GraFT: Graph Filtered Temporal Dictionary Learning for Functional Neural Imaging.

Optical imaging of calcium signals in the brain has enabled researchers to observe the activity of hundreds-to-thousands of individual neurons simultaneously. Current methods predominantly use morphological information, typically focusing on expected shapes of cell bodies, to better identify neurons in the field-of-view. The explicit shape constraints limit the applicability of automated cell identification to other important imaging scales with more complex morphologies, e.g., dendritic or widefield imaging. Specifically, fluorescing components may be broken up, incompletely found, or merged in ways that do not accurately describe the underlying neural activity. Here we present Graph Filtered Temporal Dictionary (GraFT), a new approach that frames the problem of isolating independent fluorescing components as a dictionary learning problem. Specifically, we focus on the time-traces-the main quantity used in scientific discovery-and learn a time trace dictionary with the spatial maps acting as the presence coefficients encoding which pixels the time-traces are active in. Furthermore, we present a novel graph filtering model which redefines connectivity between pixels in terms of their shared temporal activity, rather than spatial proximity. This model greatly eases the ability of our method to handle data with complex non-local spatial structure. We demonstrate important properties of our method, such as robustness to morphology, simultaneously detecting different neuronal types, and implicitly inferring number of neurons, on both synthetic data and real data examples. Specifically, we demonstrate applications of our method to calcium imaging both at the dendritic, somatic, and widefield scales.

Dynamic compartmental computations in tuft dendrites of layer 5 neurons during motor behavior.

Tuft dendrites of layer 5 pyramidal neurons form specialized compartments important for motor learning and performance, yet their computational capabilities remain unclear. Structural-functional mapping of the tuft tree from the motor cortex during motor tasks revealed two morphologically distinct populations of layer 5 pyramidal tract neurons (PTNs) that exhibit specific tuft computational properties. Early bifurcating and large nexus PTNs showed marked tuft functional compartmentalization, representing different motor variable combinations within and between their two tuft hemi-trees. By contrast, late bifurcating and smaller nexus PTNs showed synchronous tuft activation. Dendritic structure and dynamic recruitment of the N-methyl-d-aspartate (NMDA)-spiking mechanism explained the differential compartmentalization patterns. Our findings support a morphologically dependent framework for motor computations, in which independent amplification units can be combinatorically recruited to represent different motor sequences within the same tree.

Plasticity of olfactory bulb inputs mediated by dendritic NMDA-spikes in rodent piriform cortex.

The piriform cortex (PCx) is essential for learning of odor information. The current view postulates that odor learning in the PCx is mainly due to plasticity in intracortical (IC) synapses, while odor information from the olfactory bulb carried via the lateral olfactory tract (LOT) is 'hardwired.' Here, we revisit this notion by studying location- and pathway-dependent plasticity rules. We find that in contrast to the prevailing view, synaptic and optogenetically activated LOT synapses undergo strong and robust long-term potentiation (LTP) mediated by only a few local NMDA-spikes delivered at theta frequency, while global spike timing-dependent plasticity (STDP) protocols failed to induce LTP in these distal synapses. In contrast, IC synapses in apical and basal dendrites undergo plasticity with both NMDA-spikes and STDP protocols but to a smaller extent compared with LOT synapses. These results are consistent with a self-potentiating mechanism of odor information via NMDA-spikes that can form branch-specific memory traces of odors that can further associate with contextual IC information via STDP mechanisms to provide cognitive and emotional value to odors.

State-Dependent Synchrony and Functional Connectivity in the Primary and Secondary Whisker Somatosensory Cortices.

