Information Processing Functions Research Articles

Social Information Processing and Executive Functions in Male Children and Adolescents with Internet Gaming Disorder.

In recent years, in addition to its clinical importance, interest in the social-cognitive aspect of internet gaming disorder (IGD) has increased. This study aimed to investigate autistic traits, executive functions, and self-regulation abilities of patients with IGD. Eighty-seven male patients with IGD and eighty-three male healthy controls (HC) were included in the study. All patients were diagnosed with IGD as per the diagnostic criteria of Diagnostic and Statistical Manual of Mental Disorders-5. Healthy controls without any comorbid psychiatric diagnosis were recruited from the community. The Brief Rating Inventory of Executive Function (BRIEF) and the Social Responsiveness Scale (SRS) were implemented to evaluate autistic traits, executive functions, and self-regulation skills. The Beck Depression Inventory (BDI), Screen for Child Anxiety and Related Disorders and Internet Gaming Disorder Scale-Short-Form were used to evaluate psychopathology. The effect size of the impairments in executive functions and self-regulation skills was large (Cohen's d = 1.0-2.0). IGD groups had higher levels of autistic traits compared to healthy controls (d = 1.0-1.4). The differences in BDI and BRIEF scores remained significant in logistic regression analysis. Age at illness-onset, total severity of anxiety, and autistic traits were found as significant correlates of deficits in executive functions among patients with IGD. The results of this study supported the higher autistic traits and poorer executive function skills of patients with IGD. Deficits in executive functions were associated with autistic traits and younger age-onset of the illness.

A novel method for efficient estimation of brain effective connectivity in EEG

Background and Objective: Brain connectivity plays a pivotal role in understanding the brain’s information processing functions by providing various details including magnitude, direction, and temporal dynamics of inter-neuron connections. While the connectivity may be classified as structural, functional and causal, a complete in-vivo directional analysis is guaranteed by the latter and is referred to as Effective Connectivity (EC). Two most widely used EC techniques are Directed Transfer Function (DTF) and Partial Directed Coherence (PDC) which are based on multivariate autoregressive models. The drawbacks of these techniques include poor frequency resolution and the requirement for experimental approach to determine signal normalization and thresholding techniques in identifying significant connectivities between multivariate sources.Methods: In this study, the drawbacks of DTF and PDC are addressed by proposing a novel technique, termed as Efficient Effective Connectivity (EEC), for the estimation of EC between multivariate sources using AR spectral estimation and Granger causality principle. In EEC, a linear predictive filter with AR coefficients obtained via multivariate EEG is used for signal prediction. This leads to the estimation of full-length signals which are then transformed into frequency domain by using Burg spectral estimation method. Furthermore, the newly proposed normalization method addressed the effect on each source in EEC using the sum of maximum connectivity values over the entire frequency range. Lastly, the proposed dynamic thresholding works by subtracting the first moment of causal effects of all the sources on one source from individual connections present for that source.Results: The proposed method is evaluated using synthetic and real resting-state EEG of 46 healthy controls. A 3D-Convolutional Neural Network is trained and tested using the PDC and EEC samples. The result indicates that compared to PDC, EEC improves the EEG eye-state classification accuracy, sensitivity and specificity by 5.57%, 3.15% and 8.74%, respectively.Conclusion: Correct identification of all connections in synthetic data and improved resting-state classification performance using EEC proved that EEC gives better estimation of directed causality and indicates that it can be used for reliable understanding of brain mechanisms. Conclusively, the proposed technique may open up new research dimensions for clinical diagnosis of mental disorders.

