Competition in neurite outgrowth and the development of nerve connections

The storage capacity of a directed graph and nodewise autonomous, ubiquitous learning

The brain, an exceedingly intricate information processing system, poses a constant challenge to memory research, particularly in comprehending how it encodes, stores, and retrieves information. Cognitive psychology studies memory mechanism from behavioral experiment level and fMRI level, and neurobiology studies memory mechanism from anatomy and electrophysiology level. Current research findings are insufficient to provide a comprehensive, detailed explanation of memory processes within the brain. Numerous unknown details must be addressed to establish a complete information processing mechanism connecting micro molecular cellular levels with macro cognitive behavioral levels. Key issues include characterizing and distributing content within biological neural networks, coexisting information with varying content, and sharing limited resources and storage capacity. Compared with the hard disk of computer mass storage, it is very clear from the polarity of magnetic particles in the bottom layer, the division of tracks and sectors in the middle layer, to the directory tree and file management system in the high layer, but the understanding of memory is not sufficient. Biological neural networks are abstracted as directed graphs, and the encoding, storage, and retrieval of information within directed graphs at the cellular level are explored. A memory computational model based on active directed graphs and node-adaptive learning is proposed. First, based on neuronal local perspectives, autonomous initiative, limited resource competition, and other neurobiological characteristics, a resource-based adaptive learning algorithm for directed graph nodes is designed. To minimize resource consumption of memory content in directed graphs, two resource-occupancy optimization strategies-lateral inhibition and path pruning-are proposed. Second, this paper introduces a novel memory mechanism grounded in graph theory, which considers connected subgraphs as the physical manifestation of memory content in directed graphs. The encoding, storage, consolidation, and retrieval of the brain's memory system correspond to specific operations such as forming subgraphs, accommodating multiple subgraphs, strengthening connections and connectivity of subgraphs, and activating subgraphs. Lastly, a series of experiments were designed to simulate cognitive processes and evaluate the performance of the directed graph model. Experimental results reveal that the proposed adaptive connectivity learning algorithm for directed graphs in this paper possesses the following four features: (1) Demonstrating distributed, self-organizing, and self-adaptive properties, the algorithm achieves global-level functions through local node interactions; (2) Enabling incremental storage and supporting continuous learning capabilities; (3) Displaying stable memory performance, it surpasses the Hopfield network in memory accuracy, capacity, and diversity, as demonstrated in experimental comparisons. Moreover, it maintains high memory performance with large-scale datasets; (4) Exhibiting a degree of generalization ability, the algorithm's macroscopic performance remains unaffected by the topological structure of the directed graph. Large-scale, decentralized, and node-autonomous directed graphs are suitable simulation methods. Examining storage problems within directed graphs can reveal the essence of phenomena and uncover fundamental storage rules hidden within complex neuronal mechanisms, such as synaptic plasticity, ion channels, neurotransmitters, and electrochemical activities.

miR-744 and miR-224 Downregulate Npas4 and Affect Lineage Differentiation Potential and Neurite Development During Neural Differentiation of Mouse Embryonic Stem Cells

Neuronal PAS domain protein 4 (Npas4) is a brain-specific transcription factor whose expression is enriched in neurogenic regions of the brain. In addition, it was demonstrated that Npas4 expression is dynamic and highly regulated during neural differentiation of embryonic stem cells (ESCs). While these findings implicate a role for Npas4 in neurogenesis, the underlying mechanisms of regulation remain unknown. Given that growing evidence suggests that microRNAs (miRNAs) play important roles in both embryonic and adult neurogenesis, we reasoned that miRNAs are good candidates for regulating Npas4 expression during neural differentiation of ESCs. In this study, we utilized the small RNA sequencing method to profile miRNA expression during neural differentiation of mouse ESCs. Two differentially expressed miRNAs were identified to be able to significantly reduce reporter gene activity by targeting the Npas4 3'UTR, namely miR-744 and miR-224. More importantly, ectopic expression of these miRNAs during neural differentiation resulted in downregulation of endogenous Npas4 expression. Subsequent functional analysis revealed that overexpression of either miR-744 or miR-224 delayed early neural differentiation, reduced GABAergic neuron production and inhibited neurite outgrowth. Collectively, our findings indicate that Npas4 not only functions at the early stages of neural differentiation but may also, in part, contribute to neuronal subtype specification and neurite development.

Insulin attenuates arsenic-induced neurite outgrowth impairments by activating the PI3K/Akt/SIRT1 signaling pathway

Arsenic neurotoxicity has a broad range of adverse effects on human health, which are induced in part by inhibition of neurite outgrowth. Insulin has been reported to promote neurite extension. The present study investigated whether insulin can protect neurons from impaired neurite outgrowth induced by arsenic, and examined the signaling pathway involved in this action. The study demonstrated that NaAsO2 caused inhibition of neurite outgrowth in differentiated SH-SY5Y cells indicating its neurotoxicity. This inhibitory effect of NaAsO2 was attenuated by insulin. It was found that blocking PI3K or Akt by selective inhibitors canceled the protective effect of insulin against NaAsO2-induced neurite outgrowth impairment suggesting the essential role of active PI3K and Akt in insulin's protective action. Inhibition of GSK3, which mimics an effect of insulin stimulation, had no effect on the impairment of neurite outgrowth by NaAsO2 implying that the insulin protective action is probably not due to its mediation of GSK3 inhibition ability. Moreover, NaAsO2 decreased the Akt activity, as it caused reduction in Akt phosphorylation, and downregulated expression of SIRT1. Additionally, the reduction of these signals by NaAsO2 was attenuated by insulin. Taken together, these results show that insulin attenuates arsenic-induced neurite outgrowth impairment possibly via activation of PI3K/Akt/SIRT1 signaling, and arsenic may exert neurite outgrowth inhibition through a mechanism involving reduction of signaling molecules downstream from insulin, PI3K/Akt/SIRT1. Our findings raise the possibility of using insulin to combat arsenic neurotoxicity.

