Long Term Recordings with Immobile Silicon Probes in the Mouse Cortex

Temporal coding carries more stable cortical visual representations than firing rate over time

The brain's ability to stably represent recurring visual scenes is crucial for behavior. Previous studies have used slow dynamic (1-5 seconds) rate code measurements to study visual tuning, revealing varying degrees of gradual activity changes over time or "representational drifts." However, it remains unclear if there is an underlying neural code that maintains the encoding of information stable over time. In this study, we extracted structures in fast (tens of milliseconds) temporal responses and explored the role of such temporal codes in supporting the stability of visual representations. We tracked the spiking activity of the same visual cortical populations in male mice for 15 consecutive days using custom-developed, large-scale, ultraflexible electrode arrays. Across various types of stimuli, we found that neurons exhibited varying degrees of day-to-day stability in their firing rate-based tuning. The across day stability correlated with tuning reliability. Notably, accounting for spiking temporal dynamics increased single neuron tuning stability, especially for less reliable neurons. Temporal coding further improved population representation discriminability and decoding accuracy. The stability of temporal codes was more correlated with network functional connectivity than rate coding. These results show that temporal coding is crucial for stably encoding sensory stimuli, suggesting its significant role in ensuring consistent sensory experiences.

Tracking neurons across days with high-density probes

Neural activity spans multiple time scales, from milliseconds to months. Its evolution can be recorded with chronic high-density arrays such as Neuropixels probes, which can measure each spike at tens of sites and record hundreds of neurons. These probes produce vast amounts of data that require different approaches for tracking neurons across recordings. Here, to meet this need, we developed UnitMatch, a pipeline that operates after spike sorting, based only on each unit's average spike waveform. We tested UnitMatch in Neuropixels recordings from the mouse brain, where it tracked neurons across weeks. Across the brain, neurons had distinctive inter-spike interval distributions. Their correlations with other neurons remained stable over weeks. In the visual cortex, the neurons' selectivity for visual stimuli remained similarly stable. In the striatum, however, neuronal responses changed across days during learning of a task. UnitMatch is thus a promising tool to reveal both invariance and plasticity in neural activity across days.

An adaptable, reusable, and light implant for chronic Neuropixels probes

Electrophysiology has proven invaluable to record neural activity, and the development of Neuropixels probes dramatically increased the number of recorded neurons. These probes are often implanted acutely, but acute recordings cannot be performed in freely moving animals and the recorded neurons cannot be tracked across days. To study key behaviors such as navigation, learning, and memory formation, the probes must be implanted chronically. An ideal chronic implant should (1) allow stable recordings of neurons for weeks; (2) allow reuse of the probes after explantation; (3) be light enough for use in mice. Here, we present the 'Apollo Implant', an open-source and editable device that meets these criteria and accommodates up to two Neuropixels 1.0 or 2.0 probes. The implant comprises a 'payload' module which is attached to the probe and is recoverable, and a 'docking' module which is cemented to the skull. The design is adjustable, making it easy to change the distance between probes, the angle of insertion, and the depth of insertion. We tested the implant across eight labs in head-fixed mice, freely moving mice, and freely moving rats. The number of neurons recorded across days was stable, even after repeated implantations of the same probe. The Apollo implant provides an inexpensive, lightweight, and flexible solution for reusable chronic Neuropixels recordings.

Overwriting an instinct: Visual cortex instructs learning to suppress fear responses

Fast instinctive responses to environmental stimuli can be crucial for survival but are not always optimal. Animals can adapt their behavior and suppress instinctive reactions, but the neural pathways mediating such ethologically relevant forms of learning remain unclear. We found that posterolateral higher visual areas (plHVAs) are crucial for learning to suppress escapes from innate visual threats through a top-down pathway to the ventrolateral geniculate nucleus (vLGN). plHVAs are no longer necessary after learning; instead, the learned behavior relies on plasticity within vLGN populations that exert inhibitory control over escape responses. vLGN neurons receiving input from plHVAs enhance their responses to visual threat stimuli during learning through endocannabinoid-mediated long-term suppression of their inhibitory inputs. We thus reveal the detailed circuit, cellular, and synaptic mechanisms underlying experience-dependent suppression of fear responses.

Population imaging of internal state circuits relevant to psychiatric disease: a review

Internal states involve brain-wide changes that subserve coordinated behavioral and physiological responses for adaptation to changing environments and body states. Investigations of single neurons or small populations have yielded exciting discoveries for the field of neuroscience, but it has been increasingly clear that the encoding of internal states involves the simultaneous representation of multiple different variables in distributed neural ensembles. Thus, an understanding of the representation and regulation of internal states requires capturing large population activity and benefits from approaches that allow for parsing intermingled, genetically defined cell populations. We will explain imaging technologies that permit recording from large populations of single neurons in rodents and the unique capabilities of these technologies in comparison to electrophysiological methods. We will focus on findings for appetitive and aversive states given their high relevance to a wide range of psychiatric disorders and briefly explain how these approaches have been applied to models of psychiatric disease in rodents. We discuss challenges for studying internal states which must be addressed with future studies as well as the therapeutic implications of findings from rodents for improving treatments for psychiatric diseases.

Microinstrumentation for Brain Organoids

Brain organoids are three-dimensional aggregates of self-organized differentiated stem cells that mimic the structure and function of human brain regions. Organoids bridge the gaps between conventional drug screening models such as planar mammalian cell culture, animal studies, and clinical trials. They can revolutionize the fields of developmental biology, neuroscience, toxicology, and computer engineering. Conventional microinstrumentation for conventional cellular engineering, such as planar microfluidic chips; microelectrode arrays (MEAs); and optical, magnetic, and acoustic techniques, has limitations when applied to three-dimensional (3D) organoids, primarily due to their limits with inherently two-dimensional geometry and interfacing. Hence, there is an urgent need to develop new instrumentation compatible with live cell culture techniques and with scalable 3D formats relevant to organoids. This review discusses conventional planar approaches and emerging 3D microinstrumentation necessary for advanced organoid-machine interfaces. Specifically, this article surveys recently developed microinstrumentation, including 3D printed and curved microfluidics, 3D and fast-scan optical techniques, buckling and self-folding MEAs, 3D interfaces for electrochemical measurements, and 3D spatially controllable magnetic and acoustic technologies relevant to two-way information transfer with brain organoids. This article highlights key challenges that must be addressed for robust organoid culture and reliable 3D spatiotemporal information transfer.