Task-dependent fractal patterns of information processing in working memory

We applied detrended fluctuation analysis, power spectral density, and eigenanalysis of detrended cross-correlations to investigate fMRI data representing a diurnal variation of working memory in four visual tasks: two verbal and two nonverbal. We show that the degree of fractal scaling is regionally dependent on the engagement in cognitive tasks. A particularly apparent difference was found between memorisation in verbal and nonverbal tasks. Furthermore, the detrended cross-correlations between brain areas were predominantly indicative of differences between resting state and other tasks, between memorisation and retrieval, and between verbal and nonverbal tasks. The fractal and spectral analyses presented in our study are consistent with previous research related to visuospatial and verbal information processing, working memory (encoding and retrieval), and executive functions, but they were found to be more sensitive than Pearson correlations and showed the potential to obtain other subtler results. We conclude that regionally dependent cognitive task engagement can be distinguished based on the fractal characteristics of BOLD signals and their detrended cross-correlation structure.

Modification of the CRITIC method using fuzzy rough numbers

This paper presents a new approach in the modification of the CRiteria Importance Through Intercriteria Correlation (CRITIC) method using fuzzy rough numbers. In the modified CRITIC method (CRITIC-M), the normalization procedure of the home matrix elements was improved and the aggregation function for information processing in the normalized home matrix was improved. By introducing a new way of normalization, smaller deviations between normalized elements are obtained, which affects smaller values of standard deviation. Thus, the relationships between the data in the initial decision matrix are presented in a more objective way. The introduction of a new way of aggregating the values of weights in the CRITIC-M method enables a more comprehensive view of information in the initial decision matrix, which leads to obtaining more objective values of weights. A new concept of fuzzy rough numbers was used to address uncertainties in the CRITIC-M methodology.

Astrocytes Learn to Detect and Signal Deviations From Critical Brain Dynamics.

Astrocytes are nonneuronal brain cells that were recently shown to actively communicate with neurons and are implicated in memory, learning, and regulation of cognitive states. Interestingly, these information processing functions are also closely linked to the brain's ability to self-organize at a critical phase transition. Investigating the mechanistic link between astrocytes and critical brain dynamics remains beyond the reach of cellular experiments, but it becomes increasingly approachable through computational studies. We developed a biologically plausible computational model of astrocytes to analyze how astrocyte calcium waves can respond to changes in underlying network dynamics. Our results suggest that astrocytes detect synaptic activity and signal directional changes in neuronal network dynamics using the frequency of their calcium waves. We show that this function may be facilitated by receptor scaling plasticity by enabling astrocytes to learn the approximate information content of input synaptic activity. This resulted in a computationally simple, information-theoretic model, which we demonstrate replicating the signaling functionality of the biophysical astrocyte model with receptor scaling. Our findings provide several experimentally testable hypotheses that offer insight into the regulatory role of astrocytes in brain information processing.

Intestinal Bacterial Diversity and Functional Analysis of Three Lepidopteran Corn Ear Worm Larvae

Simple SummaryCorn is one of the most important food crops in the world and comprises a large proportion of crops in China. Pests are one of the important factors affecting corn yield. Conogethes punctiferalis, Ostrinia furnacalis and Helicoverpa armigera are three main pests in the ear stages of corn, which significantly affect the yield and quality of corn. The three co-occurring lepidopteran pests at the ear stage occur frequently. Recently, the amount of Conogethes punctiferalis increased, even becoming the most serious pest in the Huang-Huai-Hai summer corn region of China, which is the second-largest corn producing area in China. Gut bacteria play important roles in insect adaptation to various environments. This study aimed to compare the diversity and function of the intestinal bacteria in three co-occurring lepidopteran pests, and to explore the reason for their prevalence. The results might provide insight into the prevalence of corn earworm larvae from the perspective of gut microbiota and function prediction.Insects, as the most abundant animal group on earth, and their symbionts help their hosts to adapt to various environments. Conogethes punctiferalis, Ostrinia furnacalis and Helicoverpa armigera are three main pests co-occurring in the ear stage of corn, which significantly affect the yield and quality of corn. The purpose of this study was to compare the diversity and function of the intestinal bacteria of the three co-occurring lepidopteran pests, C. punctiferalis, O. furnacalis and H. armigera, and to explore the reason of their prevalence from the microbiota’s view. Our results showed the difference of diversity and abundance of the gut bacteria of three co-occurring lepidopteran pests at the ear stage. Proteobacteria and Firmicutes were the dominant phyla, and the Enterobacteriaceae and Enterococcaceae were the dominant families in the three pests. Compared with the other two pests, Bacteroidetes was found much more in C. punctiferalis. In addition, C. punctiferalis showed more correlation and similarity in bacteria composition with corn endophytic bacteria, as well as had obvious advantages in metabolic, environmental information processing, cellular processes and organic systems function pathways. Our findings may provide insight into the prevalence of corn earworm larvae from the perspective of gut microbiota and function prediction.

