Neurons In Brain Research Articles

Feasibility of a Personal Neuromorphic Emulation.

The representation of intelligence is achieved by patterns of connections among neurons in brains and machines. Brains grow continuously, such that their patterns of connections develop through activity-dependent specification, with the continuing ontogenesis of individual experience. The theory of active inference proposes that the developmental organization of sentient systems reflects general processes of informatic self-evidencing, through the minimization of free energy. We interpret this theory to imply that the mind may be described in information terms that are not dependent on a specific physical substrate. At a certain level of complexity, self-evidencing of living (self-organizing) information systems becomes hierarchical and reentrant, such that effective consciousness emerges as the consequence of a good regulator. We propose that these principles imply that an adequate reconstruction of the computational dynamics of an individual human brain/mind is possible with sufficient neuromorphic computational emulation.

State of the Art in Sub-Phenotyping Midbrain Dopamine Neurons.

Dopaminergic neurons in the ventral tegmental area (VTA) and the substantia nigra pars compacta (SNpc) comprise around 75% of all dopaminergic neurons in the human brain. While both groups of dopaminergic neurons are in close proximity in the midbrain and partially overlap, development, function, and impairments in these two classes of neurons are highly diverse. The molecular and cellular mechanisms underlying these differences are not yet fully understood, but research over the past decade has highlighted the need to differentiate between these two classes of dopaminergic neurons during their development and in the mature brain. This differentiation is crucial not only for understanding fundamental circuitry formation in the brain but also for developing therapies targeted to specific dopaminergic neuron classes without affecting others. In this review, we summarize the state of the art in our understanding of the differences between the dopaminergic neurons of the VTA and the SNpc, such as anatomy, structure, morphology, output and input, electrophysiology, development, and disorders, and discuss the current technologies and methods available for studying these two classes of dopaminergic neurons, highlighting their advantages, limitations, and the necessary improvements required to achieve more-precise therapeutic interventions.

A gut-brain-gut interoceptive circuit loop gates sugar ingestion in Drosophila.

The communication between the brain and digestive tract is critical for optimising nutrient preference and food intake, yet the underlying neural mechanisms remain poorly understood1-7. Here, we show that a gut-brain-gut circuit loop gates sugar ingestion in flies. We discovered that brain neurons regulating food ingestion, IN18, receive excitatory input from enteric sensory neurons, which innervate the oesophagus and express the sugar receptor Gr43a. These enteric sensory neurons monitor the sugar content of food within the oesophagus during ingestion and send positive feedback signals to IN1s, stimulating the consumption of high-sugar foods. Connectome analyses reveal that IN1s form a core ingestion circuit. This interoceptive circuit receives synaptic input from enteric afferents and provides synaptic output to enteric motor neurons, which modulate the activity of muscles at the entry segments of the crop, a stomach-like food storage organ. While IN1s are persistently activated upon ingestion of sugar-rich foods, enteric motor neurons are continuously inhibited, causing the crop muscles to relax and enabling flies to consume large volumes of sugar. Our findings reveal a key interoceptive mechanism that underlies the rapid sensory monitoring and motor control of sugar ingestion within the digestive tract, optimising the diet of flies across varying metabolic states.

A Soft-Fiber Bioelectronic Device with Axon-Like Architecture Enables Reliable Neural Recording In Vivo under Vigorous Activities.

Implantable neural devices that record neurons in various states, including static states, light activities such as walking, and vigorous activities such as running, offer opportunities for understanding brain functions and dysfunctions. However, recording neurons under vigorous activities remains a long-standing challenge because it leads to intense brain deformation. Thus, three key requirements are needed simultaneously for neural devices, that is, low modulus, low specific interfacial impedance, and high electrical conductivity, to realize stable device/brain interfaces and high-quality transmission of neural signals. However, they always contradict each other in current material strategies. Here, a soft fiber neural device capable of stably tracking individual neurons in the deep brain of medium-sized animals under vigorous activity is reported. Inspired by the axon architecture, this fiber neural device is constructed with a conductive gel fiber possessing a network-in-liquid structure using conjugated polymers and liquid matrices and then insulated with soft fluorine rubber. This strategy reconciles the contradictions and simultaneously confers the fiber neural device with low modulus (300kPa), low specific impedance (579kΩµm2), and high electrical conductivity (32700Sm-1) - ≈1-3 times higher than hydrogels. Stable single-unit spike tracking in running cats, which promises new opportunities for neuroscience is demonstrated.

