Circuit Function Research Articles

WITHDRAWN: Monolithically stacked VIA-free liquid metal circuit for stretchable electronics

Researchers are eagerly developing stretchable conductors because they constitute basic building blocks for stretchable electronic devices in the fields of wearable electronics, soft robotics, and human–machine interfaces. Though various stretchable conductors with high stability are being devised, fabricating stretchable stacked circuits with them leads to new challenges. The most critical problem is evoked by vertical interconnection access (VIA) structures, which inevitably become stress-concentrated areas when stretched. Consequently, stretchable circuits become much more unstable when manufactured as stacked circuits than single-layered circuits. Here, we demonstrate a monolithically stacked VIA-free stretchable liquid metal circuit that is mechanically one-body-merged and electrically stacked-circuit-designed. The circuit has no vertical structures, which endows extreme electromechanical stability with various features. It is realized by unique combinations of liquid metal conductor and selective surface treatment. The stacked circuit can be elongated over 1,100 % strain, demonstrating negligible difference in stretchability compared to a single-layered circuit. The circuit also possesses various distinctive characteristics of security, choosability, and extendability. As proof, we demonstrate an encryption element, a choosable circuit, an extendable circuit, and other functional circuits. We expect the proposed stacked circuit to give directions to stretchable stacked electronics with various functionalities.

Self-Lateral Propagation Elevates Synaptic Modifications in Spiking Neural Networks for the Efficient Spatial and Temporal Classification.

The brain's mystery for efficient and intelligent computation hides in the neuronal encoding, functional circuits, and plasticity principles in natural neural networks. However, many plasticity principles have not been fully incorporated into artificial or spiking neural networks (SNNs). Here, we report that incorporating a novel feature of synaptic plasticity found in natural networks, whereby synaptic modifications self-propagate to nearby synapses, named self-lateral propagation (SLP), could further improve the accuracy of SNNs in three benchmark spatial and temporal classification tasks. The SLP contains lateral pre ( SLPpre ) and lateral post ( SLPpost ) synaptic propagation, describing the spread of synaptic modifications among output synapses made by axon collaterals or among converging synapses on the postsynaptic neuron, respectively. The SLP is biologically plausible and can lead to a coordinated synaptic modification within layers that endow higher efficiency without losing much accuracy. Furthermore, the experimental results showed the impressive role of SLP in sharpening the normal distribution of synaptic weights and broadening the more uniform distribution of misclassified samples, which are both considered essential for understanding the learning convergence and network generalization of neural networks.

The astrocyte α1A-adrenoreceptor is a key component of the neuromodulatory system in mouse visual cortex.

Noradrenaline (norepinephrine) is known to modulate many physiological functions and behaviors. In this study, we tested to what extent astrocytes, a type of glial cell, participate in noradrenergic signaling in mouse primary visual cortex (V1). Astrocytes are essential partners of neurons in the central nervous system. They are central to brain homeostasis, but also dynamically regulate neuronal activity, notably by relaying and regulating neuromodulator signaling. Indeed, astrocytes express receptors for multiple neuromodulators, including noradrenaline, but the extent to which astrocytes are involved in noradrenergic signaling remains unclear. To test whether astrocytes are involved in noradrenergic neuromodulation in mice, we employed both short hairpin RNA mediated knockdown as well as pharmacological manipulation of the major noradrenaline receptor in astrocytes, the α1A-adrenoreceptor. Using acute brain slices, we found that the astrocytic α1A-adrenoreceptor subtype contributes to the generation of large intracellular Ca2+ signals in visual cortex astrocytes, which are generally thought to underlie astrocyte function. To test if reduced α1A-adrenoreceptor signaling in astrocytes affected the function of neuronal circuits in V1, we used both patch-clamp and field potential recordings. These revealed that noradrenergic signaling through the astrocyte α1A-adrenoreceptor is important to not only modulate synaptic activity but also to regulate plasticity in V1, through the potentiation of synaptic responses in circuits involved in visual information processing.

Higher-order cortical and thalamic pathways shape visual processing streams in the mouse cortex.

