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By mimicking the neurons and synapses of the human brain and employing spiking neural networks on neuromorphic chips, neuromorphic computing offers a promising energy-efficient machine intelligence. How to borrow high-level brain dynamic mechanisms to help neuromorphic computing achieve energy advantages is a fundamental issue. This work presents an application-oriented algorithm-software-hardware co-designed neuromorphic system for this issue. First, we design and fabricate an asynchronous chip called “Speck”, a sensing-computing neuromorphic system on chip. With the low processor resting power of 0.42mW, Speck can satisfy the hardware requirements of dynamic computing: no-input consumes no energy. Second, we uncover the “dynamic imbalance” in spiking neural networks and develop an attention-based framework for achieving the algorithmic requirements of dynamic computing: varied inputs consume energy with large variance. Together, we demonstrate a neuromorphic system with real-time power as low as 0.70mW. This work exhibits the promising potentials of neuromorphic computing with its asynchronous event-driven, sparse, and dynamic nature. Mimicking high-level abstraction of the brain to achieve energy advantages is a fundamental issue in neuromorphic computing. Here, the authors fabricate an asynchronous chip and demonstrate a high-accuracy neuromorphic system with power consumption of 0.7mW.

Alzheimer's disease (AD) is a common neurodegenerative disease in which the brain undergoes alterations for decades before symptoms become obvious. Subjective cognitive decline (SCD) have self-complain of persistent decline in cognitive function especially in memory but perform normally on standard neuropsychological tests. SCD with the presence of AD pathology is the transitional stage 2 of Alzheimer's continuum, earlier than the prodromal stage, mild cognitive impairment (MCI), which seems to be the best target to research AD. In this study, we aimed to detect the transformational patterns of the intrinsic brain activity as the disease burden got heavy. In this study, we enrolled 44 SCD, 55 amnestic MCI (aMCI), 47 AD dementia (d-AD) patients and 57 normal controls (NC) in total. A machine learning classification was utilized to detect identification accuracies between groups by using ALFF, fALFF, and fusing ALFF with fALFF features. Then, we measured the amplitude of the low-frequency fluctuation (ALFF) and fractional ALFF (fALFF) levels in three frequency bands (classic: 0.01-0.1 Hz; slow-5: 0.01-0.027 Hz; and slow-4: 0.027-0.073 Hz) and compared alterations in patients with NC. In the machine learning verification, the identification accuracy of SCD, aMCI, d-AD from NC was higher when fused ALFF and fALFF features (76.44, 81.94, and 91.83%, respectively) than only using ALFF or fALFF features. Several brain regions showed significant differences in ALFF/fALFF within these bands among four groups: brain regions presented decreasing trend of values, including the Cingulum_Mid_R (aal), bilateral inferior cerebellum lobe, bilateral precuneus, and the Cingulum_Ant_R (aal); increasing trend of values were detected in the Hippocampus_L (aal), Frontal_Mid_Orb_R (aal), Frontal_Sup_R (aal) and Paracentral_Lobule_R (aal) as disease progressed. The normalized ALFF/fALFF values of these features were significantly correlated with the neuropsychological test scores. This study revealed gradual disturbances in intrinsic brain activity as the disease progressed: the normal objective performance in SCD may be dependent on compensation; as disease advanced, the cognitive function gradually impaired and decompensated in aMCI, severer in d-AD. Our results indicated that the ALFF and fALFF may help detect the underlying pathological mechanism in AD continuum. ClinicalTrials.gov, identifier NCT02353884 and NCT02225964.

The hippocampal CA3 contributes to spatial working memory (SWM), but which stage of SWM the CA3 neurons act on and whether the lateralization of CA3 function occurs in SWM is also unknown. Here, we reveal increased neural activity in both sample and choice phases of SWM. Left CA3 (LCA3) neurons show higher sensitivity in the choice phase during the correct versus error trials compared with right CA3 (RCA3) neurons. LCA3 initiates firing prior to RCA3 in the choice phase. Optogenetic suppression of pyramidal neurons in LCA3 disrupts SWM only in the choice phase. Furthermore, we discover that parvalbumin (PV) neurons, rather than cholinergic neurons in the medial septum (DB were cholinergic neurons), can project directly to unilateral CA3. Selective suppression of PV neurons in the MS projecting to LCA3 impairs SWM. The findings suggest that MS PV -LCA3 projection plays a crucial role in manipulating the lateralization of LCA3 in the retrieval of SWM. The CA3 region of the hippocampus is involved in spatial working memory. Here, the authors show that neurons in the left CA3 are more active in the choice phase of correct trials of spatial working memory than neurons in the right CA3, revealing lateralization of spatial working memory.

