Biology subjects

Aguiar, P.

Publications and source records attributed to Aguiar, P..

18 recordsLinked to original sources

bioRxiv2026

Closed-loop control of in vitro neuronal activity using reinforcement learning after in silico pre-training

Controlling specific neuronal dynamics with electrical stimulation is critical for therapeutic neuromodulation, yet deriving optimal control policies remains challenging due to the complex and non-stationary nature of biological neuronal networks. While reinforcement learning (RL) offers a powerful closed-loop control framework, its reliance on prolonged stimulus-driven exploration is difficult to reconcile with the physiological limits of living tissue. Here, we demonstrate an in silico-to-in vitro transfer strategy that achieves efficient state-dependent control of network bursting in cultured neurons. The transferred policy outperforms heuristic controls, while maintaining constrained stimulation usage. Concurrent calcium imaging reveals the mechanistic basis of the learned policy: the agent optimizes stimulation spatially and temporally, exploiting local network topology and intrinsic physiological temporal dynamics. These results establish in vitro brain-on-chip cultures as a tractable stepping stone for RL-based neuromodulation and demonstrate that effective control policies can be derived in biophysically calibrated digital twins and transferred directly to living networks.

neuroscience↗

bioRxiv2026

Low-latency neuromorphic closed-loop control of hippocampal ripples in vivo

Real-time closed-loop neuromodulation, in which stimulation is precisely timed to ongoing brain dynamics, holds transformative potential for treating neurological disorders and probing neural circuit function. However, it requires low-latency, energy-efficient processing of high-bandwidth neural signals that conventional computing architectures struggle to deliver. Neuromorphic computing, which emulates the event-driven and massively parallel operation of biological neural circuits, offers a compelling alternative. Yet, its integration into closed-loop frameworks validated in vivo for fast, transient oscillations has not been demonstrated. Here, we present a fully integrated neuromorphic framework for real-time detection and manipulation of hippocampal ripples: brief (30-100 ms), high-frequency (100-250 Hz) oscillations that are critical for memory consolidation and implicated in neurological disorders. We train compact spiking neural networks comprising 41 neurons and 530 parameters using surrogate-gradient backpropagation, achieving detection performance competitive with deep learning models across 23 recording sessions while consuming up to 200-fold less energy when deployed on SpiNNaker neuromorphic hardware. Integration with the open-source Open Ephys platform yields total closed-loop latencies of approximately 50 ms, enabling intra-event stimulation in up to 80% of ripples. Validating the complete sensing-processing-stimulation pipeline in awake, head-fixed mice, we demonstrate that neuromorphic-triggered optogenetic inhibition significantly alters ripple dynamics and reduces oscillatory energy. This work establishes a practical and accessible neuromorphic framework for low-latency closed-loop control of fast brain dynamics in vivo.

neuroscience↗

bioRxiv2025

Reprogramming breast cancer cells to breast cancer stem cell-like by the POU1F1 transcription factor

Breast cancer stem cells (BCSCs) have been proposed as the cause of resistance to conventional treatments and as the origin of breast cancer recurrence and metastasis. However, BCSC origin is not fully understood. Using breast cancer cell lines with POU1F1 overexpression and knockdown as well as immunodeficient mice models, this study provides compelling evidence of the role of POU1F1 in reprogramming breast cancer cells into BCSC-like by deregulating CD24, CD44, CD133, and ALDH markers. In addition, a subpopulation from POU1F1 overexpressing MCF-7 cells with high levels of ALDH present functional changes, e.g., higher invasion, glycolytic metabolism, increased clonogenicity and mammosphere formation, high tumor-initiating capacity, and resistance to treatment. Mechanistically, these features seem to be mediated by POU1F1 activation of the IL-6/JAK2/STAT3 pathway. Our data suggests that hormone therapy-resistant Luminal A breast tumors with high levels of POU1F1 could be targeted by blocking the IL-6/JAK2/STAT3 pathway.

cancer biology↗

bioRxiv2024

Stress-actuated Flexible Microelectrode Arrays for Activity Recording in 3D Neuronal Cultures

