Electrochemical Determination of Fentanyl Using Carbon Nanofiber-Modified Electrodes

In this work, we report the direct electrochemical oxidation of fentanyl using commercial screen-printed carbon electrodes (SPCEs) modified with carboxyl-functionalized carbon nanofibers (fCNFs). CNFs have surface chemistry and reactivity similar to carbon nanotubes (CNTs), yet they are easier to produce and are of a lower cost than CNTs. By monitoring the current produced during the electrochemical oxidation of fentanyl, variables such as fCNF loading, fentanyl accumulation time, electrolyte pH, and differential pulse voltammetry parameters were optimized. Under an optimized set of conditions, the fCNF/SPCEs responded linearly to fentanyl in the concentration range of 0.125-10 μM, with a limit of detection of 75 nM. The fCNF/SPCEs also demonstrated excellent selectivity against common cutting agents found in illicit drugs (e.g., glucose, sucrose, caffeine, acetaminophen, and theophylline) and interferents found in biological samples (e.g., ascorbic acid, NaCl, urea, creatinine, and uric acid). The performance of the sensor was also successfully tested using fentanyl spiked into an artificial urine sample. The straightforward electrode assembly process, low cost, ease of use, and rapid response make the fCNF/SPCEs prime candidates for the detection of fentanyl in both physiological samples and street drugs.

A spatially-resolved transcriptional atlas of the murine dorsal pons at single-cell resolution

The "dorsal pons", or "dorsal pontine tegmentum" (dPnTg), is part of the brainstem. It is a complex, densely packed region whose nuclei are involved in regulating many vital functions. Notable among them are the parabrachial nucleus, the Kölliker Fuse, the Barrington nucleus, the locus coeruleus, and the dorsal, laterodorsal, and ventral tegmental nuclei. In this study, we applied single-nucleus RNA-seq (snRNA-seq) to resolve neuronal subtypes based on their unique transcriptional profiles and then used multiplexed error robust fluorescence in situ hybridization (MERFISH) to map them spatially. We sampled ~1 million cells across the dPnTg and defined the spatial distribution of over 120 neuronal subtypes. Our analysis identified an unpredicted high transcriptional diversity in this region and pinpointed the unique marker genes of many neuronal subtypes. We also demonstrated that many neuronal subtypes are transcriptionally similar between humans and mice, enhancing this study's translational value. Finally, we developed a freely accessible, GPU and CPU-powered dashboard ( http://harvard.heavy.ai:6273/ ) that combines interactive visual analytics and hardware-accelerated SQL into a data science framework to allow the scientific community to query and gain insights into the data.

A spatially-resolved transcriptional atlas of the murine dorsal pons at single-cell resolution

The "dorsal pons", or "dorsal pontine tegmentum" (dPnTg), is part of the brainstem. It is a complex, densely packed region whose nuclei are involved in regulating many vital functions. Notable among them are the parabrachial nucleus, the Kölliker Fuse, the Barrington nucleus, the locus coeruleus, and the dorsal, laterodorsal, and ventral tegmental nuclei. In this study, we applied single-nucleus RNA-seq (snRNA-seq) to resolve neuronal subtypes based on their unique transcriptional profiles and then used multiplexed error robust fluorescence in situ hybridization (MERFISH) to map them spatially. We sampled ~1 million cells across the dPnTg and defined the spatial distribution of over 120 neuronal subtypes. Our analysis identified an unpredicted high transcriptional diversity in this region and pinpointed many neuronal subtypes' unique marker genes. We also demonstrated that many neuronal subtypes are transcriptionally similar between humans and mice, enhancing this study's translational value. Finally, we developed a freely accessible, GPU and CPU-powered dashboard (http://harvard.heavy.ai:6273/) that combines interactive visual analytics and hardware-accelerated SQL into a data science framework to allow the scientific community to query and gain insights into the data.

Mouse frontal cortex mediates additive multisensory decisions

The brain can combine auditory and visual information to localize objects. However, the cortical substrates underlying audiovisual integration remain uncertain. Here, we show that mouse frontal cortex combines auditory and visual evidence; that this combination is additive, mirroring behavior; and that it evolves with learning. We trained mice in an audiovisual localization task. Inactivating frontal cortex impaired responses to either sensory modality, while inactivating visual or parietal cortex affected only visual stimuli. Recordings from >14,000 neurons indicated that after task learning, activity in the anterior part of frontal area MOs (secondary motor cortex) additively encodes visual and auditory signals, consistent with the mice's behavioral strategy. An accumulator model applied to these sensory representations reproduced the observed choices and reaction times. These results suggest that frontal cortex adapts through learning to combine evidence across sensory cortices, providing a signal that is transformed into a binary decision by a downstream accumulator.

A modular architecture for organizing, processing and sharing neurophysiology data

We describe an architecture for organizing, integrating and sharing neurophysiology data within a single laboratory or across a group of collaborators. It comprises a database linking data files to metadata and electronic laboratory notes; a module collecting data from multiple laboratories into one location; a protocol for searching and sharing data and a module for automatic analyses that populates a website. These modules can be used together or individually, by single laboratories or worldwide collaborations.

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.

