Patterns Of Synaptic Connectivity Research Articles

Synaptic recognition molecules in development and disease.

Synaptic connectivity patterns underlie brain functions. How recognition molecules control where and when neurons form synapses with each other, therefore, is a fundamental question of cellular neuroscience. This chapter delineates adhesion and signaling complexes as well as secreted factors that contribute to synaptic partner recognition in the vertebrate brain. The sections follow a developmental perspective and discuss how recognition molecules (1) guide initial synaptic wiring, (2) provide for the rejection of incorrect partner choices, (3) contribute to synapse specification, and (4) support the removal of inappropriate synapses once formed. These processes involve a rich repertoire of molecular players and key protein families are described, notably the Cadherin and immunoglobulin superfamilies, Semaphorins/Plexins, Leucine-rich repeat containing proteins, and Neurexins and their binding partners. Molecular themes that diversify these recognition systems are defined and highlighted throughout the text, including the neuron-type specific expression and combinatorial action of recognition factors, alternative splicing, and post-translational modifications. Methodological innovations advancing the field such as proteomic approaches and single cell expression studies are additionally described. Further, the chapter highlights the importance of choosing an appropriate brain region to analyze synaptic recognition factors and the advantages offered by laminated structures like the hippocampus or retina. In a concluding section, the profound disease relevance of aberrant synaptic recognition for neurodevelopmental and psychiatric disorders is discussed. Based on the current progress, an outlook is presented on research goals that can further advance insights into how recognition molecules provide for the astounding precision and diversity of synaptic connections.

PsychRNN: An Accessible and Flexible Python Package for Training Recurrent Neural Network Models on Cognitive Tasks.

Task-trained artificial recurrent neural networks (RNNs) provide a computational modeling framework of increasing interest and application in computational, systems, and cognitive neuroscience. RNNs can be trained, using deep-learning methods, to perform cognitive tasks used in animal and human experiments and can be studied to investigate potential neural representations and circuit mechanisms underlying cognitive computations and behavior. Widespread application of these approaches within neuroscience has been limited by technical barriers in use of deep-learning software packages to train network models. Here, we introduce PsychRNN, an accessible, flexible, and extensible Python package for training RNNs on cognitive tasks. Our package is designed for accessibility, for researchers to define tasks and train RNN models using only Python and NumPy, without requiring knowledge of deep-learning software. The training backend is based on TensorFlow and is readily extensible for researchers with TensorFlow knowledge to develop projects with additional customization. PsychRNN implements a number of specialized features to support applications in systems and cognitive neuroscience. Users can impose neurobiologically relevant constraints on synaptic connectivity patterns. Furthermore, specification of cognitive tasks has a modular structure, which facilitates parametric variation of task demands to examine their impact on model solutions. PsychRNN also enables task shaping during training, or curriculum learning, in which tasks are adjusted in closed-loop based on performance. Shaping is ubiquitous in training of animals in cognitive tasks, and PsychRNN allows investigation of how shaping trajectories impact learning and model solutions. Overall, the PsychRNN framework facilitates application of trained RNNs in neuroscience research.

Neurodevelopment: UNC-40/DCC and the Patterning of Neural Circuits

A new study in Caenorhabditis elegans suggests the ubiquitin-proteasome system promotes degradation of the netrin receptor UNC-40 in a particular neuron only in one sex, leading to sex-specific patterns of synaptic connections.

Transcriptional Programs of Circuit Assembly in the Drosophila Visual System

Precise patterns of synaptic connections between neurons are encoded in their genetic programs. Here, we use single-cell RNA sequencing to profile neuronal transcriptomes at multiple stages in the developing Drosophila visual system. We devise an efficient strategy for profiling neurons at multiple time points in a single pool, thereby minimizing batch effects and maximizing the reliability of time-course data. A transcriptional atlas spanning multiple stages is generated, including more than 150 distinct neuronal populations; of these, 88 are followed through synaptogenesis. This analysis reveals a common (pan-neuronal) program unfolding in highly coordinated fashion in all neurons, including genes encoding proteins comprising the core synaptic machinery and membrane excitability. This program is overlaid by cell-type-specific programs with diverse cell recognition molecules expressed in different combinations and at different times. We propose that a pan-neuronal program endows neurons with the competence to form synapses and that cell-type-specific programs control synaptic specificity.

