Biology subjects

Paulsen, O.

Publications and source records attributed to Paulsen, O..

14 recordsLinked to original sources

bioRxiv2025

Mecp2 deficiency impairs microscale cortical network topology and dynamics in a Rett syndrome mouse model

Rett syndrome is a debilitating neurodevelopmental disorder with cerebral processing impairments caused by MECP2 loss-of-function mutations. Mecp2-deficient mouse models reveal disruptions of microscale cortical circuits. Yet how cellular-scale information processing is altered in Mecp2-deficient microscale functional networks is unknown. We investigated the development of functional connectivity, network topology, and dynamics in microelectrode array (MEA) recordings of primary cortical cultures from Mecp2-deficient and wild-type mice. Mecp2-deficient cortical networks developed more slowly and showed decreased functional connectivity compared to wild-type, leading to smaller network size, density, and strength of connectivity. Altered network topological features in Mecp2-deficient microscale circuits predicted decreased efficiency and information-sharing capacity. This reveals developmental deficits in microscale functional networks, which may in turn underlie the cortical decline and severe cognitive disability in Rett syndrome. These findings also offer circuit-level targets and an in-vitro approach for evaluating new therapeutic products for restoring microscale network function.

neuroscience↗

bioRxiv2025

NeuroSuite for Long-term Functional and Structural Studies of Air-Liquid Interface Cerebral Organoids

Over the past decade, air-liquid interface cerebral organoids (ALI-COs) have emerged as powerful in vitro models that capture essential structural and functional traits of the human brain, offering an exciting alternative to traditional animal models in neuroscience. Yet, the full potential of these systems has remained untapped due to the lack of non-invasive, long-term electrophysiological tools capable of preserving organoid integrity. Existing techniques, ranging from patch clamping to rigid and 3D microelectrode arrays, often compromise organoid growth and disrupt delicate cytoarchitecture. Here, we present NeuroSuite, an innovative bioelectronic platform designed to overcome these challenges. At its core is Neuroweb, a perforated, ultra-thin, and conformable organic microelectrode array engineered for minimal disruption of nutrient and oxygen exchange. Neuroweb is reusable and supports stable recordings for over six months, making it uniquely suited for longitudinal studies. Coated with poly(3,4-ethylenedioxythiophene):polystyrene sulfonate (PEDOT:PSS), a high-performance mixed ionic-electronic conductor, Neuroweb delivers exceptional signal-to-noise ratio recordings with high spatial precision. By pairing Neuroweb with NeuroMaps, an intuitive software for interactive analysis and visualisation, NeuroSuite enables long-term, non-invasive tracking and spatial mapping of electrical activity from brain organoids and ex vivo brain slices at the air-liquid interface. Following rigorous validation, we demonstrate that NeuroSuite can capture both high- and low-frequency throughout maturation. Our pipeline reveals evolving network connectivity, including the development of GABA-ergic interneurons, and concurrent shifts in high-frequency spiking and low-frequency oscillations indicative of a refinement in the excitatory-inhibitory balance. Finally, automated data acquisition and spatial spike mapping highlight local activity changes in response to media composition, a factor often overlooked in conventional recordings. NeuroSuite thus opens a new frontier in organoid neuroscience, enabling precise, long-term monitoring essential for modelling neurological diseases, understanding human brain development, and accelerating drug discovery. TeaserConformal organic bioelectronic arrays, combined with an open-access toolbox for analysis and visualisation, reveal real-time and long-term neural dynamics in brain organoid slices at the air-liquid interface.