Mammalian visual functions rely on distributed processing across interconnected cortical and subcortical regions. In higher-order visual areas (HVAs), visual features are processed in specialized streams that integrate feedforward and higher-order inputs from intracortical and thalamocortical pathways. However, the precise circuit organization responsible for HVA specialization remains unclear. We investigated the cellular architecture of primary visual cortex (V1) and higher-order visual pathways in the mouse, focusing on their roles in shaping visual representations. Using invivo functional imaging and neural circuit tracing, we found that HVAs preferentially receive inputs from both V1 and higher-order pathways tuned to similar spatiotemporal properties, with the strongest selectivity seen in layer 2/3 neurons. These neurons exhibit target-specific tuning and sublaminar specificity in their projections, reflecting cell-type-specific visual information flow. In contrast, HVA layer 5 pathways nonspecifically broadcast visual signals across cortical areas, suggesting a role in distributing HVA outputs. Additionally, thalamocortical pathways from the lateral posterior thalamic nucleus (LP) provide highly specific, nearly non-overlapping visual inputs to HVAs, complementing intracortical inputs and contributing to input functional diversity. Our findings suggest that the convergence of laminar and cell-type-specific pathways V1 and higher-order intracortical and thalamocortical pathways plays a key role in shaping the functional specialization and diversity of HVAs.

A Step Forward for Smart Clothes: Printed Fabric-Based Hybrid Electronics for Wearable Health Monitoring.

Smart clothes equipped with flexible sensing systems provide a comfortable means to track health status in real time. Although these sensors are flexible and small, the core signal-processing units still rely on a conventional printed circuit board (PCB), making current health-monitoring devices bulky and inconvenient to wear. In this study, a printed fabric-based hybrid circuit was designed and prepared-with a series of characteristics, such as surface/sectional morphology, electrical properties, and stability-to study its reliability. Furthermore, to verify the function of the fabric-based circuit, simulations and measurements of the circuit, as well as the collection and processing of a normal adult's electrophysiological signals, were conducted. Under 10,000 stretching and bending cycles with a certain elongation and bending angle, the resistance remained 0.27 Ω/cm and 0.64 Ω/cm, respectively, demonstrating excellent conductivity and reliability. Additionally, the results of the simulation and experiment showed that the circuit can successfully amplify weak electrocardiogram (ECG) signals with a magnification of 1600 times with environmental filtering and 50 Hz of industrial frequency interference. This technology can monitor human electrophysiological signals, such as ECGs, electromyograms (EMGs), and joint motion, providing valuable practical guidance for the unobtrusive monitoring of smart clothes.

Corrigendum: Modeling the Emergence of Circuit Organization and Function during Development.

Corrigendum: Modeling the Emergence of Circuit Organization and Function during Development.

Synaptic composition, activity, mRNA translation and dynamics in combined single-synapse profiling using multimodal imaging.

The function of neuronal circuits, and its perturbation by psychoactive molecules or disease-associated genetic variants, is governed by the interplay between synapse activity and synaptic protein localization and synthesis across a heterogeneous synapse population. Here, we combine in situ measurement of synaptic multiprotein compositions and activation states, synapse activity in calcium traces or glutamate spiking, and local translation of specific genes, across the same individual synapses. We demonstrate how this high-dimensional data enables identification of interdependencies in the multiprotein-activity network, and causal dissection of complex synaptic phenotypes in disease-relevant chemical and genetic NMDAR loss of function that translate in vivo . We show how this method generalizes to other subcellular systems by deriving mitochondrial protein networks, and, using support vector machines, its value in overcoming animal variability in phenotyping. Integrating multiple synapse information modalities enables deep structure-function characterization of synapse populations and their responses to genetic and chemical perturbations.

Astrocyte regional specialization is shaped by postnatal development.

Astrocytes are an abundant class of glial cells with critical roles in neural circuit assembly and function. Though many studies have uncovered significant molecular distinctions between astrocytes from different brain regions, how this regionalization unfolds over development is not fully understood. We used single-nucleus RNA sequencing to characterize the molecular diversity of brain cells across six developmental stages and four brain regions in the mouse and marmoset brain. Our analysis of over 170,000 single astrocyte nuclei revealed striking regional heterogeneity among astrocytes, particularly between telencephalic and diencephalic regions, at all developmental time points surveyed in both species. At the stages sampled, most of the region patterning was private to astrocytes and not shared with neurons or other glial types. Though astrocytes were already regionally patterned in late embryonic stages, this region-specific astrocyte gene expression signature changed dramatically over postnatal development, and its composition suggests that regional astrocytes further specialize postnatally to support their local neuronal circuits. Comparing across species, we found divergence in the expression of astrocytic region- and age-differentially expressed genes and the timing of astrocyte maturation relative to birth between mouse and marmoset, as well as hundreds of species differentially expressed genes. Finally, we used expansion microscopy to show that astrocyte morphology is largely conserved across gray matter regions of prefrontal cortex, striatum, and thalamus in the mouse, despite substantial molecular divergence.

