Identifying the function and type of a cell

Identifying the function of a cell and therefore its type is the holy grail of cellular-level Neuroscience research. What is it that makes one type of neuron more suited to a task than another? In the case of working memory; Dr. Yun Wang and collaborators (Heterogeneity in the pyramidal network of the medial prefrontal. 2006, Yun Wang, Henry Markram, Philip H. Goodman, Thomas K. Berger, Junying Ma, and Patricia S. Goldman-Rakic) Nature Neuroscience 9:534-542) show compelling evidence that there may be a specific type of cell in the medial prefrontal cortex (mPFC) involved in storing information that is needed for solving a delayed task. What are the characteristics that make one neuron unique from another? They certainly include morphology. How are the dendrites arranged? In a highly structured area like the neocortex, this is very important in determining what inputs the cells get. The complex pyramidal cell (cPC) unlike the simple pyramidal cell (sPC), is common in the mPFC and has dendrites that bifurcate in the layer of cortex that receives inputs from other pyramidal cells, layer V (see figure 6D and 6E). Note that the cPC on the left has dual apical dendrites that branch further away from the cell body than the tufted apical dendrite that branches close to the cell body for the sPC on the right. Neurons were reconstructed in three dimensions and quantitative morphological data was analyzed using Neurolucida and Neurolucida Explorer.

But the evidence extends beyond morphology. The authors used multiple microelectrodes to make very low resistance electrical connections to pairs of pre- and post-synaptic pyramidal neurons in mPFC. This way they could study how the postsynaptic cell receives a train of signals from the presynaptic cell. They found the mPFC, compared to the visual cortex, had more heterogeneous synapse types, and had more synapses that showed potentiation on time scales ranging from milliseconds to minutes. The authors also used computer modeling to study the time course of synaptic depression and synaptic facilitation. Synaptic depression means the excitatory post synaptic potential (EPSP) gets smaller during a train of presynaptic stimuli, which makes it less likely the neuron will pass on its information by firing an action potential, facilitation means the chance for an action potential increases. Facilitation was also demonstrated experimentally by recording in a calcium free environment, which lessens the probability of neurotransmitter being released into the synapse thus unmasking the increase in EPSPs. The time-constant (longer time constants mean longer and greater effects) for facilitation in the mPFC was shown to be 20 times greater than for pyramidal cells in the visual cortex. These facilitating excitatory synapses are not unique to the mPFC but seem to be a major part of it. The group identified three putative cell types and named them based on the names already given to three analogous clusters of inhibitory cells. E1 cells show more facilitation than depression, E2 cells are depression dominated, and E3 cells have about equal amounts of depression and facilitation. Unlike the diversity in the mPFC, all visual cortex synapses studies were E2.

Besides morphology and the nature of the synapses received, connectivity, or what types of cells are being communicated with through the synapses, is important for determining function. cPCs mainly send information to each other, and do it through E1 and E3 type synapses while sPCs are connected to each other and to cPCs mainly by type E2 synapses. Pyramidal cells in the mPFC tend to be connected to each other (through synapses) and have twice the amount of reciprocal connections as visual cortex pyramidal cells. All the ingredients are there to make the cPC a candidate for being the substrate of a network in the mPFC that favors enhanced recurrent excitation. The grouping of morphological and synaptic characteristics shown by cPCs and their reciprocity make them possibly important for creating persistent neuronal activity that underlies working memory.

“The Neurolucida system is very useful for doing quantitative analysis of neuronal morphology. Multiple parameters extracted by using this quantitative analysis program represent the intrinsic features of neurons. For example, axonal segment lengths, maximum branch angles and bouton density usually stay consistent for a neuron type although the general axonal and dendritic clusters may vary significantly according to the locations of the neuron type. When combined with multiple-neuron patch clamp recording, the quantitative morphological analysis has served as an essential step to enable us to successfully carry out the following research. We have been able to reveal the organizing principles of inhibitory networks (Gupta et al., 2000); define and systematically study a new subclass of basket cell– nest basket cell (Wang et al., 2002); systematically study Martinotti cells in anatomy, electrophysiology and synaptology (Wang et al., 2004); discover glutamatergic differential innervation of different target neurons by single PCs (Markram et al., 1998) and anatomical principles for differential glutamatergic innervation based on a large number of reconstructed connections Wang et al., 1999). In addition, recently we have been able to reveal cellular, synaptic and network features of the layer 5 pyramidal microcircuitry (Wang et al., 2006). Furthermore, a unique reconstruction data base of over ten thousand neurons and hundreds of synaptic connections has been developed, which will be essential to put the neuronal microcircuitry together with the biologically realistic computer simulations in the Blue Brain
Project.” —Dr. Yun Wang