Microelectrode arrays (MEAs) are instrumental in monitoring electrogenic cell populations, such as neuronal cultures, allowing high precision measurements of electrical activity. Although three-dimensional neuronal cultures replicate the behavior of in vivo systems better than two-dimensional models, conventional planar MEAs are not well suited to capture activity within such networks. Novel MEA geometries can overcome this difficulty, but often at the cost of increased fabrication complexity. Here, we used the stress mismatch between thin film layers to fabricate MEAs with vertical electrodes, using methods compatible with established microfabrication protocols. A micrometric SiO2 hinge enables control over the bending angle of flexible polyimide structures with embedded electrodes. The performance of the patterned electrodes was assessed before and after stress actuation, through impedance measurements, voltage noise mapping, and neuronal activity recordings. 3D MEAs with 30x30 {micro}m2 electrodes showed an impedance of 0.96 {+/-} 0.07 M{Omega} per electrode and detected neuronal activity spikes with amplitudes as high as 400 {micro}V. These results demonstrate the potential of the developed methods to provide a scalable approach to fabricate 3D MEAs, enabling enhanced recording capabilities for in vitro neuronal cultures.

bioengineering↗

bioRxiv2024

Influence of asymmetric microchannels in the structure and function of engineered neuronal circuits

Understanding the intricate structure-function relationships of neuronal circuits is crucial for unraveling how the brain sustains efficient information transfer. In specific brain regions, like the hippocampus, neurons are organized in layers and form unidirectional connectivity, which is thought to help ensure controlled signal flow and information processing. In recent years, researchers have tried emulating these structural principles by providing cultured neurons with asymmetric environmental cues, namely microfluidics microchannels that promote directed axonal growth. Even though a few reports have claimed achieving unidirectional connectivity of in vitro neuronal circuits, given the lack of functional characterization, whether this structural connectivity correlates with functional connectivity remains unknown. We have replicated and tested the performance of asymmetric microchannel designs previously reported in the literature to be successful in the promotion of directed axonal growth, as well as other custom variations. A new variation of "Arrowhead", termed "Rams", was the best-performing motif with a [~]76% probability per microchannel of allowing strictly unidirectional connections at 14 days in vitro. Importantly, we assessed the functional implications of these different asymmetric microchannel designs. For this purpose, we combined custom microfluidics with microelectrode array (MEA) technology to record the electrophysiological activity of two segregated populations of hippocampal neurons ("Source" and "Target"). This functional characterization revealed that up to [~]94% of the spiking activity recorded along microchannels with the "Rams" motif propagates towards the "Target" population. Moreover, our results indicate that these engineered circuits also tended to exhibit network-level synchronizations with defined directionality. Overall, this characterization of the structure-function relationships promoted by asymmetric microchannels has the potential to provide insights into how neuronal circuits use specific network architectures for effective computations. Moreover, the here-developed devices and approaches may be used in a wide range of applications, such as disease modeling or preclinical drug screening.

neuroscience↗

bioRxiv2024

Excitatory and inhibitory synapses form a tight subcellular balance along dendrites that decorrelates over development

A balance between excitation and inhibition is crucial for neurotypical brain function. Indeed, disruptions in this relationship are frequently associated with the pathophysiology of neurodevelopmental disorders. Nevertheless, how this balance is established during the dynamic period of neurodevelopment remains unexplored. Using multiple techniques, including in utero electroporation, electron microscopy and electrophysiology, we reveal a tight correlation in the distribution of excitatory and inhibitory synapses along dendrites of developing CA1 hippocampal neurons. This balance was present within short dendritic stretches (<20{micro}m), and surprisingly, was most pronounced during early development, sharply declining with maturity. The tight matching between excitation and inhibition was unexpected, as inhibitory synapses lacked an active zone when formed and exhibited compromised evoked release. We propose that inhibitory synapses form as a stabilising scaffold, to counterbalance growing excitation levels. This relationship diminishes over time, suggesting a critical role for a subcellular balance in early neuronal function and circuit formation.

