Open source silicon microprobes for high throughput neural recording

Identification of the subventricular tegmental nucleus as brainstem reward center

Rewards are essential for motivation, decision-making, memory, and mental health. We identified the subventricular tegmental nucleus (SVTg) as a brainstem reward center. In mice, reward and its prediction activate the SVTg, and SVTg stimulation leads to place preference, reduced anxiety, and accumbal dopamine release. Mice self-stimulate the SVTg, which can also be activated directly by the neocortex, resulting in effective inhibition of the lateral habenula, a region associated with depression. This mechanism may also explain why SVTg suppression induces aversion and increases fear. The translational relevance of these findings is supported by evidence in the rat, monkey, and human brainstem, establishing SVTg as a key hub for reward processing, emotional valence, and motivation.

Probabilistically constrained vector summation of motion direction in the mouse superior colliculus

Visual motion is a crucial cue for the brain to track objects and take appropriate actions, enabling effective interactions with the environment. Here, we study how the superior colliculus (SC) integrates motion information using asymmetric plaids composed of drifting gratings of different directions and speeds. With both in vivo electrophysiology and two-photon calcium imaging, we find that mouse SC neurons integrate motion direction by performing vector summation of the component gratings. The computation is constrained probabilistically by the possible physical motions consistent with each grating. Excitatory and inhibitory SC neurons respond similarly to the plaid stimuli. Finally, the probabilistically constrained vector summation also guides optokinetic eye movements. Such a computation is fundamentally different from that in the visual cortex, where motion integration follows the intersection of the constraints. Our studies thus demonstrate a novel neural computation in motion processing and raise intriguing questions regarding its neuronal implementation and functional significance.

Coherent cortical representations develop after experience via feedforward-recurrent circuit alignment

Sensory cortical areas guide behavior by transforming stimulus-driven inputs into selective responses representing relevant features. A classic example is the representation of edge orientations in the visual cortex 1-4 , where layer 4 (L4) neurons co-activated by an orientation provide feedforward inputs to specific functional modules in layer 2/3 (L2/3) that share strong recurrent connections 5-7 . The aligned state of feedforward-recurrent interactions is critical for amplifying selective cortical responses 8-12 , but how it develops remains unclear. Using simultaneous electrophysiology and calcium imaging in visually naïve animals we find that coactivity of L4 neurons and L2/3 modular responses elicited by oriented gratings lacks the tight relationship to orientation preference found in experienced animals. One factor that could contribute to the lack of functionally specific coactivity is high variability in naïve L4 neuron responses that decreases significantly following experience. But a computational model of feedforward-recurrent interaction suggests that high variability alone is insufficient to explain the naïve state and provides a biological signature of feedforward-recurrent misalignment that we confirm with whole-cell recordings: dynamic changes in orientation tuning of L2/3 subthreshold responses shortly after stimulus onset. In conclusion, we provide diverse evidence for a realignment of feedforward-recurrent interactions following experience that is critical for building reliable sensory representations with interlaminar temporal coherence.

Tonic and burst-like locus coeruleus stimulation distinctly shift network activity across the cortical hierarchy

Noradrenaline (NA) release from the locus coeruleus (LC) changes activity and connectivity in neuronal networks across the brain, modulating multiple behavioral states. NA release is mediated by both tonic and burst-like LC activity. However, it is unknown whether the functional changes in target areas depend on these firing patterns. Using optogenetics, photometry, electrophysiology and functional magnetic resonance imaging in mice, we show that tonic and burst-like LC firing patterns elicit brain responses that hinge on their distinct NA release dynamics. During moderate tonic LC activation, NA release engages regions associated with associative processing, while burst-like stimulation biases the brain toward sensory processing. These activation patterns locally couple with increased astrocytic and inhibitory activity and change the brain's topological configuration in line with the hierarchical organization of the cerebral cortex. Together, these findings reveal how the LC-NA system achieves a nuanced regulation of global circuit operations.

Constraints on the subsecond modulation of striatal dynamics by physiological dopamine signaling

Dopaminergic neurons play a crucial role in associative learning, but their capacity to regulate behavior on subsecond timescales remains debated. It is thought that dopaminergic neurons drive certain behaviors by rapidly modulating striatal spiking activity; however, a view has emerged that only artificially high (that is, supra-physiological) dopamine signals alter behavior on fast timescales. This raises the possibility that moment-to-moment striatal spiking activity is not strongly shaped by dopamine signals in the physiological range. To test this, we transiently altered dopamine levels while monitoring spiking responses in the ventral striatum of behaving mice. These manipulations led to only weak changes in striatal activity, except when dopamine release exceeded reward-matched levels. These findings suggest that dopaminergic neurons normally play a minor role in the subsecond modulation of striatal dynamics in relation to other inputs and demonstrate the importance of discerning dopaminergic neuron contributions to brain function under physiological and potentially nonphysiological conditions.

Ultraflexible electrodes for recording neural activity in the mouse spinal cord during motor behavior

Implantable electrode arrays are powerful tools for directly interrogating neural circuitry in the brain, but implementing this technology in the spinal cord in behaving animals has been challenging due to the spinal cord's significant motion with respect to the vertebral column during behavior. Consequently, the individual and ensemble activity of spinal neurons processing motor commands remains poorly understood. Here, we demonstrate that custom ultraflexible 1-μm-thick polyimide nanoelectronic threads can conduct laminar recordings of many neuronal units within the lumbar spinal cord of unrestrained, freely moving mice. The extracellular action potentials have high signal-to-noise ratio, exhibit well-isolated feature clusters, and reveal diverse patterns of activity during locomotion. Furthermore, chronic recordings demonstrate the stable tracking of single units and their functional tuning over multiple days. This technology provides a path for elucidating how spinal circuits compute motor actions.

Differential disruptions in population coding along the dorsal-ventral axis of CA1 in the APP/PS1 mouse model of Aβ pathology

Alzheimer's Disease (AD) is characterized by a range of behavioral alterations, including memory loss and psychiatric symptoms. While there is evidence that molecular pathologies, such as amyloid beta (Aβ), contribute to AD, it remains unclear how this histopathology gives rise to such disparate behavioral deficits. One hypothesis is that Aβ exerts differential effects on neuronal circuits across brain regions, depending on the neurophysiology and connectivity of different areas. To test this, we recorded from large neuronal populations in dorsal CA1 (dCA1) and ventral CA1 (vCA1), two hippocampal areas known to be structurally and functionally diverse, in the APP/PS1 mouse model of amyloidosis. Despite similar levels of Aβ pathology, dCA1 and vCA1 showed distinct disruptions in neuronal population activity as animals navigated a virtual reality environment. In dCA1, pairwise correlations and entropy, a measure of the diversity of activity patterns, were decreased in APP/PS1 mice relative to age-matched C57BL/6 controls. However, in vCA1, APP/PS1 mice had increased pair-wise correlations and entropy as compared to age matched controls. Finally, using maximum entropy models, we connected the microscopic features of population activity (correlations) to the macroscopic features of the population code (entropy). We found that the models' performance increased in predicting dCA1 activity, but decreased in predicting vCA1 activity, in APP/PS1 mice relative to the controls. Taken together, we found that Aβ exerts distinct effects across different hippocampal regions, suggesting that the various behavioral deficits of AD may reflect underlying heterogeneities in neuronal circuits and the different disruptions that Aβ pathology causes in those circuits.