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bioRxiv2025

Layer 1 NDNF interneurons form distinct subpopulations with opposite activation patterns during sleep in freely behaving mice

Non-rapid eye movement (NREM) sleep facilitates memory consolidation by transferring information from the hippocampus to the neocortex. Recent evidence suggests that this transfer occurs primarily when hippocampal sharp-wave ripples (SWRs) and thalamocortical spindles are synchronized. In this study, we asked what role cortical layer 1 NDNF-expressing (L1 NDNF) interneurons play during NREM sleep in gating information transfer during SWR-spindle synchronization. Using simultaneous cell-specific calcium imaging and local field potential recordings in freely moving mice, we discovered that L1 NDNF neurons form cell assemblies tuned to specific sleep stages, exhibiting differential responses to spindle synchronization. L1 NDNF neurons mediate slow inhibition through GABAB receptors. Systemic application of a GABAB receptor antagonist increased pyramidal neuron excitability during NREM sleep, enhanced inhibitory responses during SWRs, and disrupted SWR-spindle coupling. Overall, these findings suggest an important contribution of L1 NDNF neuron-mediated slow inhibition to the synchronization of sleep oscillations with potential implications for memory consolidation processes.

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bioRxiv2024

Dopamine increases protein synthesis in hippocampal neurons enabling dopamine-dependent LTP

The reward and novelty related neuromodulator dopamine plays an important role in hippocampal long- term memory, which is thought to involve protein synthesis-dependent synaptic plasticity. However, the direct effects of dopamine on protein synthesis, and the functional implications of newly synthesized proteins for synaptic plasticity, have not yet been investigated. We have previously reported that timing- dependent synaptic depression (t-LTD) can be converted into potentiation by dopamine application during synaptic stimulation (Brzosko et al., 2015) or postsynaptic burst activation (Fuchsberger et al., 2022). Here we show that dopamine increases protein synthesis in mouse hippocampal CA1 neurons, enabling dopamine-dependent long-term potentiation (DA-LTP), which is mediated via the Ca2+-sensitive adenylate cyclase (AC) subtypes 1/8, cAMP, and cAMP-dependent protein kinase (PKA). We found that neuronal activity is required for the dopamine-induced increase in protein synthesis. Furthermore, dopamine induced a protein synthesis-dependent increase in the AMPA receptor subunit GluA1, but not GluA2. We found that DA-LTP is absent in GluA1 knock-out mice and that it requires calcium-permeable AMPA receptors. Taken together, our results suggest that dopamine together with neuronal activity controls synthesis of plasticity-related proteins, including GluA1, which enable DA-LTP via a signalling pathway distinct from that of conventional LTP.

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bioRxiv2024

Machine learning-based spike sorting reveals how subneuronal concentrations of monomeric Tau cause a loss in excitatory postsynaptic currents in hippocampal neurons

Extracellular recordings of neuronal activity constitute a powerful tool for investigating the intricate dynamics of neural networks and the activity of individual neurons. Microelectrode arrays (MEAs) allow for recordings with a high electrode count, ranging from 10s to 1000s, generating extensive datasets of neuronal information. Furthermore, MEAs capture extracellular field potentials from cultured cells, resulting in highly complex neuronal signals that necessitate precise spike sorting for meaningful data extraction. Nevertheless, conventional spike sorting methods face limitations in recognising diverse spike shapes, thereby constraining the full utilisation of the rich dataset acquired from MEA recordings. To overcome these limitations, we have developed a machine learning algorithm, named PseudoSort, which employs advanced self-supervised learning techniques, a distinctive density-based pseudo-labelling strategy, and an iterative fine-tuning process to enhance spike sorting accuracy. Through extensive benchmarking on large-scale simulated datasets, we demonstrate the superior performance of PseudoSort compared to recently developed machine learning-based (ML) spike sorting algorithms. We showcase the practical application of PseudoSort by utilising MEA recordings from hippocampal neurons exposed to subneuronal concentrations of monomeric Tau, a protein associated with Alzheimers disease (AD). Our results, validated against patch clamp experiments, unveil that monomeric Tau at subneuronal concentrations induces stimulation-dependent disruptions in both local and global activity of hippocampal neurons. Remarkably, patch clamp electrophysiology highlights the effect of combined Tau and neuronal stimulation treatment on excitatory postsynaptic currents, whereas PseudoSort excels in identifying neuronal clusters that exhibit diminished firing capacity following Tau treatment alone, i.e., in the absence of stimulation. This comprehensive approach validates the prowess of PseudoSort and unravels the intricate effects of Tau on neuronal activity, particularly in the context of AD.