Planar amorphous silicon carbide microelectrode arrays for chronic recording in rat motor cortex

Chronic implantation of intracortical microelectrode arrays (MEAs) capable of recording from individual neurons can be used for the development of brain-machine interfaces. However, these devices show reduced recording capabilities under chronic conditions due, at least in part, to the brain's foreign body response (FBR). This creates a need for MEAs that can minimize the FBR to possibly enable long-term recording. A potential approach to reduce the FBR is the use of MEAs with reduced cross-sectional geometries. Here, we fabricated 4-shank amorphous silicon carbide (a-SiC) MEAs and implanted them into the motor cortex of seven female Sprague-Dawley rats. Each a-SiC MEA shank was 8 μm thick by 20 μm wide and had sixteen sputtered iridium oxide film (SIROF) electrodes (4 per shank). A-SiC was chosen as the fabrication base for its high chemical stability, good electrical insulation properties, and amenability to thin film fabrication. Electrochemical analysis and neural recordings were performed weekly for 4 months. MEAs were characterized pre-implantation in buffered saline and in vivo using electrochemical impedance spectroscopy and cyclic voltammetry at 50 mV/s and 50,000 mV/s. Neural recordings were analyzed for single unit activity. At the end of the study, animals were sacrificed for immunohistochemical analysis. We observed statistically significant, but small, increases in 1 and 30 kHz impedance values and 50,000 mV/s charge storage capacity over the 16-week implantation period. Slow sweep 50 mV/s CV and 1 Hz impedance did not significantly change over time. Impedance values increased from 11.6 MΩ to 13.5 MΩ at 1 Hz, 1.2 MΩ-2.9 MΩ at 1 kHz, and 0.11 MΩ-0.13 MΩ at 30 kHz over 16 weeks. The median charge storage capacity of the implanted electrodes at 50 mV/s was 58.1 mC/cm2 on week 1 and 55.9 mC/cm2 on week 16, and at 50,000 mV/s, 4.27 mC/cm2 on week 1 and 5.93 mC/cm2 on week 16. Devices were able to record neural activity from 92% of all active channels at the beginning of the study, At the study endpoint, a-SiC devices were still recording single-unit activity on 51% of electrochemically active electrode channels. In addition, we observed that the signal-to-noise ratio experienced a small decline of -0.19 per week. We also classified observed units as fast and slow repolarizing based on the trough-to-peak time. Although the overall presence of single units declined, fast and slow repolarizing units declined at a similar rate. At recording electrode depth, immunohistochemistry showed minimal tissue response to the a-SiC devices, as indicated by statistically insignificant differences in activated glial cell response between implanted brains slices and contralateral sham slices at 150 μm away from the implant location, as evidenced by GFAP staining. NeuN staining revealed the presence of neuronal cell bodies close to the implantation site, again statistically not different from a contralateral sham slice. These results warrant further investigation of a-SiC MEAs for future long-term implantation neural recording studies.

Large scale, simultaneous, chronic neural recordings from multiple brain areas

Understanding how brain activity is related to animal behavior requires measuring multi-area interactions on multiple timescales. However, methods to perform chronic, simultaneous recordings of neural activity from many brain areas are lacking. Here, we introduce a novel approach for independent chronic probe implantation that enables flexible, simultaneous interrogation of neural activity from many brain regions during head restrained or freely moving behavior. The approach, that we called indie (independent dovetail implants for electrophysiology), enables repeated retrieval and reimplantation of probes. The chronic implantation approach can be combined with other modalities such as skull clearing for cortex wide access and optogenetics with optic fibers. Using this approach, we implanted 6 probes chronically in one hemisphere of the mouse brain. The implant is lightweight, allows flexible targeting with different angles, and offers enhanced stability. Our approach broadens the applications of chronic recording while retaining its main advantages over acute recordings (superior stability, longitudinal monitoring of activity and freely moving interrogations) and provides an appealing venue to study processes not accessible by acute methods, such as the neural substrate of learning across multiple areas.

Impact of Impedance Levels on Recording Quality in Flexible Neural Probes

Flexible neural probes are attractive emerging technologies for brain recording because they can effectively record signals with minimal risk of brain damage. Reducing the electrode impedance of the probe before recording is a common practice of many researchers. However, studies investigating the impact of low impedance levels on high-quality recordings using flexible neural probes are lacking. In this study, we electrodeposited Pt onto a commercial flexible polyimide neural probe and investigated the relationship between the impedance level and the recording quality. The probe was inserted into the brains of anesthetized mice. The electrical signals of neurons in the brain, specifically the ventral posteromedial nucleus of the thalamus, were recorded at impedance levels of 50, 250, 500 and 1000 kΩ at 1 kHz. The study results demonstrated that as the impedance decreased, the quality of the signal recordings did not consistently improve. This suggests that extreme lowering of the impedance may not always be advantageous in the context of flexible neural probes.

Lifetime engineering of bioelectronic implants with mechanically reliable thin film encapsulations

While the importance of thin form factor and mechanical tissue biocompatibility has been made clear for next generation bioelectronic implants, material systems meeting these criteria still have not demonstrated sufficient long-term durability. This review provides an update on the materials used in modern bioelectronic implants as substrates and protective encapsulations, with a particular focus on flexible and conformable devices. We review how thin film encapsulations are known to fail due to mechanical stresses and environmental surroundings under processing and operating conditions. This information is then reflected in recommending state-of-the-art encapsulation strategies for designing mechanically reliable thin film bioelectronic interfaces. Finally, we assess the methods used to evaluate novel bioelectronic implant devices and the current state of their longevity based on encapsulation and substrate materials. We also provide insights for future testing to engineer long-lived bioelectronic implants more effectively and to make implantable bioelectronics a viable option for chronic diseases in accordance with each patient's therapeutic timescale.