Neural and behavioural state switching during hippocampal dentate spikes

Distinct brain and behavioural states are associated with organized neural population dynamics that are thought to serve specific cognitive functions1-3. Memory replay events, for example, occur during synchronous population events called sharp-wave ripples in the hippocampus while mice are in an 'offline' behavioural state, enabling cognitive mechanisms such as memory consolidation and planning4-11. But how does the brain re-engage with the external world during this behavioural state and permit access to current sensory information or promote new memory formation? Here we found that the hippocampal dentate spike, an understudied population event that frequently occurs between sharp-wave ripples12, may underlie such a mechanism. We show that dentate spikes are associated with distinctly elevated brain-wide firing rates, primarily observed in higher order networks, and couple to brief periods of arousal. Hippocampal place coding during dentate spikes aligns to the mouse's current spatial location, unlike the memory replay accompanying sharp-wave ripples. Furthermore, inhibiting neural activity during dentate spikes disrupts associative memory formation. Thus, dentate spikes represent a distinct brain state and support memory during non-locomotor behaviour, extending the repertoire of cognitive processes beyond the classical offline functions.

Dopamine lesions alter the striatal encoding of single-limb gait

The striatum serves an important role in motor control, and neurons in this area encode the body's initiation, cessation, and speed of locomotion. However, it remains unclear whether the same neurons also encode the step-by-step rhythmic motor patterns of individual limbs that characterize gait. By combining high-speed video tracking, electrophysiology, and optogenetic tagging, we found that a sizable population of both D1 and D2 receptor expressing medium spiny projection neurons (MSNs) were phase-locked to the gait cycle of individual limbs in mice. Healthy animals showed balanced limb phase-locking between D1 and D2 MSNs, while dopamine depletion led to stronger phase-locking in D2 MSNs. These findings indicate that striatal neurons represent gait on a single-limb and step basis, and suggest that elevated limb phase-locking of D2 MSNs may underlie some of the gait impairments associated with dopamine loss.

Correlated signatures of social behavior in cerebellum and anterior cingulate cortex

The cerebellum has been implicated in the regulation of social behavior. Its influence is thought to arise from communication, via the thalamus, to forebrain regions integral in the expression of social interactions, including the anterior cingulate cortex (ACC). However, the signals encoded or the nature of the communication between the cerebellum and these brain regions is poorly understood. Here, we describe an approach that overcomes technical challenges in exploring the coordination of distant brain regions at high temporal and spatial resolution during social behavior. We developed the E-Scope, an electrophysiology-integrated miniature microscope, to synchronously measure extracellular electrical activity in the cerebellum along with calcium imaging of the ACC. This single coaxial cable device combined these data streams to provide a powerful tool to monitor the activity of distant brain regions in freely behaving animals. During social behavior, we recorded the spike timing of multiple single units in cerebellar right Crus I (RCrus I) Purkinje cells (PCs) or dentate nucleus (DN) neurons while synchronously imaging calcium transients in contralateral ACC neurons. We found that during social interactions a significant subpopulation of cerebellar PCs were robustly inhibited, while most modulated neurons in the DN were activated, and their activity was correlated with positively modulated ACC neurons. These distinctions largely disappeared when only non-social epochs were analyzed suggesting that cerebellar-cortical interactions were behaviorally specific. Our work provides new insights into the complexity of cerebellar activation and co-modulation of the ACC during social behavior and a valuable open-source tool for simultaneous, multimodal recordings in freely behaving mice.

Dopamine lesions alter the striatal encoding of single-limb gait

The striatum serves an important role in motor control, and neurons in this area encode the body's initiation, cessation, and speed of locomotion. However, it remains unclear whether the same neurons also encode the step-by-step rhythmic motor patterns of individual limbs that characterize gait. By combining high-speed video tracking, electrophysiology, and optogenetic tagging, we found that a sizable population of both D1 and D2 receptor expressing medium spiny projection neurons (MSNs) were phase-locked to the gait cycle of individual limbs in mice. Healthy animals showed balanced limb phase-locking between D1 and D2 MSNs, while dopamine depletion led to stronger phase-locking in D2 MSNs. These findings indicate that striatal neurons represent gait on a single-limb and step basis, and suggest that elevated limb phase-locking of D2 MSNs may underlie some of the gait impairments associated with dopamine loss.

Recent Advancements in Graphene-Based Implantable Electrodes for Neural Recording/Stimulation

Implantable electrodes represent a groundbreaking advancement in nervous system research, providing a pivotal tool for recording and stimulating human neural activity. This capability is integral for unraveling the intricacies of the nervous system's functionality and for devising innovative treatments for various neurological disorders. Implantable electrodes offer distinct advantages compared to conventional recording and stimulating neural activity methods. They deliver heightened precision, fewer associated side effects, and the ability to gather data from diverse neural sources. Crucially, the development of implantable electrodes necessitates key attributes: flexibility, stability, and high resolution. Graphene emerges as a highly promising material for fabricating such electrodes due to its exceptional properties. It boasts remarkable flexibility, ensuring seamless integration with the complex and contoured surfaces of neural tissues. Additionally, graphene exhibits low electrical resistance, enabling efficient transmission of neural signals. Its transparency further extends its utility, facilitating compatibility with various imaging techniques and optogenetics. This paper showcases noteworthy endeavors in utilizing graphene in its pure form and as composites to create and deploy implantable devices tailored for neural recordings and stimulations. It underscores the potential for significant advancements in this field. Furthermore, this paper delves into prospective avenues for refining existing graphene-based electrodes, enhancing their suitability for neural recording applications in in vitro and in vivo settings. These future steps promise to revolutionize further our capacity to understand and interact with the neural research landscape.

Recent strategies for neural dynamics observation at a larger scale and wider scope

The tremendous technical progress in neuroscience offers opportunities to observe a more minor or/and broader dynamic picture of the brain. Moreover, the large-scale neural activity of individual neurons enables the dissection of detailed mechanistic links between neural populations and behaviors. To measure neural activity in-vivo, multi-neuron recording, and neuroimaging techniques are employed and developed to acquire more neurons. The tools introduced concurrently recorded dozens to hundreds of neurons in the coordinated brain regions and elucidated the neuronal ensembles from a massive population perspective of diverse neurons at cellular resolution. In particular, the increasing spatiotemporal resolution of neuronal monitoring across the whole brain dramatically facilitates our understanding of additional nervous system functions in health and disease. Here, we will introduce state-of-the-art neuroscience tools involving large-scale neural population recording and the long-range connections spanning multiple brain regions. Their synergic effects provide to clarify the controversial circuitry underlying neuroscience. These challenging neural tools present a promising outlook for the fundamental dynamic interplay across levels of synaptic cellular, circuit organization, and brain-wide. Hence, more observations of neural dynamics will provide more clues to elucidate brain functions and push forward innovative technology at the intersection of neural engineering disciplines. We hope this review will provide insight into the use or development of recent neural techniques considering spatiotemporal scales of brain observation.

