Ultra-high density electrodes improve detection, yield, and cell type identification in neuronal recordings.

To understand the neural basis of behavior, it is essential to sensitively and accurately measure neural activity at single neuron and single spike resolution. Extracellular electrophysiology delivers this, but it has biases in the neurons it detects and it imperfectly resolves their action potentials. To minimize these limitations, we developed a silicon probe with much smaller and denser recording sites than previous designs, called Neuropixels Ultra (NP Ultra). This device samples neuronal activity at ultra-high spatial density (~10 times higher than previous probes) with low noise levels, while trading off recording span. NP Ultra is effectively an implantable voltage-sensing camera that captures a planar image of a neuron's electrical field. We use a spike sorting algorithm optimized for these probes to demonstrate that the yield of visually-responsive neurons in recordings from mouse visual cortex improves up to ~3-fold. We show that NP Ultra can record from small neuronal structures including axons and dendrites. Recordings across multiple brain regions and four species revealed a subset of extracellular action potentials with unexpectedly small spatial spread and axon-like features. We share a large-scale dataset of these brain-wide recordings in mice as a resource for studies of neuronal biophysics. Finally, using ground-truth identification of three major inhibitory cortical cell types, we found that these cell types were discriminable with approximately 75% success, a significant improvement over lower-resolution recordings. NP Ultra improves spike sorting performance, detection of subcellular compartments, and cell type classification to enable more powerful dissection of neural circuit activity during behavior.

STED microscopy reveals dendrite-specificity of spines in turtle cortex.

Dendritic spines are key structures for neural communication, learning and memory. Spine size and shape probably reflect synaptic strength and learning. Imaging with superresolution STED microscopy the detailed shape of the majority of the spines of individual neurons in turtle cortex (Trachemys scripta elegans) revealed several distinguishable shape classes. Dendritic spines of a given class were not distributed randomly, but rather decorated significantly more often some dendrites than others. The individuality of dendrites was corroborated by significant inter-dendrite differences in other parameters such as spine density and length. In addition, many spines were branched or possessed spinules. These findings may have implications for the role of individual dendrites in this cortex.

The dynamics of pattern matching in camouflaging cuttlefish.

Many cephalopods escape detection using camouflage1. This behaviour relies on a visual assessment of the surroundings, on an interpretation of visual-texture statistics2-4 and on matching these statistics using millions of skin chromatophores that are controlled by motoneurons located in the brain5-7. Analysis of cuttlefish images proposed that camouflage patterns are low dimensional and categorizable into three pattern classes, built from a small repertoire of components8-11. Behavioural experiments also indicated that, although camouflage requires vision, its execution does not require feedback5,12,13, suggesting that motion within skin-pattern space is stereotyped and lacks the possibility of correction. Here, using quantitative methods14, we studied camouflage in the cuttlefish Sepia officinalis as behavioural motion towards background matching in skin-pattern space. An analysis of hundreds of thousands of images over natural and artificial backgrounds revealed that the space of skin patterns is high-dimensional and that pattern matching is not stereotyped-each search meanders through skin-pattern space, decelerating and accelerating repeatedly before stabilizing. Chromatophores could be grouped into pattern components on the basis of their covariation during camouflaging. These components varied in shapes and sizes, and overlay one another. However, their identities varied even across transitions between identical skin-pattern pairs, indicating flexibility of implementation and absence of stereotypy. Components could also be differentiated by their sensitivity to spatial frequency. Finally, we compared camouflage to blanching, a skin-lightening reaction to threatening stimuli. Pattern motion during blanching was direct and fast, consistent with open-loop motion in low-dimensional pattern space, in contrast to that observed during camouflage.

Interhemispheric competition during sleep.

Our understanding of the functions and mechanisms of sleep remains incomplete, reflecting their increasingly evident complexity1-3. Likewise, studies of interhemispheric coordination during sleep4-6 are often hard to connect precisely to known sleep circuits and mechanisms. Here, by recording from the claustra of sleeping bearded dragons (Pogona vitticeps), we show that, although the onsets and offsets of Pogona rapid-eye-movement (REMP) and slow-wave sleep are coordinated bilaterally, these two sleep states differ markedly in their inter-claustral coordination. During slow-wave sleep, the claustra produce sharp-wave ripples independently of one another, showing no coordination. By contrast, during REMP sleep, the potentials produced by the two claustra are precisely coordinated in amplitude and time. These signals, however, are not synchronous: one side leads the other by about 20 ms, with the leading side switching typically once per REMP episode or in between successive episodes. The leading claustrum expresses the stronger activity, suggesting bilateral competition. This competition does not occur directly between the two claustra or telencephalic hemispheres. Rather, it occurs in the midbrain and depends on the integrity of a GABAergic (γ-aminobutyric-acid-producing) nucleus of the isthmic complex, which exists in all vertebrates and is known in birds to underlie bottom-up attention and gaze control. These results reveal that a winner-take-all-type competition exists between the two sides of the brain of Pogona, which originates in the midbrain and has precise consequences for claustrum activity and coordination during REMP sleep.