Synchronized activity plays an important role in sensory coding and memory and is a hallmark of functional network connectivity. However, the effect of sensory activation on synchronization and cortical functional connectivity is largely unknown. In this study, we investigated the effect of whisker activation on synchronization and functional connectivity of the primary (wS1) and secondary (wS2) whisker somatosensory cortices at the single-cell level. The results showed that during the spontaneous pre-stimulus state, neurons tended to be functionally connected with nearby neurons which shared similar tuning characteristics. Whisker activation using either ramp-and-hold stimulation or artificial whisking against sandpaper has significantly reduced the average overall pairwise synchronization and functional connectivity within the wS1 barrel and wS2 cortices. Whisker stimulation disconnected approximately a third of neuronal pairs that were functionally connected during the unstimulated state. Nearby neurons with congruent tuning properties were more likely to remain functionally connected during whisker activation. The findings of this study indicated that cortical somatosensory networks are organized in non-random small world networks composed of neurons sharing relatively similar tuning properties. Sensory whisker activation intensifies these properties and further subdivides the cortical network into smaller more functionally uniform subnetworks, which possibly serve to increase the computational capacity of the network.

Intrinsic Disruption of the M1 Cortical Network in a Mouse Model of Parkinson's Disease.

BACKGROUND: Parkinson's disease (PD) disrupts motor performance by affecting the basal ganglia system. Yet, despite the critical position of the primary motor cortex in linking basal ganglia computations with motor performance, its contribution to motor disability in PD is largely unknown. The objective of this study was to characterize the role of the primary motor cortex in PD-related motor disability. METHODS: Two-photon calcium imaging and optogenetic stimulation of primary motor cortex neurons was done during performance of a dexterous reach-to-grasp motor task in control and 6-hydroxydopamine-induced PD mice. RESULTS: Experimental PD disrupted performance of the reach-to-grasp motor task and especially initiation of the task, which was partially restored by optogenetic activation of the primary motor cortex. Two-photon calcium imaging during task performance revealed experimental-PD affected the primary motor cortex in a cell-type-specific manner. It suppressed activation of output layer 5 pyramidal tract neurons, with greater effects on freeze versus nonfreeze trials. In contrast, it did not attenuate the initial movement-related activation response of layer 2/3 pyramidal neurons while diminishing the late inhibitory phase of their response. At the network level, experimental PD disrupted movement-related population dynamics of the layer 5 pyramidal tract network while almost not affecting the dynamics of the layer 2/3 neuronal population. It also disrupted short- and long-term robustness and stability of the pyramidal tract subnetwork, with reduced intertrial temporal accuracy and diminished reproducibility of motor parameter encoding and temporal recruitment of the output pyramidal tract neurons over repeated daily sessions. CONCLUSIONS: Experimental PD disrupts both external driving and intrinsic properties of the primary motor cortex. Motor disability in experimental PD results primarily from the inability to generate robust and stable output motor sequences in the parkinsonian primary motor cortex output layer 5 pyramidal tract subnetwork. © 2021 International Parkinson and Movement Disorder Society.

Cell-Type-Specific Outcome Representation in the Primary Motor Cortex.

Adaptive movements are critical for animal survival. To guide future actions, the brain monitors various outcomes, including achievement of movement and appetitive goals. The nature of these outcome signals and their neuronal and network realization in the motor cortex (M1), which directs skilled movements, is largely unknown. Using a dexterity task, calcium imaging, optogenetic perturbations, and behavioral manipulations, we studied outcome signals in the murine forelimb M1. We found two populations of layer 2-3 neurons, termed success- and failure-related neurons, that develop with training, and report end results of trials. In these neurons, prolonged responses were recorded after success or failure trials independent of reward and kinematics. In addition, the initial state of layer 5 pyramidal tract neurons contained a memory trace of the previous trial's outcome. Intertrial cortical activity was needed to learn new task requirements. These M1 layer-specific performance outcome signals may support reinforcement motor learning of skilled behavior.

NMDA spikes mediate amplification of inputs in the rat piriform cortex.

The piriform cortex (PCx) receives direct input from the olfactory bulb (OB) and is the brain's main station for odor recognition and memory. The transformation of the odor code from OB to PCx is profound: mitral and tufted cells in olfactory glomeruli respond to individual odorant molecules, whereas pyramidal neurons (PNs) in the PCx responds to multiple, apparently random combinations of activated glomeruli. How these 'discontinuous' receptive fields are formed from OB inputs remains unknown. Counter to the prevailing view that olfactory PNs sum their inputs passively, we show for the first time that NMDA spikes within individual dendrites can both amplify OB inputs and impose combination selectivity upon them, while their ability to compartmentalize voltage signals allows different dendrites to represent different odorant combinations. Thus, the 2-layer integrative behavior of olfactory PN dendrites provides a parsimonious account for the nonlinear remapping of the odor code from bulb to cortex.

