Connected Neurons in Multiple Neocortical Areas, Comprising Parallel Circuits, Encode Essential Information for Visual Shape Learning
Journal of Chemical Neuroanatomy
Neocortical areas comprised of multiple neuronal circuits which are encoded with innumerable advanced cognitive tasks. Studies focused on neuronal network and synaptic plasticity has hypothesized that every specific neuron and the circuit process the explicit essential information for the specific tasks. However, the structure of these circuits and the involved critical neurons remain to be elucidated. Considering our previous studies, showing the specificity of rat postrhinal cortex comprising specific neuronal circuit for encoding both the learning and recall of shape discrimination through a fast neurotransmitter release from the transduced neurons, here we have demonstrated that postsynaptic neurons in two distinct areas, perirhinal cortex and the ventral temporal association areas are required for the specific visual shape discriminations learning. The constitutively active PKC was delivered into neuronal cells in postrhinal cortex, and the animals were allowed to learn the new shape discriminations, and then the silencing siRNA was delivered into postsynaptic neurons in either perirhinal cortex or ventral temporal association areas, using a novel technology for gene transfer into connected neurons. We observed that expression of the siRNA caused the deficits in visual performance, via blocking the activity in the neurons, as displayed by activity-dependent gene imaging, and also subsequently obstructed the activation of specific signaling pathways required for further learning, and dendritic protein synthesis and CREB. Thus, ratifying the conclusion that the two parallel circuits are both required for the visual shape discrimination learning.
Nagayach, Aarti; Ghafari, Maryam; Zhao, Yinghong; Collins, Grant S.; Singh, Anshuman; and Geller, Alfred I., "Connected Neurons in Multiple Neocortical Areas, Comprising Parallel Circuits, Encode Essential Information for Visual Shape Learning" (2021). School of Medicine Faculty Publications. 154.