neuroscience↗

bioRxiv2024

Bringing astrocytes into the spotlight of electrical brain stimulation

Astrocytes, primarily viewed only as supportive units, are now emerging as active players in the information processing of the brain. Accumulated evidence supports that the bidirectional communication between astrocytes and neurons maintains complex animal behaviours such as memory formation and decision-making. The lack of characterisation of astrocytic electrophysiology is, in our opinion, associated with the early idea of a passive electrical nature of astrocytes, in opposition to the electrically active neurons. A better understanding of the effect of electrical stimulation on astrocytes physiology and activity will greatly strengthen the current knowledge in neural biology. Here, we assessed if astrocytes may have a role in therapies based on electrical brain stimulation by being able to respond to the same electrical stimulus used to modulate neuronal activity. To do so, we took advantage of microelectrode arrays (MEAs) capability to simultaneously record and deliver extracellular electrical signals. Additionally, we synchronized the recording of electrophysiological data with the recording of calcium activity, a hallmark of astrocytic activity. Here, we show that astrocytes respond to electrical stimulation with the generation of strong membrane voltage oscillations and simultaneous production of calcium waves, demonstrating, unequivocally, that astrocytes respond to electrical stimulation in the same range as neurons do. Importantly, these responses are dependent on the stimuli amplitude. Furthermore, membrane voltage oscillations are significantly reduced in the absence of extracellular calcium, but not abolished, while calcium activity is not detected.

neuroscience↗

bioRxiv2022

A novel closed-loop control algorithm to disrupt pathological neuronal oscillations - implementation and validation in vitro

Adaptive neuronal stimulation has a strong therapeutic potential for neurological disorders such as Parkinsons disease and epilepsy. However, standard stimulation protocols mostly rely on continuous open-loop stimulation. We implement here, for the first time in neuronal populations, two different Delayed Feedback Control (DFC) algorithms and assess their efficacy in disrupting unwanted neuronal oscillations. DFC is a well-established closed-loop control technique but its use in neuromodulation has been limited so far to models and computational studies. Leveraging on the high spatiotemporal monitoring capabilities of specialized in vitro platforms, we show that standard DFC in fact worsens the neuronal population oscillatory behaviour and promotes faster bursting, which was never reported in silico. Alternatively, we present adaptive DFC (aDFC) that monitors ongoing oscillation periodicity and self-tunes accordingly. aDFC disrupts collective neuronal oscillations and decreases network synchrony. Furthermore, we show that the intrinsic population dynamics have a strong impact in the susceptibility of networks to neuromodulation. Experimental data was complemented with computer simulations to show how this network controllability might be determined by specific network properties. Overall, these results support aDFC as a better candidate for therapeutic neurostimulation and provide new insights regarding the controllability of neuronal systems.

neuroscience↗

bioRxiv2022

BigNeuron: A resource to benchmark and predict best-performing algorithms for automated reconstruction of neuronal morphology

BigNeuron is an open community bench-testing platform combining the expertise of neuroscientists and computer scientists toward the goal of setting open standards for accurate and fast automatic neuron reconstruction. The project gathered a diverse set of image volumes across several species representative of the data obtained in most neuroscience laboratories interested in neuron reconstruction. Here we report generated gold standard manual annotations for a selected subset of the available imaging datasets and quantified reconstruction quality for 35 automatic reconstruction algorithms. Together with image quality features, the data were pooled in an interactive web application that allows users and developers to perform principal component analysis, t-distributed stochastic neighbor embedding, correlation and clustering, visualization of imaging and reconstruction data, and benchmarking of automatic reconstruction algorithms in user-defined data subsets. Our results show that image quality metrics explain most of the variance in the data, followed by neuromorphological features related to neuron size. By benchmarking automatic reconstruction algorithms, we observed that diverse algorithms can provide complementary information toward obtaining accurate results and developed a novel algorithm to iteratively combine methods and generate consensus reconstructions. The consensus trees obtained provide estimates of the neuron structure ground truth that typically outperform single algorithms. Finally, to aid users in predicting the most accurate automatic reconstruction results without manual annotations for comparison, we used support vector machine regression to predict reconstruction quality given an image volume and a set of automatic reconstructions.