Single spikes drive sequential propagation and routing of activity in a cortical network.

Single spikes can trigger repeatable firing sequences in cortical networks. The mechanisms that support reliable propagation of activity from such small events and their functional consequences remain unclear. By constraining a recurrent network model with experimental statistics from turtle cortex, we generate reliable and temporally precise sequences from single spike triggers. We find that rare strong connections support sequence propagation, while dense weak connections modulate propagation reliability. We identify sections of sequences corresponding to divergent branches of strongly connected neurons which can be selectively gated. Applying external inputs to specific neurons in the sparse backbone of strong connections can effectively control propagation and route activity within the network. Finally, we demonstrate that concurrent sequences interact reliably, generating a highly combinatorial space of sequence activations. Our results reveal the impact of individual spikes in cortical circuits, detailing how repeatable sequences of activity can be triggered, sustained, and controlled during cortical computations.

Neurons in the brain form thousands of connections, or synapses, with one another, allowing signals to pass from one cell to the next. To activate a neuron, a high enough activating signal or 'action potential' must be reached. However, the accepted view of signal transmission assumes that the great majority of synapses are too weak to activate neurons. This means that often simultaneous inputs from many neurons are required to trigger a single neuron's activation. However, such coordination is likely unreliable as neurons can react differently to the same stimulus depending on the circumstances. An alternative way of transmitting signals has been reported in turtle brains, where impulses from a single neuron can trigger activity across a network of connections. Furthermore, these responses are reliably repeatable, activating the same neurons in the same order. Riquelme et al. set out to understand the mechanism that underlies this type of neuron activation using a mathematical model based on data from the turtle brain. These data showed that the neural network in the turtle's brain had many weak synapses but also a few, rare, strong synapses. Simulating this neural network showed that those rare, strong synapses promote the signal's reliability by providing a consistent route for the signal to travel through the network. The numerous weak synapses, on the other hand, have a regulatory role in providing flexibility to how the activation spreads. This combination of strong and weak connections produces a system that can reliably promote or stop the signal flow depending on the context. Riquelme et al.'s work describes a potential mechanism for how signals might travel reliably through neural networks in the brain, based on data from turtles. Experimental work will need to address whether strong connections play a similar role in other animal species, including humans. In the future, these results may be used as the basis to design new systems for artificial intelligence, building on the success of neural networks.

Molecular diversity and evolution of neuron types in the amniote brain.

The existence of evolutionarily conserved regions in the vertebrate brain is well established. The rules and constraints underlying the evolution of neuron types, however, remain poorly understood. To compare neuron types across brain regions and species, we generated a cell type atlas of the brain of a bearded dragon and compared it with mouse datasets. Conserved classes of neurons could be identified from the expression of hundreds of genes, including homeodomain-type transcription factors and genes involved in connectivity. Within these classes, however, there are both conserved and divergent neuron types, precluding a simple categorization of the brain into ancestral and novel areas. In the thalamus, neuronal diversification correlates with the evolution of the cortex, suggesting that developmental origin and circuit allocation are drivers of neuronal identity and evolution.

Rapid, high-yield production of full-length SARS-CoV-2 spike ectodomain by transient gene expression in CHO cells.

Recombinant forms of the spike protein of SARS-CoV-2 and related viruses have proven difficult to produce with good yields in mammalian cells. Given the panoply of potential COVID-19 diagnostic tools and therapeutic candidates that require purified spike protein and its importance for ongoing SARS-CoV-2 research, we have explored new approaches for spike production and purification. Three transient gene expression methods based on PEI-mediated transfection of CHO or HEK293 cells in suspension culture in chemically-defined media were compared for rapid production of full-length SARS-CoV-2 spike ectodomain. A high-cell-density protocol using DXB11-derived CHOBRI/55E1 cells gave substantially better yields than the other methods. Different forms of the spike ectodomain were expressed, including the wild-type SARS-CoV-2 sequence and a mutated form (to favor expression of the full-length spike ectodomain stabilized in pre-fusion conformation), with and without fusion to putative trimerization domains. An efficient two-step affinity purification method was also developed. Ultimately, we have been able to produce highly homogenous preparations of full-length spike, both monomeric and trimeric, with yields of 100-150 mg/L in the harvested medium. The speed and productivity of this method support further development of CHO-based approaches for recombinant spike protein manufacturing.

