Search

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, being 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 towards 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.

Network dynamics have been proposed as a mechanistic substrate for the information transfer across cortical and hippocampal circuits. During sleep and offline states, synchronous reactivation across these regions underlies the consolidation of memories. However, little is known about the mechanisms that synchronize and coordinate these processes across widespread brain regions. Here we address the hypothesis that breathing acts as an oscillatory pacemaker, persistently coupling distributed brain circuit dynamics. Using large-scale recordings from seven cortical and subcortical brain regions in quiescent and sleeping mice, we identified a novel global mechanism, termed respiratory corollary discharge, that co-modulates neural activity across these circuits. Analysis of inter-regional population activity and optogenetic perturbations revealed that breathing rhythm couples hippocampal sharp-wave ripples and cortical DOWN/UP state transitions by jointly modulating excitability in these circuits. These results highlight breathing, a perennial brain rhythm, as an oscillatory scaffold for the functional coordination of the limbic circuit, supporting the segregation and integration of information flow across neuronal networks during offline states.

Graphene active sensors have demonstrated promising capabilities for the detection of electrophysiological signals in the brain. Their functional properties, together with their flexibility as well as their expected stability and biocompatibility have raised them as a promising building block for large-scale sensing neural interfaces. However, in order to provide reliable tools for neuroscience and biomedical engineering applications, the maturity of this technology must be thoroughly studied. Here, we evaluate the performance of 64-channel graphene sensor arrays in terms of homogeneity, sensitivity and stability using a wireless, quasi-commercial headstage and demonstrate the biocompatibility of epicortical graphene chronic implants. Furthermore, to illustrate the potential of the technology to detect cortical signals from infra-slow to high-gamma frequency bands, we perform proof-of-concept long-term wireless recording in a freely behaving rodent. Our work demonstrates the maturity of the graphene-based technology, which represents a promising candidate for chronic, wide frequency band neural sensing interfaces., This work has been funded by the European Union’s Horizon 2020 research and innovation program under Grant Agreement No. 732032 (BrainCom) and Graphene Flagship Grant Agreements No. 785219 (GrapheneCore2) and 881603 (GrapheneCore3). The ICN2 is supported by the Severo Ochoa Centres of Excellence program, funded by the Spanish Research Agency (AEI, grant no. SEV-2017-0706), and by the CERCA Program/Generalitat de Catalunya. R.G.C. is supported by the International Ph.D Program La Caixa-Severo Ochoa (Programa Internacional de Becas “la Caixa”-Severo Ochoa). This work has made use of the Spanish ICTS Network MICRONANOFABS partially supported by MICINN and the ICTS “NANBIOSIS”, more specifically by the Micro-NanoTechnology Unit of the CIBER in Bioengineering, Biomaterials, and Nanomedicine (CIBER-BBN) at the IMB-CNM. This work is within the project FIS2017-85787-R funded by the “Ministerio de Ciencia, Innovación y Universidades” of Spain, the “Agencia Estatal de Investigación (AEI)”, and the “Fondo Europeo de Desarrollo Regional (FEDER/UE)”. A.S. and G.S. were also supported by Bundesministerium für Bildung und Forschung [grant number 01GQ0440]. R.G.C. acknowledges that this work has been done in the framework of the Ph.D in Electrical and Telecommunication Engineering at the Universitat Autònoma de Barcelona.

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.

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., This work has been funded by the European Union’s Horizon 2020 research and innovation programme under Grant Agreement 732032 (BrainCom), Grant Agreement 85219 and 881603 (Graphene Flagship). The ICN2 is supported by the Severo Ochoa Centres of Excellence programme, funded by the Spanish Research Agency (AEI, Grant SEV-2017-0706), and by the CERCA Programme/Generalitat de Catalunya. R.G.C. and N.S. acknowledge that this work has been done in the framework of the Ph.D. in Electrical and Telecommunication Engineering at the Universitat Autonoma de Barcelona. R.G.C is supported by the International Ph.D. Programme La Caixa - Severo Ochoa (Programa Internacional de Becas “la Caixa”-Severo Ochoa). This work has made use of the Spanish ICTS Network MICRONANOFABS partially supported by MICINN and the ICTS “NANBIOSIS”, more specifically by the Micro-NanoTechnology Unit of the CIBER in Bioengineering, Biomaterials, and Nanomedicine (CIBER-BBN) at the IMB-CNM. This work is within the project 2DTecBio (FIS2017-85787-R) funded by the “Ministerio de Ciencia, Innovacion y Universidades” of Spain, the “Agencia Estatal de Investigacion (AEI)”, and the “Fondo Europeo de Desarrollo Regional (FEDER/UE)” and has received funding from Generalitat de Cataluña 2017 SGR 1426.

