Following a first version AAL of the automated anatomical labeling atlas (Tzourio-Mazoyer et al., 2002), a second version (AAL2) (Rolls et al., 2015) was developed that provided an alternative ...parcellation of the orbitofrontal cortex following the description provided by Chiavaras, Petrides, and colleagues. We now provide a third version, AAL3, which adds a number of brain areas not previously defined, but of interest in many neuroimaging investigations. The 26 new areas in the third version are subdivision of the anterior cingulate cortex into subgenual, pregenual and supracallosal parts; subdivision of the thalamus into 15 parts; the nucleus accumbens, substantia nigra, ventral tegmental area, red nucleus, locus coeruleus, and raphe nuclei. The new atlas is available as a toolbox for SPM, and can be used with MRIcron.
•The automated anatomical atlas 3 (AAL3) is described. The following new areas are added.•Subdivision of the anterior cingulate cortex into subgenual, pregenual and supracallosal parts.•Thalamus, nucleus accumbens, substantia nigra, ventral tegmental area, red nucleus.•Locus coeruleus, and raphe nuclei.•AAL3 is available as a toolbox for SPM at www.oxcns.org.
Sixth-generation (6G) mobile networks will have to cope with diverse threats on a space-air-ground integrated network environment, novel technologies, and an accessible user information explosion. ...However, for now, security and privacy issues for 6G remain largely in concept. This survey provides a systematic overview of security and privacy issues based on prospective technologies for 6G in the physical, connection, and service layers, as well as through lessons learned from the failures of existing security architectures and state-of-the-art defenses. Two key lessons learned are as follows. First, other than inheriting vulnerabilities from the previous generations, 6G has new threat vectors from new radio technologies, such as the exposed location of radio stripes in ultra-massive MIMO systems at Terahertz bands and attacks against pervasive intelligence. Second, physical layer protection, deep network slicing, quantum-safe communications, artificial intelligence (AI) security, platform-agnostic security, real-time adaptive security, and novel data protection mechanisms such as distributed ledgers and differential privacy are the top promising techniques to mitigate the attack magnitude and personal data breaches substantially.
Various attacks have emerged as the major threats to the success of a connected world like the Internet of Things (IoT), in which billions of devices interact with each other to facilitate human ...life. By exploiting the vulnerabilities of cheap and insecure devices such as IP cameras, an attacker can create hundreds of thousands of zombie devices and then launch massive volume attacks to take down any target. For example, in 2016, a record large-scale DDoS attack launched by millions of Mirai-injected IP cameras and smart printers blocked the accessibility of several high-profile websites. To date, the state-of-the-art defense systems against such attacks rely mostly on pre-defined features extracted from the entire flows or signatures. The feature definitions are manual, and it would be too late to block a malicious flow after extracting the flow features. In this work, we present an effective anomaly traffic detection mechanism, namely D-PACK, which consists of a Convolutional Neural Network (CNN) and an unsupervised deep learning model (e.g., Autoencoder) for auto-profiling the traffic patterns and filtering abnormal traffic. Notably, D-PACK inspects only the first few bytes of the first few packets in each flow for early detection. Our experimental results show that, by examining just the first two packets in each flow, D-PACK still performs with nearly 100% accuracy, while features an extremely low false-positive rate, e.g., 0.83%. The design can inspire the emerging efforts towards online anomaly detection systems that feature reducing the volume of processed packets and blocking malicious flows in time.
The first brain-wide voxel-level resting state functional connectivity neuroimaging analysis of depression is reported, with 421 patients with major depressive disorder and 488 control subjects. ...Resting state functional connectivity between different voxels reflects correlations of activity between those voxels and is a fundamental tool in helping to understand the brain regions with altered connectivity and function in depression. One major circuit with altered functional connectivity involved the medial orbitofrontal cortex Brodmann area 13, which is implicated in reward, and which had reduced functional connectivity in depression with memory systems in the parahippocampal gyrus and medial temporal lobe, especially involving the perirhinal cortex Brodmann area 36 and entorhinal cortex Brodmann area 28. The Hamilton Depression Rating Scale scores were correlated with weakened functional connectivity of the medial orbitofrontal cortex Brodmann area 13. Thus in depression there is decreased reward-related and memory system functional connectivity, and this is related to the depressed symptoms. The lateral orbitofrontal cortex Brodmann area 47/12, involved in non-reward and punishing events, did not have this reduced functional connectivity with memory systems. Second, the lateral orbitofrontal cortex Brodmann area 47/12 had increased functional connectivity with the precuneus, the angular gyrus, and the temporal visual cortex Brodmann area 21. This enhanced functional connectivity of the non-reward/punishment system (Brodmann area 47/12) with the precuneus (involved in the sense of self and agency), and the angular gyrus (involved in language) is thus related to the explicit affectively negative sense of the self, and of self-esteem, in depression. A comparison of the functional connectivity in 185 depressed patients not receiving medication and 182 patients receiving medication showed that the functional connectivity of the lateral orbitofrontal cortex Brodmann area 47/12 with these three brain areas was lower in the medicated than the unmedicated patients. This is consistent with the hypothesis that the increased functional connectivity of the lateral orbitofrontal cortex Brodmann area 47/12 is related to depression. Relating the changes in cortical connectivity to our understanding of the functions of different parts of the orbitofrontal cortex in emotion helps to provide new insight into the brain changes related to depression.
