Development of twitching in sleeping infant mice depends on sensory experience

Abstract

Myoclonic twitches are jerky movements that occur exclusively and abundantly during active (or REM) sleep in mammals, especially in early development [1-4]. In rat pups, limb twitches exhibit a complex spatiotemporal structure that changes across early development [5]. However, it is not known whether this developmental change is influenced by sensory experience, which is a prerequisite to the notion that sensory feedback from twitches not only activates sensorimotor circuits but modifies them [4]. Here, we investigated the contributions of proprioception to twitching in newborn ErbB2 conditional knockout mice that lack muscle spindles and grow up to exhibit dysfunctional proprioception [6-8]. High-speed videography of forelimb twitches unexpectedly revealed a category of reflex-like twitching-comprising an agonist twitch followed immediately by an antagonist twitch-that developed postnatally in wild-types/heterozygotes, but not in knockouts. Contrary to evidence from adults that spinal reflexes are inhibited during twitching [9-11], this finding suggests that twitches trigger the monosynaptic stretch reflex and, by doing so, contribute to its activity-dependent development [12-14]. Next, we assessed developmental changes in the frequency and organization (i.e., entropy) of more-complex, multi-joint patterns of twitching; again, wild-types/heterozygotes exhibited developmental changes in twitch patterning that were not seen in knockouts. Thus, targeted deletion of a peripheral sensor alters the normal development of local and global features of twitching, demonstrating that twitching is shaped by sensory experience. These results also highlight the potential use of twitching as a uniquely informative diagnostic tool for assessing the functional status of spinal and supraspinal circuits.

Figure 1. Frequency distributions of inter-twitch intervals for wild type, heterozygous, and knockout mice at 4 and 10 days of age

Inter-twitch intervals were restricted to one of two movement categories. For each category, the first twitch of a pair could occur at any joint, whereas the second immediately succeeding twitch was (A) an antagonist twitch (e.g., right elbow flexion → right elbow extension) or (B) a repeat of the first twitch (e.g., right elbow flexion → right elbow flexion). Frequencies were normalized over the 150-ms window. P4: Ns = 3995–6931 ITIs; P10: Ns = 1784–2131 ITIs.

Figure 2. Mean latencies and likelihoods for (A) agonist-antagonist and (B) agonist-agonist twitch pairs in wild type, heterozygous, and knockout mice at 4 (P4) and 10 (P10) days of age

These movement categories correspond to those in Figure 1. Mean latencies between twitch pairs were calculated over 150-ms windows (and thus are longer than the peak latencies observed in Figure 1) and mean likelihoods of each pair were calculated over a 0- to 50-ms window. Means were calculated across individual pups (N = 7–11 pups per group). * significant difference from both WT and Het; † significant difference from WT only. Mean + SEM.

Figure 3. Perievent histograms comparing temporal pairwise relationships for agonist-antagonist (red) and agonist-agonist (black) twitches for wild type, heterozygous, and knockout mice at 4 and 10 days of age

Perievent histograms were computed from data pooled across subjects. Significant bins for the agonist-antagonist plots are indicated by upper and lower confidence bands (solid and dashed black lines; p < 0.01). The agonist-agonist perievent histograms exhibit mirror imaging because they are auto-correlations. See Supplemental Experimental Procedures for details.

Figure 4. Regression analyses of LCA cluster frequency (freq) and entropy for (A) wild type, (B) heterozygous, and (C) knockout mice at 4 (P4) and 10 (P10) days of age

Correlation coefficients (r) in red are statistically significant (p < 0.05) and the width of each connecting line is scaled to the magnitude of r.