Pain processing by spinal microcircuits: afferent combinatorics

Abstract

Pain, itch, heat, cold, and touch represent different percepts arising from somatosensory input. How stimuli give rise to these percepts has been debated for over a century. Recent work supports the view that primary afferents are highly specialized to transduce and encode specific stimulus modalities. However, cross-modal interactions (e.g. inhibition or exacerbation of pain by touch) support convergence rather than specificity in central circuits. We outline how peripheral specialization together with central convergence could enable spinal microcircuits to combine inputs from distinctly specialized, co-activated afferents and to modulate the output signals thus formed through computations like normalization. These issues will be discussed alongside recent advances in our understanding of microcircuitry in the superficial dorsal horn.

Figure 1. Afferent termination patterns in the spinal dorsal horn

Primary afferents are routinely categorized as Aβ (thickly myelinated), Aδ (thinly myelinated), and C (unmyelinated) fibers based on conduction velocity, and can be further divided according to their responsiveness to different modalities and intensities of stimulation. The spinal dorsal horn is divided into laminae (indicated along left margin). Different types of afferents terminate in different laminae. HTMR, high-threshold mechanoreceptor. LTMR, low-threshold mechanoreceptor. Modified from [45].

Figure 2. Classification of neurons in the superficial dorsal horn

Left column shows sample spiking patterns elicited by current injection into the cell body. Right column shows cartoon representation of differences in dendritic morphology.

Figure 3. Circuitry in the superficial dorsal horn

Summary of what is currently known about synaptic input to and connectivity between different types of spinal neurons based primarily on paired recording data [49,63,71,73]. Notably, ref. reports that tonic central cells receive input from TRPM8-expressing C fibers (which have fast conduction velocities relative to other C fibers) whereas ref reports that islet cells receive fast C fiber input (relative to transient central cells); this figure depicts the former results, which are arguably more definitive. Also, this figure does not depict input from Mrgprd-expressing C fibers to all cell types other than islet cells [77], input from TRPA1-expressing C fibers to excitatory interneurons [76], or input from Aβ fibers onto some inhibitory interneurons [78], not to mention the full extent of polsynaptic connections.

Figure 4. Putative microcircuits and their computational role

Motif 1: Pure labeled lines do not interact, meaning input a gives output A in the top pathway and input b gives output B in the bottom pathway even when inputs a and b are co-activated. Motif 2: Opponency is implemented by lateral inhibition, meaning output A is modulated by inhibition B′ and output B is modulated by inhibition A′ if inputs a and b are co-activated. Motif 3: Normalization is implemented when inputs a and b converge (perhaps via an excitatory interneuron; not shown) on an inhibitory interneuron whose output A′+B′ modulates outputs A and B. Motif 4: Mixing is implemented by an excitatory interneuron relaying excitation B* to the top circuit, which, if combined with polysynaptic inhibition B′, would give output (A+B*)/B′. This is the first example in which two letters occur in the numerator of the output, which is to say that the labeled line has been corrupted. Motif 5: Coloring is implemented when an excitatory interneuron’s output C indicates that input a and b have occurred together. Output C thus gives context to, or “colors”, outputs A and B. In this example, the excitatory interneuron must behave as a coincidence detector. See text for additional discussion.