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The brain's capacity to rewire is thought to diminish with age. It is widely believed that development stabilizes the synapses from thalamus to cortex and that adult experience alters only synaptic connections between cortical neurons. Here we show that thalamocortical (TC) inputs themselves undergo massive plasticity in adults. We combined whole-cell recording from individual thalamocortical neurons in adult rats with a recently developed automatic tracing technique to reconstruct individual axonal trees. Whisker trimming substantially reduced thalamocortical axon length in barrel cortex but not the density of TC synapses along a fiber. Thus, sensory experience alters the total number of TC synapses. After trimming, sensory stimulation evoked more tightly time-locked responses among thalamorecipient layer 4 cortical neurons. These findings indicate that thalamocortical input itself remains plastic in adulthood, raising the possibility that the axons of other subcortical structures might also remain in flux throughout life., (Copyright © 2012 Elsevier Inc. All rights reserved.)

The cortical output layer 5 contains two excitatory cell types, slender- and thick-tufted neurons. In rat vibrissal cortex, slender-tufted neurons carry motion and phase information during active whisking, but remain inactive after passive whisker touch. In contrast, thick-tufted neurons reliably increase spiking preferably after passive touch. By reconstructing the 3D patterns of intracortical axon projections from individual slender- and thick-tufted neurons, filled in vivo with biocytin, we were able to identify cell type-specific intracortical circuits that may encode whisker motion and touch. Individual slender-tufted neurons showed elaborate and dense innervation of supragranular layers of large portions of the vibrissal area (total length, 86.8 ± 5.5 mm). During active whisking, these long-range projections may modulate and phase-lock the membrane potential of dendrites in layers 2 and 3 to the whisking cycle. Thick-tufted neurons with soma locations intermingling with those of slender-tufted ones display less dense intracortical axon projections (total length, 31.6 ± 14.3 mm) that are primarily confined to infragranular layers. Based on anatomical reconstructions and previous measurements of spiking, we put forward the hypothesis that thick-tufted neurons in rat vibrissal cortex receive input of whisker motion from slender-tufted neurons onto their apical tuft dendrites and input of whisker touch from thalamic neurons onto their basal dendrites. During tactile-driven behavior, such as object location, near-coincident input from these two pathways may result in increased spiking activity of thick-tufted neurons and thus enhanced signaling to their subcortical targets.

Sensory-evoked signal flow, at cellular and network levels, is primarily determined by the synaptic wiring of the underlying neuronal circuitry. Measurements of synaptic innervation, connection probabilities and subcellular organization of synaptic inputs are thus among the most active fields of research in contemporary neuroscience. Methods to measure these quantities range from electrophysiological recordings over reconstructions of dendrite-axon overlap at light-microscopic levels to dense circuit reconstructions of small volumes at electron-microscopic resolution. However, quantitative and complete measurements at subcellular resolution and mesoscopic scales to obtain all local and long-range synaptic in/outputs for any neuron within an entire brain region are beyond present methodological limits. Here, we present a novel concept, implemented within an interactive software environment called NeuroNet, which allows (i) integration of sparsely sampled (sub)cellular morphological data into an accurate anatomical reference frame of the brain region(s) of interest, (ii) up-scaling to generate an average dense model of the neuronal circuitry within the respective brain region(s) and (iii) statistical measurements of synaptic innervation between all neurons within the model. We illustrate our approach by generating a dense average model of the entire rat vibrissal cortex, providing the required anatomical data, and illustrate how to measure synaptic innervation statistically. Comparing our results with data from paired recordings in vitro and in vivo, as well as with reconstructions of synaptic contact sites at light- and electron-microscopic levels, we find that our in silico measurements are in line with previous results. [ABSTRACT FROM AUTHOR]