Biology subjects

Sharf, T.

Publications and source records attributed to Sharf, T..

12 recordsLinked to original sources

bioRxiv2026

Spatially defined axonal guidance in neural organoids with micropatterned microfluidic channels

Three-dimensional stem cell-derived neural organoids provide a promising platform for investigating early brain development and interregional circuit formation. Although co-culture of region-specific organoids into assembloids has enabled the study of cortical and subcortical interactions, these models lack directional specificity and spatial control, limiting their ability to recapitulate canonical circuit architecture. Here, we present a microfluidic platform for constructing directional and tunable interregional circuits while preserving anatomical distinction. This system, which we term "directoids" incorporates micropatterned polydimethylsiloxane (PDMS) microstructures to control uni- and bidirectional axonal growth between cortical and thalamic organoids. We observed a 70.4% success rate of axons traversing the full channel length in the permissive direction and reaching the opposing organoid, whereas no neurites successfully crossed the probative direction. These results demonstrate robust directionally bias in axon outgrowth and establish a scalable, reproducible strategy for controlling asymmetric connectivity between anatomically distinct neural organoids. Using high-density CMOS microelectrode arrays, we further validated directional tuning of extracellular action potential propagation within directoid microchannels, a feature not observed in straight-channel connectoid controls. Directoids also exhibited significant asymmetry in firing rates between channel entry and exit sites, consistent with engineered bias in signal flow. This provides an experimental paradigm for dissecting how anatomical connectivity and functional activity converge to shape neuronal networks. Together, these findings establish a microfluidic platform for investigating the mechanisms underlying hierarchical circuit formation, regional specification, and functional integration in developing human neural organoid models at cellular resolution not possible in vivo.

bioengineering↗

bioRxiv2026

SpikeLab: Agentic tools for spike data analysis

Large language models have the potential to transform scientific research and analysis, but without domain-specific structure they produce silent methodological errors, unreported decisions, and irreproducible results. Here we present SpikeLab, a text-to-analysis framework for neural spike data that combines composable data structures with a skill-based agentic system enforcing bounded autonomy: mandatory use of expert-vetted methods, correctness over efficiency, and clarification-seeking on ambiguous requests. In a controlled benchmark on electrophysiology data, Sonnet 4.6 with SpikeLab produced correct and reproducible results across all tasks, outperforming both the unassisted Sonnet and the more capable Opus 4.6, which exhibited deterministic failures including ad hoc method invention, silent data reduction, and inconsistent experimental designs. We demonstrate versatility across in vivo mouse, human, and in vitro brain organoid recordings, and apply the framework to a pharmacological dose-response study spanning single-unit dynamics, pairwise network structure, burst-level temporal sequences, and latent population states, all through natural language prompts without writing analysis code.

neuroscience↗

bioRxiv2025

Distinct Synaptic Mechanisms Drive NRXN1 Variant-Mediated Pathogenesis in iPSC-Derived Neuronal Models of Autism and Schizophrenia

Copy number deletions in the 2p16.3/NRXN1 locus confer genome wide risk for autism spectrum disorder (ASD) and schizophrenia (SCZ). Prior work demonstrated that heterozygous NRXN1 deletions decreases synaptic strength and neurotransmitter release probability in human-iPSC derived cortical glutamatergic induced neurons and this synaptic phenotype is replicated in SCZ patient iPSCs with varying NRXN1 genomic deletions. What is unknown, however, is whether similar synaptic impairment exists in ASD patients carrying NRXN1 deletions. Answering this question is important to determine whether all NRXN1 deletion carriers should be treated similarly or individually, based on their genetic backgrounds and deletion breakpoints. Here, using previously uncharacterized ASD patient iPSC lines, we show that ASD-NRXN1 deletions impact cortical synaptic function and plasticity in unique ways compared to SCZ-NRXN1 deletions. Specifically, at a single neuronal level, ASD-NRXN1 deletions alter basal spontaneous synaptic transmission by selectively enhancing excitatory synaptic signaling with no changes at inhibitory synapses while SCZ-NRXN1 deletions reduce both excitatory and inhibitory synaptic transmission. At the neuronal network level, there exists enhanced transmission probability and irregular firing patterns in ASD-NRXN1 deletions. Such changes at the synaptic and network level connectivity patterns influence a critical form of developmental cortical plasticity, synaptic scaling, as ASD-NRXN1 deletions uniquely fail to upscale their synaptic strength in response to chronic neuronal silencing. Together, these findings highlight the disorder-specific consequences of NRXN1 deletions on synaptic function and connectivity, offering mechanistic insights with implications for therapeutic targeting and refinement strategies for NRXN1-associated synaptopathies. HighlightsO_LINovel ASD patient-iPSC-derived E-I culture model to investigate pathogenic NRXN1 deletions on cortical synaptic function and plasticity C_LIO_LIASD-NRXN1 deletions enhance basal synaptic transmission by specifically increasing excitatory neurotransmitter release, opposite of SCZ-NRXN1 deletions C_LIO_LISynaptic scaling homeostasis is impaired in ASD-NRXN1 deletions C_LIO_LISpike train cross-correlation analysis reveals increased transmission probability and irregular firing patterns in ASD-NRXN1 deletions C_LI

neuroscience↗

bioRxiv2025

Self-Organizing Neural Networks in Organoids Reveal Principles of Forebrain Circuit Assembly