Uncoordinated sleep replay across hemispheres in the zebra finch

Bilaterally organized brain regions are often simultaneously active in both humans1,2,3 and animal models,4,5,6,7,8,9 but the extent to which the temporal progression of internally generated dynamics is coordinated across hemispheres and how this coordination changes with brain state remain poorly understood. To address these issues, we investigated the zebra finch courtship song (duration: 0.5-1.0 s), a highly stereotyped complex behavior10,11 produced by a set of bilaterally organized nuclei.12,13,14 Unilateral lesions to these structures can eliminate or degrade singing,13,15,16,17 indicating that both hemispheres are required for song production.18 Additionally, previous work demonstrated broadly coherent and symmetric bilateral premotor signals during song.9 To precisely track the temporal evolution of activity in each hemisphere, we recorded bilaterally in the song production pathway. We targeted the robust nucleus of the arcopallium (RA) in the zebra finch, where population activity reflects the moment-to-moment progression of the courtship song during awake vocalizations19,20,21,22,23,24 and sleep, where song-related network dynamics reemerge in "replay" events.24,25 We found that activity in the left and right RA is synchronized within a fraction of a millisecond throughout song. In stark contrast, the two hemispheres displayed largely independent replay activity during sleep, despite shared interhemispheric arousal levels. These findings demonstrate that the degree of bilateral coordination in the zebra finch song system is dynamically modulated by behavioral state.

DREDge: robust motion correction for high-density extracellular recordings across species

High-density microelectrode arrays (MEAs) have opened new possibilities for systems neuroscience in human and non-human animals, but brain tissue motion relative to the array poses a challenge for downstream analyses, particularly in human recordings. We introduce DREDge (Decentralized Registration of Electrophysiology Data), a robust algorithm which is well suited for the registration of noisy, nonstationary extracellular electrophysiology recordings. In addition to estimating motion from spikes in the action potential (AP) frequency band, DREDge enables automated tracking of motion at high temporal resolution in the local field potential (LFP) frequency band. In human intraoperative recordings, which often feature fast (period <1s) motion, DREDge correction in the LFP band enabled reliable recovery of evoked potentials, and significantly reduced single-unit spike shape variability and spike sorting error. Applying DREDge to recordings made during deep probe insertions in nonhuman primates demonstrated the possibility of tracking probe motion of centimeters across several brain regions while simultaneously mapping single unit electrophysiological features. DREDge reliably delivered improved motion correction in acute mouse recordings, especially in those made with an recent ultra-high density probe. We also implemented a procedure for applying DREDge to recordings made across tens of days in chronic implantations in mice, reliably yielding stable motion tracking despite changes in neural activity across experimental sessions. Together, these advances enable automated, scalable registration of electrophysiological data across multiple species, probe types, and drift cases, providing a stable foundation for downstream scientific analyses of these rich datasets.

Stimulus-Specific Prediction Error Neurons in Mouse Auditory Cortex

Comparing expectation with experience is an important neural computation performed throughout the brain and is a hallmark of predictive processing. Experiments that alter the sensory outcome of an animal's behavior reveal enhanced neural responses to unexpected self-generated stimuli, indicating that populations of neurons in sensory cortex may reflect prediction errors (PEs), mismatches between expectation and experience. However, enhanced neural responses to self-generated stimuli could also arise through nonpredictive mechanisms, such as the movement-based facilitation of a neuron's inherent sound responses. If sensory prediction error neurons exist in sensory cortex, it is unknown whether they manifest as general error responses, or respond with specificity to errors in distinct stimulus dimensions. To answer these questions, we trained mice of either sex to expect the outcome of a simple sound-generating behavior and recorded auditory cortex activity as mice heard either the expected sound or sounds that deviated from expectation in one of multiple distinct dimensions. Our data reveal that the auditory cortex learns to suppress responses to self-generated sounds along multiple acoustic dimensions simultaneously. We identify a distinct population of auditory cortex neurons that are not responsive to passive sounds or to the expected sound but that encode prediction errors. These prediction error neurons are abundant only in animals with a learned motor-sensory expectation, and encode one or two specific violations rather than a generic error signal. Together, these findings reveal that cortical predictions about self-generated sounds have specificity in multiple simultaneous dimensions and that cortical prediction error neurons encode specific violations from expectation.SIGNIFICANCE STATEMENT Audette et. al record neural activity in the auditory cortex while mice perform a sound-generating forelimb movement and measure neural responses to sounds that violate an animal's expectation in different ways. They find that predictions about self-generated sounds are highly specific across multiple stimulus dimensions and that a population of typically nonsound-responsive neurons respond to sounds that violate an animal's expectation in a specific way. These results identify specific prediction error (PE) signals in the mouse auditory cortex and suggest that errors may be calculated early in sensory processing.

Correlated signatures of social behavior in cerebellum and anterior cingulate cortex

The cerebellum has been implicated in the regulation of social behavior. Its influence is thought to arise from communication, via the thalamus, to forebrain regions integral in the expression of social interactions, including the anterior cingulate cortex (ACC). However, the signals encoded or the nature of the communication between the cerebellum and these brain regions is poorly understood. Here, we describe an approach that overcomes technical challenges in exploring the coordination of distant brain regions at high temporal and spatial resolution during social behavior. We developed the E-Scope, an electrophysiology-integrated miniature microscope, to synchronously measure extracellular electrical activity in the cerebellum along with calcium imaging of the ACC. This single coaxial cable device combined these data streams to provide a powerful tool to monitor the activity of distant brain regions in freely behaving animals. During social behavior, we recorded the spike timing of multiple single units in cerebellar right Crus I (RCrus I) Purkinje cells (PCs) or dentate nucleus (DN) neurons while synchronously imaging calcium transients in contralateral ACC neurons. We found that during social interactions a significant subpopulation of cerebellar PCs were robustly inhibited, while most modulated neurons in the DN were activated, and their activity was correlated with positively modulated ACC neurons. These distinctions largely disappeared when only non-social epochs were analyzed suggesting that cerebellar-cortical interactions were behaviorally specific. Our work provides new insights into the complexity of cerebellar activation and co-modulation of the ACC during social behavior and a valuable open-source tool for simultaneous, multimodal recordings in freely behaving mice.

Widespread and Multifaceted Binocular Integration in the Mouse Primary Visual Cortex

The brain combines two-dimensional images received from the two eyes to form a percept of three-dimensional surroundings. This process of binocular integration in the primary visual cortex (V1) serves as a useful model for studying how neural circuits generate emergent properties from multiple input signals. Here, we perform a thorough characterization of binocular integration using electrophysiological recordings in the V1 of awake adult male and female mice by systematically varying the orientation and phase disparity of monocular and binocular stimuli. We reveal widespread binocular integration in mouse V1 and demonstrate that the three commonly studied binocular properties-ocular dominance, interocular matching, and disparity selectivity-are independent of each other. For individual neurons, the responses to monocular stimulation can predict the average amplitude of binocular response but not its selectivity. Finally, the extensive and independent binocular integration of monocular inputs is seen across cortical layers in both regular-spiking and fast-spiking neurons, regardless of stimulus design. Our data indicate that the current model of simple feedforward convergence is inadequate to account for binocular integration in mouse V1, thus suggesting an indispensable role played by intracortical circuits in binocular computation.SIGNIFICANCE STATEMENT Binocular integration is an important step of visual processing that takes place in the visual cortex. Studying the process by which V1 neurons become selective for certain binocular disparities is informative about how neural circuits integrate multiple information streams at a more general level. Here, we systematically characterize binocular integration in mice. Our data demonstrate more widespread and complex binocular integration in mouse V1 than previously reported. Binocular responses cannot be explained by a simple convergence of monocular responses, contrary to the prevailing model of binocular integration. These findings thus indicate that intracortical circuits must be involved in the exquisite computation of binocular disparity, which would endow brain circuits with the plasticity needed for binocular development and processing.

