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.

Spatial Organization of Chromatic Pathways in the Mouse Dorsal Lateral Geniculate Nucleus.

In both dichromats and trichromats, cone opsin signals are maintained independently in cones and combined at the bipolar and retinal ganglion cell level, creating parallel color opponent pathways to the central visual system. Like other dichromats, the mouse retina expresses a short-wavelength (S) and a medium-wavelength (M) opsin, with the S-opsin shifted to peak sensitivity in the ultraviolet (UV) range. Unlike in primates, nonuniform opsin expression across the retina and coexpression in single cones creates a mostly mixed chromatic signal. Here, we describe the visuotopic and chromatic organization of spiking responses in the dorsal lateral geniculate and of the local field potentials in their recipient zone in primary visual cortex (V1). We used an immersive visual stimulus dome that allowed us to present spatiotemporally modulated UV and green luminance in any region of the visual field of an awake, head-fixed mouse. Consistent with retinal expression of opsins, we observed graded UV-to-green dominated responses from the upper to lower visual fields, with a smaller difference across azimuth. In addition, we identified a subpopulation of cells (<10%) that exhibited spectrally opponent responses along the S-M axis. Luminance signals of each wavelength and color signals project to the middle layers of V1. SIGNIFICANCE STATEMENT: In natural environments, color information is useful for guiding behavior. How small terrestrial mammals such as mice use graded expression of cone opsins to extract visual information from their environments is not clear, even as the use of mice for studying visually guided behavior grows. In this study, we examined the color signals that the retina sends to the visual cortex via the lateral geniculate nucleus of the thalamus. We found that green dominated responses in the lower and nasal visual field and ultraviolet dominated responses in the upper visual field. We describe a subset of cells that exhibit color opponent responses.

Closed-loop, ultraprecise, automated craniotomies.

A large array of neuroscientific techniques, including in vivo electrophysiology, two-photon imaging, optogenetics, lesions, and microdialysis, require access to the brain through the skull. Ideally, the necessary craniotomies could be performed in a repeatable and automated fashion, without damaging the underlying brain tissue. Here we report that when drilling through the skull a stereotypical increase in conductance can be observed when the drill bit passes through the skull base. We present an architecture for a robotic device that can perform this algorithm, along with two implementations--one based on homebuilt hardware and one based on commercially available hardware--that can automatically detect such changes and create large numbers of precise craniotomies, even in a single skull. We also show that this technique can be adapted to automatically drill cranial windows several millimeters in diameter. Such robots will not only be useful for helping neuroscientists perform both small and large craniotomies more reliably but can also be used to create precisely aligned arrays of craniotomies with stereotaxic registration to standard brain atlases that would be difficult to drill by hand.

Functional connectivity and tuning curves in populations of simultaneously recorded neurons.

How interactions between neurons relate to tuned neural responses is a longstanding question in systems neuroscience. Here we use statistical modeling and simultaneous multi-electrode recordings to explore the relationship between these interactions and tuning curves in six different brain areas. We find that, in most cases, functional interactions between neurons provide an explanation of spiking that complements and, in some cases, surpasses the influence of canonical tuning curves. Modeling functional interactions improves both encoding and decoding accuracy by accounting for noise correlations and features of the external world that tuning curves fail to capture. In cortex, modeling coupling alone allows spikes to be predicted more accurately than tuning curve models based on external variables. These results suggest that statistical models of functional interactions between even relatively small numbers of neurons may provide a useful framework for examining neural coding.

Nyquist interpolation improves neuron yield in multiunit recordings.

Multiunit electrodes, in particular tetrodes and polytrodes, are able to isolate action potentials from many neurons simultaneously. However, inaccuracies in the post-acquisition reconstruction of recorded spike waveforms can affect the reliability of spike detection and sorting. Here we show that bandlimited interpolation with sample-and-hold delay correction reduces waveform variability, leading to improved reliability of threshold-based event detection and improved spike sorting accuracy. Interpolation of continuously acquired data is, however, computationally expensive. A cost-benefit analysis was made of varying sampling rates from 12.5 kHz (no interpolation) to 100 kHz (eight times oversampling, with respect to the Nyquist frequency), taking into consideration the final application of the data. For most purposes, including spike sorting, sample rates below 25 kHz with bandlimited interpolation to 50 kHz were ideal, with negligible gains above this rate. A practical benefit, especially for large electrode arrays, is that the bandwidth and storage requirements can be greatly reduced by using data acquisition rates at or slightly above the Nyquist frequency.