Multifunctional plasmonic waveguide system based on coding metamaterials and inverse design

The benefits of low-power consumption, high throughput and high parallel processing suggest that optical computing has great potential for information processing. In this article, we propose a multifunctional plasmonic waveguide system (MPWS) to implement various optical functions based on metal coding metamaterials and inverse design technology. Due to the flexible and multivariant manipulation of electromagnetic waves with coding metamaterials, the MPWS can be utilized as an ultra-compact multifunctional component in integrated optical processors for optical computing. Because every optical component is designed by a same scheme, the MPWS avoids additional connection loss and waveguide coupling region caused by inconsistent interfaces and footprints. Driven by strong constraint of electromagnetic waves and overcoming the diffraction limit, the size of the core area in MPWS is only 400 nm × 500 nm. To demonstrate the effectiveness of the MPWS, we use it to implement four typical filtering functions and plasmon-induced transparency (PIT)-like effects. Especially, the Q-factor of PIT-like effects reaches to 58.13. Meanwhile, the simulation results optimized by inverse design technology show high consistency with that theoretically calculated by the combination of coupled-mode theory and the transfer-matrix method. Compared to previous works, our proposed MPWS not only provides a universal scheme to implement various optical information processing functions for optical computing but also shows the applications of inverse design on photonic devices.

High-density spin-wave soliton train

A new class of information technology, called magnonics, has been employed to develop several information-processing functionalities, such as logic gates, majority gates, and multiplexers. However, the application of these functionalities has been limited because the transmission loss of spin-wave signals makes combining these functionalities challenging. A promising technique called spin-wave soliton train was developed by experimental pioneers, however, the problem of information density was not yet overcome. In this study, a generation method of soliton train was revisited, and a 10 times larger density of spin-wave soliton train was achieved in time-domain electric experiments.

Differences in cognition, short-chain fatty acids and related metabolites in pregnant versus non-pregnant women: a cross-sectional study

BackgroundPregnancy induces cognitive reorganization which can lead to mental disorders. The aim of this study is to determine differences in cognitive scores, short-chain fatty acids (SCFAs) and related metabolites between pregnant and non-pregnant participants.MethodsThis cross-sectional study included 67 full-term pregnant women and 31 non-pregnant women. We compared scores of mental state and cognitive assessment tests, as well as serum concentrations of SCFAs, hormones, inflammatory factors, and neurotransmitters between these groups.ResultsScores for information processing speed, immediate visual memory, motor response speed and accuracy, execution ability and verbal use ability in the pregnant group were lower than those in the non-pregnant group (p < 0.05 for all tests). Total serum SCFAs in the pregnant group were significantly lower than those in the non-pregnant group (P = 0.031). Among them, acetate and propionate were significantly decreased (P = 0.013 and 0.037, respectively) whereas butyrate was significantly increased (P = 0.035). Serum peptide YY, glucagon-like peptide-1, γ-aminobutyric acid, and dopamine showed no differences between the two groups. However, cortisol, adrenocorticotropic hormone, and acetylcholine were significantly increased in the pregnant group as compared with the non-pregnant group (P = 0.039, 0.016, and 0.012, respectively). Tumor necrosis factor-α was increased and interleukin-10 significantly decreased in the pregnant group (P = 0.045 and 0.019, respectively).ConclusionAccording to our study findings, cognitive reorganization in the third trimester of pregnancy showed that both the passive storage capacity of working memory and the executive function of online information processing were decreased to varying degrees. At the same time, the changes in total SCFAs, the proportions of SCFAs and related metabolites were also detected. These changes in the internal environment may be increasing the risk of perinatal mental illness.

