A consensus statement on detection of hippocampal sharp wave ripples and differentiation from other fast oscillations

Decades of rodent research have established the role of hippocampal sharp wave ripples (SPW-Rs) in consolidating and guiding experience. More recently, intracranial recordings in humans have suggested their role in episodic and semantic memory. Yet, common standards for recording, detection, and reporting do not exist. Here, we outline the methodological challenges involved in detecting ripple events and offer practical recommendations to improve separation from other high-frequency oscillations. We argue that shared experimental, detection, and reporting standards will provide a solid foundation for future translational discovery.

A novel approach to prepare polymer mixed-brushes via single crystal surface patterning

Single crystals having matrix-dispersed surface morphologies were prepared and characterized.

Self-assembling nano mixed-brushes having co-continuous surface morphology by melt growing single crystals and comparison with solution patterned leopard-skin surface morphology

The behavior of melt-grown mixed-brushes was studied and compared with the behavior of the corresponding solution-grown matrix-dispersed mixed-brushes.

Theta- and gamma-band oscillatory uncoupling in the macaque hippocampus

Nested hippocampal oscillations in the rodent give rise to temporal dynamics that may underlie learning, memory, and decision making. Although theta/gamma coupling in rodent CA1 occurs during exploration and sharp-wave ripples emerge in quiescence, it is less clear that these oscillatory regimes extend to primates. We therefore sought to identify correspondences in frequency bands, nesting, and behavioral coupling of oscillations taken from macaque hippocampus. We found that, in contrast to rodent oscillations, theta and gamma frequency bands in macaque CA1 were segregated by behavioral states. In both stationary and freely-moving designs, beta2/gamma (15-70 Hz) had greater power during visual search whereas the theta band (3-10 Hz; peak ~8 Hz) dominated during quiescence and early sleep. Moreover, theta band amplitude was strongest when beta2/slow gamma (20-35 Hz) amplitude was weakest, instead occurring along with higher frequencies (60-150 Hz). Spike-field coherence was most frequently seen in these three bands, (3-10 Hz, 20-35 Hz and 60-150 Hz); however, the theta-band coherence was largely due to spurious coupling during sharp-wave ripples. Accordingly, no intrinsic theta spiking rhythmicity was apparent. These results support a role for beta2/slow gamma modulation in CA1 during active exploration in the primate that is decoupled from theta oscillations. The apparent difference to the rodent oscillatory canon calls for a shift in focus of frequency when considering the primate hippocampus.

GABAA receptor in the Pedunculopontine tegmental (PPT) nucleus: Effects on cardiovascular system

BACKGROUND

The pedunculopontine tegmental (PPT) nucleus is a heterogeneous nucleus with several functions including cardiovascular regulation. The presence of GABAA receptor has been shown in the PPT. Therefore, the cardiovascular effects of this receptor were examined.

METHODS

Rats were divided into: Control; Muscimol; Bicuculline (BMI); Hexamethonium (Hexa)+BMI and Atropine+BMI groups. The femoral vein and artery were cannulated for drug administration and recording of cardiovascular parameters, respectively. Muscimol (a GABAA agonist; 1.5 and 2.5nmol), BMI (a GABAA antagonist; 0.1 and 0.2nmol) were stereotaxically microinjected into the PPT. To evaluate the peripheral cardiovascular mechanisms of GABAA receptors, Hexa (a ganglionic blocker; 10mg/kg) and atropine (a muscarinic receptor antagonist; 1mg/kg) were intravenously (iv) injected before BMI (0.2nmol). The average changes of mean arterial pressure (ΔMAP), systolic blood pressure (ΔSBP) and heart rate (ΔHR) in different intervals were calculated and compared both within and between case group and control group (repeated measures ANOVA). The peak changes in each group were also calculated and compared with those of the control group (independent sample t-test).

RESULTS

Both doses of BMI significantly increased ΔMAP, ΔSBP and ΔHR compared to control, while the only higher dose of muscimol significantly decreased ΔSBP. Iv injection of Hexa significantly attenuated ΔMAP, ΔSBP and ΔHR responses induced by BMI but atropine did not affect.

CONCLUSIONS

Our results demonstrate that GABAA receptor of the PPT has a tonic inhibitory effect on the cardiovascular system and its peripheral effect mostly is mediated by sympathetic system.

Retrosplenial and Hippocampal Synchrony during Retrieval of Old Memories in Macaques

Memory for events from the distant past relies on multiple brain regions, but little is known about the underlying neural dynamics that give rise to such abilities. We recorded neural activity in the hippocampus and retrosplenial cortex of two female rhesus macaques as they visually selected targets in year-old and newly acquired object-scene associations. Whereas hippocampal activity was unchanging with memory age, the retrosplenial cortex responded with greater magnitude alpha oscillations (10-15 Hz) and greater phase locking to memory-guided eye movements during retrieval of old events. A similar old-memory enhancement was observed in the anterior cingulate cortex but in a beta2/gamma band (28-35 Hz). In contrast, remote retrieval was associated with decreased gamma-band synchrony between the hippocampus and each neocortical area. The increasing retrosplenial alpha oscillation and decreasing hippocampocortical synchrony with memory age may signify a shift in frank memory allocation or, alternatively, changes in selection among distributed memory representations in the primate brain.SIGNIFICANCE STATEMENT Memory depends on multiple brain regions, whose involvement is thought to change with time. Here, we recorded neuronal population activity from the hippocampus and retrosplenial cortex as nonhuman primates searched for objects embedded in scenes. These memoranda were either newly presented or a year old. Remembering old material drove stronger oscillations in the retrosplenial cortex and led to a greater locking of neural activity to search movements. Remembering new material revealed stronger oscillatory synchrony between the hippocampus and retrosplenial cortex. These results suggest that with age, memories may come to rely more exclusively on neocortical oscillations for retrieval and search guidance and less on long-range coupling with the hippocampus.