Altres ajuts: this work has made use of the Spanish ICTS Network MICRONANOFABS partially supported by MICINN and the ICTS 'NANBIOSIS', more specifically by the Micro-NanoTechnology Unit of the CIBER in Bioengineering, Biomaterials and Nanomedicine (CIBERBBN) at the IMB-CNM. Electrocorticography (ECoG) is a well-established technique to monitor electrophysiological activity from the surface of the brain and has proved crucial for the current generation of neural prostheses and brain-computer interfaces. However, existing ECoG technologies still fail to provide the resolution necessary to accurately map highly localized activity across large brain areas, due to the rapidly increasing size of connector footprint with sensor count. This work demonstrates the use of a flexible array of graphene solution-gated field-effect transistors (gSGFET), exploring the concept of multiplexed readout using an external switching matrix. This approach does not only allow for an increased sensor count, but due to the use of active sensing devices (i.e. transistors) over microelectrodes it makes additional buffer transistors redundant, which drastically eases the complexity of device fabrication on flexible substrates. The presented results pave the way for upscaling the gSGFET technology towards large-scale, high-density μECoG-arrays, eventually capable of resolving neural activity down to a single neuron level, while simultaneously mapping large brain regions.

The advent of implantable active dense CMOS neural probes opened a new era for electrophysiology in neuroscience. These single shank electrode arrays, and the emerging tailored analysis tools, provide for the first time to neuroscientists the neurotechnology means to spatiotemporally resolve the activity of hundreds of different single-neurons in multiple vertically aligned brain structures. However, while these unprecedented experimental capabilities to study columnar brain properties are a big leap forward in neuroscience, there is the need to spatially distribute electrodes also horizontally. Closely spacing and consistently placing in well-defined geometrical arrangement multiple isolated single-shank probes is methodologically and economically impractical. Here, we present the first high-density CMOS neural probe with multiple shanks integrating thousand’s of closely spaced and simultaneously recording microelectrodes to map neural activity across 2D lattice. Taking advantage from the high-modularity of our electrode-pixels-based SiNAPS technology, we realized a four shanks active dense probe with 256 electrode-pixels/shank and a pitch of 28 µm, for a total of 1024 simultaneously recording channels. The achieved performances allow for full-band, whole-array read-outs at 25 kHz/channel, show a measured input referred noise in the action potential band (300-7000 Hz) of 6.5 ± 2.1µVRMS, and a power consumption µW/electrode-pixel. Preliminary recordings in awake behaving mice demonstrated the capability of multi-shanks SiNAPS probes to simultaneously record neural activity (both LFPs and spikes) from a brain area >6 mm2, spanning cortical, hippocampal and thalamic regions. High-density 2D array enables combining large population unit recording across distributed networks with precise intra- and interlaminar/nuclear mapping of the oscillatory dynamics. These results pave the way to a new generation of high-density and extremely compact multi-shanks CMOS-probes with tunable layouts for electrophysiological mapping of brain activity at the single-neurons resolution.

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. Electronic supplementary material The online version of this article (10.3758/s13428-019-01245-x) contains supplementary material, which is available to authorized users.

