Biology subjects

Nevian, T.

Publications and source records attributed to Nevian, T..

5 recordsLinked to original sources

bioRxiv2025

Advancing Human iPSC-Derived Motor Neuron Models Using Glutamatergic Modulators for Synaptic Function Studies

Understanding human synapse structure and function at nanoscale resolution requires experimental systems that support both high-quality imaging and robust synaptogenesis. While brain tissue and primary neuronal cultures have been widely used, human induced pluripotent stem cells (iPSCs) offer key advantages: they enable patient-specific modeling and provide a renewable source of human neurons without relying on animal models. However, reproducible synapse formation in iPSC-derived neurons, particularly motor neurons (MNs), remains challenging due to variable differentiation efficiencies and low synaptic density. Here, we optimized MN differentiation to enhance synaptogenesis and enable high-resolution structural analysis using cryo-electron tomography (cryo-ET). Within 28 days, human iPSC-derived MNs developed into morphologically and functionally mature neuronal networks, characterized by phase-bright somata, elongated axons, and dense axodendritic branching. To further promote synaptic connectivity, we applied the glutamatergic modulators CX516 and CDPPB during differentiation. Their effects were validated by immunolabeling of synaptic markers, electrophysiology, calcium imaging, live-cell synaptic vesicle recycling assays, and ultrastructural imaging, including cryo-ET. This combined approach of optimized differentiation and targeted neuromodulation yielded reproducible MN networks with enhanced synaptic density and function, providing a robust in vitro platform for investigating human MN physiology, synaptic mechanisms, and disease-relevant synaptopathies.

neuroscience↗

bioRxiv2025

Differentiated SH-SY5Y Cells Exhibit Neuronal Features but Lack Synaptic Maturity

A vital question in neuroscience is if and how efficiently cellular models may be differentiated into functional neuronal cells in culture. Despite the frequent use of the human neuroblastoma cell line SH-SY5Y, differentiation protocols vary extensively, with the most common being differentiation via the addition of retinoic acid and brain-derived neurotrophic factor. However, due to the lack of a reliable evaluation method, their adequacy as synaptic models remains unclear. Here, we investigate whether SH-SY5Y cells constitute a functional model for synaptic studies by phenotypically and ultra structurally analyzing synaptogenesis in SH-SY5Y cells subjected to different differentiation protocols. Electron microscopy (EM) techniques, including conventional EM, cryo-EM, and cryo-electron tomography, were systematically applied to characterize synaptogenesis in SH-SY5Y cells. Further characterization was performed through immunostaining and functional assays, such as live exocytosis assays and whole-cell patch-clamp electrophysiology. Despite exhibiting some presynaptic-like features, differentiated SH-SY5Y cells do not form morphologically or functionally complete synapses under the conditions tested. Immunostaining results were consistent with previous findings, showing synaptic markers. However, functional investigations did not detect synaptic activity. High-throughput EM analyses revealed an absence of synaptic structures in these cells. Additionally, an alternative differentiation approach incorporating additional neurotrophic factors promoted the formation of pre-synaptic-like compartments containing synapse-like synaptic vesicles (SVLVs). Though these SVLVs exhibited pleomorphic size distributions, differing from typical synaptic vesicles, and lacked connectors. These findings emphasize the need for cautious interpretation of results derived from SH-SY5Y cells when studying molecular synaptic architecture or neurodegenerative diseases.

neuroscience↗

bioRxiv2023

Top-down modulation of sensory processing and mismatch in the mouse posterior parietal cortex

An important function of the neocortex is to compare sensory feedback stimuli with internal predictions of the outside world and evoke mismatch responses to deviations, thus allowing expectations to be updated. The mechanisms behind sensory feedback mismatch and prediction formation however remain unclear. Here we created a learned association of an auditory-tactile stimulus sequence in awake head-fixed mice, where a sound predicted an up-coming whisker stimulus and introduced mismatches by omitting or altering the whisker stimulus intensity. We showed that layer 2/3 posterior parietal cortex (PPC) neurons could report stimulus sequence mismatches, as well as display neural correlates of expectation. Inhibition of PPC-projecting secondary motor cortex (M2) neurons suppressed these correlates, along with population mismatch responses. Hence, M2 can influence sensory processing in the PPC and potentially provide the prediction of sensory feedback from learned relationships within sequences of sensory stimuli.

neuroscience↗

bioRxiv2020

Cortical representation of pain by stable dedicated neurons and dynamic ensembles

The perception of pain arises from distributed brain activity triggered by noxious stimuli. However, which patterns of activity make nociception distinct from other salient sensory experiences is still unknown. Using in vivo chronic two-photon calcium imaging in slightly anaesthetized mice, we identified a nociception-specific representation in the anterior cingulate cortex (ACC), that is attained by a core of neurons that code for a generalized concept of the pain experience. The overall ensemble activity allowed for an efficient discrimination of the sensory space, despite a drift in single-neuron sensory tuning over time. Following sciatic nerve lesion, the representation of nociceptive stimuli was impaired as a consequence of innocuous stimuli expanded into the nociception-specific ensemble, leading to a dysfunctional discrimination of sensory events in the ACC. Thus, the hallmark of chronic pain at the cortical neuronal network level is an impairment of pattern separation and classification identifying a circuit mechanism for altered pain processing in the brain.

neuroscience↗

bioRxiv2020

Data-driven reduction of dendritic morphologies with preserved dendro-somatic responses

Dendrites shape information flow in neurons. Yet, there is little consensus on the level of spatial complexity at which they operate. We present a flexible and fast method to obtain simplified neuron models at any level of complexity. Through carefully chosen parameter fits, solvable in the least squares sense, we obtain optimal reduced compartmental models. We show that (back-propagating) action potentials, calcium-spikes and NMDA-spikes can all be reproduced with few compartments. We also investigate whether afferent spatial connectivity motifs admit simplification by ablating targeted branches and grouping the affected synapses onto the next proximal dendrite. We find that voltage in the remaining branches is reproduced if temporal conductance fluctuations stay below a limit that depends on the average difference in input impedance between the ablated branches and the next proximal dendrite. Further, our methodology fits reduced models directly from experimental data, without requiring morphological reconstructions. We provide a software toolbox that automatizes the simplification, eliminating a common hurdle towards including dendritic computations in network models.

neuroscience↗