Periodic Reporting for period 1 - COGSTIM (COGSTIM: Online Computational Modulation of Visual Perception.)
Reporting period: 2023-02-01 to 2025-01-31
Human survival and adaptation hinge on the nuanced interplay between stability and flexibility in visual perception. This project is dedicated to probing this intricate balance, with a specific focus on the dynamics of visual perception.
Visual perception entails the continuous processing of information by the brain. To unravel the mechanisms governing stability and flexibility in visual perception, we employ a novel experimental paradigm utilizing complex stereoscopic visual stimuli. These stimuli, characterized by bistable appearances, transition between stable and ambiguous states, providing an opportunity to investigate the neural networks underpinning perceptual stability and flexibility.
The research project integrates advanced electrophysiological recording and stimulating techniques with online decoding through adaptive machine learning algorithms. This integration seeks to unravel the temporal correlation between dynamic changes in visual stimuli and corresponding neuronal activity across cortical columns, with a specific focus on V5/MT.
Building upon existing knowledge, the project utilizes dense electrophysiological recordings in V5/MT, capturing the firing activity of the neuronal population and associated with online decoding of neuronal activity. In addition, we propose a novel paradigm by integrating closed-loop electrical stimulation in V5/MT to modulate real-time perceptual decisions regarding bistable visual stimuli.
The introduction of closed-loop stimulation in real time modulates key neuronal circuits and signaling patterns, establishing a causal link between neuronal activity and perceptual changes. This integrated approach represents a promising avenue for studying the dynamic relationship between neural processes and visual perception.
This approach enables the examination of neural codes and temporal dynamics, aiming to construct a comprehensive model elucidating how neuronal signals encode primate visual perceptual experiences.
The overarching objective of this project is to develop perceptual Brain-Machine Interfaces (BMIs) with promising implications for rehabilitating individuals with various visual perceptual impairments. This innovative approach holds potential for addressing a spectrum of disorders, including eye diseases, Parkinson's, Schizophrenia, and Autism. In summary, named CѺGSTIM, this project endeavors to unravel the functional neuronal networks governing visual perception, exploring their role in stability and flexibility. By leveraging cutting-edge technologies and innovative methodologies, the research aims to make significant strides in both scientific understanding and societal impact, paving the way for future rehabilitative BMI applications.
Visual perception entails the continuous processing of information by the brain. To unravel the mechanisms governing stability and flexibility in visual perception, we employ a novel experimental paradigm utilizing complex stereoscopic visual stimuli. These stimuli, characterized by bistable appearances, transition between stable and ambiguous states, providing an opportunity to investigate the neural networks underpinning perceptual stability and flexibility.
The research project integrates advanced electrophysiological recording and stimulating techniques with online decoding through adaptive machine learning algorithms. This integration seeks to unravel the temporal correlation between dynamic changes in visual stimuli and corresponding neuronal activity across cortical columns, with a specific focus on V5/MT.
Building upon existing knowledge, the project utilizes dense electrophysiological recordings in V5/MT, capturing the firing activity of the neuronal population and associated with online decoding of neuronal activity. In addition, we propose a novel paradigm by integrating closed-loop electrical stimulation in V5/MT to modulate real-time perceptual decisions regarding bistable visual stimuli.
The introduction of closed-loop stimulation in real time modulates key neuronal circuits and signaling patterns, establishing a causal link between neuronal activity and perceptual changes. This integrated approach represents a promising avenue for studying the dynamic relationship between neural processes and visual perception.
This approach enables the examination of neural codes and temporal dynamics, aiming to construct a comprehensive model elucidating how neuronal signals encode primate visual perceptual experiences.
The overarching objective of this project is to develop perceptual Brain-Machine Interfaces (BMIs) with promising implications for rehabilitating individuals with various visual perceptual impairments. This innovative approach holds potential for addressing a spectrum of disorders, including eye diseases, Parkinson's, Schizophrenia, and Autism. In summary, named CѺGSTIM, this project endeavors to unravel the functional neuronal networks governing visual perception, exploring their role in stability and flexibility. By leveraging cutting-edge technologies and innovative methodologies, the research aims to make significant strides in both scientific understanding and societal impact, paving the way for future rehabilitative BMI applications.
During the CѺGSTIM project, several technical and scientific developments were performed:
First, I developed and adapted stereoscopic visual stimuli, designed with specific arrangements of moving dots, inducing bistable perceptions of 3D solid shapes. The primary achievement in this phase was the successful implementation of a paradigm that mirrored the complex and dynamic nature of our perceptual experiences.
The scientific development advanced with a comprehensive investigation into the neural underpinnings of visual perception within the V5/MT area. Dense electrophysiological recordings were conducted, capturing the firing activity of single neurons. This meticulous approach enabled the identification of neuronal pools and codes responsible for perceptual stability and adaptability, contributing significantly to our understanding of how the brain controls visual percepts.
