Crossmodal Integration Improves Sensory Detection Thresholds in the Ferret

May Crossmodal Integration Improves Sensory Detection Thresholds in the Ferret Karl J. Hollensteiner 0 1 Florian Pieper 0 1 Gerhard Engler 0 1 Peter Knig 0 1 Andreas K. Engel 0 1 0 1 Dept. of Neurophysiology and Pathophysiology, University Medical Center Hamburg-Eppendorf , 20246 Hamburg, Germany , 2 Institute of Cognitive Science, University of Osnabruck , 49069 Osnabruck , Germany 1 Academic Editor: Maurice Ptito, University of Montreal , CANADA During the last two decades ferrets (Mustela putorius) have been established as a highly efficient animal model in different fields in neuroscience. Here we asked whether ferrets integrate sensory information according to the same principles established for other species. Since only few methods and protocols are available for behaving ferrets we developed a head-free, body-restrained approach allowing a standardized stimulation position and the utilization of the ferret's natural response behavior. We established a behavioral paradigm to test audiovisual integration in the ferret. Animals had to detect a brief auditory and/or visual stimulus presented either left or right from their midline. We first determined detection thresholds for auditory amplitude and visual contrast. In a second step, we combined both modalities and compared psychometric fits and the reaction times between all conditions. We employed Maximum Likelihood Estimation (MLE) to model bimodal psychometric curves and to investigate whether ferrets integrate modalities in an optimal manner. Furthermore, to test for a redundant signal effect we pooled the reaction times of all animals to calculate a race model. We observed that bimodal detection thresholds were reduced and reaction times were faster in the bimodal compared to unimodal conditions. The race model and MLE modeling showed that ferrets integrate modalities in a statistically optimal fashion. Taken together, the data indicate that principles of multisensory integration previously demonstrated in other species also apply to crossmodal processing in the ferret. - Competing Interests: The authors have declared that no competing interests exist. During the last two decades ferrets (Mustela putorius) have become increasingly relevant as an animal model in different fields in neuroscience [124]. Ferrets have been domesticated for over 2000 years and are easy to handle and train on behavioral tasks [15,2529]. As a carnivore ferrets have excellent visual and auditory sensing and are well suited for cross-modal integration studies. An additional advantage is that the ferret brain shows substantial homologies with that of other animal models established in neuroscience, such as the cat [10,11,1820] and the primate [26]. Extensive work has been performed to map cortical and subcortical regions of the ferret brain functionally and anatomically [3,11,1720,22]. These mapping studies have shown that ferrets have highly complex sensory cortical systems, making them an interesting model for the study of sensory processing pathways, response properties and topographies of sensory neurons. Several studies have addressed multisensory response properties in anesthetized ferrets [2,4,8,14], but multisensory interactions have not yet been studied in a behavioral preparation in this species. Substantial effort has been made to uncover principles of multisensory integration in a variety of species and paradigms [3035]. Multisensory integration is crucial for animals and influences behavior in synergistic or competitive ways. Sensory integration can lead to faster reaction times, better detection rates and higher accuracy values in multi- compare to unimodal conditions [33,36,37]. Specifically, sensory integration increases the reliability by reducing the variance in the sensory estimate [36,38,39]. The consistent estimate with the lowest variance is the Maximum Likelihood Estimate (MLE) [40], which can be derived from the weighted sum of the individual sensory estimates, with weights being inversely proportional to the variance of the unisensory signals [36,39]. A substantial number of studies indicate that humans and animals indeed integrate information across sensory modalities in this way [33,36,38,39,4146]. For example, Ernst and Banks [36] used a MLE model to predict the results of a visual-haptic experiment and showed that humans integrate information in a statistically optimal fashion. Similar results were obtained by application of MLE in a human audiovisual study [37] and in a vestibular-visual study in macaque monkeys [47]. These studies demonstrate that the MLE is a robust statistical model to predict the crossmodal response and to test whether subjects integrate information in a statistically optimal fashion. As a results of the sensory integration process, the accumulation of information in multimodal compared to unimodal conditions is faster, which in turn leads to decreased reaction times (RT) [4853]. In the present study, we investigated whether ferrets integrate sensory signals according to the same principles established for humans [33,54] and non-human primates [47]. Previous studies in behaving ferrets have used either freely-moving [13,15,55] or head-restrained [26] animals. Here, we developed a head-free, body-restrained approach allowing a standardized stimulation position and the utilization of the ferrets natural response behavior. An additional demand was that the setup should be sufficiently flexible to allow combination of the behavioral protocol with electrophysiological recordings. We established a behavioral paradigm, requiring combination and integration in the auditory and/or visual modality, to investigate features of uni- and multisensory integration in the ferret and compare it to data reported from other species. Ferrets were tested in a 2-alternative-choice task requiring them to detect lateralized auditory, visual, or combined audio-visual targets of varying intensity. We expected the ferrets to perform more accurate and faster in the bimodal cases, because congruent inputs from two modalities provide more reliable sensory evidence. We first determined unimodal thresholds for auditory amplitude and visual contrast detection. Subsequently, we combined both modalities and compared psychometric fits and the RTs between all conditions. We used MLE to model psychometric curves and to probe whether ferrets integrate visual and auditory signals in an optimal manner. Furthermore, to test for a redundant signal effect (RSE) we pooled the RT of all animals in order to calculate a race model and to investigate potential intensity- and modality-dependent effects [49,56,57]. Materials and Methods Ferrets were trained in a spatial detection paradigm, which was used to perform two behavioral experiments. In the first experiment, the animals auditory and visual unisensory detection thresholds were determined. In the second experiment, unimodal and bimodal thresholds were assessed in a combined (...truncated)