A claustrum in reptiles and its role in slow-wave sleep.

The mammalian claustrum, owing to its widespread connectivity with other forebrain structures, has been hypothesized to mediate functions that range from decision-making to consciousness1. Here we report that a homologue of the claustrum, identified by single-cell transcriptomics and viral tracing of connectivity, also exists in a reptile-the Australian bearded dragon Pogona vitticeps. In Pogona, the claustrum underlies the generation of sharp waves during slow-wave sleep. The sharp waves, together with superimposed high-frequency ripples2, propagate to the entire neighbouring pallial dorsal ventricular ridge (DVR). Unilateral or bilateral lesions of the claustrum suppress the production of sharp-wave ripples during slow-wave sleep in a unilateral or bilateral manner, respectively, but do not affect the regular and rapidly alternating sleep rhythm that is characteristic of sleep in this species3. The claustrum is thus not involved in the generation of the sleep rhythm itself. Tract tracing revealed that the reptilian claustrum projects widely to a variety of forebrain areas, including the cortex, and that it receives converging inputs from, among others, areas of the mid- and hindbrain that are known to be involved in wake-sleep control in mammals4-6. Periodically modulating the concentration of serotonin in the claustrum, for example, caused a matching modulation of sharp-wave production there and in the neighbouring DVR. Using transcriptomic approaches, we also identified a claustrum in the turtle Trachemys scripta, a distant reptilian relative of lizards. The claustrum is therefore an ancient structure that was probably already present in the brain of the common vertebrate ancestor of reptiles and mammals. It may have an important role in the control of brain states owing to the ascending input it receives from the mid- and hindbrain, its widespread projections to the forebrain and its role in sharp-wave generation during slow-wave sleep.

Visual perception and cuttlefish camouflage.

Visual perception is inherently statistical: brains exploit repeating features of natural scenes to disambiguate images that could, in principle, have many causes. A clear case for the relevance of statistical inference in vision is animal camouflage. Although visual scenes are each composed of unique arrangements of pixels, they are usually perceived mainly as groupings of statistically defined patches (sandy/leafy/smooth etc…); this fact is exploited by camouflaging animals. The unique ability of certain cephalopods to camouflage actively within many different surroundings provides a rare and direct behavioral readout for texture perception. In addition, because cephalopods and chordates each arose after a phylogenetic split that occurred some 600M years ago, the apparent convergence of texture perception across these groups suggests common principles. Studying cephalopod camouflage may thus help us resolve general problems of visual perception.

Reliable Sequential Activation of Neural Assemblies by Single Pyramidal Cells in a Three-Layered Cortex.

Recent studies reveal the occasional impact of single neurons on surround firing statistics and even simple behaviors. Exploiting the advantages of a simple cortex, we examined the influence of single pyramidal neurons on surrounding cortical circuits. Brief activation of single neurons triggered reliable sequences of firing in tens of other excitatory and inhibitory cortical neurons, reflecting cascading activity through local networks, as indicated by delayed yet precisely timed polysynaptic subthreshold potentials. The evoked patterns were specific to the pyramidal cell of origin, extended over hundreds of micrometers from their source, and unfolded over up to 200 ms. Simultaneous activation of pyramidal cell pairs indicated balanced control of population activity, preventing paroxysmal amplification. Single cortical pyramidal neurons can thus trigger reliable postsynaptic activity that can propagate in a reliable fashion through cortex, generating rapidly evolving and non-random firing sequences reminiscent of those observed in mammalian hippocampus during "replay" and in avian song circuits.

Evolution of neuronal identity in the cerebral cortex.

To understand neocortex evolution, we must define a theory for the elaboration of cell types, circuits, and architectonics from an ancestral structure that is consistent with developmental, molecular, and genetic data. To this end, cross-species comparison of cortical cell types emerges as a very informative approach. We review recent results that illustrate the contribution of molecular and transcriptomic data to the construction of plausible models of cortical cell-type evolution.

Elucidating the control and development of skin patterning in cuttlefish.