Increased density and age-related sharing of synapses at the cone to OFF bipolar cell synapse in the mouse retina.

Neural circuits in the adult nervous system are characterized by stable, cell type-specific patterns of synaptic connectivity. In many parts of the nervous system these patterns are established during development through initial over-innervation by multiple pre- or postsynaptic targets, followed by a process of refinement that takes place during development and is in many instances activity dependent. Here we report on an identified synapse in the mouse retina, the cone photoreceptor➔type 4 bipolar cell (BC4) synapse, and show that its development is distinctly different from the common motif of over-innervation followed by refinement. Indeed, the majority of cones are contacted by single BC4 throughout development, but are contacted by multiple BC4s through ongoing dendritic elaboration between 1 and 6 months of age-well into maturity. We demonstrate that cell density drives contact patterns downstream of single cones in Bax null mice and may serve to maintain constancy in both the dendritic and axonal projective field.

Modular transcriptional programs separately define axon and dendrite connectivity.

Patterns of synaptic connectivity are remarkably precise and complex. Single-cell RNA sequencing has revealed a vast transcriptional diversity of neurons. Nevertheless, a clear logic underlying the transcriptional control of neuronal connectivity has yet to emerge. Here, we focused on Drosophila T4/T5 neurons, a class of closely related neuronal subtypes with different wiring patterns. Eight subtypes of T4/T5 neurons are defined by combinations of two patterns of dendritic inputs and four patterns of axonal outputs. Single-cell profiling during development revealed distinct transcriptional programs defining each dendrite and axon wiring pattern. These programs were defined by the expression of a few transcription factors and different combinations of cell surface proteins. Gain and loss of function studies provide evidence for independent control of different wiring features. We propose that modular transcriptional programs for distinct wiring features are assembled in different combinations to generate diverse patterns of neuronal connectivity.

FGF receptors are required for proper axonal branch targeting in Drosophila

Proper axonal branch growth and targeting are essential for establishing a hard-wired neural circuit. Here, we examined the role of Fibroblast Growth Factor Receptors (FGFRs) in axonal arbor development using loss of function and overexpression genetic analyses within single neurons. We used the invariant synaptic connectivity patterns of Drosophila mechanosensory neurons with their innate cleaning reflex responses as readouts for errors in synaptic targeting and circuit function. FGFR loss of function resulted in a decrease in axonal branch number and lengths, and overexpression of FGFRs resulted in ectopic branches and increased lengths. FGFR mutants produced stereotyped axonal targeting errors. Both loss of function and overexpression of FGFRs within the mechanosensory neuron decreased the animal’s frequency of response to mechanosensory stimulation. Our results indicate that FGFRs promote axonal branch growth and proper branch targeting. Disrupting FGFRs results in miswiring and impaired neural circuit function.

Structure of auditory nerve synapses in normal and in hearing impaired

The neurons of the cochlear nuclei in the brainstem are the first central processors of auditory information, and they provide inputs to all the major brainstem and midbrain auditory nuclei. The synaptic connectivity pattern of neural networks in each part of the cochlear nuclear complex is an essential determinant of their role in information processing. The synapse of the auditory nerve on principal neurons in the cochlear nucleus is biophysically and anatomically specialized for the fast conduction of excitatory currents into the auditory pathway. A growing interest in the field is to determine how auditory nerve synapses adapt to fluctuations in the sound environment. In this paper, we will discuss novel findings related to the structural and molecular responses of auditory nerve synapses and enwrapping astrocytes in the normal hearing and in the hearing impaired.Support or Funding InformationNIDCD/NIH: R01DC013048; R56DC013048This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.

Dendritic and Axonal Propagation Delays May Shape Neuronal Networks With Plastic Synapses.