Intrinsic dopamine and acetylcholine dynamics in the striatum of mice

External rewards such as food and money are potent modifiers of behaviour1,2. Pioneering studies established that these salient sensory stimuli briefly interrupt the tonic discharge of neurons that produce the neuromodulators dopamine (DA) and acetylcholine (ACh): midbrain DA neurons (DANs) fire a burst of action potentials that broadly elevates DA in the striatum3,4 at the same time that striatal cholinergic interneurons (CINs) produce a characteristic pause in firing5,6. These phasic responses are thought to create unique, temporally limited conditions that motivate action and promote learning7-11. However, the dynamics of DA and ACh outside explicitly rewarded situations remain poorly understood. Here we show that extracellular DA and ACh levels fluctuate spontaneously and periodically at a frequency of approximately 2 Hz in the dorsal striatum of mice and maintain the same temporal relationship relative to one another as that evoked by reward. We show that this neuromodulatory coordination does not arise from direct interactions between DA and ACh within the striatum. Instead, we provide evidence that periodic fluctuations in striatal DA are inherited from midbrain DANs, while striatal ACh transients are driven by glutamatergic inputs, which act to locally synchronize the spiking of CINs. Together, our findings show that striatal neuromodulatory dynamics are autonomously organized by distributed extra-striatal afferents. The dominance of intrinsic rhythms in DA and ACh offers new insights for explaining how reward-associated neural dynamics emerge and how the brain motivates action and promotes learning from within.

A mosquito mouthpart-like bionic neural probe

Advancements in microscale electrode technology have revolutionized the field of neuroscience and clinical applications by offering high temporal and spatial resolution of recording and stimulation. Flexible neural probes, with their mechanical compliance to brain tissue, have been shown to be superior to rigid devices in terms of stability and longevity in chronic recordings. Shuttle devices are commonly used to assist flexible probe implantation; however, the protective membrane of the brain still makes penetration difficult. Hidden damage to brain vessels during implantation is a significant risk. Inspired by the anatomy of the mosquito mouthparts, we present a biomimetic neuroprobe system that integrates high-sensitivity sensors with a high-fidelity multichannel flexible electrode array. This customizable system achieves distributed and minimally invasive implantation across brain regions. Most importantly, the system's nonvisual monitoring capability provides an early warning detection for intracranial soft tissues, such as vessels, reducing the potential for injury during implantation. The neural probe system demonstrates exceptional sensitivity and adaptability to environmental stimuli, as well as outstanding performance in postoperative and chronic recordings. These findings suggest that our biomimetic neural-probe device offers promising potential for future applications in neuroscience and brain-machine interfaces. A mosquito mouthpart-like bionic neural probe consisting of a highly sensitive tactile sensor module, a flexible microelectrode array, and implanted modules that mimic the structure of mosquito mouthparts. The system enables distributed implantation of electrode arrays across multiple brain regions while making the implantation minimally invasive and avoiding additional dural removal. The tactile sensor array can monitor the implantation process to achieve early warning of vascular damage. The excellent postoperative short-term recording performance and long-term neural activity tracking ability demonstrate that the system is a promising tool in the field of brain-computer interfaces.

Optogenetics reveals paradoxical network stabilizations in hippocampal CA1 and CA3

Recurrent connectivity between excitatory neurons and the strength of feedback from inhibitory neurons are critical determinants of the dynamics and computational properties of neuronal circuits. Toward a better understanding of these circuit properties in regions CA1 and CA3 of the hippocampus, we performed optogenetic manipulations combined with large-scale unit recordings in rats under anesthesia and in quiet waking, using photoinhibition and photoexcitation with different light-sensitive opsins. In both regions, we saw striking paradoxical responses: subsets of cells increased firing during photoinhibition, while other cells decreased firing during photoexcitation. These paradoxical responses were more prominent in CA3 than in CA1, but, notably, CA1 interneurons showed increased firing in response to photoinhibition of CA3. These observations were recapitulated in simulations where we modeled both CA1 and CA3 as inhibition-stabilized networks in which strong recurrent excitation is balanced by feedback inhibition. To directly test the inhibition-stabilized model, we performed large-scale photoinhibition directed at (GAD-Cre) inhibitory cells and found that interneurons in both regions increased firing when photoinhibited, as predicted. Our results highlight the often-paradoxical circuit dynamics that are evidenced during optogenetic manipulations and indicate that, contrary to long-standing dogma, both CA1 and CA3 hippocampal regions display strongly recurrent excitation, which is stabilized through inhibition.

Stimulus-specific prediction error neurons in mouse auditory cortex

Comparing expectation with experience is an important neural computation performed throughout the brain and is a hallmark of predictive processing. Experiments that alter the sensory outcome of an animal's behavior reveal enhanced neural responses to unexpected self-generated stimuli, indicating that populations of neurons in sensory cortex may reflect prediction errors - mismatches between expectation and experience. However, enhanced neural responses to self-generated stimuli could also arise through non-predictive mechanisms, such as the movement-based facilitation of a neuron's inherent sound responses. If sensory prediction error neurons exist in sensory cortex, it is unknown whether they manifest as general error responses, or respond with specificity to errors in distinct stimulus dimensions. To answer these questions, we trained mice to expect the outcome of a simple sound-generating behavior and recorded auditory cortex activity as mice heard either the expected sound or sounds that deviated from expectation in one of multiple distinct dimensions. Our data reveal that the auditory cortex learns to suppress responses to self-generated sounds along multiple acoustic dimensions simultaneously. We identify a distinct population of auditory cortex neurons that are not responsive to passive sounds or to the expected sound but that explicitly encode prediction errors. These prediction error neurons are abundant only in animals with a learned motor-sensory expectation, and encode one or two specific violations rather than a generic error signal.

An open-source head-fixation and implant-protection system for mice

Mice are widely used in neuroscience experiments, which often require head-fixation and attachment of skull-mounted hardware. For many experiments, these components must remain intact over weeks to months, ideally with animals group housed. Many labs have designed ad-hoc head-fixation systems, which is an inefficient process. For example, when reinventing these solutions in our lab, we faced challenges with group housing, wherein mice would chew and damage implanted cannulas and electrodes of their cage mates. We performed several non-trivial design iterations to solve this problem, and present the most successful designs as an open-source collection. The designs include a standard mounting headbar compatible with most skull-mounted hardware, a snap-on protective mouse hat (headhat) to prevent mice from chewing the hardware, and a head-fixation station to facilitate common experimental procedures. We provide 3D-printing files, detail vendors and software used to make the components of the system, and provide editable design files for maximum flexibility to individual lab requirements.

Mice and primates use distinct strategies for visual segmentation

The rodent visual system has attracted great interest in recent years due to its experimental tractability, but the fundamental mechanisms used by the mouse to represent the visual world remain unclear. In the primate, researchers have argued from both behavioral and neural evidence that a key step in visual representation is 'figure-ground segmentation', the delineation of figures as distinct from backgrounds. To determine if mice also show behavioral and neural signatures of figure-ground segmentation, we trained mice on a figure-ground segmentation task where figures were defined by gratings and naturalistic textures moving counterphase to the background. Unlike primates, mice were severely limited in their ability to segment figure from ground using the opponent motion cue, with segmentation behavior strongly dependent on the specific carrier pattern. Remarkably, when mice were forced to localize naturalistic patterns defined by opponent motion, they adopted a strategy of brute force memorization of texture patterns. In contrast, primates, including humans, macaques, and mouse lemurs, could readily segment figures independent of carrier pattern using the opponent motion cue. Consistent with mouse behavior, neural responses to the same stimuli recorded in mouse visual areas V1, RL, and LM also did not support texture-invariant segmentation of figures using opponent motion. Modeling revealed that the texture dependence of both the mouse's behavior and neural responses could be explained by a feedforward neural network lacking explicit segmentation capabilities. These findings reveal a fundamental limitation in the ability of mice to segment visual objects compared to primates.

