Apical length governs computational diversity of layer 5 pyramidal neurons

Chemogenetic activation of Gq signaling modulates dendritic development of cortical neurons in a time- and layer-specific manner

Designer receptors exclusively activated by designer drugs (DREADDs) are established tools for modulating neuronal activity. Calcium-mobilizing DREADD hM3Dq has been widely used to enhance neuronal activity. hM3Dq activates the Gq protein signaling cascade and mimics the action of native Gq protein-coupled receptors such as muscarinic m1 and m3 receptors leading to calcium release from intracellular storages. Depolarization evoked by increased intracellular calcium levels is an important factor for neuronal maturation. Here, we used repetitive activation of biolistically overexpressed hM3Dq to increase the activity of individual neurons differentiating in organotypic slice cultures of rat visual cortex. HM3Dq was activated by 3 μM clozapine-N-oxide (CNO) dissolved in H2O. Transfectants expressing hM3Dq mock-stimulated with H2O served as batch-internal controls. Pyramidal cells and multipolar interneurons were analyzed after treatment from DIV 5-10, DIV 10-20, and DIV 15-20 to investigate if Gq signaling is involved in dendritic maturation. Results show that hM3Dq activation accelerated the maturation of apical dendrites of L2/3 pyramidal cells in the early, but no longer in the later time windows. In contrast, dendritic dimensions of L5/6 pyramidal cells and interneurons were not altered at DIV 10. These findings suggest a growth-promoting role of activated Gq signaling selectively for early postnatal L2/3 pyramidal cells. Unexpectedly, hM3Dq activation from DIV 10-20 reduced the dendritic complexity of L5/6 pyramidal cells and multipolar interneurons. Together, results suggest a role of Gq signaling for neuronal differentiation and support evidence that it may also limit dendritic growth.

Context-Sensitive Processing in a Model Neocortical Pyramidal Cell With Two Sites of Input Integration

Neocortical layer 5 thick-tufted pyramidal cells are prone to exhibiting burst firing on receipt of coincident basal and apical dendritic inputs. These inputs carry different information, with basal inputs coming from feedforward sensory pathways and apical inputs coming from diverse sources that provide context in the cortical hierarchy. We explore the information processing possibilities of this burst firing using computer simulations of a noisy compartmental cell model. Simulated data on stochastic burst firing due to brief, simultaneously injected basal and apical currents allow estimation of burst firing probability for different stimulus current amplitudes. Information-theory-based partial information decomposition (PID) is used to quantify the contributions of the apical and basal input streams to the information in the cell output bursting probability. Four different operating regimes are apparent, depending on the relative strengths of the input streams, with output burst probability carrying more or less information that is uniquely contributed by either the basal or apical input, or shared and synergistic information due to the combined streams. We derive and fit transfer functions for these different regimes that describe burst probability over the different ranges of basal and apical input amplitudes. The operating regimes can be classified into distinct modes of information processing, depending on the contribution of apical input to output bursting: apical cooperation, in which both basal and apical inputs are required to generate a burst; apical amplification, in which basal input alone can generate a burst but the burst probability is modulated by apical input; apical drive, in which apical input alone can produce a burst; and apical integration, in which strong apical or basal inputs alone, as well as their combination, can generate bursting. In particular, PID and the transfer function clarify that the apical amplification mode has the features required for contextually modulated information processing.

scConfluence: single-cell diagonal integration with regularized Inverse Optimal Transport on weakly connected features

The abundance of unpaired multimodal single-cell data has motivated a growing body of research into the development of diagonal integration methods. However, the state-of-the-art suffers from the loss of biological information due to feature conversion and struggles with modality-specific populations. To overcome these crucial limitations, we here introduce scConfluence, a method for single-cell diagonal integration. scConfluence combines uncoupled autoencoders on the complete set of features with regularized Inverse Optimal Transport on weakly connected features. We extensively benchmark scConfluence in several single-cell integration scenarios proving that it outperforms the state-of-the-art. We then demonstrate the biological relevance of scConfluence in three applications. We predict spatial patterns for Scgn, Synpr and Olah in scRNA-smFISH integration. We improve the classification of B cells and Monocytes in highly heterogeneous scRNA-scATAC-CyTOF integration. Finally, we reveal the joint contribution of Fezf2 and apical dendrite morphology in Intra Telencephalic neurons, based on morphological images and scRNA.

