Jorge F. Mejías

Serotonin induces DOWN states across the anesthetized mouse forebrain

This study shows serotonin induces DOWN states in the anesthetized mouse forebrain, with effects on cortex and striatum but not midbrain, using optogenetics and Neuropixel recordings.

A computational architecture incorporating shallow brain networks: integrating parallel cortical and subcortical processing

The paper introduces a computational model integrating cortical and subcortical processing to better replicate brain behavior in decision-making tasks.

A dynamical systems model of arousal-driven behavioural state transitions

The paper models how arousal drives behavioural state transitions in mice using a dynamical systems approach, showing arousal affects engagement in a visual decision-making task.

Diverse and flexible behavioral strategies arise in recurrent neural networks trained on multisensory decision making

This study uses recurrent neural networks to model multisensory decision-making and finds that behavioral variability arises from network-specific strategies and modality-selectivity.

Cortical networks with multiple interneuron types generate oscillatory patterns during predictive coding

The paper presents a computational model of predictive coding in the cortex that incorporates biologically plausible neuron types and connectivity, showing how they generate oscillatory patterns and handle prediction errors.

Adaptive arousal regulation: Pharmacologically shifting the peak of the Yerkes-Dodson curve by catecholaminergic enhancement of arousal

This study pharmacologically manipulates arousal in humans to test its impact on performance, finding that catecholaminergic enhancement shifts the arousal-performance curve while cholinergic agents do not.

Mesoscale imaging of the human cerebellum reveals converging regional specialization of its morphology, vasculature and cytoarchitecture.

The paper uses mesoscale imaging to show cerebellar cortex heterogeneity in morphology, vasculature, and cytoarchitecture, challenging the notion of uniformity.

Synaptic plasticity facilitates oscillations in a V1 cortical column model with multiple interneuron types

The paper shows that synaptic plasticity, not intrinsic circuit structure, enables oscillations in a mouse V1 cortical column model with multiple interneuron types.

Cell type specific firing patterns in a V1 cortical column model depend on feedforward and feedback-driven states

The paper develops a spiking network model of a mouse V1 cortical column to study how feedforward and feedback inputs affect neural dynamics under different network states.

Functional connectivity drifts during sleep as a marker of fluctuations in the level of consciousness

This study examines functional connectivity in rats during the wake-sleep cycle to determine if consciousness fluctuates within brain states.

Efficient laminar-distributed interactions and orientation selectivity in the mouse V1 cortical column

This study uses a biologically detailed model of the mouse V1 cortical column to explain orientation selectivity through laminar-distributed interactions and subnetwork coupling.

Predictive coding with spiking neurons and feedforward gist signalling

This paper develops a spiking neural network for predictive coding that generates hierarchical internal representations and reconstructs unseen data, suggesting biologically plausible mechanisms for perceptual inference.

A disinhibitory circuit mechanism explains a general principle of peak performance during mid-level arousal

The paper provides evidence for the inverted U-shaped relationship between arousal and performance in perceptual decision-making and presents a neurobiological model explaining it.

Distributed evidence accumulation across macaque large-scale neocortical networks during perceptual decision making

The paper builds a large-scale macaque cortical model to show distributed sensory evidence accumulation across multiple brain regions during decision-making.

Local minimization of prediction errors drives learning of invariant object representations in a generative network model of visual perception

This paper shows how a predictive coding network learns invariant object representations and generative models through local prediction error minimization, using dynamic inputs to simulate visual perception.

Spontaneous Variations in Arousal Modulate Subsequent Visual Processing and Local Field Potential Dynamics in the Ferret during Quiet Wakefulness

The paper examines how pre-stimulus arousal variability affects post-stimulus neural activity in ferret visual and parietal cortices during quiet wakefulness.

Emergence of distributed working memory in a human brain network model

This paper develops a human brain network model to study distributed working memory, finding that it relies on long-range projections rather than local connectivity and explains 80% of observed variability.

A MESOSCALE CONNECTOME-BASED MODEL OF CONSCIOUS ACCESS IN THE MACAQUE MONKEY

This paper develops a mesoscale connectome-based model of the macaque cortex to simulate conscious access, showing how receptor dynamics drive ignition-like events in neural networks.

Mechanisms of distributed working memory in a large-scale network of macaque neocortex

This study develops a computational model of macaque cortex to show that persistent neural activity for working memory can arise from inter-areal reverberation, even when individual areas cannot generate it alone.

Directed functional and structural connectivity in a large-scale model for the mouse cortex

The paper evaluates the ability of Generalized Partial Directed Coherence (GPDC) to estimate structural connectivity in a mouse cortex model using electrophysiological data.

Cerebellar Purkinje cells can differentially modulate coherence between sensory and motor cortex depending on region and behavior

This study shows cerebellar Purkinje cells modulate S1-M1 coherence in theta and gamma bands during whisker stimulation, with effects dependent on region and behavior.

Engagement of pulvino-cortical feedforward and feedback pathways in cognitive computations

This paper presents a computational model of pulvino-cortical circuits in macaques, showing how the pulvinar modulates cortical operations during attention, memory, and decision-making.

Inter-areal balanced amplification enhances signal propagation in a large-scale circuit model of the primate cortex

This study shows that balanced amplification across cortical areas enables stable signal propagation in a primate cortex model, supporting the ignition model of conscious processing.

Response Reversal During Top-Down Modulation In Cortical Circuits With Multiple Interneuron Types

The paper develops a theoretical framework and cortical circuit model to explain response reversal in mouse V1 neural populations under top-down modulation.