Acute head-fixed recordings in awake mice with multiple Neuropixels probes

Multi-electrode arrays such as Neuropixels probes enable electrophysiological recordings from large populations of single neurons with high temporal resolution. By using such probes, the activity from functionally interacting, yet distinct, brain regions can be measured simultaneously by inserting multiple probes into the same subject. However, the use of multiple probes in small animals such as mice requires the removal of a sizable fraction of the skull, while also minimizing tissue damage and keeping the brain stable during the recordings. Here, we describe a step-by-step process designed to facilitate reliable recordings from up to six Neuropixels probes simultaneously in awake, head-fixed mice. The procedure involves four stages: the implantation of a headframe and a removable glass coverslip, the precise positioning of the Neuropixels probes at targeted points on the brain surface, the placement of a perforated plastic imaging window and the insertion of the probes into the brain of an awake mouse. The approach provides access to multiple brain regions and has been successfully applied across hundreds of mice. The procedure has been optimized for dense recordings from the mouse visual system, but it can be adapted for alternative recording configurations to target multiple probes in other brain areas. The protocol is suitable for users with experience in stereotaxic surgery in mice.

Neuroprosthetics: from sensorimotor to cognitive disorders

Neuroprosthetics is a multidisciplinary field at the interface between neurosciences and biomedical engineering, which aims at replacing or modulating parts of the nervous system that get disrupted in neurological disorders or after injury. Although neuroprostheses have steadily evolved over the past 60 years in the field of sensory and motor disorders, their application to higher-order cognitive functions is still at a relatively preliminary stage. Nevertheless, a recent series of proof-of-concept studies suggest that electrical neuromodulation strategies might also be useful in alleviating some cognitive and memory deficits, in particular in the context of dementia. Here, we review the evolution of neuroprosthetics from sensorimotor to cognitive disorders, highlighting important common principles such as the need for neuroprosthetic systems that enable multisite bidirectional interactions with the nervous system.

Strong tuning for stereoscopic depth indicates orientation-specific recurrent circuitry in tree shrew V1

Neurons in the primary visual cortex (V1) are tuned to specific disparities between the two retinal images, which form the neural substrate for stereoscopic vision. We show that V1 neurons in tree shrews, but not in mice, display highly selective responses to narrow ranges of disparity in random-dot stereograms. Surprisingly, V1 neurons in both species show similarly strong tuning to gratings of varying interocular phase differences. This stimulus-dependent dissociation of disparity tuning can be explained by a network model that combines both feedforward and recurrent connections. The features of the model connections are supported by cortical organizations specific to each species. We validate this model by identifying putative inhibitory neurons and confirming their predicted disparity tuning in both species. Together, our studies establish a foundation for using tree shrews in studying binocular vision and raise an exciting possibility of how cortical columns could be uniquely important in computing stereoscopic depth.

Precise movement-based predictions in the mouse auditory cortex

Many of the sensations experienced by an organism are caused by their own actions, and accurately anticipating both the sensory features and timing of self-generated stimuli is crucial to a variety of behaviors. In the auditory cortex, neural responses to self-generated sounds exhibit frequency-specific suppression, suggesting that movement-based predictions may be implemented early in sensory processing. However, it remains unknown whether this modulation results from a behaviorally specific and temporally precise prediction, nor is it known whether corresponding expectation signals are present locally in the auditory cortex. To address these questions, we trained mice to expect the precise acoustic outcome of a forelimb movement using a closed-loop sound-generating lever. Dense neuronal recordings in the auditory cortex revealed suppression of responses to self-generated sounds that was specific to the expected acoustic features, to a precise position within the movement, and to the movement that was coupled to sound during training. Prediction-based suppression was concentrated in L2/3 and L5, where deviations from expectation also recruited a population of prediction-error neurons that was otherwise unresponsive. Recording in the absence of sound revealed abundant movement signals in deep layers that were biased toward neurons tuned to the expected sound, as well as expectation signals that were present throughout the cortex and peaked at the time of expected auditory feedback. Together, these findings identify distinct populations of auditory cortical neurons with movement, expectation, and error signals consistent with a learned internal model linking an action to its specific acoustic outcome.

A silk-based self-adaptive flexible opto-electro neural probe

The combination of optogenetics and electrophysiological recording enables high-precision bidirectional interactions between neural interfaces and neural circuits, which provides a promising approach for the study of progressive neurophysiological phenomena. Opto-electrophysiological neural probes with sufficient flexibility and biocompatibility are desirable to match the low mechanical stiffness of brain tissue for chronic reliable performance. However, lack of rigidity poses challenges for the accurate implantation of flexible neural probes with less invasiveness. Herein, we report a hybrid probe (Silk-Optrode) consisting of a silk protein optical fiber and multiple flexible microelectrode arrays. The Silk-Optrode can be accurately inserted into the brain and perform synchronized optogenetic stimulation and multichannel recording in freely behaving animals. Silk plays an important role due to its high transparency, excellent biocompatibility, and mechanical controllability. Through the hydration of the silk optical fiber, the Silk-Optrode probe enables itself to actively adapt to the environment after implantation and reduce its own mechanical stiffness to implant into the brain with high fidelity while maintaining mechanical compliance with the surrounding tissue. The probes with 128 recording channels can detect high-yield well-isolated single units while performing intracranial light stimulation with low optical losses, surpassing previous work of a similar type. Two months of post-surgery results suggested that as-reported Silk-Optrode probes exhibit better implant-neural interfaces with less immunoreactive glial responses and tissue lesions. A silk optical fiber-based Silk-Optrode probe consisting of a natural silk optical fiber and a flexible micro/nano electrode array is reported. The multifunctional soft probe can modify its own Young's modulus through hydration to achieve accurate implantation into the brain. The low optical loss and single-unit recording abilities allow simultaneous optogenetic stimulation and multichannel readout, which expands the applications in the operation and parsing of neural circuits in behavioral animals.

Updates to the guinea pig animal model for in-vivo auditory neuroscience in the low-frequency hearing range

For gaining insight into general principles of auditory processing, it is critical to choose model organisms whose set of natural behaviors encompasses the processes being investigated. This reasoning has led to the development of a variety of animal models for auditory neuroscience research, such as guinea pigs, gerbils, chinchillas, rabbits, and ferrets; but in recent years, the availability of cutting-edge molecular tools and other methodologies in the mouse model have led to waning interest in these unique model species. As laboratories increasingly look to include in-vivo components in their research programs, a comprehensive description of procedures and techniques for applying some of these modern neuroscience tools to a non-mouse small animal model would enable researchers to leverage unique model species that may be best suited for testing their specific hypotheses. In this manuscript, we describe in detail the methods we have developed to apply these tools to the guinea pig animal model to answer questions regarding the neural processing of complex sounds, such as vocalizations. We describe techniques for vocalization acquisition, behavioral testing, recording of auditory brainstem responses and frequency-following responses, intracranial neural signals including local field potential and single unit activity, and the expression of transgenes allowing for optogenetic manipulation of neural activity, all in awake and head-fixed guinea pigs. We demonstrate the rich datasets at the behavioral and electrophysiological levels that can be obtained using these techniques, underscoring the guinea pig as a versatile animal model for studying complex auditory processing. More generally, the methods described here are applicable to a broad range of small mammals, enabling investigators to address specific auditory processing questions in model organisms that are best suited for answering them.

