Over and above frequency: Gamma oscillations as units of neural circuit operations.

Gamma oscillations (∼30-150 Hz) are widespread correlates of neural circuit functions. These network activity patterns have been described across multiple animal species, brain structures, and behaviors, and are usually identified based on their spectral peak frequency. Yet, despite intensive investigation, whether gamma oscillations implement causal mechanisms of specific brain functions or represent a general dynamic mode of neural circuit operation remains unclear. In this perspective, we review recent advances in the study of gamma oscillations toward a deeper understanding of their cellular mechanisms, neural pathways, and functional roles. We discuss that a given gamma rhythm does not per se implement any specific cognitive function but rather constitutes an activity motif reporting the cellular substrates, communication channels, and computational operations underlying information processing in its generating brain circuit. Accordingly, we propose shifting the attention from a frequency-based to a circuit-level definition of gamma oscillations.

Breathing coordinates cortico-hippocampal dynamics in mice during offline states.

Network dynamics have been proposed as a mechanistic substrate for the information transfer across cortical and hippocampal circuits. However, little is known about the mechanisms that synchronize and coordinate these processes across widespread brain regions during offline states. Here we address the hypothesis that breathing acts as an oscillatory pacemaker, persistently coupling distributed brain circuit dynamics. Using large-scale recordings from a number of cortical and subcortical brain regions in behaving mice, we uncover the presence of an intracerebral respiratory corollary discharge, that modulates neural activity across these circuits. During offline states, the respiratory modulation underlies the coupling of hippocampal sharp-wave ripples and cortical DOWN/UP state transitions, which mediates systems memory consolidation. These results highlight breathing, a perennial brain rhythm, as an oscillatory scaffold for the functional coordination of the limbic circuit that supports the segregation and integration of information flow across neuronal networks during offline states.

Phasic oxygen dynamics confounds fast choline-sensitive biosensor signals in the brain of behaving rodents.

Cholinergic fast time-scale modulation of cortical physiology is critical for cognition, but direct local measurement of neuromodulators in vivo is challenging. Choline oxidase (ChOx)-based electrochemical biosensors have been used to capture fast cholinergic signals in behaving animals. However, these transients might be biased by local field potential and O2-evoked enzymatic responses. Using a novel Tetrode-based Amperometric ChOx (TACO) sensor, we performed highly sensitive and selective simultaneous measurement of ChOx activity (COA) and O2. In vitro and in vivo experiments, supported by mathematical modeling, revealed that non-steady-state enzyme responses to O2 give rise to phasic COA dynamics. This mechanism accounts for most of COA transients in the hippocampus, including those following locomotion bouts and sharp-wave/ripples. Our results suggest that it is unfeasible to probe phasic cholinergic signals under most behavioral paradigms with current ChOx biosensors. This confound is generalizable to any oxidase-based biosensor, entailing rigorous controls and new biosensor designs.

Sensory Island Task (SIT): A New Behavioral Paradigm to Study Sensory Perception and Neural Processing in Freely Moving Animals.

A central function of sensory systems is the gathering of information about dynamic interactions with the environment during self-motion. To determine whether modulation of a sensory cue was externally caused or a result of self-motion is fundamental to perceptual invariance and requires the continuous update of sensory processing about recent movements. This process is highly context-dependent and crucial for perceptual performances such as decision-making and sensory object formation. Yet despite its fundamental ecological role, voluntary self-motion is rarely incorporated in perceptual or neurophysiological investigations of sensory processing in animals. Here, we present the Sensory Island Task (SIT), a new freely moving search paradigm to study sensory processing and perception. In SIT, animals explore an open-field arena to find a sensory target relying solely on changes in the presented stimulus, which is controlled by closed-loop position tracking in real-time. Within a few sessions, animals are trained via positive reinforcement to search for a particular area in the arena ("target island"), which triggers the presentation of the target stimulus. The location of the target island is randomized across trials, making the modulated stimulus feature the only informative cue for task completion. Animals report detection of the target stimulus by remaining within the island for a defined time ("sit-time"). Multiple "non-target" islands can be incorporated to test psychometric discrimination and identification performance. We exemplify the suitability of SIT for rodents (Mongolian gerbil, Meriones unguiculatus) and small primates (mouse lemur, Microcebus murinus) and for studying various sensory perceptual performances (auditory frequency discrimination, sound source localization, visual orientation discrimination). Furthermore, we show that pairing SIT with chronic electrophysiological recordings allows revealing neuronal signatures of sensory processing under ecologically relevant conditions during goal-oriented behavior. In conclusion, SIT represents a flexible and easily implementable behavioral paradigm for mammals that combines self-motion and natural exploratory behavior to study sensory sensitivity and decision-making and their underlying neuronal processing.