The coordinated activity between remote brain regions underlies cognition and memory function. Althoughneuronal oscillations have been proposed as a mechanistic substrate for the coordination of information trans-fer and memory consolidation during sleep, little is known about the mechanisms that support the widespreadsynchronization of brain regions and the relationship of neuronal dynamics with other bodily rhythms, such asbreathing. Here we address this question using large-scale recordings from a number of structures, includingthe medial prefrontal cortex, hippocampus, thalamus, amygdala and nucleus accumbens in mice. We identifya dual mechanism of respiratory entrainment, in the form of an intracerebral corollary discharge that actsjointly with an olfactory reafference to coordinate limbic network dynamics, such as hippocampal ripplesand cortical UP and DOWN states, involved in memory consolidation. These results highlight breathing, aperennial rhythmic input to the brain, as an oscillatory scaffold for the functional coordination of the limbiccircuit, enabling the segregation and integration of information flow across neuronal network

The coordinated activity between remote brain regions underlies cognition and memory function. Although neuronal oscillations have been proposed as a mechanistic substrate for the coordination of information transfer and memory consolidation during sleep, little is known about the mechanisms that support the widespread synchronization of brain regions and the relationship of neuronal dynamics with other bodily rhythms, such as breathing. Here we address this question using large-scale recordings from a number of structures, including the medial prefrontal cortex, hippocampus, thalamus, amygdala and nucleus accumbens in mice. We identify a dual mechanism of respiratory entrainment, in the form of an intracerebral corollary discharge that acts jointly with an olfactory reafference to coordinate limbic network dynamics, such as hippocampal ripples and cortical UP and DOWN states, involved in memory consolidation. These results highlight breathing, a perennial rhythmic input to the brain, as an oscillatory scaffold for the functional coordination of the limbic circuit, enabling the segregation and integration of information flow across neuronal networks.

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 H 2 O 2 generated by choline oxidase (ChOx) in the presence of choline (Ch). The microelectrode design consists of a twisted pair of 50 µm 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±46 nA µM −1 cm −2 ), a limit of detection of 16 nM and a t 50 response time of 1.4 s. 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 O 2 changes, in agreement with the low biosensor Km for O 2 (2.6 µM). Design and performance of the novel biosensor opens the way for multisite recordings of spontaneous cholinergic dynamics in behaving animals.

Spatial navigation, active sensing, and most cognitive functions rely on a tight link between motor output and sensory input. Virtual reality (VR) systems simulate the sensorimotor loop, allowing flexible manipulation of enriched sensory input. Conventional rodent VR systems provide 3D visual cues linked to restrained locomotion on a treadmill, leading to a mismatch between visual and most other sensory inputs, sensory-motor conflicts, as well as restricted naturalistic behavior. To rectify these limitations, we developed a VR system (ratCAVE) that provides realistic and low-latency visual feedback directly to head movements of completely unrestrained rodents. Immersed in this VR system, rats displayed naturalistic behavior by spontaneously interacting with and hugging virtual walls, exploring virtual objects, and avoiding virtual cliffs. We further illustrate the effect of ratCAVE-VR manipulation on hippocampal place fields. The newly-developed methodology enables a wide range of experiments involving flexible manipulation of visual feedback in freely-moving behaving animals.

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.

International audience; 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.

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.

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 report that freezing, a behavioural expression of fear, temporally coincides with the development of sustained, internally generated 4 Hz oscillations within 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 behaviour. These results unravel a novel sustained oscillatory mechanism mediating prefrontal-amygdala coupling during fear behaviour.

Two thin-film microelectrode arrays with integrated circuitry have been developed for extracellular neural recording in behaving animals. An eight-site probe for simultaneous neural recording and stimulation has been designed that includes on-chip amplifiers that can be individually bypassed, allowing direct access to the iridium sites for electrical stimulation. The on-probe amplifiers have a gain of 38.9 dB, an upper-cutoff frequency of 9.9 kHz, and an input-referred noise of 9.2 /spl mu/V /sub rms/ integrated from 100 Hz to 10 kHz. The low-frequency cutoff of the amplifier is tunable to allow the recording of field potentials and minimize stimulus artifact. The amplifier consumes 68 /spl mu/W from /spl plusmn/1.5 V supplies and occupies 0.177 mm/sup 2/ in 3 /spl mu/m features. In vivo recordings have shown that the preamplifiers can record single-unit activity 1 ms after the onset of stimulation on sites as close as 20 /spl mu/m to the stimulating electrode. A second neural recording array has been developed which multiplexes 32 neural signals onto four output data leads. Providing gain on this array eliminates the need for bulky head-mounted circuitry and reduces motion artifacts. The time-division multiplexing circuitry has crosstalk between consecutive channels of less than 6% at a sample rate of 20 kHz per channel. Amplified, time-division-multiplexed multichannel neural recording allows the large-scale recording of neuronal activity in freely behaving small animals with minimum number of interconnect leads.

