Biology subjects

Perez-Gonzalez, D.

Publications and source records attributed to Perez-Gonzalez, D..

4 recordsLinked to original sources

bioRxiv2025

Comparison and Dynamic interaction between Auditory Cortex and Prefrontal Cortex of Behaving Monkeys during Novelty Detection

The ability to detect deviations from expected sensory input is fundamental for adaptive behavior. We recorded electrocorticographic activity from the auditory (AC) and prefrontal (PFC) cortices of behaving macaques during an auditory oddball task to probe the cortical dynamics of predictive processing. Repetition of standard stimuli evoked suppression and facilitation in AC and strong low-frequency (2 Hz) enhancement in PFC, accompanied by bidirectional delta-band coupling indicative of a shared predictive state. Deviant stimuli triggered early AC responses followed by PFC activation and increased feedforward and feedback connectivity across delta, theta, and gamma bands. Behavioral engagement amplified both prediction and prediction error signals, strengthening cortical network coordination. Together, these findings reveal a hierarchical predictive network in which the AC encodes sensory regularities and violations, while the PFC integrates predictive context in a behaviorally dependent manner.

neuroscience↗

bioRxiv2023

Acetylcholine Modulates the Precision of Prediction Error in the Auditory Cortex

A fundamental property of sensory systems is their ability to detect novel stimuli in the ambient environment. The auditory brain contains neurons that decrease their response to repetitive sounds but increase their firing rate to novel or deviant stimuli; the difference between both responses is known as stimulus-specific adaptation or neuronal mismatch (nMM). Here, we tested the effect of microiontophoretic applications of ACh on the neuronal responses in the auditory cortex (AC) of anesthetized rats during an auditory oddball paradigm, including cascade controls. Results indicate that ACh modulates the nMM, affecting prediction error responses but not repetition suppression, and this effect is manifested predominantly in infragranular cortical layers. The differential effect of ACh on responses to standards, relative to deviants (in terms of averages and variances), were consistent with the representational sharpening that accompanies an increase in the precision of prediction errors. These findings suggest that ACh plays an important role in modulating prediction error signaling in the AC and gating the access of these signals to higher cognitive levels.

neuroscience↗

bioRxiv2019

Dopamine gates prediction error forwarding in the cortices of the inferior colliculus

The predictive processing framework describes perception as a hierarchical predictive model of sensation. Higher-level neural structures constrain the processing at lower-level structures by suppressing synaptic activity induced by predictable sensory input. But when predictions fail, deviant input is forwarded bottom-up as prediction error to update the perceptual model. The earliest prediction error signals identified in the auditory pathway emerge from the nonlemniscal inferior colliculus (IC). The drive that these feedback signals exert on the perceptual model depends on their expected precision, which determines the postsynaptic gain applied in prediction error forwarding. Expected precision is theoretically encoded by the neuromodulatory (e.g., dopaminergic) systems. To test this empirically, we recorded extracellular responses from the rat nonlemniscal IC to oddball and cascade sequences before, during and after the microiontophoretic application of dopamine or eticlopride (a D2-like receptor antagonist). Hence, we studied dopaminergic modulation on the subcortical processing of unpredictable and predictable auditory changes. Results demonstrate that dopamine reduces the net neuronal responsiveness exclusively to unexpected input, without significantly altering the processing of expected auditory events at population level. We propose that, in natural conditions, dopaminergic projections from the thalamic subparafascicular nucleus to the nonlemniscal IC could serve as a precision-weighting mechanism mediated by D2-like receptors. Thereby, the levels of dopamine release in the nonlemniscal IC could modulate the early bottom-up flow of prediction error signals in the auditory system by encoding their expected precision.

neuroscience↗

bioRxiv2019

Prediction errors explain mismatch signals of neurons in the medial prefrontal cortex

The mismatch negativity (MMN) is a key biomarker of automatic deviance detection thought to emerge from two cortical sources. First, the auditory cortex (AC) encodes spectral regularities and reports frequency-specific deviances. Then, more abstract representations in the prefrontal cortex (PFC) allow to detect contextual changes of potential behavioral relevance. However, the precise location and time asynchronies between neuronal correlates underlying this fronto-temporal network remain unclear and elusive. Our study presented auditory oddball paradigms along with no-repetition controls to record mismatch responses in neuronal spiking activity and local field potentials at the rat medial PFC. Whereas mismatch responses in the auditory system are mainly induced by stimulus-dependent effects, we found that auditory responsiveness in the PFC was driven by unpredictability, yielding context-dependent, comparatively delayed, more robust and longer-lasting mismatch responses mostly comprised of prediction error signaling activity. This characteristically different composition discarded that mismatch responses in the PFC could be simply inherited or amplified downstream from the auditory system. Conversely, it is more plausible for the PFC to exert top-down influences on the AC, since the PFC exhibited flexible and potent predictive processing, capable of suppressing redundant input more efficiently than the AC. Remarkably, the time course of the mismatch responses we observed in the spiking activity and local field potentials of the AC and the PFC combined coincided with the time course of the large-scale MMN-like signals reported in the rat brain, thereby linking the microscopic, mesoscopic and macroscopic levels of automatic deviance detection.

neuroscience↗