2 citations · 3 across the 7 of their papers we have counts for
8 papers
Discovering Functionally Selective Brain Regions with a Deep Topographic Multimodal Model
Badr AlKhamissi, Johannes Mehrer, Lara Marinov +3
Nearby neurons in cortex share similar response profiles, producing systematic spatial organization across sensory and cognitive systems. Recent topographic models reproduce aspect…
MIRAGE: Adaptive Multimodal Gating for Whole-Brain fMRI Encoding
Abdulkadir Gokce, Badr AlKhamissi, Martin Schrimpf
Recent progress in task-optimized neural networks has established encoding models as a powerful tool for predicting brain responses to naturalistic stimuli, yet most existing appro…
Large Language Models Align with the Human Brain during Creative Thinking
Mete Ismayilzada, Simone A. Luchini, Abdulkadir Gokce +5
Creative thinking is a fundamental aspect of human cognition, and divergent thinking-the capacity to generate novel and varied ideas-is widely regarded as its core generative engin…
Model-Guided Microstimulation Steers Primate Visual Behavior
Johannes Mehrer, Ben Lonnqvist, Anna Mitola +3
Brain stimulation is a powerful tool for understanding cortical function and holds promise for therapeutic interventions in neuropsychiatric disorders. Initial visual prosthetics a…
Contour Integration Underlies Human-Like Vision
Ben Lonnqvist, Elsa Scialom, Abdulkadir Gokce +3
Despite the tremendous success of deep learning in computer vision, models still fall behind humans in generalizing to new input distributions. Existing benchmarks do not investiga…
Scaling Laws for Task-Optimized Models of the Primate Visual Ventral Stream
Abdulkadir Gokce, Martin Schrimpf
When trained on large-scale object classification datasets, certain artificial neural network models begin to approximate core object recognition behaviors and neural response patt…
Dreaming Out Loud: A Self-Synthesis Approach For Training Vision-Language Models With Developmentally Plausible Data
Badr AlKhamissi, Yingtian Tang, Abdülkadir Gökce +2
While today's large language models exhibit impressive abilities in generating human-like text, they require massive amounts of data during training. We here take inspiration from…
EndoL2H: Deep Super-Resolution for Capsule Endoscopy
Yasin Almalioglu, Kutsev Bengisu Ozyoruk, Abdulkadir Gokce +8
Although wireless capsule endoscopy is the preferred modality for diagnosis and assessment of small bowel diseases, the poor camera resolution is a substantial limitation for both…