Brain-machine interface learning is facilitated by specific patterning of distributed cortical feedback

Neuroprosthetics offer great hope for motor-impaired patients. One obstacle is that fine motor control requires near-instantaneous, rich somatosensory feedback. Such distributed feedback may be recreated in a brain-machine interface using distributed artificial stimulation across the cortical surface. Here, we hypothesized that neuronal stimulation must be contiguous in its spatiotemporal dynamics to be efficiently integrated by sensorimotor circuits. Using a closed-loop brain-machine interface, we trained head-fixed mice to control a virtual cursor by modulating the activity of motor cortex neurons. We provided artificial feedback in real time with distributed optogenetic stimulation patterns in the primary somatosensory cortex. Mice developed a specific motor strategy and succeeded to learn the task only when the optogenetic feedback pattern was spatially and temporally contiguous while it moved across the topography of the somatosensory cortex. These results reveal spatiotemporal properties of the sensorimotor cortical integration that set constraints on the design of neuroprosthetics.

Electrophysiology of Laminar Cortical Activity in the Common Marmoset

The marmoset monkey provides an ideal model for examining laminar cortical circuits due to its smooth cortical surface, which facilitates recordings with linear arrays. The marmoset has recently grown in popularity due to its similar neural functional organization to other primates and its technical advantages for recording and imaging. However, neurophysiology in this model poses some unique challenges due to the small size and lack of gyri as anatomical landmarks. Using custom-built micro-drives, researchers can manipulate linear array placement to sub-millimeter precision and reliably record at the same retinotopically targeted location across recording days. This protocol describes the step-by-step construction of the micro-drive positioning system and the neurophysiological recording technique with silicon linear electrode arrays. With precise control of electrode placement across recording sessions, researchers can easily traverse the cortex to identify areas of interest based on their retinotopic organization and the tuning properties of the recorded neurons. Further, using this laminar array electrode system, it is possible to apply a current source density analysis (CSD) to determine the recording depth of individual neurons. This protocol also demonstrates examples of laminar recordings, including spike waveforms isolated in Kilosort, which span multiple channels on the arrays.

Translating Pathological Brain Activity Primers in Parkinson's Disease Research

Translational experimental approaches that help us better trace Parkinson's disease (PD) pathophysiological mechanisms leading to new therapeutic targets are urgently needed. In this article, we review recent experimental and clinical studies addressing abnormal neuronal activity and pathological network oscillations, as well as their underlying mechanisms and modulation. Our aim is to enhance our knowledge about the progression of Parkinson's disease pathology and the timing of its symptom's manifestation. Here, we present mechanistic insights relevant for the generation of aberrant oscillatory activity within the cortico-basal ganglia circuits. We summarize recent achievements extrapolated from available PD animal models, discuss their advantages and limitations, debate on their differential applicability, and suggest approaches for transferring knowledge on disease pathology into future research and clinical applications.

Multilayer Arrays for Neurotechnology Applications (MANTA): Chronically Stable Thin-Film Intracortical Implants

Flexible implantable neurointerfaces show great promise in addressing one of the major challenges of implantable neurotechnology, namely the loss of signal connected to unfavorable probe tissue interaction. The authors here show how multilayer polyimide probes allow high-density intracortical recordings to be combined with a reliable long-term stable tissue interface, thereby progressing toward chronic stability of implantable neurotechnology. The probes could record 10-60 single units over 5 months with a consistent peak-to-peak voltage at dimensions that ensure robust handling and insulation longevity. Probes that remain in intimate contact with the signaling tissue over months to years are a game changer for neuroscience and, importantly, open up for broader clinical translation of systems relying on neurotechnology to interface the human brain.

Multi-area recordings and optogenetics in the awake, behaving marmoset

The common marmoset has emerged as a key model in neuroscience. Marmosets are small in size, show great potential for genetic modification and exhibit complex behaviors. Thus, it is necessary to develop technology that enables monitoring and manipulation of the underlying neural circuits. Here, we describe a novel approach to record and optogenetically manipulate neural activity in awake, behaving marmosets. Our design utilizes a light-weight, 3D printed titanium chamber that can house several high-density silicon probes for semi-chronic recordings, while enabling simultaneous optogenetic stimulation. We demonstrate the application of our method in male marmosets by recording multi- and single-unit data from areas V1 and V6 with 192 channels simultaneously, and show that optogenetic activation of excitatory neurons in area V6 can influence behavior in a detection task. This method may enable future studies to investigate the neural basis of perception and behavior in the marmoset.

Behavioral origin of sound-evoked activity in mouse visual cortex

Sensory cortices can be affected by stimuli of multiple modalities and are thus increasingly thought to be multisensory. For instance, primary visual cortex (V1) is influenced not only by images but also by sounds. Here we show that the activity evoked by sounds in V1, measured with Neuropixels probes, is stereotyped across neurons and even across mice. It is independent of projections from auditory cortex and resembles activity evoked in the hippocampal formation, which receives little direct auditory input. Its low-dimensional nature starkly contrasts the high-dimensional code that V1 uses to represent images. Furthermore, this sound-evoked activity can be precisely predicted by small body movements that are elicited by each sound and are stereotyped across trials and mice. Thus, neural activity that is apparently multisensory may simply arise from low-dimensional signals associated with internal state and behavior.

Learning in a closed-loop brain-machine interface with distributed optogenetic cortical feedback

Objective.Distributed microstimulations at the cortical surface can efficiently deliver feedback to a subject during the manipulation of a prosthesis through a brain-machine interface (BMI). Such feedback can convey vast amounts of information to the prosthesis user and may be key to obtain an accurate control and embodiment of the prosthesis. However, so far little is known of the physiological constraints on the decoding of such patterns. Here, we aimed to test a rotary optogenetic feedback that was designed to encode efficiently the 360° movements of the robotic actuators used in prosthetics. We sought to assess its use by mice that controlled a prosthesis joint through a closed-loop BMI.Approach.We tested the ability of mice to optimize the trajectory of a virtual prosthesis joint in order to solve a rewarded reaching task. They could control the speed of the joint by modulating the activity of individual neurons in the primary motor cortex. During the task, the patterned optogenetic stimulation projected on the primary somatosensory cortex continuously delivered information to the mouse about the position of the joint.Main results.We showed that mice are able to exploit the continuous, rotating cortical feedback in the active behaving context of the task. Mice achieved better control than in the absence of feedback by detecting reward opportunities more often, and also by moving the joint faster towards the reward angular zone, and by maintaining it longer in the reward zone. Mice controlling acceleration rather than speed of the joint failed to improve motor control.Significance.These findings suggest that in the context of a closed-loop BMI, distributed cortical feedback with optimized shapes and topology can be exploited to control movement. Our study has direct applications on the closed-loop control of rotary joints that are frequently encountered in robotic prostheses.