From Frog Muscle to Brain Neurons: Joys and Sorrows in Neuroscience.

One element, potassium, can be identified as the connecting link in the research of Czech neurophysiologist Prof. František Vyskočil. It accompanied him from the first student experiments on the frog muscle (Solandt effect) via sodium-potassium pump and quantum and non-quantum release of neurotransmitters (e.g. acetylcholine) to the most appreciated work on the reversible leakage of K+ from brain neurons during the Leao´s spreading cortical depression, often preceding migraine. He used a wide range of methods at the systemic, cellular and genetic levels. The electrophysiology and biochemistry of nerve-muscle contacts and synapses in the muscles and brain led to a range of interesting findings and discoveries on normal, denervated and hibernating laboratory mammals and in tissue cultures. Among others, he co-discovered the facilitating effects of catecholamines (adrenaline in particular) by end-plate synchronization of individual evoked quanta. This helps to understand the general effectiveness of nerve-muscle performance during actual stress. After the transition of the Czech Republic to capitalism, together with Dr. Josef Zicha from our Institute, he was an avid promoter of scientometry as an objective system of estimating a scientist´s success in basic research (journal Vesmír, 69: 644-645, 1990 in Czech).

COST OF ILLNESS ANALYSIS OF EPILEPSY OUTPATIENTS USING VALPROIC ACID, PHENYTOIN AND CARBAMAZEPINE THERAPY IN HOSPITAL IN INDONESIA

Epilepsy is a condition of the onset of attacks in the form of abnormal, irregular brain nerve cell movements, occurring repeatedly and causing temporary motor, sensory or mental function disorders. The treatment of epilepsy has costs that must be known, including direct medical costs, indirect medical costs, and indirect costs; this study aims to determine the cost of illness of epilepsy in one hospital in banyuasin regency with retrospective costing in outpatients. The research method used in this study is a cross-sectional study using patient medical record data and cost data taken from BPJS claims data and hospital rate patterns. This study uses the BPJS perspective and societal perspective, the cost data taken from the BPJS perspective is the result of BPJS claims according to the INACBGs. Package tariff and for the socital perspective the data taken is doctor consultation data, administrative costs, laboratory costs, drug costs and transportation costs and lost productivity costs carried out by interview method for 12 months. The results of this study indicate that the cost of epilepsy outpatients from a societal perspective is Rp.3,141,414 and for BPJS perspective is Rp.2,338,567.

Descending Motor Pathways

The brain is the origin of the descending motor pathways or tracts. These are responsible for the origination or modification of motor activity. This action is performed by motor signals, which transmitted from the brain and target lower motor neurons. Motor control is a chief task of the central nervous system (CNS). It can be recognized as the initiation of signals to coordinate muscle contraction of the body and head, aiming to keep a posture or to make a movement (transition between two postures). A large amount of the CNS is included in the process of motor control. The term "motor neuron, also known as motoneurons" may refer to single or one type of neurons responsible for the movement. However, this is not the truth. Actually, the “motor neuron” describe two categories of neurons, the “upper and lower motor neurons”. They are significantly different in their origins, synapses, pathways, neurotransmitters and developed lesions due to their affection. Motor neurons are essential constituents of two different circuits “the upper and lower motor circuits”. These circuits control both voluntary and involuntary movements. This was achieved by the connection of higher centers with muscles and glands Descending tracts of the motor system are originating mainly from two parts, the cortex and the brainstem. Tracts originating from the cortex control the voluntary movements and adjust posture relating to voluntary movement. Furthermore, the descending pathways are subdivided into (pathways) describing their start and termination. These are (1) corticospinal and corticobulbar, (2) cortico-reticulo-spinal, (3) cortico-rubro-spinal (4) cortico-tecto-spinal, (5) vestibulo-spinal and (6) raphe–spinal and ceruleus–spinal tracts (aminergic pathways) Pyramidal tracts, originating in the cortex and carry motor fibres to the spinal cord and brain stem. It is subdivided into corticospinal and Corticobulbar tracts. The extrapyramidal tracts originate in the brainstem. Then carry motor projections to the spinal cord. These tracts are primarily concerned with the control of the involuntary and automatic innervations for all musculature (e.g., muscle tone, balance, posture and locomotion).