Visuomotor learning promotes visually evoked activity in the medial prefrontal cortex

The medial prefrontal cortex (mPFC) is necessary for executing many learned associations between stimuli and movement. It is unclear, however, how activity in the mPFC evolves across learning, and how this activity correlates with sensory stimuli and the learned movements they evoke. To address these questions, we record cortical activity with widefield calcium imaging while mice learned to associate a visual stimulus with a forelimb movement. After learning, the mPFC shows stimulus-evoked activity both during task performance and during passive viewing, when the stimulus evokes no action. This stimulus-evoked activity closely tracks behavioral performance across training, with both exhibiting a marked increase between days when mice first learn the task, followed by a steady increase with further training. Electrophysiological recordings localized this activity to the secondary motor and anterior cingulate cortex. We conclude that learning a visuomotor task promotes a route for visual information to reach the prefrontal cortex.

Task specificity in mouse parietal cortex

Parietal cortex is implicated in a variety of behavioral processes, but it is unknown whether and how its individual neurons participate in multiple tasks. We trained head-fixed mice to perform two visual decision tasks involving a steering wheel or a virtual T-maze and recorded from the same parietal neurons during these two tasks. Neurons that were active during the T-maze task were typically inactive during the steering-wheel task and vice versa. Recording from the same neurons in the same apparatus without task stimuli yielded the same specificity as in the task, suggesting that task specificity depends on physical context. To confirm this, we trained some mice in a third task combining the steering wheel context with the visual environment of the T-maze. This hybrid task engaged the same neurons as those engaged in the steering-wheel task. Thus, participation by neurons in mouse parietal cortex is task specific, and this specificity is determined by physical context.

A transcriptomic axis predicts state modulation of cortical interneurons

Transcriptomics has revealed that cortical inhibitory neurons exhibit a great diversity of fine molecular subtypes^1-6, but it is not known whether these subtypes have correspondingly diverse patterns of activity in the living brain. Here we show that inhibitory subtypes in primary visual cortex (V1) have diverse correlates with brain state, which are organized by a single factor: position along the main axis of transcriptomic variation. We combined in vivo two-photon calcium imaging of mouse V1 with a transcriptomic method to identify mRNA for 72 selected genes in ex vivo slices. We classified inhibitory neurons imaged in layers 1-3 into a three-level hierarchy of 5 subclasses, 11 types and 35 subtypes using previously defined transcriptomic clusters³. Responses to visual stimuli differed significantly only between subclasses, with cells in the Sncg subclass uniformly suppressed, and cells in the other subclasses predominantly excited. Modulation by brain state differed at all hierarchical levels but could be largely predicted from the first transcriptomic principal component, which also predicted correlations with simultaneously recorded cells. Inhibitory subtypes that fired more in resting, oscillatory brain states had a smaller fraction of their axonal projections in layer 1, narrower spikes, lower input resistance and weaker adaptation as determined in vitro⁷, and expressed more inhibitory cholinergic receptors. Subtypes that fired more during arousal had the opposite properties. Thus, a simple principle may largely explain how diverse inhibitory V1 subtypes shape state-dependent cortical processing.

Neural correlates of blood flow measured by ultrasound

Functional ultrasound imaging (fUSI) is an appealing method for measuring blood flow and thus infer brain activity, but it relies on the physiology of neurovascular coupling and requires extensive signal processing. To establish to what degree fUSI trial-by-trial signals reflect neural activity, we performed simultaneous fUSI and neural recordings with Neuropixels probes in awake mice. fUSI signals strongly correlated with the slow (<0.3 Hz) fluctuations in the local firing rate and were closely predicted by the smoothed firing rate of local neurons, particularly putative inhibitory neurons. The optimal smoothing filter had a width of ∼3 s, matched the hemodynamic response function of awake mice, was invariant across mice and stimulus conditions, and was similar in the cortex and hippocampus. fUSI signals also matched neural firing spatially: firing rates were as highly correlated across hemispheres as fUSI signals. Thus, blood flow measured by ultrasound bears a simple and accurate relationship to neuronal firing.

High surface area nitrogen-functionalized Ni nanozymes for efficient peroxidase-like catalytic activity

Nitrogen-functionalization is an effective means of improving the catalytic performances of nanozymes. In the present work, plasma-assisted nitrogen modification of nanocolumnar Ni GLAD films was performed using an ammonia plasma, resulting in an improvement in the peroxidase-like catalytic performance of the porous, nanostructured Ni films. The plasma-treated nanozymes were characterized by TEM, SEM, XRD, and XPS, revealing a nitrogen-rich surface composition. Increased surface wettability was observed after ammonia plasma treatment, and the resulting nitrogen-functionalized Ni GLAD films presented dramatically enhanced peroxidase-like catalytic activity. The optimal time for plasma treatment was determined to be 120 s; when used to catalyze the oxidation of the colorimetric substrate TMB in the presence of H2O2, Ni films subjected to 120 s of plasma treatment yielded a much higher maximum reaction velocity (3.7⊆10-8 M/s vs. 2.3⊆10-8 M/s) and lower Michaelis-Menten coefficient (0.17 mM vs. 0.23 mM) than pristine Ni films with the same morphology. Additionally, we demonstrate the application of the nanozyme in a gravity-driven, continuous catalytic reaction device. Such a controllable plasma treatment strategy may open a new door toward surface-functionalized nanozymes with improved catalytic performance and potential applications in flow-driven point-of-care devices.