From End to End: Gaining, Sorting, and Employing High-Density Neural Single Unit Recordings

The meaning behind neural single unit activity has constantly been a challenge, so it will persist in the foreseeable future. As one of the most sourced strategies, detecting neural activity in high-resolution neural sensor recordings and then attributing them to their corresponding source neurons correctly, namely the process of spike sorting, has been prevailing so far. Support from ever-improving recording techniques and sophisticated algorithms for extracting worthwhile information and abundance in clustering procedures turned spike sorting into an indispensable tool in electrophysiological analysis. This review attempts to illustrate that in all stages of spike sorting algorithms, the past 5 years innovations' brought about concepts, results, and questions worth sharing with even the non-expert user community. By thoroughly inspecting latest innovations in the field of neural sensors, recording procedures, and various spike sorting strategies, a skeletonization of relevant knowledge lays here, with an initiative to get one step closer to the original objective: deciphering and building in the sense of neural transcript.

Scalable batch fabrication of ultrathin flexible neural probes using a bioresorbable silk layer

Flexible intracerebral probes for neural recording and electrical stimulation have been the focus of many research works to achieve better compliance with the surrounding tissue while minimizing rejection. Strategies have been explored to find the best way to insert flexible probes into the brain while maintaining their flexibility once positioned. Here, we present a novel and versatile scalable batch fabrication approach to deliver ultrathin and flexible probes consisting of a silk-parylene bilayer. The biodegradable silk layer, whose degradation time is programmable, provides a temporary and programmable stiffener to allow the insertion of ultrathin parylene-based flexible devices. Our innovative and robust batch fabrication technology allows complete freedom over probe design in terms of materials, size, shape, and thickness. We demonstrate successful ex vivo insertion of the probe with acute high-fidelity recordings of epileptic seizures in field potentials as well as single-unit action potentials in mouse brain slices. Our novel technological solution for implanting ultraflexible devices in the brain while minimizing rejection risks shows high potential for use in both brain research and clinical therapies.

Cellular activity in insular cortex across seconds to hours: Sensations and predictions of bodily states

Our wellness relies on continuous interactions between our brain and body: different organs relay their current state to the brain and are regulated, in turn, by descending visceromotor commands from our brain and by actions such as eating, drinking, thermotaxis, and predator escape. Human neuroimaging and theoretical studies suggest a key role for predictive processing by insular cortex in guiding these efforts to maintain bodily homeostasis. Here, we review recent studies recording and manipulating cellular activity in rodent insular cortex at timescales from seconds to hours. We argue that consideration of these findings in the context of predictive processing of future bodily states may reconcile several apparent discrepancies and offer a unifying, heuristic model for guiding future work.

Representational drift in the mouse visual cortex

Recent studies have shown that neuronal representations gradually change over time despite no changes in the stimulus, environment, or behavior. However, such representational drift has been assumed to be a property of high-level brain structures, whereas earlier circuits, such as sensory cortices, have been assumed to stably encode information over time. Here, we analyzed large-scale optical and electrophysiological recordings from six visual cortical areas in behaving mice that were repeatedly presented with the same natural movies. Contrary to the prevailing notion, we found representational drift over timescales spanning minutes to days across multiple visual areas, cortical layers, and cell types. Notably, neural-code stability did not reflect the hierarchy of information flow across areas. Although individual neurons showed time-dependent changes in their coding properties, the structure of the relationships between population activity patterns remained stable and stereotypic. Such population-level organization may underlie stable visual perception despite continuous changes in neuronal responses.

Intracortical Microelectrode Array Unit Yield under Chronic Conditions: A Comparative Evaluation

While microelectrode arrays (MEAs) offer the promise of elucidating functional neural circuitry and serve as the basis for a cortical neuroprosthesis, the challenge of designing and demonstrating chronically reliable technology remains. Numerous studies report “chronic” data but the actual time spans and performance measures corresponding to the experimental work vary. In this study, we reviewed the experimental durations that constitute chronic studies across a range of MEA types and animal species to gain an understanding of the widespread variability in reported study duration. For rodents, which are the most commonly used animal model in chronic studies, we examined active electrode yield (AEY) for different array types as a means to contextualize the study duration variance, as well as investigate and interpret the performance of custom devices in comparison to conventional MEAs. We observed wide-spread variance within species for the chronic implantation period and an AEY that decayed linearly in rodent models that implanted commercially-available devices. These observations provide a benchmark for comparing the performance of new technologies and highlight the need for consistency in chronic MEA studies. Additionally, to fully derive performance under chronic conditions, the duration of abiotic failure modes, biological processes induced by indwelling probes, and intended application of the device are key determinants.

Representational drift in primary olfactory cortex

Perceptual constancy requires the brain to maintain a stable representation of sensory input. In the olfactory system, activity in primary olfactory cortex (piriform cortex) is thought to determine odour identity^1-5. Here we present the results of electrophysiological recordings of single units maintained over weeks to examine the stability of odour-evoked responses in mouse piriform cortex. Although activity in piriform cortex could be used to discriminate between odorants at any moment in time, odour-evoked responses drifted over periods of days to weeks. The performance of a linear classifier trained on the first recording day approached chance levels after 32 days. Fear conditioning did not stabilize odour-evoked responses. Daily exposure to the same odorant slowed the rate of drift, but when exposure was halted the rate increased again. This demonstration of continuous drift poses the question of the role of piriform cortex in odour perception. This instability might reflect the unstructured connectivity of piriform cortex^6-12, and may be a property of other unstructured cortices.

