Cell-class-specific electric field entrainment of neural activity.

Electric fields affect the activity of neurons and brain circuits, yet how this happens at the cellular level remains enigmatic. Lack of understanding of how to stimulate the brain to promote or suppress specific activity significantly limits basic research and clinical applications. Here, we study how electric fields impact subthreshold and spiking properties of major cortical neuronal classes. We find that neurons in the rodent and human cortex exhibit strong, cell-class-dependent entrainment that depends on stimulation frequency. Excitatory pyramidal neurons, with their slower spike rate, entrain to both slow and fast electric fields, while inhibitory classes like Pvalb and Sst (with their fast spiking) predominantly phase-lock to fast fields. We show that this spike-field entrainment is the result of two effects: non-specific membrane polarization occurring across classes and class-specific excitability properties. Importantly, these properties are present across cortical areas and species. These findings allow for the design of selective and class-specific neuromodulation.

Simple synaptic modulations implement diverse novelty computations.

Detecting novelty is ethologically useful for an organism's survival. Recent experiments characterize how different types of novelty over timescales from seconds to weeks are reflected in the activity of excitatory and inhibitory neuron types. Here, we introduce a learning mechanism, familiarity-modulated synapses (FMSs), consisting of multiplicative modulations dependent on presynaptic or pre/postsynaptic neuron activity. With FMSs, network responses that encode novelty emerge under unsupervised continual learning and minimal connectivity constraints. Implementing FMSs within an experimentally constrained model of a visual cortical circuit, we demonstrate the generalizability of FMSs by simultaneously fitting absolute, contextual, and omission novelty effects. Our model also reproduces functional diversity within cell subpopulations, leading to experimentally testable predictions about connectivity and synaptic dynamics that can produce both population-level novelty responses and heterogeneous individual neuron signals. Altogether, our findings demonstrate how simple plasticity mechanisms within a cortical circuit structure can produce qualitatively distinct and complex novelty responses.

Cell class-specific electric field entrainment of neural activity.

Electric fields affect the activity of neurons and brain circuits, yet how this interaction happens at the cellular level remains enigmatic. Lack of understanding on how to stimulate the human brain to promote or suppress specific activity patterns significantly limits basic research and clinical applications. Here we study how electric fields impact the subthreshold and spiking properties of major cortical neuronal classes. We find that cortical neurons in rodent neocortex and hippocampus as well as human cortex exhibit strong and cell class-dependent entrainment that depends on the stimulation frequency. Excitatory pyramidal neurons with their typically slower spike rate entrain to slow and fast electric fields, while inhibitory classes like Pvalb and SST with their fast spiking predominantly phase lock to fast fields. We show this spike-field entrainment is the result of two effects: non-specific membrane polarization occurring across classes and class-specific excitability properties. Importantly, these properties of spike-field and class-specific entrainment are present in cells across cortical areas and species (mouse and human). These findings open the door to the design of selective and class-specific neuromodulation technologies.

Familiarity modulated synapses model visual cortical circuit novelty responses.

Since environments are constantly in flux, the brain's ability to identify novel stimuli that fall outside its own internal representation of the world is crucial for an organism's survival. Within the mammalian neocortex, inhibitory microcircuits are proposed to regulate activity in an experience-dependent manner and different inhibitory neuron subtypes exhibit distinct novelty responses. Discerning the function of diverse neural circuits and their modulation by experience can be daunting unless one has a biologically plausible mechanism to detect and learn from novel experiences that is both understandable and flexible. Here we introduce a learning mechanism, familiarity modulated synapses (FMSs), through which a network response that encodes novelty emerges from unsupervised synaptic modifications depending only on the presynaptic or both the pre- and postsynaptic activity. FMSs stand apart from other familiarity mechanisms in their simplicity: they operate under continual learning, do not require specialized architecture, and can distinguish novelty rapidly without requiring feedback. Implementing FMSs within a model of a visual cortical circuit that includes multiple inhibitory populations, we simultaneously reproduce three distinct novelty effects recently observed in experimental data from visual cortical circuits in mice: absolute, contextual, and omission novelty. Additionally, our model results in a set of diverse physiological responses across cell subpopulations, allowing us to analyze how their connectivity and synaptic dynamics influences their distinct behavior, leading to predictions that can be tested in experiment. Altogether, our findings demonstrate how experimentally-constrained cortical circuit structure can give rise to qualitatively distinct novelty responses using simple plasticity mechanisms. The flexibility of FMSs opens the door to computationally and theoretically investigating how distinct synapse modulations can lead to a variety of experience-dependent responses in a simple, understandable, and biologically plausible setup.

