Learning and Its Neural Correlates in a Virtual Environment for Honeybees

The search for neural correlates of operant and observational learning requires a combination of two (experimental) conditions that are very difficult to combine: stable recording from high order neurons and free movement of the animal in a rather natural environment. We developed a virtual environment (VE) that simulates a simplified 3D world for honeybees walking stationary on an air-supported spherical treadmill. We show that honeybees perceive the stimuli in the VE as meaningful by transferring learned information from free flight to the virtual world. In search for neural correlates of learning in the VE, mushroom body extrinsic neurons were recorded over days during learning. We found changes in the neural activity specific to the rewarded and unrewarded visual stimuli. Our results suggest an involvement of the mushroom body extrinsic neurons in operant learning in the honeybee (Apis mellifera)

Spike-based acquisition of grammatical structure: on the importance of low-level brain mechanisms for high-level cognitive skills

Cognition can be studied across a variety of interfaces. While the 'brain-cognition' interface highlights the aim to build explanatory models for the implementation of cognition in the biological brain, 'low-high' and 'subsymbolic-symbolic' interfaces demonstrate the scope of possible representation and computation types underlying cognition. This thesis aimed at contributing potential connecting links across these interfaces by taking a closer look at the underlying learning mechanisms of human grammar acquisition (i.e. a high-level and possibly symbolic cognitive skill). Motivated by the hypothesis that especially early childhood language acquisition phases are characterised by associative, statistical learning types, the acquisition of isolated and nested non-adjacent grammars was modelled by associative, statistical learning in a spiking recurrent neural network (i.e. a low-level and subsymbolic mechanism). By demonstrating that grammar learning outcomes of the model (i.e. distributed synapse assembly strengths) complied with a variety of grammar acquisition performance patterns of human learners, associative, statistical learning was identified as an essential contributor for successful grammar learning and potentially also language acquisition. Moreover, given that a low-level and subsymbolic mechanism accounted for aspects of high-level human grammar learning, this cognitive skill might potentially be grounded on a subsymbolic basis. Finally, by including core brain components and processing principles into the model (i.e. a generic recurrent neural network, distributed encoding and unsupervised learning), a potential minimal set of neurobiological requirements for non-adjacent grammar learning was identified. Taken together, this thesis provided a connecting link between the fields of psycho- and neurolinguistics and neuroinformatics that was identified by a salient commonality in both, namely the central role of associative, statistical learning. The model especially described how a naive learner might acquire first knowledge about the statistics of the surrounding environment by passive exposure. However, other cognitive mechanisms that potentially build up on the formed low-level knowledge representations might go beyond mere associative, statistical learning. This thesis therefore provided a potential starting point for future research with a focus on understanding in more detail the potential interplay of different cognitive strategies: starting from low-level and subsymbolic learning towards reaching high-level and symbolic cognition

Spike-based statistical learning explains human performance in non-adjacent dependency learning tasks

Grammar acquisition is of significant importance for mastering human language. As the language signal is sequential in its nature, it poses the challenging task to extract its structure during online processing. This modeling study shows how spike-timing dependent plasticity (STDP) successfully enables sequence learning of artificial grammars that include non-adjacent dependencies (NADs) and nested NADs. Spike-based statistical learning leads to synaptic representations that comply with human acquisition performances under various distributional stimulus conditions. STDP, therefore, represents a practicable neural mechanism underlying human statistical grammar learning. These findings highlight that initial stages of the language acquisition process are possibly based on associative learning strategies. Moreover, the applicability of STDP demonstrates that the non-human brain possesses potential precursor abilities that support the acquisition of linguistic structure

Strategic Investment in Sperm Removal Behaviour in a Bushcricket

Foraita M, Lehfeldt S, Reinhold K, Ramm SA. Strategic Investment in Sperm Removal Behaviour in a Bushcricket. JOURNAL OF INSECT BEHAVIOR. 2017;30(2):170-179.Multiple mating by females is widespread and generates sperm competition among the ejaculates of rival males over fertilization. One way in which males can avoid or reduce sperm competition is by displacing or removing previous males' sperm from female sperm stores. An apparent example of this occurs in the bushcricket Metaplastes ornatus. Males perform a specialised sperm removal behaviour (SRB), using their highly-derived subgenital plate, with which they remove sperm from the female's spermatheca during the early phases of mating before transferring a spermatophore of their own. Here we investigated whether males strategically invest in SRB according to the amount of previously stored sperm present in females. Each male was tested twice, once with a female containing sperm ('filled' condition) and once with a female from whom most previously deposited sperm had recently been removed by another male (emptied' condition). For comparison, a separate group of males was paired with virgin females. Males did not discriminate between non-virgin females in the 'emptied' or 'filled' conditions in terms of their investment in SRB, suggesting they may not able to perceive the amount of sperm present in the female's spermatheca. By contrast, male investment in SRB was significantly reduced in pairings with virgin females, indicating that males are sensitive to some aspect of a female's mating status. Our results thus suggest that males modulate SRB in response to female-mediated cues, possibly chemical cues left by previous males, which would not be present on virgin but would be on non-virgin females