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Markowitz, J. E.

Publications and source records attributed to Markowitz, J. E..

7 recordsLinked to original sources

Hydrogel Fiber Endomicroscopy

Multimode fibers enable minimally invasive, high-resolution imaging through ultrathin probes, thereby enhancing diagnostic precision and facilitating real-time monitoring in delicate anatomical regions. In this work, we introduce HYFEN, a hydrogel-based endomicroscopic imaging platform for flexible, biocompatible, and subcellular-scale fluorescence microscopy. HYFEN leverages the unique properties of hydrogel materials, adaptive optics, and pixel-wise image enhancement to address challenges associated with silica-based fibers, including mode scrambling, limited field of view, and mechanical rigidity. The technique achieves precise mode threading, rapid diffraction-limited focusing at kilohertz speeds, and high-fidelity fluorescence signal acquisition with subcellular resolution. Notably, the approach extends fluorescence imaging under enhanced fiber dimensions and bending conditions that are unachievable with conventional modalities. Together, these advances establish HYFEN as a versatile platform for next-generation biointerfacing and minimally invasive imaging across biomedical and clinical settings.

bioengineering↗

A spinal substrate for modular control of natural behavior

Natural behavior unfolds as coordinated sequences of body movements. This organization suggests that behavior may be built from discrete motor patterns, yet how such arrangements are implemented by neural circuits remains unknown. Here, we combined kinematic analysis, muscle recordings, genetically identified cell types, and closed-loop optogenetic perturbations to examine the organizational logic of natural gap-crossing jumps in mice. Jumping was characterized by a series of precisely defined phases and their associated modular motor patterns. The core phases, propulsion and flight, exhibited distinct signatures of neural control, including unique bursts of coordinated hindlimb muscle activity, differential tuning strategies for jump distance, and active requirements for spinal neural drive. Mapping activity across lumbar interneuron populations and functionally screening candidate cell types for their ability to drive coordinated movement revealed that a population of dorsal excitatory dILB6 neurons can autonomously evoke coordinated multi-joint hindlimb flexion characteristic of the jumping flight phase, across behavioral contexts. These findings provide a specific cellular substrate for the long-standing concept of spinal modular motor control: a flexible, preconfigured motor template that the mammalian CNS can recruit and modulate to meet the demands of natural behavior. Highlights- Jumping behavior is organized into discrete phases with stereotyped motor patterns - Each phase contains a distinct signature of body-wide, joint, and muscle coordination - dILB6 spinal interneurons autonomously evoke a triple-flexion hindlimb motor module - dILB6 neurons can shape active jumping behavior

neuroscience↗

An optogenetics-compatible red fluorescent calcium indicator with negligible blue light photoactivation

Red genetically encoded calcium indicators (GECIs) are important tools for live cell and in vivo imaging. However, their application in optogenetic experiments has been limited by their complex photophysics, which can yield blue-light-induced artifacts. These photophysical drawbacks arise from the fluorescent protein (FP) used to construct the GECI. To address these limitations, we engineered novel red GECIs based on photostable red FPs, including mScarlet variants. After testing multiple design topologies and screening for calcium responses, we identified a lead variant, named ScaRCaMP-1.0. ScaRCaMP-1.0 exhibits moderate Ca2+ responses ({Delta}F/F0 = -13%) relative to other red GECIs, a tradeoff that appears to have enabled remarkable blue-light photostability at power densities exceeding 200 mW/mm2. We validated the performance of ScaRCaMP-1.0 in an optogenetic regime, and in vivo via fiber photometry. Finally, guided by structural predictions, we investigated the mechanism underlying ScaRCaMP responses. A pair of lysine residues on the surface of the FP appear to be important for controlling Ca2+ responses, and mutation of one residue (K132Y) notably increased the response size ({Delta}F/F0 = -22%) without compromising blue-light photostability. We call the improved variant ScaRCaMP-2.0. Taken together, these results establish ScaRCaMP as an optogenetics-compatible red GECI and demonstrate the potential of mScarlet-based fluorophores as a basis for generating photostable red biosensors.

neuroscience↗

Behavioral Signature of Trihexyphenidyl in The Tor1a (DYT1) Knockin Mouse Model of Dystonia