Coarse-to-fine processing drives the efficient coding of natural scenes in mouse visual cortex

The visual system processes sensory inputs sequentially, perceiving coarse information before fine details. Here we study the neural basis of coarse-to-fine processing and its computational benefits in natural vision. We find that primary visual cortical neurons in awake mice respond to natural scenes in a coarse-to-fine manner, primarily driven by individual neurons rapidly shifting their spatial frequency preference from low to high over a brief response period. This shift transforms the population response in a way that counteracts the statistical regularities of natural scenes, thereby reducing redundancy and generating a more efficient neural representation. The increase in representational efficiency does not occur in either dark-reared or anesthetized mice, which show significantly attenuated coarse-to-fine spatial processing. Collectively, these results illustrate that coarse-to-fine processing is state dependent, develops postnatally via visual experience, and provides a computational advantage by generating more efficient representations of the complex spatial statistics of ethologically relevant natural scenes.

Skyberg et al. show that the visual cortex of mice processes natural scenes in a coarse-to-fine manner, driven by individual neuron’s temporal dynamics. These response dynamics, which require visual experience to develop, reduce redundancy in the neural code and lead to more efficient representations of complex visual stimuli.

Breathing coordinates cortico-hippocampal dynamics in mice during offline states

Network dynamics have been proposed as a mechanistic substrate for the information transfer across cortical and hippocampal circuits. However, little is known about the mechanisms that synchronize and coordinate these processes across widespread brain regions during offline states. Here we address the hypothesis that breathing acts as an oscillatory pacemaker, persistently coupling distributed brain circuit dynamics. Using large-scale recordings from a number of cortical and subcortical brain regions in behaving mice, we uncover the presence of an intracerebral respiratory corollary discharge, that modulates neural activity across these circuits. During offline states, the respiratory modulation underlies the coupling of hippocampal sharp-wave ripples and cortical DOWN/UP state transitions, which mediates systems memory consolidation. These results highlight breathing, a perennial brain rhythm, as an oscillatory scaffold for the functional coordination of the limbic circuit that supports the segregation and integration of information flow across neuronal networks during offline states.

Distinct "driving" versus "modulatory" influences of different visual corticothalamic pathways

Higher-order (HO) thalamic nuclei interact extensively and reciprocally with the cerebral cortex. These corticothalamic (CT) interactions are thought to be important for sensation and perception, attention, and many other important brain functions. CT projections to HO thalamic nuclei, such as the visual pulvinar, originate from two different excitatory populations in cortical layers 5 and 6, whereas first-order nuclei (such as the dorsolateral geniculate nucleus; dLGN) only receive layer 6 CT input. It has been proposed that these layer 5 and layer 6 CT pathways have different functional influences on the HO thalamus, but this has never been directly tested. By optogenetically inactivating different CT populations in the primary visual cortex (V1) and recording single-unit activity from V1, dLGN, and pulvinar of awake mice, we demonstrate that layer 5, but not layer 6, CT projections drive visual responses in the pulvinar, even while both pathways provide retinotopic, baseline excitation to their thalamic targets. Inactivating the superior colliculus also suppressed visual responses in the same subregion of the pulvinar, demonstrating that cortical layer 5 and subcortical inputs both contribute to HO visual thalamic activity-even at the level of putative single neurons. Altogether, these results indicate a functional division of "driver" and "modulator" CT pathways from V1 to the visual thalamus in vivo.

Recruitment and inhibitory action of hippocampal axo-axonic cells during behavior

The axon initial segment of hippocampal pyramidal cells is a key subcellular compartment for action potential generation, under GABAergic control by the "chandelier" or axo-axonic cells (AACs). Although AACs are the only cellular source of GABA targeting the initial segment, their in vivo activity patterns and influence over pyramidal cell dynamics are not well understood. We achieved cell-type-specific genetic access to AACs in mice and show that AACs in the hippocampal area CA1 are synchronously activated by episodes of locomotion or whisking during rest. Bidirectional intervention experiments in head-restrained mice performing a random foraging task revealed that AACs inhibit CA1 pyramidal cells, indicating that the effect of GABA on the initial segments in the hippocampus is inhibitory in vivo. Finally, optogenetic inhibition of AACs at specific track locations induced remapping of pyramidal cell place fields. These results demonstrate brain-state-specific dynamics of a critical inhibitory controller of cortical circuits.

Sleep replay reveals premotor circuit structure for a skilled behavior

Neural circuits often exhibit sequences of activity, but the contribution of local networks to their generation remains unclear. In the zebra finch, song-related premotor sequences within HVC may result from some combination of local connectivity and long-range thalamic inputs from nucleus uvaeformis (Uva). Because lesions to either structure abolish song, we examine "sleep replay" using high-density recording methods to reconstruct precise song-related events. Replay activity persists after the upstream nucleus interfacialis of the nidopallium is lesioned and slows when HVC is cooled, demonstrating that HVC provides temporal structure for these events. To further gauge the importance of intra-HVC connectivity for shaping network dynamics, we lesion Uva during sleep and find that residual replay sequences could span syllable boundaries, supporting a model in which HVC can propagate sequences throughout the duration of the song. Our results highlight the power of studying offline activity to investigate behaviorally relevant circuit organization.

Light-weight electrophysiology hardware and software platform for cloud-based neural recording experiments

Objective.Neural activity represents a functional readout of neurons that is increasingly important to monitor in a wide range of experiments. Extracellular recordings have emerged as a powerful technique for measuring neural activity because these methods do not lead to the destruction or degradation of the cells being measured. Current approaches to electrophysiology have a low throughput of experiments due to manual supervision and expensive equipment. This bottleneck limits broader inferences that can be achieved with numerous long-term recorded samples.Approach.We developed Piphys, an inexpensive open source neurophysiological recording platform that consists of both hardware and software. It is easily accessed and controlled via a standard web interface through Internet of Things (IoT) protocols.Main results.We used a Raspberry Pi as the primary processing device along with an Intan bioamplifier. We designed a hardware expansion circuit board and software to enable voltage sampling and user interaction. This standalone system was validated with primary human neurons, showing reliability in collecting neural activity in near real-time.Significance.The hardware modules and cloud software allow for remote control of neural recording experiments as well as horizontal scalability, enabling long-term observations of development, organization, and neural activity at scale.

Nonlinear visuoauditory integration in the mouse superior colliculus

Sensory information from different modalities is processed in parallel, and then integrated in associative brain areas to improve object identification and the interpretation of sensory experiences. The Superior Colliculus (SC) is a midbrain structure that plays a critical role in integrating visual, auditory, and somatosensory input to assess saliency and promote action. Although the response properties of the individual SC neurons to visuoauditory stimuli have been characterized, little is known about the spatial and temporal dynamics of the integration at the population level. Here we recorded the response properties of SC neurons to spatially restricted visual and auditory stimuli using large-scale electrophysiology. We then created a general, population-level model that explains the spatial, temporal, and intensity requirements of stimuli needed for sensory integration. We found that the mouse SC contains topographically organized visual and auditory neurons that exhibit nonlinear multisensory integration. We show that nonlinear integration depends on properties of auditory but not visual stimuli. We also find that a heuristically derived nonlinear modulation function reveals conditions required for sensory integration that are consistent with previously proposed models of sensory integration such as spatial matching and the principle of inverse effectiveness.