Depth-depended quality comparison of light-flavor fermented grains from two fermentation rounds

To improve the utilization of raw materials, the fermentation of light-flavor Baijiu (LFB) will usually take two rounds of fermentation to the same batch of raw materials. The microorganisms involved in the fermented grains (FG) from these two fermentation rounds are the key to the quality formation of light-flavor style. Using Illumina MiSeq high-throughput sequencing and electronic-senses, it was found that the microbiota and flavor of FG for light-flavor Baijiu were mainly affected by fermentation rounds rather than depths, while the physicochemical factors were just the opposite. Starch was the most influential physiochemical factor on the microbiota. FG from the first fermentation round (FFRFG) had a higher fungal diversity, while FG from the second fermentation round (SFRFG) had a higher microbial richness and bacterial diversity. Monascus and the function of metabolism were significantly enriched in FFRFG; while Nocardia, Saccharomyces, Aspergillus and the functions of information storage and processing as well as cellular processes and signaling were significantly enriched in SFRFG. The flavor characteristics of FFRFG were mainly sourness as well as rich in sulfur organic compounds and broad range compounds, while that of SFRFG was mainly saltiness, umami, and bitterness, as well as rich in aromatic compounds. The findings could contribute to a comprehensive understanding of the role of FG in LFB fermentation from the perspective of rounds and depths.

5G-BSS: 5G-Based Universal Blockchain Smart Sensors.

A smart sensor is a sensor with information processing functions. It is the product of the combination of sensor integration and a microprocessor. It has the characteristics of intelligence, networking and high precision. It has been widely used in aerospace, aviation, intelligent transportation, industrial control and medical and health care. However, in some specific application scenarios with high data security requirements and low transmission delay, such as environmental detection, transportation, etc., smart sensors have three obvious shortcomings. First, the data transmission delay is high. Second, the confidentiality and integrity of the data transmission process cannot be effectively guaranteed. Third, centralized data storage is easily leaked and tampered with by malicious users and semi-trusted administrators. Therefore, a 5G-based blockchain smart sensor 5G-BSS was designed. 5G-BSS has three innovation points. First, the 5G communication module enables the smart sensor 5G-BSS. The 5G communication module is integrated into the smart sensor 5G-BSS to reduce the delay of data transmission and improve the speed and reliability of data transmission. Second, cryptographic algorithms enable the smart sensor 5G-BSS. The data encryption module of the smart sensor 5G-BSS improves the confidentiality and integrity of the data transmission process. Third, blockchain empowers the smart sensor 5G-BSS. The blockchain client is integrated into the smart sensor 5G-BSS to ensure the centralized storage of data and prevent data leakage and tampering by semi-trusted administrators. The operation process of the hardware and software architecture is described in detail and tested on the Fisco-Bcos. The experimental results show that 5G-BSS not only has fast data transmission speed but also can effectively guarantee the integrity, confidentiality and availability of data. 5G-BSS is suitable for application scenarios with high requirements for data security and data transmission, such as environmental monitoring, intelligent transportation, autonomous driving, etc.

Comparison of Gut Microbiota Diversity Between Captive and Wild Tokay Gecko (Gekko gecko).

