Population decoding of visual motion direction in V1 marmoset monkey : effects of uncertainty
🧠 Excited to share our latest research led by Alexandre Lainé and presented this summer at CNS2025 in beautiful Firenze, Italy!
“Population decoding of visual motion direction in V1 marmoset monkey: effects of uncertainty”
Our work explores how populations of neurons in the primary visual cortex (V1) of marmoset monkeys encode visual motion direction, with a particular focus on understanding how uncertainty influences this neural decoding process. Key highlights:
- Advanced population-level analysis of V1 neural responses to motion stimuli
- Novel insights into how the brain handles uncertainty in visual motion processing
- Marmoset model providing crucial translational insights for visual neuroscience
This research contributes to our fundamental understanding of how the visual system processes motion information at the earliest stages of cortical processing, with important implications for both basic neuroscience and potential clinical applications. Thank you to the CNS organizing committee for hosting such an inspiring conference in the stunning venue of Palazzo dei Congressi in Villa Vittoria! 🇮🇹
#ComputationalNeuroscience #VisualNeuroscience #MotionProcessing #CNS2025 #Neuroscience #Research #MarmosetModel #V1 #PopulationDecoding
Link to publication: https://laurentperrinet.github.io/publication/laine-25-cns/
For deeper insights into uncertainty processing mechanisms in the visual cortex, see our Nature Communications Biology study:
Laurent U Perrinet
Researcher in Computational Neuroscience
My research interests include Machine Learning and computational neuroscience applied to Vision.