Parkinson’s disease (PD) can be considered as the dysfunction in segregation and integration of large-scale structural networks in the late stage of disease progression. However, the altered patterns in the early stage have not been extensively investigated, especially the altered structural rich-club patterns, which is proved powerful to detect the altered patterns of structural networks in Alzheimer’s disease and schizophrenia. To this end, we investigated the rich-club organization of the structural networks derived from diffusion tensor imaging (DTI) data in the early stage of PD, and further investigated the relationship between rich-club organization and clinicopathological measures, including motor and non-motor scales and cerebrospinal fluid (CSF) biomarkers. Two datasets were included for validation in this study. The first one included 41 healthy controls (HC) and 64 PD patients from Parkinson’s Disease Progression Marker Initiative (PPMI) dataset, and the second one included 24 HC and 26 PD patients. Results revealed that PD patients in early stage had disrupted rich-club organization, with abnormal connectivity strength between peripheral regions (two-sample t-test between PD and HC: p < 0.001), whereas connectivity strength between rich-club regions remained relatively stable (two-sample t-test between PD and HC: p = 0.108). The classification accuracies on three types of connections were 59.93%, 73.96% and 77.44% for rich-club, feeder and local connections. Furthermore, abnormal local and feeder connections showed significant correlation with poor clinical scales and CSF biomarkers. In summary, a selective disruption of non-rich-club connections here could be regarded as a potential marker in the early diagnosis of PD.

IntroductionWe aimed to investigate whether Interleukin-29 (IL-29) directly affects T follicular helper (Tfh) cell frequency in rheumatoid arthritis (RA), which are both related to RA-specific antibody responses.MethodsHere, we explored the effect of IL-29 on Tfh cell production in RA patients using a combination of enzyme-linked immunosorbent assay (ELISA), flow cytometry (FCM), CD4+ T cell culture, western blotting, and reverse transcription–polymerase chain reaction (RT-PCR).ResultsWe reported that serum IL-29 levels, peripheral blood CD4+CXCR5+ Tfh cell frequency, CD4+CXCR5+CD40L+ Tfh cell frequency, and IL-28 receptor (IL-28Rα) and IL-10 receptor (IL-10R2) levels in peripheral blood Tfh cells were higher in RA patients than in healthy controls (HCs). Serum IL-29 levels were positively correlated with peripheral blood CD4+CXCR5+CD40L+ Tfh cell frequency in RA patients, and both parameters also correlated with anti-cyclic citrullinated peptide (anti-CCP) antibodies. Furthermore, we showed that IL-29 may suppress Tfh cell differentiation in RA patients partly via decreased BCL6 level through reduced STAT3 activity.ConclusionsTaken together, our findings reveal the regulatory effect of IL-29 on Tfh cells, which participate in the pathogenesis of RA and provide new targets for its clinical treatment.Key Points• There is an increase in circulating Tfh cells and IL-29 levels in RA patients, which are correlated to anti-CCP antibodies levels and may be associated with RA pathogenesis.• We show for the first time that IL-29 may contribute to RA by inhibiting Tfh cell production, through decreasing the activity of STAT3 and downregulating the expression of BCL6.• The use of IL-29 biologics in patients with RA inhibits the production of Tfh cells, may prevent progression in patients with RA, and provides new targets for clinical treatment.

•MR-compatible hand-adaptive multichannel device for tactile stimulation.•Somatotopic maps of the human hand in primary somatosensory cortex in between- and within-digit dimensions using 7T fMRI.•Somatotopic map in random order paradigm verified the leading function of the thumb compared to other fingers. The 7T functional magnetic resonance imaging (fMRI) can provide a detailed somatotopic map. However, due to the constraints of MR-compatible applications, current tactile stimulation devices for the human hand are insufficient for precise somatotopic mapping experiments. In this study, we developed a novel 23-channel, hand-adaptive tactile stimulation device with high temporal and spatial resolution. The device consisted of an execution module and a control module. The device's output performance was measured using a laser displacement sensor. We investigated the somatotopic map of the non-dominant hand in the primary somatosensory cortex (S1) using the Bayesian population receptive field (pRF) model. The activation patterns, relative volumes, and activation center locations on S1 were assessed in somatotopic mapping experiments involving traveling wave stimulus paradigms with three stimulus orders (forward, backward, and random) in two dimensions (between-digit and within-digit). The percussive stimulation provided by the tactile stimulation device exhibited a stable displacement (2.58 mm) and a minimal output delay (4.45 milliseconds) across a wide range of vibration frequencies (0–30 Hz). The representation of digits and the palm in the between-digit dimension showed consistent somatotopic organization (D1-D2-D3-D4-D5-palm along the postcentral gyrus (poCG) from ventral to dorsal) across all three stimulation orders. Additionally, the relative volume of D1 in the random paradigm was significantly larger than in the forward and backward paradigms. The relative volume of the palm in the random paradigm was significantly larger than in the backward paradigm. The representation of the phalanges and palm in the within-digit dimension exhibited different activation patterns across different stimulation orders. These results provide new insights into the neural mechanisms in S1 and validate that the developed stimulation device can contribute to exploring the somatotopic map of the human hand.

