Reach errors may be broadly classified into errors arising from unpredictable changes in target location, called target errors, and errors arising from miscalibration of internal models (e.g., when prisms alter visual feedback or a force field alters limb dynamics), called execution errors. Execution errors may be caused by miscalibration of dynamics (e.g., when a force field alters limb dynamics) or by miscalibration of kinematics (e.g., when prisms alter visual feedback). Although all types of errors lead to similar on-line corrections, we found that the motor system showed strong trial-by-trial adaptation in response to random execution errors but not in response to random target errors. We used functional magnetic resonance imaging and a compatible robot to study brain regions involved in processing each kind of error. Both kinematic and dynamic execution errors activated regions along the central and the postcentral sulci and in lobules V, VI, and VIII of the cerebellum, making these areas possible sites of plastic changes in internal models for reaching. Only activity related to kinematic errors extended into parietal area 5. These results are inconsistent with the idea that kinematics and dynamics of reaching are computed in separate neural entities. In contrast, only target errors caused increased activity in the striatum and the posterior superior parietal lobule. The cerebellum and motor cortex were as strongly activated as with execution errors. These findings indicate a neural and behavioral dissociation between errors that lead to switching of behavioral goals and errors that lead to adaptation of internal models of limb dynamics and kinematics.

Adaptation is sometimes viewed as a process in which the nervous system learns to predict and cancel effects of a novel environment, returning movements to near baseline (unperturbed) conditions. An alternate view is that cancellation is not the goal of adaptation. Rather, the goal is to maximize performance in that environment. If performance criteria are well defined, theory allows one to predict the reoptimized trajectory. For example, if velocity-dependent forces perturb the hand perpendicular to the direction of a reaching movement, the best reach plan is not a straight line but a curved path that appears to overcompensate for the forces. If this environment is stochastic (changing from trial to trial), the reoptimized plan should take into account this uncertainty, removing the overcompensation. If the stochastic environment is zero-mean, peak velocities should increase to allow for more time to approach the target. Finally, if one is reaching through a via-point, the optimum plan in a zero-mean deterministic environment is a smooth movement but in a zero-mean stochastic environment is a segmented movement. We observed all of these tendencies in how people adapt to novel environments. Therefore, motor control in a novel environment is not a process of perturbation cancellation. Rather, the process resembles reoptimization: through practice in the novel environment, we learn internal models that predict sensory consequences of motor commands. Through reward-based optimization, we use the internal model to search for a better movement plan to minimize implicit motor costs and maximize rewards.

No abstract

Digital nucleic acid detection is rapidly becoming a popular technique for ultra-sensitive and quantitative detection of nucleic acid molecules in a wide range of biomedical studies. Digital polymerase chain reaction (PCR) remains the most popular way of conducting digital nucleic acid detection. However, due to the need for thermocycling, digital PCR is difficult to implement in a streamlined manner on a single microfluidic device, leading to complex fragmented workflows and multiple separate devices and instruments. Loop-mediated isothermal amplification (LAMP) is an excellent isothermal alternative to PCR with potentially better specificity than PCR through the use of multiple primer sets for a nucleic acid target. Here we report a microfluidic droplet device implementing all the steps required for digital nucleic acid detection including droplet generation, incubation and in-line detection for digital LAMP. As compared to microchamber or droplet array-based digital assays, continuous flow operation of this device eliminates the constraints on the number of total reactions by the footprint of the device and the analysis throughput by the time for lengthy incubation and transfers of materials between instruments.