Captive animals and wild animals may exhibit different characteristics due to the heterogeneity of their living environments. The gut microbiota play an important role in the digestion and absorption, energy metabolism, immune regulation, and physiological health of the host. However, information about the gut microbiota of captive and wild Gekko gecko is currently limited. To determine the difference in gut microbiota community composition, diversity, and structure between captive and wild geckos, we used the Illumina miseq platform to conduct high-throughput sequencing and bioinformatics analysis of the v3–v4 hypervariable region of 16S rRNA in 54 gecko samples. Our results showed that Proteobacteria, Firmicutes, Bacteroidetes, and Actinobacteria were the dominant gut microbiota phyla of the gecko. The dominant genera comprised mainly Pseudomonas, Burkholderia-caballeronia-paraburkholderia, Ralstonia, Romboutsia, and Bacteroides. Captive geckos had significantly higher alpha diversity and potential pathogenic bacteria than wild populations. Moreover, significant differences in beta diversity of gut microbiota were observed between two populations. Functional prediction analysis showed that the relative abundance of functional pathways of wild geckos was more higher in metabolism, genetic information processing and organismal system function than those in captive geckos. Total length significantly affected gut microbial community (R2 = 0.4527, p = 0.001) and explained 10.45% of the total variation for gut microbial community variance between two groups. These results may be related to differences in diet and living environment between two populations, suggesting that the management of captive populations should mimic wild environments to the greatest extent possible to reduce the impact on their gut microbiota.

Neuropathic pain correlates with worsening cognition in people with human immunodeficiency virus.

Neuropathic pain and cognitive impairment are among the HIV-related conditions that have most stubbornly resisted amelioration by virally suppressive antiretroviral therapy. Overlaps between the regional brain substrates and mechanisms of neuropathic pain and cognitive disorders are increasingly recognized, yet no studies have examined the longitudinal relationship between these two disorders. Participants in the prospective, observational CNS HIV AntiRetroviral Therapy Effects Research (CHARTER) cohort underwent standardized clinical evaluations for clinical examination findings of distal sensory polyneuropathy, reporting distal neuropathic pain and neurocognitive performance at study entry (baseline) and an average of 12 years later. Change in neuropathic pain and neuropathy status from baseline to follow-up was by self-report and repeat examination, and change in neurocognitive performance was assessed using a previously published summary regression-based change score. Relationships between incident or worsened neuropathic pain and neurocognitive change were evaluated using uni- and multivariable regressions, including age at baseline and other relevant covariates. Participants were 385 people with HIV, 91 (23.6%) females, mean ± standard deviation (SD) age at baseline 43.5 (7.81) years, ethnicity 44.9% African American, 10.6% Hispanic, 42.6% non-Hispanic white and 1.82% other. Baseline median (interquartile range) nadir CD4 was 175 (34 309) cells/µl and current CD4 was 454 (279 639). Incident or worsened distal neuropathic pain occurred in 98 (25.5%) over the follow-up period. People with HIV with incident or worsened distal neuropathic pain had significantly worsened neurocognitive performance at follow-up compared to those without incident or worsened distal neuropathic pain (summary regression-based change score mean ± SD -0.408 ± 0.700 versus -0.228 ± 0.613; P = 0.0158). This effect remained significant when considering viral suppression on antiretroviral therapy, incident diabetes and other covariates as predictors. Overall neurocognitive change related to neuropathic pain was driven primarily by changes in the domains of executive function and speed of information processing. Those with incident distal neuropathy signs did not have neurocognitive worsening, nor did individuals who used opioid analgesics or other pain-modulating drugs such as amitriptyline. Worsened neurocognitive performance in people with HIV was associated with worsened neuropathic pain but not with changes in physical signs of neuropathy, and this was not attributable to therapies for pain or depression or to differences in viral suppression. This finding implies that incident or worsened pain may signal increased risk for neurocognitive impairment, and deserves more investigation, particularly if better pain management might stabilize or improve neurocognitive performance.

