scholarly journals Large-Scale Cortical Networks for Hierarchical Prediction and Prediction Error in the Primate Brain

Neuron ◽  
2018 ◽  
Vol 100 (5) ◽  
pp. 1252-1266.e3 ◽  
Author(s):  
Zenas C. Chao ◽  
Kana Takaura ◽  
Liping Wang ◽  
Naotaka Fujii ◽  
Stanislas Dehaene
2018 ◽  
Author(s):  
Zenas C. Chao ◽  
Kana Takaura ◽  
Liping Wang ◽  
Naotaka Fujii ◽  
Stanislas Dehaene

Author(s):  
Katherine L. Bryant ◽  
Dirk Jan Ardesch ◽  
Lea Roumazeilles ◽  
Lianne H. Scholtens ◽  
Alexandre A. Khrapitchev ◽  
...  

AbstractLarge-scale comparative neuroscience requires data from many species and, ideally, at multiple levels of description. Here, we contribute to this endeavor by presenting diffusion and structural MRI data from eight primate species that have not or rarely been described in the literature. The selected samples from the Primate Brain Bank cover a prosimian, New and Old World monkeys, and a great ape. We present preliminary labelling of the cortical sulci and tractography of the optic radiation, dorsal part of the cingulum bundle, and dorsal parietal–frontal and ventral temporal-frontal longitudinal white matter tracts. Both dorsal and ventral association fiber systems could be observed in all samples, with the dorsal tracts occupying much less relative volume in the prosimian than in other species. We discuss the results in the context of known primate specializations and present hypotheses for further research. All data and results presented here are available online as a resource for the scientific community.


2019 ◽  
Author(s):  
Daniel A Llano ◽  
Chihua Ma ◽  
Umberto Di Fabrizio ◽  
Aynaz Taheri ◽  
Kevin A. Stebbings ◽  
...  

AbstractNetwork analysis of large-scale neuroimaging data has proven to be a particularly challenging computational problem. In this study, we adapt a novel analytical tool, known as the community dynamic inference method (CommDy), which was inspired by social network theory, for the study of brain imaging data from an aging mouse model. CommDy has been successfully used in other domains in biology; this report represents its first use in neuroscience. We used CommDy to investigate aging-related changes in network parameters in the auditory and motor cortices using flavoprotein autofluorescence imaging in brain slices and in vivo. Analysis of spontaneous activations in the auditory cortex of slices taken from young and aged animals demonstrated that cortical networks in aged brains were highly fragmented compared to networks observed in young animals. Specifically, the degree of connectivity of each activated node in the aged brains was significantly lower than those seen in the young brain, and multivariate analyses of all derived network metrics showed distinct clusters of these metrics in young vs. aged brains. CommDy network metrics were then used to build a random-forests classifier based on NMDA-receptor blockade data, which successfully recapitulated the aging findings, suggesting that the excitatory synaptic substructure of the auditory cortex may be altered during aging. A similar aging-related decline in network connectivity was also observed in spontaneous activity obtained from the awake motor cortex, suggesting that the findings in the auditory cortex are reflections of general mechanisms that occur during aging. Therefore, CommDy therefore provides a new dynamic network analytical tool to study the brain and provides links between network-level and synaptic-level dysfunction in the aging brain.


Neurology ◽  
2019 ◽  
Vol 92 (22) ◽  
pp. e2550-e2558 ◽  
Author(s):  
Gianluca Coppola ◽  
Antonio Di Renzo ◽  
Barbara Petolicchio ◽  
Emanuele Tinelli ◽  
Cherubino Di Lorenzo ◽  
...  

ObjectiveWe investigated resting-state (RS)-fMRI using independent component analysis (ICA) to determine the functional connectivity (FC) between networks in chronic migraine (CM) patients and their correlation with clinical features.MethodsTwenty CM patients without preventive therapy or acute medication overuse underwent 3T MRI scans and were compared to a group of 20 healthy controls (HC). We used MRI to collect RS data in 3 selected networks, identified using group ICA: the default mode network (DMN), the executive control network (ECN), and the dorsal attention system (DAS).ResultsCompared to HC, CM patients had significantly reduced functional connectivity between the DMN and the ECN. Moreover, in patients, the DAS showed significantly stronger FC with the DMN and weaker FC with the ECN. The higher the severity of headache, the increased the strength of DAS connectivity, and the lower the strength of ECN connectivity.ConclusionThese results provide evidence for large-scale reorganization of functional cortical networks in chronic migraine. They suggest that the severity of headache is associated with opposite connectivity patterns in frontal executive and dorsal attentional networks.


2019 ◽  
Vol 116 (49) ◽  
pp. 24861-24871 ◽  
Author(s):  
Michael J. Arcaro ◽  
Peter F. Schade ◽  
Margaret S. Livingstone

Topographic sensory maps are a prominent feature of the adult primate brain. Here, we asked whether topographic representations of the body are present at birth. Using functional MRI (fMRI), we find that the newborn somatomotor system, spanning frontoparietal cortex and subcortex, comprises multiple topographic representations of the body. The organization of these large-scale body maps was indistinguishable from those in older monkeys. Finer-scale differentiation of individual fingers increased over the first 2 y, suggesting that topographic representations are refined during early development. Last, we found that somatomotor representations were unchanged in 2 visually impaired monkeys who relied on touch for interacting with their environment, demonstrating that massive shifts in early sensory experience in an otherwise anatomically intact brain are insufficient for driving cross-modal plasticity. We propose that a topographic scaffolding is present at birth that both directs and constrains experience-driven modifications throughout somatosensory and motor systems.


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