF <-> PFC (analysis) ->
FB <-> amygdala (rational override)
FF <-> language cortex (naming) <-> hippocampus (memory)
FB <-> spatial cortex (location confirmation)
FB <-> medial temporal lobe (symbolic intensity, memory intensity)
FF <-> pre-motor cortex (array of responses, analysis, reaction)
SENSORY RESPONSE : MEMORY & BEHAVIOR (ONGOING)
FF <-> motor cortex (action / response)
FF <-> rhinal cortex (multi-modal sensory compression)
FF <-> hippocampus (memory storage, confirmation, recall, updates)
The above diagram illustrates a very crude waking model of cognitive workflow. Beginning with raw feed-forward (FF) sensory input at somatic nerve endings, nervous signal runs up the spinal cord, into the brainstem, is routed through the thalamus, is gated for noise and screened for focus, and then sent to divergent areas of the cortex for primary processing. Visual data is sent to the visual cortex in the occipital lobe; audio data is sent to the audio cortex in the forward part of the temporal lobe; and somatic data is passed to the forward area of the parietal lobe. Each of these higher-cortical processing areas have four-to-six layers of neuronal networks to do the primary sensory analysis. The bottom layers of the cortex (generally 4 - 6) catch snippets of raw sensory data coming in from the thalamus and lower brain and send the signal upwards towards the dendritic arbors at the higher layers, forming what is known as bottom-up awareness within the cortex. The dendritic arbors at the top cortical layers (layers 1 – 3 rich with 5-HT2A receptors) catch all the upcoming data; use networked holographic compression to fill in the blank spots; and then sends a re-constructed top-down image back to lower layers and for further analysis, feedback (FB) and feed-forward (FF) routing.
Until this point in our workflow, all sensory processing is pre-conscious, meaning we haven’t even “sensed” it in our conscious minds. That only happens when top-down signal from the cortex is fed forward from the middle and lower cortical layers into the executive areas of the pre-frontal cortex and the sensory convergence zone in the rhinal cortex, which is where multi-modal sensory data is re-assembled for memory compression and storage in the hippocampus. But even while all of that is happening, data is also being fed-back (FB) onto the amygdala, medial temporal lobe, and thalamus for ongoing emotional processing, memory updates, and contextual noise/focus gating of incoming signal (respectively).
Once the incoming, convergent, holistic data hits the pre-frontal cortices for secondary analysis, a series of feedback (FB) mechanisms allow constant interaction with the middle layers of the sensory cortices for further resolution of spatial, emotional, and symbolic data content. Once the executive areas have confirmed object identification, location, and emotional significance, the sensory data converging on the rhinal cortex can be named, compressed, and stored in memory with appropriate cues and recall strength via new neural connectivity formed within the layers of the hippocampus and its corollary connectivity back to the cortex. Feedback between the hippocampus, the rhinal cortex, and the primary sensory cortices is essential to creating solid memories with strong imprinting and recall.
It should be noted that this
is a very crude — but essentially accurate — model of cognitive processing.
Keep in mind that tasks like sensory aggregation, compression, storage, and
recall are ongoing all the time, even when incoming data is slow or stopped.
While the above model shows interconnectivity between areas as a stepped
process that trickles down to create perception and memory, these steps are
actually more like a cascade of current moving through divergent pipes and
channels with varying degrees of resistance and feedback (as in analog signal)
than it is like packets of data being stepped precisely though a
packet-switching network (as in digital signal). Although the neural firing
model would suggest a packet-oriented delivery of data in discrete coded
pulses, the neuron does not really act this way. Neurons fire based on the intensity
of the incoming signal, not based on the actual data being transmitted, and
data is fed-forward based on electro-chemically mediated threshold responses to
incoming signal strength. Though the above flow-chart would suggest a properly
cascading multi-threaded digital logic network, the actual brain has very
complex connectivity between sensory processing and memory storage areas, and
these redundant layers of interconnectivity allow for pre-cognitive (or
automatic) memory formation, simultaneous cognitive analysis of data and memory
formation (as in learning and discovery), as well as post-cognitive recall and
revision of memories that have already been formed (such as memory updates
based on new signal, new consideration, or random compression between related memories).
Thus, the cascade of data-to-memory is more like a fountain of raw signal
feeding forward and back on itself in a fluid motion of tides and cascades,
rippling and gating with electrochemical charge along the neural network until
it is recognized, named, and eventually sears a compressed mental picture of
itself into the very networking of our brains.
Excerpted from Psychedelic Information Theory, by James Kent.