The stoichiometry and spectral properties of [Ni(4-Etpy)4(NCS)2]⋅nG clathrates have been studied where n = 2 for G = 1-BrN (N = naphthalene), n = 1 or 2 for G = 1-MeN, and n = 0.5 for 2-MeN and 2-BrN. The complexes under study show electronic absorption spectra typical of an octahedral environment of the Ni(II) central atom. The differences found in IR spectra for the ν (C≡N) and ν(Ni–-NNCS) vibrations are discussed. The crystal structure of [Ni(4-Etpy)4(NCS)2]⋅1-MeN was determined by X-ray diffraction and refined to R = 0.0586. Discrete non-centrosymmetric [Ni(4-Etpy)4(NCS)2] molecules form layers of a host structure and the space between the layers is occupied by 1-MeN. The relationship between interatomic distances in the host complex of similar clathrates are discussed.

International audience; 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.

Low intensity electric fields have been suggested to affect the ongoing neuronal activityin vitroand in human studies. However, the physiological mechanism of how weak electrical fields affect and interact with intact brain activity is not well understood. We performedin vivoextracellular 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.

Structured interactions among distributed neurons serve as building blocks for systems-level functions. This article describes the most prominent neurophysiological patterns observed within the hippocampus and their relation to neocortical patterns. Evidence is presented that sensory related activation of hippocampal neurons during awake experience is both iterated during sleep and that this iteration supports memory. Understanding the mechanism that govern ensemble activity in association with structured patterns and the differences between patterns during awake experience and sleep states should provide formative insight to a neural systems-level understanding of memory and cognition.

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.

SummaryAlthough 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.

The phase of spikes of hippocampal pyramidal cells relative to the local field θ oscillation shifts forward (“phase precession”) over a full θ cycle as the animal crosses the cell's receptive field (“place field”). The linear relationship between the phase of the spikes and the travel distance within the place field is independent of the animal's running speed. This invariance of the phase–distance relationship is likely to be important for coordinated activity of hippocampal cells and space coding, yet the mechanism responsible for it is not known. Here we show that at faster running speeds place cells are active for fewer θ cycles but oscillate at a higher frequency and emit more spikes per cycle. As a result, the phase shift of spikes from cycle to cycle (i.e., temporal precession slope) is faster, yet spatial-phase precession stays unchanged. Interneurons can also show transient-phase precession and contribute to the formation of coherently precessing assemblies. We hypothesize that the speed-correlated acceleration of place cell assembly oscillation is responsible for the phase–distance invariance of hippocampal place cells.

Both the thalamocortical and limbic systems generate a variety of brain state-dependent rhythms but the relationship between the oscillatory families is not well understood. Transfer of information across structures can be controlled by the offset oscillations. We suggest that slow oscillation of the neocortex, which was discovered by Mircea Steriade, temporally coordinates the self-organized oscillations in the neocortex, entorhinal cortex, subiculum and hippocampus. Transient coupling between rhythms can guide bidirectional information transfer among these structures and might serve to consolidate memory traces.

International audience; Sensorimotor coordination emerges early in development. The maturation period is characterized by the establishment of somatotopic cortical maps, the emergence of long-range cortical connections, heightened experience-dependent plasticity and spontaneous uncoordinated skeletal movement. How these various processes cooperate to allow the somatosensory system to form a three-dimensional representation of the body is not known. In the visual system, interactions between spontaneous network patterns and afferent activity have been suggested to be vital for normal development. Although several intrinsic cortical patterns of correlated neuronal activity have been described in developing somatosensory cortex in vitro, the in vivo patterns in the critical developmental period and the influence of physiological sensory inputs on these patterns remain unknown. We report here that in the intact somatosensory cortex of the newborn rat in vivo, spatially confined spindle bursts represent the first and only organized network pattern. The localized spindles are selectively triggered in a somatotopic manner by spontaneous muscle twitches, motor patterns analogous to human fetal movements. We suggest that the interaction between movement-triggered sensory feedback signals and self-organized spindle oscillations shapes the formation of cortical connections required for sensorimotor coordination.