Response-related sensorimotor rhythms under scopolamine and MK-801 exposures in the touchscreen visual discrimination test in rats

The human mu rhythm has been suggested to represent an important function in information processing. Rodent homologue rhythms have been assumed though no study has investigated them from the cognitive aspect yet. As voluntary goal-directed movements induce the desynchronization of mu rhythm, we aimed at exploring whether the response-related brain activity during the touchscreen visual discrimination (VD) task is suitable to detect sensorimotor rhythms and their change under cognitive impairment. Different doses of scopolamine or MK-801 were injected subcutaneously to rats, and epidural electroencephalogram (EEG) was recorded during task performance. Arciform ~ 10 Hz oscillations appeared during visual processing, then two characteristic alpha/beta desynchronization-resynchronization patterns emerged mainly above the sensorimotor areas, serving presumably different motor functions. Beyond causing cognitive impairment, both drugs supressed the touch-related upper alpha (10–15 Hz) reactivity for desynchronization. Reaction time predominantly correlated positively with movement-related alpha and beta power both in normal and impaired conditions. These results support the existence of a mu homologue rodent rhythm whose upper alpha component appeared to be modulated by cholinergic and glutamatergic mechanisms and its power change might indicate a potential EEG correlate of processing speed. The VD task can be utilized for the investigation of sensorimotor rhythms in rats.

Upregulation of LncRNA71132 in the spinal cord regulates hypersensitivity in a rat model of bone cancer pain.

Bone cancer pain (BCP) is a pervasive clinical symptom which impairs the quality life. Long noncoding RNAs (lncRNAs) are enriched in the central nervous system and play indispensable roles in numerous biological processes, while its regulatory function in nociceptive information processing remains elusive. Here, we reported that functional modulatory role of ENSRNOT00000071132 (lncRNA71132) in the BCP process and sponging with miR-143 and its downstream GPR85-dependent signaling cascade. Spinal lncRNA71132 was remarkably increased in the rat model of bone cancer pain. The knockdown of spinal lncRNA71132 reverted BCP behaviors and spinal c-Fos neuronal sensitization. Overexpression of spinal lncRNA71132 in naive rat generated pain behaviors, which were accompanied by increased spinal c-Fos neuronal sensitization. Furthermore, it was found that lncRNA71132 participates in the modulation of BCP by inversely regulating the processing of miR-143-5p. In addition, an increase in expression of spinal lncRNA71132 resulted in the decrease in expression of miR-143 under the BCP state. Finally, it was found that miR-143-5p regulates pain behaviors by targeting GPR85. Overexpression of miR-143-5p in the spinal cord reverted the nociceptive behaviors triggered by BCP, accompanied by a decrease in expression of spinal GPR85 protein, but no influence on expression of gpr85 mRNA. The findings of this study indicate that lncRNA71132 works as a miRNA sponge in miR-143-5p-mediated posttranscriptional modulation of GPR85 expression in BCP. Therefore, epigenetic interventions against lncRNA71132 may potentially work as novel treatment avenues in treating nociceptive hypersensitivity triggered by bone cancer.

Evaluating Axon Conduction Characteristics of Cultured Sensory Neurons Toward Soft Robot Control

Information processing in axons has attracted attention for potential application in the control of soft robots. In this letter, we present the evaluation of axon conduction properties in cultured sensory neurons. Distal axons showed latency oscillations in response to high-frequency stimulation, thereby suggesting the suitability of our method for evaluating the information processing function of axons. Understanding axon information processing has a potential to contribute to the development of an advanced control method for soft robots.

Biogeographic patterns of benthic microbial communities in metal(loid)-contaminated semi-enclosed bay

Anthropogenic activities can adversely impact biogeochemical processes essential for maintaining ecosystem health in semi-enclosed bays. However, the influence of anthropogenic contaminants such as potentially toxic elements on microbial communities that regulate biogeochemical cycles in semi-enclosed bays is poorly understood. We determined the concentrations of four potentially toxic elements (Cu, Zn, Pb, and As) in sediments from a typical tropical semi-enclosed bay in Guangdong, China. Source apportionment using Pearson's correlation analysis revealed that aquaculture activities were probably the primary source of Cu, Zn, and Pb. Using high-throughput sediment DNA sequencing, we found that Proteobacteria was the dominant phylum in sediments. There was no evidence suggesting site-specific variation in microbial function even though sediments adjacent to aquaculture discharge points had higher microbial diversity. In contrast, pollutant-specific variations were observed; for example, Zn and Pd showed potential adverse effects on the environmental information processing function, while As showed a negative correlation with metabolic function. Based on different environmental characteristics, future research should consider the impact of multiple factors on the bacterial community in aquaculture systems.