Auditory Corticofugal Neurons Transmit Auditory and Non-auditory Information During Behavior

Layer 5 pyramidal neurons of sensory cortices project "corticofugal" axons to myriad sub-cortical targets, thereby broadcasting high-level signals important for perception and learning. Recent studies suggest dendritic Ca2+ spikes as key biophysical mechanisms supporting corticofugal neuron function: these long-lasting events drive burst firing, thereby initiating uniquely powerful signals to modulate sub-cortical representations and trigger learning-related plasticity. However, the behavioral relevance of corticofugal dendritic spikes is poorly understood. We shed light on this issue using 2-photon Ca2+ imaging of auditory corticofugal dendrites as mice of either sex engage in a GO/NO-GO sound-discrimination task. Unexpectedly, only a minority of dendritic spikes were triggered by behaviorally relevant sounds under our conditions. Task related dendritic activity instead mostly followed sound cue termination and co-occurred with mice's instrumental licking during the answer period of behavioral trials, irrespective of reward consumption. Temporally selective, optogenetic silencing of corticofugal neurons during the trial answer period impaired auditory discrimination learning. Thus, auditory corticofugal systems' contribution to learning and plasticity may be partially nonsensory in nature.

Controlling morpho-electrophysiological variability of neurons with detailed biophysical models

Variability, which is known to be a universal feature among biological units such as neuronal cells, holds significant importance, as, for example, it enables a robust encoding of a high volume of information in neuronal circuits and prevents hypersynchronizations. While most computational studies on electrophysiological variability in neuronal circuits were done with single-compartment neuron models, we instead focus on the variability of detailed biophysical models of neuron multi-compartmental morphologies. We leverage a Markov chain Monte Carlo method to generate populations of electrical models reproducing the variability of experimental recordings while being compatible with a set of morphologies to faithfully represent specifi morpho-electrical type. We demonstrate our approach on layer 5 pyramidal cells and study the morpho-electrical variability and in particular, find that morphological variability alone is insufficient to reproduce electrical variability. Overall, this approach provides a strong statistical basis to create detailed models of neurons with controlled variability.

Endogenous Modulators of NMDA Receptor Control Dendritic Field Expansion of Cortical Neurons

Impairments of N-methyl-D-aspartate receptor (NMDAR) activity have been implicated in several neuropsychiatric disorders, with pharmacological inhibition of NMDAR-mediated currents and associated neurobehavioral changes considered as a model of schizophrenia. We analyzed the effects of brief and long-term exposure of rat cortical cultures to the most prevalent endogenous modulators of NMDAR (kynurenic acid, pregnenolone sulfate, spermidine, and zinc) on neuronal viability, stimulation-induced release of glutamate, and dendritic morphology with synaptic density. Both, glutamate release and neuronal viability studies revealed no difference between the test and control groups. No differences were also observed in the number of dendritic branching and length, or density of synaptic connections and neuronal soma size. Comparison of the extent of dendritic projections and branching patterns, however, revealed enhanced distal arborization with the expansion of the dendritic area under prolonged treatment of cultures with physiological concentrations of NMDAR modulators, with differences reaching significance in spermidine and pregnenolone sulfate tests. Measurements of the density of glutamatergic synapses showed consistency across all neuronal groups, except those treated with pregnenolone sulfate, which showed a reduction of PSD-95-positive elements. Overall, our data suggest that constitutive glutamatergic activity mediated by NMDAR controls the dendritic field expansion and can influence the integrative properties of cortical neurons.