Biological neuronal networks are highly adaptive and plastic. For instance, spike-timing-dependent plasticity (STDP) is a core mechanism which adapts the synaptic strengths based on the relative timing of pre- and postsynaptic spikes. In various fields of physiology, time delays cause a plethora of biologically relevant dynamical phenomena. However, time delays increase the complexity of model systems together with the computational and theoretical analysis burden. Accordingly, in computational neuronal network studies propagation delays were often neglected. As a downside, a classic STDP rule in oscillatory neurons without propagation delays is unable to give rise to bidirectional synaptic couplings, i.e., loops or uncoupled states. This is at variance with basic experimental results. In this mini review, we focus on recent theoretical studies focusing on how things change in the presence of propagation delays. Realistic propagation delays may lead to the emergence of neuronal activity and synaptic connectivity patterns, which cannot be captured by classic STDP models. In fact, propagation delays determine the inventory of attractor states and shape their basins of attractions. The results reviewed here enable to overcome fundamental discrepancies between theory and experiments. Furthermore, these findings are relevant for the development of therapeutic brain stimulation techniques aiming at shifting the diseased brain to more favorable attractor states.

A Proposed Mechanism for Spontaneous Transitions between Interictal and Ictal Activity.

Epileptic networks are characterized by two outputs: brief interictal spikes and rarer, more prolonged seizures. Although either output state is readily modeled in silico and induced experimentally, the transition mechanisms are unknown, in part because no models exhibit both output states spontaneously. In silico small-world neural networks were built using single-compartment neurons whose physiological parameters were derived from dual whole-cell recordings of pyramidal cells in organotypic hippocampal slice cultures that were generating spontaneous seizure-like activity. In silico, neurons were connected by abundant local synapses and rare long-distance synapses. Activity-dependent synaptic depression and gradual recovery delimited synchronous activity. Full synaptic recovery engendered interictal population spikes that spread via long-distance synapses. When synaptic recovery was incomplete, postsynaptic neurons required coincident activation of multiple presynaptic terminals to reach firing threshold. Only local connections were sufficiently dense to spread activity under these conditions. This coalesced network activity into traveling waves whose velocity varied with synaptic recovery. Seizures were comprised of sustained traveling waves that were similar to those recorded during experimental and human neocortical seizures. Sustained traveling waves occurred only when wave velocity, network dimensions, and the rate of synaptic recovery enabled wave reentry into previously depressed areas at precisely ictogenic levels of synaptic recovery. Wide-field, cellular-resolution GCamP7b calcium imaging demonstrated similar initial patterns of activation in the hippocampus, although the anatomical distribution of traveling waves of synaptic activation was altered by the pattern of synaptic connectivity in the organotypic hippocampal cultures.SIGNIFICANCE STATEMENT When computerized distributed neural network models are required to generate both features of epileptic networks (i.e., spontaneous interictal population spikes and seizures), the network structure is substantially constrained. These constraints provide important new hypotheses regarding the nature of epileptic networks and mechanisms of seizure onset.

Verifying, Challenging, and Discovering New Synapses Among Fully EM-Reconstructed Neurons in the Leech Ganglion.

Neural circuits underpin the production of animal behavior, largely based upon the precise pattern of synaptic connectivity among the neurons involved. For large numbers of neurons, determining such “connectomes” by direct physiological means is difficult, as physiological accessibility is ultimately required to verify and characterize the function of synapses. We collected a volume of images spanning an entire ganglion of the juvenile leech nervous system via serial blockface electron microscopy (SBEM). We validated this approach by reconstructing a well-characterized circuit of motor neurons involved in the swimming behavior of the leech by locating the synapses among them. We confirm that there are multiple synaptic contacts between connected pairs of neurons in the leech, and that these synapses are widely distributed across the region of neuropil in which the neurons’ arbors overlap. We verified the anatomical existence of connections that had been described physiologically among longitudinal muscle motor neurons. We also found that some physiological connections were not present anatomically. We then drew upon the SBEM dataset to design additional physiological experiments. We reconstructed an uncharacterized neuron and one of its presynaptic partners identified from the SBEM dataset. We subsequently interrogated this cell pair via intracellular electrophysiology in an adult ganglion and found that the anatomically-discovered synapse was also functional physiologically. Our findings demonstrate the value of combining a connectomics approach with electrophysiology in the leech nervous system.

