The fasciola cinereum of the hippocampal tail as an interventional target in epilepsy.

Targeted tissue ablation involving the anterior hippocampus is the standard of care for patients with drug-resistant mesial temporal lobe epilepsy. However, a substantial proportion continues to suffer from seizures even after surgery. We identified the fasciola cinereum (FC) neurons of the posterior hippocampal tail as an important seizure node in both mice and humans with epilepsy. Genetically defined FC neurons were highly active during spontaneous seizures in epileptic mice, and closed-loop optogenetic inhibition of these neurons potently reduced seizure duration. Furthermore, we specifically targeted and found the prominent involvement of FC during seizures in a cohort of six patients with epilepsy. In particular, targeted lesioning of the FC in a patient reduced the seizure burden present after ablation of anterior mesial temporal structures. Thus, the FC may be a promising interventional target in epilepsy.

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.

Retrograde endocannabinoid signaling at inhibitory synapses in vivo.

Endocannabinoid (eCB)-mediated suppression of inhibitory synapses has been hypothesized, but this has not yet been demonstrated to occur in vivo because of the difficulty in tracking eCB dynamics and synaptic plasticity during behavior. In mice navigating a linear track, we observed location-specific eCB signaling in hippocampal CA1 place cells, and this was detected both in the postsynaptic membrane and the presynaptic inhibitory axons. All-optical in vivo investigation of synaptic responses revealed that postsynaptic depolarization was followed by a suppression of inhibitory synaptic potentials. Furthermore, interneuron-specific cannabinoid receptor deletion altered place cell tuning. Therefore, rapid, postsynaptic, activity-dependent eCB signaling modulates inhibitory synapses on a timescale of seconds during behavior.

Acetylcholine receptor based chemogenetics engineered for neuronal inhibition and seizure control assessed in mice.

Epilepsy is a prevalent disorder involving neuronal network hyperexcitability, yet existing therapeutic strategies often fail to provide optimal patient outcomes. Chemogenetic approaches, where exogenous receptors are expressed in defined brain areas and specifically activated by selective agonists, are appealing methods to constrain overactive neuronal activity. We developed BARNI (Bradanicline- and Acetylcholine-activated Receptor for Neuronal Inhibition), an engineered channel comprised of the α7 nicotinic acetylcholine receptor ligand-binding domain coupled to an α1 glycine receptor anion pore domain. Here we demonstrate that BARNI activation by the clinical stage α7 nicotinic acetylcholine receptor-selective agonist bradanicline effectively suppressed targeted neuronal activity, and controlled both acute and chronic seizures in male mice. Our results provide evidence for the use of an inhibitory acetylcholine-based engineered channel activatable by both exogenous and endogenous agonists as a potential therapeutic approach to treating epilepsy.

Artificial intelligence in epilepsy phenotyping.

Artificial intelligence (AI) allows data analysis and integration at an unprecedented granularity and scale. Here we review the technological advances, challenges, and future perspectives of using AI for electro-clinical phenotyping of animal models and patients with epilepsy. In translational research, AI models accurately identify behavioral states in animal models of epilepsy, allowing identification of correlations between neural activity and interictal and ictal behavior. Clinical applications of AI-based automated and semi-automated analysis of audio and video recordings of people with epilepsy, allow significant data reduction and reliable detection and classification of major motor seizures. AI models can accurately identify electrographic biomarkers of epilepsy, such as spikes, high-frequency oscillations, and seizure patterns. Integrating AI analysis of electroencephalographic, clinical, and behavioral data will contribute to optimizing therapy for patients with epilepsy.

Creation of an albino squid line by CRISPR-Cas9 and its application for in vivo functional imaging of neural activity.

Cephalopods are remarkable among invertebrates for their cognitive abilities, adaptive camouflage, novel structures, and propensity for recoding proteins through RNA editing. Due to the lack of genetically tractable cephalopod models, however, the mechanisms underlying these innovations are poorly understood. Genome editing tools such as CRISPR-Cas9 allow targeted mutations in diverse species to better link genes and function. One emerging cephalopod model, Euprymna berryi, produces large numbers of embryos that can be easily cultured throughout their life cycle and has a sequenced genome. As proof of principle, we used CRISPR-Cas9 in E. berryi to target the gene for tryptophan 2,3 dioxygenase (TDO), an enzyme required for the formation of ommochromes, the pigments present in the eyes and chromatophores of cephalopods. CRISPR-Cas9 ribonucleoproteins targeting tdo were injected into early embryos and then cultured to adulthood. Unexpectedly, the injected specimens were pigmented, despite verification of indels at the targeted sites by sequencing in injected animals (G0s). A homozygote knockout line for TDO, bred through multiple generations, was also pigmented. Surprisingly, a gene encoding indoleamine 2,3, dioxygenase (IDO), an enzyme that catalyzes the same reaction as TDO in vertebrates, was also present in E. berryi. Double knockouts of both tdo and ido with CRISPR-Cas9 produced an albino phenotype. We demonstrate the utility of these albinos for in vivo imaging of Ca2+ signaling in the brain using two-photon microscopy. These data show the feasibility of making gene knockout cephalopod lines that can be used for live imaging of neural activity in these behaviorally sophisticated organisms.