Estrogen is a disease‐modifying factor in multiple sclerosis (MS) and its animal model experimental autoimmune encephalomyelitis (EAE) via estrogen receptor alpha (ERα). However, the mechanisms by ...which ERα signaling contributes to changes in disease pathogenesis have not been completely elucidated. Here, we demonstrate that ERα deletion in dendritic cells (DCs) of mice induces severe neurodegeneration in the central nervous system in a mouse EAE model and resistance to interferon beta (IFNβ), a first‐line MS treatment. Estrogen synthesized by extragonadal sources is crucial for controlling disease phenotypes. Mechanistically, activated ERα directly interacts with TRAF3, a TLR4 downstream signaling molecule, to degrade TRAF3 via ubiquitination, resulting in reduced IRF3 nuclear translocation and transcription of membrane lymphotoxin (mLT) and IFNβ components. Diminished ERα signaling in DCs generates neurotoxic effector CD4+ T cells via mLT‐lymphotoxin beta receptor (LTβR) signaling. Lymphotoxin beta receptor antagonist abolished EAE disease symptoms in the DC‐specific ERα‐deficient mice. These findings indicate that estrogen derived from extragonadal sources, such as lymph nodes, controls TRAF3‐mediated cytokine production in DCs to modulate the EAE disease phenotype.
Synopsis
ERα signaling in dendritic cells (DCs) suppresses the activation of neurotoxic CD4+ T cells and thereby modulates mouse autoimmune disease phenotypes. This effect is mediated by endogenous estrogen derived from extragonadal sources.
Estrogen derived from extragonadal sites modulates disease phenotype in a mouse model of experimental autoimmune encephalomyelitis (EAE) dependent on ERα function in DCs.
DC‐specific ERα knockout mice express high levels of membrane lymphotoxin (mLT) and interferon beta (IFNβ) and show prolonged disease and severe neurodegeneration in the central nervous system.
ERα interacts with TRAF3 downstream of TLR4 activation to suppress the synthesis of IFNβ and mLT. Increased expression of IFNβ and mLT in the absence of ERα renders resistance to exogenous IFNβ treatment and induces neurodegeneration, respectively.
ERα signaling in dendritic cells suppresses the activation of neurotoxic CD4+ T cells and thereby modulates mouse autoimmune disease phenotypes. This effect is mediated by endogenous estrogen derived from extragonadal sources.
The role of cerebellum and cerebro-cerebellar system in neural plasticity induced by cerebral gliomas involving language network has long been ignored. Moreover, whether or not the process of ...reorganization is different in glioma patients with different growth kinetics remains largely unknown. To address this issue, we utilized preoperative structural and resting-state functional MRI data of 78 patients with left cerebral gliomas involving language network areas, including 46 patients with low-grade glioma (LGG, WHO grade II), 32 with high-grade glioma (HGG, WHO grade III/IV), and 44 healthy controls. Spontaneous brain activity, resting-state functional connectivity and gray matter volume alterations of the cerebellum were examined. We found that both LGG and HGG patients exhibited bidirectional alteration of brain activity in language-related cerebellar areas. Brain activity in areas with increased alteration was significantly correlated with the language and MMSE scores. Structurally, LGG patients exhibited greater gray matter volume in regions with increased brain activity, suggesting a structure-function coupled alteration in cerebellum. Furthermore, we observed that cerebellar regions with decreased brain activity exhibited increased functional connectivity with contralesional cerebro-cerebellar system in LGG patients. Together, our findings provide empirical evidence for a vital role of cerebellum and cerebro-cerebellar circuit in neural plasticity following lesional damage to cerebral language network. Moreover, we highlight the possible different reorganizational mechanisms of brain functional connectivity underlying different levels of behavioral impairments in LGG and HGG patients.
A modified and extended version, HCPex, is provided of the surface-based Human Connectome Project-MultiModal Parcellation atlas of human cortical areas (HCP-MMP v1.0, Glasser et al. 2016). The ...original atlas with 360 cortical areas has been modified in HCPex for ease of use with volumetric neuroimaging software, such as SPM, FSL, and MRIcroGL. HCPex is also an extended version of the original atlas in which 66 subcortical areas (33 in each hemisphere) have been added, including the amygdala, thalamus, putamen, caudate nucleus, nucleus accumbens, globus pallidus, mammillary bodies, septal nuclei and nucleus basalis. HCPex makes available the excellent parcellation of cortical areas in HCP-MMP v1.0 to users of volumetric software, such as SPM and FSL, as well as adding some subcortical regions, and providing labelled coronal views of the human brain.
PDF