A Physical Memristor Model for Pavlovian Associative Memory

Abstract Brain-inspired intelligence is considered a computational model with the most promising potential to overcome the shortcomings of the von Neumann architecture, making it a current research hotspot. Due to advantages such as nonvolatility, high density, low power consumption, and high response ratio, memristors are regarded as devices with promising applications in brain-inspired intelligence. This paper proposes a physical Ag/HfO$_{x}$/FeO$_{x}$/Pt memristor model. Firstly, the Ag/HfO$_{x}$/FeO$_{x}$/Pt memristor is fabricated using magnetron sputtering, and its internal principles and characteristics are thoroughly analyzed. Furthermore, we constructed a corresponding physical memristor model which achieves a simulation accuracy of up to 99.72% for the physical memristor. We design a fully functional Pavlovian associative memory circuit, realizing functions including generalization, primary differentiation, secondary differentiation, and forgetting. Finally, the circuit is validated through PSPICE simulation and analysis.

Glia control experience-dependent plasticity in an olfactory critical period.

Sensory experience during developmental critical periods has lifelong consequences for circuit function and behavior, but the molecular and cellular mechanisms through which experience causes these changes are not well understood. The Drosophila antennal lobe houses synapses between olfactory sensory neurons (OSNs) and downstream projection neurons (PNs) in stereotyped glomeruli. Many glomeruli exhibit structural plasticity in response to early-life odor exposure, indicating a general sensitivity of the fly olfactory circuitry to early sensory experience. We recently found that glia shape antennal lobe development in young adults, leading us to ask if glia also drive experience-dependent plasticity during this period. Here we define a critical period for structural and functional plasticity of OSN-PN synapses in the ethyl butyrate (EB)-sensitive glomerulus VM7. EB exposure for the first two days post-eclosion drives large-scale reductions in glomerular volume, presynapse number, and post-synaptic activity. Crucially, pruning during the critical period has long-term consequences for circuit function since both OSN-PN synapse number and spontaneous activity of PNs remain persistently decreased following early-life odor exposure. The highly conserved engulfment receptor Draper is required for this critical period plasticity as ensheathing glia upregulate Draper, invade the VM7 glomerulus, and phagocytose OSN presynaptic terminals in response to critical-period EB exposure. Loss of Draper fully suppresses the morphological and physiological consequences of critical period odor exposure, arguing that phagocytic glia engulf intact synaptic terminals. These data demonstrate experience-dependent pruning of synapses and argue that Drosophila olfactory circuitry is a powerful model for defining the function of glia in critical period plasticity.

Development of a novel concentrated solar-powered material extrusion system for producing printed circuit assemblies

A novel material extrusion system powered by Concentrated Solar Energy (CSE) for functional small-scale applications is proposed. The open literature has reported that any other system employs CSE to heat the extruding needle directly, which is the main component and function of any material extrusion device and the one that allows the building of the desired product or prototype. Polycaprolactone (PCL) is selected as the depositing material that gives shape to the substrates sheltering electric traces, resulting in a printed circuit assembly (PCA). A set of 15 experiments with different shapes allows the compilation of enough data to identify the exposure time and the direct radiation received as the main variables for obtaining the needed temperature for converting the depositing material to its rubbery state. Examples of functional circuits obtained by this device are included, showing his capabilities and potential. This information and the help of simulations on Computational Fluid Dynamics (CFD) software allow finding an expression of the material temperature at the depositing needle's exit as a function of the abovementioned variables. The obtained function describes the experimental equipment's behavior and has an average relative error of 12.6 % compared with the measured material's temperature at the depositing needle's exit. This proposal is expected to summarize the evidence of the CSE's potential for powering some manufacturing systems to obtain consumer goods and that a melt casting system mainly powered by CSE will be plausible shortly.

