RetINaBox: A Hands-On Learning Tool for Experimental Neuroscience

Area of Science:

• Neuroscience
• Computational Neuroscience
• Educational Technology

Background:

• Neuroscience experimentation is crucial but often inaccessible in educational settings due to cost and logistics.
• Hands-on learning is vital for understanding complex biological systems like the visual pathway.

Purpose of the Study:

• To introduce RetINaBox, an affordable, open-source electronic visual system simulator.
• To provide an accessible tool for users to discover the mechanisms of visual feature detection.

Main Methods:

• Developed RetINaBox, featuring an LED array for stimuli and photodiode arrays as model photoreceptors.
• Utilized a Raspberry Pi with custom software to simulate signal processing from photoreceptors to retinal ganglion cells.
• Integrated interactive lesson plans for guided discovery of visual processing concepts.

Main Results:

• Users can explore the construction of various feature detectors, including ON/OFF, center-surround, orientation-selective, and direction-selective receptive fields.
• The simulator allows manipulation of signal polarity and delay to understand circuit computations.
• Demonstrated the system's capability to simulate fundamental visual processing principles.

Conclusions:

• RetINaBox effectively bridges the gap between theoretical neuroscience and practical experimentation in educational contexts.
• The simulator facilitates a deeper understanding of visual system circuitry and feature detection mechanisms.
• Promotes inquiry-based learning in neuroscience through an engaging, low-cost platform.