In parallel, the development of machine learning algorithms allowed real-time decoding of the subject's perceptual choices. This not only demonstrated technological innovation and feasibility but also facilitated the identification of temporal correlations between dynamic changes in visual stimuli and percept-related neuronal activity across cortical columns.
Moreover, to causally modulate visual perception in real time, I developed a closed-loop electrical stimulation system associated with the behavioral system developed in the first step. This involved targeting key neuronal circuits and signaling patterns within the V5/MT area during perceptual experiences to produce refined modulation of perceptual processing and report through intra-cortical microsimulation.
In summary, the work performed in the CѺGSTIM project represents a significant stride in advancing our scientific understanding of the dynamic interplay between neural processes and visual perception, particularly within the V5/MT area. The achievements include the successful development of an innovative experimental paradigm, the identification of critical neuronal mechanisms, and the groundbreaking application of real-time decoding and closed-loop electrical stimulation techniques. These accomplishments set the stage for future research and hold promise for potential applications in brain-machine interfaces and rehabilitative protocols for visual and cognitive functions, as well as the valorization and sharing of this knowledge in scientific publications.
First, I developed and adapted stereoscopic visual stimuli, designed with specific arrangements of moving dots, inducing bistable perceptions of 3D solid shapes. The primary achievement in this phase was the successful implementation of a paradigm that mirrored the complex and dynamic nature of our perceptual experiences.
The scientific development advanced with a comprehensive investigation into the neural underpinnings of visual perception within the V5/MT area. Dense electrophysiological recordings were conducted, capturing the firing activity of single neurons. This meticulous approach enabled the identification of neuronal pools and codes responsible for perceptual stability and adaptability, contributing significantly to our understanding of how the brain controls visual percepts.
In parallel, the development of machine learning algorithms allowed real-time decoding of the subject's perceptual choices. This not only demonstrated technological innovation and feasibility but also facilitated the identification of temporal correlations between dynamic changes in visual stimuli and percept-related neuronal activity across cortical columns.
Moreover, to causally modulate visual perception in real time, I developed a closed-loop electrical stimulation system associated with the behavioral system developed in the first step. This involved targeting key neuronal circuits and signaling patterns within the V5/MT area during perceptual experiences to produce refined modulation of perceptual processing and report through intra-cortical microsimulation.
In summary, the work performed in the CѺGSTIM project represents a significant stride in advancing our scientific understanding of the dynamic interplay between neural processes and visual perception, particularly within the V5/MT area. The achievements include the successful development of an innovative experimental paradigm, the identification of critical neuronal mechanisms, and the groundbreaking application of real-time decoding and closed-loop electrical stimulation techniques. These accomplishments set the stage for future research and hold promise for potential applications in brain-machine interfaces and rehabilitative protocols for visual and cognitive functions, as well as the valorization and sharing of this knowledge in scientific publications.
The CѺGSTIM project participate to develop visual perception research beyond existing paradigms, yielding unprecedented advancements.
Key results include:
Innovative Experimental Paradigm: Developed a novel stereoscopic visual stimulus inducing bistable 3D perceptual states, mirroring the dynamic nature of human perceptual experiences.
Refined Neuronal Identification in V5/MT: Identified neuronal pools responsible for perceptual stability and adaptability through dense electrophysiological recordings in the extrastriate area V5/MT .
Real-time Decoding: Real-time decoding of subject's perceptual choices using adaptive machine learning algorithms, establishing temporal correlations between dynamic stimuli and neuronal activity.
Closed-loop Electrical Stimulation: Modulation of visual motion percepts in real time through closed-loop electrical stimulation, showcasing the causal validation of temporal relationships within identified neuronal pools.
These results represent a paradigm shift in understanding the intricate dynamics of visual perception, particularly in the V5/MT area, setting new benchmarks for future research and applications in brain-machine interfaces and rehabilitative protocols.
Key results include:
Innovative Experimental Paradigm: Developed a novel stereoscopic visual stimulus inducing bistable 3D perceptual states, mirroring the dynamic nature of human perceptual experiences.
Refined Neuronal Identification in V5/MT: Identified neuronal pools responsible for perceptual stability and adaptability through dense electrophysiological recordings in the extrastriate area V5/MT .
Real-time Decoding: Real-time decoding of subject's perceptual choices using adaptive machine learning algorithms, establishing temporal correlations between dynamic stimuli and neuronal activity.
Closed-loop Electrical Stimulation: Modulation of visual motion percepts in real time through closed-loop electrical stimulation, showcasing the causal validation of temporal relationships within identified neuronal pools.
These results represent a paradigm shift in understanding the intricate dynamics of visual perception, particularly in the V5/MT area, setting new benchmarks for future research and applications in brain-machine interfaces and rehabilitative protocols.