Thermosensitive double-membrane neurons and their network dynamics

Abstract Cell membrane of biological neurons has distinct geometric structure, and involvement of diffusive term is suitable to estimate the spatial effect of cell membrane on neural activities. The gradient field diversity between two sides of the cell membrane can be approached by using a double-layer membrane model for the neuron. Therefore, two capacitive variables and diffusive terms are used to investigate the neural activities of cell membrane, and the local kinetics is described by a functional circuit composed of two capacitors. The voltages for the two parallel capacitors describe the inner and outer membrane potentials, and the diffusive effect of ions is considered on the membrane surface. The results reveal that neural activities are relative to the capacitance ratio between the inside and outside of the membrane and diffusive coefficient. High-energy periodic external stimulation induces the target waves to spread uniformly, while low-energy chaotic stimulation results in wave fragmentation. Furthermore, when the capacitance ratio exhibits exponential growth under an adaptive control law, the resulting energy gradient within the network induces stable target waves. That is, energy distribution affects the wave propagation and pattern formation in the neuron. The result indicates that the spatial diffusive effect and capacitance diversity between outer and inner cell membranes are important for selection of firing patterns and signal processing during neural activities. This model is more suitable to estimate neural activities than using generic oscillator-like or map neurons without considering the spatial diffusive effect.

Mechanisms of Action Underlying Conductance-Modifying Positive Allosteric Modulators of the NMDA Receptor.

N-methyl-D-aspartate receptors (NMDARs) are ionotropic glutamate receptors that mediate a slow, Ca2+-permeable component of excitatory neurotransmission. Modulation of NMDAR function has the potential for disease modification as NMDAR dysfunction has been implicated in neurodevelopment, neuropsychiatric, neurologic, and neurodegenerative disorders. We recently described the thieno[2,3-day]pyrimidin-4-one (EU1622) class of positive allosteric modulators, including several potent and efficacious analogs. Here we have used electrophysiological recordings from Xenopus oocytes, human embryonic kidney cells, and cultured cerebellar and cortical neurons to determine the mechanisms of action of a representative member of this class of modulator. EU1622-240 enhances current response to saturating agonist (doubling response amplitude at 0.2-0.5 μM), slows the deactivation time course following rapid removal of glutamate, increases open probability, enhances coagonist potency, and reduces single-channel conductance. We also show that EU1622-240 facilitates NMDAR activation when only glutamate or glycine is bound. EU1622-240-bound NMDARs channels activated by a single agonist (glutamate or glycine) open to a unique conductance level with different pore properties and Mg2+ sensitivity, in contrast to channels arising from activation of NMDARs with both coagonists bound. These data demonstrate that previously hypothesized distinct gating steps can be controlled by glutamate and glycine binding and shows that the 1622-series modulators enable glutamate- or glycine-bound NMDARs to generate open conformations with different pore properties. The properties of this class of allosteric modulators present intriguing therapeutic opportunities for the modulation of circuit function. SIGNIFICANCE STATEMENT: NMDA receptors are expressed throughout the central nervous system and are permeable to calcium. EU1622-240 increases open probability and agonist potency while reducing single-channel conductance and prolonging the deactivation time course. EU1622-240 allows NMDA receptor activation by the binding of one coagonist (glycine or glutamate), which produces channels with distinct properties. Evaluation of this modulator provides insight into gating mechanisms and may lead to the development of new therapeutic strategies.

A lightweight dual-link accelerated authentication protocol based on NLFSR-XOR APUF

Physical Unclonable Function (PUF) circuits, as a lightweight hardware security primitive, can provide reliable authentication for resource-constrained Internet of Things (IoT) devices. However, in real-time environments and systems, authentication of embedded devices has strict requirements on resources and low latency. Therefore, this paper proposes a lightweight dual-link accelerated authentication protocol design based on NLFSR-XOR APUF, through the study of Non-Linear Feedback Shift Registers (NLFSR) and XOR APUF circuits. First, the scheme utilizes the symmetric path delay deviation characteristics of APUF and the complexity of NLFSR state transitions to form a nonlinear output function that changes with the challenge signal. Then, a lightweight and attack-resistant authentication protocol is established by combining the random probability of shuffling array bits with the XOR confusion mechanism. Finally, the advantages of GPU parallel computing and AES T-table reconfiguration scheme are used to achieve an accelerated and side-channel attack-resistant authentication protocol. Experimental results show that the PUF circuit can effectively resist various modeling attacks, including logistic regression (LR), artificial neural network (ANN), and support vector machine (SVM). The security of the protocol has been formally verified, and the prototype has been implemented on the Xilinx xc100T development board, effectively resisting deception attacks, physical attacks, and modeling attacks. The protocol's area overhead in terms of LUT and encryption time is reduced by 58.6 % and 67.8 %, respectively, compared to similar protocols.

