The Analyze Blog

Single Neuron Unit and Local Field Potential Activity in Visual Memory

By AnalyzeDirect Staff, last updated March 17, 2016



Neurons are electrically excitable cells that encode information and transmit it to neighboring neurons through synaptic connections. Current neurotechnologies are focusing on finding new ways to simultaneously record the activity of both single neurons and connected neural networks.

A recent study from the Department of Neurology at Mayo Clinic explored and compared single neuron spiking activity and local field potential generated by the summed electrical current flowing from multiple nearby neurons. The team hypothesized that recording micro-scale single neuron unit activity together with macro-scale oscillations would provide valuable information regarding the role of neural networks in cognitive processes, such as visual memory.

To explore this hypothesis, the group used hybrid depth electrodes, as they contained both micro- and macro-electrode contacts. The subjects of the study were 4 patients with drug-resistant temporal lobe epilepsy who were implanted with the electrodes into medial temporal lobe structures. Analyze software was used to identify the location of the implants. Pre-operative MRI and post-operative high-resolution CT scans of the brain were co-registered and mapped onto the Mayo 3D Brain Atlas. The integration of the 3D anatomical atlas of the human brain with the software enabled precise sub-millimetric localization of the contact sites in the hippocampus, amygdala, and the surrounding parahippocampal neocortex.

During the acquisition of electrophysiological signals the subjects performed a visual recognition memory task. Patients were shown a set of 80 images and were asked, 24 hours later, to recognize the same images mixed with 60 new ones.

Results from this study indicate that single neuron spiking activity and local field potential oscillations recorded respectively from micro- and macro- electrode signals should be used complementarily. When investigating the capacity to decode memorized image properties, the combination of these signal processing approaches will be useful for exploring activity spanning individual neurons and large-scale populations at different spatial scale.