Target cell-specific synaptic dynamics of excitatory to inhibitory neuron connections in supragranular layers of human neocortex.

Rodent studies have demonstrated that synaptic dynamics from excitatory to inhibitory neuron types are often dependent on the target cell type. However, these target cell-specific properties have not been well investigated in human cortex, where there are major technical challenges in reliably obtaining healthy tissue, conducting multiple patch-clamp recordings on inhibitory cell types, and identifying those cell types. Here, we take advantage of newly developed methods for human neurosurgical tissue analysis with multiple patch-clamp recordings, post-hoc fluorescent in situ hybridization (FISH), machine learning-based cell type classification and prospective GABAergic AAV-based labeling to investigate synaptic properties between pyramidal neurons and PVALB- vs. SST-positive interneurons. We find that there are robust molecular differences in synapse-associated genes between these neuron types, and that individual presynaptic pyramidal neurons evoke postsynaptic responses with heterogeneous synaptic dynamics in different postsynaptic cell types. Using molecular identification with FISH and classifiers based on transcriptomically identified PVALB neurons analyzed by Patch-seq, we find that PVALB neurons typically show depressing synaptic characteristics, whereas other interneuron types including SST-positive neurons show facilitating characteristics. Together, these data support the existence of target cell-specific synaptic properties in human cortex that are similar to rodent, thereby indicating evolutionary conservation of local circuit connectivity motifs from excitatory to inhibitory neurons and their synaptic dynamics.

Sensitivity optimization of a rhodopsin-based fluorescent voltage indicator.

The ability to optically image cellular transmembrane voltages at millisecond-timescale resolutions can offer unprecedented insight into the function of living brains in behaving animals. Here, we present a point mutation that increases the sensitivity of Ace2 opsin-based voltage indicators. We use the mutation to develop Voltron2, an improved chemigeneic voltage indicator that has a 65% higher sensitivity to single APs and 3-fold higher sensitivity to subthreshold potentials than Voltron. Voltron2 retained the sub-millisecond kinetics and photostability of its predecessor, although with lower baseline fluorescence. In multiple in vitro and in vivo comparisons with its predecessor across multiple species, we found Voltron2 to be more sensitive to APs and subthreshold fluctuations. Finally, we used Voltron2 to study and evaluate the possible mechanisms of interneuron synchronization in the mouse hippocampus. Overall, we have discovered a generalizable mutation that significantly increases the sensitivity of Ace2 rhodopsin-based sensors, improving their voltage reporting capability.

Local connectivity and synaptic dynamics in mouse and human neocortex.

We present a unique, extensive, and open synaptic physiology analysis platform and dataset. Through its application, we reveal principles that relate cell type to synaptic properties and intralaminar circuit organization in the mouse and human cortex. The dynamics of excitatory synapses align with the postsynaptic cell subclass, whereas inhibitory synapse dynamics partly align with presynaptic cell subclass but with considerable overlap. Synaptic properties are heterogeneous in most subclass-to-subclass connections. The two main axes of heterogeneity are strength and variability. Cell subclasses divide along the variability axis, whereas the strength axis accounts for substantial heterogeneity within the subclass. In the human cortex, excitatory-to-excitatory synaptic dynamics are distinct from those in the mouse cortex and vary with depth across layers 2 and 3.

Synaptic connectivity to L2/3 of primary visual cortex measured by two-photon optogenetic stimulation.

Understanding cortical microcircuits requires thorough measurement of physiological properties of synaptic connections formed within and between diverse subclasses of neurons. Towards this goal, we combined spatially precise optogenetic stimulation with multicellular recording to deeply characterize intralaminar and translaminar monosynaptic connections to supragranular (L2/3) neurons in the mouse visual cortex. The reliability and specificity of multiphoton optogenetic stimulation were measured across multiple Cre lines, and measurements of connectivity were verified by comparison to paired recordings and targeted patching of optically identified presynaptic cells. With a focus on translaminar pathways, excitatory and inhibitory synaptic connections from genetically defined presynaptic populations were characterized by their relative abundance, spatial profiles, strength, and short-term dynamics. Consistent with the canonical cortical microcircuit, layer 4 excitatory neurons and interneurons within L2/3 represented the most common sources of input to L2/3 pyramidal cells. More surprisingly, we also observed strong excitatory connections from layer 5 intratelencephalic neurons and potent translaminar inhibition from multiple interneuron subclasses. The hybrid approach revealed convergence to and divergence from excitatory and inhibitory neurons within and across cortical layers. Divergent excitatory connections often spanned hundreds of microns of horizontal space. In contrast, divergent inhibitory connections were more frequently measured from postsynaptic targets near each other.