Can infrared light really be doing what we claim it is doing? Infrared light penetration principles, practices, and limitations.

Near infrared (NIR) light has been shown to provide beneficial treatment of traumatic brain injury (TBI) and other neurological problems. This concept has spawned a plethora of commercial entities and practitioners utilizing panels of light emitting diodes (LEDs) and promising to treat patients with TBI and other disorders, who are desperate for some treatment for their untreatable conditions. Unfortunately, an LED intended to deliver photonic energy to the human brain does not necessarily do what an LED pointed at a mouse brain does. There is a problem of scale. Extensive prior research has shown that infrared light from a 0.5-watt LED will not penetrate the scalp and skull of a human. Both the properties of NIR light and the manner in which it interacts with tissue are examined. Based on these principles, the shortcomings of current approaches to treating neurological disorders with NIR light are explored. Claims of clinical benefit from low-level LED-based devices are explored and the proof of concept challenged. To date, that proof is thin with marginal benefits which are largely transient. Extensive research has shown fluence at the level of the target tissue which falls within the range of 0.9 J/cm2 to 15 J/cm2 is most effective in activating the biological processes at the cellular level which underlie direct photobiomodulation. If low-level infrared light from LED devices is not penetrating the scalp and skull, then these devices certainly are not delivering that level of fluence to the neurons of the subjacent brain. Alternative mechanisms, such as remote photobiomodulation, which may underlie the small and transient benefits for TBI symptoms reported for low-power LED-based NIR studies are presented. Actionable recommendations for the field are offered.

Gated parametric neuron for spike-based audio recognition

Spiking neural networks (SNNs) aim to simulate real neural networks in the human brain with biologically plausible neurons. The leaky integrate-and-fire (LIF) neuron is one of the most widely studied SNN architectures. However, it has the vanishing gradient problem when trained with backpropagation. Additionally, its neuronal parameters are often manually specified and fixed, in contrast to the heterogeneity of real neurons in the human brain. This paper proposes a gated parametric neuron (GPN) to process spatio-temporal information effectively with the gating mechanism. Compared with the LIF neuron, the GPN has two distinguishing advantages: (1) it copes well with the vanishing gradients by improving the flow of gradient propagation; and, (2) it learns spatio-temporal heterogeneous neuronal parameters automatically. Additionally, we use the same gate structure to eliminate initial neuronal parameter selection and design a hybrid recurrent neural network-SNN structure. Experiments on two spike-based audio datasets demonstrated that the GPN network outperformed several state-of-the-art SNNs, could mitigate vanishing gradients, and had spatio-temporal heterogeneous parameters. Our work shows the ability of SNNs to handle long-term dependencies and achieve high performance simultaneously.

Widespread Neuroanatomical Integration and Distinct Electrophysiological Properties of Glioma-Innervating Neurons.