Dopamine Axons in Dorsal Striatum Encode Contralateral Visual Stimuli and Choices

The striatum plays critical roles in visually-guided decision-making and receives dense axonal projections from midbrain dopamine neurons. However, the roles of striatal dopamine in visual decision-making are poorly understood. We trained male and female mice to perform a visual decision task with asymmetric reward payoff, and we recorded the activity of dopamine axons innervating striatum. Dopamine axons in the dorsomedial striatum (DMS) responded to contralateral visual stimuli and contralateral rewarded actions. Neural responses to contralateral stimuli could not be explained by orienting behavior such as eye movements. Moreover, these contralateral stimulus responses persisted in sessions where the animals were instructed to not move to obtain reward, further indicating that these signals are stimulus-related. Lastly, we show that DMS dopamine signals were qualitatively different from dopamine signals in the ventral striatum (VS), which responded to both ipsilateral and contralateral stimuli, conforming to canonical prediction error signaling under sensory uncertainty. Thus, during visual decisions, DMS dopamine encodes visual stimuli and rewarded actions in a lateralized fashion, and could facilitate associations between specific visual stimuli and actions.SIGNIFICANCE STATEMENT While the striatum is central to goal-directed behavior, the precise roles of its rich dopaminergic innervation in perceptual decision-making are poorly understood. We found that in a visual decision task, dopamine axons in the dorsomedial striatum (DMS) signaled stimuli presented contralaterally to the recorded hemisphere, as well as the onset of rewarded actions. Stimulus-evoked signals persisted in a no-movement task variant. We distinguish the patterns of these signals from those in the ventral striatum (VS). Our results contribute to the characterization of region-specific dopaminergic signaling in the striatum and highlight a role in stimulus-action association learning.

Sensory coding and the causal impact of mouse cortex in a visual decision

Correlates of sensory stimuli and motor actions are found in multiple cortical areas, but such correlates do not indicate whether these areas are causally relevant to task performance. We trained mice to discriminate visual contrast and report their decision by steering a wheel. Widefield calcium imaging and Neuropixels recordings in cortex revealed stimulus-related activity in visual (VIS) and frontal (MOs) areas, and widespread movement-related activity across the whole dorsal cortex. Optogenetic inactivation biased choices only when targeted at VIS and MOs,proportionally to each site's encoding of the visual stimulus, and at times corresponding to peak stimulus decoding. A neurometric model based on summing and subtracting activity in VIS and MOs successfully described behavioral performance and predicted the effect of optogenetic inactivation. Thus, sensory signals localized in visual and frontal cortex play a causal role in task performance, while widespread dorsal cortical signals correlating with movement reflect processes that do not play a causal role.

The Role of Al3+ -Based Aqueous Electrolytes in the Charge Storage Mechanism of MnOx Cathodes

Rechargeable aqueous aluminium batteries are the subject of growing interest, however, the charge storage mechanisms at manganese oxide-based cathodes remain poorly understood. In essense, every study proposes a different mechanism. Here, an in situ spectroelectrochemical methodology is used to unambiguously demonstrate that reversible proton-coupled MnO₂ -to-Mn²⁺ conversion is the main charge storage mechanism occurring at MnO₂ cathodes for a range of slightly acidic Al³⁺ -based aqueous electrolytes, with the Al³⁺ hexaaquo complex playing the key role of proton donor. In Zn/MnO₂ assemblies, this mechanism is associated with high gravimetric capacities and discharge potentials, up to 560 mAh g^-1 and 1.65 V respectively, attractive efficiencies (CE > 99.5% and EE > 82%) and excellent cyclability (almost 100% capacity retention over 1 400 cycles at 2 A g^-1 ). Finally, a critical analysis of the data previously published on MnO_x cathodes in Al³⁺ -based aqueous electrolytes is conducted to conclude on a universal charge storage mechanism, i.e., the reversible electrodissolution/electrodeposition of MnO₂ .

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.

Spatial modulation of visual responses arises in cortex with active navigation

During navigation, the visual responses of neurons in mouse primary visual cortex (V1) are modulated by the animal's spatial position. Here we show that this spatial modulation is similarly present across multiple higher visual areas but negligible in the main thalamic pathway into V1. Similar to hippocampus, spatial modulation in visual cortex strengthens with experience and with active behavior. Active navigation in a familiar environment, therefore, enhances the spatial modulation of visual signals starting in the cortex.

Cortical State Fluctuations during Sensory Decision Making

In many behavioral tasks, cortex enters a desynchronized state where low-frequency fluctuations in population activity are suppressed. The precise behavioral correlates of desynchronization and its global organization are unclear. One hypothesis holds that desynchronization enhances stimulus coding in the relevant sensory cortex. Another hypothesis holds that desynchronization reflects global arousal, such as task engagement. Here, we trained mice on tasks where task engagement could be distinguished from sensory accuracy. Using widefield calcium imaging, we found that performance-related desynchronization was global and correlated better with engagement than with accuracy. Consistent with this link between desynchronization and engagement, rewards had a long-lasting desynchronizing effect. To determine whether engagement-related state changes depended on the relevant sensory modality, we trained mice on visual and auditory tasks and found that in both cases desynchronization was global, including regions such as somatomotor cortex. We conclude that variations in low-frequency fluctuations are predominately global and related to task engagement.

