TEX2022: Bringing together Predictive Processes and Statistical Learning

Session

Modeling

S5

Jul 21, 2022, 4:00 PM

Aula Magna (SISSA - International School for Advanced Studies)

3. Joint modeling confirms pupil dilation as neurophysiological marker of Bayesian spatial inference in dynamic auditory environments

David Meijer (Acoustics Research Institute, Austrian Academy of Sciences)

7/21/22, 4:00 PM

Predictive Processes and Statistical Learning

Talk

Bayesian inference has been used successfully to explain how listeners integrate prior information with auditory signals to stabilize perception in dynamic and noisy environments. Recently, it was suggested that the arousal system plays a notable role by modulating the relevance and reliability of priors (Krishnamurthy, Nassar, et al., 2017, Nat Hum Behav). This suggestion was based on...

5. Predictive neural representations of dynamic sensory input revealed by a novel dynamic extension to RSA

Ingmar de Vries (1. Donders Institute. 2. Centre for Mind/Brain Sciences (CIMeC))

7/21/22, 4:20 PM

Predictive Processes and Statistical Learning

Talk

To successfully navigate our dynamic environment, our brain needs to continuously update its representation of external information. This poses a fundamental problem: how does the brain cope with a stream of dynamic input? It takes time to transmit and process information along the hierarchy of the visual system. Our capacity to interact with dynamic stimuli in a timely manner (e.g., catch a...

7. Phase transitions in when feedback is useful

Lokesh Boominathan (Rice University)

7/21/22, 4:40 PM

Predictive Processes and Statistical Learning

Talk

Sensory observations about the world are invariably ambiguous. Inference about the world's latent variables is thus an important computation for the brain. However, computational constraints limit the performance of these computations. These constraints include energetic costs for neural activity and noise on every channel. Efficient coding is one prominent theory that describes how such...