Dendritic Integration Research Articles

Paroxysmal dystonia results from the loss of RIM4 in Purkinje cells.

Full-length RIM1 and 2 are key components of the presynaptic active zone that ubiquitously control excitatory and inhibitory neurotransmitter release. Here, we report that the function of the small RIM isoform RIM4, consisting of a single C2 domain, is strikingly different from that of the long isoforms. RIM4 is dispensable for neurotransmitter release but plays a postsynaptic, cell type-specific role in cerebellar Purkinje cells that is essential for normal motor function. In the absence of RIM4, Purkinje cell intrinsic firing is reduced and caffeine-sensitive, and dendritic integration of climbing fibre input is disturbed. Mice lacking RIM4, but not mice lacking RIM1/2, selectively in Purkinje cells exhibit a severe, hours-long paroxysmal dystonia. These episodes can also be induced by caffeine, ethanol or stress and closely resemble the deficits seen with mutations of the PNKD (paroxysmal non-kinesigenic dystonia) gene. Our data reveal essential postsynaptic functions of RIM proteins and show non-overlapping specialized functions of a small isoform despite high homology to a single domain in the full-length proteins.

Artificial organic afferent nerves enable closed-loop tactile feedback for intelligent robot

The emulation of tactile sensory nerves to achieve advanced sensory functions in robotics with artificial intelligence is of great interest. However, such devices remain bulky and lack reliable competence to functionalize further synaptic devices with proprioceptive feedback. Here, we report an artificial organic afferent nerve with low operating bias (−0.6 V) achieved by integrating a pressure-activated organic electrochemical synaptic transistor and artificial mechanoreceptors. The dendritic integration function for neurorobotics is achieved to perceive directional movement of object, further reducing the control complexity by exploiting the distributed and parallel networks. An intelligent robot assembled with artificial afferent nerve, coupled with a closed-loop feedback program is demonstrated to rapidly implement slip recognition and prevention actions upon occurrence of object slippage. The spatiotemporal features of tactile patterns are well differentiated with a high recognition accuracy after processing spike-encoded signals with deep learning model. This work represents a breakthrough in mimicking synaptic behaviors, which is essential for next-generation intelligent neurorobotics and low-power biomimetic electronics.

A dendrite is a dendrite is a dendrite? Dendritic signal integration beyond the "antenna" model.

Neurons in central nervous systems receive multiple synaptic inputs and transform them into a largely standardized output to their target cells-the action potential. A simplified model posits that synaptic signals are integrated by linear summation and passive propagation towards the axon initial segment, where the threshold for spike generation is either crossed or not. However, multiple lines of research during past decades have shown that signal integration in individual neurons is much more complex, with important functional consequences at the cellular, network, and behavioral-cognitive level. The interplay between concomitant excitatory and inhibitory postsynaptic potentials depends strongly on the relative timing and localization of the respective synapses. In addition, dendrites contain multiple voltage-dependent conductances, which allow scaling of postsynaptic potentials, non-linear input processing, and compartmentalization of signals. Together, these features enable a rich variety of single-neuron computations, including non-linear operations and synaptic plasticity. Hence, we have to revise over-simplified messages from textbooks and use simplified computational models like integrate-and-fire neurons with some caution. This concept article summarizes the most important mechanisms of dendritic integration and highlights some recent developments in the field.

A dendritic substrate for temporal diversity of cortical inhibition.

In the mammalian neocortex, GABAergic interneurons (INs) inhibit cortical networks in profoundly different ways. The extent to which this depends on how different INs process excitatory signals along their dendrites is poorly understood. Here, we reveal that the functional specialization of two major populations of cortical INs is determined by the unique association of different dendritic integration modes with distinct synaptic organization motifs. We found that somatostatin (SST)-INs exhibit NMDAR-dependent dendritic integration and uniform synapse density along the dendritic tree. In contrast, dendrites of parvalbumin (PV)-INs exhibit passive synaptic integration coupled with proximally enriched synaptic distributions. Theoretical analysis shows that these two dendritic configurations result in different strategies to optimize synaptic efficacy in thin dendritic structures. Yet, the two configurations lead to distinct temporal engagement of each IN during network activity. We confirmed these predictions with in vivo recordings of IN activity in the visual cortex of awake mice, revealing a rapid and linear recruitment of PV-INs as opposed to a long-lasting integrative activation of SST-INs. Our work reveals the existence of distinct dendritic strategies that confer distinct temporal representations for the two major classes of neocortical INs and thus dynamics of inhibition.