Spatial connectivity matches direction selectivity in visual cortex

The selectivity of neuronal responses arises from the architecture of excitatory and inhibitory connections. In the primary visual cortex, the selectivity of a neuron in layer 2/3 for stimulus orientation and direction is thought to arise from intracortical inputs that are similarly selective^1-8. However, the excitatory inputs of a neuron can have diverse stimulus preferences^1-4,6,7,9, and inhibitory inputs can be promiscuous¹⁰ and unselective¹¹. Here we show that the excitatory and inhibitory intracortical connections to a layer 2/3 neuron accord with its selectivity by obeying precise spatial patterns. We used rabies tracing^1,12 to label and functionally image the excitatory and inhibitory inputs to individual pyramidal neurons of layer 2/3 of the mouse visual cortex. Presynaptic excitatory neurons spanned layers 2/3 and 4 and were distributed coaxial to the preferred orientation of the postsynaptic neuron, favouring the region opposite to its preferred direction. By contrast, presynaptic inhibitory neurons resided within layer 2/3 and favoured locations near the postsynaptic neuron and ahead of its preferred direction. The direction selectivity of a postsynaptic neuron was unrelated to the selectivity of presynaptic neurons, but correlated with the spatial displacement between excitatory and inhibitory presynaptic ensembles. Similar asymmetric connectivity establishes direction selectivity in the retina^13-17. This suggests that this circuit motif might be canonical in sensory processing.

Mouse Visual Cortex Is Modulated by Distance Traveled and by Theta Oscillations

The visual responses of neurons in the primary visual cortex (V1) are influenced by the animal's position in the environment [1-5]. V1 responses encode positions that co-fluctuate with those encoded by place cells in hippocampal area CA1 [2, 5]. This correlation might reflect a common influence of non-visual spatial signals on both areas. Place cells in CA1, indeed, do not rely only on vision; their place preference depends on the physical distance traveled [6-11] and on the phase of the 6-9 Hz theta oscillation [12, 13]. Are V1 responses similarly influenced by these non-visual factors? We recorded V1 and CA1 neurons simultaneously while mice performed a spatial task in a virtual corridor by running on a wheel and licking at a reward location. By changing the gain that couples the wheel movement to the virtual environment, we found that ∼20% of V1 neurons were influenced by the physical distance traveled, as were ∼40% of CA1 place cells. Moreover, the firing rate of ∼24% of V1 neurons was modulated by the phase of theta oscillations recorded in CA1 and the response profiles of ∼7% of V1 neurons shifted spatially across the theta cycle, analogous to the phase precession observed in ∼37% of CA1 place cells. The influence of theta oscillations on V1 responses was more prominent in putative layer 6. These results reveal that, in a familiar environment, sensory processing in V1 is modulated by the key non-visual signals that influence spatial coding in the hippocampus.

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.

Peroxidase-Like Behavior of Ni Thin Films Deposited by Glancing Angle Deposition for Enzyme-Free Uric Acid Sensing

We present a nanozyme-based biosensor fabricated from nanostructured Ni films deposited onto a silicon wafer by glancing angle deposition (GLAD) for enzyme-free colorimetric monitoring of uric acid (UA), a biomarker for gout, high blood pressure, heart disease, and kidney disease. The helically structured Ni GLAD nanozymes exhibit excellent peroxidase-like activity to accelerate the oxidation reaction of colorless 3,3',5,5'-tetramethylbenzidine (TMB) to a blue product, oxidized TMB (oxTMB), mediated by H₂O₂. In the presence of UA, oxTMB is reduced, decreasing the optical absorbance by an amount determined by the concentration of UA in the solution. The nanozyme not only mimics peroxidase but also possesses the notable qualities of reusability, simple operation, and reliability, making it environment-friendly and suitable for on-demand analysis. We optimized essential working parameters (pH, TMB concentration, and H₂O₂ concentration) to maximize the initial color change of the TMB solution. The catalytic activity of this nanozyme was compared with conventional nanofilms using the Michaelis-Menten theory. Based on this, enzyme-free biosensors were developed for colorimetric detection of UA, providing a wide detection range and a limit of detection (3.3 μM) suitable for measurements of UA concentration in sweat. Furthermore, interference from glucose and urea was studied so as to explore the potential of the biosensor for use in the clinical diagnosis of UA biomarkers.

Dopaminergic and Prefrontal Basis of Learning from Sensory Confidence and Reward Value

Deciding between stimuli requires combining their learned value with one's sensory confidence. We trained mice in a visual task that probes this combination. Mouse choices reflected not only present confidence and past rewards but also past confidence. Their behavior conformed to a model that combines signal detection with reinforcement learning. In the model, the predicted value of the chosen option is the product of sensory confidence and learned value. We found precise correlates of this variable in the pre-outcome activity of midbrain dopamine neurons and of medial prefrontal cortical neurons. However, only the latter played a causal role: inactivating medial prefrontal cortex before outcome strengthened learning from the outcome. Dopamine neurons played a causal role only after outcome, when they encoded reward prediction errors graded by confidence, influencing subsequent choices. These results reveal neural signals that combine reward value with sensory confidence and guide subsequent learning.

