In a recent study, scientists at the Indian Institute of Science (IISc) demonstrated how an image sensor inspired by the brain can identify minute items that are undetectable to modern microscopes, such as cellular components or nanoparticles, by going beyond the diffraction limit of light.
According to the institute, their cutting-edge method, which combines optical microscopy with a neuromorphic camera and machine learning algorithms, represents a significant advance in the identification of objects smaller than 50 nanometers.
The neuromorphic camera used in the study has various advantages over traditional cameras and is around 40 mm (height) by 60 mm (width) by 25 mm (diameter) and weighs about 100 grammes. It simulates how the human retina turns light into electrical impulses.
In the current study, the team shone laser pulses at both high and low intensities, recording the fluctuation in the fluorescence levels, and then utilised their neuromorphic camera to locate individual fluorescent beads smaller than the limit of diffraction. The camera records the signal as a “ON” event as the light intensity rises, while a “OFF” event is reported as the light intensity falls. Reconstructing frames required pooling the data from these occurrences.