Conductance-based dendrites perform Bayes-optimal cue integration.

A fundamental function of cortical circuits is the integration of information from different sources to form a reliable basis for behavior. While animals behave as if they optimally integrate information according to Bayesian probability theory, the implementation of the required computations in the biological substrate remains unclear. We propose a novel, Bayesian view on the dynamics of conductance-based neurons and synapses which suggests that they are naturally equipped to optimally perform information integration. In our approach apical dendrites represent prior expectations over somatic potentials, while basal dendrites represent likelihoods of somatic potentials. These are parametrized by local quantities, the effective reversal potentials and membrane conductances. We formally demonstrate that under these assumptions the somatic compartment naturally computes the corresponding posterior. We derive a gradient-based plasticity rule, allowing neurons to learn desired target distributions and weight synaptic inputs by their relative reliabilities. Our theory explains various experimental findings on the system and single-cell level related to multi-sensory integration, which we illustrate with simulations. Furthermore, we make experimentally testable predictions on Bayesian dendritic integration and synaptic plasticity.

An organic artificial soma for spatio-temporal pattern recognition via dendritic integration

A novel organic neuromorphic device performing pattern classification is presented and demonstrated. It features an artificial soma capable of dendritic integration from three pre-synaptic neurons. The time-response of the interface between electrolytic solutions and organic mixed ionic-electronic conductors is proposed as the sole computational feature for pattern recognition, and it is easily tuned in the organic dendritic integrator by simply controlling electrolyte ionic strength. The classifier is benchmarked in speech-recognition experiments, with a sample of 14 words, encoded either from audio tracks or from kinematic data, showing excellent discrimination performances in a planar, miniaturizable, fully passive device, designed to be promptly integrated in more complex architectures where on-board pattern classification is required.

Kinetics and functional consequences of BK channels activation by N-type Ca2+ channels in the dendrite of mouse neocortical layer-5 pyramidal neurons.

The back-propagation of an action potential (AP) from the axon/soma to the dendrites plays a central role in dendritic integration. This process involves an intricate orchestration of various ion channels, but a comprehensive understanding of the contribution of each channel type remains elusive. In this study, we leverage ultrafast membrane potential recordings (Vm) and Ca2+ imaging techniques to shed light on the involvement of N-type voltage-gated Ca2+ channels (VGCCs) in layer-5 neocortical pyramidal neurons' apical dendrites. We found a selective interaction between N-type VGCCs and large-conductance Ca2+-activated K+ channels (BK CAKCs). Remarkably, we observe that BK CAKCs are activated within a mere 500 μs after the AP peak, preceding the peak of the Ca2+ current triggered by the AP. Consequently, when N-type VGCCs are inhibited, the early broadening of the AP shape amplifies the activity of other VGCCs, leading to an augmented total Ca2+ influx. A NEURON model, constructed to replicate and support these experimental results, reveals the critical coupling between N-type and BK channels. This study not only redefines the conventional role of N-type VGCCs as primarily involved in presynaptic neurotransmitter release but also establishes their distinct and essential function as activators of BK CAKCs in neuronal dendrites. Furthermore, our results provide original functional validation of a physical interaction between Ca2+ and K+ channels, elucidated through ultrafast kinetic reconstruction. This insight enhances our understanding of the intricate mechanisms governing neuronal signaling and may have far-reaching implications in the field.