Switchless Multiplexing of Graphene Active Sensor Arrays for Brain Mapping.

Sensor arrays used to detect electrophysiological signals from the brain are paramount in neuroscience. However, the number of sensors that can be interfaced with macroscopic data acquisition systems currently limits their bandwidth. This bottleneck originates in the fact that, typically, sensors are addressed individually, requiring a connection for each of them. Herein, we present the concept of frequency-division multiplexing (FDM) of neural signals by graphene sensors. We demonstrate the high performance of graphene transistors as mixers to perform amplitude modulation (AM) of neural signals in situ, which is used to transmit multiple signals through a shared metal line. This technology eliminates the need for switches, remarkably simplifying the technical complexity of state-of-the-art multiplexed neural probes. Besides, the scalability of FDM graphene neural probes has been thoroughly evaluated and their sensitivity demonstrated in vivo. Using this technology, we envision a new generation of high-count conformal neural probes for high bandwidth brain machine interfaces.

Distortion-Free Sensing of Neural Activity Using Graphene Transistors.

Graphene solution-gated field-effect transistors (g-SGFETs) are promising sensing devices to transduce electrochemical potential signals in an electrolyte bath. However, distortion mechanisms in g-SGFET, which can affect signals of large amplitude or high frequency, have not been evaluated. Here, a detailed characterization and modeling of the harmonic distortion and non-ideal frequency response in g-SGFETs is presented. This accurate description of the input-output relation of the g-SGFETs allows to define the voltage- and frequency-dependent transfer functions, which can be used to correct distortions in the transduced signals. The effect of signal distortion and its subsequent calibration are shown for different types of electrophysiological signals, spanning from large amplitude and low frequency cortical spreading depression events to low amplitude and high frequency action potentials. The thorough description of the distortion mechanisms presented in this article demonstrates that g-SGFETs can be used as distortion-free signal transducers not only for neural sensing, but also for a broader range of applications in which g-SGFET sensors are used.

Quantitative and Discrete Evolutionary Changes in the Egg-Laying Behavior of Single Drosophila Females.

How a nervous system assembles and coordinates a suite of elementary behavioral steps into a complex behavior is not well understood. While often presented as a stereotyped sequence of events, even extensively studied behaviors such as fly courtship are rarely a strict repetition of the same steps in a predetermined sequence in time. We are focusing on oviposition, the act of laying an egg, in flies of the genus Drosophila to describe the elementary behavioral steps or microbehaviors that a single female fly undertakes prior to and during egg laying. We have analyzed the hierarchy and relationships in time of these microbehaviors in three closely related Drosophila species with divergent egg-laying preferences and uncovered cryptic differences in their behavioral patterns. Using high-speed imaging, we quantified in depth the oviposition behavior of single females of Drosophila suzukii, Drosophila biarmipes and Drosophila melanogaster in a novel behavioral assay. By computing transitions between microbehaviors, we identified a common ethogram structure underlying oviposition of all three species. Quantifying parameters such as relative time spent on a microbehavior and its average duration, however, revealed clear differences between species. In addition, we examined the temporal dynamics and probability of transitions to different microbehaviors relative to a central event of oviposition, ovipositor contact. Although the quantitative analysis highlights behavioral variability across flies, it reveals some interesting trends for each species in the mode of substrate sampling, as well as possible evolutionary differences. Larger datasets derived from automated video annotation will overcome this paucity of data in the future, and use the same framework to reappraise these observed differences. Our study reveals a common architecture to the oviposition ethogram of three Drosophila species, indicating its ancestral state. It also indicates that Drosophila suzukii's behavior departs quantitatively and qualitatively from that of the outgroup species, in line with its known divergent ethology. Together, our results illustrate how a global shift in ethology breaks down in the quantitative reorganization of the elementary steps underlying a complex behavior.

Ratcave: A 3D graphics python package for cognitive psychology experiments.

