Artificial activation of neural circuitry through electrical microstimulation and optogenetic techniques is important for both scientific discovery of circuit function and for engineered approaches to alleviate various disorders of the nervous system. However, evidence suggests that neural activity generated by artificial stimuli differs dramatically from normal circuit function, in terms of both the local neuronal population activity at the site of activation and the propagation to downstream brain structures. The precise nature of these differences and the implications for information processing remain unknown. Here, we used voltage-sensitive dye imaging of primary somatosensory cortex in the anesthetized rat in response to deflections of the facial vibrissae and electrical or optogenetic stimulation of thalamic neurons that project directly to the somatosensory cortex. Although the different inputs produced responses that were similar in terms of the average cortical activation, the variability of the cortical response was strikingly different for artificial versus sensory inputs. Furthermore, electrical microstimulation resulted in highly unnatural spatial activation of cortex, whereas optical input resulted in spatial cortical activation that was similar to that induced by sensory inputs. A thalamocortical network model suggested that observed differences could be explained by differences in the way in which artificial and natural inputs modulate the magnitude and synchrony of population activity. Finally, the variability structure in the response for each case strongly influenced the optimal inputs for driving the pathway from the perspective of an ideal observer of cortical activation when considered in the context of information transmission.

Acquiring the behavioral significance of a sound has repeatedly been shown to correlate with long term changes in response properties of neurons in the adult primary auditory cortex. However, the molecular and cellular basis for such changes is still poorly understood. To address this, we have begun examining the auditory cortical expression of an activity-dependent effector immediate early gene (IEG) with documented roles in synaptic plasticity and memory consolidation in the hippocampus: Arc/Arg3.1. For initial characterization, we applied a repeated 10 minute (24 hour separation) sound exposure paradigm to determine the strength and consistency of sound-evoked Arc/Arg3.1 mRNA expression in the absence of explicit behavioral contingencies for the sound. We used 3D surface reconstruction methods in conjunction with fluorescent in-situ hybridization (FISH) to assess the layer-specific sub-cellular compartmental expression of Arc/Arg3.1 mRNA. We unexpectedly found that both the intranuclear and cytoplasmic patterns of expression depended on the prior history of sound stimulation. Specifically, the percentage of neurons with expression only in the cytoplasm increased for repeated versus singular sound exposure, while intranuclear expression decreased. In contrast, the total cellular expression did not differ, consistent with prior IEG studies of primary auditory cortex. Our results were specific for cortical layers 3-6, as there was virtually no sound driven Arc/Arg3.1 mRNA in layers 1-2 immediately after stimulation. Our results are consistent with the kinetics and/or detectability of cortical subcellular Arc/Arg3.1 mRNA expression being altered by the initial exposure to the sound, suggesting exposure-induced modifications in the cytoplasmic Arc/Arg3.1 mRNA pool. Keywordsimmediate early gene; mouse; catFISH; novelty; familiarity; synaptic plasticity © 2011 IBRO. Published by Elsevier Ltd. All rights reserved.Corresponding Author: Robert C. Liu, Department of Biology, Emory University, Rollins Research, Center Rm. 2006, 1510 404-727-5274 (phone); 404-727-2880, (fax); robert.liu@emory.edu. Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. Response properties of sensory cortical neurons change as a stimulus gains behavioral relevance (Weinberger, 2004). On short time scales, such changes may represent attentional effects (Fritz et al., 2007), but on longer time scales, they provide a basis for the distributed storage of sensory memories (Sutherland and McNaughton, 2000;Kilgard et al., 2002;Sacco and Sacchetti, 2010). The molecular mechanisms underlying such long term c...

Objective Nonlinear system identification approaches were used to develop a dynamical model of the network level response to patterns of microstimulation in-vivo. Approach The thalamocortical circuit of the rodent vibrissa pathway was the model system, with voltage sensitive dye imaging capturing the cortical response to patterns of stimulation delivered from a single electrode in the ventral posteromedial thalamus. The results of simple paired stimulus experiments formed the basis for the development of a phenomenological model explicitly containing nonlinear elements observed experimentally. The phenomenological model was fit using datasets obtained with impulse train inputs, Poisson-distributed in time and uniformly varying in amplitude. Main Results The phenomenological model explained 58% of the variance in the cortical response to out of sample patterns of thalamic microstimulation. Furthermore, while fit on trial averaged data, the phenomenological model reproduced single trial response properties when simulated with noise added into the system during stimulus presentation. The simulations indicate that the single trial response properties were dependent on the relative sensitivity of the static nonlinearities in the two stages of the model, and ultimately suggest that electrical stimulation activates local circuitry through linear recruitment, but that this activity propagates in a highly nonlinear fashion to downstream targets. Significance The development of nonlinear dynamical models of neural circuitry will guide information delivery for sensory prosthesis applications, and more generally reveal properties of population coding within neural circuits.