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Friedemann Zenke7/4/23, 9:40 AMLong talk
Discriminating distinct objects and concepts from sensory stimuli is essential for survival. Our brains perform this processing in deep sensory networks shaped through plasticity. However, our understanding of the underlying plasticity mechanisms is still limited. First, I will present recent work on Latent Predictive Learning (LPL), a plausible normative theory of representation learning...
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Veronika Koren7/4/23, 11:00 AMLong talk
Understanding how the dynamics of neural networks is shaped by the computations they perform is a fundamental question in neuroscience. Recently, the framework of efficient coding proposed a theory of how spiking neural networks can compute low-dimensional stimulus signals with high efficiency. Efficient spiking networks are based on time-dependent minimization of a loss function related to...
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Luigi Acerbi7/4/23, 11:50 AMLong talk
In this talk, I will discuss recent results in Bayesian deep learning and how they may provide a new theoretical perspective that unifies several seemingly distinct functional interpretations for the role of noise in the brain. Specifically, I will show how: (a) multiplicative noise in neural network units; (b) Bayesian inference over neural network parameters; (c) "data augmentation"; (d)...
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Paolo Muratore (SISSA)7/4/23, 2:35 PMShort talk
Deep Convolutional Neural Networks (Deep CNNs) are currently unsurpassed as our best models of the object-recognition pathway in the visual stream of macaque monkeys. However, the extent to which these models generalize to the rodent visual ventral stream is disputed. In this talk I will recap recent attempts at using CNNs to model the rat ventral stream and present a novel,...
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Maria Ravera (SISSA)7/4/23, 3:10 PMShort talk
In an environment where sensory evidence indicates reward location, while a non-sensory, hidden probabilistic structure simultaneously imposes reward location likelihood, how will the two information channels interact in the brain? We developed a two-alternative forced-choice foraging task, where matching the probabilistic environment promotes reward collection. Rats initiate each trial at a...
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Laurenz Wiskott7/5/23, 10:00 AMLong talk
Many studies have suggested that episodic memory is a generative process, but most computational models adopt a storage view. In this talk, I will first present a system level model of generative episodic memory, in which incomplete memory traces are completed by semantic information [1]. It is based on standard machine learning components, like a vector-quantized variational autoencoder...
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Wiktor Mlynarski (IST / LMU Muenchen)7/5/23, 12:00 PMLong talk
Our thinking about sensory systems has been shaped by two dominant theoretical frameworks: probabilistic inference and efficient coding. Probabilistic inference specifies optimal strategies for learning about relevant properties of the environment from local and ambiguous sensory signals. Efficient coding provides a normative approach to study encoding of natural stimuli in...
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Peter Neri7/5/23, 2:10 PMLong talk
We can view cortex from two fundamentally different perspectives: a powerful device for performing optimal inference, or an assembly of biological components not built for achieving statistical optimality. The former approach is attractive thanks to its elegance and potentially wide applicability, however the basic facts of human pattern vision do not support it. Instead, they indicate that...
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Andrea Benucci7/5/23, 3:00 PMLong talk
The neural mechanisms underlying natural vision remain poorly understood. Here, we examined the processing of a class of natural images—textures—across mid-level visual areas in the mouse ventral cortical stream. First, we established that mice are capable of perceptually distinguishing between different textures and simpler stimuli matched for spectral content. Then, using GCaMP imaging, we...
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Camillo Padoa-Schioppa7/6/23, 10:00 AMLong talk
A binary economic choice entails the computation and comparison of two offer values. When monkeys chose between different goods, two groups of neurons in orbitofrontal cortex (OFC) encode the two offer values. Importantly, experiments using electrical stimulation demonstrated a causal relationship between the activity of offer value cells and choices. Given a value range, the tuning curves of...
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Raunak Basu7/6/23, 11:00 AMLong talk
Successful goal-directed navigation requires estimating one’s current position in the environment, representing the future goal location, and maintaining a map that preserves the topological relationship between positions. In addition, we often need to implement similar navigational strategies in a continuously changing environment, thereby necessitating certain invariance in the underlying...
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Angeles Salles7/6/23, 11:50 AMLong talk
Bats are auditory specialists, processing acoustic signals to guide their behaviors, including prey tracking, navigation and communication. In this talk I will provide a brief overview of my previous work related to how bats analyze and process signals for action-selection; and I will focus on communication signals, the line of research of my current lab. There is strong evidence that context...
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Gaia Tavoni (Washington University in St. Louis)7/6/23, 2:15 PMLong talk
Neural representations of sensory stimuli are modulated by a variety of contextual factors, such as information on other stimuli present in the environment, the novelty or familiarity of the sensory inputs, and behavioral goals. Despite decades of attention in systems neuroscience, many questions persist regarding how sensory codes adapt to these different variables. Here, we study this...
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