We present here a free, open source Python 3D graphics library called Ratcave that extends existing Python psychology stimulus software by allowing scientists to load, display, and transform 3D stimuli created in 3D modeling software. This library makes 3D programming intuitive to new users by providing 3D graphics engine concepts (Mesh, Scene, Light, and Camera classes) that can be manipulated using an interface similar to existing 2D stimulus libraries. In addition, the use of modern OpenGL constructs by Ratcave helps scientists create fast, hardware-accelerated dynamic stimuli using the same intuitive high-level, lightweight interface. Because Ratcave supplements, rather than replaces, existing Python stimulus libraries, scientists can continue to use their preferred libraries by simply adding Ratcave graphics to their existing experiments. We hope this tool will be useful both as a stimulus library and as an example of how tightly-focused libraries can add quality to the existing scientific open-source software ecosystem.

Investigating large-scale brain dynamics using field potential recordings: analysis and interpretation.

New technologies to record electrical activity from the brain on a massive scale offer tremendous opportunities for discovery. Electrical measurements of large-scale brain dynamics, termed field potentials, are especially important to understanding and treating the human brain. Here, our goal is to provide best practices on how field potential recordings (electroencephalograms, magnetoencephalograms, electrocorticograms and local field potentials) can be analyzed to identify large-scale brain dynamics, and to highlight critical issues and limitations of interpretation in current work. We focus our discussion of analyses around the broad themes of activation, correlation, communication and coding. We provide recommendations for interpreting the data using forward and inverse models. The forward model describes how field potentials are generated by the activity of populations of neurons. The inverse model describes how to infer the activity of populations of neurons from field potential recordings. A recurring theme is the challenge of understanding how field potentials reflect neuronal population activity given the complexity of the underlying brain systems.

4-Hz oscillations synchronize prefrontal-amygdala circuits during fear behavior.

Fear expression relies on the coordinated activity of prefrontal and amygdala circuits, yet the mechanisms allowing long-range network synchronization during fear remain unknown. Using a combination of extracellular recordings, pharmacological and optogenetic manipulations, we found that freezing, a behavioral expression of fear, temporally coincided with the development of sustained, internally generated 4-Hz oscillations in prefrontal-amygdala circuits. 4-Hz oscillations predict freezing onset and offset and synchronize prefrontal-amygdala circuits. Optogenetic induction of prefrontal 4-Hz oscillations coordinates prefrontal-amygdala activity and elicits fear behavior. These results unravel a sustained oscillatory mechanism mediating prefrontal-amygdala coupling during fear behavior.

Simultaneous measurement of cholinergic tone and neuronal network dynamics in vivo in the rat brain using a novel choline oxidase based electrochemical biosensor.

Acetylcholine (ACh) modulates neuronal network activities implicated in cognition, including theta and gamma oscillations but the mechanisms remain poorly understood. Joint measurements of cholinergic activity and neuronal network dynamics with high spatio-temporal resolution are critical to understand ACh neuromodulation. However, current electrochemical biosensors are not optimized to measure nanomolar cholinergic signals across small regions like hippocampal sub-layers. Here, we report a novel oxidase-based electrochemical biosensor that matches these constraints. The approach is based on measurement of H2O2 generated by choline oxidase (ChOx) in the presence of choline (Ch). The microelectrode design consists of a twisted pair of 50µm diameter Pt/Ir wires (sensor and sentinel), which is scalable, provides high spatial resolution and optimizes common mode rejection. Microelectrode coating with ChOx in chitosan cross-linked with benzoquinone is simple, mechanically robust and provides high sensitivity (324±46nAµM(-1)cm(-2)), a limit of detection of 16nM and a t50 response time of 1.4s. Local field potential (LFP)-related currents dominate high-frequency component of electrochemical recordings in vivo. We significantly improved signal-to-noise-ratio compared to traditional sentinel subtraction by a novel frequency domain common mode rejection procedure that accounts for differential phase and amplitude of LFP-related currents on the two channels. We demonstrate measurements of spontaneous nanomolar Ch fluctuations, on top of which micromolar Ch increases occurred during periods of theta activity in anesthetized rats. Measurements were not affected by physiological O2 changes, in agreement with the low biosensor Km for O2 (2.6µM). Design and performance of the novel biosensor opens the way for multisite recordings of spontaneous cholinergic dynamics in behaving animals.

Neurosharing: large-scale data sets (spike, LFP) recorded from the hippocampal-entorhinal system in behaving rats.

