Boston University Scientists Use AutoNeuron and AutoSynapse to Compare Neurons in the Visual and Prefrontal Cortices

MBF_Figure

Use of Neurolucida to assess the detailed morphology – including spines and synapses – of a layer 3 pyramidal neuron from the anterior cingulate cortex of a rhesus monkey. A) 40x confocal image of a layer 3 pyramidal neuron that was filled with biocytin during whole-cell patch-clamp recordings and subsequently processed with Alexa-Streptavidin-488. B) Basilar dendritic segment (indicated by the box in A), scanned in 2 channels: green= the neuron; red= VGat. C) Dendritic reconstruction indicated in light blue. Spine subtypes identified by the AutoSpine module (magenta= mushroom; yellow= thin; red= stubby). D) VGat-positive appositions (indicated by white dots) against the dendritic shaft and spines identified with AutoSynapse. Scale bars: A= 20 µm; B= 2 µm

The ball comes flying and you swing the bat. A car pulls out and you hit the brakes. As we go about our daily routines, we process everything we see in a region in the back of our brains known as the visual cortex. But when we sit down to plan a kitchen remodel, or next summer’s vacation, an area in the front of the brain gets activated, the prefrontal cortex, a region involved in higher level thinking.

Recent research has offered insight into the structure and function of neurons in these two distinct brain regions. Scientists at the Luebke Lab at Boston University set out to find out more about their morphology, and if their structural differences affect their behavior. Their study, published in the Journal of Neuroscience offers evidence that pyramidal neurons in the primary visual cortex (V1) and dorsolateral granular prefrontal cortex (dlPFC) of the rhesus monkey display “marked electrophysiological and structural differences.”

“We chose to examine these two areas because they represent distinct ends of the spectrum of neocortical complexity and specialization, from primary sensory processing by V1 to mediation of high-order cognitive processes by dlPFC,” the authors say in their paper.

To assess the structural and functional properties of the neurons in these regions, the researchers examined whole-cell patch-clamp recordings, 3D reconstructions, and computational models. They used AutoNeuron to automatically generate 3D neuron reconstructions, then imported this data into NeuroExplorer to assess dendritic length and complexity, finding that V1 neurons are relatively simpler in structure, with a smaller size and sparser dendritic arborization than neurons in the dlPFC, which were characterized by extensive dendritic branching and more complex synaptic connectivity.

The neurons in the two regions also showed differences in action potential firing rates, with V1 neurons firing faster than dlPFC neurons – a physiological characteristic the authors attribute to the cell’s necessity to rapidly process continuously changing inputs. These calculations were obtained by incorporating the 3D neuronal reconstructions into computational models that simulated neuronal electrical activity, allowing the researchers to gather information on the cells’ excitability and firing power.

“The compact electrotonic arbor and increased excitability of V1 neurons support the rapid signal integration required for early processing of visual information, [while] the greater connectivity and dendritic complexity of dlPFC neurons likely support higher level cognitive functions including working memory and planning,” the authors say.

“Our ongoing studies continue to benefit enormously from the AutoNeuron, AutoSpine and AutoSynapse modules of Neurolucida,” said Dr. Jennifer Luebke, senior author of the study.

“The figure above demonstrates our use of the AutoNeuron, AutoSpine and AutoSynapse modules of Neurolucida, to reconstruct a dendritic segment, identify and provide volumetric data on spine subtypes, and identify VGat-positive (GABAergic) synapses in a layer 3 pyramidal neuron from the anterior cingulate cortex of a rhesus monkey” – Jennifer Luebke, PhD

Amatrudo, J. M., Weaver, C. M., Crimins, J. L., Hof, P. R., Rosene, D. L., & Luebke, J. I. (2012). Influence of Highly Distinctive Structural Properties on the Excitability of Pyramidal Neurons in Monkey Visual and Prefrontal Cortices. Journal of Neuroscience, 32(40), 13644-13660. doi: 10.1523/jneurosci.2581-12.2012.

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