Few animals provide a readout that is as objective of their perceptual state as camouflaging cephalopods. Their skin display system includes an extensive array of pigment cells (chromatophores), each expandable by radial muscles controlled by motor neurons. If one could track the individual expansion states of the chromatophores, one would obtain a quantitative description-and potentially even a neural description by proxy-of the perceptual state of the animal in real time. Here we present the use of computational and analytical methods to achieve this in behaving animals, quantifying the states of tens of thousands of chromatophores at sixty frames per second, at single-cell resolution, and over weeks. We infer a statistical hierarchy of motor control, reveal an underlying low-dimensional structure to pattern dynamics and uncover rules that govern the development of skin patterns. This approach provides an objective description of complex perceptual behaviour, and a powerful means to uncover the organizational principles that underlie the function, dynamics and morphogenesis of neural systems.

Evolution of pallium, hippocampus, and cortical cell types revealed by single-cell transcriptomics in reptiles.

Computations in the mammalian cortex are carried out by glutamatergic and γ-aminobutyric acid-releasing (GABAergic) neurons forming specialized circuits and areas. Here we asked how these neurons and areas evolved in amniotes. We built a gene expression atlas of the pallium of two reptilian species using large-scale single-cell messenger RNA sequencing. The transcriptomic signature of glutamatergic neurons in reptilian cortex suggests that mammalian neocortical layers are made of new cell types generated by diversification of ancestral gene-regulatory programs. By contrast, the diversity of reptilian cortical GABAergic neurons indicates that the interneuron classes known in mammals already existed in the common ancestor of all amniotes.

Spatial Information in a Non-retinotopic Visual Cortex.

Turtle dorsal cortex (dCx), a three-layered cortical area of the reptilian telencephalon, receives inputs from the retina via the thalamic lateral geniculate nucleus and constitutes the first cortical stage of visual processing. The receptive fields of dCx neurons usually occupy the entire contralateral visual field. Electrophysiological recordings in awake and anesthetized animals reveal that dCx is sensitive to the spatial structure of natural images, that dCx receptive fields are not entirely uniform across space, and that adaptation to repeated stimulation is position specific. Hence, spatial information can be found both at the single-neuron and population scales. Anatomical data are consistent with the absence of a clear retinotopic mapping of thalamocortical projections. The mapping and representation of visual space in this three-layered cortex thus differ from those found in mammalian primary visual cortex. Our results support the notion that dCx performs a global, rather than local, analysis of the visual scene.

On the Value of Reptilian Brains to Map the Evolution of the Hippocampal Formation.

Our ability to navigate through the world depends on the function of the hippocampus. This old cortical structure plays a critical role in spatial navigation in mammals and in a variety of processes, including declarative and episodic memory and social behavior. Intense research has revealed much about hippocampal anatomy, physiology, and computation; yet, even intensely studied phenomena such as the shaping of place cell activity or the function of hippocampal firing patterns during sleep remain incompletely understood. Interestingly, while the hippocampus may be a 'higher order' area linked to a complex cortical hierarchy in mammals, it is an old cortical structure in evolutionary terms. The reptilian cortex, structurally much simpler than the mammalian cortex and hippocampus, therefore presents a good alternative model for exploring hippocampal function. Here, we trace common patterns in the evolution of the hippocampus of reptiles and mammals and ask which parts can be profitably compared to understand functional principles. In addition, we describe a selection of the highly diverse repertoire of reptilian behaviors to illustrate the value of a comparative approach towards understanding hippocampal function.

Large-scale mapping of cortical synaptic projections with extracellular electrode arrays.

Understanding circuit computation in the nervous system requires sampling activity over large neural populations and maximizing the number of features that can be extracted. By combining planar arrays of extracellular electrodes with the three-layered cortex of turtles, we show that synaptic signals induced along individual axons as well as action potentials can be easily captured. Two types of information can be extracted from these signals, the neuronal subtype (inhibitory or excitatory)-whose identification is more reliable than with traditional measures such as action potential width-and a (partial) spatial map of functional axonal projections from individual neurons. Because our approach is algorithmic, it can be carried out in parallel on hundreds of simultaneously recorded neurons. Combining our approach with soma triangulation, we reveal an axonal projection bias among a population of pyramidal neurons in turtle cortex and confirm this bias through anatomical reconstructions.

Comparative approaches to cortical microcircuits.

Recent trends in neuroscience have narrowed the scope of this field, notably through the progressive elimination of 'model systems' that were key to the development of modern molecular, developmental and functional neuroscience. Although the fantastic opportunities offered by modern molecular biology entirely justify the use of selected organisms (e.g., for their genetic advantages), we argue that a diversity of model systems is essential if we wish to identify the brain's computational principles. It is through comparisons that we can hope to separate mechanistic details (results of each organism's specific history) from functional principles, those that will hopefully one day lead to a theory of the brain.