Biology subjects

Maldonado, P. E.

Publications and source records attributed to Maldonado, P. E..

4 recordsLinked to original sources

bioRxiv2020

Extending the integrate-and-fire model to account for metabolic dependencies

It is widely accepted that the brain, like any other physical system, is subjected to physical constraints restricting its operation. The brains metabolic demands are particularly critical for proper neuronal function, but the impact of these constraints is still poorly understood. Detailed single-neuron models are recently integrating metabolic constraints, but the computational resources these models need, make it difficult to explore the dynamics of extended neural networks imposed by such constraints. Thus, there is a need for a simple-enough neuron model that incorporates metabolic activity and allows us to explore neural network dynamics. This work introduces an energy-dependent leaky integrate-and-fire (LIF) neuronal model extension to account for the effects of metabolic constraints on the single-neuron behavior (EDLIF). This simple energy-dependent model shows better performance predicting real spikes trains -in spike coincidence measure sense-than the classical leaky integrate-and-fire model. It can describe the relationship between the average firing rate and the ATP cost, and replicate a neurons behavior under a clinical setting such as amyotrophic lateral sclerosis. The simplicity of the energy-dependent model presented here, makes it computationally efficient and thus, suitable to study the dynamics of large neural networks. Author summaryAny physical system or biological tissue is restricted by physical constraints bounding their behavior, and the brain is not free from these constraints. Energetic disorders in the brain have been linked to several neurodegenerative diseases, highlighting the relevance of maintaining a critical balance between energy production and consumption in neurons. These observations motivate the development of mathematical tools that can help to understand the dependence of the brains behavior in metabolism. One of the essential building blocks to achieve this task is the mathematical representation of neurons through models, allowing computational simulations of single-neurons and neural networks. Here we construct a simple and computational cheap energy-dependent neuron model that allows the study of neurons behavior under an energetic perspective. The introduced neuron model is contrasted with one of the widest-used neuron models and shows better prediction capabilities when real neuron recordings are used. Our model is suitable for replicating neurons behavior under a specific neurodegenerative disease, which cannot be achieved by the abovementioned popular model. Our simple model is promising because it allows the simulation and study of neuronal networks under a metabolic-dependent perspective.

neuroscience↗

bioRxiv2020

Agency improves working memory and accelerates visual and attentional processing

Agency, understood as the ability of an organism to control stimuli onset, modulates perceptual and attentional functions. Since stimulus encoding is an essential component of working memory (WM), we conjectured that the perceptual processs agency would positively modulate WM. To corroborate this proposition, we tested twenty-five healthy subjects in a modified-Sternberg WM task under three stimuli presentation conditions: an unpredictable presentation of encoding stimulus, self-initiated presentation of the stimulus, and self-initiation presentation with random-delay stimulus onset. Concurrently, we recorded the subjects electroencephalographic signals during WM encoding. We found that the self-initiation condition was associated with better WM accuracy, and earlier latencies of N100 and P200 evoked potential components representing visual and attentional processes, respectively. Our work demonstrates that agency enhances WM performance and accelerates early visual and attentional processes deployed during WM encoding. We also found that self-initiation presentation correlates with an increased attentional state compared to the other two conditions, suggesting a role for temporal stimuli predictability. Our study remarks on the relevance of agency in sensory and attentional processing for WM.

neuroscience↗

bioRxiv2018

Local Cortical Activity Of Distant Brain Areas Can Time-Lock To The Respiratory Rhythm In The Freely Behaving Rat

An important unresolved question about neural processing is the mechanism by which distant brain areas coordinate their activities and relate their local processing to global neural events. A potential candidate for the local-global integration are slow rhythms such as respiration, which is also linked to sensory exploration. In this article, we asked if there are modulations of local cortical processing which are time-locked to (peripheral) sensory-motor exploratory rhythms. We studied rats freely behaving on an elevated platform where they would display exploratory and rest behaviors. Concurrent with behavior, we monitored orofacial sampling rhythms (whisking and sniffing) and local field potentials (LFP) from olfactory bulb, dorsal hippocampus, primary motor cortex, primary somatosensory cortex and primary visual cortex. We defined exploration as simultaneous whisking and sniffing above 5 Hz and found that this activity peaked at about 8 Hz. We considered rest as the absence of whisking and sniffing, and in this case, mean respiration occurred at about 3 Hz. We found a consistent shift across all areas toward these rhythm peaks accompanying behavioral state changes. We also found, across areas, that LFP gamma (70-100 Hz) amplitude could phase-lock to the animals respiratory rhythm, a finding indicative of respiration-locked changes in local processing. The respiratory rhythm, although occurring at the same frequencies of hippocampal theta, was not spectrally coherent with it, implying a different oscillator. Our results are consistent with the notion of respiration as a binder or integrator of activity between distant brain regions.

neuroscience↗

bioRxiv2017

Precise Timing Of Sensory Modulations Coupled To Eye Movements During Active Vision

Perception is the result of ongoing brain activity combined with sensory stimuli. In natural vision, changes in the visual input typically occur as the result of self-initiated eye movements. Nonetheless, in most studies, stimuli are flashed, and natural eye movements are avoided or restricted. As a consequence, the neural sensory processing associated with active vision is poorly understood. Here, we show that occipital event-related potentials (ERP) to eye movements during free exploration of natural images exhibited different amplitudes, time course and motor dependency than that from the same flashed stimuli. We found that the ERP to visual fixations doubles in P1 magnitude and does not show a late component, which is classically seen with flashed stimuli1,2. In addition, we discovered that the ERP to the saccade onset was as large as the ERP to fixations onset, with an early component that preceded the visual input, suggesting that a motor modulation was associated with the saccades3. Furthermore, the use of different visual scenes revealed that both the ERP amplitude and time course were dependent on the type of image explored. Our results demonstrated that during active vision, the nervous system engages a mechanism of sensory modulation that is precisely timed to the self-initiated stimulus changes. This mechanism could help coordinate neural activity across different cortical areas and, by extension, serve as a general mechanism for the global coordination of neural networks.

neuroscience↗