Mervyn Hobden

About

Mervyn Hobden is a researcher whose work bridges computational neuroscience and hardware implementation, with a focus on the Lobula Giant Movement Detector (LGMD)—a visual neuron in the locust that responds to looming objects. His key contributions include developing modified neural network models that enhance the LGMD’s ability to detect depth movement features, offering insights into how biological systems process rapid approach. In his 2010 paper (27 citations), Hobden introduced an FPGA implementation of this model, demonstrating a practical pathway for translating neural algorithms into real-time hardware. His 2009 study (18 citations) further refined the model by incorporating additional depth movement cues, improving the detection of object proximity and velocity. Together, these works have advanced the understanding of collision avoidance systems in robotics and neuromorphic engineering. Hobden’s research is notable for its interdisciplinary approach, combining biology, neural modeling, and digital circuit design, and his citation counts reflect its influence on both theoretical and applied studies in visual processing.

Research Focus

Key Achievements

Top Papers

1. 1
   A modified model for the Lobula Giant Movement Detector and its FPGA implementation

   27 citations · 2010
2. 2
   A modified neural network model for Lobula Giant Movement Detector with additional depth movement feature

   18 citations · 2009

Key Collaborators

Contact & Links