Effect of cerebral small vessel disease on cognitive impairment in Parkinson's disease: a systematic review and meta-analysis.

BackgroundThe occurrence of various cerebrovascular diseases can easily induce cognitive impairment in the elderly. Therefore, it is of great clinical significance to correctly understand the relationship between these key pathogenic factors and cognitive impairment of Parkinson’s disease. To explore the effect of cerebrovascular disease on cognitive impairment in Parkinson’s disease by meta-analysis.MethodsPubMed, Medline, Embase, and Web of Science databases were selected as the sources for the literature search. English language articles were included. Literature related to this study were published from January 2001 to January 2021. Literature was screened and the quality was evaluated. RevMan 5.3 software was used to perform the meta-analysis on the effects of cerebrovascular disease on cognitive impairment in Parkinson’s disease.ResultsSix articles were finally included, involving a total of 5,552 cases. Of these, 2,684 were positive cases, accounting for 48.3%. Compared with patients with non-Parkinson’s cognitive impairment, patients with cognitive impairment in Parkinson’s disease caused by cerebral small vessel disease had significant differences in executive ability (OR =1.62, 95% CI: 1.21–2.16, P=0.001), memory (OR =1.48, 95% CI: 1.30–1.68, P<0.00001), information processing (OR =0.60, 95% CI: 0.35–1.03, P=0.07), language communication (OR= 4.72, 95% CI: 3.26–6.85, P<0.00001), and overall cognitive function (OR =0.72, 95% CI: 0.52–0.99, P=0.05).ConclusionsA total of 6 studies were included in this meta-analysis on the influence of cerebral small vessel disease on cognitive impairment in Parkinson’s disease. This study shows that cerebrovascular disease has different effects on all aspects of cognitive function of Parkinson’s disease.

Differential Serotonergic Modulation of Principal Neurons and Interneurons in the Anterior Piriform Cortex.

Originating from the brainstem raphe nuclei, serotonin is an important neuromodulator involved in a variety of physiological and pathological functions. Specific optogenetic stimulation of serotonergic neurons results in the divisive suppression of spontaneous, but not sensory evoked activity in the majority of neurons in the primary olfactory cortex and an increase in firing in a minority of neurons. To reveal the mechanisms involved in this dual serotonergic control of cortical activity we used a combination of in vitro electrophysiological recordings from identified neurons in the primary olfactory cortex, optogenetics and pharmacology and found that serotonin suppressed the activity of principal neurons, but excited local interneurons. The results have important implications in sensory information processing and other functions of the olfactory cortex and related brain areas.

Light‐Stimulated Synaptic Transistor with High PPF Feature for Artificial Visual Perception System Application

AbstractOptoelectronic synaptic devices, which combine the functions of photosensitivity and information processing, are essential for the development of artificial visual perception systems. Nevertheless, improving the paired pulse facilitation (PPF) index of optoelectronic synaptic devices, which is an urgent problem in the construction of high‐precision artificial visual perception systems, has received less attention so far. Herein, a light‐stimulated synaptic transistor (LSST) device with an ultra‐high PPF index (≈196%) is presented by introducing an ultra‐thin carrier regulator layer hexagonal boron nitride (h‐BN) into a classic graphene‐based hybrid transistor frame (graphene/CsPbBr3 quantum dots). Crucially, analysis of the rate‐limiting effect of h‐BN on photogenerated carriers reveals the mechanism behind the LSST ultra‐high PPF index. Furthermore, a two‐layer artificial neural network connected by LSST devices demonstrate ≈91.5% recognition accuracy of handwritten digits. This work provides an effective method for constructing artificial visual perception systems using a hybrid transistor frame in the future.