Excitatory and inhibitory effects of HCN channel modulation on excitability of layer V pyramidal cells

Dendrites of cortical pyramidal cells are densely populated by hyperpolarization-activated cyclic nucleotide-gated (HCN) channels, a.k.a. Ih channels. Ih channels are targeted by multiple neuromodulatory pathways, and thus are one of the key ion-channel populations regulating the pyramidal cell activity. Previous observations and theories attribute opposing effects of the Ih channels on neuronal excitability due to their mildly hyperpolarized reversal potential. These effects are difficult to measure experimentally due to the fine spatiotemporal landscape of the Ih activity in the dendrites, but computational models provide an efficient tool for studying this question in a reduced but generalizable setting. In this work, we build upon existing biophysically detailed models of thick-tufted layer V pyramidal cells and model the effects of over- and under-expression of Ih channels as well as their neuromodulation. We show that Ih channels facilitate the action potentials of layer V pyramidal cells in response to proximal dendritic stimulus while they hinder the action potentials in response to distal dendritic stimulus at the apical dendrite. We also show that the inhibitory action of the Ih channels in layer V pyramidal cells is due to the interactions between Ih channels and a hot zone of low voltage-activated Ca2+ channels at the apical dendrite. Our simulations suggest that a combination of Ih-enhancing neuromodulation at the proximal part of the apical dendrite and Ih-inhibiting modulation at the distal part of the apical dendrite can increase the layer V pyramidal excitability more than either of the two alone. Our analyses uncover the effects of Ih-channel neuromodulation of layer V pyramidal cells at a single-cell level and shed light on how these neurons integrate information and enable higher-order functions of the brain.

Improving a cortical pyramidal neuron model's classification performance on a real-world ecg dataset by extending inputs

Pyramidal neurons display a variety of active conductivities and complex morphologies that support nonlinear dendritic computation. Given growing interest in understanding the ability of pyramidal neurons to classify real-world data, in our study we applied both a detailed pyramidal neuron model and the perceptron learning algorithm to classify real-world ECG data. We used Gray coding to generate spike patterns from ECG signals as well as investigated the classification performance of the pyramidal neuron's subcellular regions. Compared with the equivalent single-layer perceptron, the pyramidal neuron performed poorly due to a weight constraint. A proposed mirroring approach for inputs, however, significantly boosted the classification performance of the neuron. We thus conclude that pyramidal neurons can classify real-world data and that the mirroring approach affects performance in a way similar to non-constrained learning.

Chemogenetic Silencing of Differentiating Cortical Neurons Impairs Dendritic and Axonal Growth

Electrical activity is considered a key driver for the neurochemical and morphological maturation of neurons and the formation of neuronal networks. Designer receptors exclusively activated by designer drugs (DREADDs) are tools for controlling neuronal activity at the single cell level by triggering specific G protein signaling. Our objective was to investigate if prolonged silencing of differentiating cortical neurons can influence dendritic and axonal maturation. The DREADD hM4Di couples to G_i/o signaling and evokes hyperpolarization via GIRK channels. HM4Di was biolistically transfected into neurons in organotypic slice cultures of rat visual cortex, and activated by clozapine-N-oxide (CNO) dissolved in H₂O; controls expressed hM4Di, but were mock-stimulated with H₂O. Neurons were analyzed after treatment for two postnatal time periods, DIV 5-10 and 10-20. We found that CNO treatment delays the maturation of apical dendrites of L2/3 pyramidal cells. Further, the number of collaterals arising from the main axon was significantly lower, as was the number of bouton terminaux along pyramidal cell and basket cell axons. The dendritic maturation of L5/6 pyramidal cells and of multipolar interneurons (basket cells and bitufted cells) was not altered by CNO treatment. Returning CNO-treated cultures to CNO-free medium for 7 days was sufficient to recover dendritic and axonal complexity. Our findings add to the view that activity is a key driver in particular of postnatal L2/3 pyramidal cell maturation. Our results further suggest that inhibitory G protein signaling may represent a factor balancing the strong driving force of neurotrophic factors, electrical activity and calcium signaling.