Alzheimer’s disease (AD) is the most common neurodegenerative disease in elderly individuals. We conducted this study to examine whether alterations in the fractional amplitudes of low-frequency fluctuations (fALFF) in the AD spectrum were frequency-dependent and symptom-relevant. A total of 43 patients with subjective cognitive decline (SCD), 52 with amnestic mild cognitive impairment (aMCI), 44 with Alzheimer’s dementia (d-AD) and 55 well-matched controls participated in resting-state functional magnetic resonance imaging (rs-fMRI) scans. The amplitudes were measured using fALFF within the slow-4 (0.027–0.073 Hz) and slow-5 (0.01–0.027 Hz) bands. Repeated-measures analysis of variance was performed on fALFF within two bands and correlated with neuropsychological test scores. The significant main effects of frequency and group on fALFF differed widely across brain regions. There were more varied areas in the slow-5 band than the slow-4 band. The fALFF associated with primary disease effects was mainly distributed in the parietal lobe. Obvious frequency band and group interaction effects were observed in the left angular gyrus, left calcarine fissure and surrounding cortex, left superior cerebellum, left cuneus and right lingual gyrus. Neuropsychological tests scores were significantly correlated with the fALFF magnitude of the left cuneus and right lingual in the slow-5 band. Our results suggested that the AD continuum had abnormal amplitudes in intrinsic brain activity, and these abnormalities were frequency-dependent and mainly associated with the slow-5 band rather than the slow-4 band. This may guide the frequency choice of future rs-fMRI studies and provide new insights into the neuropathophysiology of AD.

Background: Multiple sclerosis (MS) biomarker identification is important for pathogenesis research and diagnosis in routine clinical practice. Cerebrospinal fluid (CSF) and blood cytokines as potential biomarkers that can inform MS pathogenesis, diagnosis and response to treatment have been assessed in numerous studies. However, there have been no comprehensive meta-analyses to pool cytokine data and to address their diagnostic performance. We systematically reviewed literature with meta-analyses to assess the alteration levels of cytokines and chemokines in MS. Methods: We searched PubMed and Web of Science for articles published between January 1, 1990 and April 30, 2018 for this systematic review and meta-analysis. Data were extracted from 226 included studies encompassing 13,526 MS patients and 8,428 controls. Biomarker performance was rated by a random-effects meta-analysis based on the standard mean difference between cytokine concentration in patients with MS and controls, or patients before and after treatments. Results: Of the 26 CSF cytokines and 37 blood cytokines for potential differentiation between MS patients and controls, the random-effects meta-analysis showed that 13 CSF cytokines and 21 blood cytokines were significantly increased in MS patients in comparison to the controls. Interestingly, TNF-α, CXCL8, IL-15, IL-12p40, and CXCL13 were increased in both blood and CSF of MS patients. For those cytokines analyzed in at least 10 studies, differentiation between case and control was strong for CSF CXCL13, blood IL-2R, and blood IL-23; CSF CXCL8, blood IL-2, and blood IL-17 also performed well in differentiating between MS patients and controls, whereas those of CSF TNF-α and blood TNF-α, CXCL8, IL-12, IFN-γ were moderate. Furthermore, CSF IL-15, CCL19, CCL11, CCL-3, and blood CCL20, IL-12p40, IL-21, IL-17F, IL-22 had large effective sizes when differentiating between MS patients and controls but had a relatively small number of studies (three to seven studies). Conclusion: Our findings clarified the circulating cytokine profile in MS, which provide targets for disease modifying treatments, and suggest that cytokines have the potential to be used as biomarkers for MS.Background: Multiple sclerosis (MS) biomarker identification is important for pathogenesis research and diagnosis in routine clinical practice. Cerebrospinal fluid (CSF) and blood cytokines as potential biomarkers that can inform MS pathogenesis, diagnosis and response to treatment have been assessed in numerous studies. However, there have been no comprehensive meta-analyses to pool cytokine data and to address their diagnostic performance. We systematically reviewed literature with meta-analyses to assess the alteration levels of cytokines and chemokines in MS. Methods: We searched PubMed and Web of Science for articles published between January 1, 1990 and April 30, 2018 for this systematic review and meta-analysis. Data were extracted from 226 included studies encompassing 13,526 MS patients and 8,428 controls. Biomarker performance was rated by a random-effects meta-analysis based on the standard mean difference between cytokine concentration in patients with MS and controls, or patients before and after treatments. Results: Of the 26 CSF cytokines and 37 blood cytokines for potential differentiation between MS patients and controls, the random-effects meta-analysis showed that 13 CSF cytokines and 21 blood cytokines were significantly increased in MS patients in comparison to the controls. Interestingly, TNF-α, CXCL8, IL-15, IL-12p40, and CXCL13 were increased in both blood and CSF of MS patients. For those cytokines analyzed in at least 10 studies, differentiation between case and control was strong for CSF CXCL13, blood IL-2R, and blood IL-23; CSF CXCL8, blood IL-2, and blood IL-17 also performed well in differentiating between MS patients and controls, whereas those of CSF TNF-α and blood TNF-α, CXCL8, IL-12, IFN-γ were moderate. Furthermore, CSF IL-15, CCL19, CCL11, CCL-3, and blood CCL20, IL-12p40, IL-21, IL-17F, IL-22 had large effective sizes when differentiating between MS patients and controls but had a relatively small number of studies (three to seven studies). Conclusion: Our findings clarified the circulating cytokine profile in MS, which provide targets for disease modifying treatments, and suggest that cytokines have the potential to be used as biomarkers for MS.

