475 citations · 542 across the 12 of their papers we have counts for
13 papers
The illusory simplicity of the feedforward pass: evidence for the dynamical nature of stimulus encoding along the primate ventral stream
Daniel Anthes, Sushrut Thorat, Anna Mitola +3
In studying primate vision, a large body of work focuses on the first feedforward sweep. During this initial time window, information is thought to pass through ventral stream regi…
Helping Blind People Grasp: Enhancing a Tactile Bracelet with an Automated Hand Navigation System
Marcin Furtak, Florian Pätzold, Tim Kietzmann +2
Grasping constitutes a critical challenge for visually impaired people. To address this problem, we developed a tactile bracelet that assists in grasping by guiding the user's hand…
Sparks of cognitive flexibility: self-guided context inference for flexible stimulus-response mapping by attentional routing
Rowan P. Sommers, Sushrut Thorat, Daniel Anthes +1
Flexible cognition demands discovering hidden rules to quickly adapt stimulus-response mappings. Standard neural networks struggle in such tasks requiring rapid, context-driven rem…
Diagnosing Catastrophe: Large parts of accuracy loss in continual learning can be accounted for by readout misalignment
Daniel Anthes, Sushrut Thorat, Peter König +1
Unlike primates, training artificial neural networks on changing data distributions leads to a rapid decrease in performance on old tasks. This phenomenon is commonly referred to a…
Keep Moving: identifying task-relevant subspaces to maximise plasticity for newly learned tasks
Daniel Anthes, Sushrut Thorat, Peter König +1
Continual learning algorithms strive to acquire new knowledge while preserving prior information. Often, these algorithms emphasise stability and restrict network updates upon lear…
End-to-end topographic networks as models of cortical map formation and human visual behaviour: moving beyond convolutions
Zejin Lu, Adrien Doerig, Victoria Bosch +4
Computational models are an essential tool for understanding the origin and functions of the topographic organisation of the primate visual system. Yet, vision is most commonly mod…
Characterising representation dynamics in recurrent neural networks for object recognition
Sushrut Thorat, Adrien Doerig, Tim C. Kietzmann
Recurrent neural networks (RNNs) have yielded promising results for both recognizing objects in challenging conditions and modeling aspects of primate vision. However, the represen…
The neuroconnectionist research programme
Adrien Doerig, Rowan Sommers, Katja Seeliger +8
Artificial Neural Networks (ANNs) inspired by biology are beginning to be widely used to model behavioral and neural data, an approach we call neuroconnectionism. ANNs have been la…
Visual representations in the human brain are aligned with large language models
Adrien Doerig, Tim C Kietzmann, Emily Allen +4
The human brain extracts complex information from visual inputs, including objects, their spatial and semantic interrelations, and their interactions with the environment. However,…
Category-orthogonal object features guide information processing in recurrent neural networks trained for object categorization
Sushrut Thorat, Giacomo Aldegheri, Tim C. Kietzmann
Recurrent neural networks (RNNs) have been shown to perform better than feedforward architectures in visual object categorization tasks, especially in challenging conditions such a…
Visualizing Representational Dynamics with Multidimensional Scaling Alignment
Baihan Lin, Marieke Mur, Tim Kietzmann +1
Representational similarity analysis (RSA) has been shown to be an effective framework to characterize brain-activity profiles and deep neural network activations as representation…
Learning robust visual representations using data augmentation invariance
Alex Hernández-García, Peter König, Tim C. Kietzmann
Deep convolutional neural networks trained for image object categorization have shown remarkable similarities with representations found across the primate ventral visual stream. Y…
Recurrence is required to capture the representational dynamics of the human visual system
Tim C Kietzmann, Courtney J Spoerer, Lynn Sörensen +3
The human visual system is an intricate network of brain regions that enables us to recognize the world around us. Despite its abundant lateral and feedback connections, object pro…