Towards reconstructing intelligible speech from the human auditory cortex, bioRxiv, 2018-06-19
AbstractAuditory stimulus reconstruction is a technique that finds the best approximation of the acoustic stimulus from the population of evoked neural activity. Reconstructing speech from the human auditory cortex creates the possibility of a speech neuroprosthetic to establish a direct communication with the brain and has been shown to be possible in both overt and covert conditions. However, the low quality of the reconstructed speech has severely limited the utility of this method for brain-computer interface (BCI) applications. To advance the state-of-the-art in speech neuroprosthesis, we combined the recent advances in deep learning with the latest innovations in speech synthesis technologies to reconstruct closed-set intelligible speech from the human auditory cortex. We investigated the dependence of reconstruction accuracy on linear and nonlinear (deep neural network) regression methods and the acoustic representation that is used as the target of reconstruction, including auditory spectrogram and speech synthesis parameters. In addition, we compared the reconstruction accuracy from low and high neural frequency ranges. Our results show that a deep neural network model that directly estimates the parameters of a speech synthesizer from all neural frequencies achieves the highest subjective and objective scores on a digit recognition task, improving the intelligibility by 65% over the baseline method which used linear regression to reconstruct the auditory spectrogram. These results demonstrate the efficacy of deep learning and speech synthesis algorithms for designing the next generation of speech BCI systems, which not only can restore communications for paralyzed patients but also have the potential to transform human-computer interaction technologies.
biorxiv neuroscience 0-100-users 2018Re-identification of genomic data using long range familial searches, bioRxiv, 2018-06-18
AbstractConsumer genomics databases reached the scale of millions of individuals. Recently, law enforcement investigators have started to exploit some of these databases to find distant familial relatives, which can lead to a complete re-identification. Here, we leveraged genomic data of 600,000 individuals tested with consumer genomics to investigate the power of such long-range familial searches. We project that half of the searches with European-descent individuals will result with a third cousin or closer match and will provide a search space small enough to permit re-identification using common demographic identifiers. Moreover, in the near future, virtually any European-descent US person could be implicated by this technique. We propose a potential mitigation strategy based on cryptographic signature that can resolve the issue and discuss policy implications to human subject research.
biorxiv genomics 500+-users 2018Altering the temporal regulation of one transcription factor drives sensory trade-offs, bioRxiv, 2018-06-16
SUMMARYSize trade-offs of visual versus olfactory organs is a pervasive feature of animal evolution. Comparing Drosophila species, we find that larger eyes correlate with smaller antennae, where olfactory organs reside, and narrower faces. We demonstrate that this tradeoff arises through differential subdivision of the head primordium into visual versus non-visual fields. Specification of the visual field requires a highly-conserved eye development gene called eyeless in flies and Pax6 in humans. We discover that changes in the temporal regulation of eyeless expression during development is a conserved mechanism for sensory trade-offs within and between Drosophila species. We identify a natural single nucleotide polymorphism in the cis-regulatory region of eyeless that is sufficient to alter its temporal regulation and eye size. Because Pax6 is a conserved regulator of sensory placode subdivision, we propose that alterations in the mutual repression between sensory territories is a conserved mechanism for sensory trade-offs in animals.
biorxiv developmental-biology 0-100-users 2018Enzymatic DNA synthesis for digital information storage, bioRxiv, 2018-06-16
AbstractDNA is an emerging storage medium for digital data but its adoption is hampered by limitations of phosphoramidite chemistry, which was developed for single-base accuracy required for biological functionality. Here, we establish a de novo enzymatic DNA synthesis strategy designed from the bottom-up for information storage. We harness a template-independent DNA polymerase for controlled synthesis of sequences with user-defined information content. We demonstrate retrieval of 144-bits, including addressing, from perfectly synthesized DNA strands using batch-processed Illumina and real-time Oxford Nanopore sequencing. We then develop a codec for data retrieval from populations of diverse but imperfectly synthesized DNA strands, each with a ~30% error tolerance. With this codec, we experimentally validate a kilobyte-scale design which stores 1 bit per nucleotide. Simulations of the codec support reliable and robust storage of information for large-scale systems. This work paves the way for alternative synthesis and sequencing strategies to advance information storage in DNA.
biorxiv synthetic-biology 100-200-users 2018Live Mouse Tracker real-time behavioral analysis of groups of mice, bioRxiv, 2018-06-14
Preclinical studies of psychiatric disorders require the use of animal models to investigate the impact of environmental factors or genetic mutations on complex traits such as decision-making and social interactions. Here, we present a real-time method for behavior analysis of mice housed in groups that couples computer vision, machine learning and Triggered-RFID identification to track and monitor animals over several days in enriched environments. The system extracts a thorough list of individual and collective behavioral traits and provides a unique phenotypic profile for each animal. On mouse models, we study the impact of mutations of genes Shank2 and Shank3 involved in autism. Characterization and integration of data from behavioral profiles of mutated female mice reveals distinctive activity levels and involvement in complex social configuration.
biorxiv animal-behavior-and-cognition 100-200-users 2018Real-time cryo-EM data pre-processing with Warp, bioRxiv, 2018-06-14
The acquisition of cryo-electron microscopy (cryo-EM) data from biological specimens is currently largely uncoupled from subsequent data evaluation, correction and processing. Therefore, the acquisition strategy is difficult to optimize during data collection, often leading to suboptimal microscope usage and disappointing results. Here we provide Warp, a software for real-time evaluation, correction, and processing of cryo-EM data during their acquisition. Warp evaluates and monitors key parameters for each recorded micrograph or tomographic tilt series in real time. Warp also rapidly corrects micrographs for global and local motion, and estimates the local defocus with the use of novel algorithms. The software further includes a deep learning-based particle picking algorithm that rivals human accuracy to make the pre-processing pipeline truly automated. The output from Warp can be directly fed into established tools for particle classification and 3D image reconstruction. In a benchmarking study we show that Warp automatically processed a published cryo-EM data set for influenza virus hemagglutinin, leading to an improvement of the nominal resolution from 3.9 Å to 3.2 Å. Warp is easy to install, computationally inexpensive, and has an intuitive and streamlined user interface.
biorxiv biophysics 0-100-users 2018