PRI in Neuro

SeminarNeuroscience

Computational Mechanisms of Predictive Processing in Brains and Machines

Dr. Antonino Greco

Hertie Institute for Clinical Brain Research, Germany

Dec 10, 2025

Predictive processing offers a unifying view of neural computation, proposing that brains continuously anticipate sensory input and update internal models based on prediction errors. In this talk, I will present converging evidence for the computational mechanisms underlying this framework across human neuroscience and deep neural networks. I will begin with recent work showing that large-scale distributed prediction-error encoding in the human brain directly predicts how sensory representations reorganize through predictive learning. I will then turn to PredNet, a popular predictive coding inspired deep network that has been widely used to model real-world biological vision systems. Using dynamic stimuli generated with our Spatiotemporal Style Transfer algorithm, we demonstrate that PredNet relies primarily on low-level spatiotemporal structure and remains insensitive to high-level content, revealing limits in its generalization capacity. Finally, I will discuss new recurrent vision models that integrate top-down feedback connections with intrinsic neural variability, uncovering a dual mechanism for robust sensory coding in which neural variability decorrelates unit responses, while top-down feedback stabilizes network dynamics. Together, these results outline how prediction error signaling and top-down feedback pathways shape adaptive sensory processing in biological and artificial systems.

SeminarNeuroscience

Organization of thalamic networks and mechanisms of dysfunction in schizophrenia and autism

Vasileios Zikopoulos

Boston University

Nov 3, 2025

Thalamic networks, at the core of thalamocortical and thalamosubcortical communications, underlie processes of perception, attention, memory, emotions, and the sleep-wake cycle, and are disrupted in mental disorders, including schizophrenia and autism. However, the underlying mechanisms of pathology are unknown. I will present novel evidence on key organizational principles, structural, and molecular features of thalamocortical networks, as well as critical thalamic pathway interactions that are likely affected in disorders. This data can facilitate modeling typical and abnormal brain function and can provide the foundation to understand heterogeneous disruption of these networks in sleep disorders, attention deficits, and cognitive and affective impairments in schizophrenia and autism, with important implications for the design of targeted therapeutic interventions

SeminarNeuroscience

Spike train structure of cortical transcriptomic populations in vivo

Kenneth Harris

UCL, UK

Oct 29, 2025

The cortex comprises many neuronal types, which can be distinguished by their transcriptomes: the sets of genes they express. Little is known about the in vivo activity of these cell types, particularly as regards the structure of their spike trains, which might provide clues to cortical circuit function. To address this question, we used Neuropixels electrodes to record layer 5 excitatory populations in mouse V1, then transcriptomically identified the recorded cell types. To do so, we performed a subsequent recording of the same cells using 2-photon (2p) calcium imaging, identifying neurons between the two recording modalities by fingerprinting their responses to a “zebra noise” stimulus and estimating the path of the electrode through the 2p stack with a probabilistic method. We then cut brain slices and performed in situ transcriptomics to localize ~300 genes using coppaFISH3d, a new open source method, and aligned the transcriptomic data to the 2p stack. Analysis of the data is ongoing, and suggests substantial differences in spike time coordination between ET and IT neurons, as well as between transcriptomic subtypes of both these excitatory types.

SeminarNeuroscience