Neuropixels 2.0: A miniaturized high-density probe for stable, long-term brain recordings

Measuring the dynamics of neural processing across time scales requires following the spiking of thousands of individual neurons over milliseconds and months. To address this need, we introduce the Neuropixels 2.0 probe together with newly designed analysis algorithms. The probe has more than 5000 sites and is miniaturized to facilitate chronic implants in small mammals and recording during unrestrained behavior. High-quality recordings over long time scales were reliably obtained in mice and rats in six laboratories. Improved site density and arrangement combined with newly created data processing methods enable automatic post hoc correction for brain movements, allowing recording from the same neurons for more than 2 months. These probes and algorithms enable stable recordings from thousands of sites during free behavior, even in small animals such as mice.

Neuropixels 2.0: A miniaturized high-density probe for stable, long-term brain recordings

Measuring the dynamics of neural processing across time scales requires following the spiking of thousands of individual neurons over milliseconds and months. To address this need, we introduce the Neuropixels 2.0 probe together with newly designed analysis algorithms. The probe has more than 5000 sites and is miniaturized to facilitate chronic implants in small mammals and recording during unrestrained behavior. High-quality recordings over long time scales were reliably obtained in mice and rats in six laboratories. Improved site density and arrangement combined with newly created data processing methods enable automatic post hoc correction for brain movements, allowing recording from the same neurons for more than 2 months. These probes and algorithms enable stable recordings from thousands of sites during free behavior, even in small animals such as mice.

State-space optimal feedback control of optogenetically driven neural activity

Objective.The rapid acceleration of tools for recording neuronal populations and targeted optogenetic manipulation has enabled real-time, feedback control of neuronal circuits in the brain. Continuously-graded control of measured neuronal activity poses a wide range of technical challenges, which we address through a combination of optogenetic stimulation and a state-space optimal control framework implemented in the thalamocortical circuit of the awake mouse.Approach.Closed-loop optogenetic control of neurons was performed in real-time via stimulation of channelrhodopsin-2 expressed in the somatosensory thalamus of the head-fixed mouse. A state-space linear dynamical system model structure was used to approximate the light-to-spiking input-output relationship in both single-neuron as well as multi-neuron scenarios when recording from multielectrode arrays. These models were utilized to design state feedback controller gains by way of linear quadratic optimal control and were also used online for estimation of state feedback, where a parameter-adaptive Kalman filter provided robustness to model-mismatch.Main results.This model-based control scheme proved effective for feedback control of single-neuron firing rate in the thalamus of awake animals. Notably, the graded optical actuation utilized here did not synchronize simultaneously recorded neurons, but heterogeneity across the neuronal population resulted in a varied response to stimulation. Simulated multi-output feedback control provided better control of a heterogeneous population and demonstrated how the approach generalizes beyond single-neuron applications.Significance.To our knowledge, this work represents the first experimental application of state space model-based feedback control for optogenetic stimulation. In combination with linear quadratic optimal control, the approaches laid out and tested here should generalize to future problems involving the control of highly complex neural circuits. More generally, feedback control of neuronal circuits opens the door to adaptively interacting with the dynamics underlying sensory, motor, and cognitive signaling, enabling a deeper understanding of circuit function and ultimately the control of function in the face of injury or disease.

An easy-to-assemble, robust, and lightweight drive implant for chronic tetrode recordings in freely moving animals

Tetrode arrays are a standard method for neuronal recordings in behaving animals, especially for chronic recordings of many neurons in freely-moving animals.

Experience and sleep-dependent synaptic plasticity: from structure to activity

Synaptic plasticity is important for learning and memory. With increasing evidence linking sleep states to changes in synaptic strength, an emerging view is that sleep promotes learning and memory by facilitating experience-induced synaptic plasticity. In this review, we summarize the recent progress on the function of sleep in regulating cortical synaptic plasticity. Specifically, we outline the electroencephalogram signatures of sleep states (e.g. slow-wave sleep, rapid eye movement sleep, spindles), sleep state-dependent changes in gene and synaptic protein expression, synaptic morphology, and neuronal and network activity. We highlight studies showing that post-experience sleep potentiates experience-induced synaptic changes and discuss the potential mechanisms that may link sleep-related brain activity to synaptic structural remodelling. We conclude that both synapse formation or strengthening and elimination or weakening occur across sleep. This sleep-dependent synaptic plasticity plays an important role in neuronal circuit refinement during development and after learning, while sleep disorders may contribute to or exacerbate the development of common neurological diseases. This article is part of the Theo Murphy meeting issue 'Memory reactivation: replaying events past, present and future'.

64-Channel Carbon Fiber Electrode Arrays for Chronic Electrophysiology

A chief goal in neuroscience is to understand how neuronal activity relates to behavior, perception, and cognition. However, monitoring neuronal activity over long periods of time is technically challenging, and limited, in part, by the invasive nature of recording tools. While electrodes allow for recording in freely-behaving animals, they tend to be bulky and stiff, causing damage to the tissue they are implanted in. One solution to this invasiveness problem may be probes that are small enough to fly under the immune system's radar. Carbon fiber (CF) electrodes are thinner and more flexible than typical metal or silicon electrodes, but the arrays described in previous reports had low channel counts and required time-consuming manual assembly. Here we report the design of an expanded-channel-count carbon fiber electrode array (CFEA) as well as a method for fast preparation of the recording sites using acid etching and electroplating with PEDOT-TFB, and demonstrate the ability of the 64-channel CFEA to record from rat visual cortex. We include designs for interfacing the system with micro-drives or flex-PCB cables for recording from multiple brain regions, as well as a facilitated method for coating CFs with the insulator Parylene-C. High-channel-count CFEAs may thus be an alternative to traditional microwire-based electrodes and a practical tool for exploring the neural code.

