Learning to learn: Single session acquisition of new rules by freely moving mice.

Learning from examples and adapting to new circumstances are fundamental attributes of human cognition. However, it is unclear what conditions allow for fast and successful learning, especially in nonhuman subjects. To determine how rapidly freely moving mice can learn a new discrimination criterion (DC), we design a two-alternative forced-choice visual discrimination paradigm in which the DCs governing the task can change between sessions. We find that experienced animals can learn a new DC after being exposed to only five training and three testing trials. The propensity for single session learning improves over time and is accurately predicted based on animal experience and criterion difficulty. After establishing the procedural learning of a paradigm, mice continuously improve their performance in new circumstances. Thus, mice learn to learn.

Local activation of CA1 pyramidal cells induces theta-phase precession.

Hippocampal theta-phase precession is involved in spatiotemporal coding and in generating multineural spike sequences, but how precession originates remains unresolved. To determine whether precession can be generated directly in hippocampal area CA1 and disambiguate multiple competing mechanisms, we used closed-loop optogenetics to impose artificial place fields in pyramidal cells of mice running on a linear track. More than one-third of the CA1 artificial fields exhibited synthetic precession that persisted for a full theta cycle. By contrast, artificial fields in the parietal cortex did not exhibit synthetic precession. These findings are incompatible with precession models based on inheritance, dual-input, spreading activation, inhibition-excitation summation, or somato-dendritic competition. Thus, a precession generator resides locally within CA1.

Wired together, change together: Spike timing modifies transmission in converging assemblies.

The precise timing of neuronal spikes may lead to changes in synaptic connectivity and is thought to be crucial for learning and memory. However, the effect of spike timing on neuronal connectivity in the intact brain remains unknown. Using closed-loop optogenetic stimulation in CA1 of freely moving mice, we generated unique spike patterns between presynaptic pyramidal cells (PYRs) and postsynaptic parvalbumin (PV)-immunoreactive cells. The stimulation led to spike transmission changes that occurred together across all presynaptic PYRs connected to the same postsynaptic PV cell. The precise timing of all presynaptic and postsynaptic cell spikes affected transmission changes. These findings reveal an unexpected plasticity mechanism, in which the spike timing of an entire cell assembly has a more substantial impact on effective connectivity than that of individual cell pairs.

In vivo optogenetic identification and manipulation of GABAergic interneuron subtypes.

Identification and manipulation of different GABAergic interneuron classes in the behaving animal are important to understand their role in circuit dynamics and behavior. The combination of optogenetics and large-scale neuronal recordings allows specific interneuron populations to be identified and perturbed for circuit analysis in intact animals. A crucial aspect of this approach is coupling electrophysiological recording with spatially and temporally precise light delivery. Focal multisite illumination of neuronal activators and silencers in predetermined temporal configurations or a closed loop manner opens the door to addressing many novel questions. Recent progress demonstrates the utility and power of this novel technique for interneuron research.

Short-term auditory priming in freely-moving mice.

Priming, a change in the mental processing of a stimulus as a result of prior encounter with a related stimulus, has been observed repeatedly and studied extensively in humans. Yet currently, there is no behavioral model of short-term priming in lab animals, precluding research on the neurobiological basis of priming. Here, we describe an auditory discrimination paradigm for studying response priming in freely moving mice. We find a priming effect in success rate in all mice tested on the task. In contrast, we do not find a priming effect in response times. Compared to non-primed discrimination trials, the addition of incongruent prime stimuli reduces success rate more than congruent prime stimuli, suggesting a cognitive mechanism based on differential interference. The results establish the short-term priming phenomenon in rodents, and the paradigm opens the door to studying the cellular-network basis of priming.

Positive and biphasic extracellular waveforms correspond to return currents and axonal spikes.

Multiple biophysical mechanisms may generate non-negative extracellular waveforms during action potentials, but the origin and prevalence of positive spikes and biphasic spikes in the intact brain are unknown. Using extracellular recordings from densely-connected cortical networks in freely-moving mice, we find that a tenth of the waveforms are non-negative. Positive phases of non-negative spikes occur in synchrony or just before wider same-unit negative spikes. Narrow positive spikes occur in isolation in the white matter. Isolated biphasic spikes are narrower than negative spikes, occurring right after spikes of verified inhibitory units. In CA1, units with dominant non-negative spikes exhibit place fields, phase precession, and phase-locking to ripples. Thus, near-somatic narrow positive extracellular potentials correspond to return currents, and isolated non-negative spikes correspond to axonal potentials. Identifying non-negative extracellular waveforms that correspond to non-somatic compartments during spikes can enhance the understanding of physiological and pathological neural mechanisms in intact animals.

