Learning to see

How do we learn to see? Proper visual experience during the first weeks and months of life is critical for the proper development of the visual system. But how does experience modify neural circuits so that they exhibit the proper responses to visual stimuli? Knowledge of the mechanisms by which the brain is constructed early in development should inspire new therapies for repairing the brain if it develops improperly or is damaged by disease or injury.

At the present time, it is not possible to directly view all or even most connections within a living neural circuit. Therefore, neuroscientists often build computational models to study how these circuits may be constructed and how they may change with experience. A good model allows scientists to understand how these circuits may work in principle, and offers testable predictions that can be examined in the living animal to either support or refute the model.

Undergraduate Ian Christie ’16 was interested in understanding how neural circuits in the ferret visual system become selective to visual motion. At the time of eye opening, neurons in ferret visual cortex respond to an object moving in either of two opposite directions. With about a week of visual experience, each neuron develops a preference for only one of these directions, and greatly reduces its responses to the opposite direction.

Previous models of this process posited that the primary source of the change was in the organization and pattern of inputs to the cortex. But, recent experiments from the Van Hooser lab (Roy/Osik/Ritter et al., 2016) showed that stimulating the cortex by itself was sufficient to cause the development of motion selectivity, which suggests that some changes within the cortex itself must be underlying the increase in selectivity, at least in part. Further, other experiments in the lab of former Brandeis postdoc Arianna Maffei (Griffen et al., 2012) have shown that the cortex becomes less excitable to focal stimulation over the first weeks after eye opening.

Ian constructed families of computational models that could account for both of these observations. In the model, columns of neurons in the cortex already receive input that is slightly selective for motion in one of two opposite directions, but the connections between these cortical columns are so strong that both columns respond to both directions. However, the activity that is caused by simulated visual experience activates synaptic plasticity mechanisms in the model, that served to greatly reduce the strength of these connections between the columns, allowing motion selectivity to emerge in the cortical columns. The project was supervised by faculty members Paul Miller and Stephen Van Hooser, and the results were published in Journal of Neurophysiology (Christie et al., 2017).

Future experiments will now look for evidence of weaker connectivity between cortical neurons with visual experience.

This work was supported by the “Undergraduate and Graduate Training in Computational Neuroscience” grant to Brandeis University from NIH, and by the National Eye Institute grant EY022122. It also used the Brandeis University High Performance Computing Cluster.

Protected by Akismet
Blog with WordPress

Welcome Guest | Login (Brandeis Members Only)