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Maldonado, P.

Publications and source records attributed to Maldonado, P..

2 recordsLinked to original sources

The relationship between confidence and gaze-at-nothing oculomotor dynamics during decision-making

How does confidence relate to oculomotor dynamics during decision-making? Do oculomotor dynamics reflect deliberation and the buildup of confidence in the absence of visual stimuli? Here we examine the hypothesis that working memory, deliberation, and confidence warp oculomotor dynamics, both in the presence and absence of visual stimuli. We analyzed oculomotor dynamics in a decision-making task in which participants were provided with an abstract context in which to make the decision, and two similar option images which became eventually invisible. We show that fixations between the empty locations in which the images were formerly shown continued after the options disappeared, consistently with a sustained deliberative process facilitated by oculomotor dynamics. Both, oculomotor dynamics and decision patterns remained unchanged regardless of whether the stimuli were visible. Furthermore, our analyses show that the number of alternative fixations between stimuli correlated negatively with the confidence reported after each decision, while the observation time of the selected target correlated positively. Given that decisions in our experimental paradigm are reported in the absence of the stimuli, this suggests a relationship between evidence retrieval from working memory, confidence gathering and oculomotor dynamics. Finally, we performed a model comparison based on predictions from drift-diffusion models to assess the relationship between sequential fixations between images, deliberation and confidence gathering, and the ensuing choice. These analyses supported confidence as a contributing cognitive process encompassing serial evidence-gathering and parallel option consideration during decision-making. One-Sentence SummaryThe dynamics of oculomotor dynamics between absent stimuli are related with the participants confidence during value-based decision-making.

neuroscience↗

Unveiling the role of local metabolic constraints on the structure and activity of spiking neural networks

Understanding the intricate interplay between neural dynamics and metabolic constraints is crucial for unraveling the mysteries of the brain. Despite the significance of this relationship, specific details concerning the impact of metabolism on neuronal dynamics and neural network architecture remain elusive, creating a notable gap in the existing literature. This study employs an energy-dependent neuron and plasticity model to analyze the role of local metabolic constraints in shaping both the dynamics and structure of Spiking Neural Networks (SNN). Specifically, an energy-dependent version of the leaky integrate-and-fire model is utilized, along with a three-factor learning rule that incorporates postsynaptic available energy as the third factor. These models allow for fine-tuning sensitivity in the presence of energy imbalances. Analytical expressions predicting the networks activity and structure are derived, and a fixed-point analysis reveals the emergence of attractor states characterized by neuronal and synaptic sensitivity to energy imbalances. Analytical findings are validated through numerical simulations using an excitatory-inhibitory network. Furthermore, these simulations enable the study of SNN activity and structure under conditions simulating metabolic impairment. In conclusion, by employing energy-dependent models with adjustable sensitivity to energy imbalances, our study advances the understanding of how metabolic constraints shape SNN dynamics and structure. Moreover, in light of compelling evidence linking neuronal metabolic impairment to neurodegenerative diseases, the incorporation of local metabolic constraints into the investigation of neuronal network structure and activity opens an intriguing avenue for inspiring the development of therapeutic interventions.

neuroscience↗