Prior experience modulates top-down predictive processing in the ventral visual areas

Repetition suppression(RS)refers to that the reduction of neural activities for repeated presentations of a given stimulus compared to its first presentation. Summerfield et al(2008) found the magnitude of RS is affected by the repetition probability of stimuli, called as P(rep) effect. Based on the predictive coding theory, prior experience about the sensory inputs is necessary to optimally achieve cognitive processes. But it remains unclear how prior experience modulates predictive processes. To address this issue, in Study I, we estimated the P(rep) effects for Chinese characters and German words in native Chinese and German participants to test whether prior experience affects the P(rep) effect of lexical stimuli. The results showed that the P(rep) effect is only manifest for words of a language with which participants had prior experience. Study II performed fMRI measurements before and after a 10-day perceptual learning (PL) training for cars to test the modulation of short-term experience on the P(rep) effect. The results replicated the P(rep) effect for faces and cars. More interestingly, the P(rep) effect can be temporarily abolished by the short-term PL experience. The third study investigated how prior experience modulates sensory inputs. Study 3a adopted a classic stimulus repetition paradigm to measure RS for faces, together with either concurrent short-term memory (STM) load or a control condition. The results showed that RS is significantly attenuated when visual STM is loaded. Study 3b manipulates attention by a face inversion detection task. The results showed that the RS effect appears in the STM condition when participants attend to faces. The main conclusions: i) predictive processes, as measured by the P(rep) effect, require extensive prior experiences with stimuli, but ii) these can also be modulated by short-term learning experience. Further, iii) STM and attention are two modulators of prior experiences on predictive processes

Non-linear signal detection for molecular communications

Molecular communications convey information via diffusion propagation. The inherent long-tail channel response causes severe inter-symbol interference, which may seriously degrade signal detection performances. Traditional linear signal detection techniques, unfortunately, require both high complexity and a high signal-to-noise (SNR) ratio to operate. In this paper, we proposed a new non-linear signal processing paradigm inspired by the biological systems that achieves low-complexity signal detection even in low SNR regimes. First, we introduce a stochastic resonance inspired non-linear filtering scheme for molecular communications, and show that it significantly improves the output SNR by transforming the noise energy into useful signals. Second, we design a novel non-coherent detector by exploiting the transient features of molecular signaling, which are independent of channel response and involves only lowcomplexity linear summation operations. Numerical simulations show that this new scheme can improve the detection performance remarkably (approx. 7dB gain), even when compared against linearly optimal coherent methods. This is one of the first attempts to demodulate molecular signals from an entirely biological point of view, and the designed non-linear noncoherent paradigm will provide significant potential to the design and future implementation of nano-systems in noisy biological environments

In Situ Mechanical Characterization of the Mixed- Mode Fracture Strength of the Cu/Si Interface for TSV Structures

In situ nanoindentation experiments have been widely adopted to characterize material behaviors of microelectronic devices. This work introduces the latest developments of nanoindentation experiments in the characterization of nonlinear material properties of 3D integrated microelectronic devices using the through-silicon via (TSV) technique. The elastic, plastic, and interfacial fracture behavior of the copper via and matrix via interface were characterized using small-scale specimens prepared with a focused ion beam (FIB) and nanoindentation experiments. A brittle interfacial fracture was found at the Cu/Si interface under mixed-mode loading with a phase angle ranging from 16.7° to 83.7°. The mixed-mode fracture strengths were extracted using the linear elastic fracture mechanics (LEFM) analysis and a fracture criterion was obtained by fitting the extracted data with the power-law function. The vectorial interfacial strength and toughness were found to be independent with the mode-mix