Propagation delays determine neuronal activity and synaptic connectivity patterns emerging in plastic neuronal networks.

In plastic neuronal networks, the synaptic strengths are adapted to the neuronal activity. Specifically, spike-timing-dependent plasticity (STDP) is a fundamental mechanism that modifies the synaptic strengths based on the relative timing of pre- and postsynaptic spikes, taking into account the spikes' temporal order. In many studies, propagation delays were neglected to avoid additional dynamic complexity or computational costs. So far, networks equipped with a classic STDP rule typically rule out bidirectional couplings (i.e., either loops or uncoupled states) and are, hence, not able to reproduce fundamental experimental findings. In this review paper, we consider additional features, e.g., extensions of the classic STDP rule or additional aspects like noise, in order to overcome the contradictions between theory and experiment. In addition, we review in detail recent studies showing that a classic STDP rule combined with realistic propagation patterns is able to capture relevant experimental findings. In two coupled oscillatory neurons with propagation delays, bidirectional synapses can be preserved and potentiated. This result also holds for large networks of type-II phase oscillators. In addition, not only the mean of the initial distribution of synaptic weights, but also its standard deviation crucially determines the emergent structural connectivity, i.e., the mean final synaptic weight, the number of two-neuron loops, and the symmetry of the final connectivity pattern. The latter is affected by the firing rates, where more symmetric synaptic configurations emerge at higher firing rates. Finally, we discuss these findings in the context of the computational neuroscience-based development of desynchronizing brain stimulation techniques.

Refinement of Spatial Receptive Fields in the Developing Mouse Lateral Geniculate Nucleus Is Coordinated with Excitatory and Inhibitory Remodeling.

Receptive field properties of individual visual neurons are dictated by the precise patterns of synaptic connections they receive, including the arrangement of inputs in visual space and features such as polarity (On vs Off). The inputs from the retina to the lateral geniculate nucleus (LGN) in the mouse undergo significant refinement during development. However, it is unknown how this refinement corresponds to the establishment of functional visual response properties. Here we conducted in vivo and in vitro recordings in the mouse LGN, beginning just after natural eye opening, to determine how receptive fields develop as excitatory and feedforward inhibitory retinal afferents refine. Experiments used both male and female subjects. For in vivo assessment of receptive fields, we performed multisite extracellular recordings in awake mice. Spatial receptive fields at eye-opening were >2 times larger than in adulthood, and decreased in size over the subsequent week. This topographic refinement was accompanied by other spatial changes, such as a decrease in spot size preference and an increase in surround suppression. Notably, the degree of specificity in terms of On/Off and sustained/transient responses appeared to be established already at eye opening and did not change. We performed in vitro recordings of the synaptic responses evoked by optic tract stimulation across the same time period. These recordings revealed a pairing of decreased excitatory and increased feedforward inhibitory convergence, providing a potential mechanism to explain the spatial receptive field refinement.SIGNIFICANCE STATEMENT The development of precise patterns of retinogeniculate connectivity has been a powerful model system for understanding the mechanisms underlying the activity-dependent refinement of sensory systems. Here we link the maturation of spatial receptive field properties in the lateral geniculate nucleus (LGN) to the remodeling of retinal and inhibitory feedforward convergence onto LGN neurons. These findings should thus provide a starting point for testing the cell type-specific plasticity mechanisms that lead to refinement of different excitatory and inhibitory inputs, and for determining the effect of these mechanisms on the establishment of mature receptive fields in the LGN.

Heparan Sulfate Proteoglycans as Emerging Players in Synaptic Specificity.