Parallel recording of neuronal activity in the behaving animal is a prerequisite for our understanding of neuronal representation and storage of information. Here we describe the development of micro-machined silicon microelectrode arrays for unit and local field recordings. The two-dimensional probes with 96 or 64 recording sites provided high-density recording of unit and field activity with minimal tissue displacement or damage. The on-chip active circuit eliminated movement and other artifacts and greatly reduced the weight of the headgear. The precise geometry of the recording tips allowed for the estimation of the spatial location of the recorded neurons and for high-resolution estimation of extracellular current source density. Action potentials could be simultaneously recorded from the soma and dendrites of the same neurons. Silicon technology is a promising approach for high-density, high-resolution sampling of neuronal activity in both basic research and prosthetic devices.

Both neocortical and hippocampal networks organize the firing patterns of their neurons by prominent oscillations during sleep, but the functional role of these rhythms is not well understood. Here, we show a robust correlation of neuronal discharges between the somatosensory cortex and hippocampus on both slow and fine time scales in the mouse and rat. Neuronal bursts in deep cortical layers, associated with sleep spindles and delta waves/slow rhythm, effectively triggered hippocampal discharges related to fast (ripple) oscillations. We hypothesize that oscillation-mediated temporal links coordinate specific information transfer between neocortical and hippocampal cell assemblies. Such a neocortical–hippocampal interplay may be important for memory consolidation.

An intrinsic factor analysis (factorization) framework for information redundancy elimination by means of Hebbian learning in sparsely encoded Hopfield-like neural networks is presented. Computer simulations revealed that the information redundancy, which can be eliminated by factorization, is sparseness dependent. Due to strong similarity of Hopfield-like neural networks to that of CA3 field of the hippocampus and following Marr's ideas we propose a physiological mechanism for redundancy elimination (fractorization) in CA3 and further replay to neocortex in the form of "classificatory units".

SummaryBrain systems communicate by means of neuronal oscillations at multiple temporal and spatial scales. In anesthetized rats, we find that neocortical “slow” oscillation engages neurons in prefrontal, somatosensory, entorhinal, and subicular cortices into synchronous transitions between UP and DOWN states, with a corresponding bimodal distribution of their membrane potential. The membrane potential of hippocampal granule cells and CA3 and CA1 pyramidal cells lacked bimodality, yet it was influenced by the slow oscillation in a region-specific manner. Furthermore, in both anesthetized and naturally sleeping rats, the cortical UP states resulted in increased activity of dentate and most CA1 neurons, as well as the highest probability of ripple events. Yet, the CA3-CA1 network could self-organize into gamma bursts and occasional ripples during the DOWN state. Thus, neo/paleocortical and hippocampal networks periodically reset, self-organize, and temporally coordinate their cell assemblies via the slow oscillation.

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.

SummaryTheta 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.

Graphene active sensors have demonstrated promising capabilities for the detection of electrophysiological signals in the brain. Their functional properties, together with their flexibility as well as their expected stability and biocompatibility have raised them as a promising building block for large-scale sensing neural interfaces. However, in order to provide reliable tools for neuroscience and biomedical engineering applications, the maturity of this technology must be thoroughly studied. Here, we evaluate the performance of 64-channel graphene sensor arrays in terms of homogeneity, sensitivity and stability using a wireless, quasi-commercial headstage and demonstrate the biocompatibility of epicortical graphene chronic implants. Furthermore, to illustrate the potential of the technology to detect cortical signals from infra-slow to high-gamma frequency bands, we perform proof-of-concept long-term wireless recording in a freely behaving rodent. Our work demonstrates the maturity of the graphene-based technology, which represents a promising candidate for chronic, wide frequency band neural sensing interfaces.