210 citations · 639 across the 10 of their papers we have counts for
10 papers
Brain-inspired Computational Modeling of Action Recognition with Recurrent Spiking Neural Networks Equipped with Reinforcement Delay Learning
Alireza Nadafian, Milad Mozafari, Timothée Masquelier +1
The growing interest in brain-inspired computational models arises from the remarkable problem-solving efficiency of the human brain. Action recognition, a complex task in computat…
Modality-Agnostic fMRI Decoding of Vision and Language
Mitja Nikolaus, Milad Mozafari, Nicholas Asher +2
Previous studies have shown that it is possible to map brain activation data of subjects viewing images onto the feature representation space of not only vision models (modality-sp…
Reconstruction of Perceived Images from fMRI Patterns and Semantic Brain Exploration using Instance-Conditioned GANs
Furkan Ozcelik, Bhavin Choksi, Milad Mozafari +2
Reconstructing perceived natural images from fMRI signals is one of the most engaging topics of neural decoding research. Prior studies had success in reconstructing either the low…
Multimodal neural networks better explain multivoxel patterns in the hippocampus
Bhavin Choksi, Milad Mozafari, Rufin VanRullen +1
The human hippocampus possesses "concept cells", neurons that fire when presented with stimuli belonging to a specific concept, regardless of the modality. Recently, similar concep…
On the role of feedback in visual processing: a predictive coding perspective
Andrea Alamia, Milad Mozafari, Bhavin Choksi +1
Brain-inspired machine learning is gaining increasing consideration, particularly in computer vision. Several studies investigated the inclusion of top-down feedback connections in…
Predify: Augmenting deep neural networks with brain-inspired predictive coding dynamics
Bhavin Choksi, Milad Mozafari, Callum Biggs O'May +3
Deep neural networks excel at image classification, but their performance is far less robust to input perturbations than human perception. In this work we explore whether this shor…
Reconstructing Natural Scenes from fMRI Patterns using BigBiGAN
Milad Mozafari, Leila Reddy, Rufin VanRullen
Decoding and reconstructing images from brain imaging data is a research area of high interest. Recent progress in deep generative neural networks has introduced new opportunities…
SpykeTorch: Efficient Simulation of Convolutional Spiking Neural Networks with at most one Spike per Neuron
Milad Mozafari, Mohammad Ganjtabesh, Abbas Nowzari-Dalini +1
Application of deep convolutional spiking neural networks (SNNs) to artificial intelligence (AI) tasks has recently gained a lot of interest since SNNs are hardware-friendly and en…
Bio-inspired digit recognition using reward-modulated spike-timing-dependent plasticity in deep convolutional networks
Milad Mozafari, Mohammad Ganjtabesh, Abbas Nowzari-Dalini +2
The primate visual system has inspired the development of deep artificial neural networks, which have revolutionized the computer vision domain. Yet these networks are much less en…
First-spike based visual categorization using reward-modulated STDP
Milad Mozafari, Saeed Reza Kheradpisheh, Timothée Masquelier +2
Reinforcement learning (RL) has recently regained popularity, with major achievements such as beating the European game of Go champion. Here, for the first time, we show that RL ca…