Effects of targeted memory reactivation during sleep at home depend on sleep disturbances and habituation.

Targeted memory reactivation (TMR) during sleep improves memory consolidation. However, it is still unknown whether TMR also benefits memory in real-life conditions. We tested whether TMR during sleep enhances Dutch-German vocabulary learning when applied during multiple nights at home in an unsupervised fashion. During 3 consecutive nights, 66 healthy young participants used an mp3-player to play Dutch words during sleep, without any control of sleep or awakenings by tones (unsupervised TMR). Unsupervised TMR benefitted overall memory scores only in a subgroup of participants, who reported no disturbances by TMR during sleep. Participants who reported general disturbances of sleep showed no benefit, while TMR specifically impaired memory in a third group who reported specific disturbances by the played words during sleep. Separate analysis per night indicated that memory benefits by TMR were significant in the entire sample in the third night only. Our results indicate that sleep disturbances and habituation might be critical factors for the success of unsupervised TMR in a home setting. Habituation to the TMR process as well as automatic sleep monitoring and avoidance of auditory-induced awakenings might be a precondition to successful application of TMR to language learning in real-life.

Increased neuronal signatures of targeted memory reactivation during slow-wave up states.

It is assumed that slow oscillatory up-states represent crucial time windows for memory reactivation and consolidation during sleep. We tested this assumption by utilizing closed-loop targeted memory reactivation: Participants were re-exposed to prior learned foreign vocabulary during up- and down-states of slow oscillations. While presenting memory cues during slow oscillatory up-states improved recall performance, down-state cueing did not result in a clear behavioral benefit. Still, no robust behavioral benefit of up- as compared to down-state cueing was observable. At the electrophysiological level however, successful memory reactivation during up-states was associated with a characteristic power increase in the theta and sleep spindle band. No oscillatory changes were observable for down-state cues. Our findings provide experimental support for the assumption that slow oscillatory up-states may represent privileged time windows for memory reactivation, while the interplay of slow oscillations, theta and sleep spindle activity promotes successful memory consolidation during sleep.

Cueing vocabulary during sleep increases theta activity during later recognition testing.

Neural oscillations in the theta band have repeatedly been implicated in successful memory encoding and retrieval. Several recent studies have shown that memory retrieval can be facilitated by reactivating memories during their consolidation during sleep. However, it is still unknown whether reactivation during sleep also enhances subsequent retrieval-related neural oscillations. We have recently demonstrated that foreign vocabulary cues presented during sleep improve later recall of the associated translations. Here, we examined the effect of cueing foreign vocabulary during sleep on oscillatory activity during subsequent recognition testing after sleep. We show that those words that were replayed during sleep after learning (cued words) elicited stronger centroparietal theta activity during recognition as compared to noncued words. The reactivation-induced increase in theta oscillations during later recognition testing might reflect a strengthening of individual memory traces and the integration of the newly learned words into the mental lexicon by cueing during sleep.

HelioScan: a software framework for controlling in vivo microscopy setups with high hardware flexibility, functional diversity and extendibility.

Intravital microscopy such as in vivo imaging of brain dynamics is often performed with custom-built microscope setups controlled by custom-written software to meet specific requirements. Continuous technological advancement in the field has created a need for new control software that is flexible enough to support the biological researcher with innovative imaging techniques and provide the developer with a solid platform for quickly and easily implementing new extensions. Here, we introduce HelioScan, a software package written in LabVIEW, as a platform serving this dual role. HelioScan is designed as a collection of components that can be flexibly assembled into microscope control software tailored to the particular hardware and functionality requirements. Moreover, HelioScan provides a software framework, within which new functionality can be implemented in a quick and structured manner. A specific HelioScan application assembles at run-time from individual software components, based on user-definable configuration files. Due to its component-based architecture, HelioScan can exploit synergies of multiple developers working in parallel on different components in a community effort. We exemplify the capabilities and versatility of HelioScan by demonstrating several in vivo brain imaging modes, including camera-based intrinsic optical signal imaging for functional mapping of cortical areas, standard two-photon laser-scanning microscopy using galvanometric mirrors, and high-speed in vivo two-photon calcium imaging using either acousto-optic deflectors or a resonant scanner. We recommend HelioScan as a convenient software framework for the in vivo imaging community.

Morphology-induced collective behaviors: dynamic pattern formation in water-floating elements.

Complex systems involving many interacting elements often organize into patterns. Two types of pattern formation can be distinguished, static and dynamic. Static pattern formation means that the resulting structure constitutes a thermodynamic equilibrium whose pattern formation can be understood in terms of the minimization of free energy, while dynamic pattern formation indicates that the system is permanently dissipating energy and not in equilibrium. In this paper, we report experimental results showing that the morphology of elements plays a significant role in dynamic pattern formation. We prepared three different shapes of elements (circles, squares, and triangles) floating in a water-filled container, in which each of the shapes has two types: active elements that were capable of self-agitation with vibration motors, and passive elements that were mere floating tiles. The system was purely decentralized: that is, elements interacted locally, and subsequently elicited global patterns in a process called self-organized segregation. We showed that, according to the morphology of the selected elements, a different type of segregation occurs. Also, we quantitatively characterized both the local interaction regime and the resulting global behavior for each type of segregation by means of information theoretic quantities, and showed the difference for each case in detail, while offering speculation on the mechanism causing this phenomenon.