Circuit dynamics of superficial and deep CA1 pyramidal cells and inhibitory cells in freely-moving macaques

Diverse neuron classes in hippocampal CA1 have been identified through the heterogeneity of their cellular/molecular composition. How these classes relate to hippocampal function and the network dynamics that support cognition in primates remains unclear. Here we report inhibitory functional cell groups in CA1 of freely-moving macaques whose diverse response profiles to network states and each other suggest distinct and specific roles in the functional microcircuit of CA1. In addition, pyramidal cells that were segregated into superficial and deep layers differed in firing rate, burstiness, and sharp-wave ripple-associated firing. They also showed strata-specific spike-timing interactions with inhibitory cell groups, suggestive of segregated neural populations. Furthermore, ensemble recordings revealed that cell assemblies were preferentially organized according to these strata. These results suggest sublayer-specific circuit organization in hippocampal CA1 of the freely-moving macaques that may underlie its role in cognition.

A machine learning toolbox for the analysis of sharp-wave ripples reveal common features across species

The study of sharp-wave ripples (SWRs) has advanced our understanding of memory function, and their alteration in neurological conditions such as epilepsy and Alzheimer's disease is considered a biomarker of dysfunction. SWRs exhibit diverse waveforms and properties that cannot be fully characterized by spectral methods alone. Here, we describe a toolbox of machine learning (ML) models for automatic detection and analysis of SWRs. The ML architectures, which resulted from a crowdsourced hackathon, are able to capture a wealth of SWR features recorded in the dorsal hippocampus of mice. When applied to data from the macaque hippocampus, these models were able to generalize detection and revealed shared SWR properties across species. We hereby provide a user-friendly open-source toolbox for model use and extension, which can help to accelerate and standardize SWR research, lowering the threshold for its adoption in biomedical applications.

Learning of object-in-context sequences in freely-moving macaques

Flexible learning is a hallmark of primate cognition, which arises through interactions with changing environments. Studies of the neural basis for this flexibility are typically limited by laboratory settings that use minimal environmental cues and restrict interactions with the environment, including active sensing and exploration. To address this, we constructed a 3-D enclosure containing touchscreens on its walls, for studying cognition in freely moving macaques. To test flexible learning, two monkeys completed trials consisting of a regular sequence of object selections across four touchscreens. On each screen, the monkeys had to select by touching the sole correct object item ('target') among a set of four items, irrespective of their positions on the screen. Each item was the target on exactly one screen of the sequence, making correct performance conditioned on the spatiotemporal sequence rule across screens. Both monkeys successfully learned multiple 4-item sets (N=14 and 22 sets), totaling over 50 and 80 unique, conditional item-context memoranda, with no indication of capacity limits. The enclosure allowed freedom of movements leading up to and following the touchscreen interactions. To determine whether movement economy changed with learning, we reconstructed 3D position and movement dynamics using markerless tracking software and gyroscopic inertial measurements. Whereas general body positions remained consistent across repeated sequences, fine head movements varied as monkeys learned, within and across sequence sets, demonstrating learning set or "learning to learn". These results demonstrate monkeys' rapid, capacious, and flexible learning within an integrated, multisensory 3-D space. Furthermore, this approach enables the measurement of continuous behavior while ensuring precise experimental control and behavioral repetition of sequences over time. Overall, this approach harmonizes the design features that are needed for electrophysiological studies with tasks that showcase fully situated, flexible cognition.

Circuit dynamics of superficial and deep CA1 pyramidal cells and inhibitory cells in freely moving macaques

Diverse neuron classes in hippocampal CA1 have been identified through the heterogeneity of their cellular/molecular composition. How these classes relate to hippocampal function and the network dynamics that support cognition in primates remains unclear. Here, we report inhibitory functional cell groups in CA1 of freely moving macaques whose diverse response profiles to network states and each other suggest distinct and specific roles in the functional microcircuit of CA1. In addition, pyramidal cells that were grouped by their superficial or deep layer position differed in firing rate, burstiness, and sharp-wave ripple-associated firing. They also showed strata-specific spike-timing interactions with inhibitory cell groups, suggestive of segregated neural populations. Furthermore, ensemble recordings revealed that cell assemblies were preferentially organized according to these strata. These results suggest that hippocampal CA1 in freely moving macaques bears a sublayer-specific circuit organization that may shape its role in cognition.

A machine learning toolbox for the analysis of sharp-wave ripples reveals common waveform features across species

The study of sharp-wave ripples has advanced our understanding of memory function, and their alteration in neurological conditions such as epilepsy is considered a biomarker of dysfunction. Sharp-wave ripples exhibit diverse waveforms and properties that cannot be fully characterized by spectral methods alone. Here, we describe a toolbox of machine-learning models for automatic detection and analysis of these events. The machine-learning architectures, which resulted from a crowdsourced hackathon, are able to capture a wealth of ripple features recorded in the dorsal hippocampus of mice across awake and sleep conditions. When applied to data from the macaque hippocampus, these models are able to generalize detection and reveal shared properties across species. We hereby provide a user-friendly open-source toolbox for model use and extension, which can help to accelerate and standardize analysis of sharp-wave ripples, lowering the threshold for its adoption in biomedical applications.