Iterative category inference in recurrent neural networks

With: Adrien Doerig, Tim Kietzmann
Summary: Can we see signs of iterative category inference in RNNs? What kind of shape/texture/semantic space does the inference adhere to? Does the network play 20 questions with the image? What operations in the RNN lead to these processes?

Characterising catastrophic forgetting and finding solutions

With: Daniel Anthes, Tim Kietzmann, Peter König
Summary: What aspects of training neural networks continually leads to catastrophic forgetting? Can we find simple solutions, either bio-inspired or executable without much overhead, to workaround those aspects?

Brain reading with a Transformer

With: Victoria Bosch, Tim Kietzmann, et al.
Summary: Using fMRI responses to natural scenes to condition the sentence generation in a Transformer, we are studying the neural underpinnings of scene semantics (objects and their relationships) encoded in natural language.

Task-dependent characteristics of neural multi-object processing

With: Lu-Chun Yeh, Marius Peelen
Summary: The association between the neural processing of multi-object displays and the representations of those objects presented in isolation is task-dependent: unique associations with spatiotemporal stages of the object representations, same/different judgement - earlier, and object search - later stages in MEG/fMRI signals.
Comments: Paper being written.

Size-dependence of object search templates in natural scenes

With: Surya Gayet, Marius Peelen, et al.
Summary: Object size varies with the location of the object in scenes. These variations get reflected in the search for that object in a given set of locations in a scene: our search is better for a smaller object further out in the scene as compared to closer in the scene.
Comments: Paper being written.

Perception of rare inverted letters among upright ones

With: Jochem Koopmans, Genevieve Quek, Marius Peelen
Summary: In a Sperling-like task where the letters are mostly upright, there is a general tendency to report occasionally-present and absent inverted letters as upright to the same extent. This suggests that previously reported expectation-driven illusions might be post-perceptual in nature.
Comments: Paper being written.

Statistical learning of distractor co-occurrences facilitates visual search

With: Genevieve Quek, Marius Peelen
Summary: Efficient visual search relies on the co-occurrence statistics of distractor shapes. Increased search efficiency among co-occurring distractors is probably driven by faster and/or more accurate rejection of a distractor's partner as a possible target.
Publication: JOV'22 paper
Comments: JOV paper in brief

Bodies as features in visual search

With: Marius Peelen
Summary: Are high-level visual features prioritised, via feature-based attention, spatially-globally? We found attentional gain modulation of the fMRI representations of body silhouettes, presented in task-irrelevant locations, in high-level visual cortex.
Publication: NeuroImage'22 paper
Comments: NeuroImage paper in brief, Code + Data

Recurrent operations in neural networks trained to recognise objects

With: Giacomo Aldegheri, Tim Kietzmann
Summary: In a recurrent neural network trained for object categorization, the recurrent flow carries category-orthogonal object feature (e.g. object location) information, which is used, iteratively, to constrain the subsequent inferences about the object's category.
Publication: SVRHM'21 paper
Comments: SVRHM paper in brief

The function of early task-based modulations in object detection

With: Giacomo Aldegheri, Marcel van Gerven, Marius Peelen
Summary: Task-based modulation of early visual processing in neural networks alleviates subsequent capacity limits caused by task and neural constraints. Bias/gain modulation of neural activations can be linked to tapping into a superposition of networks. Optimised neural modulations are not feature-similarity gain modulations.
Publications: CCN'18 paper, CCN'19 paper

The influence of scene information on object processing

With: Ilze Thoonen, Sjoerd Meijer, Marius Peelen
Summary: Task-irrelevant scene information biases categorization response towards co-varying objects (e.g. cars on roads). However, no evidence is found, across 4 experiments, for task-irrelevant scene information boosting the sensitivity of detecting co-varying objects. Further experimentation is required for validating these observations.
Comments: Summary presentation

The nature of the animacy organization in human ventral temporal cortex

With: Daria Proklova, Daniel Kaiser, Marius Peelen
Summary: The animacy organisation in the ventral temporal cortex is not fully driven by visual feature differences (modelled with a CNN). It also depends on non-visual (inferred) factors such as agency (quantified through a behavioural task).
Publications: eLife'19 paper, Masters Thesis
Comments: Masters thesis in brief, eLife paper in brief

Reverse dictionary using a word-definition based graph search

With: Varad Choudhari
Summary: A method to process any forward word dictionary to build a reverse dictionary, using a n-hop reverse search on a graph, through word definitions. Performs as well as the state-of-the-art on a 3k lexicon. Doesn't scale well to 80k.
Publication: COLING'16 Paper
Comments: COLING paper in brief

A Spiking Neural Network as a Quadcopter Flight Controller

With: Sukanya Patil, Bipin Rajendran
Summary: a. Model-based control system for quadcopters towards velocity-waypoint navigation.
b. Modular SNNs for real-time arithmetic operations, using plastic synapses. SNNs are hard to tame!
Publications: IJCNN'15 paper, B.Tech. Thesis
Comments: Thesis rumination, IJCNN paper in brief