Cortical Pyramidal and Parvalbumin Cells Exhibit Distinct Spatiotemporal Extracellular Electric Potentials.

Brain circuits are composed of diverse cell types with distinct morphologies, connections, and distributions of ion channels. Modeling suggests that the spatial distribution of the extracellular voltage during a spike depends on cellular morphology, connectivity, and identity. However, experimental evidence from the intact brain is lacking. Here, we combined high-density recordings from hippocampal region CA1 and neocortex of freely moving mice with optogenetic tagging of parvalbumin-immunoreactive (PV) cells. We used ground truth tagging of the recorded pyramidal cells (PYR) and PV cells to construct binary classification models. Features derived from single-channel waveforms or from spike timing alone allowed near-perfect classification of PYR and PV cells. To determine whether there is unique information in the spatial distribution of the extracellular potentials, we removed all single-channel waveform information from the multichannel waveforms using an event-based delta-transformation. We found that spatiotemporal features derived from the transformed waveforms yield accurate classification. The extracellular analog of the spatial distribution of the initial depolarization phase provided the highest contribution to the spatially based prediction. Compared with PV cell spikes, PYR spikes exhibited higher spatial synchrony at the beginning of the extracellular spike and lower synchrony at the trough. The successful classification of PYR and PV cells based on purely spatial features provides direct experimental evidence that spikes of distinct cell types are associated with distinct spatial distributions of extracellular potentials.

Error correction and improved precision of spike timing in converging cortical networks.

The brain propagates neuronal signals accurately and rapidly. Nevertheless, whether and how a pool of cortical neurons transmits an undistorted message to a target remains unclear. We apply optogenetic white noise signals to small assemblies of cortical pyramidal cells (PYRs) in freely moving mice. The directly activated PYRs exhibit a spike timing precision of several milliseconds. Instead of losing precision, interneurons driven via synaptic activation exhibit higher precision with respect to the white noise signal. Compared with directly activated PYRs, postsynaptic interneuron spike trains allow better signal reconstruction, demonstrating error correction. Data-driven modeling shows that nonlinear amplification of coincident spikes can generate error correction and improved precision. Over multiple applications of the same signal, postsynaptic interneuron spiking is most reliable at timescales ten times shorter than those of the presynaptic PYR, exhibiting temporal coding. Similar results are observed in hippocampal region CA1. Coincidence detection of convergent inputs enables messages to be precisely propagated between cortical PYRs and interneurons.

Hybrid Offspring of C57BL/6J Mice Exhibit Improved Properties for Neurobehavioral Research.

C57BL/6 is the most commonly used mouse strain in neurobehavioral research, serving as a background for multiple transgenic lines. However, C57BL/6 exhibit behavioral and sensorimotor disadvantages that worsen with age. We bred FVB/NJ females and C57BL/6J males to generate first-generation hybrid offspring (FVB/NJ x C57BL/6J)F1. The hybrid mice exhibit reduced anxiety-like behavior, improved learning, and enhanced long-term spatial memory. In contrast to both progenitors, hybrids maintain sensorimotor performance upon aging and exhibit improved long-term memory. The hybrids are larger than C57BL/6J, exhibiting enhanced running behavior on a linear track during freely-moving electrophysiological recordings. Hybrids exhibit typical rate and phase coding of space by CA1 pyramidal cells. Hybrids generated by crossing FVB/NJ females with transgenic males of a C57BL/6 background support optogenetic neuronal control in neocortex and hippocampus. The hybrid mice provide an improved model for neurobehavioral studies combining complex behavior, electrophysiology, and genetic tools readily available in C57BL/6 mice.

Network resonance can be generated independently at distinct levels of neuronal organization.

