Neuronal Activity in Rat Barrel Cortex Underlying Texture Discrimination

Rats and mice palpate objects with their whiskers to generate tactile sensations. This form of active sensing endows the animals with the capacity for fast and accurate texture discrimination. The present work is aimed at understanding the nature of the underlying cortical signals. We recorded neuronal activity from barrel cortex while rats used their whiskers to discriminate between rough and smooth textures. On whisker contact with either texture, firing rate increased by a factor of two to ten. Average firing rate was significantly higher for rough than for smooth textures, and we therefore propose firing rate as the fundamental coding mechanism. The rat, however, cannot take an average across trials, but must make an immediate decision using the signals generated on each trial. To estimate single-trial signals, we calculated the mutual information between stimulus and firing rate in the time window leading to the rat's observed choice. Activity during the last 75 ms before choice transmitted the most informative signal; in this window, neuronal clusters carried, on average, 0.03 bits of information about the stimulus on trials in which the rat's behavioral response was correct. To understand how cortical activity guides behavior, we examined responses in incorrect trials and found that, in contrast to correct trials, neuronal firing rate was higher for smooth than for rough textures. Analysis of high-speed films suggested that the inappropriate signal on incorrect trials was due, at least in part, to nonoptimal whisker contact. In conclusion, these data suggest that barrel cortex firing rate on each trial leads directly to the animal's judgment of texture

Whisker-Mediated Texture Discrimination

Rats use their whiskers to rapidly and accurately measure the texture of objects. The authors evaluate recent evidence about how whisker movement across a surface produces texture-specific motion signals, and how the signals are represented by the brain

Effects of GPR139 agonism on effort expenditure for food reward in rodent models: Evidence for pro-motivational actions

Apathy, deficiency of motivation including willingness to exert effort for reward, is a common symptom in many psychiatric and neurological disorders, including depression and schizophrenia. Despite improved understanding of the neurocircuitry and neurochemistry underlying normal and deficient motivation, there is still no approved pharmacological treatment for such a deficiency. GPR139 is an orphan G protein-coupled receptor expressed in brain regions which contribute to the neural circuitry that controls motivation including effortful responding for reward, typically sweet gustatory reward. The GPR139 agonist TAK-041 is currently under development for treatment of negative symptoms in schizophrenia which include apathy. To date, however, there are no published preclinical data regarding its potential effect on reward motivation or deficiencies thereof. Here we report in vitro evidence confirming that TAK-041 increases intracellular Ca2+ mobilization and has high selectivity for GPR139. In vivo, TAK-041 was brain penetrant and showed a favorable pharmacokinetic profile. It was without effect on extracellular dopamine concentration in the nucleus accumbens. In addition, TAK-041 did not alter the effort exerted to obtain sweet gustatory reward in rats that were moderately food deprived. By contrast, TAK-041 increased the effort exerted to obtain sweet gustatory reward in mice that were only minimally food deprived; furthermore, this effect of TAK-041 occurred both in control mice and in mice in which deficient effortful responding was induced by chronic social stress. Overall, this study provides preclinical evidence in support of GPR139 agonism as a molecular target mechanism for treatment of apathy

Comparison of Whisker Motion Profiles Collected under Different Conditions

<div><p>Kinetic signatures are apparent in position (blue traces) and velocity (green traces), and these are conserved across experimental conditions.</p> <p>(A) Contact of D3 whisker with texture P150, measured ~10 mm from the base (adapted from [<a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.0060220#pbio-0060220-b012" target="_blank">12</a>]). (B) Contact of C3 whisker with texture P280 (upper panel) and with texture P100 (lower panel), both measured 1 mm from the base (adapted from [<a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.0060220#pbio-0060220-b010" target="_blank">10</a>]).</p></div

Whisker Trajectories

<p>Whisker trajectory measured when the whiskers moved through the air with no texture present (upper trace) and when the whiskers contacted texture P1200 (middle trace) and texture P400 (lower trace). Adapted from [<a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.0060220#pbio-0060220-b012" target="_blank">12</a>]. Texture photographs from [<a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.0060220#pbio-0060220-b010" target="_blank">10</a>].</p

Candidate Texture-Coding Mechanisms

<p>(A) In two different studies, progressively coarser textures evoked kinetic signatures with higher magnitude kinetic events. Red marks are slip-stick events from [<a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.0060220#pbio-0060220-b012" target="_blank">12</a>] measured for whiskers D1 and D2; blue marks are ENL from [<a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.0060220#pbio-0060220-b010" target="_blank">10</a>] measured for whisker C3. (B) Higher ENLs led to higher firing rates in the trigeminal ganglion (black diamonds) and barrel cortex (green squares). Adapted from [<a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.0060220#pbio-0060220-b010" target="_blank">10</a>]. (C) Texture-specific spike patterns. Peristimulus time histogram (2 ms bins; 100 trials) of a ganglion cell for two whisks on textures P280 (left) and P100 (right). Mean firing rate (dashed red lines) were similar, suggesting temporal firing pattern as a critical coding mechanism.</p

Coordinated population activity underlying texture discrimination in rat barrel cortex

Rodents can robustly distinguish fine differences in texture using their whiskers, a capacity that depends on neuronal activity in primary somatosensory “barrel” cortex. Here we explore how texture was collectively encoded by populations of three to seven neuronal clusters simultaneously recorded from barrel cortex while a rat performed a discrimination task. Each cluster corresponded to the single-unit or multiunit activity recorded at an individual electrode. To learn how the firing of different clusters combines to represent texture, we computed population activity vectors across moving time windows and extracted the signal available in the optimal linear combination of clusters. We quantified this signal using receiver operating characteristic analysis and compared it to that available in single clusters. Texture encoding was heterogeneous across neuronal clusters, and only a minority of clusters carried signals strong enough to support stimulus discrimination on their own. However, jointly recorded groups of clusters were always able to support texture discrimination at a statistically significant level, even in sessions where no individual cluster represented the stimulus. The discriminative capacity of neuronal activity was degraded when error trials were included in the data, compared to only correct trials, suggesting a link between the neuronal activity and the animal's performance. These analyses indicate that small groups of barrel cortex neurons can robustly represent texture identity through synergistic interactions, and suggest that neurons downstream to barrel cortex could extract texture identity on single trials through simple linear combination of barrel cortex responses.This work was supported by the Human Frontier Science Program (Project RG0041/2009-C); European Research Council Advanced Grant CONCEPT (Project 294498); European Union FET Grants BIOTACT (Project 215910), CORONET (Project 269459), and SICODE (Project 284553); the Compagnia San Paolo; Spanish Ministry of Science and Innovation Grants BFU2008-03017/BFI and Consolider CSD2007-00023 (cofunded by the European Fund for Regional Development); and Valencia Regional Government Grants PROMETEO/2011/086 and ACOMP2010/199.Peer reviewe