Early impairment of thalamocortical circuit activity and coherence in a mouse model of Huntington's disease

Huntington's disease (HD) is a progressive, fatal neurodegenerative disorder characterized by motor, cognitive, and psychiatric disturbances. There is no known cure for HD, but its progressive nature allows for early therapeutic intervention. Currently, much of the research has focused on the striatum, however, there is evidence suggesting that disruption of thalamocortical circuits could underlie some of the early symptoms of HD. Loss of both cortical pyramidal neurons (CPNs) and thalamic neurons occurs in HD patients, and cognitive, somatosensory, and attention deficits precede motor abnormalities. However, the role of thalamocortical pathways in HD progression has been understudied. Here, we measured single unit activity and local field potentials (LFPs) from electrode arrays implanted in the thalamus and primary motor cortex of 4-5 month-old male and female Q175 mice. We assessed neuronal activity under baseline conditions as well as during presentation of rewards delivered via actuation of an audible solenoid valve. HD mice showed a significantly delayed licking response to the reward stimulus. At the same time, neuronal activation to the reward was delayed in thalamic neurons, CPNs and fast-spiking cortical interneurons (FSIs) of HD mice. In addition, thalamocortical coherence increased at lower frequencies in HD relative to wildtype mice. Together, these data provide evidence that impaired cortical and thalamic responses to reward stimuli, and impaired thalamocortical coherence, may play an important early role in motor, cognitive, and learning deficits in HD patients.

Divergence in Population Coding for Space between Dorsal and Ventral CA1

Molecular, anatomic, and behavioral studies show that the hippocampus is structurally and functionally heterogeneous, with dorsal hippocampus implicated in mnemonic processes and spatial navigation and ventral hippocampus involved in affective processes. By performing electrophysiological recordings of large neuronal populations in dorsal and ventral CA1 in head-fixed mice navigating a virtual environment, we found that this diversity resulted in different strategies for population coding of space. Populations of neurons in dorsal CA1 showed more complex patterns of activity, which resulted in a higher dimensionality of neural representations that translated to more information being encoded, as compared ensembles in vCA1. Furthermore, a pairwise maximum entropy model was better at predicting the structure of these global patterns of activity in ventral CA1 as compared with dorsal CA1. Taken together, the different coding strategies we uncovered likely emerge from anatomic and physiological differences along the longitudinal axis of hippocampus and that may, in turn, underpin the divergent ethological roles of dorsal and ventral CA1.

Restoring upper extremity function with brain-machine interfaces

One of the most exciting advances to emerge in neural interface technologies has been the development of real-time brain-machine interface (BMI) neuroprosthetic devices to restore upper extremity function. BMI neuroprostheses, made possible by synergistic advances in neural recording technologies, high-speed computation and signal processing, and neuroscience, have permitted the restoration of volitional movement to patients suffering the loss of upper-extremity function. In this chapter, we review the scientific and technological advances underlying these remarkable devices. After presenting an introduction to the current state of the field, we provide an accessible technical discussion of the two fundamental requirements of a successful neuroprosthesis: signal extraction from the brain and signal decoding that results in robust prosthetic control. We close with a presentation of emerging technologies that are likely to substantially advance the field.

Short-Term Effects of Vagus Nerve Stimulation on Learning and Evoked Activity in Auditory Cortex

Chronic vagus nerve stimulation (VNS) has been shown to facilitate learning, but effects of acute VNS on neural coding and behavior remain less well understood. Ferrets implanted with cuff electrodes on the vagus nerve were trained by classical conditioning on an auditory tone frequency-reward association. One tone was associated with reward while another tone was not. Tone frequencies and reward associations were changed every 2 d, requiring learning of a new relationship. When tones were paired with VNS, animals consistently learned the new association within 2 d. When VNS occurred randomly between trials, learning within 2 d was unreliable. In passively listening animals, neural activity in primary auditory cortex (A1) and pupil size were recorded before and after acute VNS-tone pairing. After pairing with a neuron’s best-frequency (BF) tone, responses by a subpopulation of neurons were reduced. VNS paired with an off-BF tone or during intertrial intervals had no effect. The BF-specific reduction in neural responses after VNS remained, even after regressing out changes explained by pupil-indexed arousal. VNS induced brief dilation in the pupil, and the size of this change predicted the magnitude of persistent changes in the neural response. This interaction suggests that fluctuations in neuromodulation associated with arousal gate the long-term VNS effects on neural activity.

Modular Data Acquisition System for Recording Activity and Electrical Stimulation of Brain Tissue Using Dedicated Electronics

In this paper, we present a modular Data Acquisition (DAQ) system for simultaneous electrical stimulation and recording of brain activity. The DAQ system is designed to work with custom-designed Application Specific Integrated Circuit (ASIC) called Neurostim-3 and a variety of commercially available Multi-Electrode Arrays (MEAs). The system can control simultaneously up to 512 independent bidirectional i.e., input-output channels. We present in-depth insight into both hardware and software architectures and discuss relationships between cooperating parts of that system. The particular focus of this study was the exploration of efficient software design so that it could perform all its tasks in real-time using a standard Personal Computer (PC) without the need for data precomputation even for the most demanding experiment scenarios. Not only do we show bare performance metrics, but we also used this software to characterise signal processing capabilities of Neurostim-3 (e.g., gain linearity, transmission band) so that to obtain information on how well it can handle neural signals in real-world applications. The results indicate that each Neurostim-3 channel exhibits signal gain linearity in a wide range of input signal amplitudes. Moreover, their high-pass cut-off frequency gets close to 0.6Hz making it suitable for recording both Local Field Potential (LFP) and spiking brain activity signals. Additionally, the current stimulation circuitry was checked in terms of the ability to reproduce complex patterns. Finally, we present data acquired using our system from the experiments on a living rat’s brain, which proved we obtained physiological data from non-stimulated and stimulated tissue. The presented results lead us to conclude that our hardware and software can work efficiently and effectively in tandem giving valuable insights into how information is being processed by the brain.

Efficient optogenetic silencing of neurotransmitter release with a mosquito rhodopsin

Information is carried between brain regions through neurotransmitter release from axonal presynaptic terminals. Understanding the functional roles of defined neuronal projection pathways requires temporally precise manipulation of their activity. However, existing inhibitory optogenetic tools have low efficacy and off-target effects when applied to presynaptic terminals, while chemogenetic tools are difficult to control in space and time. Here, we show that a targeting-enhanced mosquito homolog of the vertebrate encephalopsin (eOPN3) can effectively suppress synaptic transmission through the G_i/o signaling pathway. Brief illumination of presynaptic terminals expressing eOPN3 triggers a lasting suppression of synaptic output that recovers spontaneously within minutes in vitro and in vivo. In freely moving mice, eOPN3-mediated suppression of dopaminergic nigrostriatal afferents induces a reversible ipsiversive rotational bias. We conclude that eOPN3 can be used to selectively suppress neurotransmitter release at presynaptic terminals with high spatiotemporal precision, opening new avenues for functional interrogation of long-range neuronal circuits in vivo.