L-methionine and the L-type Ca2+ channel agonist BAY K 8644 collaboratively contribute to the reduction of depressive-like behavior in mice.

The L-type Ca2+ channel (LTCC, also known as Cav1,2) is involved in the regulation of key neuronal functions, such as dendritic information integration, cell survival, and neuronal gene expression. Clinical studies have shown an association between L-type calcium channels and the onset of depression, although the precise mechanisms remain unclear. The development of depression results from a combination of environmental and genetic factors. DNA methylation, a significant epigenetic modification, plays a regulatory role in the pathogenesis of psychiatric disorders such as posttraumatic stress disorder (PTSD), depression, and autism. In our study, we observed reduced Dnmt3a expression levels in the hippocampal DG region of mice with LPS-induced depression compared to control mice. The antidepressant Venlafaxine was able to increase Dnmt3a expression levels. Conversely, Bay K 8644, an agonist of the L-type Ca2+ channel, partially ameliorated depression-like behaviors but did not elevate Dnmt3a expression levels. Furthermore, when we manipulated DNA methylation levels during Bay K 8644 intervention in depression-like models, we found that enhancing the expression of Dnmt3a could improve LPS-induced depression/anxiety-like behaviors, while inhibiting DNA methylation exacerbated anxiety-like behaviors, the combined use of BAY K 8644 and L-methionine can better improve depressive-like behavior. These findings indicate that DNA methylation plays a role in the regulation of depression-like behaviors by the L-type Ca2+ channel, and further research is needed to elucidate the interactions between DNA methylation and L-type Ca2+ channels.

Advances in Multi‐Terminal Transistors as Reconfigurable Interconnections for Neuromorphic Sensing and Processing

AbstractInspired by the brain, neuromorphic computing seeks to improve data‐centric applications in terms of power consumption and device footprint. The processing efficiency can be attributed to reconfigurable connections coupled with complex dynamics and efficient data sensing and signal processing. With field‐effect tunability, the three‐terminal thin‐film transistor is initially explored as a switch. Recently, transistors with added gates and modes have been fashioned as multi‐terminal devices capable of interconnecting complex networks and transducing multiple inputs. Here, the advances in both the semiconducting channel material and the configurational design of multi‐terminal devices are reviewed. The use of strong coupling and dynamical material properties in novel ion‐based capacitors, mixed‐ionic‐electronic semiconductors, low‐dimensional confined systems, stimuli‐responsive materials and redox‐active semiconductors has enabled new neuromorphic functionalities. These include improving reconfigurability using the regulatory ability of homeostasis, dendritic integration of sensory signals and the synaptic competition of resources. The transistor devices are also highly relevant in circuits that improve the efficiency of sensory transduction and signal processing; stimuli‐responsive semiconductors that adapt to the sensory inputs can be employed in the transistors and highly efficient sensorimotor connections between sensors and actuators can be emulated. These highly efficient, low‐complexity analog devices are crucial design elements for next‐generation neuromorphic systems.

Teorija dendritičke integracije kao stanični most za dominantne suvremene teorije svijesti

Consciousness is often described as the final frontier in science, tackled from multiple disciplines including philosophy, neuroscience, and computer science. Consciousness is most commonly defined as what exists from a first-person perspective, as the feeling of what it is like to be something, as well as through neuronal mechanisms that generate and support this phenomenology. Countless theories on consciousness have emerged to try to elucidate this complicated phenomenon. In our review, we aim to examine the three dominant theories of consciousness - Global Neuronal Workspace Theory (GNWT), Recurrent Processing Theory (RPT), Higher-order Theory (HOT) - and the Dendritic Integration Theory (DIT) as a newer, less prominent, theory that focuses on the cellular basis of consciousness. We propose that DIT may complement the postulations of the other three theories through its cellular approach that bridges state and content consciousness. Finally, we discuss the future of consciousness research more generally.

