Publications by authors named "Alvaro Tejero-Cantero"

Animals use salient cues to navigate in their environment, but their specific cognitive strategies are largely unknown. We developed a conditioned place avoidance paradigm to discover whether and how zebrafish form spatial memories. In less than an hour, juvenile zebrafish, as young as 3 weeks, learned to avoid the arm of a Y-maze that was cued with a mild electric shock.

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The brain is capable of producing coordinated fast changing neural dynamics across multiple brain regions in order to adapt to rapidly changing environments. However, it is non-trivial to identify multiregion dynamics at fast sub-second time-scales in electrophysiological data. We propose a method that, with no knowledge of any task timings, can simultaneously identify and describe fast transient multiregion dynamics in terms of their temporal, spectral and spatial properties.

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We found that optogenetic burst stimulation of hippocampal dopaminergic fibers from midbrain neurons in mice exploring novel environments enhanced the reactivation of pyramidal cell assemblies during subsequent sleep/rest. When applied during spatial learning of new goal locations, dopaminergic photostimulation improved the later recall of neural representations of space and stabilized memory performance. These findings reveal that midbrain dopaminergic neurons promote hippocampal network dynamics associated with memory persistence.

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Neuroscience today deals with a "data deluge" derived from the availability of high-throughput sensors of brain structure and brain activity, and increased computational resources for detailed simulations with complex output. We report here (1) a novel approach to data sharing between collaborating scientists that brings together file system tools and cloud technologies, (2) a service implementing this approach, called NeuronDepot, and (3) an example application of the service to a complex use case in the neurosciences. The main drivers for our approach are to facilitate collaborations with a transparent, automated data flow that shields scientists from having to learn new tools or data structuring paradigms.

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Recurring sequences of neuronal activation in the hippocampus are a candidate for a neurophysiological correlate of episodic memory. Here, we discuss a mean-field theory for such spike sequences in phase space and show how they become unstable when the neuronal network operates at maximum memory capacity. We find that inhibitory feedback rescues replay of the sequences, giving rise to oscillations and thereby enhancing the network's capacity.

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High-frequency hippocampal network oscillations, or "ripples," are thought to be involved in episodic memory. According to current theories, memory traces are represented by assemblies of principal neurons that are activated during ripple-associated network states. Here we performed in vivo and in vitro experiments to investigate the synaptic mechanisms during ripples.

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