bioinformatics↗

bioRxiv2022

Deep learning-based system for real-time behavior recognition and closed-loop control of behavioral mazes using depth sensing

Robust quantification of animal behavior is fundamental in experimental neuroscience research. Systems providing automated behavioral assessment are an important alternative to manual measurements avoiding problems such as human bias, low reproducibility and high cost. Integrating these tools with closed-loop control systems creates conditions to correlate environment and behavioral expressions effectively, and ultimately explain the neural foundations of behavior. We present an integrated solution for automated behavioral analysis of rodents using deep learning networks on video streams acquired from a depth-sensing camera. The use of depth sensors has notable advantages: tracking/classification performance is improved and independent of animals coat color, and videos can be recorded in dark conditions without affecting animals natural behavior. Convolutional and recurrent layers were combined in deep network architectures, and both spatial and temporal representations were successfully learned for a 4- classes behavior classification task (standstill, walking, rearing and grooming). Integration with Arduino microcontrollers creates an easy-to-use control platform providing low-latency feedback signals based on the deep learning automatic classification of animal behavior. The complete system, combining depth-sensor camera, computer, and Arduino microcontroller, allows simple mapping of input-output control signals using the animals current behavior and position. For example, a feeder can be controlled not by pressing a lever but by the animal behavior itself. An integrated graphical user interface completes a user-friendly and cost-effective solution for animal tracking and behavior classification. This open-software/open-hardware platform can boost the development of customized protocols for automated behavioral research, and support ever more sophisticated, reliable and reproducible behavioral neuroscience experiments.

animal behavior and cognition↗

bioRxiv2021

Nanoscale patterning of in vitro neuronal circuits

Methods for patterning neurons in vitro have gradually improved and are used to investigate questions difficult to address in or ex vivo. Though these techniques guide axons between groups of neurons, multiscale control of neuronal connectivity, from circuits to synapses, is yet to be achieved in vitro. As studying neuronal circuits with synaptic resolution in vivo poses significant challenges, an in vitro alternative could serve as a testbed for in vivo experiments or as a platform for validating biophysical and computational models. In this work we use a combination of electron beam and photolithography to create polydimethylsiloxane (PDMS) structures with features ranging from 150 nanometers to a few millimeters. Leveraging the difference between average axon and dendritic spine diameters, we restrict axon growth while allowing spines to pass through nanochannels to guide synapse formation between small groups of neurons (i.e. nodes). We show this technique can be used to generate large numbers of isolated feed-forward circuits where connections between nodes are restricted to regions connected by nanochannels. Using a genetically encoded calcium indicator in combination with fluorescently tagged post synaptic protein, PSD-95, we demonstrate functional synapses can form in this region. Although more work needs to be done to control connectivity in vitro, we believe this is a significant step in that direction.

neuroscience↗

bioRxiv2021

Mechanosensitive control of mitotic entry

As cells prepare to divide, they must ensure that enough space is available to assemble the mitotic machinery without perturbing tissue homeostasis1. To do so, cells undergo a series of biochemical reactions regulated by cyclin B1-CDK1 that trigger the reorganization of the actomyosin cytoskeleton2 and ensure the coordination of cytoplasmic and nuclear events3. Along with the biochemical events that control mitotic entry, mechanical forces have recently emerged as important players in the regulation of cell cycle events4-6. However, the exact link between mechanical forces and the biochemical pathways that control mitotic progression remains to be established. Here, we identify a mechanical signal on the nucleus that helps set the time for nuclear envelope permeabilization (NEP) and mitotic entry. This signal relies on actomyosin contractility, which leads to nuclear unfolding during the G2-M transition, activating the stretch-sensitive cPLA2 on the nuclear envelope. This contributes to the spatiotemporal translocation of cyclin B1 to the nucleus. Our data demonstrate how nuclear mechanics during the G2-M transition contribute to timely and efficient mitotic spindle assembly and prevents chromosomal instability.

cell biology↗

bioRxiv2021

A mitotic screen in Indian muntjac cells unveils how Augmin drives kinetochore fiber maturation