Spatial Molecular Imager (SMI) is an automated microscope imaging system with microfluidic reagent cycling, for high-plex, spatial in-situ detection of multiomic targets (RNA and protein) on FFPE and other intact samples with subcellular resolution. The key attributes of the CosMxTM SMI platform (NanoString®, Seattle, WA) include: 1) high-plex and high-sensitivity imaging chemistry that works for both RNA and protein detection, 2) three-dimensional subcellular-resolution image analysis with a target localization accuracy of ∼50 nm in the XY plane, 3) large Hamming-distance encoding scheme with low error rate (0.0092 false calls per cell per gene) and low background (∼ 0.04 counts per cell per gene), 4) high-throughput (up to 1 million cells per sample, four samples per run), 5) antibody-based cell segmentation methods, and 6) compatibility with formalin-fixed, paraffin-embedded (FFPE) samples.In this study, 980 RNAs and 80 proteins were measured at subcellular resolution in FFPE cultured cell pellets, as well as FFPE tissues from biobanked samples of non-small cell lung cancer (NSCLC) and breast cancer. Cross-platform analysis using 16 cancer cell lines validated high-correlation (R2 ∼0.77) and high sensitivity (∼1.44 FPKM/TPM; roughly 1 to 2 copies of RNA per cell) when compared to RNA-seq. Real-world archived NSCLC FFPE tumor sections revealed greater than 94% cell detection efficiency for RNA, despite the low RNA quality QV200 20% to the medium quality 65%. The accuracy of protein expression measurements was independent of the level of multiplexing, as demonstrated by the linear behavior of nested multiplexing panels (R2 > 0.9). At 980-plex RNA detection, data analysis allowed identification of over 18 distinct cell types, at least 10 unique tumor microenvironment neighborhoods, and over 100 pairwise ligand-receptor interactions. Data from 8 NSCLC samples comprising over 800,000 single cells and ∼260 million transcripts are released into the public domain (www.nanostring.com) to allow for extended data analysis by the entire spatial biology research community.

In this article we present a novel droplet microfluidic chip enabling amplification-free detection of single pathogenic cells. The device streamlines multiple functionalities to carry out sample digitization, cell lysis, probe-target hybridization for subsequent fluorescent detection. A peptide nucleic acid fluorescence resonance energy transfer probe (PNA beacon) is used to detect 16S rRNA present in pathogenic cells. Initially the sensitivity and quantification ability of the platform is tested using a synthetic target mimicking the actual expression level of 16S rRNA in single cells. The capability of the device to perform “sample-to-answer” pathogen detection of single cells is demonstrated using E. coli as a model pathogen.

We propose a highly versatile and programmable nanolitre droplet-based platform that accepts an unlimited number of sample plugs from a multi-well plate, performs digitization of these sample plugs into smaller daughter droplets and subsequent synchronization-free, robust injection of multiple reagents in to the sample daughter droplets on-demand. This platform combines excellent control of valve-based microfluidics with the high-throughput capability of droplet microfluidics. We demonstrate the functioning of a proof-of-concept device which generates combinatorial mixture droplets from a linear array of sample plugs and four different reagents, using food dyes to mimic samples and reagents. Generation of a one dimensional array of the combinatorial mixture droplets on the device leads to automatic spatial indexing of these droplets, precluding the need to include a barcode in each droplet to identify its contents. We expect this platform to further expand the range of applications of droplet microfluidics to include applications requiring high degree of multiplexing as well as high throughput analysis of multiple samples.

We demonstrate single biomolecule detection and quantification within sub-nanolitre droplets through application of Cylindrical Illumination Confocal Spectrosocpy (CICS) and droplet confinement within a retractable microfluidic constriction.Droplet-based microfluidic platforms offer the distinct advantages of fast sample mixing, limited reagant dispersion, and lower sample loss or contamination when compared to traditional microfluidic devices. 1, 2 In addition, simple control stategies for kHz frequency droplet generation, transportation, storage, and sorting give the platform a propensity for high throughput analysis. While initial applications have been shown in a range of research disciplines, including biochemical analysis 3 , chemical and material synthesis 4 , and chemical reactions 5 , more recent applications have emerged that seek to expand this high throughput capability to the analysis of individual biological entities, such as single cells 6-8 or biomolecules. 9,10 In single cell experiments, in vitro compartmentalization in droplets enables rapid accumulation of secreted cellular factors 11 , and provides both chemical isolation and a unique means of cell selection and control. 12 Alternately, single molecule compartmentalization enables nucleic acid analysis through single-copy DNA PCR, extending the high throughput capacity of droplet-based microfluidics to digital PCR assays. 7, 9, 10 However, the current dependence on amplification techniques (e.g. PCR or fluorogenic substrate) 1 for detection of low concentration biomolecules presents limitations in droplet-based platforms; these include decreased throughput and added complexity involved with enzymatic amplification. These limitations point towards the need for integration of a highly sensitive detection platform for amplification-free detection of lowabundance biomolecules.Confocal Fluorescence Spectroscopy (CFS) has traditionally been used for fluorescence based single molecule detection (SMD). [13][14][15][16][17][18] Resolution of single fluorophores is accomplished through reduction of a laser-illuminated probe volume to femtolitre size, thus minimizing background noise. Although well suited for SMD in continuous sample streams,