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bioRxiv2024

MEA-NAP compares microscale functional connectivity, topology, and network dynamics in organoid or monolayer neuronal cultures

Microelectrode array (MEA) recordings are commonly used to compare firing and burst rates in neuronal cultures. MEA recordings can also reveal microscale functional connectivity, topology, and network dynamics--patterns seen in brain networks across spatial scales. Network topology is frequently characterized in neuroimaging with graph theoretical metrics. However, few computational tools exist for analyzing microscale functional brain networks from MEA recordings. Here, we present a MATLAB MEA network analysis pipeline (MEA-NAP) for raw voltage time-series acquired from single- or multi-well MEAs. Applications to 3D human cerebral organoids or 2D human-derived or murine cultures reveal differences in network development, including topology, node cartography, and dimensionality. MEA-NAP incorporates multi-unit template-based spike detection, probabilistic thresholding for determining significant functional connections, and normalization techniques for comparing networks. MEA-NAP can identify network-level effects of pharmacologic perturbation and/or disease-causing mutations and, thus, can provide a translational platform for revealing mechanistic insights and screening new therapeutic approaches.

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bioRxiv2023

Low-latency extracellular spike assignment for high-density electrodes at single-neuron resolution

Real-time neural signal processing is essential for brain-machine interfaces and closed-loop neuronal perturbations. However, most existing applications sacrifice cell-specific identity and temporal spiking information for speed. We developed a hybrid hardware-software system that utilizes a Field Programmable Gate Array (FPGA) chip to acquire and process data in parallel, enabling individual spikes from many simultaneously recorded neurons to be assigned single-neuron identities with 1-millisecond latency. The FPGA assigns labels, validated with ground-truth data, by comparing multichannel spike waveforms from tetrode or silicon probe recordings to a spike-sorted model generated offline in software. This platform allowed us to rapidly inactivate a region in vivo based on spikes from an upstream neuron before these spikes could excite the downstream region. Furthermore, we could decode animal location within 3 ms using data from a population of individual hippocampal neurons. These results demonstrate our systems suitability for a broad spectrum of research and clinical applications.

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bioRxiv2022

Postsynaptic burst reactivation of hippocampal neurons enables associative plasticity of temporally discontiguous inputs

A fundamental unresolved problem in neuroscience is how the brain associates in memory events that are separated in time. Here we propose that reactivation-induced synaptic plasticity can solve this problem. Previously, we reported that the reinforcement signal dopamine converts hippocampal spike timing-dependent depression into potentiation during continued synaptic activity (Brzosko et al., 2015). Here, we report that postsynaptic bursts in the presence of dopamine produces input-specific LTP in hippocampal synapses 10 minutes after they were primed with coincident pre- and postsynaptic activity. The priming activity sets an NMDAR-dependent silent eligibility trace which, through the cAMP-PKA cascade, is rapidly converted into protein synthesis-dependent synaptic potentiation, mediated by a signaling pathway distinct from that of conventional LTP. Incorporated into a computational model, this synaptic learning rule adds specificity to reinforcement learning by controlling memory allocation and enabling both instructive and supervised reinforcement learning. We predicted that this mechanism would make reactivated neurons activate more strongly and carry more spatial information than non-reactivated cells, which was confirmed in freely moving mice performing a reward-based navigation task.

