All-Optical Interface to a 3D Neuronal Construct Mimicking Cortical Pathway Connectivity
Research Summary:
This study developed an all-optical interface to stimulate and monitor three-dimensional neuronal constructs, mimicking how the brain receives sensory inputs. Saeed and his team guided axons and dendrites within the constructs into microchannel bundles and optogenetically stimulated them while recording activity through calcium imaging.
This stimulation created distinct input patterns, similar to real sensory signals, and the resulting neuronal responses showed characteristics of population coding. Notably, individual neurons displayed mixed selectivity, and the network could distinguish between different input patterns.
This approach avoids using costly microelectrode arrays and opens new possibilities for studying brain-like information processing and the impact of neurological disorders in vitro.
Mightex’s Contribution:
- Precise Optical Stimulation: The Mightex Polygon was used to deliver targeted blue light pulses to neurites inside specific micro-channels, enabling controlled optogenetic stimulation.
- Custom Protocol Design: Our PolyScan software allowed Saeed and his team to select individual micro-channels and design precise stimulation protocols, simultaneously delivering pulse trains of varying wavelengths, pulse widths, and pulse intervals to specific ROIs, supporting complex experimental paradigms.
- Integration with Analysis Tools: Mightex’s hardware and software enabled spatially-resolved activation of neuronal regions, which was visualized and quantified, facilitating downstream analysis such as machine learning-based classification of neural responses.
Together, Mightex’s hardware and software provided high spatial and temporal control of optical stimulation, critical for designing and analyzing complex optogenetic experiments.
Saeed is a fourth-year Bioengineering Ph.D. student at Lehigh University, specializing in neuroengineering and brain-on-chip systems. His research combines human neuron differentiation, optical neuromodulation, and machine learning to study brain information processing and neural network development. Saeed’s work bridges bioscience and engineering, with a focus on real-time analysis and control of complex neural systems.