Hidden behavioral fingerprints in epilepsy.

Epilepsy is a major disorder affecting millions of people. Although modern electrophysiological and imaging approaches provide high-resolution access to the multi-scale brain circuit malfunctions in epilepsy, our understanding of how behavior changes with epilepsy has remained rudimentary. As a result, screening for new therapies for children and adults with devastating epilepsies still relies on the inherently subjective, semi-quantitative assessment of a handful of pre-selected behavioral signs of epilepsy in animal models. Here, we use machine learning-assisted 3D video analysis to reveal hidden behavioral phenotypes in mice with acquired and genetic epilepsies and track their alterations during post-insult epileptogenesis and in response to anti-epileptic drugs. These results show the persistent reconfiguration of behavioral fingerprints in epilepsy and indicate that they can be employed for rapid, automated anti-epileptic drug testing at scale.

Galactic cosmic radiation exposure causes multifaceted neurocognitive impairments.

Technological advancements have facilitated the implementation of realistic, terrestrial-based complex 33-beam galactic cosmic radiation simulations (GCR Sim) to now probe central nervous system functionality. This work expands considerably on prior, simplified GCR simulations, yielding new insights into responses of male and female mice exposed to 40-50 cGy acute or chronic radiations relevant to deep space travel. Results of the object in updated location task suggested that exposure to acute or chronic GCR Sim induced persistent impairments in hippocampus-dependent memory formation and reconsolidation in female mice that did not manifest robustly in irradiated male mice. Interestingly, irradiated male mice, but not females, were impaired in novel object recognition and chronically irradiated males exhibited increased aggressive behavior on the tube dominance test. Electrophysiology studies used to evaluate synaptic plasticity in the hippocampal CA1 region revealed significant reductions in long-term potentiation after each irradiation paradigm in both sexes. Interestingly, network-level disruptions did not translate to altered intrinsic electrophysiological properties of CA1 pyramidal cells, whereas acute exposures caused modest drops in excitatory synaptic signaling in males. Ultrastructural analyses of CA1 synapses found smaller postsynaptic densities in larger spines of chronically exposed mice compared to controls and acutely exposed mice. Myelination was also affected by GCR Sim with acutely exposed mice exhibiting an increase in the percent of myelinated axons; however, the myelin sheathes on small calibur (< 0.3 mm) and larger (> 0.5 mm) axons were thinner when compared to controls. Present findings might have been predicted based on previous studies using single and mixed beam exposures and provide further evidence that space-relevant radiation exposures disrupt critical cognitive processes and underlying neuronal network-level plasticity, albeit not to the extent that might have been previously predicted.

Offline memory replay in recurrent neuronal networks emerges from constraints on online dynamics.

During spatial exploration, neural circuits in the hippocampus store memories of sequences of sensory events encountered in the environment. When sensory information is absent during 'offline' resting periods, brief neuronal population bursts can 'replay' sequences of activity that resemble bouts of sensory experience. These sequences can occur in either forward or reverse order, and can even include spatial trajectories that have not been experienced, but are consistent with the topology of the environment. The neural circuit mechanisms underlying this variable and flexible sequence generation are unknown. Here we demonstrate in a recurrent spiking network model of hippocampal area CA3 that experimental constraints on network dynamics such as population sparsity, stimulus selectivity, rhythmicity and spike rate adaptation, as well as associative synaptic connectivity, enable additional emergent properties, including variable offline memory replay. In an online stimulus-driven state, we observed the emergence of neuronal sequences that swept from representations of past to future stimuli on the timescale of the theta rhythm. In an offline state driven only by noise, the network generated both forward and reverse neuronal sequences, and recapitulated the experimental observation that offline memory replay events tend to include salient locations like the site of a reward. These results demonstrate that biological constraints on the dynamics of recurrent neural circuits are sufficient to enable memories of sensory events stored in the strengths of synaptic connections to be flexibly read out during rest and sleep, which is thought to be important for memory consolidation and planning of future behaviour. KEY POINTS: A recurrent spiking network model of hippocampal area CA3 was optimized to recapitulate experimentally observed network dynamics during simulated spatial exploration. During simulated offline rest, the network exhibited the emergent property of generating flexible forward, reverse and mixed direction memory replay events. Network perturbations and analysis of model diversity and degeneracy identified associative synaptic connectivity and key features of network dynamics as important for offline sequence generation. Network simulations demonstrate that population over-representation of salient positions like the site of reward results in biased memory replay.