Diversity of Interneurons in the Dorsal Striatum Revealed by Single-Cell RNA Sequencing and PatchSeq

Striatal locally projecting neurons, or interneurons, act on nearby circuits and shape functional output to the rest of the basal ganglia. We performed single-cell RNA sequencing of striatal cells enriching for interneurons. We find seven discrete interneuron types, six of which are GABAergic. In addition to providing specific markers for the populations previously described, including those expressing Sst/Npy, Th, Npy without Sst, and Chat, we identify two small populations of cells expressing Cck with or without Vip. Surprisingly, the Pvalb-expressing cells do not constitute a discrete cluster but rather are part of a larger group of cells expressing Pthlh with a spatial gradient of Pvalb expression. Using PatchSeq, we show that Pthlh cells exhibit a continuum of electrophysiological properties correlated with expression of Pvalb. Furthermore, we find significant molecular differences that correlate with differences in electrophysiological properties between Pvalb-expressing cells of the striatum and those of the cortex.

Distributed coding of choice, action and engagement across the mouse brain

Vision, choice, action and behavioural engagement arise from neuronal activity that may be distributed across brain regions. Here we delineate the spatial distribution of neurons underlying these processes. We used Neuropixels probes1,2 to record from approximately 30,000 neurons in 42 brain regions of mice performing a visual discrimination task3. Neurons in nearly all regions responded non-specifically when the mouse initiated an action. By contrast, neurons encoding visual stimuli and upcoming choices occupied restricted regions in the neocortex, basal ganglia and midbrain. Choice signals were rare and emerged with indistinguishable timing across regions. Midbrain neurons were activated before contralateral choices and were suppressed before ipsilateral choices, whereas forebrain neurons could prefer either side. Brain-wide pre-stimulus activity predicted engagement in individual trials and in the overall task, with enhanced subcortical but suppressed neocortical activity during engagement. These results reveal organizing principles for the distribution of neurons encoding behaviourally relevant variables across the mouse brain.

Hippocampal CA1 Somatostatin Interneurons Originate in the Embryonic MGE/POA

Oriens lacunosum-moleculare (O-LM) interneurons constitute 40% of hippocampal interneurons expressing Somatostatin (SST). Recent evidence has indicated a dual origin for these cells in the medial and caudal ganglionic eminences (MGE and CGE), with expression of Htr3a as a distinguishing factor. This is strikingly different from cortical SST interneurons that have a single origin within the MGE/preoptic area (POA). We reassessed the origin of hippocampal SST interneurons using a range of genetic lineage-tracing mice combined with single-cell transcriptomic analysis. We find a common origin for all hippocampal SST interneurons in NKX2-1-expressing progenitors of the telencephalic neuroepithelium and an MGE/POA-like transcriptomic signature for all SST clusters. This suggests that functional heterogeneity within the SST CA1 population cannot be attributed to a differential MGE/CGE genetic origin.

On the unsuspected role of multivalent metal ions on the charge storage of a metal oxide electrode in mild aqueous electrolytes

Insertion mechanisms of multivalent ions in transition metal oxide cathodes are poorly understood and subject to controversy and debate, especially when performed in aqueous electrolytes. To address this issue, we have here investigated the reversible reduction of nanostructured amorphous TiO2 electrodes by spectroelectrochemistry in mild aqueous electrolytes containing either a multivalent metal salt as AlCl3 or a weak organic acid as acetic acid. Our results show that the reversible charge storage in TiO2 is thermodynamically and kinetically indistinguishable when carried out in either an Al3+- or acetic acid-based electrolyte, both leading under similar conditions of pH and concentrations to an almost identical maximal charge storage of ∼115 mA h g-1. These observations are in agreement with a mechanism where the inserting/deinserting cation is the proton and not the multivalent metal cation. Analysis of the data also demonstrates that the proton source is the Brønsted weak acid present in the aqueous electrolyte, i.e. either the acetic acid or the aquo metal ion complex generated from solvation of Al3+ (i.e. [Al(H2O)6]3+). Such a proton-coupled charge storage mechanism is also found to occur with other multivalent metal ions such as Zn2+ and Mn2+, albeit with a lower efficiency than Al3+, an effect we have attributed to the lower acidity of [Zn(H2O)6]2+ and [Mn(H2O)6]2+. These findings are of fundamental importance because they shed new light on previous studies assuming reversible Al3+-insertion into metal oxides, and, more generally, they highlight the unsuspected proton donor role played by multivalent metal cations commonly involved in rechargeable aqueous batteries.