Chronic Implantation of Multiple Flexible Polymer Electrode Arrays

Simultaneous recordings from large populations of individual neurons across distributed brain regions over months to years will enable new avenues of scientific and clinical development. The use of flexible polymer electrode arrays can support long-lasting recording, but the same mechanical properties that allow for longevity of recording make multiple insertions and integration into a chronic implant a challenge. Here is a methodology by which multiple polymer electrode arrays can be targeted to a relatively spatially unconstrained set of brain areas. The method utilizes thin-film polymer devices, selected for their biocompatibility and capability to achieve long-term and stable electrophysiologic recording interfaces. The resultant implant allows accurate and flexible targeting of anatomically distant regions, physical stability for months, and robustness to electrical noise. The methodology supports up to sixteen serially inserted devices across eight different anatomic targets. As previously demonstrated, the methodology is capable of recording from 1024 channels. Of these, the 512 channels in this demonstration used for single neuron recording yielded 375 single units distributed across six recording sites. Importantly, this method also can record single units for at least 160 days. This implantation strategy, including temporarily bracing each device with a retractable silicon insertion shuttle, involves tethering of devices at their target depths to a skull-adhered plastic base piece that is custom-designed for each set of recording targets, and stabilization/protection of the devices within a silicone-filled, custom-designed plastic case. Also covered is the preparation of devices for implantation, and design principles that should guide adaptation to different combinations of brain areas or array designs.

Monolayer Graphene Coating of Intracortical Probes for Long-Lasting Neural Activity Monitoring

The invasiveness of intracortical interfaces currently used today is responsible for the formation of an intense immunoresponse and inflammatory reaction from neural cells and tissues. This leads to a high concentration of reactive glial cells around the implant site, creating a physical barrier between the neurons and the recording channels. Such a rejection of foreign analog interfaces causes neural signals to fade from recordings which become flooded by background noise after a few weeks. Despite their invasiveness, those devices are required to track single neuron activity and decode fine sensory or motor commands. In particular, such quantitative and long-lasting recordings of individual neurons are crucial during a long time period (several months) to restore essential functions of the cortex, disrupted after injuries, stroke, or neurodegenerative diseases. To overcome this limitation, graphene and related materials have attracted numerous interests, as they gather in the same material many suitable properties for interfacing living matter, such as an exceptionally high neural affinity, diffusion barrier, and high physical robustness. In this work, the neural affinity of a graphene monolayer with numerous materials commonly used in neuroprostheses is compared, and its impact on the performance and durability of intracortical probes is investigated. For that purpose, an innovative coating method to wrap 3D intracortical probes with a continuous monolayer graphene is developed. Experimental evidence demonstrate the positive impact of graphene on the bioacceptance of conventional intracortical probes, in terms of detection efficiency and tissues responses, allowing real-time samplings of motor neuron activity during 5 weeks. Since continuous graphene coatings can easily be implemented on a wide range of 3D surfaces, this study further motivates the use of graphene and related materials as it could significantly contribute to reduce the current rejection of neural probes currently used in many research areas, from fundamental neurosciences to medicine and neuroprostheses.

Chronically implanted Neuropixels probes enable high-yield recordings in freely moving mice

The advent of high-yield electrophysiology using Neuropixels probes is now enabling researchers to simultaneously record hundreds of neurons with remarkably high signal to noise. However, these probes have not been well-suited to use in freely moving mice. It is critical to study neural activity in unrestricted animals for many reasons, such as leveraging ethological approaches to study neural circuits. We designed and implemented a novel device that allows Neuropixels probes to be customized for chronically implanted experiments in freely moving mice. We demonstrate the ease and utility of this approach in recording hundreds of neurons during an ethological behavior across weeks of experiments. We provide the technical drawings and procedures for other researchers to do the same. Importantly, our approach enables researchers to explant and reuse these valuable probes, a transformative step which has not been established for recordings with any type of chronically-implanted probe.

In vivo Recording Quality of Mechanically Decoupled Floating Versus Skull-Fixed Silicon-Based Neural Probes

Throughout the past decade, silicon-based neural probes have become a driving force in neural engineering. Such probes comprise sophisticated, integrated CMOS electronics which provide a large number of recording sites along slender probe shanks. Using such neural probes in a chronic setting often requires them to be mechanically anchored with respect to the skull. However, any relative motion between brain and implant causes recording instabilities and tissue responses such as glial scarring, thereby shielding recordable neurons from the recording sites integrated on the probe and thus decreasing the signal quality. In the current work, we present a comparison of results obtained using mechanically fixed and floating silicon neural probes chronically implanted into the cortex of a non-human primate. We demonstrate that the neural signal quality estimated by the quality of the spiking and local field potential (LFP) recordings over time is initially superior for the floating probe compared to the fixed device. Nonetheless, the skull-fixed probe also allowed long-term recording of multi-unit activity (MUA) and low frequency signals over several months, especially once pulsations of the brain were properly controlled.

Distinct Structure of Cortical Population Activity on Fast and Infraslow Timescales

Cortical activity is organized across multiple spatial and temporal scales. Most research on the dynamics of neuronal spiking is concerned with timescales of 1 ms-1 s, and little is known about spiking dynamics on timescales of tens of seconds and minutes. Here, we used frequency domain analyses to study the structure of individual neurons' spiking activity and its coupling to local population rate and to arousal level across 0.01-100 Hz frequency range. In mouse medial prefrontal cortex, the spiking dynamics of individual neurons could be quantitatively captured by a combination of interspike interval and firing rate power spectrum distributions. The relative strength of coherence with local population often differed across timescales: a neuron strongly coupled to population rate on fast timescales could be weakly coupled on slow timescales, and vice versa. On slow but not fast timescales, a substantial proportion of neurons showed firing anticorrelated with the population. Infraslow firing rate changes were largely determined by arousal rather than by local factors, which could explain the timescale dependence of individual neurons' population coupling strength. These observations demonstrate how neurons simultaneously partake in fast local dynamics, and slow brain-wide dynamics, extending our understanding of infraslow cortical activity beyond the mesoscale resolution of fMRI.

Continuing progress of spike sorting in the era of big data

Engineering efforts are currently attempting to build devices capable of collecting neural activity from one million neurons in the brain. Part of this effort focuses on developing dense multiple-electrode arrays, which require post-processing via 'spike sorting' to extract neural spike trains from the raw signal. Gathering information at this scale will facilitate fascinating science, but these dreams are only realizable if the spike sorting procedure and data pipeline are computationally scalable, at or superior to hand processing, and scientifically reproducible. These challenges are all being amplified as the data scale continues to increase. In this review, recent efforts to attack these challenges are discussed, which have primarily focused on increasing accuracy and reliability while being computationally scalable. These goals are addressed by adding additional stages to the data processing pipeline and using divide-and-conquer algorithmic approaches. These recent developments should prove useful to most research groups regardless of data scale, not just for cutting-edge devices.

