Motor vs. sensory predictions

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Chapter 4 endnote 50, from How Emotions are Made: The Secret Life of the Brain by Lisa Feldman Barrett.
Some context is:

...these regions predict that your heart rate should increase and your blood vessels should dilate, for instance, in preparation to run. A pounding heart and surging blood would cause interoceptive sensations, so your brain must predict those sensations as well.

The brain's control of the body, sent as body-budgeting predictions, and interoceptive predictions come from the same columns of neurons and are related information. (They may even be exactly the same pattern of neural firing, just arriving at different places.) To the neurons in subcortical regions and in the spinal cord, the information is a body-budgeting prediction to the body (Figure B, below), whereas to the sensory regions, it’s a sensory prediction (Figure D). This arrangement is sometimes called corollary discharge or sending efference copies.

Neurons in Layers V and VI of body-budgeting (visceromotor) regions in the brain (which are part of the interoceptive network; see blue regions in Figure A) send predictions to Layers II through III to posterior/mid insula, which serves as primary interoceptive cortex. This serves to change the firing of those neurons in advance of incoming thalamic input from the body to Layer IV of primary interoceptive cortex, completing the simulated sensation.[1]

Body-budgeting regions send a variety of efference copies to motor cortex (Figure C) and to other sensory cortices (Figure D).


Key body-budgeting regions (in blue) that provide cortical control the body’s internal systems. Primary motor cortex is depicted in red, and primary sensory regions are in yellow. For simplicity, only primary visual, interoceptive and somatosensory cortices are shown; subcortical regions are not shown.

Legend: daIns = dorsal anterior insula (and in this figure includes ventrolateral prefrontal cortex); dmPFC = dorsomedial prefrontal cortex; m/pIns = mid/posterior insula (primary interoceptive cortex); MC = motor cortex; MCC = midcingulate cortex; pgACC = pregenual anterior cingulate cortex; PMA = premotor area; sgACC = subgenual anterior cingulate cortex; SMA = supplementary motor area; SSC = somatosensory cortex; V1 = primary visual cortex; vaIns = ventral anterior insula; vmPFC = ventromedial prefrontal cortex.
The body-budgeting neurons in the blue regions initiate body-budgeting predictions to the amygdala, ventral striatum, hypothalamus and brainstem nuclei (the parabrachial nucleus, periaqueductal grey, and the nucleus of the solitary tract) to control the autonomic nervous system, the immune system, and the endocrine system (solid lines).[2][3] My hypothesis is that these regions of the brain, which are responsible for keeping the body's budget in balance, in conjunction with the hippocampus and the cerebellum, are ‘driving’ predictions in the brain.[2] The incoming sensory inputs from the body are carried along the vagus nerve and small diameter C and Aδ fibers to the cortex; these are prediction errors, which are learning signals that update predictions (dotted lines)
Copies of the body-budgeting signals cascade to primary motor cortex as skeletomotor prediction signals.[4][5][6][7] Prediction signals flow from deep layers of body-budgeting cortices and terminate in the upper layers of cortical regions with more developed (i.e. more granular) structure, such as primary motor cortex.[8] The skeletomotor prediction signals prepare the body for movement.
Sensory cortices receive sensory predictions from several sources. Copies of the body-budgeting signals cascade to primary gustatory and olfactory cortex, to primary interoceptive cortex, and to the primary visual, auditory and somatosensory regions (in black solid lines). Because motor has a less developed laminar organization than primary interoceptive, visual, auditory, and somatosensory cortices, it sends sensory prediction signals to these regions (as efferent copies of motor predictions, red solid lines). And because of their differential development, I hypothesize that primary interoceptive cortex in mid-to-posterior dorsal insula sends sensory predictions to primary visual, auditory and somatosensory cortices (propagating across either a single or multiple synapses (gold solid lines). The interoceptive prediction signals initiate a change in affect (i.e. the expected sensory consequences within the body), and the extrapersonal sensory prediction signals prepare upcoming perceptions). For simplicity’s sake, prediction errors are not depicted here.

Notes on the Notes

  1. As explained in Barrett, Lisa Feldman, and W. Kyle Simmons. 2015. “Interoceptive Predictions in the Brain.” Nature Reviews Neuroscience 16 (7): 419–429.
  2. 2.0 2.1 As explained in Barrett, Lisa Feldman. 2017. "The theory of constructed emotion: an active inference account of interoception and categorization." Social Cognitive and Affective Neuroscience 12 (1): 1-23.
  3. As explained in Kleckner, Ian, Jiahe Zhang, Alexandra Touroutoglou, Lorena Chanes, Chenjie Xia, W. Kyle Simmons, Karen Quigley, Bradford Dickerson, and Lisa Feldman Barrett. 2017. “Evidence for a Large-Scale Brain System Supporting Interoception in Humans.” Nature Human Behavior 1: 0069.
  4. Bastos, Andre M., W. Martin Usrey, Rick A. Adams, George R. Mangun, Pascal Fries, and Karl J. Friston. 2012. "Canonical microcircuits for predictive coding." Neuron 76 (4): 695-711.
  5. Adams, Rick A., Stewart Shipp, and Karl J. Friston. 2013. "Predictions not commands: active inference in the motor system." Brain Structure and Function 218 (3): 611-643.
  6. Barrett, Lisa Feldman, and W. Kyle Simmons. 2015. “Interoceptive Predictions in the Brain.” Nature Reviews Neuroscience 16 (7): 419–429.
  7. Chanes, Lorena, and Lisa Feldman Barrett. 2016. “Redefining the Role of Limbic Areas in Cortical Processing.” Trends in Cognitive Sciences 20 (2): 96–106.
  8. For evidence that primary motor cortex is granular in structure, see Barbas, Helen, and Miguel Á. García-Cabezas. 2015. "Motor cortex layer 4: less is more." Trends in Neurosciences 38 (5): 259-261.