Effects of Arousal on Mouse Sensory Cortex Depend on Modality

Changes in arousal modulate the activity of mouse sensory cortex, but studies in different mice and different sensory areas disagree on whether this modulation enhances or suppresses activity. We measured this modulation simultaneously in multiple cortical areas by imaging mice expressing voltage-sensitive fluorescent proteins (VSFP). VSFP imaging estimates local membrane potential across large portions of cortex. We used temporal filters to predict local potential from running speed or from pupil dilation, two measures of arousal. The filters provided good fits and revealed that the effects of arousal depend on modality. In the primary visual cortex (V1) and auditory cortex (Au), arousal caused depolarization followed by hyperpolarization. In the barrel cortex (S1b) and a secondary visual area (LM), it caused only hyperpolarization. In all areas, nonetheless, arousal reduced the phasic responses to trains of sensory stimuli. These results demonstrate diverse effects of arousal across sensory cortex but similar effects on sensory responses.

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Voltage-sensitive fluorescent proteins reveal effects of arousal across the cortex

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In auditory and primary visual areas, arousal depolarizes then hyperpolarizes

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In somatosensory and secondary visual areas, arousal only hyperpolarizes

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In all areas, arousal reduces phasic responses to trains of sensory stimuli

High-dimensional geometry of population responses in visual cortex

A neuronal population encodes information most efficiently when its stimulus responses are high-dimensional and uncorrelated, and most robustly when they are lower-dimensional and correlated. Here we analysed the dimensionality of the encoding of natural images by large populations of neurons in the visual cortex of awake mice. The evoked population activity was high-dimensional, and correlations obeyed an unexpected power law: the nth principal component variance scaled as 1/n. This scaling was not inherited from the power law spectrum of natural images, because it persisted after stimulus whitening. We proved mathematically that if the variance spectrum was to decay more slowly then the population code could not be smooth, allowing small changes in input to dominate population activity. The theory also predicts larger power-law exponents for lower-dimensional stimulus ensembles, which we validated experimentally. These results suggest that coding smoothness may represent a fundamental constraint that determines correlations in neural population codes.

The impact of bilateral ongoing activity on evoked responses in mouse cortex

In the absence of external stimuli or overt behavior, the activity of the left and right cortical hemispheres shows fluctuations that are largely bilateral. Here, we show that these fluctuations are largely responsible for the variability observed in cortical responses to sensory stimuli. Using widefield imaging of voltage and calcium signals, we measured activity in the cortex of mice performing a visual detection task. Bilateral fluctuations invested all areas, particularly those closest to the midline. Activity was less bilateral in the monocular region of primary visual cortex and, especially during task engagement, in secondary motor cortex. Ongoing bilateral fluctuations dominated unilateral visual responses, and interacted additively with them, explaining much of the variance in trial-by-trial activity. Even though these fluctuations occurred in regions necessary for the task, they did not affect detection behavior. We conclude that bilateral ongoing activity continues during visual stimulation and has a powerful additive impact on visual responses.

Spontaneous behaviors drive multidimensional, brainwide activity

Neuronal populations in sensory cortex produce variable responses to sensory stimuli and exhibit intricate spontaneous activity even without external sensory input. Cortical variability and spontaneous activity have been variously proposed to represent random noise, recall of prior experience, or encoding of ongoing behavioral and cognitive variables. Recording more than 10,000 neurons in mouse visual cortex, we observed that spontaneous activity reliably encoded a high-dimensional latent state, which was partially related to the mouse's ongoing behavior and was represented not just in visual cortex but also across the forebrain. Sensory inputs did not interrupt this ongoing signal but added onto it a representation of external stimuli in orthogonal dimensions. Thus, visual cortical population activity, despite its apparently noisy structure, reliably encodes an orthogonal fusion of sensory and multidimensional behavioral information.

Decision and navigation in mouse parietal cortex

Posterior parietal cortex (PPC) has been implicated in navigation, in the control of movement, and in visually-guided decisions. To relate these views, we measured activity in PPC while mice performed a virtual navigation task driven by visual decisions. PPC neurons were selective for specific combinations of the animal's spatial position and heading angle. This selectivity closely predicted both the activity of individual PPC neurons, and the arrangement of their collective firing patterns in choice-selective sequences. These sequences reflected PPC encoding of the animal's navigation trajectory. Using decision as a predictor instead of heading yielded worse fits, and using it in addition to heading only slightly improved the fits. Alternative models based on visual or motor variables were inferior. We conclude that when mice use vision to choose their trajectories, a large fraction of parietal cortex activity can be predicted from simple attributes such as spatial position and heading.

Coherent encoding of subjective spatial position in visual cortex and hippocampus

A major role of vision is to guide navigation, and navigation is strongly driven by vision^1-4. Indeed, the brain's visual and navigational systems are known to interact^5,6, and signals related to position in the environment have been suggested to appear as early as in the visual cortex^6,7. Here, to establish the nature of these signals, we recorded in the primary visual cortex (V1) and hippocampal area CA1 while mice traversed a corridor in virtual reality. The corridor contained identical visual landmarks in two positions, so that a purely visual neuron would respond similarly at those positions. Most V1 neurons, however, responded solely or more strongly to the landmarks in one position rather than the other. This modulation of visual responses by spatial location was not explained by factors such as running speed. To assess whether the modulation is related to navigational signals and to the animal's subjective estimate of position, we trained the mice to lick for a water reward upon reaching a reward zone in the corridor. Neuronal populations in both CA1 and V1 encoded the animal's position along the corridor, and the errors in their representations were correlated. Moreover, both representations reflected the animal's subjective estimate of position, inferred from the animal's licks, better than its actual position. When animals licked in a given location-whether correctly or incorrectly-neural populations in both V1 and CA1 placed the animal in the reward zone. We conclude that visual responses in V1 are controlled by navigational signals, which are coherent with those encoded in hippocampus and reflect the animal's subjective position. The presence of such navigational signals as early as a primary sensory area suggests that they permeate sensory processing in the cortex.