Resonance is defined as maximal response of a system to periodic inputs in a limited frequency band. Resonance may serve to optimize inter-neuronal communication, and has been observed at multiple levels of neuronal organization. However, it is unknown how neuronal resonance observed at the network level is generated and how network resonance depends on the properties of the network building blocks. Here, we first develop a metric for quantifying spike timing resonance in the presence of background noise, extending the notion of spiking resonance for in vivo experiments. Using conductance-based models, we find that network resonance can be inherited from resonances at other levels of organization, or be intrinsically generated by combining mechanisms across distinct levels. Resonance of membrane potential fluctuations, postsynaptic potentials, and single neuron spiking can each be generated independently of resonance at any other level and be propagated to the network level. At all levels of organization, interactions between processes that give rise to low- and high-pass filters generate the observed resonance. Intrinsic network resonance can be generated by the combination of filters belonging to different levels of organization. Inhibition-induced network resonance can emerge by inheritance from resonance of membrane potential fluctuations, and be sharpened by presynaptic high-pass filtering. Our results demonstrate a multiplicity of qualitatively different mechanisms that can generate resonance in neuronal systems, and provide analysis tools and a conceptual framework for the mechanistic investigation of network resonance in terms of circuit components, across levels of neuronal organization.

Deconvolution improves the detection and quantification of spike transmission gain from spike trains.

Accurate detection and quantification of spike transmission between neurons is essential for determining neural network mechanisms that govern cognitive functions. Using point process and conductance-based simulations, we found that existing methods for determining neuronal connectivity from spike times are highly affected by burst spiking activity, resulting in over- or underestimation of spike transmission. To improve performance, we developed a mathematical framework for decomposing the cross-correlation between two spike trains. We then devised a deconvolution-based algorithm for removing effects of second-order spike train statistics. Deconvolution removed the effect of burst spiking, improving the estimation of neuronal connectivity yielded by state-of-the-art methods. Application of deconvolution to neuronal data recorded from hippocampal region CA1 of freely-moving mice produced higher estimates of spike transmission, in particular when spike trains exhibited bursts. Deconvolution facilitates the precise construction of complex connectivity maps, opening the door to enhanced understanding of the neural mechanisms underlying brain function.

High Fidelity Theta Phase Rolling of CA1 Neurons.

Single hippocampal cells encode the spatial position of an animal by increasing their firing rates within "place fields," and by shifting the phase of their spikes to earlier phases of the ongoing theta oscillations (theta phase precession). Whether other forms of spatial phase changes exist in the hippocampus is unknown. Here, we used high-density electrophysiological recordings in mice of either sex running back and forth on a 150-cm linear track. We found that the instantaneous phase of spikes shifts to progressively later theta phases as the animal traverses the place field. We term this shift theta "phase rolling." Phase rolling is opposite in direction to precession, faster than precession, and occurs between distinct theta cycles. Place fields that exhibit phase rolling are larger than nonrolling fields, and in-field spikes occur in distinct theta phases in rolling compared with nonrolling fields. As a phase change associated with position, theta phase rolling may be used to encode space.SIGNIFICANCE STATEMENT Theta phase precession is a well-known coding scheme in which neurons represent the position of the animal by the timing of their spikes with respect to the phase of ongoing theta oscillations. Here, we show that hippocampal neurons also undergo "theta phase rolling," a phase change faster and opposite in direction to precession. As the animal advances in space, spikes occur at progressively later phases of consecutive theta cycles. Future studies may reveal whether phase rolling constitutes a novel coding mechanism of space.

Outan: An On-Head System for Driving µLED Arrays Implanted in Freely Moving Mice.

In the intact brain, neural activity can be recorded using sensing electrodes and manipulated using light stimulation. Silicon probes with integrated electrodes and µLEDs enable the detection and control of neural activity using a single implanted device. Miniaturized solutions for recordings from small freely moving animals are commercially available, but stimulation is driven by large, stationary current sources. We designed and fabricated a current source chip and integrated it into a headstage PCB that weighs 1.37 g. The proposed system provides 10-bit resolution current control for 32 channels, driving µLEDs with up to 4.6 V and sourcing up to 0.9 mA at a refresh rate of 5 kHz per channel. When calibrated against a µLED probe, the system allows linear control of light output power, up to 10 µW per µLED. To demonstrate the capabilities of the system, synthetic sequences of neural spiking activity were produced by driving multiple µLEDs implanted in the hippocampal CA1 area of a freely moving mouse. The high spatial, temporal, and amplitude resolution of the system provides a rich variety of stimulation patterns. Combined with commercially available sampling headstages, the system provides an easy to use back-end, fully utilizing the bi-directional potential of integrated opto-electronic arrays.