From single-neuron dynamics to higher-order circuit motifs in control and pathological brain networks.

The convergence of advanced single-cell in vivo functional imaging techniques, computational modelling tools and graph-based network analytics has heralded new opportunities to study single-cell dynamics across large-scale networks, providing novel insights into principles of brain communication and pointing towards potential new strategies for treating neurological disorders. A major recent finding has been the identification of unusually richly connected hub cells that have capacity to synchronize networks and may also be critical in network dysfunction. While hub neurons are traditionally defined by measures that consider solely the number and strength of connections, novel higher-order graph analytics now enables the mining of massive networks for repeating subgraph patterns called motifs. As an illustration of the power offered by higher-order analysis of neuronal networks, we highlight how recent methodological advances uncovered a new functional cell type, the superhub, that is predicted to play a major role in regulating network dynamics. Finally, we discuss open questions that will be critical for assessing the importance of higher-order cellular-scale network analytics in understanding brain function in health and disease.

A tool for monitoring cell type-specific focused ultrasound neuromodulation and control of chronic epilepsy.

Focused ultrasound (FUS) is a powerful tool for noninvasive modulation of deep brain activity with promising therapeutic potential for refractory epilepsy; however, tools for examining FUS effects on specific cell types within the deep brain do not yet exist. Consequently, how cell types within heterogeneous networks can be modulated and whether parameters can be identified to bias these networks in the context of complex behaviors remains unknown. To address this, we developed a fiber Photometry Coupled focused Ultrasound System (PhoCUS) for simultaneously monitoring FUS effects on neural activity of subcortical genetically targeted cell types in freely behaving animals. We identified a parameter set that selectively increases activity of parvalbumin interneurons while suppressing excitatory neurons in the hippocampus. A net inhibitory effect localized to the hippocampus was further confirmed through whole brain metabolic imaging. Finally, these inhibitory selective parameters achieved significant spike suppression in the kainate model of chronic temporal lobe epilepsy, opening the door for future noninvasive therapies.

A consensus statement on detection of hippocampal sharp wave ripples and differentiation from other fast oscillations.

Decades of rodent research have established the role of hippocampal sharp wave ripples (SPW-Rs) in consolidating and guiding experience. More recently, intracranial recordings in humans have suggested their role in episodic and semantic memory. Yet, common standards for recording, detection, and reporting do not exist. Here, we outline the methodological challenges involved in detecting ripple events and offer practical recommendations to improve separation from other high-frequency oscillations. We argue that shared experimental, detection, and reporting standards will provide a solid foundation for future translational discovery.

The Neurodata Without Borders ecosystem for neurophysiological data science.

The neurophysiology of cells and tissues are monitored electrophysiologically and optically in diverse experiments and species, ranging from flies to humans. Understanding the brain requires integration of data across this diversity, and thus these data must be findable, accessible, interoperable, and reusable (FAIR). This requires a standard language for data and metadata that can coevolve with neuroscience. We describe design and implementation principles for a language for neurophysiology data. Our open-source software (Neurodata Without Borders, NWB) defines and modularizes the interdependent, yet separable, components of a data language. We demonstrate NWB's impact through unified description of neurophysiology data across diverse modalities and species. NWB exists in an ecosystem, which includes data management, analysis, visualization, and archive tools. Thus, the NWB data language enables reproduction, interchange, and reuse of diverse neurophysiology data. More broadly, the design principles of NWB are generally applicable to enhance discovery across biology through data FAIRness.

