Spinal motoneurons of the human newborn are highly synchronized during leg movements

Motoneurons of neonatal rodents show synchronous activity that modulates the development of the neuromuscular system. However, the characteristics of the activity of human neonatal motoneurons are largely unknown. Using a noninvasive neural interface, we identified the discharge timings of individual spinal motoneurons in human newborns. We found highly synchronized activities of motoneurons of the tibialis anterior muscle, which were associated with fast leg movements. Although neonates’ motor units exhibited discharge rates similar to those of adults, their synchronization was significantly greater than in adults. Moreover, neonatal motor units showed coherent oscillations in the delta band, which is directly translated into force generation. These results suggest that motoneuron synchronization in human neonates might be an important mechanism for controlling fast limb movements, such as those of primitive reflexes. In addition to help revealing mechanisms of development, the proposed neural interface might monitor children at risk of developing motor disorders.

Chirp analyzer for estimating amplitude and latency of steady-state auditory envelope following responses

The envelope following response (EFR) is a scalp-recorded evoked potential elicited by carrier tones or noise, modulated in amplitude with a continuous sweep of modulation frequencies. This non-stationary response reflects the phase-locked neural activity of the auditory pathway to the temporal envelope of sounds and has been commonly assessed by fixed-frequency methods based on the discrete Fourier transform, such as the Fourier Analyzer (FA). In this work, we study the estimation of the EFR with the use of explicit time-frequency methods, which offer more information about the energy distribution of the recorded signal, such as the Short-Term Fourier Transform (STFT) and the Morlet Continuous Wavelet Transform (CWT). We further introduce the Chirp Analyzer (CA), which is similar to FA, but using as basis function the same linear chirp that amplitude-modulates the carrier stimulus. In a direct comparison using controlled simulated responses, the CA showed to be able to estimate the correct EFR amplitudes, without the typical bias offered by the estimation using STFT (equivalent to FA) and more robust to noise than the CWT method, although with higher sensitivity to the presence of a delay in the response with respect to the stimulus. For addressing the latter issue, we also propose here a novel methodology for estimating the apparent latency of the response. This method proved to be reliable when using the STFT and the CA methods, as assessed using simulated responses. The estimation of the EFR amplitude with any of the methods, but especially with CA, should be corrected by using the estimated delay when possible. An illustrative application of these methods to small datasets of a rat and a human newborn, suggested that all time-frequency methods can be used to study the EFR amplitudes in a wide range of modulation frequencies, but they should be interpreted in the light of the limitations shown in the simulation studies.

Ancient of Days The Vocal Pattern as Primordial Big Bang of Communication

Familiar voice recognition appeared on the earth 250 million years ago with the advent of frogs. Interestingly, air breathing and vocalization coemerged in the amphibian, as they do as first gesture in the human newborn, suggesting that the larynx was designed to serve these two functions with equal commitment. Establishing a repertory of familiar voices plays a crucial role across biological species, enabling identification of family, friend, and foe in the distance and at night. All voices, familiar and unfamiliar, transmit a cornucopia of data about the speaker, a capability which began simply and has flourished prodigiously in the human to include gender, age, size, sexual preference, socioeconomic and geographical background, mood, emotion, linguistic meanings, pragmatic communication, attitude, and psychiatric state. Considering that vocal information draws on an immense range of human behaviour, one can conclude that it takes a whole brain to produce and perceive a voice pattern.