Neurodevelopmental Preparedness for Language in the Neonatal Brain

Neonates show broad-based, universal speech perception abilities, allowing them to acquire any language. Moreover, an increasing body of research shows that prenatal experience with speech, which is a low-pass signal mainly preserving prosody, already shapes those abilities. In this review, we first provide a summary of the empirical evidence available today on newborns’ universal and experience-modulated speech perception abilities. We then interpret these findings in a new framework, focusing on the role of the prenatal prosodic experience in speech perception development. We argue that the chronological sequence of infants’ experience with speech, starting before birth with a low-pass filtered signal and continuing with the full-band signal after birth, sets up the prosodic hierarchy and a cascade of embedded neural oscillations as its brain correlate, laying the foundations for language acquisition. Prosody, constituting infants’ very first experience with language, may thus play a fundamental role in speech perception and language development.

FM-CW compact reflectometer using DDS signal generation

A prototype of a compact coherent fast frequency sweeping RF back-end is being developed at IPFN-IST using commercial Monolithic Microwave Integrated Circuits (MMIC). On this work we present the usability of this concept of compact reflectometry associated with a Direct Digital Synthesis (DDS) source. Flexibility is one of the design goals for the back-end prototype, so that it can easily match the required frequency range. The backend alone covers the NATO J-band (10 GHz to 20 GHz) and is designed to drive external full band frequency multipliers, resulting in an ultra-wideband coverage of up to 140 GHz. FM-CW radar precision is strongly dependent on the probing source linearity. DDS nowadays plays an important role in signal generation in many fields of applications for communication systems as well as in radar technology. Modern DDSs are fully integrated, low-cost, single chip solutions that only need an external clock source for generating sinusoidal output signals up to several gigahertz. The DDS benefits from the totally digital generation of the output signal, which allows full control of the signal’s frequency and phase, both with very high precision and resolution. Recent implementations feature automatic sweeping capability, thus allowing the DDS to generate very linear and agile frequency chirps, assuming a high quality and constant frequency reference clock source. We propose to implement a DDS signal generation solution with the capability of a full band sweep in 1 μs. On the receiver side the IF and reference signals will be digitised allowing the use of high flexible data processing techniques. Input/output signals will allow the synchronisation of several systems.

Update to the dataset of cerebral ischemia in juvenile pigs with evoked potentials

We expand from a spontaneous to an evoked potentials (EP) data set of brain electrical activities as electrocorticogram (ECoG) and electrothalamogram (EThG) in juvenile pig under various sedation, ischemia and recovery states. This EP data set includes three stimulation paradigms: auditory (AEP, 40 and 2000 Hz), sensory (SEP, left and right maxillary nerve) and high-frequency oscillations (HFO) SEP. This permits derivation of electroencephalogram (EEG) biomarkers of corticothalamic communication under these conditions. The data set is presented in full band sampled at 2000 Hz. We provide technical validation of the evoked responses for the states of sedation, ischemia and recovery. This extended data set now permits mutual inferences between spontaneous and evoked activities across the recorded modalities. Future studies on the dataset may contribute to the development of new brain monitoring technologies, which will facilitate the prevention of neurological injuries.

Research on Detection Method of Pea Seed Vigor based on Hyperspectral Imaging Technology

Rapid and noninvasive detection methods of seed vigor, an important index to evaluate seed quality, have been the research focus in recent years. In this paper, the detection method of pea seed vigor based on hyperspectral imaging technology was researched. First, the spectral images of different vigor grade samples with artificial aging were captured, and the original spectrum was pretreated with multiple scattering correction. Secondly, SPA and PCA were used to select respective bands. Finally, PLS-DA and LS-SVM model were established to identify the seed vigor of the pea seed, based on the whole band spectrum, the characteristic bands extracted by SPA and PCA respectively. The results showed that PLS-DA and LS-SVM models are effective, but LS-SVM had better performance. Through comparison, the method using full band spectrum was more accurate, the efficiency of method using 5 characteristic bands extracted by PCA was the highest while the way of extracting the representative band by SPA was the most meaningful to this study which achieved similar accuracy to the full band with only 20 bands. The SPA-LS-SVM method afforded the recognition accuracy (100%) for modeling set and validation set used to determine the vigor of pea seeds. The overall results suggest that hyperspectral imaging technology is useful for classification of different vitality pea seeds with non-destructive manner, which can provide a basis for further development of online scoring devices