P285 A two-region recurrent neural network reproduces the cortical dynamics underlying subjective visual perception
Artemio Soto-Breceda1, Nathan Faivre2, João Barbosa3,4,Michael Pereira1
1.Univ. Grenoble Alpes, Inserm, Grenoble Institut Neurosciences, 38000 Grenoble, France 2.Univ. Grenoble Alpes, Univ. Savoie Mont Blanc, CNRS, LPNC, 38000 Grenoble, France 3 Cognitive Neuroimaging Unit, INSERM, CEA, CNRS, Université Paris-Saclay, NeuroSpin center, Gif/Yvette, France 4 Institut de Neuromodulation, GHU Paris Psychiatrie et Neurosciences, Centre Hospitalier Sainte-Anne, Université Paris Cité, Paris, France Introduction
This study aims to model the cortical activity associated with the detection of visual stimuli, as well as the subjective duration of visual percepts and associated confidence. We propose a two-region neural network model: a sensory region integrating sensory inputs and a decision region with longer integration timescales. The model is constrained by biological parameters to simulate region-dependent temporal integration and includes top-down feedback and excitation-inhibition balance to test hypotheses on the neural basis of perception.
Methods The model consists of a recurrent rate-based neural network of excitatory (80%) and inhibitory (20%) neurons with GABA, AMPA, and NMDA synapses. The sensory region receives and integrates sensory inputs and projects to a decision region with longer integration timescales. This decision region defines whether and when a near-threshold stimulus is detected. The dynamics of the simulated neural activity in the sensory region were compared to the dynamics of neural activity consisting of local field potentials recorded using stereotaxic EEG in humans undergoing epilepsy monitoring and associated behavioral measures of detection, response times, subjective confidence and subjective duration collected with a time-reproduction task [1]. Results The model successfully replicated key behavioral metrics. Qualitatively, simulated activity in the decision region matched high-gamma activity recorded in the anterior insula, while sensory region activity aligned with activity in the inferior temporal cortex during a face detection task. We find that, for example, temporal integration in sensory regions explains the magnitude-duration illusion, where higher intensity stimuli are perceived as longer. We also examined model predictions when altering the E/I ratio by changing the synaptic strength of NMDA receptors in either the excitatory or inhibitory population [2], or modulating the top-down feedback. We intend to test alternative models corresponding to different hypotheses on how temporal integration explains subjective aspects of perception such as duration and confidence. Discussion Many studies have provided computational models of perceptual decision-making. However, the neuronal mechanisms underlying the subjective aspects of perception remain poorly understood. Here, starting from a model of decision-making [3], we harness temporal properties of these subjective aspects of perception to isolate the underlying neuronal mechanism. The model is able to predict behavior in perceptual decision-making tasks. This model allows us to investigate how biological parameters such as E/I balance or top-down feedback affect behavior and cortical activity during perceptual decision-making tasks. We will interpret our findings in the context of current theories of consciousness.