Recent Progress on Non-Conventional Microfabricated Probes for the Chronic Recording of Cortical Neural Activity

Microfabrication technology for cortical interfaces has advanced rapidly over the past few decades for electrophysiological studies and neuroprosthetic devices offering the precise recording and stimulation of neural activity in the cortex. While various cortical microelectrode arrays have been extensively and successfully demonstrated in animal and clinical studies, there remains room for further improvement of the probe structure, materials, and fabrication technology, particularly for high-fidelity recording in chronic implantation. A variety of non-conventional probes featuring unique characteristics in their designs, materials and fabrication methods have been proposed to address the limitations of the conventional standard shank-type ("Utah-" or "Michigan-" type) devices. Such non-conventional probes include multi-sided arrays to avoid shielding and increase recording volumes, mesh- or thread-like arrays for minimized glial scarring and immune response, tube-type or cylindrical probes for three-dimensional (3D) recording and multi-modality, folded arrays for high conformability and 3D recording, self-softening or self-deployable probes for minimized tissue damage and extensions of the recording sites beyond gliosis, nanostructured probes to reduce the immune response, and cone-shaped electrodes for promoting tissue ingrowth and long-term recording stability. Herein, the recent progress with reference to the many different types of non-conventional arrays is reviewed while highlighting the challenges to be addressed and the microfabrication techniques necessary to implement such features.

Long-term recording performance and biocompatibility of chronically implanted cylindrically-shaped, polymer-based neural interfaces

Stereo-electroencephalography depth electrodes, regularly implanted into drug-resistant patients with focal epilepsy to localize the epileptic focus, have a low channel count (6–12 macro- or microelectrodes), limited spatial resolution (0.5–1 cm) and large contact area of the recording sites (~mm2). Thus, they are not suited for high-density local field potential and multiunit recordings. In this paper, we evaluated the long-term electrophysiological recording performance and histocompatibility of a neural interface consisting of 32 microelectrodes providing a physical shape similar to clinical devices. The cylindrically-shaped depth probes made of polyimide (PI) were chronically implanted for 13 weeks into the brain of rats, while cortical or thalamic activity (local field potentials, single-unit and multi-unit activity) was recorded regularly to monitor the temporal change of several features of the electrophysiological performance. To examine the tissue reaction around the probe, neuron-selective and astroglia-selective immunostaining methods were applied. Stable single-unit and multi-unit activity were recorded for several weeks with the implanted depth probes and a weak or moderate tissue reaction was found around the probe track. Our data on biocompatibility presented here and in vivo experiments in non-human primates provide a strong indication that this type of neural probe can be applied in stereo-electroencephalography recordings of up to 2 weeks in humans targeting the localization of epileptic foci providing an increased spatial resolution and the ability to monitor local field potentials and neuronal spiking activity.

Fiber-optic implant for simultaneous fluorescence-based calcium recordings and BOLD fMRI in mice

Despite the growing popularity of blood oxygen level-dependent (BOLD) functional MRI (fMRI), understanding of its underlying principles is still limited. This protocol describes a technique for simultaneous measurement of neural activity using fluorescent calcium indicators together with the corresponding hemodynamic BOLD fMRI response in the mouse brain. Our early work using small-molecule fluorophores in rats gave encouraging results but was limited to acute measurements using synthetic dyes. Our latest procedure combines fMRI with optical detection of cell-type-specific virally delivered GCaMP6, a genetically encoded calcium indicator (GECI). GCaMP6 fluorescence, which increases upon calcium binding, is collected by a chronically implanted optical fiber, allowing longitudinal studies in mice. The chronic implant, placed horizontally on the skull, has an angulated tip that reflects light into the brain and is connected via fiber optics to a remote optical setup. The technique allows access to the neocortex and does not require adaptations of commercial MRI hardware. The hybrid approach permits fiber-optic calcium recordings with simultaneous artifact-free BOLD fMRI with full brain coverage and 1-s temporal resolution using standard gradient-echo echo-planar imaging (GE-EPI) sequences. The method provides robust, cell-type-specific readouts to link neural activity to BOLD signals, as emonstrated for task-free ('resting-state') conditions and in response to hind-paw stimulation. These results highlight the power of fiber photometry combined with fMRI, which we aim to further advance in this protocol. The approach can be easily adapted to study other molecular processes using suitable fluorescent indicators.

Nanomaterials at the neural interface

Interfacing the nervous system with devices able to efficiently record or modulate the electrical activity of neuronal cells represents the underlying foundation of future theranostic applications in neurology and of current openings in neuroscience research. These devices, usually sensing cell activity via microelectrodes, should be characterized by safe working conditions in the biological milieu together with a well-controlled operation-life. The stable device/neuronal electrical coupling at the interface requires tight interactions between the electrode surface and the cell membrane. This neuro-electrode hybrid represents the hyphen between the soft nature of neural tissue, generating electrical signals via ion motions, and the rigid realm of microelectronics and medical devices, dealing with electrons in motion. Efficient integration of these entities is essential for monitoring, analyzing and controlling neuronal signaling but poses significant technological challenges. Improving the cell/electrode interaction and thus the interface performance requires novel engineering of (nano)materials: tuning at the nanoscale electrode's properties may lead to engineer interfacing probes that better camouflaged with their biological target. In this brief review, we highlight the most recent concepts in nanotechnologies and nanomaterials that might help reducing the mismatch between tissue and electrode, focusing on the device's mechanical properties and its biological integration with the tissue.

Decision-making behaviors: weighing ethology, complexity, and sensorimotor compatibility

Rodent decision-making research aims to uncover the neural circuitry underlying the ability to evaluate alternatives and select appropriate actions. Designing behavioral paradigms that provide a solid foundation to ask questions about decision-making computations and mechanisms is a difficult and often underestimated challenge. Here, we propose three dimensions on which we can consider rodent decision-making tasks: ethological validity, task complexity, and stimulus-response compatibility. We review recent research through this lens, and provide practical guidance for researchers in the decision-making field.