The Many Worlds of Plasticity Rules.

Two recent papers have tackled the fundamental questions of how place fields are formed in a new environment and what plasticity mechanisms contribute to this process. Bittner et al., in their recent publication, discovered a novel plasticity rule that, in contrast to previous rules, spans the behavioral, seconds-long, timescale. Sheffield et al. have monitored, for the first time, dendritic activity during place field formation, and show the emergence of spatially tuned local NMDA spikes in basal dendrites of CA1 neurons. Together, these papers suggest that multiple complementary dendritic plasticity mechanisms may contribute to place field formation in changing environmental contexts.

Synaptic plasticity in dendrites: complications and coping strategies.

The elaborate morphology, nonlinear membrane mechanisms and spatiotemporally varying synaptic activation patterns of dendrites complicate the expression, compartmentalization and modulation of synaptic plasticity. To grapple with this complexity, we start with the observation that neurons in different brain areas face markedly different learning problems, and dendrites of different neuron types contribute to the cell's input-output function in markedly different ways. By committing to specific assumptions regarding a neuron's learning problem and its input-output function, specific inferences can be drawn regarding the synaptic plasticity mechanisms and outcomes that we 'ought' to expect for that neuron. Exploiting this assumption-driven approach can help both in interpreting existing experimental data and designing future experiments aimed at understanding the brain's myriad learning processes.

Feedforward motor information enhances somatosensory responses and sharpens angular tuning of rat S1 barrel cortex neurons.

The primary vibrissae motor cortex (vM1) is responsible for generating whisking movements. In parallel, vM1 also sends information directly to the sensory barrel cortex (vS1). In this study, we investigated the effects of vM1 activation on processing of vibrissae sensory information in vS1 of the rat. To dissociate the vibrissae sensory-motor loop, we optogenetically activated vM1 and independently passively stimulated principal vibrissae. Optogenetic activation of vM1 supra-linearly amplified the response of vS1 neurons to passive vibrissa stimulation in all cortical layers measured. Maximal amplification occurred when onset of vM1 optogenetic activation preceded vibrissa stimulation by 20 ms. In addition to amplification, vM1 activation also sharpened angular tuning of vS1 neurons in all cortical layers measured. Our findings indicated that in addition to output motor signals, vM1 also sends preparatory signals to vS1 that serve to amplify and sharpen the response of neurons in the barrel cortex to incoming sensory input signals.

A Designer AAV Variant Permits Efficient Retrograde Access to Projection Neurons.

Efficient retrograde access to projection neurons for the delivery of sensors and effectors constitutes an important and enabling capability for neural circuit dissection. Such an approach would also be useful for gene therapy, including the treatment of neurodegenerative disorders characterized by pathological spread through functionally connected and highly distributed networks. Viral vectors, in particular, are powerful gene delivery vehicles for the nervous system, but all available tools suffer from inefficient retrograde transport or limited clinical potential. To address this need, we applied in vivo directed evolution to engineer potent retrograde functionality into the capsid of adeno-associated virus (AAV), a vector that has shown promise in neuroscience research and the clinic. A newly evolved variant, rAAV2-retro, permits robust retrograde access to projection neurons with efficiency comparable to classical synthetic retrograde tracers and enables sufficient sensor/effector expression for functional circuit interrogation and in vivo genome editing in targeted neuronal populations. VIDEO ABSTRACT.

A Novel Form of Local Plasticity in Tuft Dendrites of Neocortical Somatosensory Layer 5 Pyramidal Neurons.

