Musicianship and neural synchronization at multiple timescales

Auditory events can be considered to have spectral energy at short and long timescales, corresponding to the musical phenomena of pitch and pulse. Neural synchronization—when neurons synchronize their firing with external oscillatory stimuli—can be measured using spectral EEG at both subcortical and cortical levels. It has been shown that subcortical synchronization to tones is more robust in musicians than nonmusicians, suggesting a type of experience-dependent plasticity; a similar test for long timescales has not been investigated. In the current study, EEG was measured from musicians and nonmusicians while they listened to an isochronous sequence of tones. Neural synchronization at short timescales was found to be stronger in musicians. Additionally, the extent of synchronization correlated with the current level of musical engagement. These findings indicate that the experience-dependent plasticity observed in musicians manifests itself at multiple cortical levels corresponding to oscillations at different timescales present in music.

Musicianship and neural synchronization at multiple timescales

Auditory events can be considered to have spectral energy at short and long timescales, corresponding to the musical phenomena of pitch and pulse. Neural synchronization—when neurons synchronize their firing with external oscillatory stimuli—can be measured using spectral EEG at both subcortical and cortical levels. It has been shown that subcortical synchronization to tones is more robust in musicians than nonmusicians, suggesting a type of experience-dependent plasticity; a similar test for long timescales has not been investigated. In the current study, EEG was measured from musicians and nonmusicians while they listened to an isochronous sequence of tones. Neural synchronization at short timescales was found to be stronger in musicians. Additionally, the extent of synchronization correlated with the current level of musical engagement. These findings indicate that the experience-dependent plasticity observed in musicians manifests itself at multiple cortical levels corresponding to oscillations at different timescales present in music.

VIP neurons desynchronize cortical assemblies

Neural synchronization on fast timescales has been linked to critical aspects of sensation, cognition and action, and impairments in synchronization are associated with neurological disease. Although the strength and spatial scale of neural synchronization varies dramatically with sensory and behavioral context, the circuit mechanisms that regulate the magnitude and spatial spread of neural oscillations are largely unknown. As in humans, monkeys, and cats, we found that in the mouse primary visual cortex (V1) the stimulus properties and behavioral state powerfully modulate gamma band synchronization. To reveal the underlying circuit that mediates this dependence, we used multi-site multi-electrode electrophysiology and cell type specific optogenetic suppression of vasoactive intestinal peptide (VIP) interneurons in awake mice. Our results show that VIP neurons potently control the gain and behavioral state-dependence of gamma band network synchronization by desynchronizing local and global networks on fine time scales. Importantly, VIP neurons preferentially decouple spatially separated cortical ensembles when they are processing non-matched stimulus features. Based on these data, we propose that cortical disinhibition by VIP interneurons fine-tunes the strength and spatial architecture of gamma-oscillating neural assemblies, which may facilitate the downstream generation of coherent visual percepts.

Mutual learning-based efficient synchronization of neural networks to exchange the neural key

Synchronization of two neural networks through mutual learning is used to exchange the key over a public channel. In the absence of a weight vector from another party, the key challenge with neural synchronization is how to assess the coordination of two communication parties. There is an issue of delay in the current techniques in the synchronization assessment that has an impact on the security and privacy of the neural synchronization. In this paper, to assess the complete coordination of a cluster of neural networks more efficiently and timely, an important strategy for assessing coordination is presented. To approximately determine the degree of synchronization, the frequency of the two networks having the same output in prior iterations is used. The hash is used to determine if both the networks are completely synchronized exactly when a certain threshold is crossed. The improved technique makes absolute coordination between two communication parties using the weight vectors’ has value. In contrast, with existing approaches, two communicating parties who follow the proposed approach will detect complete synchronization sooner. This reduces the effective geometric likelihood. The proposed method, therefore, increases the safety of the protocol for neural key exchange. This proposed technique has been passed through different parametric tests. Simulations of the process show effectiveness in terms of cited results in the paper.