Neurons as hierarchies of quantum reference frames

Conceptual and mathematical models of neurons have lagged behind empirical understanding for decades. Here we extend previous work in modeling biological systems with fully scale-independent quantum information-theoretic tools to develop a uniform, scalable representation of synapses, dendritic and axonal processes, neurons, and local networks of neurons. In this representation, hierarchies of quantum reference frames act as hierarchical active-inference systems. The resulting model enables specific predictions of correlations between synaptic activity, dendritic remodeling, and trophic reward. We summarize how the model may be generalized to nonneural cells and tissues in developmental and regenerative contexts.

Layer-specific pyramidal neuron properties underlie diverse anterior cingulate cortical motor and limbic networks

The laminar cellular and circuit mechanisms by which the anterior cingulate cortex (ACC) exerts flexible control of motor and affective information for goal-directed behavior have not been elucidated. Using multimodal tract-tracing, in vitro patch-clamp recording and computational approaches in rhesus monkeys (M. mulatta), we provide evidence that specialized motor and affective network dynamics can be conferred by layer-specific biophysical and structural properties of ACC pyramidal neurons targeting two key downstream structures -the dorsal premotor cortex (PMd) and the amygdala (AMY). AMY-targeting neurons exhibited significant laminar differences, with L5 more excitable (higher input resistance and action potential firing rates) than L3 neurons. Between-pathway differences were found within L5, with AMY-targeting neurons exhibiting greater excitability, apical dendritic complexity, spine densities, and diversity of inhibitory inputs than PMd-targeting neurons. Simulations using a pyramidal-interneuron network model predict that these layer- and pathway-specific single-cell differences contribute to distinct network oscillatory dynamics. L5 AMY-targeting networks are more tuned to slow oscillations well-suited for affective and contextual processing timescales, while PMd-targeting networks showed strong beta/gamma synchrony implicated in rapid sensorimotor processing. These findings are fundamental to our broad understanding of how layer-specific cellular and circuit properties can drive diverse laminar activity found in flexible behavior.

Dendritic Domain-Specific Sampling of Long-Range Axons Shapes Feedforward and Feedback Connectivity of L5 Neurons

Feedforward and feedback pathways interact in specific dendritic domains to enable cognitive functions such as predictive processing and learning. Based on axonal projections, hierarchically lower areas are thought to form synapses primarily on dendrites in middle cortical layers, whereas higher-order areas are thought to target dendrites in layer 1 and in deep layers. However, the extent to which functional synapses form in regions of axodendritic overlap has not been extensively studied. Here, we use viral tracing in the secondary visual cortex of male mice to map brain-wide inputs to thick-tufted layer 5 pyramidal neurons. Furthermore, we provide a comprehensive map of input locations through subcellular optogenetic circuit mapping. We show that input pathways target distinct dendritic domains with far greater specificity than appears from their axonal branching, often deviating substantially from the canonical patterns. Common assumptions regarding the dendrite-level interaction of feedforward and feedback inputs may thus need revisiting.SIGNIFICANCE STATEMENT Perception and learning depend on the ability of the brain to shape neuronal representations across all processing stages. Long-range connections across different hierarchical levels enable diverse sources of contextual information, such as predictions or motivational state, to modify feedforward signals. Assumptions regarding the organization of this hierarchical connectivity have not been extensively verified. Here, we assess the synaptic connectivity of brain-wide projections onto pyramidal neurons in the visual cortex of mice. Using trans-synaptic viral tracing and subcellular optogenetic circuit mapping, we show that functional synapses do not follow the consistent connectivity rule predicted by their axonal branching patterns. These findings highlight the diversity of computational strategies operating throughout cortical networks and may aid in building better artificial networks.

