Biology subjects

Pardo-Vazquez, J. L.

Publications and source records attributed to Pardo-Vazquez, J. L..

4 recordsLinked to original sources

bioRxiv2026

Reduced food accessibility enhances value-based decision-making in rats

Finding nutrients regularly is critical for survival; therefore, most animals invest a large portion of their time and energy in securing access to food. Food acquisition activates the brain's reward system, enhancing motivation and thereby increasing chances to succeed again in the future. However, little is known about the effect of food accessibility on cognition. We hypothesize that reducing food accessibility by requiring laboratory animals to get it with effort, will expose them to daily learning challenges, enhance reward system engagement and consequently have a positive impact on cognitive performance. To test whether effortful access to food confers cognitive benefits, one group of rats was housed with a food dispenser specifically designed to reduce food accessibility (Low Accessibility, LA). The comparison group had free access to food at any time (High Accessibility, HA). Both groups were trained in a value-based task in which they were required to choose between two options and, through trial and error, learn which option was more likely to deliver a reward. We found that both groups learned the task structure similarly. However, the LA group showed a higher proportion of optimal choices throughout training, indicating better task performance. We also found that LA rats were more sensitive to the outcomes of previous decisions. Collectively, our findings suggest that reducing food accessibility improves value-based decision-making, potentially by increasing sensitivity to action outcomes, highlighting a previously underappreciated link between food acquisition demands and cognitive performance.

animal behavior and cognition↗

bioRxiv2018

State-dependent geometry of population activity in rat auditory cortex

The accuracy of the sensory neural code depends on the relationship between variability in population activity caused by the stimuli versus variability caused by noise. Whereas a large body of work has addressed this issue at a theoretical level, there have been few systematic empirical investigations using large-scale simultaneous recordings. We studied the geometry of the population code in the rat auditory cortex using sound stimuli varying across two orthogonal dimensions: the difference in sound level between the two ears, and the average level across the ears. We quantified the structure of the code across recordings spanning a wide range of brain states along the activation/inactivation continuum. We found that the nature of the code, both in terms of the stimulus and the noise subspaces, depends strongly on the degree of cortical activation. During the inactive (or synchronized) state, the code is characterized by a prevalence of contra-lateral tuning, a preference for loud sounds, gain-modulated tuning curves and coherent global noise fluctuations overlapping with the signal subspace. In contrast, in the most active (or desynchronized) recordings, there is an approximately symmetric preference between contra-, ipsi-, quiet and loud sounds, no systematic changes in the gain of lateralization tuning curves by sound intensity, and noise fluctuations span dimensions orthogonal to those evoked by the stimuli. Logistic regression could predict the sound lateralization with accuracy similar to the behaving rats, but only during cortical activation. Furthermore, also exclusively during the active state, the lateralization of sounds of different overall level could be decoded with the same accuracy, even by the same decoder, due to an orthogonal representation of level-differences and overall level across the population. Decoding accuracy from surrogate datasets with independent noise across neurons still displays strong state-dependence, suggesting that tuning curve reorganization plays a critical role in the overall effect of brain state on the population code. Our results provide an empirical foundation for the geometry and state dependence of cortical population codes.

neuroscience↗

bioRxiv2018

Weber’s law is the result of exact temporal accumulation of evidence

Webers law states that the discriminability between two stimulus intensities depends only on their ratio. Despite its status as the cornerstone of psychophysics, the mecha-nisms underlying Webers law are still debated, as no principled way exists to choose between its many proposed alternative explanations. We studied this problem training rats to discriminate the lateralization of sounds of different overall level. We found that the rats discrimination accuracy in this task is level-invariant, consistent with Webers law. Surprisingly, the shape of the reaction time distributions is also level-invariant, implying that the only behavioral effect of changes in the overall level of the sounds is a uniform scaling of time. Furthermore, we demonstrate that Webers law breaks down if the stimulus duration is capped at values shorter than the typical reaction time. Together, these facts suggest that Webers law is associated to a process of bounded evidence accumulation. Consistent with this hypothesis, we show that, among a broad class of sequential sampling models, the only robust mechanism consistent with reaction time scale-invariance is based on perfect accumulation of evidence up to a constant bound, Poisson-like statistics, and a power-law encoding of stimulus intensity. Fits of a minimal diffusion model with these characteristics describe the rats performance and reaction time distributions with virtually no error. Various manipulations of motivation were unable to alter the rats psychometric function, demonstrating the stability of the just-noticeable-difference and suggesting that, at least under some conditions, the bound for evidence accumulation can set a hard limit on discrimination accuracy. Our results establish the mechanistic foundation of the process of intensity discrimination and clarify the factors that limit the precision of sensory systems.

neuroscience↗

bioRxiv2017

Using experience to improve: How errors shape behavior and brain activity in monkeys

Previous works have shown that neurons from the ventral premotor cortex (PMv) represent several elements of perceptual decisions. One of the most striking findings was that, after the outcome of the choice is known, neurons from PMv encode all the information necessary for evaluating the decision process. These results prompted us to suggest that this cortical area could be involved in shaping future behavior. In this work, we have characterized neuronal activity and behavioral performance as a function of the outcome of the previous trial. We found that the outcome of the immediately previous trial (n-1) significantly changes, in the current trial (n), the activity of single cells and behavioral performance. The outcome of trial n-2, however, does not affect either behavior or neuronal activity. Moreover, the outcome of difficult trials had a greater impact on performance and recruited more PMv neurons than the outcome of easy trials. These results give strong support to our suggestion that PMv neurons evaluate the decision process and use this information to modify future behavior.

neuroscience↗