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Interactions between the body and the environment are dynamically modulated by upcoming sensory information and motor execution. To adapt to this behavioral state-shift, brain activity must also be flexible and possess a large repertoire of brain networks so as to switch them flexibly. Recently, flexible internal brain communications, i.e. brain network flexibility, have come to be recognized as playing a vital role in integrating various sensorimotor information. Therefore, brain network flexibility is one of the key factors that define sensorimotor skill. However, little is known about how flexible communications within the brain characterize the interindividual variation of sensorimotor skill and trial-by-trial variability within individuals. To address this, we recruited skilled musical performers and used a novel approach that combined multichannel-scalp electroencephalography, behavioral measurements of musical performance, and mathematical approaches to extract brain network flexibility. We found that brain network flexibility immediately before initiating the musical performance predicted interindividual differences in the precision of tone timbre when required for feedback control, but not for feedforward control. Furthermore, brain network flexibility in broad cortical regions predicted skilled musical performance. Our results provide novel evidence that brain network flexibility plays an important role in building skilled sensorimotor performance.

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Two-dimensional (vertical and horizontal) vibrations of a wedge-type probe upon food rupture were evaluated separately using two accelerometers placed perpendicular to a guide rod of a swing-arm device for texture evaluation of the flesh of three varieties of apples and three types of potato chips. Voltage signals from the accelerometers were filtered using a half-octave band-pass filter. The energy texture index (ETI), based on kinetic energy of the vertical or horizontal probe vibrations, was calculated over low to high frequency bands (no. 1-21). The spectra for the flesh of the three varieties of apples included two common peaks for vertical ETI at band no. 11 (1,120-1,600 Hz) and 19 (17,920-25,600 Hz) and horizontal ETI at band no. 1 (0-10 Hz) and 15 (4,480-6,400 Hz). The spectra for the three types of potato chips had a common ETI peak at band no. 11 (1,120-1,600 Hz) for horizontal ETI and at no. 15 (4,480-6,400 Hz) for vertical ETI. The three apple varieties gave rise to different intensities of vertical and horizontal ETIs while the two peaks were maintained. The thick potato chip type had higher vertical and horizontal ETIs than the thin and soft varieties in most bands; however, the thin type had the highest vertical ETIs only in lower bands (0-200 Hz). The soft type had the lowest vertical and horizontal ETI. The above results suggest that different food textures can be distinguished by two-dimensional vibration analyses of probe insertion into a food sample based on frequency bands.

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In human fingertips, the fingerprint patterns and interlocked epidermal-dermal microridges play a critical role in amplifying and transferring tactile signals to various mechanoreceptors, enabling spatiotemporal perception of various static and dynamic tactile signals. Inspired by the structure and functions of the human fingertip, we fabricated fingerprint-like patterns and interlocked microstructures in ferroelectric films, which can enhance the piezoelectric, pyroelectric, and piezoresistive sensing of static and dynamic mechanothermal signals. Our flexible and microstructured ferroelectric skins can detect and discriminate between multiple spatiotemporal tactile stimuli including static and dynamic pressure, vibration, and temperature with high sensitivities. As proof-of-concept demonstration, the sensors have been used for the simultaneous monitoring of pulse pressure and temperature of artery vessels, precise detection of acoustic sounds, and discrimination of various surface textures. Our microstructured ferroelectric skins may find applications in robotic skins, wearable sensors, and medical diagnostic devices.