Identifying robust communities and multi-community nodes by combining top-down and bottom-up approaches to clustering.

Biological functions are carried out by groups of interacting molecules, cells or tissues, known as communities. Membership in these communities may overlap when biological components are involved in multiple functions. However, traditional clustering methods detect non-overlapping communities. These detected communities may also be unstable and difficult to replicate, because traditional methods are sensitive to noise and parameter settings. These aspects of traditional clustering methods limit our ability to detect biological communities, and therefore our ability to understand biological functions. To address these limitations and detect robust overlapping biological communities, we propose an unorthodox clustering method called SpeakEasy which identifies communities using top-down and bottom-up approaches simultaneously. Specifically, nodes join communities based on their local connections, as well as global information about the network structure. This method can quantify the stability of each community, automatically identify the number of communities, and quickly cluster networks with hundreds of thousands of nodes. SpeakEasy shows top performance on synthetic clustering benchmarks and accurately identifies meaningful biological communities in a range of datasets, including: gene microarrays, protein interactions, sorted cell populations, electrophysiology and fMRI brain imaging.

Optogenetics in Mice Performing a Visual Discrimination Task: Measurement and Suppression of Retinal Activation and the Resulting Behavioral Artifact.

Optogenetic techniques are used widely to perturb and interrogate neural circuits in behaving animals, but illumination can have additional effects, such as the activation of endogenous opsins in the retina. We found that illumination, delivered deep into the brain via an optical fiber, evoked a behavioral artifact in mice performing a visually guided discrimination task. Compared with blue (473 nm) and yellow (589 nm) illumination, red (640 nm) illumination evoked a greater behavioral artifact and more activity in the retina, the latter measured with electrical recordings. In the mouse, the sensitivity of retinal opsins declines steeply with wavelength across the visible spectrum, but propagation of light through brain tissue increases with wavelength. Our results suggest that poor retinal sensitivity to red light was overcome by relatively robust propagation of red light through brain tissue and stronger illumination of the retina by red than by blue or yellow light. Light adaptation of the retina, via an external source of illumination, suppressed retinal activation and the behavioral artifact without otherwise impacting behavioral performance. In summary, long wavelength optogenetic stimuli are particularly prone to evoke behavioral artifacts via activation of retinal opsins in the mouse, but light adaptation of the retina can provide a simple and effective mitigation of the artifact.

Neurodata Without Borders: Creating a Common Data Format for Neurophysiology.

The Neurodata Without Borders (NWB) initiative promotes data standardization in neuroscience to increase research reproducibility and opportunities. In the first NWB pilot project, neurophysiologists and software developers produced a common data format for recordings and metadata of cellular electrophysiology and optical imaging experiments. The format specification, application programming interfaces, and sample datasets have been released.

High-density optrodes for multi-scale electrophysiology and optogenetic stimulation.

We demonstrate the design and implementation of hybrid optical-electrical probes (`optrodes') for high resolution electrophysiology and optogenetic stimulation of neurons in multiple brain areas. Our 64-channel implantable optrodes are minimally invasive (50 µm × 20 µm) and span 1~2 mm. To minimize tethering forces on the brain tissue a monolithic high-density flexible cable (6 µm thin) connects the probe to a lightweight headstage (1.3 gr, 256 channel configuration) designed for awake, freely-behaving small animals. A polymer-based multi-channel photonic light delivery system is integrated on shank in a separate layer, providing local optogenetic stimulation of the neural population adjacent to the probe. The entire manufacturing process, including the nanofabrication of the optrodes, post-fabrication assembly, and surgical implantation procedures are designed to be scalable, high-yield, and high-throughput.

Construction of direction selectivity through local energy computations in primary visual cortex.