The brain is an immensely complex organ which regulates many of the behaviors that animals need to survive. To understand how the brain works, scientists monitor and record brain activity under different conditions using a variety of experimental techniques. These neurophysiological studies are often conducted on multiple types of cells in the brain as well as a variety of species, ranging from mice to flies, or even frogs and worms. Such a range of approaches provides us with highly informative, complementary 'views' of the brain. However, to form a complete, coherent picture of how the brain works, scientists need to be able to integrate all the data from these different experiments. For this to happen effectively, neurophysiology data need to meet certain criteria: namely, they must be findable, accessible, interoperable, and re-usable (or FAIR for short). However, the sheer diversity of neurophysiology experiments impedes the 'FAIR'-ness of the information obtained from them. To overcome this problem, researchers need a standardized way to communicate their experiments and share their results ­ in other words, a 'standard language' to describe neurophysiology data. Rübel, Tritt, Ly, Dichter, Ghosh et al. therefore set out to create such a language that was not only FAIR, but could also co-evolve with neurophysiology research. First, they produced a computer software program (called Neurodata Without Borders, or NWB for short) which generated and defined the different components of the new standard language. Then, other tools for data management were created to expand the NWB platform using the standardized language. This included data analysis and visualization methods, as well as an 'archive' to store and access data. Testing the new language and associated tools showed that they indeed allowed researchers to access, analyze, and share information from many different types of experiments, in organisms ranging from flies to humans. The NWB software is open-source, meaning that anyone can obtain a copy and make changes to it. Thus, NWB and its associated resources provide the basis for a collaborative, community-based system for sharing neurophysiology data. Rübel et al. hope that NWB will inspire similar developments across other fields of biology that share similar levels of complexity with neurophysiology.

Ripple-selective GABAergic projection cells in the hippocampus.

Ripples are brief high-frequency electrographic events with important roles in episodic memory. However, the in vivo circuit mechanisms coordinating ripple-related activity among local and distant neuronal ensembles are not well understood. Here, we define key characteristics of a long-distance projecting GABAergic cell group in the mouse hippocampus that selectively exhibits high-frequency firing during ripples while staying largely silent during theta-associated states when most other GABAergic cells are active. The high ripple-associated firing commenced before ripple onset and reached its maximum before ripple peak, with the signature theta-OFF, ripple-ON firing pattern being preserved across awake and sleep states. Controlled by septal GABAergic, cholinergic, and CA3 glutamatergic inputs, these ripple-selective cells innervate parvalbumin and cholecystokinin-expressing local interneurons while also targeting a variety of extra-hippocampal regions. These results demonstrate the existence of a hippocampal GABAergic circuit element that is uniquely positioned to coordinate ripple-related neuronal dynamics across neuronal assemblies.

Topological supramolecular network enabled high-conductivity, stretchable organic bioelectronics.

Intrinsically stretchable bioelectronic devices based on soft and conducting organic materials have been regarded as the ideal interface for seamless and biocompatible integration with the human body. A remaining challenge is to combine high mechanical robustness with good electrical conduction, especially when patterned at small feature sizes. We develop a molecular engineering strategy based on a topological supramolecular network, which allows for the decoupling of competing effects from multiple molecular building blocks to meet complex requirements. We obtained simultaneously high conductivity and crack-onset strain in a physiological environment, with direct photopatternability down to the cellular scale. We further collected stable electromyography signals on soft and malleable octopus and performed localized neuromodulation down to single-nucleus precision for controlling organ-specific activities through the delicate brainstem.

Toward Understanding the Diverse Roles of Perisomatic Interneurons in Epilepsy.

Epileptic seizures are associated with excessive neuronal spiking. Perisomatic γ-aminobutyric acid (GABA)ergic interneurons specifically innervate the subcellular domains of postsynaptic excitatory cells that are critical for spike generation. With a revolution in transcriptomics-based cell taxonomy driving the development of novel transgenic mouse lines, selectively monitoring and modulating previously elusive interneuron types is becoming increasingly feasible. Emerging evidence suggests that the three types of hippocampal perisomatic interneurons, axo-axonic cells, along with parvalbumin- and cholecystokinin-expressing basket cells, each follow unique activity patterns in vivo, suggesting distinctive roles in regulating epileptic networks.

A fluorescent sensor for spatiotemporally resolved imaging of endocannabinoid dynamics in vivo.

Endocannabinoids (eCBs) are retrograde neuromodulators with important functions in a wide range of physiological processes, but their in vivo dynamics remain largely uncharacterized. Here we developed a genetically encoded eCB sensor called GRABeCB2.0. GRABeCB2.0 consists of a circular-permutated EGFP and the human CB1 cannabinoid receptor, providing cell membrane trafficking, second-resolution kinetics with high specificity for eCBs, and shows a robust fluorescence response at physiological eCB concentrations. Using GRABeCB2.0, we monitored evoked and spontaneous changes in eCB dynamics in cultured neurons and acute brain slices. We observed spontaneous compartmentalized eCB transients in cultured neurons and eCB transients from single axonal boutons in acute brain slices, suggesting constrained, localized eCB signaling. When GRABeCB2.0 was expressed in the mouse brain, we observed foot shock-elicited and running-triggered eCB signaling in the basolateral amygdala and hippocampus, respectively. In a mouse model of epilepsy, we observed a spreading wave of eCB release that followed a Ca2+ wave through the hippocampus. GRABeCB2.0 is a robust probe for eCB release in vivo.