Tuft dendrites of layer 5 pyramidal neurons form a separate biophysical and processing compartment. Presently, little is known about plasticity mechanisms in this isolated compartment. Here, we describe a novel form of plasticity in which unpaired low-frequency (0.1 Hz) stimulation of tuft inputs resulted in prolonged transient (86.3 ± 7.3 min) potentiation of EPSPs (286.1% ± 30.5%) and enhanced local excitability that enabled more-efficient back-propagation of axo-somatic action potentials and dendritic calcium spikes selectively into the activated dendritic segments. This plasticity was exclusive to tuft dendrites and did not occur in basal dendrites. Induction of this plasticity depended on activation of Kv4.2 potassium and NMDAR channels, internalization of membrane proteins, and insertion of AMPAR. This unique form of tuft plasticity increases proximal-distal electrical coupling of activated tuft dendrites and opens a prolonged time window for binding and storing feedforward and feedback information in a branch-specific manner.

The alanine-serine-cysteine-1 (Asc-1) transporter controls glycine levels in the brain and is required for glycinergic inhibitory transmission.

Asc-1 (SLC7A10) is an amino acid transporter whose deletion causes neurological abnormalities and early postnatal death in mice. Using metabolomics and behavioral and electrophysiological methods, we demonstrate that Asc-1 knockout mice display a marked decrease in glycine levels in the brain and spinal cord along with impairment of glycinergic inhibitory transmission, and a hyperekplexia-like phenotype that is rescued by replenishing brain glycine. Asc-1 works as a glycine and L-serine transporter, and its transport activity is required for the subsequent conversion of L-serine into glycine in vivo. Asc-1 is a novel regulator of glycine metabolism and a candidate for hyperekplexia disorders.

Texture coarseness responsive neurons and their mapping in layer 2-3 of the rat barrel cortex in vivo.

Texture discrimination is a fundamental function of somatosensory systems, yet the manner by which texture is coded and spatially represented in the barrel cortex are largely unknown. Using in vivo two-photon calcium imaging in the rat barrel cortex during artificial whisking against different surface coarseness or controlled passive whisker vibrations simulating different coarseness, we show that layer 2-3 neurons within barrel boundaries differentially respond to specific texture coarsenesses, while only a minority of neurons responded monotonically with increased or decreased surface coarseness. Neurons with similar preferred texture coarseness were spatially clustered. Multi-contact single unit recordings showed a vertical columnar organization of texture coarseness preference in layer 2-3. These findings indicate that layer 2-3 neurons perform high hierarchical processing of tactile information, with surface coarseness embodied by distinct neuronal subpopulations that are spatially mapped onto the barrel cortex.

An Augmented Two-Layer Model Captures Nonlinear Analog Spatial Integration Effects in Pyramidal Neuron Dendrites.

In pursuit of the goal to understand and eventually reproduce the diverse functions of the brain, a key challenge lies in reverse engineering the peculiar biology-based "technology" that underlies the brain's remarkable ability to process and store information. The basic building block of the nervous system is the nerve cell, or "neuron," yet after more than 100 years of neurophysiological study and 60 years of modeling, the information processing functions of individual neurons, and the parameters that allow them to engage in so many different types of computation (sensory, motor, mnemonic, executive, etc.) remain poorly understood. In this paper, we review both historical and recent findings that have led to our current understanding of the analog spatial processing capabilities of dendrites, the major input structures of neurons, with a focus on the principal cell type of the neocortex and hippocampus, the pyramidal neuron (PN). We encapsulate our current understanding of PN dendritic integration in an abstract layered model whose spatially sensitive branch-subunits compute multidimensional sigmoidal functions. Unlike the 1-D sigmoids found in conventional neural network models, multidimensional sigmoids allow the cell to implement a rich spectrum of nonlinear modulation effects directly within their dendritic trees.

Active properties of neocortical pyramidal neuron dendrites.

Dendrites are the main recipients of synaptic inputs and are important sites that determine neurons' input-output functions. This review focuses on thin neocortical dendrites, which receive the vast majority of synaptic inputs in cortex but also have specialized electrogenic properties. We present a simplified working-model biophysical scheme of pyramidal neurons that attempts to capture the essence of their dendritic function, including the ability to behave under plausible conditions as dynamic computational subunits. We emphasize the electrogenic capabilities of NMDA receptors (NMDARs) because these transmitter-gated channels seem to provide the major nonlinear depolarizing drive in thin dendrites, even allowing full-blown NMDA spikes. We show how apparent discrepancies in experimental findings can be reconciled and discuss the current status of dendritic spikes in vivo; a dominant NMDAR contribution would indicate that the input-output relations of thin dendrites are dynamically set by network activity and cannot be fully predicted by purely reductionist approaches.