•High inter-subject variability for brain fingerprinting and cognitive behavior predicting.•Conditional deep generative network for extracting shared information of inter-subject.•Embed the state information into the conditional deep generative network.•High accuracy based on a large number of subjects and numerous states.•Higher fingerprinting is useful for resulting in higher behavioral associations. The functional connectivity (FC) graph of the brain has been widely recognized as a ``fingerprint'' that can be used to identify individuals from a group of subjects. Research has indicated that individual identification accuracy can be improved by eliminating the impact of shared information among individuals. However, current research extracts not only shared information of inter-subject but also individual-specific information from FC graphs, resulting in incomplete separation of shared information and fingerprint information among individuals, leading to lower individual identification accuracy across all functional magnetic resonance imaging (fMRI) states session pairs and poor cognitive behavior prediction performance. In this paper, we propose a method to enhance inter-subject variability combining conditional variational autoencoder (CVAE) network and sparse dictionary learning (SDL) module. By embedding fMRI state information in the encoding and decoding processes, the CVAE network can better capture and represent the common features among individuals and enhance inter-subject variability by residual. Our experimental results on Human Connectome Project (HCP) data show that the refined connectomes obtained by using CVAE with SDL can accurately distinguish an individual from the remaining participants. The success accuracies reached 99.7 % and 99.6 % in the session pair rest1-rest2 and reverse rest2-rest1, respectively. In the identification experiment involving task-task combinations carried out on the same day, the identification accuracies ranged from 94.2 % to 98.8 %. Furthermore, we showed the Frontoparietal and Default networks make the most significant contributions to individual identification and the edges that significantly contribute to individual identification are found within and between the Frontoparietal and Default networks. Additionally, high-level cognitive behaviors can also be better predicted with the obtained refined connectomes, suggesting that higher fingerprinting can be useful for resulting in higher behavioral associations. In summary, our proposed framework provides a promising approach to use functional connectivity networks for studying cognition and behavior, promoting a deeper understanding of brain functions.

Background MicroRNAs (miRNAs) are implicated in the progression of ischemic stroke (IS) and bone marrow-derived mesenchymal stem cells (BMSCs)-derived exosomes play a role in IS therapy. Herein we hypothesized that the BMSCs-derived exosomes containing overexpressed miR-138-5p could protect the astrocytes following IS involved with lipocalin 2 (LCN2). Methods The differentially expressed gene related to IS was initially identified by bioinformatics analysis. miR-138-5p was predicted to regulate LCN2. The expression of miR-138-5p and LCN2 was altered in the oxygen-glucose deprivation (OGD)-induced astrocytes. Furthermore, the cell behaviors and inflammatory responses were evaluated both in astrocytes alone and astrocytes co-cultured with exosomes derived from BMSCs overexpressing miR-138-5p to explore the involvement of miR-138-5p and LCN2 in IS. Besides, middle cerebral artery occlusion (MCAO) mouse model was established to explore the effect of BMSCs-derived exosomal miR-138-5p in IS in vivo. Results LCN2 was highly expressed in IS. Besides, LCN2 was a target gene of miR-138-5p. BMSCs-derived exosomes could be endocytosed by astrocytes via co-culture. Overexpression of miR-138-5p promoted the proliferation and inhibited apoptosis of astrocytes injured by OGD, accompanied by the reduced expression of inflammatory factors, which was achieved by down-regulating LCN2. More importantly, BMSCs delivered miR-138-5p to the astrocytes via exosomes and BMSCs-derived exosomal miR-138-5p alleviated neuron injury in IS mice. Conclusion BMSCs-derived exosomal miR-138-5p reduces neurological impairment by promoting proliferation and inhibiting inflammatory responses of astrocytes following IS by targeting LCN2, which may provide a novel target for IS treatment.