Bright and photostable chemigenetic indicators for extended in vivo voltage imaging.

Genetically encoded voltage indicators (GEVIs) enable monitoring of neuronal activity at high spatial and temporal resolution. However, the utility of existing GEVIs has been limited by the brightness and photostability of fluorescent proteins and rhodopsins. We engineered a GEVI, called Voltron, that uses bright and photostable synthetic dyes instead of protein-based fluorophores, thereby extending the number of neurons imaged simultaneously in vivo by a factor of 10 and enabling imaging for significantly longer durations relative to existing GEVIs. We used Voltron for in vivo voltage imaging in mice, zebrafish, and fruit flies. In the mouse cortex, Voltron allowed single-trial recording of spikes and subthreshold voltage signals from dozens of neurons simultaneously over a 15-minute period of continuous imaging. In larval zebrafish, Voltron enabled the precise correlation of spike timing with behavior.

Sparse recurrent excitatory connectivity in the microcircuit of the adult mouse and human cortex.

Generating a comprehensive description of cortical networks requires a large-scale, systematic approach. To that end, we have begun a pipeline project using multipatch electrophysiology, supplemented with two-photon optogenetics, to characterize connectivity and synaptic signaling between classes of neurons in adult mouse primary visual cortex (V1) and human cortex. We focus on producing results detailed enough for the generation of computational models and enabling comparison with future studies. Here, we report our examination of intralaminar connectivity within each of several classes of excitatory neurons. We find that connections are sparse but present among all excitatory cell classes and layers we sampled, and that most mouse synapses exhibited short-term depression with similar dynamics. Synaptic signaling between a subset of layer 2/3 neurons, however, exhibited facilitation. These results contribute to a body of evidence describing recurrent excitatory connectivity as a conserved feature of cortical microcircuits.

A biophysical modelling platform of the cochlear nucleus and other auditory circuits: From channels to networks.

Models of the auditory brainstem have been an invaluable tool for testing hypotheses about auditory information processing and for highlighting the most important gaps in the experimental literature. Due to the complexity of the auditory brainstem, and indeed most brain circuits, the dynamic behavior of the system may be difficult to predict without a detailed, biologically realistic computational model. Despite the sensitivity of models to their exact construction and parameters, most prior models of the cochlear nucleus have incorporated only a small subset of the known biological properties. This confounds the interpretation of modelling results and also limits the potential future uses of these models, which require a large effort to develop. To address these issues, we have developed a general purpose, biophysically detailed model of the cochlear nucleus for use both in testing hypotheses about cochlear nucleus function and also as an input to models of downstream auditory nuclei. The model implements conductance-based Hodgkin-Huxley representations of cells using a Python-based interface to the NEURON simulator. Our model incorporates most of the quantitatively characterized intrinsic cell properties, synaptic properties, and connectivity available in the literature, and also aims to reproduce the known response properties of the canonical cochlear nucleus cell types. Although we currently lack the empirical data to completely constrain this model, our intent is for the model to continue to incorporate new experimental results as they become available.

ACQ4: an open-source software platform for data acquisition and analysis in neurophysiology research.

The complexity of modern neurophysiology experiments requires specialized software to coordinate multiple acquisition devices and analyze the collected data. We have developed ACQ4, an open-source software platform for performing data acquisition and analysis in experimental neurophysiology. This software integrates the tasks of acquiring, managing, and analyzing experimental data. ACQ4 has been used primarily for standard patch-clamp electrophysiology, laser scanning photostimulation, multiphoton microscopy, intrinsic imaging, and calcium imaging. The system is highly modular, which facilitates the addition of new devices and functionality. The modules included with ACQ4 provide for rapid construction of acquisition protocols, live video display, and customizable analysis tools. Position-aware data collection allows automated construction of image mosaics and registration of images with 3-dimensional anatomical atlases. ACQ4 uses free and open-source tools including Python, NumPy/SciPy for numerical computation, PyQt for the user interface, and PyQtGraph for scientific graphics. Supported hardware includes cameras, patch clamp amplifiers, scanning mirrors, lasers, shutters, Pockels cells, motorized stages, and more. ACQ4 is available for download at http://www.acq4.org.