We have developed a novel system utilizing rabies virus-based monosynaptic tracing to directly visualize neurons that synapse onto human glioma cells implanted in mouse brain. This approach enables the mapping and quantitative analysis of these glioma-innervating neurons (GINs) in the entire mouse brain and overcomes previous barriers of molecular and electrophysiological analysis of these neurons due to the inability to identify them. Our findings indicate that GINs integrate into existing neural networks in a location-specific manner. Long-range GINs are mostly glutamatergic, with a subset expressing both glutamatergic and GABAergic markers and local striatal GINs are GABAergic, highlighting a complex neuromodulatory profile. Additionally, GINs exhibit unique action potential characteristics, distinct from similarly selected neurons in non-tumor-bearing brains. This study provides new insights into neuronal adaptations in response to forming putative synapses onto glioma, elucidating the intricate synaptic relationship between GINs and gliomas.

Single-cell dissection of the human blood-brain barrier and glioma blood-tumor barrier

The blood-brain barrier (BBB) serves as a crucial vascular specialization, shielding and nourishing brain neurons and glia while impeding drug delivery. Here, we conducted single-cell mRNA sequencing of human cerebrovascular cells from 13 surgically resected glioma samples and adjacent normal brain tissue. The transcriptomes of 103,230 cells were mapped, including 57,324 endothelial cells (ECs) and 27,703 mural cells (MCs). Both EC and MC transcriptomes originating from lower-grade glioma were indistinguishable from those of normal brain tissue, whereas transcriptomes from glioblastoma (GBM) displayed a range of abnormalities. Among these, we identified LOXL2-dependent collagen modification as a common GBM-dependent trait and demonstrated that inhibiting LOXL2 enhanced chemotherapy efficacy in both murine and human patient-derived xenograft (PDX) GBM models. Our comprehensive single-cell RNA sequencing-based molecular atlas of the human BBB, coupled with insights into its perturbations in GBM, holds promise for guiding future investigations into brain health, pathology, and therapeutic strategies.

The mechanism of hypoxia-inducible factor-1α enhancing the transcriptional activity of transferrin ferroportin 1 and regulating the Nrf2/HO-1 pathway in ferroptosis after cerebral ischemic injury

Cerebral ischemic/reperfusion (I/R) injury has high disability and morbidity. Hypoxia-inducible factor-1α (HIF-1α) may enhance the transcriptional activity of transferrin ferroportin 1 (FPN1) in regulating ferroptosis after cerebral ischemia injury (CII). In this study, cerebral I/R injury rat models were established and treated with pcDNA3.1-HIF-1α, pcDNA3.1-NC lentiviral plasmid, or ML385 (a specific Nrf2 inhibitor). Additionally, oxygen-glucose deprivation/reoxygenation (OGD/R) exposed PC12 cells were used as an in vitro model of cerebral ischemia and treated with pcDNA3.1-HIF-1α, si-FPN1, or ML385. The results elicited that cerebral I/R injury rats exhibited increased Longa scores, TUNEL and NeuN co-positive cells, Fe2+ concentration, ROS and HIF-1α levels, and MDA content, while reduced cell density and number, GSH content, and GPX4 protein level. Morphologically abnormal and disordered hippocampal neurons were also observed in CII rats. HIF-1α inhibited brain neuron ferroptosis and ameliorated I/R injury. HIF-1α alleviated OGD-induced PC12 cell ferroptosis. OGD/R decreased FPN1 protein level in PC12 cells, and HIF-1α enhanced FPN1 transcriptional activity. FPN1 knockdown reversed HIF-1α-mediated alleviation of OGD/R-induced ferroptosis. HIF-1α activated the Nrf2/HO-1 pathway by enhancing FPN1 expression and alleviating OGD/R-induced ferroptosis. Conjointly, HIF-1α enhanced the transcriptional activity of FPN1, activated the Nrf2/HO-1 pathway, and inhibited ferroptosis of brain neurons, thereby improving I/R injury in CII rats.