Genetic Mechanisms Underlying the Evolution of Connectivity in the Human Cortex

One of the most salient features defining modern humans is our remarkable cognitive capacity, which is unrivaled by any other species. Although we still lack a complete understanding of how the human brain gives rise to these unique abilities, the past several decades have witnessed significant progress in uncovering some of the genetic, cellular, and molecular mechanisms shaping the development and function of the human brain. These features include an expansion of brain size and in particular cortical expansion, distinct physiological properties of human neurons, and modified synaptic development. Together they specify the human brain as a large primate brain with a unique underlying neuronal circuit architecture. Here, we review some of the known human-specific features of neuronal connectivity, and we outline how novel insights into the human genome led to the identification of human-specific genetic modifiers that played a role in the evolution of human brain development and function. Novel experimental paradigms are starting to provide a framework for understanding how the emergence of these human-specific genomic innovations shaped the structure and function of neuronal circuits in the human brain.

Representational 'touch' and modulatory 'retouch'-two necessary neurobiological processes in thalamocortical interaction for conscious experience

Theories of consciousness using neurobiological data or being influenced by these data have been focused either on states of consciousness or contents of consciousness. These theories have occasionally used evidence from psychophysical phenomena where conscious experience is a dependent experimental variable. However, systematic catalog of many such relevant phenomena has not been offered in terms of these theories. In the perceptual retouch theory of thalamocortical interaction, recently developed to become a blend with the dendritic integration theory, consciousness states and contents of consciousness are explained by the same mechanism. This general-purpose mechanism has modulation of the cortical layer-5 pyramidal neurons that represent contents of consciousness as its core. As a surplus, many experimental psychophysical phenomena of conscious perception can be explained by the workings of this mechanism. Historical origins and current views inherent in this theory are presented and reviewed.

Circuit mechanisms for cortical plasticity and learning

The cerebral cortex integrates sensory information with emotional states and internal representations to produce coherent percepts, form associations, and execute voluntary actions. For the cortex to optimize perception, its neuronal network needs to dynamically retrieve and encode new information. Over the last few decades, research has started to provide insight into how the cortex serves these functions. Building on classical Hebbian plasticity models, the latest hypotheses hold that throughout experience and learning, streams of feedforward, feedback, and modulatory information operate in selective and coordinated manners to alter the strength of synapses and ultimately change the response properties of cortical neurons. Here, we describe cortical plasticity mechanisms that involve the concerted action of feedforward and long-range feedback input onto pyramidal neurons as well as the implication of local disinhibitory circuit motifs in this process.

Genetically Encoded Calcium Indicators Can Impair Dendrite Growth of Cortical Neurons

A battery of genetically encoded calcium indicators (GECIs) with different binding kinetics and calcium affinities was developed over the recent years to permit long-term calcium imaging. GECIs are calcium buffers and therefore, expression of GECIs may interfere with calcium homeostasis and signaling pathways important for neuronal differentiation and survival. Our objective was to investigate if the biolistically induced expression of five commonly used GECIs at two postnatal time points (days 14 and 22–25) could affect the morphological maturation of cortical neurons in organotypic slice cultures of rat visual cortex. Expression of GCaMP3 in both time windows, and of GCaMP5G and TN-XXL in the later time window impaired apical and /or basal dendrite growth of pyramidal neurons. With time, the proportion of GECI transfectants with nuclear filling increased, but an only prolonged expression of TN-XXL caused higher levels of neurodegeneration. In multipolar interneurons, only GCaMP3 evoked a transient growth delay during the early time window. GCaMP6m and GCaMP6m-X_C were quite “neuron-friendly.” Since growth-impaired neurons might not have the physiological responses typical of age-matched wildtype neurons the results obtained after prolonged developmental expression of certain GECIs might need to be interpreted with caution.