Relationship between brain plasticity, learning and foraging performance in honey bees

Abstract

Brain structure and learning capacities both vary with experience, but the mechanistic link between them is unclear. Here, we investigated whether experience-dependent variability in learning performance can be explained by neuroplasticity in foraging honey bees. The mushroom bodies (MBs) are a brain center necessary for ambiguous olfactory learning tasks such as reversal learning. Using radio frequency identification technology, we assessed the effects of natural variation in foraging activity, and the age when first foraging, on both performance in reversal learning and on synaptic connectivity in the MBs. We found that reversal learning performance improved at foraging onset and could decline with greater foraging experience. If bees started foraging before the normal age, as a result of a stress applied to the colony, the decline in learning performance with foraging experience was more severe. Analyses of brain structure in the same bees showed that the total number of synaptic boutons at the MB input decreased when bees started foraging, and then increased with greater foraging intensity. At foraging onset MB structure is therefore optimized for bees to update learned information, but optimization of MB connectivity deteriorates with foraging effort. In a computational model of the MBs sparser coding of information at the MB input improved reversal learning performance. We propose, therefore, a plausible mechanistic relationship between experience, neuroplasticity, and cognitive performance in a natural and ecological context.

Reversal learning in Drosophila larvae

“…Nonetheless, at least for the appetitive domain, the extinction/decay of memory appears to be rather rapid in larvae and fittingly we observe "true" reversal learning only in a paradigm with relatively intense training for the initial association (3 cycles) and relatively little training for the second (1 cycle). This is in contrast with results, for example, in the honeybee, where appetitive reversal learning paradigms include several reversed-contingency training trials and often use a 1:1 ratio of trial numbers in the first and the second training phase (Ben-Shahar et al 2000;Komischke et al 2002;Hadar and Menzel 2010;Mota and Giurfa 2010;Boitard et al 2015;Cabirol et al 2018). Specifically, during the second phase, bees typically persist in responding to the cue that was originally reinforced, meaning that the effects of training from the first phase persist and need to be overcome during the second, reversed-contingency training phase (Hadar and Menzel 2010;Mota and Giurfa 2010).…”

“…1A). The ease of this reversal was striking, compared with what has been observed, for example, in experiments with honeybees (Ben-Shahar et al 2000;Komischke et al 2002;Hadar and Menzel 2010;Mota and Giurfa 2010;Boitard et al 2015;Cabirol et al 2018). We therefore wondered whether memory for the first training phase persists until the second test.…”

“…Indeed, these connections suggest a richer mnemonic functionality than previously acknowledged on the basis of the typically rather simple tasks used to investigate them (Heisenberg 1998(Heisenberg , 2003Menzel and Giurfa 2001). In this context, the present reversal learning paradigm might become useful (for pioneering work on the cellular basis of reversal learning in adult flies: Ren et al 2012;Wu et al 2012; for related work in bees: Devaud et al 2007;Boitard et al 2015;Cabirol et al 2018). In addition, the possible coexistence of (i) memory extinction/decay with (ii) memory for the first training phase, and (iii) memory for the second training phase might imply a complexity of memory "content" that also defines critical demands for computational models of adaptive behavior in these animals (for a recent circuit-level analysis of extinction memory in adults: Felsenberg et al 2018) In psychological terms, reversal learning may serve as an indicator of cognitive flexibility when an animal is confronted with environmental variations (Izquierdo et al 2017).…”

Developmental exposure to pesticide contaminated food impedes bumblebee brain growth predisposing adults to become poorer learners

“…For example, honeybees reared under sub-optimal environmental conditions have 47 exhibited reduced brain volumetric growth and altered neuronal architecture (Groh et al, 2004;Steijven 48 et al, 2017). Impeded brain development and structural plasticity may impact on behaviours such as 49 learning ability, that require detection, assimilation and processing of sensory input from the environment 50 (Cabirol et al, 2018;Chittka, 2017;Galizia et al, 2011). Knowledge of how pesticide contaminated food 51 inside bee colonies can affect individual physiological development however, is limited (Gregorc et al,52 2012; Wu et al, 2012Wu et al, , 2011.…”

Adult neurogenesis in the mushroom bodies of red flour beetles (Tribolium castaneum, Herbst) is influenced by the olfactory environment

“…Studies in adult holometabolous insects, including Apis mellifera and D. melanogaster, described synaptic plasticity, but no neurogenesis, in the mushroom bodies 36,[46][47][48][49][50][51][52][53][54][55] . Since adult neurogenesis in the mushroom bodies was first described in the hemimetabolous house cricket Acheta domestica 56,57 , it has also been found in Environmental conditions influence adult neurogenesis.…”