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Mikutta, C.

Publications and source records attributed to Mikutta, C..

2 recordsLinked to original sources

Detection of neuronal OFF periods as low amplitude neural activity segments

During non-rapid eye movement sleep (NREM), synchronised neuronal activity is reflected in a specific neural oscillation observed in neocortical electrophysiological signals: a low frequency component characterised by depth-positive/surface-negative potentials known as slow waves, corresponding to alternating periods of high (ON period) and low (OFF period) spiking activity. Often overlooked in favour of slow waves, there is an interest in understanding how neuronal silencing during OFF periods leads to the generation of slow waves and whether this relationship changes between cortical layers. The foremost issue in detecting population OFF periods is the absence of a formal, widely adopted definition. Here, we grouped segments of high frequency neural activity containing spikes, recorded from the neocortex, on the basis of amplitude and asked whether the population of low amplitude (LA) segments displayed the expected characteristics of OFF periods. We corroborate previous studies showing that LA segments in neural activity signals are a uniquely identifiable structure with distinct characteristics from the surrounding signal that identify them as OFF periods including NREM sleep predominance and association with a local field potential (LFP) slow wave. In addition, we attribute new characteristics to these segments not previously associated with OFF periods: vigilance-state-dependent duration and duration-dependent homeostatic response. This could suggest that ON/OFF periods are currently underdefined, and their appearance is less binary than previously considered, instead representing a continuum.

neuroscience↗

Neural Encoding of Auditory Features during Music Perception and Imagery: Insight into the Brain of a Piano Player

It remains unclear how the human cortex represents spectrotemporal sound features during auditory imagery, and how this representation compares to auditory perception. To assess this, we recorded electrocorticographic signals from an epileptic patient with proficient music ability in two conditions. First, the participant played two piano pieces on an electronic piano with the sound volume of the digital keyboard on. Second, the participant replayed the same piano pieces, but without auditory feedback, and the participant was asked to imagine hearing the music in his mind. In both conditions, the sound output of the keyboard was recorded, thus allowing precise time-locking between the neural activity and the spectrotemporal content of the music imagery. For both conditions, we built encoding models to predict high gamma neural activity (70-150Hz) from the spectrogram representation of the recorded sound. We found robust similarities between perception and imagery - in frequency and temporal tuning properties in auditory areas.\n\nAbbreviations

neuroscience↗