The mouse cortex is a canonical model for studying how functional neural networks emerge, yet it remains unclear which topological features arise from intrinsic cellular organization versus external regional cues. Mouse forebrain organoids provide a powerful system to investigate these intrinsic mechanisms. We generated dorsal (DF) and ventral (VF) forebrain organoids from mouse pluripotent stem cells and tracked their development using longitudinal electrophysiology. DF organoids showed progressively stronger network-wide correlations, while VF organoids developed more refined activity patterns, enhanced small-world topology, and increased modular organization. These differences emerged without extrinsic inputs and may be driven by the increased generation of Pvalb+ interneurons in VF organoids. Our findings demonstrate how variations in cellular composition influence the self-organization of neural circuits, establishing mouse forebrain organoids as a tractable platform to study how neuronal populations shape cortical network architecture.

neuroscience↗

bioRxiv2024

Goal-Directed Learning in Cortical Organoids

Experimental neuroscience techniques are advancing rapidly, with major recent developments in high-density electrophysiology and targeted electrical stimulation. In combination with these techniques, cortical organoids derived from pluripotent stem cells show great promise as in vitro models of brain development and function. Although sensory input is vital to neurodevelopment in vivo, few studies have explored the effect of meaningful input to in vitro neural cultures over time. In this work, we demonstrate the first example of goal-directed learning in brain organoids. We developed a closed-loop electrophysiology framework to embody mouse cortical organoids into a simulated dynamical task (the inverted pendulum problem known as Cartpole) and evaluate learning through high-frequency training signals. Longitudinal experiments enabled by this framework illuminate how different methods of selecting training signals enable improvement on the tasks. We found that for most organoids, training signals chosen by artificial reinforcement learning yield better performance on the task than randomly chosen training signals or the absence of a training signal. This systematic approach to studying learning mechanisms in vitro opens new possibilities for therapeutic interventions and biological computation.

neuroscience↗

bioRxiv2024

Pathological microcircuits initiate epileptiform events in patient hippocampal slices

How seizures begin at the level of microscopic neuronal circuits remains unknown. Advancements in high-density CMOS-based microelectrode arrays can be harnessed to study neuronal network activity with unprecedented spatial and temporal resolution. We use high-density electrophysiology recordings to probe the network activity of human hippocampal brain slices from six patients with mesial temporal lobe epilepsy. Two slices from the dentate gyrus exhibited epileptiform activity in the presence of low magnesium media with kainic acid. Both slices exhibit network oscillations indicative of a reciprocally connected circuit, which is unexpected under normal physiological conditions. Future studies may apply this approach to elucidate the network signals that underlie seizure initiation.

neuroscience↗

bioRxiv2024

Multiscale Cloud-based Pipeline for Neuronal Electrophysiology Analysis and Visualization

Electrophysiology offers a high-resolution method for real-time measurement of neural activity. Longitudinal recordings from high-density microelectrode arrays (HD-MEAs) can be of considerable size for local storage and of substantial complexity for extracting neural features and network dynamics. Analysis is often demanding due to the need for multiple software tools with different runtime dependencies. To address these challenges, we developed an open-source cloud-based pipeline to store, analyze, and visualize neuronal electrophysiology recordings from HD-MEAs. This pipeline is dependency agnostic by utilizing cloud storage, cloud computing resources, and an Internet of Things messaging protocol. We containerized the services and algorithms to serve as scalable and flexible building blocks within the pipeline. In this paper, we applied this pipeline on two types of cultures, cortical organoids and ex vivo brain slice recordings to show that this pipeline simplifies the data analysis process and facilitates understanding neuronal activity.

neuroscience↗

bioRxiv2024

A feedback-driven IoT microfluidic, electrophysiology, and imaging platform for brain organoid studies

The analysis of tissue cultures, particularly brain organoids, requires a sophisticated integration and coordination of multiple technologies for monitoring and measuring. We have developed an automated research platform enabling independent devices to achieve collaborative objectives for feedback-driven cell culture studies. Our approach enables continuous, communicative, non-invasive interactions within an Internet of Things (IoT) architecture among various sensing and actuation devices, achieving precisely timed control of in vitro biological experiments. The framework integrates microfluidics, electrophysiology, and imaging devices to maintain cerebral cortex organoids while measuring their neuronal activity. The organoids are cultured in custom, 3D-printed chambers affixed to commercial microelectrode arrays. Periodic feeding is achieved using programmable microfluidic pumps. We developed a computer vision fluid volume estimator used as feedback to rectify deviations in microfluidic perfusion during media feeding/aspiration cycles. We validated the system with a set of 7-day studies of mouse cerebral cortex organoids, comparing manual and automated protocols. The automated protocols were validated in maintaining robust neural activity throughout the experiment. The automated system enabled hourly electrophysiology recordings for the 7-day studies. Median neural unit firing rates increased for every sample and dynamic patterns of organoid firing rates were revealed by high-frequency recordings. Surprisingly, feeding did not affect firing rate. Furthermore, performing media exchange during a recording showed no acute effects on firing rate, enabling the use of this automated platform for reagent screening studies.