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bioRxiv2022

Homophilic wiring principles underpin neuronal network topology in vitro

Economic efficiency has been a popular explanation for how networks self-organize within the developing nervous system. However, the precise nature of the economic negotiations governing this putative organizational principle remains unclear. Here, we address this question further by combining large-scale electrophysiological recordings, to characterize the functional connectivity of developing neuronal networks in vitro, with a generative modeling approach capable of simulating network formation. We find that the best fitting model uses a homophilic generative wiring principle in which neurons form connections to other neurons which are spatially proximal and have similar connectivity patterns to themselves. Homophilic generative models outperform more canonical models in which neurons wire depending upon their spatial proximity either alone or in combination with the extent of their local connectivity. This homophily-based mechanism for neuronal network emergence accounts for a wide range of observations that are described, but not sufficiently explained, by traditional analyses of network topology. Using rodent and human monolayer and organoid cultures, we show that homophilic generative mechanisms can accurately recapitulate the topology of emerging cellular functional connectivity, representing an important wiring principle and determining factor of neuronal network formation in vitro.

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bioRxiv2021

Different encoding of reward location in dorsal and ventral hippocampus

Hippocampal neurons encode a cognitive map for spatial navigation1. When they fire at specific locations in the environment, they are known as place cells2. In the dorsal hippocampus place cells accumulate at current navigational goals, such as learned reward locations3-6. In the intermediate-to-ventral hippocampus (here collectively referred to as ventral hippocampus), neurons fire across larger place fields7-10 and regulate reward- seeking behavior11-16, but little is known about their involvement in reward-directed navigation. Here, we compared the encoding of learned reward locations in the dorsal and ventral hippocampus during spatial navigation. We used calcium imaging with a head- mounted microscope to track the activity of CA1 cells over multiple days during which mice learned different reward locations. In dorsal CA1 (dCA1), the overall number of active place cells increased in anticipation of reward but the recruited cells changed with the reward location. In ventral CA1 (vCA1), the activity of the same cells anticipated the reward locations. Our results support a model in which the dCA1 cognitive map incorporates a changing population of cells to encode reward proximity through increased population activity, while the vCA1 provides a reward-predictive code in the activity of a specific subpopulation of cells. Both of these location-invariant codes persisted over time, and together they provide a dual hippocampal reward-location code, assisting goal- directed navigation17, 18.

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bioRxiv2020

Cholinergic suppression of sharp wave-ripples impairs hippocampus-dependent spatial memory

The hippocampus plays a central role in long-term memory formation, and different hippocampal network states are thought to have different functions in this process. These network states are controlled by neuromodulatory inputs, including the cholinergic input from the medial septum. Here, we used optogenetic stimulation of septal cholinergic neurons to understand how cholinergic activity affects different stages of spatial memory formation in a reward-based navigation task in mice. We found that optogenetic stimulation of septal cholinergic neurons (1) impaired memory formation when activated at goal location but not during navigation; (2) reduced sharp wave-ripple (SWR) incidence at goal location; and (3) reduced SWR incidence and enhanced the-ta-gamma oscillations during sleep. These results underscore the importance of appropriate timing of cholinergic input in long-term memory formation, which might help explain the limited success of cholinesterase inhibitor drugs in treating memory impairment in Alzheimers disease.

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bioRxiv2019

An Emergent Neural Coactivity Code for Dynamic Memory

Coincidental spike discharge amongst distributed groups of neurons is thought to provide an efficient mechanism for encoding percepts, actions and cognitive processes1-3. Short timescale coactivity can indeed bind neurons with similar tuning, giving rise to robust representations congruent with those of the participating neurons4-6. Alternatively, coactivity may also play a role in information processing through encoding variables not represented by individual neurons. While this type of emergent coactivity-based coding has been described for physically well-defined variables, including percepts and actions7-10, its role in encoding abstract cognitive variables remains unknown. Coactivity-based representation could provide a flexible code in dynamic environments, where animals must regularly learn short-lived behavioural contingencies. Here, we tested this possibility by training mice to discriminate two new behavioural contingencies every day, while monitoring and manipulating neural ensembles in the hippocampal CA1. We found that, while the spiking of neurons within their place fields is organised into congruent coactivity patterns representing discrete locations during unsupervised exploration of the learning enclosure, additional neurons synchronised their activity into spatially-untuned patterns that discriminated opposing learning contingencies. This contingency discrimination was an emergent property of millisecond timescale coactivity rather than the tuning of individual neurons, and predicted trial-by-trial memory performance. Moreover, optogenetic suppression of plastic inputs from the upstream left CA3 region during learning selectively impaired the computation of contingency-discriminating, but not space-representing CA1 coactivity patterns. This manipulation, but not silencing the more stable right CA3 inputs, impaired memory of the contingency discrimination. Thus, the computation of an emergent, coactivity-based discrimination code necessitates plastic synapses and supports dynamic, two-contingency memory.

