Spectrally resolved fast transient brain states in electrophysiological data.

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. The approach models brain activity using a discrete set of sequential states, with each state distinguished by its own multiregion spectral properties. This can identify potentially very short-lived visits to a brain state, at the same time as inferring the state's properties, by pooling over many repeated visits to that state. We show how this can be used to compute state-specific measures such as power spectra and coherence. We demonstrate that this can be used to identify short-lived transient brain states with distinct power and functional connectivity (e.g., coherence) properties in an MEG data set collected during a volitional motor task.

Inhibition enhances memory capacity: optimal feedback, transient replay and oscillations.

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. We further argue that transient sequences in an overloaded network with feedback inhibition may provide a mechanistic picture of memory-related neuronal activity during hippocampal sharp-wave ripple complexes.

Zebrafish Exploit Visual Cues and Geometric Relationships to Form a Spatial Memory.

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. Interestingly, individual fish solved this task in different ways: by staying in the safe center of the maze or by preference for one, or both, of the safe arms. In experiments in which the learned patterns were swapped, rotated, or replaced, the animals could transfer the association of safety to a different arm or to a different pattern using either visual cues or location as the conditioned stimulus. These findings show that juvenile zebrafish exhibit several complementary spatial learning modes, which generate a flexible repertoire of behavioral strategies.

Dopaminergic neurons promote hippocampal reactivation and spatial memory persistence.

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.

NeuronDepot: keeping your colleagues in sync by combining modern cloud storage services, the local file system, and simple web applications.

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. Using NeuronDepot is simple: one-time data assignment from the originator and cloud based syncing-thus making experimental and modeling data available across the collaboration with minimum overhead. Since data sharing is cloud based, our approach opens up the possibility of using new software developments and hardware scalabitliy which are associated with elastic cloud computing. We provide an implementation that relies on existing synchronization services and is usable from all devices via a reactive web interface. We are motivating our solution by solving the practical problems of the GinJang project, a collaboration of three universities across eight time zones with a complex workflow encompassing data from electrophysiological recordings, imaging, morphological reconstructions, and simulations.

Coherent phasic excitation during hippocampal ripples.

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. We discovered postsynaptic currents that are phase-locked to ripples and coherent among even distant CA1 pyramidal neurons. These fast currents are consistent with excitatory postsynaptic currents (EPSCs) as they are observed at the equilibrium potential of Cl(-), and they display kinetics characteristic of EPSCs. Furthermore, they survived after intracellular blockade of GABAergic transmission and are effective to regulate the timing of action potentials. In addition, our data show a progressive synchronization of phasic excitation and inhibition during the course of ripples. Together, our results demonstrate the presence of phasic excitation during ripples reflecting an exquisite temporal coordination of assemblies of active pyramidal cells.