Robust iterative value conversion: Deep reinforcement learning for neurochip-driven edge robots

A neurochip is a device that reproduces the signal processing mechanisms of brain neurons and calculates Spiking Neural Networks (SNNs) with low power consumption and at high speed. Thus, neurochips are attracting attention from edge robot applications, which suffer from limited battery capacity. This paper aims to achieve deep reinforcement learning (DRL) that acquires SNN policies suitable for neurochip implementation. Since DRL requires a complex function approximation, we focus on conversion techniques from Floating Point NN (FPNN) because it is one of the most feasible SNN techniques. However, DRL requires conversions to SNNs for every policy update to collect the learning samples for a DRL-learning cycle, which updates the FPNN policy and collects the SNN policy samples. Accumulative conversion errors can significantly degrade the performance of the SNN policies. We propose Robust Iterative Value Conversion (RIVC) as a DRL that incorporates conversion error reduction and robustness to conversion errors. To reduce them, FPNN is optimized with the same number of quantization bits as an SNN. The FPNN output is not significantly changed by quantization. To robustify the conversion error, an FPNN policy that is applied with quantization is updated to increase the gap between the probability of selecting the optimal action and other actions. This step prevents unexpected replacements of the policy’s optimal actions. We verified RIVC’s effectiveness on a neurochip-driven robot. The results showed that RIVC consumed 1/15 times less power and increased the calculation speed by five times more than an edge CPU (quad-core ARM Cortex-A72). The previous framework with no countermeasures against conversion errors failed to train the policies. Videos from our experiments are available: https://youtu.be/Q5Z0-BvK1Tc.

Light and dopamine impact two circadian neurons to promote morning wakefulness

In both mammals and flies, circadian brain neurons orchestrate physiological oscillations and behaviors like wake and sleep-these neurons can be subdivided by morphology and by gene expression patterns. Recent single-cell sequencing studies identified 17 Drosophila circadian neuron groups. One of these includes only two lateral neurons (LNs), which are marked by the expression of the neuropeptide ion transport peptide (ITP). Although these two ITP+ LNs have long been grouped with five other circadian evening activity cells, inhibiting the two neurons alone strongly reduces morning activity, indicating that they also have a prominent morning function. As dopamine signaling promotes activity in Drosophila, like in mammals, we considered that dopamine might influence this morning activity function. Moreover, the ITP+ LNs express higher mRNA levels than other LNs of the type 1-like dopamine receptor Dop1R1. Consistent with the importance of Dop1R1, cell-specific CRISPR-Cas9 mutagenesis of this receptor in the two ITP+ LNs renders flies significantly less active in the morning, and exvivo live imaging shows Dop1R1-dependent cyclic AMP (cAMP) responses to dopamine in these two neurons. Notably, the response is more robust in the morning, reflecting higher morning Dop1R1 mRNA levels in the two neurons. As mRNA levels are not elevated in constant darkness, this suggests light-dependent upregulation of morning Dop1R1 transcript levels. Taken together with the enhanced morning cAMP response to dopamine, the data indicate how light and dopamine promote morning wakefulness in flies, mimicking the important effect of light on morning wakefulness in humans.

Morpho-Anatomical Degeneration of Dopaminergic Neurons in Adult Zebrafish Brain after Exposure to Nickel

Chronic exposure to heavy metals has been widely demonstrated to induce pathological features in different tissues and, in particular, in the central nervous system. Specific neurons, including dopaminergic neurons, were observed to be more susceptible to toxic agents. Several previous studies performed on zebrafish (Danio rerio) models observed that exposure to nickel (one of the most abundant heavy metals) induces impairment of memory and anxious-like behaviors. Nevertheless, this phenotypical evidence has not been associated with dopaminergic system damage, and no reports showing the effects of nickel on dopaminergic neurons are available. In this study, we aim to analyze the precise distribution and variation in dopaminergic neurons in adult zebrafish after chronic (96 h) exposure to nickel ions dissolved in water at different sub-lethal doses (0.4 mg L−1; 2 mg L−1 and 4 mg L−1). The effects of treatment on dopaminergic neurons were evaluated by measuring transcript and protein levels of tyrosine hydroxylase (TH), described as a dopaminergic neuron marker. As shown, the expression of the th1 and th2 genes was reduced in the entire brain of zebrafish treated with nickel. Immunostaining analysis allowed us to localize TH-expressing neurons mainly in the posterior tuberculum, where they were observed to be reduced after nickel treatment in a dose-dependent fashion. Consistently, the TUNEL assay revealed a significant increase in apoptosis of TH-expressing cells after treatment with 2 mg L−1 and 4 mg L−1 of nickel. Our findings represent the first evidence of the effect of nickel on the dopaminergic system.