Chromosome segregation in mammals relies on the maturation of a thick bundle of kinetochore-attached microtubules known as k-fibers. How k-fibers mature from initial kinetochore-microtubule attachments remains a fundamental question. By combining functional perturbations in Indian muntjac, a placental mammal with the lowest known chromosome number (n=3) and distinctively large kinetochores, with fixed- and subsecond live-cell super-resolution CH-STED nanoscopy, we uncovered the mechanism by which Augmin mediates k-fiber maturation. Augmin promoted kinetochore microtubule turnover by sustaining microtubule formation from kinetochores and poleward flux, regardless of pioneer centrosomal microtubules. Tracking of microtubule growth events within individual k-fibers revealed a wide angular dispersion, consistent with Augmin-mediated branched microtubule nucleation. Augmin depletion reduced the frequency of microtubule growth events within k-fibers and hampered normal repair after acute k-fiber injury by laser microsurgery. Our work underscores the contribution of microtubule formation from kinetochores and Augmin-mediated microtubule amplification for k-fiber maturation and spindle assembly in mammals.

cell biology↗

bioRxiv2021

A memristor-based neuromodulation device for real-time monitoring and adaptive control of in vitro neuronal populations

Neurons are specialized cells in information transmission and information processing. Following this, many neurologic disorders are directly linked not to cellular viability/homeostasis issues but rather to specific anomalies in electrical activity dynamics. Acknowledging this fact, therapeutic strategies based on direct modulation of neuronal electrical activity have been producing remarkable results, with successful examples ranging from cochlear implants to deep brain stimulation. Development on these implantable devices are hindered, however, by important challenges: power requirements, size factor, signal transduction, and adaptability/computational capabilities. Memristors, nanoscale electronic components able to emulate natural synapses, provide unique properties to address these constraints and their use in neuroprosthetic devices is being actively explored. Here we demonstrate for the first time the use of memristive devices in a clinically relevant setting where communication between two neuronal populations is conditioned to specific activity patterns in the source population. In our approach, the memristor device performs a simple pattern detection computation and acts as a synapstor capable of reversible short-term plasticity. Using in vitro hippocampal neuronal cultures, we show real-time adaptive control with a high degree of reproducibility using our monitor-compute-actuate paradigm. We envision very similar systems being used for automatic detection and suppression of seizures in epileptic patients.

neuroscience↗

bioRxiv2021

In vitro neuronal networks show bidirectional axonal conduction with antidromic action potentials effectively depolarizing the soma

Recent technological advances are revealing the complex physiology of the axon and challenging long-standing assumptions. Namely, while most action potential (AP) initiation occurs at the axon initial segment in central nervous system neurons, initiation in distal parts of the axon has been shown to occur in both physiological and pathological conditions. However, such ectopic action potential (EAP) activity has not been reported yet in studies using neuronal cultures and its functional role, if exists, is still not clear. Here, we show the spontaneous occurrence of EAPs and effective antidromic conduction in hippocampal neuronal cultures. We also observe a significant fraction of bidirectional axonal conduction in dorsal root ganglia neuronal cultures. We investigate and characterize this antidromic propagation via a combination of microfluidics, microelectrode arrays, advanced data analysis and in silico studies. We show that EAPs and antidromic conduction can occur spontaneously, and after distal axotomy or physiological changes in the axon biochemical environment. Conduction velocity is asymmetrical, with antidromic conduction being slower than orthodromic. Importantly, EAPs may carry information and can have a functional impact on the neuron, as they consistently depolarize the soma. Thus, plasticity or gene transduction mechanisms triggered by soma depolarization can also be affected by these antidromic APs. Altogether these findings have important implications for the study of neuronal function in vitro, reshaping our understanding on how information flows in neuronal cultures.

neuroscience↗

bioRxiv2020

Trackosome: a computational toolbox to study the spatiotemporal dynamics of centrosomes, nuclear envelope and cellular membrane

