Biology subjects

Diaz, H.

Publications and source records attributed to Diaz, H..

4 recordsLinked to original sources

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↗

bioRxiv2024

Contextual Neural Dynamics During Time Perception in Primate Ventral Premotor Cortex

Understanding how time perception adapts to cognitive demands remains a significant challenge. In some contexts, the brain encodes time categorically (as "long" or "short"), while in others, it encodes precise time intervals on a continuous scale. Although the ventral premotor cortex (VPC) is known for its role in complex temporal processes, such as speech, its specific involvement in time estimation remains underexplored. In this study, we investigated how the VPC processes temporal information during a time interval comparison task (TICT) and a time interval categorization task (TCT) in primates. We found a notable heterogeneity in neuronal responses associated with time perception across both tasks. While most neurons responded during time interval presentation, a smaller subset retained this information during the working memory periods. Population-level analysis revealed distinct dynamics between tasks: in TICT, population activity exhibited a linear and parametric relationship with interval duration, whereas in TCT, neuronal activity diverged into two distinct dynamics corresponding to the interval categories. During delay periods, these categorical or parametric representations remained consistent within each task context. This contextual shift underscores the VPCs adaptive role in interval estimation and highlights how temporal representations are modulated by cognitive demands. Significance StatementThe neural representation of time has long intrigued neuroscientists, particularly how it adapts to cognitive demands. Depending on the task, the brain encodes time either categorically ("long" or "short") or as precise intervals. While the ventral premotor cortex (VPC) is known for its role in temporal processes, its role in time estimation remains underexplored. Here, we examined how the VPC processes temporal information in primates during a time interval comparison task (TICT) and a categorization task (TCT). The VPC exhibited heterogeneous neuronal responses with distinct dynamics: a linear, parametric relationship in TICT and bifurcated dynamics in TCT. These representations remained consistent during delay periods, underscoring the VPCs adaptive role in time interval estimation.

neuroscience↗

bioRxiv2022

Hierarchical unimodal processing within the primary somatosensory cortex during a bimodal detection task

Where and how in the brain do neurons process more than one sensory modality? To answer these questions, scientists have generated a wide variety of studies at distinct space-time scales in different animal models, and often shown contradictory conclusions. Some conclude that this process occurs in early sensory cortices, but others that this occurs in areas central to sensory cortices. Here, we sought to determine whether sensory neurons process and encode physical stimulus properties of different modalities (tactile and acoustic). For this, we designed a bimodal detection task where the senses of touch and hearing compete from trial to trial. Two Rhesus monkeys performed this novel task, while neural activity was recorded in areas 3b and 1 of the primary somatosensory cortex (S1). We analyzed neurons coding properties and variability, organizing them by their receptive fields position relative to the stimulation zone. Our results indicate that neurons of areas 3b and 1 are unimodal, encoding only the tactile modality, both in the firing rate and variability, but not to the acoustic one. Moreover, we found that neurons of both subareas encode the tactile information differently, revealing a hidden processingbased hierarchy. Finally, using a powerful non-linear dimensionality reduction algorithm, we show that the activity from areas 3b and 1 can be separated, establishing a clear division in the functionality of these two subareas of S1. SIGNIFICANCE STATEMENTOur brain integrates information from all our senses to perceive the external world. But where and how in the brain this integration occurs? Here we ask if the primary somatosensory cortex (S1) encodes information from more than one sensory modality. We recorded the activity of single neurons from areas 3b and S1, while trained monkeys performed a bimodal detection task, where tactile and acoustic stimuli compete. The analysis showed that neurons from areas 3b and 1 responded only to the tactile modality both in their rate and variability. However, our results support that these two areas are different enough as to be considered functionally distinct entities.

neuroscience↗