Bidirectional Optogenetic Control of Inhibitory Neurons in Freely-Moving Mice.

OBJECTIVE: Optogenetic manipulations of excitable cells enable activating or silencing specific types of neurons. By expressing two types of exogenous proteins, a single neuron can be depolarized using light of one wavelength and hyperpolarized with another. However, routing two distinct wavelengths into the same brain locality typically requires bulky optics that cannot be implanted on the head of a freely-moving animal. METHODS: We developed a lens-free approach for constructing dual-color head-mounted, fiber-based optical units: any two wavelengths can be combined. RESULTS: Here, each unit was comprised of one 450 nm and one 638 nm laser diode, yielding light power of 0.4 mW and 8 mW at the end of a 50 micrometer multimode fiber. To create a multi-color/multi-site optoelectronic device, a four-shank silicon probe mounted on a microdrive was equipped with two dual-color and two single-color units, for a total weight under 3 g. Devices were implanted in mice expressing the blue-light sensitive cation channel ChR2 and the red-light sensitive chloride pump Jaws in parvalbumin-immunoreactive (PV) inhibitory neurons. The combination of dual-color units with recording electrodes was free from electromagnetic interference, and device heating was under 7°C even after prolonged operation. CONCLUSION: Using these devices, the same cortical PV cell could be activated and silenced. This was achieved for multiple cells both in neocortex and hippocampus of freely-moving mice. SIGNIFICANCE: This technology can be used for controlling spatially intermingled neurons that have distinct genetic profiles, and for controlling spike timing of cortical neurons during cognitive tasks.

Response and sample bridging in a primate short-term memory task.

Freely-moving rodents can solve short-term memory (STM) tasks using "response bridging" strategies, relying on motor patterns instead of mnemonic functions. This limits the interpretational power of results yielded by some STM tasks in rodents. To determine whether head-fixed monkeys can employ parallel non-mnemonic strategies, we measured eye position and velocity of two head-fixed monkeys performing a delayed response reaching and grasping task. We found that eye position during the delay period was correlated with reach direction. Moreover, reach direction as well as grasp object could be predicted from eye kinematics during the delay. Both eye velocity and eye position contributed to the prediction of reach direction. These results show that motor signals carry sufficient information to allow monkeys to solve STM tasks without using any mnemonic functions. Thus, the potential of animals to solve STM tasks using motor patterns is more diverse than previously recognized.

A novel low-noise movement tracking system with real-time analog output for closed-loop experiments.

BACKGROUND: Modern electrophysiological experiments are moving towards closing the loop, where the extrinsic (behavioral) and intrinsic (neuronal) variables automatically affect stimulation parameters. Rodent experiments targeting spatial behavior require animal 2D kinematics to be continuously monitored in a reliable and accurate manner. Cameras provide a robust, flexible, and simple way to track kinematics on the fly. Indeed, several available camera-based systems yield high spatiotemporal resolution. However, the acquired kinematic data cannot be accessed with sufficient temporal resolution for precise real-time feedback. NEW METHOD: Here, we describe a novel software and hardware system for movement tracking based on color-markers with real-time low-noise output that works in both light and dark conditions. The analog outputs precisely represent 2D movement features including position, orientation, and their temporal derivatives, velocity and angular velocity. RESULTS: Using adaptive windowing, contour extraction, and rigid-body Kalman filtering, a 640-by-360 pixel frame is processed in 28 ms with less than 4 ms jitter, for 100 frames per second. The system is robust to outliers, has low noise, and maintains a smooth, accurate output even when one or more markers are temporarily missing. Using freely-moving mice, we demonstrate novel applications such as replacing conventional sensors in a behavioral arena and inducing novel place fields via closed-loop optogenetic stimulation. COMPARISON WITH EXISTING METHOD(S): To the best of our knowledge, this is the first tracking system that yields analog output in real-time. CONCLUSIONS: This modular system for closed-loop experiment tracking can be implemented by downloading an open-source software and assembling low-cost hardware circuity.

Dual color optogenetic control of neural populations using low-noise, multishank optoelectrodes.