Dystonia is a neurological disorder characterized by involuntary repetitive movements and abnormal postures. Animal models have played a pivotal role in studying the pathophysiology of dystonia. However, many genetic models, e.g. the Tor1a+/{Delta}E (DYT1) mouse, lack an overt motor phenotype, despite significant underlying neuronal abnormalities within the striatum and other motor control regions. Because the striatum is implicated in action sequencing, it is possible that the behavioral defect arises as a disruption in the frequency and temporal ordering of behaviors, rather than execution, which cannot be captured using traditional behavioral assays, thus limiting drug discovery efforts. To address this challenge, we used MoSeq, an unsupervised behavioral segmentation framework, to compare the continuous free behavior of control Tor1a+/+ mice and knockin Tor1a+/{Delta}E mutant mice in response to the anti-dystonia drug trihexyphenidyl. Although minimal baseline differences in behavioral organization were detected, both genotypes exhibited robust and consistent shifts in behavioral space structure after treatment with trihexyphenidyl. Further, we demonstrate differences in the behavioral space structure of male vs female mice after trihexyphenidyl challenge. The distinct behavioral signatures evoked by trihexyphenidyl and biological sex, a known risk factor for dystonia, suggest that the analysis of the temporal structure of continuous free behavior provides a sensitive and novel approach to the discovery of therapeutics for the treatment of dystonia.

neuroscience↗

High-resolution in vivo kinematic tracking with injectable fluorescent nanoparticles

Behavioral quantification is a cornerstone of many neuroscience experiments. Recent advances in motion tracking have streamlined the study of behavior in small laboratory animals and enabled precise movement quantification on fast (millisecond) timescales. This includes markerless keypoint trackers, which utilize deep network systems to label positions of interest on the surface of an animal (e.g., paws, snout, tail, etc.). These approaches mark a major technological achievement. However, they have a high error rate relative to motion capture in humans and are yet to be benchmarked against ground truth datasets in mice. Moreover, the extent to which they can be used to track joint or skeletal kinematics remains unclear. As the primary output of the motor system is the activation of muscles that, in turn, exert forces on the skeleton rather than the skin, it is important to establish potential limitations of techniques that rely on surface imaging. This can be accomplished by imaging implanted fiducial markers in freely moving mice. Here, we present a novel tracking method called QD-Pi (Quantum Dot-based Pose estimation in vivo), which employs injectable near-infrared fluorescent nanoparticles (quantum dots, QDs) immobilized on microbeads. We demonstrate that the resulting tags are biocompatible and can be imaged non-invasively using commercially available camera systems when injected into fatty tissue beneath the skin or directly into joints. Using this technique, we accurately capture 3D trajectories of up to ten independent internal positions in freely moving mice over multiple weeks. Finally, we leverage this technique to create a large-scale ground truth dataset for benchmarking and training the next generation of markerless keypoint tracker systems.

neuroscience↗

Dynamics of striatal action selection and reinforcement learning

Spiny projection neurons (SPNs) in dorsal striatum are often proposed as a locus of reinforcement learning in the basal ganglia. Here, we identify and resolve a fundamental inconsistency between striatal reinforcement learning models and known SPN synaptic plasticity rules. Direct-pathway (dSPN) and indirect-pathway (iSPN) neurons, which promote and suppress actions, respectively, exhibit synaptic plasticity that reinforces activity associated with elevated or suppressed dopamine release. We show that iSPN plasticity prevents successful learning, as it reinforces activity patterns associated with negative outcomes. However, this pathological behavior is reversed if functionally opponent dSPNs and iSPNs, which promote and suppress the current behavior, are simultaneously activated by efferent input following action selection. This prediction is supported by striatal recordings and contrasts with prior models of SPN representations. In our model, learning and action selection signals can be multiplexed without interference, enabling learning algorithms beyond those of standard temporal difference models.

neuroscience↗

Distinguishing discrete and continuous behavioral variability using warped autoregressive HMMs

A core goal in systems neuroscience and neuroethology is to understand how neural circuits generate naturalistic behavior. One foundational idea is that complex naturalistic behavior may be composed of sequences of stereotyped behavioral syllables, which combine to generate rich sequences of actions. To investigate this, a common approach is to use autoregressive hidden Markov models (ARHMMs) to segment video into discrete behavioral syllables. While these approaches have been successful in extracting syllables that are interpretable, they fail to account for other forms of behavioral variability, such as differences in speed, which may be better described as continuous in nature. To overcome these limitations, we introduce a class of warped ARHMMs (WARHMM). As is the case in the ARHMM, behavior is modeled as a mixture of autoregressive dynamics. However, the dynamics under each discrete latent state (i.e. each behavioral syllable) are additionally modulated by a continuous latent "warping variable." We present two versions of warped ARHMM in which the warping variable affects the dynamics of each syllable either linearly or nonlinearly. Using depth-camera recordings of freely moving mice, we demonstrate that the failure of ARHMMs to account for continuous behavioral variability results in duplicate cluster assignments. WARHMM achieves similar performance to the standard ARHMM while using fewer behavioral syllables. Further analysis of behavioral measurements in mice demonstrates that WARHMM identifies structure relating to response vigor.

animal behavior and cognition↗