This model has proved to be an invaluable tool to scientists studying the underlying principles behind neuronal learning, memory, plasticity, connectivity, and information processing.
Researchers can then thoroughly study learning and plasticity in a realistic context, where the neuronal networks are able to interact with their environment and receive at least some artificial sensory feedback.
Foremost among these abnormalities is the fact that the neurons are usually harvested as neural stem cells from a fetus and are therefore disrupted at a critical stage in network development.
Another disadvantage lies in the fact that the cultured neurons lack a body and are thus severed from sensory input as well as the ability to express behavior – a crucial characteristic in learning and memory experiments.
Harvesting neural stem cells requires sacrificing the developing fetus, a process considered too costly to perform on many mammals that are valuable in other studies.
Additionally, when coupled with a sealed incubation chamber this device greatly reduces the risk of culture contamination by nearly eliminating the need to expose it to air.
They employ approximately sixty electrodes for recording and stimulation in varying patterns in a dish with a typical culture of 50,000 cells or more (or a density of 5,000 cells/mm2).
[9] It follows that each electrode in the array services a large cluster of neurons and cannot provide resolute information regarding signal origin and destination; such MEAs are only capable of region-specific data acquisition and stimulation.
[5] A laser beam with wavelength in the UV spectrum would have extremely high spatial accuracy and, by releasing the caged compounds, could be used to influence a very select set of neurons.
[9] However, confounding this experimental technique is the fact that normal neuronal development induces change in array-wide bursts that could easily skew data.
In a pathological sense, spontaneous network activity can be attributed to the disembodiment of the neurons; one study saw a marked difference between array-wide firing frequency in cultures that received continuous input versus those that did not.
However, this approach has great costs; quieted networks have little capacity for plasticity[11] due to a diminished ability to create action potentials.
[11] Some studies have suggested that these bursts represent information carriers, expression of memory, a means for the network to form appropriate connections, and learning when their pattern changes.
They gathered network burst profiles (BPs) through a mathematical observation of array-wide spiking rate (AWSR), which is the summation of action potentials over all electrodes in an MEA.
This analysis yielded the conclusion that, in their culture of Wistar rat neocortical cells, the AWSR has long rise and fall times during early development and sharper, more intense profiles after approximately 25 DIV.
These finding imply that studies of plasticity of neurons can only be conducted over the course of minutes or hours without bias in network activity introduced by normal development.
Plasticity, on the other hand, is simply the reshaping of an existing network by changing connections between neurons: formation and elimination of synapses or extension and retraction of neurites and dendritic spines.
Nevertheless, plasticity in neuronal networks is a phenomenon that is well-established in the neuroscience community, and one that is thought to play a very large role in learning.