Spiking information processing in a single photonic spiking neuron chip with double integrated electronic dendrites

Dendrites, branches of neurons that transmit signals between synapses and soma, play a vital role in spiking information processing, such as nonlinear integration of excitatory and inhibitory stimuli. However, the investigation of nonlinear integration of dendrites in photonic neurons and the fabrication of photonic neurons including dendritic nonlinear integration in photonic spiking neural networks (SNNs) remain open problems. Here, we fabricate and integrate two dendrites and one soma in a single Fabry–Perot laser with an embedded saturable absorber (FP-SA) neuron to achieve nonlinear integration of excitatory and inhibitory stimuli. Note that the two intrinsic electrodes of the gain section and saturable absorber (SA) section in the FP-SA neuron are defined as two dendrites for two ports of stimuli reception, with one electronic dendrite receiving excitatory stimulus and the other receiving inhibitory stimulus. The stimuli received by two electronic dendrites are integrated nonlinearly in a single FP-SA neuron, which generates spikes for photonic SNNs. The properties of frequency encoding and spatiotemporal encoding are investigated experimentally in a single FP-SA neuron with two electronic dendrites. For SNNs equipped with FP-SA neurons, the range of weights between presynaptic neurons and postsynaptic neurons is varied from negative to positive values by biasing the gain and SA sections of FP-SA neurons. Compared with SNN with all-positive weights realized by only biasing the gain section of photonic neurons, the recognition accuracy of Iris flower data is improved numerically in SNN consisting of FP-SA neurons. The results show great potential for multi-functional integrated photonic SNN chips.

Effect of applied electric fields on supralinear dendritic integration of interneuron

Evidences show that electric fields (EFs) induced by the magnetic stimulation could modulates brain activities by regulating the excitability of GABAergic interneuron. However, it is still unclear how and why the EF-induced polarization affects the interneuron response as the interneuron receives NMDA synaptic inputs. Considering the key role of NMDA receptor-mediated supralinear dendritic integration in neuronal computations, we suppose that the applied EFs could functionally modulate interneurons’ response via regulating dendritic integration. At first, we build a simplified multi-dendritic circuit model with inhomogeneous extracellular potentials, which characterizes the relationship among EF-induced spatial polarizations, dendritic integration, and somatic output. By performing model-based singular perturbation analysis, it is found that the equilibrium point of fast subsystem can be used to asymptotically depict the subthreshold input–output (sI/O) relationship of dendritic integration. It predicted that EF-induced strong depolarizations on the distal dendrites reduce the dendritic saturation output by reducing driving force of synaptic input, and it shifts the steep change of sI/O curve left by reducing stimulation threshold of triggering NMDA spike. Also, the EF modulation prefers the global dendritic integration with asymmetric scatter distribution of NMDA synapses. Furthermore, we identify the respective contribution of EF-regulated dendritic integration and EF-induced somatic polarization to an action potential generation and find that they have an antagonistic effect on AP generation due to the varied NMDA spike threshold under EF stimulation.

Low throughput screening in neuroscience: using light to study central synapses one at a time.

Neurophotonic approaches have fostered substantial progress in our understanding of the brain by providing an assortment of means to either monitor or manipulate neural processes. Among these approaches, the development of two-photon uncaging provides a useful and flexible approach to manipulate the activity of individual synapses. In this short piece, we explore how this technique has emerged at the intersection of chemistry, optics, and electrophysiology to enable spatially and temporally precise photoactivation for studying functional aspects of synaptic transmission and dendritic integration. We discuss advantages and limitations of this approach, focusing on our efforts to study several functional aspects of glutamate receptors using uncaging of glutamate. Among other advancements, this approach has contributed to further our understanding of the subcellular regulation, trafficking, and biophysical features of glutamate receptors (e.g., desensitization and silent synapse regulation), the dynamics of spine calcium, and the integrative features of dendrites, and how these functions are altered by several forms of plasticity.