Nonlinear dendritic processing determines angular tuning of barrel cortex neurons in vivo.

Layer 4 neurons in primary sensory cortices receive direct sensory information from the external world. A general feature of these neurons is their selectivity to specific features of the sensory stimulation. Various theories try to explain the manner in which these neurons are driven by their incoming sensory information. In all of these theories neurons are regarded as simple elements summing small biased inputs to create tuned output through the axosomatic amplification mechanism. However, the possible role of active dendritic integration in further amplifying the sensory responses and sharpening the tuning curves of neurons is disregarded. Our findings show that dendrites of layer 4 spiny stellate neurons in the barrel cortex can generate local and global multi-branch N-methyl-D-aspartate (NMDA) spikes, which are the main regenerative events in these dendrites. In turn, these NMDA receptor (NMDAR) regenerative mechanisms can sum supralinearly the coactivated thalamocortical and corticocortical inputs. Using in vivo whole-cell recordings combined with an intracellular NMDAR blocker and membrane hyperpolarization, we show that dendritic NMDAR-dependent regenerative responses contribute substantially to the angular tuning of layer 4 neurons by preferentially amplifying the preferred angular directions over non-preferred angles. Taken together, these findings indicate that dendritic NMDAR regenerative amplification mechanisms contribute markedly to sensory responses and critically determine the tuning of cortical neurons.

Location-dependent excitatory synaptic interactions in pyramidal neuron dendrites.

Neocortical pyramidal neurons (PNs) receive thousands of excitatory synaptic contacts on their basal dendrites. Some act as classical driver inputs while others are thought to modulate PN responses based on sensory or behavioral context, but the biophysical mechanisms that mediate classical-contextual interactions in these dendrites remain poorly understood. We hypothesized that if two excitatory pathways bias their synaptic projections towards proximal vs. distal ends of the basal branches, the very different local spike thresholds and attenuation factors for inputs near and far from the soma might provide the basis for a classical-contextual functional asymmetry. Supporting this possibility, we found both in compartmental models and electrophysiological recordings in brain slices that the responses of basal dendrites to spatially separated inputs are indeed strongly asymmetric. Distal excitation lowers the local spike threshold for more proximal inputs, while having little effect on peak responses at the soma. In contrast, proximal excitation lowers the threshold, but also substantially increases the gain of distally-driven responses. Our findings support the view that PN basal dendrites possess significant analog computing capabilities, and suggest that the diverse forms of nonlinear response modulation seen in the neocortex, including uni-modal, cross-modal, and attentional effects, could depend in part on pathway-specific biases in the spatial distribution of excitatory synaptic contacts onto PN basal dendritic arbors.

Location-dependent effects of inhibition on local spiking in pyramidal neuron dendrites.

Cortical computations are critically dependent on interactions between pyramidal neurons (PNs) and a menagerie of inhibitory interneuron types. A key feature distinguishing interneuron types is the spatial distribution of their synaptic contacts onto PNs, but the location-dependent effects of inhibition are mostly unknown, especially under conditions involving active dendritic responses. We studied the effect of somatic vs. dendritic inhibition on local spike generation in basal dendrites of layer 5 PNs both in neocortical slices and in simple and detailed compartmental models, with equivalent results: somatic inhibition divisively suppressed the amplitude of dendritic spikes recorded at the soma while minimally affecting dendritic spike thresholds. In contrast, distal dendritic inhibition raised dendritic spike thresholds while minimally affecting their amplitudes. On-the-path dendritic inhibition modulated both the gain and threshold of dendritic spikes depending on its distance from the spike initiation zone. Our findings suggest that cortical circuits could assign different mixtures of gain vs. threshold inhibition to different neural pathways, and thus tailor their local computations, by managing their relative activation of soma- vs. dendrite-targeting interneurons.