This study investigated the effects of stochastic facilitation in healthy subjects with normal and low auditory working memory capacity (AWMC). Forty healthy volunteers were recruited in this study. They performed a backward recall task (BRT) in quiet and under four white noise intensity levels: 45, 50, 55, and 60 dB. Brain activations during the task were measured using functional magnetic resonance imaging (fMRI). The behavioral performance in both groups increased significantly in 50 and 55 dB white noise. The normal AWMC group (mean score = 48.70) demonstrated higher activation in the superior temporal gyrus and prefrontal cortex than the low AWMC group (mean score = 30.85). However, comparisons in the brain activation between groups for all noise levels were not statistically different. The results support previous findings that stochastic facilitation enhances cognitive performance in healthy individuals. The results also proposed that brain activity among healthy subjects is more or less similar, at least in the context of auditory working memory. These findings indicated that there were no differential effects of stochastic facilitation in healthy subjects with different AWMC.
Many studies have been carried out to produce magnetic resonance imaging (MRI) phantoms as alternative to water phantom. Among the important properties of a phantom are the T1 and T2 relaxation times. The objective of this study is to investigate the T1 and T2 characteristics of the agarose gel phantoms with different relaxation modifier (gadolinium (III) oxide, Gd2O3) concentrations or [Gd2O3]. Six agarose gel phantoms were prepared with different [Gd2O3]. The T1 (fixed echo time (TE) and different repetition time (TR)) and T2 (fixed TR and different TE) measurements on all phantoms were conducted using the 3-T MRI system via spin echo (SE) and turbo spin echo (TSE) sequences, respectively. The signal-to-noise ratio (SNR) of all phantoms was calculated using Image-J software by implementing the region of interest (ROI) analysis. The SNR against TR and SNR against TE curves were fitted to the exponential equations for saturation, T1 and T2 determination. For every phantom, T1 curve demonstrated that the SNR increased exponentially with increasing TR, while T2 curves showed that the SNR decreased exponentially with increasing TE. Gd2O3 was found to successfully act as the relaxation modifier for the T1 but not the T2 curves. The T1 curve started to show saturated SNR (SNRo) and increasing SNRo for TR > 1000 ms and [Gd2O3] = 0.005 g/ml or higher. These behaviours are explained based on the dipole-dipole interaction that increases in phantoms with higher [Gd2O3], thus shortening the T1 relaxation. However, a systematic change in the T2 parameters with increasing [Gd2O3] was not observed. While Gd2O3 has significant effects on T1 relaxation parameters, the T2 relaxation parameters were minimally affected. With a shorter T1, the Gd2O3 added agarose gel can potentially be used as test phantom in fast imaging sequence, e.g. gradient echo pulse sequences.
The connectivity patterns among the DMN nodes when the brain is resting are still in great debate. Among the unknowns is whether a dominant node exists in the network and if any, how does it influences the other nodes. Resting state functional magnetic resonance imaging (rsfMRI) was utilized in data acquisition on 25 healthy male and female participants. The DMN nodes selected were posterior cingulate cortex (PCC), bilateral inferior parietal cortex (IPL) and medial prefrontal cortex (mPFC). Fully connected causal models were constructed comprising four DMN nodes. The time invariant covariance of the random fluctuations between nodes was then estimated to obtain the effective connectivity (EC) between the DMN nodes. The EC values among the DMN nodes were averaged over the participants using Bayesian Parameter Averaging (BPA). All the DMN nodes have self-inhibitory dynamics. All connections between nodes were significant (P > 0.9) with a condition for any of the two nodes, one node inhibited the others. The PCC which exhibited the highest signal intensity was in fact inhibited by others. Inter-hemispheric RIPC to LIPC connections acted the same way, with excitatory LIPC to RIPC and inhibitory RIPC to LIPC connections. The results also showed a stronger mPFC to RIPC connection in the right hemisphere (as compared to mPFC to LIPC connection in the left hemisphere) and a weaker PCC to RIPC connection in the right hemisphere (as compared to PCC to LIPC connection in the left hemisphere). PCC can be regarded as a dominant node among the four nodes, being connected to all other nodes in different ways. All the four nodes were significantly activated and connected to each other even though the brain was in a state of resting.