Imaging the endocannabinoid signaling system.

The endocannabinoid (eCB) system is one of the most widespread neuromodulatory systems in the mammalian brain, with a multifaceted role in functions ranging from development to synaptic plasticity. Endocannabinoids are synthesized on demand from membrane lipid precursors, and act primarily on a single G-protein coupled receptor type, CB1, to carry out diverse functions. Despite the importance of the eCB system both in healthy brain function and in disease, critically important details of eCB signaling remained unknown. How eCBs are released from the membrane, how these lipid molecules are transported between cells, and how the distribution of their receptors is controlled, remained elusive. Recent advances in optical microscopy methods and biosensor engineering may open up new avenues for studying eCB signaling. We summarize applications of superresolution microscopy using single molecule localization to reveal distinct patterns of nanoscale CB1 distribution in neuronal axons and axon terminals. We review single particle tracking studies using quantum dots that allowed visualizing CB1 trajectories. We highlight the recent development of fluorescent eCB biosensors, that revealed spatiotemporally specific eCB release in live cells and live animals. Finally, we discuss future directions where method development may help to advance a precise understanding of eCB signaling.

Bidirectional synaptic plasticity rapidly modifies hippocampal representations.

Learning requires neural adaptations thought to be mediated by activity-dependent synaptic plasticity. A relatively non-standard form of synaptic plasticity driven by dendritic calcium spikes, or plateau potentials, has been reported to underlie place field formation in rodent hippocampal CA1 neurons. Here, we found that this behavioral timescale synaptic plasticity (BTSP) can also reshape existing place fields via bidirectional synaptic weight changes that depend on the temporal proximity of plateau potentials to pre-existing place fields. When evoked near an existing place field, plateau potentials induced less synaptic potentiation and more depression, suggesting BTSP might depend inversely on postsynaptic activation. However, manipulations of place cell membrane potential and computational modeling indicated that this anti-correlation actually results from a dependence on current synaptic weight such that weak inputs potentiate and strong inputs depress. A network model implementing this bidirectional synaptic learning rule suggested that BTSP enables population activity, rather than pairwise neuronal correlations, to drive neural adaptations to experience.

A new housing development in a familiar neighborhood, a wrong turn that ends up lengthening a Sunday stroll: our internal representation of the world requires constant updating, and we need to be able to associate events separated by long intervals of time to finetune future outcome. This often requires neural connections to be altered. A brain region known as the hippocampus is involved in building and maintaining a map of our environment. However, signals from other brain areas can activate silent neurons in the hippocampus when the body is in a specific location by triggering cellular events called dendritic calcium spikes. Milstein et al. explored whether dendritic calcium spikes in the hippocampus could also help the brain to update its map of the world by enabling neurons to stop being active at one location and to start responding at a new position. Experiments in mice showed that calcium spikes could change which features of the environment individual neurons respond to by strengthening or weaking connections between specific cells. Crucially, this mechanism allowed neurons to associate event sequences that unfold over a longer timescale that was more relevant to the ones encountered in day-to-day life. A computational model was then put together, and it demonstrated that dendritic calcium spikes in the hippocampus could enable the brain to make better spatial decisions in future. Indeed, these spikes are driven by inputs from brain regions involved in complex cognitive processes, potentially enabling the delayed outcomes of navigational choices to guide changes in the activity and wiring of neurons. Overall, the work by Milstein et al. advances the understanding of learning and memory in the brain and may inform the design of better systems for artificial learning.

Supramammillary regulation of locomotion and hippocampal activity.

Locomotor speed is a basic input used to calculate one's position, but where this signal comes from is unclear. We identified neurons in the supramammillary nucleus (SuM) of the rodent hypothalamus that were highly correlated with future locomotor speed and reliably drove locomotion when activated. Robust locomotion control was specifically identified in Tac1 (substance P)­expressing (SuMTac1+) neurons, the activation of which selectively controlled the activity of speed-modulated hippocampal neurons. By contrast, Tac1-deficient (SuMTac1−) cells weakly regulated locomotion but potently controlled the spike timing of hippocampal neurons and were sufficient to entrain local network oscillations. These findings emphasize that the SuM not only regulates basic locomotor activity but also selectively shapes hippocampal neural activity in a manner that may support spatial navigation.