Using silicon-based recording electrodes, we recorded neuronal activity of the dorsal hippocampus and dorsomedial entorhinal cortex from behaving rats. The entorhinal neurons were classified as principal neurons and interneurons based on monosynaptic interactions and wave-shapes. The hippocampal neurons were classified as principal neurons and interneurons based on monosynaptic interactions, wave-shapes and burstiness. The data set contains recordings from 7,736 neurons (6,100 classified as principal neurons, 1,132 as interneurons, and 504 cells that did not clearly fit into either category) obtained during 442 recording sessions from 11 rats (a total of 204.5 hours) while they were engaged in one of eight different behaviours/tasks. Both original and processed data (time stamp of spikes, spike waveforms, result of spike sorting and local field potential) are included, along with metadata of behavioural markers. Community-driven data sharing may offer cross-validation of findings, refinement of interpretations and facilitate discoveries.

Early γ oscillations synchronize developing thalamus and cortex.

During development, formation of topographic maps in sensory cortex requires precise temporal binding in thalamocortical networks. However, the physiological substrate for such synchronization is unknown. We report that early gamma oscillations (EGOs) enable precise spatiotemporal thalamocortical synchronization in the neonatal rat whisker sensory system. Driven by a thalamic gamma oscillator and initially independent of cortical inhibition, EGOs synchronize neurons in a single thalamic barreloid and corresponding cortical barrel and support plasticity at developing thalamocortical synapses. We propose that the multiple replay of sensory input in thalamocortical circuits during EGOs allows thalamic and cortical neurons to be organized into vertical topographic functional units before the development of horizontal binding in adult brain.

The hippocampus: hub of brain network communication for memory.

A complex brain network, centered on the hippocampus, supports episodic memories throughout their lifetimes. Classically, upon memory encoding during active behavior, hippocampal activity is dominated by theta oscillations (6-10Hz). During inactivity, hippocampal neurons burst synchronously, constituting sharp waves, which can propagate to other structures, theoretically supporting memory consolidation. This 'two-stage' model has been updated by new data from high-density electrophysiological recordings in animals that shed light on how information is encoded and exchanged between hippocampus, neocortex and subcortical structures such as the striatum. Cell assemblies (tightly related groups of cells) discharge together and synchronize across brain structures orchestrated by theta, sharp waves and slow oscillations, to encode information. This evolving dynamical schema is key to extending our understanding of memory processes.

Intrinsic circuit organization and theta-gamma oscillation dynamics in the entorhinal cortex of the rat.

A thorough knowledge of the intrinsic circuit properties of the entorhinal cortex (EC) and the temporal dynamics these circuits support is essential for understanding how information is exchanged between the hippocampus and neocortex. Using intracellular and extracellular recordings in the anesthetized rat and anatomical reconstruction of single cells, we found that EC5 and EC2 principal neurons form large axonal networks mainly within their layers, interconnected by the more vertically organized axon trees of EC3 pyramidal cells. Principal cells showed layer-specific unique membrane properties and contributed differentially to theta and gamma oscillations. EC2 principal cells were most strongly phase modulated by EC theta. The multiple gamma oscillators, present in the various EC layers, were temporally coordinated by the phase of theta waves. Putative interneurons in all EC layers fired relatively synchronously within the theta cycle, coinciding with the maximum power of gamma oscillation. The special wiring architecture and unique membrane properties of EC neurons may underlie their behaviorally distinct firing patterns in the waking animal.

Transcranial electric stimulation entrains cortical neuronal populations in rats.

Low intensity electric fields have been suggested to affect the ongoing neuronal activity in vitro and in human studies. However, the physiological mechanism of how weak electrical fields affect and interact with intact brain activity is not well understood. We performed in vivo extracellular and intracellular recordings from the neocortex and hippocampus of anesthetized rats and extracellular recordings in behaving rats. Electric fields were generated by sinusoid patterns at slow frequency (0.8, 1.25 or 1.7 Hz) via electrodes placed on the surface of the skull or the dura. Transcranial electric stimulation (TES) reliably entrained neurons in widespread cortical areas, including the hippocampus. The percentage of TES phase-locked neurons increased with stimulus intensity and depended on the behavioral state of the animal. TES-induced voltage gradient, as low as 1 mV/mm at the recording sites, was sufficient to phase-bias neuronal spiking. Intracellular recordings showed that both spiking and subthreshold activity were under the combined influence of TES forced fields and network activity. We suggest that TES in chronic preparations may be used for experimental and therapeutic control of brain activity.