Neural circuits consist of distinct neuronal cell types connected in specific patterns. The specificity of these connections is achieved in a series of sequential developmental steps that involve the targeting of neurites, the identification of synaptic partners, and the formation of specific types of synapses. Cell-surface proteins play a critical role in each of these steps. The heparan sulfate proteoglycan (HSPG) family of cell-surface proteins is emerging as a key regulator of connectivity. HSPGs are expressed throughout brain development and play important roles in axon guidance, synapse development and synapse function. New insights indicate that neuronal cell types express unique combinations of HSPGs and HS-modifying enzymes. Furthermore, HSPGs interact with cell type-specific binding partners to mediate synapse development. This suggests that cell type-specific repertoires of HSPGs and specific patterns of HS modifications on the cell surface are required for the development of specific synaptic connections. Genome-wide association studies have linked these proteins to neurodevelopmental and neuropsychiatric diseases. Thus, HSPGs play an important role in the development of specific synaptic connectivity patterns important for neural circuit function, and their dysfunction may be involved in the development of brain disorders.

Developmental signature, synaptic connectivity and neurotransmission are conserved between vertebrate hair cells and tunicate coronal cells.

In tunicates, the coronal organ represents a sentinel checking particle entrance into the pharynx. The organ differentiates from an anterior embryonic area considered a proto-placode. For their embryonic origin, morphological features and function, coronal sensory cells have been hypothesized to be homologues to vertebrate hair cells. However, vertebrate hair cells derive from a posterior placode. This contradicts one of the principle historical criteria for homology, similarity of position, which could be taken as evidence against coronal cells/hair cells homology. In the tunicates Ciona intestinalis and C. robusta, we found that the coronal organ expresses genes (Atoh, Notch, Delta-like, Hairy-b, and Musashi) characterizing vertebrate neural and hair cell development. Moreover, coronal cells exhibit a complex synaptic connectivity pattern, and express neurotransmitters (Glu, ACh, GABA, 5-HT, and catecholamines), or enzymes for their synthetic machinery, involved in hair cell activity. Lastly, coronal cells express the Trpa gene, which encodes an ion channel expressed in hair cells. These data lead us to hypothesize a model in which competence to make secondary mechanoreceptors was initially broadly distributed through placode territories, but has become confined to different placodes during the evolution of the vertebrate and tunicate lineages.

Efficient encoding of motion is mediated by gap junctions in the fly visual system.

Understanding the computational implications of specific synaptic connectivity patterns is a fundamental goal in neuroscience. In particular, the computational role of ubiquitous electrical synapses operating via gap junctions remains elusive. In the fly visual system, the cells in the vertical-system network, which play a key role in visual processing, primarily connect to each other via axonal gap junctions. This network therefore provides a unique opportunity to explore the functional role of gap junctions in sensory information processing. Our information theoretical analysis of a realistic VS network model shows that within 10 ms following the onset of the visual input, the presence of axonal gap junctions enables the VS system to efficiently encode the axis of rotation, θ, of the fly’s ego motion. This encoding efficiency, measured in bits, is near-optimal with respect to the physical limits of performance determined by the statistical structure of the visual input itself. The VS network is known to be connected to downstream pathways via a subset of triplets of the vertical system cells; we found that because of the axonal gap junctions, the efficiency of this subpopulation in encoding θ is superior to that of the whole vertical system network and is robust to a wide range of signal to noise ratios. We further demonstrate that this efficient encoding of motion by this subpopulation is necessary for the fly's visually guided behavior, such as banked turns in evasive maneuvers. Because gap junctions are formed among the axons of the vertical system cells, they only impact the system’s readout, while maintaining the dendritic input intact, suggesting that the computational principles implemented by neural circuitries may be much richer than previously appreciated based on point neuron models. Our study provides new insights as to how specific network connectivity leads to efficient encoding of sensory stimuli.

Peripheral nerve injury-induced rearrangement of neural circuit in the spinal dorsal horn revealed by cross-correlation analysis.