Robustness of Spike Deconvolution for Neuronal Calcium Imaging

Calcium imaging is a powerful method to record the activity of neural populations in many species, but inferring spike times from calcium signals is a challenging problem. We compared multiple approaches using multiple datasets with ground truth electrophysiology and found that simple non-negative deconvolution (NND) outperformed all other algorithms on out-of-sample test data. We introduce a novel benchmark applicable to recordings without electrophysiological ground truth, based on the correlation of responses to two stimulus repeats, and used this to show that unconstrained NND also outperformed the other algorithms when run on "zoomed out" datasets of ∼10,000 cell recordings from the visual cortex of mice of either sex. Finally, we show that NND-based methods match the performance of a supervised method based on convolutional neural networks while avoiding some of the biases of such methods, and at much faster running times. We therefore recommend that spikes be inferred from calcium traces using simple NND because of its simplicity, efficiency, and accuracy.SIGNIFICANCE STATEMENT The experimental method that currently allows for recordings of the largest numbers of cells simultaneously is two-photon calcium imaging. However, use of this powerful method requires that neuronal firing times be inferred correctly from the large resulting datasets. Previous studies have claimed that complex supervised learning algorithms outperform simple deconvolution methods at this task. Unfortunately, these studies suffered from several problems and biases. When we repeated the analysis, using the same data and correcting these problems, we found that simpler spike inference methods perform better. Even more importantly, we found that supervised learning methods can introduce artifactual structure into spike trains, which can in turn lead to erroneous scientific conclusions. Of the algorithms we evaluated, we found that an extremely simple method performed best in all circumstances tested, was much faster to run, and was insensitive to parameter choices, making incorrect scientific conclusions much less likely.

Molecular Architecture of the Mouse Nervous System

The mammalian nervous system executes complex behaviors controlled by specialized, precisely positioned, and interacting cell types. Here, we used RNA sequencing of half a million single cells to create a detailed census of cell types in the mouse nervous system. We mapped cell types spatially and derived a hierarchical, data-driven taxonomy. Neurons were the most diverse and were grouped by developmental anatomical units and by the expression of neurotransmitters and neuropeptides. Neuronal diversity was driven by genes encoding cell identity, synaptic connectivity, neurotransmission, and membrane conductance. We discovered seven distinct, regionally restricted astrocyte types that obeyed developmental boundaries and correlated with the spatial distribution of key glutamate and glycine neurotransmitters. In contrast, oligodendrocytes showed a loss of regional identity followed by a secondary diversification. The resource presented here lays a solid foundation for understanding the molecular architecture of the mammalian nervous system and enables genetic manipulation of specific cell types.

Classes and continua of hippocampal CA1 inhibitory neurons revealed by single-cell transcriptomics

Understanding any brain circuit will require a categorization of its constituent neurons. In hippocampal area CA1, at least 23 classes of GABAergic neuron have been proposed to date. However, this list may be incomplete; additionally, it is unclear whether discrete classes are sufficient to describe the diversity of cortical inhibitory neurons or whether continuous modes of variability are also required. We studied the transcriptomes of 3,663 CA1 inhibitory cells, revealing 10 major GABAergic groups that divided into 49 fine-scale clusters. All previously described and several novel cell classes were identified, with three previously described classes unexpectedly found to be identical. A division into discrete classes, however, was not sufficient to describe the diversity of these cells, as continuous variation also occurred between and within classes. Latent factor analysis revealed that a single continuous variable could predict the expression levels of several genes, which correlated similarly with it across multiple cell types. Analysis of the genes correlating with this variable suggested it reflects a range from metabolically highly active faster-spiking cells that proximally target pyramidal cells to slower-spiking cells targeting distal dendrites or interneurons. These results elucidate the complexity of inhibitory neurons in one of the simplest cortical structures and show that characterizing these cells requires continuous modes of variation as well as discrete cell classes.

Challenges and opportunities for large-scale electrophysiology with Neuropixels probes

Electrophysiological methods are the gold standard in neuroscience because they reveal the activity of individual neurons at high temporal resolution and in arbitrary brain locations. Microelectrode arrays based on complementary metal-oxide semiconductor (CMOS) technology, such as Neuropixels probes, look set to transform these methods. Neuropixels probes provide ∼1000 recording sites on an extremely narrow shank, with on-board amplification, digitization, and multiplexing. They deliver low-noise recordings from hundreds of neurons, providing a step change in the type of data available to neuroscientists. Here we discuss the opportunities afforded by these probes for large-scale electrophysiology, the challenges associated with data processing and anatomical localization, and avenues for further improvements of the technology.