Boolean Logic Computing Based on Neuromorphic Transistor

AbstractGeneral‐purpose computers usually use logic gate computing units based on complementary metal oxide semiconductors (CMOS). Due to the separate memory and computing units in Von Neumann architecture, data transmission requires great energy and time consumption. Developing novel neuromorphic devices and comprehensively investigating their logical computing mode are crucial to achieve high‐performance and low‐power neuromorphic computation. Here, a systematic summary of Boolean logic computing based on emerging neuromorphic transistors is presented. This summary encompasses logical operation modes, materials, device structures, and working mechanisms. The input mode of Boolean logic operation is classified into electrical input, optical input, and synergistic optical/electrical input. Besides, additional modulation strategies to construct programmable logic functions by electrical, optical, and thermal signals are also summarized. These strategies hold great significance as they enable dynamic reconfiguration of logic operations and provide neuromorphic devices with decision‐making capabilities. Finally, the application prospects and current challenges to Boolean logic computing based on dendritic integration are discussed from the aspects of device integration, synergistic input/modulation modes, auxiliary peripheral circuit, software/hardware system, etc. It is believed that comprehensive investigations on neuromorphic Boolean logic operations are crucial to push forward the development of future neuromorphic computing toward high efficiency and high integration density.

A tunable leaky integrate-and-fire neuron based on one neuromorphic transistor and one memristor

Artificial leaky integrate-and-fire (LIF) neurons have attracted significant attention for building brain-like computing and neuromorphic systems. However, previous artificial LIF neurons have primarily focused on implementing integrate-and-fire function, and the function of dendritic modulation has rarely been reported. In this Letter, a tunable artificial LIF neuron based on an IGZO electric-double-layer (EDL) transistor and a TaOx memristor is fabricated, and dendritic modulation is investigated. An IGZO-based EDL transistor with a modulatory terminal is used to realize dendritic nonlinear integration and filtering capability, as well as the tunable neural excitability. An Ag/TaOx/ITO threshold switching memristor mimics the all-or-nothing spiking and threshold switching of the soma. By incorporating these two components in a customized way, such artificial LIF neuron can emulate the key function of biological neuron with rich computational flexibility. Our artificial LIF neurons with rich nonlinear dynamics have great potential to perform more complex tasks in future spiking neuromorphic systems.

Distorted neurocomputation by a small number of extra-large spines in psychiatric disorders.

Human genetics strongly support the involvement of synaptopathy in psychiatric disorders. However, trans-scale causality linking synapse pathology to behavioral changes is lacking. To address this question, we examined the effects of synaptic inputs on dendrites, cells, and behaviors of mice with knockdown of SETD1A and DISC1, which are validated animal models of schizophrenia. Both models exhibited an overrepresentation of extra-large (XL) synapses, which evoked supralinear dendritic and somatic integration, resulting in increased neuronal firing. The probability of XL spines correlated negatively with working memory, and the optical prevention of XL spine generation restored working memory impairment. Furthermore, XL synapses were more abundant in the postmortem brains of patients with schizophrenia than in those of matched controls. Our findings suggest that working memory performance, a pivotal aspect of psychiatric symptoms, is shaped by distorted dendritic and somatic integration via XL spines.

Plasticity of Cortico-striatal Neurons of the Caudal Anterior Cingulate Cortex During Experimental Neuropathic Pain

Maladaptive neuronal plasticity is a main mechanism for the development and maintenance of pathological pain. Affective, motivational and cognitive deficits that are comorbid with pain involve cellular and synaptic modifications in the anterior cingulate cortex (ACC), a major brain mediator of pain perception. Here we use a model of neuropathic pain (NP) in male mice and ex-vivo electrophysiology to investigate whether layer 5 caudal ACC (cACC) neurons projecting to the dorsomedial striatum (DMS), a critical region for motivational regulation of behavior, are involved in aberrant neuronal plasticity. We found that while the intrinsic excitability of cortico-striatal cACC neurons (cACC-CS) was preserved in NP animals, excitatory postsynaptic potentials (EPSP) induced after stimulation of distal inputs were enlarged. The highest synaptic responses were evident both after single stimuli and in each of the EPSP that compose responses to trains of stimuli, and were accompanied by increased synaptically-driven action potentials. EPSP temporal summation was intact in ACC-CS neurons from NP mice, suggesting that the plastic changes were not due to alterations in dendritic integration but rather through synaptic mechanisms. These results demonstrate for the first time that NP affects cACC neurons that project to the DMS and reinforce the notion that maladaptive plasticity of the cortico-striatal pathway may be a key factor in sustaining pathological pain.