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bioRxiv2018

Basal forebrain and brainstem cholinergic neurons differentially impact amygdala circuits and learning-related behavior

The central cholinergic system and the amygdala are important for motivation and mnemonic processes. Different cholinergic populations innervate the amygdala but it is unclear how these projections impact amygdala processes. Using optogenetic circuit-mapping strategies in ChAT-cre mice we demonstrate that amygdala-projecting basal forebrain and brainstem ChAT-containing neurons can differentially affect amygdala circuits and behavior. Photo-activating ChAT terminals in vitro revealed the underlying synaptic impact of brainstem inputs to the central lateral division to be excitatory, mediated via the synergistic glutamatergic activation of AMPA and NMDA receptors. In contrast, stimulating basal forebrain inputs to the basal nucleus resulted in endogenous ACh release resulting in biphasic inhibition-excitation responses onto principal neurons. Such response profiles are physiological hallmarks of neural oscillations and could thus form the basis of acetylcholine-mediated rhythmicity in amygdala networks. Consistent with this, in vivo NBm activation strengthened amygdala basal nucleus theta and gamma frequency rhythmicity, both of which continued for seconds after stimulation and were dependent on local muscarinic or nicotinic receptor activation, respectively. Activation of brainstem ChAT-containing neurons however resulted in a transient increase in central lateral amygdala activity that was independent of cholinergic receptors. In addition, driving these respective inputs in behaving animals induced opposing appetitive and defensive learning-related behavioral changes. Since learning and memory is supported by both cellular and network-level processes in central cholinergic and amygdala networks, these results provide a route by which distinct cholinergic inputs can convey salient information to the amygdala and promote associative biophysical changes that underlie emotional memories.

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bioRxiv2018

Cerebral organoids at the air-liquid interface generate diverse nerve tracts with functional output

Three-dimensional neural organoids are emerging tools with the potential for improving our understanding of human brain development and neurological disorders. Recent advances in this field have demonstrated their capacity to model neurogenesis1,2, neuronal migration and positioning3,4, and even response to sensory input5. However, it remains to be seen whether these tissues can model axon guidance dynamics and the formation of complex connectivity with functional neuronal output. Here, we have established a longterm air-liquid interface culture paradigm that leads to improved neuronal survival and allows for imaging of axon guidance. Over time, these cultures spontaneously form thick axon tracts capable of projecting over long distances. Axon bundles display various morphological behaviors including intracortical projection within and across the organoid, growth cone turning, decussation, and projection away from the organoid. Single-cell RNA-sequencing reveals the full repertoire of cortical neuronal identities, and retrograde labelling demonstrates these tract morphologies match the appropriate molecular identities, namely callosal and corticofugal neuron types. We show that these neurons are functionally mature, generate active networks within the organoid, and that extracortical projecting tracts innervate and activate mouse spinal cord-muscle explants. Muscle contractions can be evoked by stimulation of the organoid, while axotomy of the innervating tracts abolishes the muscle contraction response, demonstrating dependence on connection with the organoid. Overall, these results reveal a remarkable selforganization of corticofugal and callosal tracts with a functional output, providing new opportunities to examine relevant aspects of human CNS development and response to injury.

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