Biology subjects

Franci, A.

Publications and source records attributed to Franci, A..

7 recordsLinked to original sources

bioRxiv2025

A fast and tiny current as common generator of slow regular pacemaking in brain and heart

Slow pacemaking is a key physiological process in specific excitable cells, yet its underlying mechanism remains debated. Here we identify a conserved, voltage-dependent pacemaker current that is essential for slow, regular firing in both midbrain dopaminergic neurons and sinoatrial node myocytes. Conductance-based models incorporating this current reproduce stable pacemaking, requiring a fast-activating, small-amplitude current. This is further confirmed by dynamic-clamp experiments in dopaminergic neurons. Replacing the pacemaker current in a model with a voltage-independent conductance such as the non-selective sodium leak channels fails to sustain slow rhythmicity, highlighting the necessity for an adequate voltage dependence. Our results suggest a novel and shared biophysical mechanism for slow pacemaking in neuronal and cardiac systems.

physiology↗

bioRxiv2025

Relevance of Nonlinear Dimensionality Reduction for Efficient and Robust Spike Sorting

Spike sorting is one of the cornerstones of extracellular electrophysiology. By leveraging advanced signal processing and data analysis techniques, spike sorting makes it possible to detect, isolate, and map single neuron spiking activity from both in vivo and in vitro extracellular electrophysiological recordings. A crucial step of any spike sorting pipeline is to reduce the dimensionality of the recorded spike waveform data. Reducing the dimensionality of the processed data is a near-universal practice, fundamentally motivated by the use of clustering algorithms responsible to detect, isolate, and sort the recorded putative neurons. In this paper we propose and illustrate on both synthetic and experimental data that employing the nonlinear dimensionality reduction technique Uniform Manifold Approximation and Projection (UMAP) can drastically improve the performance, efficiency, robustness, and scalability of spike sorting pipelines without increasing their computational cost. We show how replacing the linear or ad hoc, expert-defined, supervised nonlinear dimensionality reduction methods commonly used in spike sorting pipelines by the unsupervised, mathematically grounded, nonlinear dimensionality reduction method provided by UMAP drastically increases the number of correctly sorted neurons, makes the identification of quieter, seldom spiking neurons more reliable, enables deeper and more precise explorations and analysis of the neural code, and paves new ways toward more efficient and end-to-end automatable spike sorting pipelines of large-scale extracellular neural recording as those produced by high-density multielectrode arrays.

neuroscience↗

bioRxiv2024

Multi-Stable Bimodal Perceptual Coding within the Ventral Premotor Cortex

Neurons in the primate ventral premotor cortex (VPC) respond to both tactile and acoustic stimuli, yet how they integrate and process information from these sensory modalities remains unclear. To investigate this, we recorded VPC neuronal activity in two trained monkeys performing a bimodal detection task (BDT), in which they reported the presence or absence of either a tactile or an acoustic stimulus. Single-cell analyses revealed diverse response types, including purely tactile, purely acoustic, bimodal, and neurons with sustained activity during the decision maintenance delay--the period between stimulus offset and motor response. To further examine VPCs role in the BDT, we applied dimensionality reduction techniques to uncover low-dimensional latent dynamics in the neuronal population and conducted parallel analyses using a recurrent neural network (RNN) model trained on the same task. Neural trajectories for tactile and acoustic responses diverged sharply, whereas in stimulus-absent trials, the dynamics remained at rest. During the delay period, the trajectories exhibited a pronounced rotational dynamic, shifting toward a subspace orthogonal to the sensory response space, suggesting memory maintenance through stable equilibria. This indicates that network dynamics can sustain distinct stable states corresponding to the three potential task outcomes. Using low-dimensional modeling, we propose a universal dynamical mechanism that underlies the transition from sensory processing to memory retention, aligning with both experimental and computational findings. These results demonstrate that VPC neurons encode bimodal information, integrate competing sensory inputs, and maintain decisions across the delay period, regardless of sensory modality.

neuroscience↗

bioRxiv2023

Orthogonality of sensory and contextual categorical dynamics embedded in a continuum of responses from the second somatosensory cortex