During the initial stages of mitosis, multiple mechanisms drive centrosome separation and positioning. How they are functionally coordinated to promote centrosome migration to opposite sides of the nucleus remains unclear. Imaging analysis software has been used to quantitatively study centrosome dynamics at this stage. However, available tracking tools are generic and not fine-tuned for the constrains and motion dynamics of centrosome pairs. Such generality limits the tracking performance and may require exhaustive optimization of parameters. Here, we present Trackosome, a freely available open-source computational tool to track the centrosomes and reconstruct the nuclear and cellular membranes, based on volumetric live-imaging data. The toolbox runs in MATLAB and provides a graphical user interface for easy and efficient access to the tracking and analysis algorithms. It outputs key metrics describing the spatiotemporal relations between centrosomes, nucleus and cellular membrane. Trackosome can also be used to measure the dynamic fluctuations of the nuclear envelope. A fine description of these fluctuations is important because they are correlated with the mechanical forces exerted on the nucleus by its adjacent cytoskeletal structures. Unlike previous algorithms based on circular/elliptical approximations of the nucleus, Trackosome measures membrane movement in a model-free condition, making it viable for irregularly shaped nuclei. Using Trackosome, we demonstrate significant correlations between the movements of the two centrosomes, and identify specific modes of oscillation of the nuclear envelope. Overall, Trackosome is a powerful tool to help unravel new elements in the spatiotemporal dynamics of subcellular structures.

cell biology↗

bioRxiv2019

Spatial Asymmetries of the Prophase Nucleus Regulate Dynein Recruitment to Ensure Mitotic Fidelity

During prophase, centrosomes need to separate and position to correctly assemble the mitotic spindle. This process occurs through the action of molecular motors, cytoskeletal networks and the nucleus. How the combined activity of these different components is spatiotemporally regulated to ensure efficient spindle assembly remains unclear. Here we show that during prophase the centrosomes-nucleus axis reorients, so that centrosomes are positioned on the shortest nuclear axis at nuclear envelope (NE) breakdown. This centrosomes-nucleus configuration depends on mechanical cues generated by mitotic chromosome condensation on the prophase nucleus. We further show these mechanosensitive cues act through SUN1/2 and NudE+NudEL to enable the polarized loading of Dynein on the NE. Finally, we observe this centrosome configuration favors the establishment of an initial bipolar spindle scaffold, facilitating chromosome capture and accurate segregation, without compromising division plane orientation. We propose that chromosome segregation fidelity depends on the mechanical properties of the prophase nucleus that facilitate spindle assembly by regulating NE-Dynein localization.

cell biology↗

bioRxiv2018

Chromosome (mis)segregation is biased by kinetochore size

Summary:\n\nAneuploidy, the gain or loss of chromosomes, arises through problems in chromosome segregation during mitosis or meiosis and has been implicated in cancer and developmental abnormalities in humans [1]. Possible routes to aneuploidy include a compromised spindle assembly checkpoint (SAC), cohesion defects, centrosome amplification, as well as improper kinetochore-microtubule attachments [2]. However, none of these established routes takes into account the intrinsic features of the kinetochore - the critical chromosomal interface with spindle microtubules. Kinetochore size and respective microtubule binding capacity varies between different animal and plant species [3-10], among different chromosomes from the same species (including humans) [3, 11-15], and in response to microtubule attachments throughout mitosis [16-18]. How kinetochore size impacts chromosome segregation remains unknown. Addressing this fundamental question in human cells is virtually impossible, because most of the 23 pairs of chromosomes cannot be morphologically distinguished, while detection of 2-3 fold differences in kinetochore size is limited by diffraction and cannot be resolved by conventional light microscopy in living cells. Here we used the unique cytological attributes of female Indian muntjac, the mammal with the lowest known chromosome number (n=3), to track individual chromosomes with distinct kinetochore sizes throughout mitosis. We found that chromosomes with larger kinetochores bi-orient more easily and are biased to congress to the equator in a motor-independent manner. However, they are also more prone to establish erroneous merotelic attachments and lag behind during anaphase. Thus, we uncovered an intrinsic kinetochore feature - size - as an important determinant of chromosome segregation fidelity.

cell biology↗