Multi-neuronal refractory period adapts centrally generated behaviour to reward

A circuit mechanism linking past and future learning through shifts in perception

Long-term memory formation is energetically costly. Neural mechanisms that guide an animal to identify fruitful associations therefore have important survival benefits. Here, we elucidate a circuit mechanism in Lymnaea, which enables past memory to shape new memory formation through changes in perception. Specifically, strong classical conditioning drives a positive shift in perception that facilitates the robust learning of a subsequent and otherwise ineffective weak association. Circuit dissection approaches reveal the neural control network responsible, characterized by a mutual inhibition motif. This both sets perceptual state and acts as the master controller for gating new learning. Pharmacological circuit manipulation in vivo fully substitutes for strong paradigm learning, shifting the network into a more receptive state to enable subsequent weak paradigm learning. Thus, perceptual change provides a conduit to link past and future memory storage. We propose that this mechanism alerts animals to learning-rich periods, lowering the threshold for new memory acquisition.

The unlimited potential of the great pond snail, Lymnaea stagnalis

Only a limited number of animal species lend themselves to becoming model organisms in multiple biological disciplines: one of these is the great pond snail, Lymnaea stagnalis. Extensively used since the 1970s to study fundamental mechanisms in neurobiology, the value of this freshwater snail has been also recognised in fields as diverse as host-parasite interactions, ecotoxicology, evolution, genome editing and 'omics', and human disease modelling. While there is knowledge about the natural history of this species, what is currently lacking is an integration of findings from the laboratory and the field. With this in mind, this article aims to summarise the applicability of L. stagnalis and points out that this multipurpose model organism is an excellent, contemporary choice for addressing a large range of different biological questions, problems and phenomena.

Proactive and retroactive interference with associative memory consolidation in the snail Lymnaea is time and circuit dependent

Interference-based forgetting occurs when new information acquired either before or after a learning event attenuates memory expression (proactive and retroactive interference, respectively). Multiple learning events often occur in rapid succession, leading to competition between consolidating memories. However, it is unknown what factors determine which memory is remembered or forgotten. Here, we challenge the snail, Lymnaea, to acquire two consecutive similar or different memories and identify learning-induced changes in neurons of its well-characterized motor circuits. We show that when new learning takes place during a stable period of the original memory, proactive interference only occurs if the two consolidating memories engage the same circuit mechanisms. If different circuits are used, both memories survive. However, any new learning during a labile period of consolidation promotes retroactive interference and the acquisition of the new memory. Therefore, the effect of interference depends both on the timing of new learning and the underlying neuronal mechanisms.

In vitro studies of neuronal networks and synaptic plasticity in invertebrates and in mammals using multielectrode arrays

Brain functions are strictly dependent on neural connections formed during development and modified during life. The cellular and molecular mechanisms underlying synaptogenesis and plastic changes involved in learning and memory have been analyzed in detail in simple animals such as invertebrates and in circuits of mammalian brains mainly by intracellular recordings of neuronal activity. In the last decades, the evolution of techniques such as microelectrode arrays (MEAs) that allow simultaneous, long-lasting, noninvasive, extracellular recordings from a large number of neurons has proven very useful to study long-term processes in neuronal networks in vivo and in vitro. In this work, we start off by briefly reviewing the microelectrode array technology and the optimization of the coupling between neurons and microtransducers to detect subthreshold synaptic signals. Then, we report MEA studies of circuit formation and activity in invertebrate models such as Lymnaea, Aplysia, and Helix. In the following sections, we analyze plasticity and connectivity in cultures of mammalian dissociated neurons, focusing on spontaneous activity and electrical stimulation. We conclude by discussing plasticity in closed-loop experiments.

Control of synchronization patterns in neural-like Boolean networks

We study experimentally the synchronization patterns in time-delayed directed Boolean networks of excitable systems. We observe a transition in the network dynamics when the refractory time of the individual systems is adjusted. When the refractory time is on the same order of magnitude as the mean link time delays or the heterogeneities of the link time delays, cluster synchronization patterns change, or are suppressed entirely, respectively. We also show that these transitions occur when we change the properties of only a small number of driver nodes identified by their larger in degree; hence, the synchronization patterns can be controlled locally by these nodes. Our findings have implications for synchronization in biological neural networks.