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Prediction / Prediction Error

The brain makes prediction about the world and our bodies and pushes those down the seconsory hierarchy. The sensory regions only pass informaton to the brain when it senses the prediction does not match the input. This becomes a Prediction Error (PE) and is the information sent up the hierarchy. If enough errors during sensory integration, then we become conscious of a novel situation. It depends on Generative models of reality - predictions based on prior experience using Bayesian math.

Review paper: How prediction errors shape perception, attention, and motivation
Hanneke E. M. den Ouden1,2*, Peter Kok 1 and Floris P . de Lange 1

Predictive coding posits the existence of separate “prediction” units (P) and prediction error units (PE) within each cortical column, the basic cortical computational module. There are both intrinsic (within the cortical column) and extrinsic (between columns) connections between P and PE units.
Prediction and Prediction Error signals travel to and from specific layers.
Large PEs lead to updating of predictions, which are then sent forward as input to higher cortical areas (via superficial layers, L2/3), as well as backward to update predictions in lower areas (via deep layers, L5/6). In this scheme, the excitatory feedback from higher to lower selection function of the basal ganglia is not limited to action selection or reinforcement learning. Given that the basal ganglia receive cortical, limbic, and brainstem inputs and thus have access to motivational,affective,cognitive,and motor information, they may form the final common pathway where information from a wide variety of sources is integrated and then guide selection among cortical representations, actions and goals. I
Functional differences then arise from differences in the input sources and output targets. For example, outcome predictions in dorsolateral stria-tum will be derived from inputs from sensorimotor areas and will lead to action selection, whereas nucleus accumbens, with inputs from the amygdala and VTA, will report reward PEs in a rein-forcement learning task and allow motivational aspects to guide behavior. Hippocampal and prefrontal glutamatergic inputs to the ventral striatum may provide the top-down context information or predictions to modulate neural activity.
Signed PEs

Layers
https://clinicalgate.com/wp-content/uploads/2015/06/f32-04-9781437702941.jpg Neurons & Layers
http://rstb.royalsocietypublishing.org/content/royptb/371/1708/20160007/F2.large.jpg Prediction Flow

Specifically, valid prior expectations allow for selection of the proper hypotheses (i.e., activating relevant P units) in advance of stimulation, facilitation of perception (Bar, 2004)

CORTICAL PREDICTION ERRORS: LAYERS AND COLUMNS

—- deviate - attracter states https://en.m.wikipedia.org/wiki/Attractor

This paper talks about the body model in layer 4 used to generate predictions. The Body Model Theory of Somatosensory Cortex

2018.08.26 draft jch