Celsr3 drives development and connectivity of the acoustic startle hindbrain circuit.

In the developing brain, groups of neurons organize into functional circuits that direct diverse behaviors. One such behavior is the evolutionarily conserved acoustic startle response, which in zebrafish is mediated by a well-defined hindbrain circuit. While numerous molecular pathways that guide neurons to their synaptic partners have been identified, it is unclear if and to what extent distinct neuron populations in the startle circuit utilize shared molecular pathways to ensure coordinated development. Here, we show that the planar cell polarity (PCP)-associated atypical cadherins Celsr3 and Celsr2, as well as the Celsr binding partner Frizzled 3a/Fzd3a, are critical for axon guidance of two neuron types that form synapses with each other: the command-like neuron Mauthner cells that drive the acoustic startle escape response, and spiral fiber neurons which provide excitatory input to Mauthner cells. We find that Mauthner axon growth towards synaptic targets is vital for Mauthner survival. We also demonstrate that symmetric spiral fiber input to Mauthner cells is critical for escape direction, which is necessary to respond to directional threats. Moreover, we identify distinct roles for Celsr3 and Celsr2, as Celsr3 is required for startle circuit development while Celsr2 is dispensable, though Celsr2 can partially compensate for loss of Celsr3 in Mauthner cells. This contrasts with facial branchiomotor neuron migration in the hindbrain, which requires Celsr2 while we find that Celsr3 is dispensable. Combined, our data uncover critical and distinct roles for individual PCP components during assembly of the acoustic startle hindbrain circuit.

Neurobiological understanding of gaming disorder: A narrative review

Gaming disorder (GD) is a mental disorder characterized by impaired control over gaming behaviors and the continuation of gaming despite negative consequences, resulting in functional impairments in important areas of life. Based on a growing body of scientific evidence demonstrating its neurobiological similarities to substance use disorders, GD is listed in the latest 5th edition of the Diagnostic and Statistical Manual of Mental Disorders and the 11th revision of the International Classification of Diseases as a behavioral addiction. Therefore, this review aims to understand the neurobiological underpinnings of GD by reviewing current literature on structural and functional changes in the brain. It is suggested that prolonged and excessive gaming may lead to alterations in the structure or function of the brain reward circuit and fronto-striatal circuit, affecting both reward processing and cognitive control. Changes in brain areas involved in executive function have been observed, indicating that GD is associated with reduced response inhibition and impaired decision-making. Furthermore, brain regions associated with craving exhibit heightened activity in response to gaming stimuli. This review highlights the significance of conducting further research to uncover the underlying mechanisms of GD and to develop effective interventions for its prevention and treatment.

Functional Brain Network of Trait Impulsivity: Whole-Brain Functional Connectivity Predicts Self-Reported Impulsivity.

Given impulsivity's multidimensional nature and its implications across various aspects of human behavior, a comprehensive understanding of functional brain circuits associated with this trait is warranted. In the current study, we utilized whole-brain resting-state functional connectivity data of healthy males (n = 156) to identify a network of connections predictive of an individual's impulsivity, as assessed by the Barratt Impulsiveness Scale (BIS)-11. Our participants were selected, in part, based on their self-reported BIS-11 impulsivity scores. Specifically, individuals who reported high or low trait impulsivity scores during screening were selected first, followed by those with intermediate impulsivity levels. This enabled us to include participants with rare, extreme scores and to cover the entire BIS-11 impulsivity spectrum. We employed repeated K-fold cross-validation for feature-selection and used stratified 10-fold cross-validation to train and test our models. Our findings revealed a widespread neural network associated with trait impulsivity and a notable correlation between predicted and observed scores. Feature importance and node degree were assessed to highlight specific nodes and edges within the impulsivity network, revealing previously overlooked key brain regions, such as the cerebellum, brainstem, and temporal lobe, while supporting previous findings on the basal ganglia-thalamo-prefrontal network and the prefrontal-motor strip network in relation to impulsiveness. This deepened understanding establishes a foundation for identifying alterations in functional brain networks associated with dysfunctional impulsivity.