Optogenetics allows for optical manipulation of neuronal activity and has been increasingly combined with intra- and extra-cellular electrophysiological recordings. Genetically-identified classes of neurons are optically manipulated, though the versatility of optogenetics would be increased if independent control of distinct neural populations could be achieved on a sufficient spatial and temporal resolution. We report a scalable multi-site optoelectrode design that allows simultaneous optogenetic control of two spatially intermingled neuronal populations in vivo. We describe the design, fabrication, and assembly of low-noise, multi-site/multi-color optoelectrodes. Each shank of the four-shank assembly is monolithically integrated with 8 recording sites and a dual-color waveguide mixer with a 7 × 30 µm cross-section, coupled to 405 nm and 635 nm injection laser diodes (ILDs) via gradient-index (GRIN) lenses to meet optical and thermal design requirements. To better understand noise on the recording channels generated during diode-based activation, we developed a lumped-circuit modeling approach for EMI coupling mechanisms and used it to limit artifacts to amplitudes under 100 µV upto an optical output power of 450 µW. We implanted the packaged devices into the CA1 pyramidal layer of awake mice, expressing Channelrhodopsin-2 in pyramidal cells and ChrimsonR in paravalbumin-expressing interneurons, and achieved optical excitation of each cell type using sub-mW illumination. We highlight the potential use of this technology for functional dissection of neural circuits.

Sharp wave ripples during learning stabilize the hippocampal spatial map.

Cognitive representation of the environment requires a stable hippocampal map, but the mechanisms maintaining a given map are unknown. Because sharp wave-ripples (SPW-R) orchestrate both retrospective and prospective spatial information, we hypothesized that disrupting neuronal activity during SPW-Rs affects spatial representation. Mice learned new sets of three goal locations daily in a multiwell maze. We used closed-loop SPW-R detection at goal locations to trigger optogenetic silencing of a subset of CA1 pyramidal neurons. Control place cells (nonsilenced or silenced outside SPW-Rs) largely maintained the location of their place fields after learning and showed increased spatial information content. In contrast, the place fields of SPW-R-silenced place cells remapped, and their spatial information remained unaltered. SPW-R silencing did not impact the firing rates or proportions of place cells. These results suggest that interference with SPW-R-associated activity during learning prevents stabilization and refinement of hippocampal maps.

Spike-Centered Jitter Can Mistake Temporal Structure.

Jitter-type spike resampling methods are routinely applied in neurophysiology for detecting temporal structure in spike trains (point processes). Several variations have been proposed. The concern has been raised, based on numerical experiments involving Poisson spike processes, that such procedures can be conservative. We study the issue and find it can be resolved by reemphasizing the distinction between spike-centered (basic) jitter and interval jitter. Focusing on spiking processes with no temporal structure, interval jitter generates an exact hypothesis test, guaranteeing valid conclusions. In contrast, such a guarantee is not available for spike-centered jitter. We construct explicit examples in which spike-centered jitter hallucinates temporal structure, in the sense of exaggerated false-positive rates. Finally, we illustrate numerically that Poisson approximations to jitter computations, while computationally efficient, can also result in inaccurate hypothesis tests. We highlight the value of classical statistical frameworks for guiding the design and interpretation of spike resampling methods.

Fiberless multicolor neural optoelectrode for in vivo circuit analysis.

Maximizing the potential of optogenetic approaches in deep brain structures of intact animals requires optical manipulation of neurons at high spatial and temporal resolutions, while simultaneously recording electrical data from those neurons. Here, we present the first fiber-less optoelectrode with a monolithically integrated optical waveguide mixer that can deliver multicolor light at a common waveguide port to achieve multicolor modulation of the same neuronal population in vivo. We demonstrate successful device implementation by achieving efficient coupling between a side-emitting injection laser diode (ILD) and a dielectric optical waveguide mixer via a gradient-index (GRIN) lens. The use of GRIN lenses attains several design features, including high optical coupling and thermal isolation between ILDs and waveguides. We validated the packaged devices in the intact brain of anesthetized mice co-expressing Channelrhodopsin-2 and Archaerhodopsin in pyramidal cells in the hippocampal CA1 region, achieving high quality recording, activation and silencing of the exact same neurons in a given local region. This fully-integrated approach demonstrates the spatial precision and scalability needed to enable independent activation and silencing of the same or different groups of neurons in dense brain regions while simultaneously recording from them, thus considerably advancing the capabilities of currently available optogenetic toolsets.