Triggering Tau Fibrillization by Electroreduction: A New Tool for Studying Amyloid Diseases

The pathological aggregation of the microtubule-associated protein tau is a hallmark of various neurodegenerative disorders, including Alzheimer’s disease (AD), Pick’s disease and frontotemporal dementia. Tau protein’s reversible assembly and binding to microtubules in brain neurons are regulated by charge-neutralizing phosphorylation. Hyperphosphorylation, on the other hand, leads to irreversible formation of cytotoxic filaments. Under physiological conditions, tau remains remarkably stable, exhibiting intrinsically disordered behavior and reversible assembly. Irreversible aggregation requires specific mutations, preformed seeds or nucleating polyanionic cofactors. However, heparin-induced fibrils differ structurally from brain-derived filaments, and the presence of such cofactors can impede therapeutic agent development. We have developed a quick and easy method to generate cofactor-free filaments using heterogeneous electroreduction as a surrogate for charge-neutralization by hyperphosphorylation. We combine electrochemistry with in situ UV absorbance, circular dichroism and dynamic light scattering spectroscopies to dynamically follow tau’s conformational changes and assembly. Electroreduction of positively charged residues of the protein leads to rapid formation of b-rich structures, even at times as short as 15 minutes. The extent of assembly can be controlled by fine-tuning electroreductive potentials and electrolyte conditions. Relevance of this new method was confirmed by examining the impact of an early-onset AD-causing tau mutant and known inhibitors on aggregation kinetics. Our results demonstrate comparable effects to heparin-induced fibrils, as assessed by thioflavin-T fluorescence, dynamic light scattering, circular dichroism and electron microscopy. Low-voltage electroreduction provides a platform to study the effects of tau mutations and effectors, as well as to develop rapid assays to test how additional effectors may inhibit, disassemble or direct the trajectory of tau assembly. The versatility of our approach also suggests its potential applicability to a broader spectrum of neurodegenerative amyloid diseases.

From Blur to Brilliance: The Ascendance of Advanced Microscopy in Neuronal Cell Biology.

The intricate network of the brain's neurons and synapses poses unparalleled challenges for research, distinct from other biological studies. This is particularly true when dissecting how neurons and their functional units work at a cell biological level. While traditional microscopy has been foundational, it was unable to reveal the deeper complexities of neural interactions. However, an imaging renaissance has transformed our capabilities. Advancements in light and electron microscopy, combined with correlative imaging, now achieve unprecedented resolutions, uncovering the most nuanced neural structures. Maximizing these tools requires more than just technical proficiency. It is crucial to align research aims, allocate resources wisely, and analyze data effectively. At the heart of this evolution is interdisciplinary collaboration, where various experts come together to translate detailed imagery into significant biological insights. This review navigates the latest developments in microscopy, underscoring both the promise of and prerequisites for bending this powerful tool set to understanding neuronal cell biology.

Novel Therapeutic Horizons: SNCA Targeting in Parkinson's Disease.