neuroscience↗

bioRxiv2023

Protosequences in human cortical organoids model intrinsic states in the developing cortex

Neuronal firing sequences are thought to be the basic building blocks of neural coding and information broadcasting within the brain. However, when sequences emerge during neurodevelopment remains unknown. We demonstrate that structured firing sequences are present in spontaneous activity of human and murine brain organoids and ex vivo neonatal brain slices from the murine somatosensory cortex. We observed a balance between temporally rigid and flexible firing patterns that are emergent phenomena in human and murine brain organoids and early postnatal murine somatosensory cortex, but not in primary dissociated cortical cultures. Our findings suggest that temporal sequences do not arise in an experience-dependent manner, but are rather constrained by an innate preconfigured architecture established during neurogenesis. These findings highlight the potential for brain organoids to further explore how exogenous inputs can be used to refine neuronal circuits and enable new studies into the genetic mechanisms that govern assembly of functional circuitry during early human brain development.

neuroscience↗

bioRxiv2022

Automated detection of extracellular action potentials from single neurons

Multi-electrode arrays (MEAs) non-invasively record extracellular action potentials (eAPs, also known as spikes) from hundreds of neurons simultaneously. However, because extracellular electrodes sample from the local electrical field, each electrode can detect eAPs from multiple nearby neurons. Interpreting spike trains at individual electrodes of high-density arrays requires spike sorting, a computational process which groups eAPs from single units based on assumptions of how spike waveforms correlate with different neuronal sources. Additionally, when experimental conditions result in changes to eAP waveforms, spike sorting routines may have difficulty correlating eAPs from multiple neurons at single electrodes before and after such waveform changes. We present here a novel, empirical method for unambiguously isolating eAPs from individual, uniquely identifiable neurons, based on automated multi- point detection of action potential propagation. This method is insensitive to changes in eAP waveform morphology because it makes no assumptions about the relationship between spike waveform and neuronal source. Our algorithm for automated detection of action potential propagation produces a fingerprint that uniquely identifies those spikes from each neuron. By unambiguously isolating eAPs from multiple neurons in each recording, on a range of platforms and experimental preparations, our method now enables high-content screening with contemporary MEAs. We outline the limitations and strengths of propagation-based isolation of eAPs from single neurons and propose how our automated method complements spike sorting and could be adapted to in vivo use.

neuroscience↗

bioRxiv2021

Intrinsic network activity in human brain organoids

Human brain organoids replicate much of the cellular diversity and developmental anatomy of the human brain. However, the physiological behavior of neuronal circuits within organoids remains relatively under-explored. With high-density CMOS microelectrode arrays (26,400 electrodes) and shank electrodes (960 electrodes), we probed broadband and three-dimensional extracellular field recordings generated by spontaneous activity of human brain organoids. These recordings simultaneously captured local field potentials (LFPs) and single-unit activity extracted through spike sorting. From spiking activity, we estimated a directed functional connectivity graph of synchronous neural network activity, which showed a large number of weak functional connections enmeshed within a network skeleton of significantly fewer strong connections. Treatment of the organoid with a benzodiazepine induced a reproducible signature response that shortened the inter-burst intervals, increased the uniformity of the firing pattern within each burst and decreased the population of weakly connected edges. Simultaneously examining the spontaneous LFPs and their phase alignment to spiking showed that spike bursts were coherent with theta oscillations in the LFPs. Our results demonstrate that human brain organoids have self-organized neuronal assemblies of sufficient size, cellular orientation, and functional connectivity to co-activate and generate field potentials from their collective transmembrane currents that phase-lock to spiking activity. These results point to the potential of brain organoids for the study of neuropsychiatric diseases, drug mechanisms, and the effects of external stimuli upon neuronal networks.

neuroscience↗

bioRxiv2017

Tau Internalization is Regulated by 6-O Sulfation on Heparan Sulfate Proteoglycans (HSPGs)

The misfolding and accumulation of tau protein into intracellular aggregates known as neurofibrillary tangles is a pathological hallmark of neurodegenerative diseases such as Alzheimers disease. However, while tau propagation is a known marker for disease progression, exactly how tau propagates from one cell to another and what mechanisms govern this spread are still unclear. Here, we report that cellular internalization of tau is regulated by quaternary structure and have developed a cellular assay to screen for genetic modulators of tau uptake. Using CRISPRi technology we have tested 3200 genes for their ability to regulate tau entry and identified enzymes in the heparan sulfate proteoglycan biosynthetic pathway as key regulators. We show that 6-O-sulfation is critical for tauheparan sulfate interactions and that this modification regulates uptake in human central nervous system cell lines, iPS-derived neurons, and mouse organotypic brain slice culture. Together, these results suggest novel strategies to halt tau transmission.

neuroscience↗