In vivo characterization of the electrophysiological and astrocytic responses to a silicon neuroprobe implanted in the mouse neocortex

Silicon neuroprobes hold great potential for studies of large-scale neural activity and brain computer interfaces, but data on brain response in chronic implants is limited. Here we explored with in vivo cellular imaging the response to multisite silicon probes for neural recordings. We tested a chronic implant for mice consisting of a CMOS-compatible silicon probe rigidly implanted in the cortex under a cranial imaging window. Multiunit recordings of cortical neurons with the implant showed no degradation of electrophysiological signals weeks after implantation (mean spike and noise amplitudes of 186 ± 42 µV_pp and 16 ± 3.2 µV_rms, respectively, n = 5 mice). Two-photon imaging through the cranial window allowed longitudinal monitoring of fluorescently-labeled astrocytes from the second week post implantation for 8 weeks (n = 3 mice). The imaging showed a local increase in astrocyte-related fluorescence that remained stable from the second to the tenth week post implantation. These results demonstrate that, in a standard electrophysiology protocol in mice, rigidly implanted silicon probes can provide good short to medium term chronic recording performance with a limited astrocyte inflammatory response. The precise factors influencing the response to silicon probe implants remain to be elucidated.

Fully integrated silicon probes for high-density recording of neural activity

Sensory, motor and cognitive operations involve the coordinated action of large neuronal populations across multiple brain regions in both superficial and deep structures. Existing extracellular probes record neural activity with excellent spatial and temporal (sub-millisecond) resolution, but from only a few dozen neurons per shank. Optical Ca2+ imaging offers more coverage but lacks the temporal resolution needed to distinguish individual spikes reliably and does not measure local field potentials. Until now, no technology compatible with use in unrestrained animals has combined high spatiotemporal resolution with large volume coverage. Here we design, fabricate and test a new silicon probe known as Neuropixels to meet this need. Each probe has 384 recording channels that can programmably address 960 complementary metal-oxide-semiconductor (CMOS) processing-compatible low-impedance TiN sites that tile a single 10-mm long, 70 × 20-μm cross-section shank. The 6 × 9-mm probe base is fabricated with the shank on a single chip. Voltage signals are filtered, amplified, multiplexed and digitized on the base, allowing the direct transmission of noise-free digital data from the probe. The combination of dense recording sites and high channel count yielded well-isolated spiking activity from hundreds of neurons per probe implanted in mice and rats. Using two probes, more than 700 well-isolated single neurons were recorded simultaneously from five brain structures in an awake mouse. The fully integrated functionality and small size of Neuropixels probes allowed large populations of neurons from several brain structures to be recorded in freely moving animals. This combination of high-performance electrode technology and scalable chip fabrication methods opens a path towards recording of brain-wide neural activity during behaviour.

Implantation of Chronic Silicon Probes and Recording of Hippocampal Place Cells in an Enriched Treadmill Apparatus

An important requisite for understanding brain function is the identification of behavior and cell activity correlates. Silicon probes are advanced electrodes for large-scale electrophysiological recording of neuronal activity, but the procedures for their chronic implantation are still underdeveloped. The activity of hippocampal place cells is known to correlate with an animal's position in the environment, but the underlying mechanisms are still unclear. To investigate place cells, here we describe a set of techniques which range from the fabrication of devices for chronic silicon probe implants to the monitoring of place field activity in a cue-enriched treadmill apparatus. A micro-drive and a hat are built by fitting and fastening together 3D-printed plastic parts. A silicon probe is mounted on the micro-drive, cleaned, and coated with dye. A first surgery is performed to fix the hat on the skull of a mouse. Small landmarks are fabricated and attached to the belt of a treadmill. The mouse is trained to run head-fixed on the treadmill. A second surgery is performed to implant the silicon probe in the hippocampus, following which broadband electrophysiological signals are recorded. Finally, the silicon probe is recovered and cleaned for reuse. The analysis of place cell activity in the treadmill reveals a diversity of place field mechanisms, outlining the benefit of the approach.

The brain during free movement - What can we learn from the animal model

Animals, just like humans, can freely move. They do so for various important reasons, such as finding food and escaping predators. Observing these behaviors can inform us about the underlying cognitive processes. In addition, while humans can convey complicated information easily through speaking, animals need to move their bodies to communicate. This has prompted many creative solutions by animal neuroscientists to enable studying the brain during movement. In this review, we first summarize how animal researchers record from the brain while an animal is moving, by describing the most common neural recording techniques in animals and how they were adapted to record during movement. We further discuss the challenge of controlling or monitoring sensory input during free movement. However, not only is free movement a necessity to reflect the outcome of certain internal cognitive processes in animals, it is also a fascinating field of research since certain crucial behavioral patterns can only be observed and studied during free movement. Therefore, in a second part of the review, we focus on some key findings in animal research that specifically address the interaction between free movement and brain activity. First, focusing on walking as a fundamental form of free movement, we discuss how important such intentional movements are for understanding processes as diverse as spatial navigation, active sensing, and complex motor planning. Second, we propose the idea of regarding free movement as the expression of a behavioral state. This view can help to understand the general influence of movement on brain function. Together, the technological advancements towards recording from the brain during movement, and the scientific questions asked about the brain engaged in movement, make animal research highly valuable to research into the human "moving brain".

Automated long-term recording and analysis of neural activity in behaving animals

Addressing how neural circuits underlie behavior is routinely done by measuring electrical activity from single neurons in experimental sessions. While such recordings yield snapshots of neural dynamics during specified tasks, they are ill-suited for tracking single-unit activity over longer timescales relevant for most developmental and learning processes, or for capturing neural dynamics across different behavioral states. Here we describe an automated platform for continuous long-term recordings of neural activity and behavior in freely moving rodents. An unsupervised algorithm identifies and tracks the activity of single units over weeks of recording, dramatically simplifying the analysis of large datasets. Months-long recordings from motor cortex and striatum made and analyzed with our system revealed remarkable stability in basic neuronal properties, such as firing rates and inter-spike interval distributions. Interneuronal correlations and the representation of different movements and behaviors were similarly stable. This establishes the feasibility of high-throughput long-term extracellular recordings in behaving animals.