Distinct representations and theta dynamics in dorsal and ventral hippocampus.

Although anatomical, lesion, and imaging studies of the hippocampus indicate qualitatively different information processing along its septo-temporal axis, physiological mechanisms supporting such distinction are missing. We found fundamental differences between the dorsal (dCA3) and the ventral-most parts (vCA3) of the hippocampus in both environmental representation and temporal dynamics. Discrete place fields of dCA3 neurons evenly covered all parts of the testing environments. In contrast, vCA3 neurons (1) rarely showed continuous two-dimensional place fields, (2) differentiated open and closed arms of a radial maze, and (3) discharged similar firing patterns with respect to the goals, both on multiple arms of a radial maze and during opposite journeys in a zigzag maze. In addition, theta power and the fraction of theta-rhythmic neurons were substantially reduced in the ventral compared with dorsal hippocampus. We hypothesize that the spatial representation in the septo-temporal axis of the hippocampus is progressively decreased. This change is paralleled with a reduction of theta rhythm and an increased representation of nonspatial information.

Theta oscillations provide temporal windows for local circuit computation in the entorhinal-hippocampal loop.

Theta oscillations are believed to play an important role in the coordination of neuronal firing in the entorhinal (EC)-hippocampal system but the underlying mechanisms are not known. We simultaneously recorded from neurons in multiple regions of the EC-hippocampal loop and examined their temporal relationships. Theta-coordinated synchronous spiking of EC neuronal populations predicted the timing of current sinks in target layers in the hippocampus. However, the temporal delays between population activities in successive anatomical stages were longer (typically by a half theta cycle) than expected from axon conduction velocities and passive synaptic integration of feed-forward excitatory inputs. We hypothesize that the temporal windows set by the theta cycles allow for local circuit interactions and thus a considerable degree of computational independence in subdivisions of the EC-hippocampal loop.

Entrainment of neocortical neurons and gamma oscillations by the hippocampal theta rhythm.

Although it has been tacitly assumed that the hippocampus exerts an influence on neocortical networks, the mechanisms of this process are not well understood. We examined whether and how hippocampal theta oscillations affect neocortical assembly patterns by recording populations of single cells and transient gamma oscillations in multiple cortical regions, including the somatosensory area and prefrontal cortex in behaving rats and mice. Laminar analysis of neocortical gamma bursts revealed multiple gamma oscillators of varying frequency and location, which were spatially confined and synchronized local groups of neurons. A significant fraction of putative pyramidal cells and interneurons as well as localized gamma oscillations in all recorded neocortical areas were phase biased by the hippocampal theta rhythm. We hypothesize that temporal coordination of neocortical gamma oscillators by hippocampal theta is a mechanism by which information contained in spatially widespread neocortical assemblies can be synchronously transferred to the associative networks of the hippocampus.

Theta and gamma coordination of hippocampal networks during waking and rapid eye movement sleep.

Rapid eye movement (REM) sleep has been considered a paradoxical state because, despite the high behavioral threshold to arousing perturbations, gross physiological patterns in the forebrain resemble those of waking states. To understand how intrahippocampal networks interact during REM sleep, we used 96 site silicon probes to record from different hippocampal subregions and compared the patterns of activity during waking exploration and REM sleep. Dentate/CA3 theta and gamma synchrony was significantly higher during REM sleep compared with active waking. In contrast, gamma power in CA1 and CA3-CA1 gamma coherence showed significant decreases in REM sleep. Changes in unit firing rhythmicity and unit-field coherence specified the local generation of these patterns. Although these patterns of hippocampal network coordination characterized the more common tonic periods of REM sleep (approximately 95% of total REM), we also detected large phasic bursts of local field potential power in the dentate molecular layer that were accompanied by transient increases in the firing of dentate and CA1 neurons. In contrast to tonic REM periods, phasic REM epochs were characterized by higher theta and gamma synchrony among the dentate, CA3, and CA1 regions. These data suggest enhanced dentate processing, but limited CA3-CA1 coordination during tonic REM sleep. In contrast, phasic bursts of activity during REM sleep may provide windows of opportunity to synchronize the hippocampal trisynaptic loop and increase output to cortical targets. We hypothesize that tonic REM sleep may support off-line mnemonic processing, whereas phasic bursts of activity during REM may promote memory consolidation.