Vision and Locomotion Shape the Interactions between Neuron Types in Mouse Visual Cortex

Cortical computation arises from the interaction of multiple neuronal types, including pyramidal (Pyr) cells and interneurons expressing Sst, Vip, or Pvalb. To study the circuit underlying such interactions, we imaged these four types of cells in mouse primary visual cortex (V1). Our recordings in darkness were consistent with a "disinhibitory" model in which locomotion activates Vip cells, thus inhibiting Sst cells and disinhibiting Pyr cells. However, the disinhibitory model failed when visual stimuli were present: locomotion increased Sst cell responses to large stimuli and Vip cell responses to small stimuli. A recurrent network model successfully predicted each cell type's activity from the measured activity of other types. Capturing the effects of locomotion, however, required allowing it to increase feedforward synaptic weights and modulate recurrent weights. This network model summarizes interneuron interactions and suggests that locomotion may alter cortical computation by changing effective synaptic connectivity.

Community-based benchmarking improves spike rate inference from two-photon calcium imaging data

In recent years, two-photon calcium imaging has become a standard tool to probe the function of neural circuits and to study computations in neuronal populations. However, the acquired signal is only an indirect measurement of neural activity due to the comparatively slow dynamics of fluorescent calcium indicators. Different algorithms for estimating spike rates from noisy calcium measurements have been proposed in the past, but it is an open question how far performance can be improved. Here, we report the results of the spikefinder challenge, launched to catalyze the development of new spike rate inference algorithms through crowd-sourcing. We present ten of the submitted algorithms which show improved performance compared to previously evaluated methods. Interestingly, the top-performing algorithms are based on a wide range of principles from deep neural networks to generative models, yet provide highly correlated estimates of the neural activity. The competition shows that benchmark challenges can drive algorithmic developments in neuroscience.

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.

Macroscopic Strain-Induced Transition from Quasi-infinite Gold Nanoparticle Chains to Defined Plasmonic Oligomers

We investigate the formation of chains of few plasmonic nanoparticles-so-called plasmonic oligomers-by strain-induced fragmentation of linear particle assemblies. Detailed investigations of the fragmentation process are conducted by in situ atomic force microscopy and UV-vis-NIR spectroscopy. Based on these experimental results and mechanical simulations computed by the lattice spring model, we propose a formation mechanism that explains the observed decrease of chain polydispersity upon increasing strain and provides experimental guidelines for tailoring chain length distribution. By evaluation of the strain-dependent optical properties, we find a reversible, nonlinear shift of the dominant plasmonic resonance. We could quantitatively explain this feature based on simulations using generalized multiparticle Mie theory (GMMT). Both optical and morphological characterization show that the unstrained sample is dominated by chains with a length above the so-called infinite chain limit-above which optical properties show no dependency on chain length-while during deformation, the average chain length decrease below this limit and chain length distribution becomes more narrow. Since the formation mechanism results in a well-defined, parallel orientation of the oligomers on macroscopic areas, the effect of finite chain length can be studied even using conventional UV-vis-NIR spectroscopy. The scalable fabrication of oriented, linear plasmonic oligomers opens up additional opportunities for strain-dependent optical devices and mechanoplasmonic sensing.

High-Yield Methods for Accurate Two-Alternative Visual Psychophysics in Head-Fixed Mice

Research in neuroscience increasingly relies on the mouse, a mammalian species that affords unparalleled genetic tractability and brain atlases. Here, we introduce high-yield methods for probing mouse visual decisions. Mice are head-fixed, facilitating repeatable visual stimulation, eye tracking, and brain access. They turn a steering wheel to make two alternative choices, forced or unforced. Learning is rapid thanks to intuitive coupling of stimuli to wheel position. The mouse decisions deliver high-quality psychometric curves for detection and discrimination and conform to the predictions of a simple probabilistic observer model. The task is readily paired with two-photon imaging of cortical activity. Optogenetic inactivation reveals that the task requires mice to use their visual cortex. Mice are motivated to perform the task by fluid reward or optogenetic stimulation of dopamine neurons. This stimulation elicits a larger number of trials and faster learning. These methods provide a platform to accurately probe mouse vision and its neural basis.

Aberrant Cortical Activity in Multiple GCaMP6-Expressing Transgenic Mouse Lines

Transgenic mouse lines are invaluable tools for neuroscience but, as with any technique, care must be taken to ensure that the tool itself does not unduly affect the system under study. Here we report aberrant electrical activity, similar to interictal spikes, and accompanying fluorescence events in some genotypes of transgenic mice expressing GCaMP6 genetically encoded calcium sensors. These epileptiform events have been observed particularly, but not exclusively, in mice with Emx1-Cre and Ai93 transgenes, of either sex, across multiple laboratories. The events occur at >0.1 Hz, are very large in amplitude (>1.0 mV local field potentials, >10% df/f widefield imaging signals), and typically cover large regions of cortex. Many properties of neuronal responses and behavior seem normal despite these events, although rare subjects exhibit overt generalized seizures. The underlying mechanisms of this phenomenon remain unclear, but we speculate about possible causes on the basis of diverse observations. We encourage researchers to be aware of these activity patterns while interpreting neuronal recordings from affected mouse lines and when considering which lines to study.