A novel sequence to improve auditory functional MRI with variable silent delays.

PURPOSE: Auditory functional MRI (fMRI) often uses silent inter-volume delays for stimulus presentation. However, maintaining the steady-state of the magnetization usually requires constant delays. Here, a novel acquisition scheme dubbed "pre-Saturated EPI using Multiple delays in Steady-state" (SEPIMS) is proposed, using spin saturation at a fixed delay before each volume to maintain steady-state conditions, independent of previous spin history. This concept allows for variable inter-volume delays and thus for flexible stimulus design in auditory fMRI. The purpose was to compare the signal stability of SEPIMS and conventional sparse EPI (CS-EPI). METHODS: The saturation module comprises two non-selective adiabatic saturation pulses. The efficiency of the saturation and its effect on the SEPIMS signal stability is tested in vitro and in vivo. RESULTS: Data show that SEPIMS yields the same signal stability as CS-EPI, even for extreme variations between inter-volume delay durations. However, dual saturation pulses are required to achieve sufficiently high saturation efficiency in compartments with long T1 values. Importantly, spoiler gradient pulses after the EPI readout have to be optimized to avoid eddy-current-induced image distortions. CONCLUSION: The proposed SEPIMS sequence maintains high signal stability in the presence of variable inter-volume durations, thus allowing for flexible stimulus design.

Sparse imaging and reconstruction tomography for high-speed high-resolution whole-brain imaging.

Understanding brain functions requires detailed knowledge of long-range connectivity through which different areas communicate. A key step toward illuminating the long-range structures is to image the whole brain at synaptic resolution to trace axonal arbors of individual neurons to their termini. However, high-resolution brain-wide imaging requires continuous imaging for many days to sample over 10 trillion voxels, even in the mouse brain. Here, we have developed a sparse imaging and reconstruction tomography (SMART) system that allows brain-wide imaging of cortical projection neurons at synaptic resolution in about 20 h, an order of magnitude faster than previous methods. Analyses of morphological features reveal that single cortical neurons show remarkable diversity in local and long-range projections, with prefrontal, premotor, and visual neurons having distinct distribution of dendritic and axonal features. The fast imaging system and diverse projection patterns of individual neurons highlight the importance of high-resolution brain-wide imaging in revealing full neuronal morphology.

Spatial and spectral dynamics in STEM hyperspectral imaging using random scan patterns.

The evolution of the scanning modules for scanning transmission electron microscopes (STEM) allows now to generate arbitrary scan pathways, an approach currently explored to improve acquisition speed and to reduce electron dose effects. In this work, we present the implementation of a random scan operating mode in STEM achieved at the hardware level via a custom scan control module. A pre-defined pattern with fully shuffled raster order is used to sample the entire region of interest. Subsampled random sparse images can then be extracted at successive time frames, to which suitable image reconstruction techniques can be applied. With respect to the conventional raster scan mode, this method permits to limit dose accumulation effects, but also to decouple the spatial and temporal information in hyperspectral images. We provide some proofs of concept of the flexibility of the random scan operating mode, presenting examples of its applications in different spectro-microscopy contexts: atomically-resolved elemental maps with electron energy loss spectroscopy and nanoscale-cathodoluminescence spectrum images. By employing adapted post-processing tools, it is demonstrated that the method allows to precisely track and correct for sample instabilities and to follow spectral diffusion with a high spatial resolution.

Amplitude modified sparse imaging for damage detection in quasi-isotropic composite laminates using non-contact laser induced Lamb waves.

Composite structure is increasingly used in civil and aerospace applications due to its high mechanical performance. Lamb wave based sparse reconstruction imaging for damage localization is promising for structural health monitoring (SHM) and nondestructive evaluation (NDE) by using few measurements. However, this dictionary based method requires accurate atoms to represent Lamb wave propagating features in structure very well. Besides dispersion, signal changes caused by amplitude modulation should be considered for waveform distortion when constructing the dictionary for sparse imaging method. In this paper, a non-contact laser is used for Lamb wave excitation which exhibits a strong amplitude modulation in low frequency. Additionally, the strong attenuation resulting from material damping would also presents a distance-dependent amplitude modulation. To reconstruct an amplitude model of Lamb wave, the decomposition method of system response and attenuation is proposed. Then, the influence of amplitude modulation on signal representation is analyzed, which shows the restriction of dictionary without considering amplitude modulation. On this basis, the amplitude considered dictionary is built together with the phase considered dictionary for sparse imaging in terms of damage detection. Furthermore, according to Lamb wave reflection model, the solution for sparse reconstruction imaging is given. Finally, the performance of sparse imaging method is discussed by experimental investigation with different parameters. The results show the efficiency of the proposed method with improved imaging performance and give comparisons for better parameter choice.

Tomographic Collection of Block-Based Sparse STEM Images: Practical Implementation and Impact on the Quality of the 3D Reconstructed Volume.

The reduction of the electron dose in electron tomography of biological samples is of high significance to diminish radiation damages. Simulations have shown that sparse data collection can perform efficient electron dose reduction. Frameworks based on compressive-sensing or inpainting algorithms have been proposed to accurately reconstruct missing information in sparse data. The present work proposes a practical implementation to perform tomographic collection of block-based sparse images in scanning transmission electron microscopy. The method has been applied on sections of chemically-fixed and resin-embedded Trypanosoma brucei cells. There are 3D reconstructions obtained from various amounts of downsampling, which are compared and eventually the limits of electron dose reduction using this method are explored.

Frequency-dependent auditory space representation in the human planum temporale.

Functional magnetic resonance imaging (fMRI) findings suggest that a part of the planum temporale (PT) is involved in representing spatial properties of acoustic information. Here, we tested whether this representation of space is frequency-dependent or generalizes across spectral content, as required from high order sensory representations. Using sounds with two different spectral content and two spatial locations in individually tailored virtual acoustic environment, we compared three conditions in a sparse-fMRI experiment: Single Location, in which two sounds were both presented from one location; Fixed Mapping, in which there was one-to-one mapping between two sounds and two locations; and Mixed Mapping, in which the two sounds were equally likely to appear at either one of the two locations. We surmised that only neurons tuned to both location and frequency should be differentially adapted by the Mixed and Fixed mappings. Replicating our previous findings, we found adaptation to spatial location in the PT. Importantly, activation was higher for Mixed Mapping than for Fixed Mapping blocks, even though the two sounds and the two locations appeared equally in both conditions. These results show that spatially tuned neurons in the human PT are not invariant to the spectral content of sounds.