Mitigating sTNF/TNFR1 activation on VGluT2 + spinal cord interneurons improves immune function after mid-thoracic spinal cord injury

Spinal cord injury (SCI) is a devastating condition with 250,000 to 500,000 new cases globally each year. Respiratory infections, e.g., pneumonia and influenza are the leading cause of death after SCI. Unfortunately, there is a poor understanding of how altered neuro-immune communication impacts an individual’s outcome to infection. In humans and rodents, SCI leads to maladaptive changes in the spinal-sympathetic reflex (SSR) circuit which is crucial to sympathetic function. The cause of the impaired immune function may be related to harmful neuroinflammation which is detrimental to homeostatic neuronal function, aberrant plasticity, and hyperexcitable circuits. Soluble tumor necrosis factor (sTNF) is a pro-inflammatory cytokine that is elevated in the CNS after SCI and remains elevated for several months after injury. By pharmacologically attenuating sTNF in the CNS after SCI we were able to demonstrate improved immune function. Furthermore, when we investigated the specific cellular population which may be involved in altered neuro-immune communication we reported that excessive TNFR1 activity on excitatory INs promotes immune dysfunction. Furthermore, this observation is NF-kβ dependent in VGluT2 + INs. Our data is the first report of a target within the CNS, TNFR1, that contributes to SCI-induced immune dysfunction after T9-SCI and is a potential avenue for future therapeutics.

Functional connectomics reveals general wiring rule in mouse visual cortex.

Understanding the relationship between circuit connectivity and function is crucial for uncovering how the brain implements computation. In the mouse primary visual cortex (V1), excitatory neurons with similar response properties are more likely to be synaptically connected, but previous studies have been limited to within V1, leaving much unknown about broader connectivity rules. In this study, we leverage the millimeter-scale MICrONS dataset to analyze synaptic connectivity and functional properties of individual neurons across cortical layers and areas. Our results reveal that neurons with similar responses are preferentially connected both within and across layers and areas - including feedback connections - suggesting the universality of the 'like-to-like' connectivity across the visual hierarchy. Using a validated digital twin model, we separated neuronal tuning into feature (what neurons respond to) and spatial (receptive field location) components. We found that only the feature component predicts fine-scale synaptic connections, beyond what could be explained by the physical proximity of axons and dendrites. We also found a higher-order rule where postsynaptic neuron cohorts downstream of individual presynaptic cells show greater functional similarity than predicted by a pairwise like-to-like rule. Notably, recurrent neural networks (RNNs) trained on a simple classification task develop connectivity patterns mirroring both pairwise and higher-order rules, with magnitude similar to those in the MICrONS data. Lesion studies in these RNNs reveal that disrupting 'like-to-like' connections has a significantly greater impact on performance compared to lesions of random connections. These findings suggest that these connectivity principles may play a functional role in sensory processing and learning, highlighting shared principles between biological and artificial systems.

Modification of Neural Circuit Functions by Microglial P2Y6 Receptors in Health and Neurodegeneration.

Neural circuits consisting of neurons and glial cells help to establish all functions of the CNS. Microglia, the resident immunocytes of the CNS, are endowed with UDP-sensitive P2Y6 receptors (P2Y6Rs) which regulate phagocytosis/pruning of excessive synapses during individual development and refine synapses in an activity-dependent manner during adulthood. In addition, this type of receptor plays a decisive role in primary (Alzheimer's disease, Parkinson's disease, neuropathic pain) and secondary (epilepsy, ischemic-, mechanical-, or irradiation-induced) neurodegeneration. A whole range of microglial cytokines controlled by P2Y6Rs, such as the interleukins IL-1β, IL-6, IL-8, and tumor necrosis factor-α (TNF-α), leads to neuroinflammation, resulting in neurodegeneration. Hence, small molecular antagonists of P2Y6Rs and genetic knockdown of this receptor provide feasible ways to alleviate inflammation-induced neurological disorders but might also interfere with the regulation of the synaptic circuitry. The present review aims at investigating this dual role of P2Y6Rs in microglia, both in shaping neural circuits by targeted phagocytosis and promoting neurodegenerative illnesses by fostering neuroinflammation through multiple transduction mechanisms.