Alpha-synuclein (αSyn) aggregates are the primary component of Lewy bodies, which are pathological hallmarks of Parkinson's disease (PD). The toxicity of αSyn seems to increase with its elevated expression during injury, suggesting that therapeutic approaches focused on reducing αSyn burden in neurons could be beneficial. Additionally, studies have shown higher levels of SNCA mRNA in the midbrain tissues and substantia nigra dopaminergic neurons of sporadic PD post-mortem brains compared to controls. Therefore, the regulation of SNCA expression and inhibition of αSyn synthesis could play an important role in the pathogenesis of injury, resulting in an effective treatment approach for PD. In this context, we summarized the most recent and innovative strategies proposed that exploit the targeting of SNCA to regulate translation and efficiently knock down cytoplasmatic levels of αSyn. Significant progress has been made in developing antisense technologies for treating PD in recent years, with a focus on antisense oligonucleotides and short-interfering RNAs, which achieve high specificity towards the desired target. To provide a more exhaustive picture of this research field, we also reported less common but highly innovative strategies, including small molecules, designed to specifically bind 5'-untranslated regions and, targeting secondary nucleic acid structures present in the SNCA gene, whose formation can be modulated, acting as a transcription and translation control. To fully describe the efficiency of the reported strategies, the effect of αSyn reduction on cellular viability and dopamine homeostasis was also considered.

IL-33 relieves nerve injury by mediating microglial polarization in neuromyelitis optica spectrum disorders via the IL-33/ST2 pathway

Interleukin-33 (IL-33) is a member of the interleukin-1 cytokine family. Its function in regulating microglial M1/M2 polarization in neuromyelitis optica spectrum disorder (NMOSD) is still unelucidated. To evaluate the role of IL-33 in NMOSD, we constructed NMOSD mice model by injecting purified serum IgG from AQP4-IgG seropositive NMOSD patients into experimental autoimmune encephalomyelitis (EAE) mice, and IL-33 was intraperitoneally injected into NMOSD mice 3 d before the model induction. We found that pretreatment of the NMOSD mice with IL-33 relieved brain neuron loss, and demyelination and improved the structure of axons, astrocytes, and mitochondria. In the neuronal and microglial coculture system, pretreatment with IL-33 in microglia alleviated NMOSD serum-induced inflammation and damaged morphology in cultured neurons. IL-33 transformed microglia to the M2 phenotype, and NMOSD serum promoted microglia to the M1 phenotype in cultured BV2 cells. Moreover, IL-33 influenced microglial polarity via the IL-33/ST2 pathway. IL-33 may be a novel insight useful for further developing NMOSD-targeted therapy and drug development.

Mechanism Analysis and Response of Digital Financial Inclusion to Labor Economy based on ANN and Contribution Analysis

Abstract Given the inclusiveness of digital inclusive finance (DFI) and its complex impact mechanism on the labor economy, this study uses the characteristics of adaptive and self-learning ability of artificial neural network (ANN) to simulate the process of delivering stimuli to nerve cells in the human brain through linear weighted summarization and functional mapping, and implement the optimization learning algorithm to adjust the weights in the network structure, thus completing the hierarchical analysis of index weight. At the same time, the neural network structure is used to approach the greatest extent and Garson algorithm is used for sensitivity analysis. We use data on the labor economy and digital financial inclusion in Heilongjiang, Jilin, and Liaoning provinces in China from 2011 to 2021 as a training dataset. The study found that (1) the indexes of DFI have different importance to the indexes of labor economy, among which the most important are the number and amount of insurance per capita and the proportion of the number and amount paid by digital technology, which have a normalized importance of 100 and 99.3%, further, R-square coverage is above 0.95, respectively, for labor economy indicators; (2) For different subdivided indicators, the indexes of DFI determine different significance. This study employs tools and policies related to DFI to address labor economy challenges, so as to promote the overall economic construction. This study studies the response and transmission mechanism of the concept of DFI to the labor economy, and explores the labor economy problems such as improving labor productivity and labor mismatch in the economy under its “inclusive” principle. Compared with the traditional weight analysis, it is closer to the real situation and has a stronger ability to fit the reality. In the future, the model could be rebased and measured against absolute indicators and a wider dataset could be adopted for extension to more areas.