Hippocampal mossy fibers and swimming navigation learning in two vole species occupying different habitats

Abstract

We showed previously for mice that size differences of the infrapyramidal hippocampal mossy fiber projection (IIP‐MF) correlate with spatial learning abilities. In order to clarify the role of the IIP‐MF in a natural environment, we studied the bank vole (Clethrionomys glareolus), adapted to a wide range of different habitats, and the root vole (Microtus oeconomus), living in homogenous grassland habitats with small home ranges. Morphometry on Timm‐stained horizontal brain sections of six C. glareolus and six M. oeconomus revealed that the size of the entire mossy fiber projection was 42% larger in C. glareolus than M. oeconomus. C. glareolus had also an IIP‐MF projection about 230% larger than that of the root vole. A sample of captured animals was then transferred to the laboratory (C. glareolus, n = 23; M. oeconomus, n = 15) and underwent testing for swimming navigation according to a standardized protocol used to assess water maze learning in about 2,000 normal and transgenic mice. Both species learned faster than laboratory mice. Overall escape times showed no differences, but path length was significantly reduced in C. glareolus, which also showed superior performance in a variety of scores assessing spatial search patterns. On the other hand, M. oeconomus showed faster swimming speed, and strong thigmotaxis combined with circular swimming. M. oeconomus also scored at chance levels during the probe trial, about as poorly as mutant knockout mice considered to be deficient in spatial memory. These differences probably reflect differential styles of water maze learning rather than spatial memory deficits: C. glareolus appears to be superior in inhibiting behavior interfering with proper spatial search behavior, while M. oeconomus succeeds in escaping by using rapid circular swimming. We assume that size variations of the IIP‐MF correspond to a mechanism stabilizing hippocampal processing during spatial learning or complex activities. This corresponds to the ecological lifestyle of the two species and is in line with previous observations on the role of the IIP‐MF. Hippocampus 2000;10:17–30. © 2000 Wiley‐Liss, Inc.

Linking ecology and cognition: does ecological specialisation predict cognitive test performance?

“…Occurring across larger and more complex areas, habitat generalists would benefit from advanced navigational strategies to efficiently explore these areas, specifically when they feed on patchy distributed but potentially predictable food sources. The habitat generalist bank vole, for instance, showed increased spatial memory compared to the more specialised root vole (Pleskacheva et al 2000). In lemurs, the species with greater habitat specialisation performed better in the spatial memory task due to more efficient use of navigational heuristics (Teichroeb and Vining 2019).…”

“…Similarly, Cocos frillgobies (Bathygobius cocosensis) and Krefft's gobies (B. krefftii) that occur in spatially complex rock pool habitats performed better in a spatial learning test than Eastern long-finned gobies (Favonigobius lentiginosus) and Hoese's sandgobies (Istigobius hoesei) occurring in homogenous sandy shores (White and Brown 2015a). Also bank voles (Myodes glareolus), which occur in more complex habitats, exhibited better spatial search behaviour than root voles (Microtus oeconomus), which occur in more open habitats (Pleskacheva et al 2000). Moreover, omnivorous bank voles and herbivorous common voles (M. arvalis) were similar in their efficiency of exploiting stable habitats, but the omnivorous bank voles were more efficient in exploiting habitats with temporally changing food locations (Haupt et al 2010).…”

“…Empirical comparisons of cognitive performance between generalists and specialists have either investigated effective habitat exploration in, for instance, spatial memory tasks (Pleskacheva et al 2000;Haupt et al 2010), or specific foraging abilities like innovative propensities (Day et al 2003;Overington et al 2009;Overington et al 2011;Griffin and Diquelou 2015;Henke-von der Malsburg and Fichtel 2018), associative learning (Hoedjes et al 2012) or behavioural flexibility (Day et al 1999a), using a variety of problem-solving experiments, including food extraction tasks, visual or olfactory discriminations or reversal learning tasks.…”

“…Interspecific differences in cognitive performance have been reported as a function of variation in ranging behaviour and search strategies (Teichroeb and Vining 2019;Trapanese et al 2019), foraging activity (Day et al 1999a;Day et al 2003;Jones et al 2017), foraging techniques (Day et al 2003), characteristics of preferred dietary items (Pleskacheva et al 2000;Henry and Stoner 2011;Teichroeb and Vining 2019), adaptations to habitat complexity (Pleskacheva et al 2000;Clarin et al 2013;White and Brown 2015a) or adaptations to seasonality (Cristol et al 2003; Barkley and Jacobs 2007;Henry and Stoner 2011) (Fig. 2).…”

Long‐term monitoring of hippocampus‐dependent behavior in naturalistic settings: Mutant mice lacking neurotrophin receptor TrkB in the forebrain show spatial learning but impaired behavioral flexibility

“…In those reports, they are interpreted as an inability of spatial learning, but see above. Likewise, variations in hippocampal mossy fiber patterns known to be associated with hippocampal functions correlate moderately with thigmotaxis (Pleskacheva et al, 2000) and place reversal learning in the Morris maze (Schöpke et al, 1991;Bernasconi-Guastalla et al, 1994); further, mice with hippocampal lesions show excessive wall swimming (Mojaheri et al, unpublished observations). Finally, lesions of the mouse hippocampus do not only impair the acquisition of finding an invisible platform, but retard, unlike in rats, learning of cued escape learning (Logue et al, 1997).…”