Peripheral nerve injury often induces abnormal pain states, such as hyperalgesia and allodynia. In this study, we attempted to elucidate how neurons are synaptically integrated into the neuronal circuitry in the spinal dorsal horn and how synaptic connectivity patterns among dorsal horn neurons are altered by peripheral nerve injury. Experiments were performed on 6-8-week-old ICR mice. Partial sciatic nerve ligation was performed. Transverse slices of the lumbar spinal cord were prepared. Spike activities were simultaneously recorded from multiple neurons in the superficial dorsal horn (SDH) using a multi-electrode array system, and cross-correlograms between spike trains of neuron pairs were constructed. In sham-operated control mice, except for the flat cross-correlogram, the most common pattern was a cross-correlogram suggestive of common excitatory synaptic inputs to neuronal pairs. Peripheral nerve ligation increased the incidences of cross-correlograms suggestive of common excitatory synaptic inputs and excitatory synaptic connections, and decreased that of inhibitory synaptic connections. Additionally, bath-applied capsaicin, an agonist for transient receptor potential vanilloid 1 receptor, increased the frequency of action potentials. The effects of capsaicin stimulation on the incidence of cross-correlograms with various patterns were significantly different between sham-operated control and sciatic nerve-ligated mice. The present observations seem to indicate that neurons in the SDH form excitatory and/or inhibitory synapses with nearby neurons, and that synaptic connections among neurons in the SDH may remarkably change after the development of neuropathic pain.

Transcriptional Architecture of Synaptic Communication Delineates GABAergic Neuron Identity

Understanding the organizational logic of neural circuits requires deciphering the biological basis of neuronal diversity and identity, but there is no consensus on how neuron types should be defined. We analyzed single-cell transcriptomes of a set ofanatomically and physiologically characterized cortical GABAergic neurons and conducted a computational genomic screen for transcriptional profiles that distinguish them from one another. We discovered that cardinal GABAergic neuron types are delineated by a transcriptional architecture that encodes their synaptic communication patterns. This architecture comprises 6 categories of ∼40 gene families, including cell-adhesion molecules, transmitter-modulator receptors, ion channels, signaling proteins, neuropeptides and vesicular release components, and transcription factors. Combinatorial expression of select members across families shapes a multi-layered molecular scaffold along the cell membrane that may customize synaptic connectivity patterns and input-output signaling properties. This molecular genetic framework of neuronal identity integrates cell phenotypes along multiple axes and provides a foundation for discovering and classifying neuron types.

An intersectional gene regulatory strategy defines subclass diversity of C. elegans motor neurons.

A core principle of nervous system organization is the diversification of neuron classes into subclasses that share large sets of features but differ in select traits. We describe here a molecular mechanism necessary for motor neurons to acquire subclass-specific traits in the nematode Caenorhabditis elegans. Cholinergic motor neuron classes of the ventral nerve cord can be subdivided into subclasses along the anterior-posterior (A-P) axis based on synaptic connectivity patterns and molecular features. The conserved COE-type terminal selector UNC-3 not only controls the expression of traits shared by all members of a neuron class, but is also required for subclass-specific traits expressed along the A-P axis. UNC-3, which is not regionally restricted, requires region-specific cofactors in the form of Hox proteins to co-activate subclass-specific effector genes in post-mitotic motor neurons. This intersectional gene regulatory principle for neuronal subclass diversification may be conserved from nematodes to mice.

Establishing Wiring Specificity in Visual System Circuits: From the Retina to the Brain.

The retina is a tremendously complex image processor, containing numerous cell types that form microcircuits encoding different aspects of the visual scene. Each microcircuit exhibits a distinct pattern of synaptic connectivity. The developmental mechanisms responsible for this patterning are just beginning to be revealed. Furthermore, signals processed by different retinal circuits are relayed to specific, often distinct, brain regions. Thus, much work has focused on understanding the mechanisms that wire retinal axonal projections to their appropriate central targets. Here, we highlight recently discovered cellular and molecular mechanisms that together shape stereotypic wiring patterns along the visual pathway, from within the retina to the brain. Although some mechanisms are common across circuits, others play unconventional and circuit-specific roles. Indeed, the highly organized connectivity of the visual system has greatly facilitated the discovery of novel mechanisms that establish precise synaptic connections within the nervous system.