Despite detailed knowledge about the anatomy and physiology of neurons in primary visual cortex (V1), the large numbers of inputs onto a given V1 neuron make it difficult to relate them to the neuron's functional properties. For example, models of direction selectivity (DS), such as the Energy Model, can successfully describe the computation of phase-invariant DS at a conceptual level, while leaving it unclear how such computations are implemented by cortical circuits. Here, we use statistical modeling to derive a description of DS computation for both simple and complex cells, based on physiologically plausible operations on their inputs. We present a new method that infers the selectivity of a neuron's inputs using extracellular recordings in macaque in the context of random bar stimuli and natural movies in cat. Our results suggest that DS is initially constructed in V1 simple cells through summation and thresholding of non-DS inputs with appropriate spatiotemporal relationships. However, this de novo construction of DS is rare, and a majority of DS simple cells, and all complex cells, appear to receive both excitatory and suppressive inputs that are already DS. For complex cells, these numerous DS inputs typically span a fraction of their overall receptive fields and have similar spatiotemporal tuning but different phase and spatial positions, suggesting an elaboration to the Energy Model that incorporates spatially localized computation. Furthermore, we demonstrate how these computations might be constructed from biologically realizable components, and describe a statistical model consistent with the feed-forward framework suggested by Hubel and Wiesel.

Multiplexed, high density electrophysiology with nanofabricated neural probes.

Extracellular electrode arrays can reveal the neuronal network correlates of behavior with single-cell, single-spike, and sub-millisecond resolution. However, implantable electrodes are inherently invasive, and efforts to scale up the number and density of recording sites must compromise on device size in order to connect the electrodes. Here, we report on silicon-based neural probes employing nanofabricated, high-density electrical leads. Furthermore, we address the challenge of reading out multichannel data with an application-specific integrated circuit (ASIC) performing signal amplification, band-pass filtering, and multiplexing functions. We demonstrate high spatial resolution extracellular measurements with a fully integrated, low noise 64-channel system weighing just 330 mg. The on-chip multiplexers make possible recordings with substantially fewer external wires than the number of input channels. By combining nanofabricated probes with ASICs we have implemented a system for performing large-scale, high-density electrophysiology in small, freely behaving animals that is both minimally invasive and highly scalable.

Polytrodes: high-density silicon electrode arrays for large-scale multiunit recording.

We developed a variety of 54-channel high-density silicon electrode arrays (polytrodes) designed to record from large numbers of neurons spanning millimeters of brain. In cat visual cortex, it was possible to make simultaneous recordings from >100 well-isolated neurons. Using standard clustering methods, polytrodes provide a quality of single-unit isolation that surpasses that attainable with tetrodes. Guidelines for successful in vivo recording and precise electrode positioning are described. We also describe a high-bandwidth continuous data-acquisition system designed specifically for polytrodes and an automated impedance meter for testing polytrode site integrity. Despite having smaller interconnect pitches than earlier silicon-based electrodes of this type, these polytrodes have negligible channel crosstalk, comparable reliability, and low site impedances and are capable of making high-fidelity multiunit recordings with minimal tissue damage. The relatively benign nature of planar electrode arrays is evident both histologically and in experiments where the polytrode was repeatedly advanced and retracted hundreds of microns over periods of many hours. It was possible to maintain stable recordings from active neurons adjacent to the polytrode without change in their absolute positions, neurophysiological or receptive field properties.

Loss of reflex inhibition following muscle tendon stimulation in essential tremor.

Electrical stimulation of human upper limb muscle tendons produces a reflex inhibition (I(1)) in the same muscles. This inhibition is reduced in Parkinson's disease (PD), prompting a similar study of essential tremor (ET). In essential tremor, two of eight subjects had no discernible inhibition, even following supramaximal stimulation (< 80 mA) of the tendons from extensor digitorum communis and extensor pollicis brevis. In the remaining six subjects, the mean thresholds for I(1) in these muscles were increased by 270 and 320%, respectively, relative to controls. The maximal amplitude of the inhibition was significantly reduced in the ET group, as was the following excitation (E(1)). The latency and duration of I(1) were not different in ET subjects and controls. The maximal duration of I(1) was correlated with tremor frequency in individuals, and tendon stimulation was effective in initiating ongoing tremor cycles. These results disclose a peripheral reflex abnormality in ET that is mediated by tendon afferents and can be linked to the coexistent tremor. The response in ET was distinguished from that in PD by its different time-course and by failure of the response to appear in the antagonist muscle. The abnormality may prove a useful marker for ET, which currently lacks a definitive pathological or neurophysiological marker to support objective clinical diagnosis.