How does the brain simultaneously process signals that bring complementary information, like raw sensory signals and their transformed counterparts, without any disruptive interference? Contemporary research underscores the brain ss adeptness in using decorrelated responses to reduce such interference. Both neurophysiological findings and artificial neural networks (ANNs) support the notion of orthogonal representation for signal differentiation and parallel processing. Yet, where, and how raw sensory signals are transformed into more abstract representations remains unclear. Using a temporal pattern discrimination task (TPDT) in trained monkeys, we revealed that the second somatosensory cortex (S2) efficiently segregates faithful and transformed neural responses into orthogonal subspaces. Importantly, S2 population encoding for transformed signals, but not for faithful ones, disappeared during a non-demanding version of the task, which suggests that signal transformation and their decoding from downstream areas are only active on-demand. A mechanistic computation model points to gain modulation as a possible biological mechanism for the observed context-dependent computation. Furthermore, individual neural activities that underlie the orthogonal population representations exhibited a continuum of responses, with no well-determined clusters. These findings advocate that the brain, while employing a continuum of heterogeneous neural responses, splits population signals into orthogonal subspaces in a context-dependent fashion to enhance robustness, performance, and improve coding efficiency. SIGNIFICANCE STATEMENTAn important function of the brain is turning sensation into perception. Yet, how this function is implemented remains unknown. Current research, insights from artificial neural networks, highlights using of orthogonal representations as an effective means to transform sensory signals into perceptual signals while separating and simultaneously processing the two information streams. Neuronal recordings in S2 while trained monkeys performed the TPDT, revealed that this function is implemented at the population level. While S2 encodes sensory information independently of context, the encoding of categorical information, like task parameters, is only performed when the task demands it. Such distinct and flexible organization, enriched by a spectrum of neural activities, reflects the brains efficiency, resilience, and overall purpose for solving cognitive tasks.

neuroscience↗

bioRxiv2021

The environment topography alters the transition from single-cell populations to multicellular structures in Myxococcus xanthus

The social soil-dwelling bacteria Myxococcus xanthus can form multicellular structures, known as fruiting bodies. Experiments in homogeneous environments have shown that this process is affected by the physico-chemical properties of the substrate, but they have largely neglected the role of complex topographies. We experimentally demonstrate that the topography alters single-cell motility and multicellular organization in M. xanthus. In topographies realized by randomly placing silica particles over agar plates, we observe that the cells interaction with particles drastically modifies the dynamics of cellular aggregation, leading to changes in the number, size and shape of the fruiting bodies, and even to arresting their formation in certain conditions. We further explore this type of cell-particle interaction in a minimal computational model. These results provide fundamental insights into how the environment topography influences the emergence of complex multicellular structures from single cells, which is a fundamental problem of biological, ecological and medical relevance.

biophysics↗

bioRxiv2019

A Systems Biology perspective of Dynamical Patterning Modules in the transition to multicellularity: lessons from an aggregative bacteria

Development and evolution are dynamical processes under the continuous control of organismic and environmental factors. Generic physical processes, associated with biological materials and certain genes or molecules, provide a morphological template for the evolution and development of organism forms. Generic dynamical behaviors, associated with recurring network motifs, provide a temporal template for the regulation and coordination of biological processes. The role of generic physical processes and their associated molecules in development is the topic of the Dynamical Patterning Module (DPM) framework. The role of generic dynamical behaviors in biological regulation is studied via the identification of the associated Network Motifs (NM). We propose a joint DPM-NM perspective on the emergence and regulation of multicellularity focusing on a multicellular aggregative bacterium, Myxococcus xanthus. Understanding M. xanthus development as a dynamical process embedded in a physical substrate provides novel insights into the interaction between developmental regulatory networks and generic physical processes in the evolutionary transition to multicellularity.

systems biology↗

bioRxiv2018

Plastic multicellular development of Myxococcus xanthus: genotype-environment interactions in a physical gradient

In order to investigate the contribution of the physical environment to variation in multicellular development of Myxococcus xanthus, phenotypes developed by different genotypes in a gradient of substrate stiffness conditions were quantitatively characterized. Statistical analysis showed that plastic phenotypes result from the genotype, the substrate conditions and the interaction between them. Also, phenotypes were expressed with scale- and trait-specificity. Overall, the presented information highlights the constructive role of the physical context in the development of microbial multicellularity, with both ecological and evolutionary implications.

developmental biology↗