Motor cortex electrical stimulation promotes axon outgrowth to brain stem and spinal targets that control the forelimb impaired by unilateral corticospinal injury

We previously showed that electrical stimulation of motor cortex (M1) after unilateral pyramidotomy in the rat increased corticospinal tract (CST) axon length, strengthened spinal connections, and restored forelimb function. Here, we tested: (i) if M1 stimulation only increases spinal axon length or if it also promotes connections to brain stem forelimb control centers, especially magnocellular red nucleus; and (ii) if stimulation-induced increase in axon length depends on whether pyramidotomy denervated the structure. After unilateral pyramidotomy, we electrically stimulated the forelimb area of intact M1, to activate the intact CST and other corticofugal pathways, for 10 days. We anterogradely labeled stimulated M1 and measured axon length using stereology. Stimulation increased axon length in both the spinal cord and magnocellular red nucleus, even though the spinal cord is denervated by pyramidotomy and the red nucleus is not. Stimulation also promoted outgrowth in the cuneate and parvocellular red nuclei. In the spinal cord, electrical stimulation caused increased axon length ipsilateral, but not contralateral, to stimulation. Thus, stimulation promoted outgrowth preferentially to the sparsely corticospinal-innervated and impaired side. Outgrowth resulted in greater axon density in the ipsilateral dorsal horn and intermediate zone, resembling the contralateral termination pattern. Importantly, as in spinal cord, increase in axon length in brain stem also was preferentially directed towards areas less densely innervated by the stimulated system. Thus, M1 electrical stimulation promotes increases in corticofugal axon length to multiple M1 targets. We propose the axon length change was driven by competition into an adaptive pattern resembling lost connections.

A quantitative approach to the dynamics of neurite sprouting induced by a neurotrophic factor

The sprouting, stabilization and growth of neurites is a dynamic process by which developing neurons establish connections with the other elements of the nervous system; this process is under the control of extracellular cues, among which neurotrophic factors play a crucial role. Due to the complexity of the spatiotemporal evolution of the neurite network, particularly in the early stages of growth, it is not easy to obtain information about the relevant parameters from qualitative observations. We have developed a quantitative description of the dynamics of production and stabilization of neuritic processes in a well-characterized experimental model of peripheral neurons in culture, and we have combined it with a simulation approach to extract the differences between the behaviour in the absence and in the presence of the neurotrophic factor basic Fibroblast Growth Factor (bFGF). We show that the factor rapidly stabilizes the neuronal morphology to a bipolar phenotype, by shifting the sprouting process from a disordered phase to a more ordered and organized one.

Verification of functional AAV-mediated neurotrophic and anti-apoptotic factor expression

The use of viral vectors for gene delivery offer many advantages for both basic research and therapeutic application through the continuous expression of a gene product within a target region. It is vital however that any gene product is correctly expressed in a biologically active form, and this should be confirmed prior to large scale in vivo studies. Using adeno-associated viral (AAV) vectors to direct the expression of either a neurotrophic factor or an anti-apoptotic protein, we have developed a range of in vitro assays to verify functional transgenic protein expression. Brain-derived neurotropic factor (BDNF) activity was confirmed by demonstrating enhanced generation of GABAergic neurons in embryonic (E15) striatal cultures and AAV-mediated glial-derived neurotrophic factor (GDNF) function using an assay for dopaminergic differentiation of embryonic (E14) ventral mesencephalic cultures. To assess functional anti-apoptotic factor expression we designed cell-survival assays, using embryonic cortical cultures to confirm Bcl-x(L) activity and the HT1080 cell-line for X-linked inhibitor of apoptosis protein (XIAP) activity following AAV-mediated expression. This study demonstrates that the use of functional assays provides valuable confirmation of desired biotherapeutic expression prior to extensive investigation with new gene delivery vectors.

Development of feedforward receptive field structure of a simple cell and its contribution to the orientation selectivity: a modeling study

Recent experimental studies of hetero-synaptic interactions in various systems have shown the role of signaling in the plasticity, challenging the conventional understanding of Hebb's rule. It has also been found that activity plays a major role in plasticity, with neurotrophins acting as molecular signals translating activity into structural changes. Furthermore, role of synaptic efficacy in biasing the outcome of competition has also been revealed recently. Motivated by these experimental findings we present a model for the development of simple cell receptive field structure based on the competitive hetero-synaptic interactions for neurotrophins combined with cooperative hetero-synaptic interactions in the spatial domain. We find that with proper balance in competition and cooperation, the inputs from two populations (ON/OFF) of LGN cells segregate starting from the homogeneous state. We obtain segregated ON and OFF regions in simple cell receptive field. Our modeling study supports the experimental findings, suggesting the role of synaptic efficacy and the role of spatial signaling. We find that using this model we obtain simple cell RF, even for positively correlated activity of ON/OFF cells. We also compare different mechanism of finding the response of cortical cell and study their possible role in the sharpening of orientation selectivity. We find that degree of selectivity improvement in individual cells varies from case to case depending upon the structure of RF field and type of sharpening mechanism.