Hybrid Multisite Silicon Neural Probe with Integrated Flexible Connector for Interchangeable Packaging

Multisite neural probes are a fundamental tool to study brain function. Hybrid silicon/polymer neural probes combine rigid silicon and flexible polymer parts into one single device and allow, for example, the precise integration of complex probe geometries, such as multishank designs, with flexible biocompatible cabling. Despite these advantages and benefiting from highly reproducible fabrication methods on both silicon and polymer substrates, they have not been widely available. This paper presents the development, fabrication, characterization, and in vivo electrophysiological assessment of a hybrid multisite multishank silicon probe with a monolithically integrated polyimide flexible interconnect cable. The fabrication process was optimized at wafer level, and several neural probes with 64 gold electrode sites equally distributed along 8 shanks with an integrated 8 µm thick highly flexible polyimide interconnect cable were produced. The monolithic integration of the polyimide cable in the same fabrication process removed the necessity of the postfabrication bonding of the cable to the probe. This is the highest electrode site density and thinnest flexible cable ever reported for a hybrid silicon/polymer probe. Additionally, to avoid the time-consuming bonding of the probe to definitive packaging, the flexible cable was designed to terminate in a connector pad that can mate with commercial zero-insertion force (ZIF) connectors for electronics interfacing. This allows great experimental flexibility because interchangeable packaging can be used according to experimental demands. High-density distributed in vivo electrophysiological recordings were obtained from the hybrid neural probes with low intrinsic noise and high signal-to-noise ratio (SNR).

Recording site placement on planar silicon-based probes affects signal quality in acute neuronal recordings

Multisite, silicon-based probes are widely used tools to record the electrical activity of neuronal populations. Several physical features of these devices are designed to improve their recording performance. Here, our goal was to investigate whether the position of recording sites on the silicon shank might affect the quality of the recorded neural signal in acute experiments. Neural recordings obtained with five different types of high-density, single-shank, planar silicon probes from anesthetized rats were analyzed. Wideband data were filtered to extract spiking activity, then the amplitude distribution of samples and quantitative properties of the recorded brain activity (single unit yield, spike amplitude and isolation distance) were compared between sites located at different positions of the silicon shank, focusing particularly on edge and center sites. Edge sites outperformed center sites: for all five probe types there was a significant difference in the signal power computed from the amplitude distributions, and edge sites recorded significantly more large amplitude samples both in the positive and negative range. Although the single unit yield was similar between site positions, the difference in spike amplitudes was noticeable in the range corresponding to high-amplitude spikes. Furthermore, the advantage of edge sites slightly decreased with decreasing shank width. Our results might aid the design of novel neural implants in enhancing their recording performance by identifying more efficient recording site placements.

Recording site placement on planar silicon-based probes affects signal quality in acute neuronal recordings

Multisite, silicon-based probes are widely used tools to record the electrical activity of neuronal populations. Several physical features of these devices are designed to improve their recording performance. Here, our goal was to investigate whether the position of recording sites on the silicon shank might affect the quality of the recorded neural signal in acute experiments. Neural recordings obtained with five different types of high-density, single-shank, planar silicon probes from anesthetized rats were analyzed. Wideband data were filtered to extract spiking activity, then the amplitude distribution of samples and quantitative properties of the recorded brain activity (single unit yield, spike amplitude and isolation distance) were compared between sites located at different positions of the silicon shank, focusing particularly on edge and center sites. Edge sites outperformed center sites: for all five probe types there was a significant difference in the signal power computed from the amplitude distributions, and edge sites recorded significantly more large amplitude samples both in the positive and negative range. Although the single unit yield was similar between site positions, the difference in spike amplitudes was noticeable in the range corresponding to high-amplitude spikes. Furthermore, the advantage of edge sites slightly decreased with decreasing shank width. Our results might aid the design of novel neural implants in enhancing their recording performance by identifying more efficient recording site placements.

Lack of Evidence for Stereotypical Direction Columns in the Mouse Superior Colliculus

Neurons in the visual system can be spatially organized according to their response properties such as receptive field location and feature selectivity. For example, the visual cortex of many mammalian species contains orientation and direction columns where neurons with similar preferences are clustered. Here, we examine whether such a columnar structure exists in the mouse superior colliculus (SC), a prominent visual center for motion processing. By performing large-scale physiological recording and two-photon calcium imaging in adult male and female mice, we show that direction-selective neurons in the mouse SC are not organized into stereotypical columns as a function of their preferred directions, although clusters of similarly tuned neurons are seen in a minority of mice. Nearby neurons can prefer similar or opposite directions in a largely position-independent manner. This finding holds true regardless of animal state (anesthetized vs awake, running vs stationary), SC depth (most superficial lamina vs deeper in the SC), research technique (calcium imaging vs electrophysiology), and stimulus type (drifting gratings vs moving dots, full field vs small patch). Together, these results challenge recent reports of region-specific organizations in the mouse SC and reveal how motion direction is represented in this important visual center.

Neural Sequences as an Optimal Dynamical Regime for the Readout of Time

Converging evidence suggests that the brain encodes time through dynamically changing patterns of neural activity, including neural sequences, ramping activity, and complex spatiotemporal dynamics. However, the potential computational significance and advantage of these different regimes have remained unaddressed. We combined large-scale recordings and modeling to compare population dynamics between premotor cortex and striatum in mice performing a two-interval timing task. Conventional decoders revealed that the dynamics within each area encoded time equally well; however, the dynamics in striatum exhibited a higher degree of sequentiality. Analysis of premotor and striatal dynamics, together with a large set of simulated prototypical dynamical regimes, revealed that regimes with higher sequentiality allowed a biologically constrained artificial downstream network to better read out time. These results suggest that, although different strategies exist for encoding time in the brain, neural sequences represent an ideal and flexible dynamical regime for enabling downstream areas to read out this information.

Stimulus-specific hypothalamic encoding of a persistent defensive state

Persistent neural activity has been described in cortical, hippocampal, and motor networks as mediating working memory of transiently encountered stimuli^1,2. Internal emotion states such as fear also exhibit persistence following exposure to an inciting stimulus³, but whether slow neural dynamics are involved is not well-studied. SF1⁺/Nr5a1⁺ neurons in the dorsomedial and central subdivisions of the ventromedial hypothalamus (VMHdm/c) are necessary for defensive responses to predators^4–7. Optogenetic activation of VMHdm^SF1 neurons elicits defensive behaviours that outlast stimulation^5,8, suggesting the induction of a persistent internal state of fear or anxiety. Here we show that in response to naturalistic threatening stimuli, VMHdm^SF1 neurons exhibit persistent activity lasting many tens of seconds. This persistent activity was correlated with, and required for, persistent defensive behavior in an open-field assay, and was dependent on neurotransmitter release from VMHdm^SF1 neurons. Stimulation and calcium imaging experiments in acute slices revealed local excitatory connectivity between VMHdm^SF1 neurons. Microendoscopic calcium imaging of VMHdm^SF1 neurons revealed that persistent activity at the population level reflects heterogeneous dynamics among individual cells. Unexpectedly, distinct but overlapping VMHdm^SF1 subpopulations were persistently activated by different modalities of threatening stimuli. Computational modeling suggests that neither recurrent excitation nor slow-acting neuromodulators alone can account for persistent activity that maintains stimulus identity. Our results identify stimulus-specific slow neural dynamics in the hypothalamus, on a time scale orders of magnitude longer than that supporting working memory in the cortex^9,10, as a contributing mechanism underlying a persistent emotion state. (238 words)