A map of functional synaptic connectivity in the mouse anteroventral cochlear nucleus.

The cochlear nuclei are the first central processors of auditory information and provide inputs to all the major brainstem and midbrain auditory nuclei. Although the local circuits within the cochlear nuclei are understood at a cellular level, the spatial patterns of connectivity and the connection strengths in these circuits have been less well characterized. We have applied a novel, quantitative approach to mapping local circuits projecting to cells in the mouse anteroventral cochlear nucleus (AVCN) using laser-scanning photostimulation and glutamate uncaging. The amplitude and kinetics of individual evoked synaptic events were measured to reveal the patterns and strengths of synaptic connections. We found that the two major excitatory projection cell classes, the bushy and T-stellate cells, receive a spatially broad inhibition from D-stellate cells in the AVCN, and a spatially confined inhibition from the tuberculoventral cells of the dorsal cochlear nucleus. Furthermore, T-stellate cells integrate D-stellate inhibition from an area that spans twice the frequency range of that integrated by bushy cells. A subset of both bushy and T-stellate cells receives inhibition from an unidentified cell population at the dorsal-medial boundary of the AVCN. A smaller subset of cells receives local excitation from within the AVCN. Our results show that inhibitory circuits can have target-specific patterns of spatial convergence, synaptic strength, and receptor kinetics, resulting in different spectral and temporal processing capabilities.

A novel form of motility in filopodia revealed by imaging myosin-X at the single-molecule level.

Although many proteins, receptors, and viruses are transported rearward along filopodia by retrograde actin flow, it is less clear how molecules move forward in filopodia. Myosin-X (Myo10) is an actin-based motor hypothesized to use its motor activity to move forward along actin filaments to the tips of filopodia. Here we use a sensitive total internal reflection fluorescence (TIRF) microscopy system to directly visualize the movements of GFP-Myo10. This reveals a novel form of motility at or near the single-molecule level in living cells wherein extremely faint particles of Myo10 move in a rapid and directed fashion toward the filopodial tip. These fast forward movements occur at approximately 600 nm/s over distances of up to approximately 10 microm and require Myo10 motor activity and actin filaments. As expected for imaging at the single-molecule level, the faint particles of GFP-Myo10 are diffraction limited, have an intensity range similar to single GFP molecules, and exhibit stepwise bleaching. Faint particles of GFP-Myo5a can also move toward the filopodial tip, but at a slower characteristic velocity of approximately 250 nm/s. Similar movements were not detected with GFP-Myo1a, indicating that not all myosins are capable of intrafilopodial motility. These data indicate the existence of a novel system of long-range transport based on the rapid movement of myosin molecules along filopodial actin filaments.

Fiber-coupled light-emitting diode for localized photostimulation of neurons expressing channelrhodopsin-2.

Channelrhodopsin-2 (ChR2) is a blue-light-gated ion channel that can be used to stimulate genetically defined neurons reproducibly, rapidly and non-invasively. Existing approaches for delivering light to cells expressing ChR2 rely upon microscopes, lasers, arc lamps and shutters, all of which are relatively expensive and are not readily scalable for use on more than one brain region or animal at a time. In this paper, we describe an inexpensive method for delivering blue light locally and with millisecond precision to cells expressing ChR2. We accomplished this by coupling the light from a high-intensity blue light-emitting diode (LED; XLamp XR-E from CREE) into an optical fiber. When positioned in proximity to ChR2-expressing HEK293 cells, this fiber-coupled LED provided localized illumination of up to 32mW/mm2 and generated ChR2 photocurrents as efficiently as wide-field mercury arc lamp illumination. This fiber-coupled LED was also used to photostimulate action potentials in ChR2-expressing dorsal root ganglia (DRG) sensory neurons. LED light power and pulse frequency were controlled with an inexpensive, custom-built amplifier circuit. This scalable fiber-coupled LED system can be used to deliver light independent of the microscope objective and could, in principle, deliver light in parallel to multiple brain regions or to multiple genetically engineered animals.