Cortico-cortical feedback engages active dendrites in visual cortex

Sensory processing in the neocortex requires both feedforward and feedback information flow between cortical areas1. In feedback processing, higher-level representations provide contextual information to lower levels, and facilitate perceptual functions such as contour integration and figure–ground segmentation2,3. However, we have limited understanding of the circuit and cellular mechanisms that mediate feedback influence. Here we use long-range all-optical connectivity mapping in mice to show that feedback influence from the lateromedial higher visual area (LM) to the primary visual cortex (V1) is spatially organized. When the source and target of feedback represent the same area of visual space, feedback is relatively suppressive. By contrast, when the source is offset from the target in visual space, feedback is relatively facilitating. Two-photon calcium imaging data show that this facilitating feedback is nonlinearly integrated in the apical tuft dendrites of V1 pyramidal neurons: retinotopically offset (surround) visual stimuli drive local dendritic calcium signals indicative of regenerative events, and two-photon optogenetic activation of LM neurons projecting to identified feedback-recipient spines in V1 can drive similar branch-specific local calcium signals. Our results show how neocortical feedback connectivity and nonlinear dendritic integration can together form a substrate to support both predictive and cooperative contextual interactions.

Direct Observation of Oxygen Ion Dynamics in a WO3‐x based Second‐Order Memristor with Dendritic Integration Functions

AbstractDirect observation of oxygen dynamics in an oxide‐based second‐order memristor can provide the valid evidence to clarify the memristive mechanism, however, which is still limited for now. In this study, the migration and diffusion of oxygen ions in the region of Pt/WO3‐x Schottky interface are observed in the WO3‐x second‐order memristor by using the technique of in situ transmission electron microscopy (TEM) and the electron energy loss spectroscopy. Interestingly, the coexistence of memristive and memcapacitive switching can be implemented in this memristor. Combined with the analysis of depth‐profile X‐ray photoelectron spectroscopy (XPS), an interface‐barrier‐modulation second‐order memristive model is proposed based on the above results. Notably, temporally correlative oxygen dynamics in the memristor offers the platform to integrate signals from multiple inputs, enabling the realization of the dendritic functions of synchronous and asynchronous integration for the application of logic operations with fault‐tolerance capability and associative learning. These findings provide the experimental evidence to in‐depth understanding of oxygen dynamics and switching mechanism in second‐order memristor, which can support the optimization of memristive performance and the achievement of biorealistic synaptic functions.

Diverse role of NMDA receptors for dendritic integration of neural dynamics.

Neurons, represented as a tree structure of morphology, have various distinguished branches of dendrites. Different types of synaptic receptors distributed over dendrites are responsible for receiving inputs from other neurons. NMDA receptors (NMDARs) are expressed as excitatory units, and play a key physiological role in synaptic function. Although NMDARs are widely expressed in most types of neurons, they play a different role in the cerebellar Purkinje cells (PCs). Utilizing a computational PC model with detailed dendritic morphology, we explored the role of NMDARs at different parts of dendritic branches and regions. We found somatic responses can switch from silent, to simple spikes and complex spikes, depending on specific dendritic branches. Detailed examination of the dendrites regarding their diameters and distance to soma revealed diverse response patterns, yet explain two firing modes, simple and complex spike. Taken together, these results suggest that NMDARs play an important role in controlling excitability sensitivity while taking into account the factor of dendritic properties. Given the complexity of neural morphology varying in cell types, our work suggests that the functional role of NMDARs is not stereotyped but highly interwoven with local properties of neuronal structure.