Body-part-centered response fields are pervasive in single neurons, functional magnetic resonance imaging, electroencephalography and behavior, but there is no unifying formal explanation of their origins and role. In the present study, we used reinforcement learning and artificial neural networks to demonstrate that body-part-centered fields do not simply reflect stimulus configuration, but rather action value: they naturally arise from the basic assumption that agents often experience positive or negative reward after contacting environmental objects. This perspective successfully reproduces experimental findings that are foundational in the peripersonal space literature. It also suggests that peripersonal fields provide building blocks that create a modular model of the world near the agent: an egocentric value map. This concept is strongly supported by the emergent modularity that we observed in our artificial networks. The short-term, close-range, egocentric map is analogous to the long-term, long-range, allocentric hippocampal map. This perspective fits empirical data from multiple experiments, provides testable predictions and accommodates existing explanations of peripersonal fields.

When using different cameras and displays in the shot and display of one subject, different color images are often showed. To solve this problem, we have developed a color chart in which the constituent colors dyed with dyes are evenly distributed in the color space. We have also developed a tool that creates an International Color Consortium (ICC) profile from the captured image of this color chart. In this report, we will describe the color difference correction accuracy when our method is applied to actual stained pathological specimens taken with multiple whole-slide imaging (WSI). We confirmed color correction accuracy of Lab values in major parts such as the cell nucleus. The Lab value of the specimen itself measured by a spectrocolorimeter was compared with that of the captured image. As a result, the color difference ΔE in H&E-stained cell nucleus was improved from 32.2 to 6.4 for Nanozoomer and from 13.5 to 7.2 for ultra-fast scanner (UFS) by our color correction. The results of the evaluations for other areas and other stain methods (PAS, EVG, MT, and PAM) were good. In the future, high-accuracy color correction of teacher data/evaluation data in AI diagnosis using pathological images will be important.

The hippocampus has a major role in encoding and consolidating long-term memories, and undergoes plastic changes during sleep 1 . These changes require precise homeostatic control by subcortical neuromodulatory structures 2 . The underlying mechanisms of this phenomenon, however, remain unknown. Here, using multi-structure recordings in macaque monkeys, we show that the brainstem transiently modulates hippocampal network events through phasic pontine waves known as pontogeniculooccipital waves (PGO waves). Two physiologically distinct types of PGO wave appear to occur sequentially, selectively influencing high-frequency ripples and low-frequency theta events, respectively. The two types of PGO wave are associated with opposite hippocampal spike-field coupling, prompting periods of high neural synchrony of neural populations during periods of ripple and theta instances. The coupling between PGO waves and ripples, classically associated with distinct sleep stages, supports the notion that a global coordination mechanism of hippocampal sleep dynamics by cholinergic pontine transients may promote systems and synaptic memory consolidation as well as synaptic homeostasis.

Event Abstract Back to Event Local field potential activity in the macaque anterior insular cortex Jennifer Smuda1, 2, 3*, Carsten A. Klein1, Yusuke Murayama1, Thomas Steudel1, Eduard Krampe1, Axel Oeltermann1, Joachim Werner1, Nikos K. Logothetis1, 4 and Henry Evrard1, 2 1 Max Planck Inst Biol Cyb, Germany 2 Ctr Integr Nsci, Germany 3 Int Max Planck Res School, Germany 4 University of Manchester, Imaging Science and Biomedical Engineering, United Kingdom The central representation and the goal-directed control of homeostatic bodily states are integrated in the anterior insular cortex (AIC) as core processes underlying emotion, cognition, and subjective perception. The AIC has been thought as a “node” of the saliency network with a role in coordinating brain network activity based on the detection of homeostatic changes. A recent model proposed that the left and right AIC preferentially represent parasympathetic and sympathetic activity while underlying appetitive and aversive emotions, respectively. Given the possible role of the AIC in switching brain network activities, we examined whether this asymmetry occurs in the functional relation of the AIC with the rest of the brain. We used laminar electrodes to record local field potential activity in the left and right AIC while simultaneously acquiring functional magnetic resonance imaging (fMRI) scans in four rhesus macaque monkeys. The electrode was placed in the AIC area containing the von Economo neuron (or ‘VEN area’), an area shown previously to be larger and independently contain more VENs on the right than on the left side (Evrard et al. 2012 Neuron 74:482-9). The ongoing spontaneous neuronal activity was analyzed focusing on the local field potential (LFP) gamma band (56-79 Hz) where frequent increases in amplitude could be observed. These gamma events were in most cases unilateral, with occurrence either in the left or in the right VEN area in the majority of the cases and only few cases where gamma band activity increased simultaneously on both sides. Following the detection of these gamma events, their occurrence was used to trigger and average the blood-oxygen-level dependent (BOLD) signal from the fMRI scans, a method called ‘neural-event-triggered fMRI’ (NET-fMRI) (Logothetis et al. Nature 2012 491:547-53). The examination and mapping of the BOLD signal change during asymmetric events revealed markedly different patterns of activation and deactivation in vast regions of the brain. These effects might substantiate a fundamental autonomic forebrain asymmetry balancing complex nurturing and expending behaviors and feelings in a homeostatically optimal manner. Acknowledgements Work supported by Werner Reichardt Center for Integrative Neuroscience (H.C.E.), Max Planck Institute for Biological Cybernetics (N.K.L.), and International Max Planck Research School (J.S.). Keywords: insular cortex (IC), NETfMRI, Electrophysiology, fMRI, monkey Conference: 12th National Congress of the Belgian Society for Neuroscience, Gent, Belgium, 22 May - 22 May, 2017. Presentation Type: Poster Presentation Topic: Cognition and Behavior Citation: Smuda J, Klein CA, Murayama Y, Steudel T, Krampe E, Oeltermann A, Werner J, Logothetis NK and Evrard H (2019). Local field potential activity in the macaque anterior insular cortex. Front. Neurosci. Conference Abstract: 12th National Congress of the Belgian Society for Neuroscience. doi: 10.3389/conf.fnins.2017.94.00021 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 02 May 2017; Published Online: 25 Jan 2019. * Correspondence: Miss. Jennifer Smuda, Max Planck Inst Biol Cyb, Tuebingen, Germany, jennifer.smuda@tuebingen.mpg.de Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Jennifer Smuda Carsten A Klein Yusuke Murayama Thomas Steudel Eduard Krampe Axel Oeltermann Joachim Werner Nikos K Logothetis Henry Evrard Google Jennifer Smuda Carsten A Klein Yusuke Murayama Thomas Steudel Eduard Krampe Axel Oeltermann Joachim Werner Nikos K Logothetis Henry Evrard Google Scholar Jennifer Smuda Carsten A Klein Yusuke Murayama Thomas Steudel Eduard Krampe Axel Oeltermann Joachim Werner Nikos K Logothetis Henry Evrard PubMed Jennifer Smuda Carsten A Klein Yusuke Murayama Thomas Steudel Eduard Krampe Axel Oeltermann Joachim Werner Nikos K Logothetis Henry Evrard Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.

The default mode network (DMN) is a commonly observed resting-state network (RSN) that includes medial temporal, parietal, and prefrontal regions involved in episodic memory [1-3]. The behavioral relevance of endogenous DMN activity remains elusive, despite an emerging literature correlating resting fMRI fluctuations with memory performance [4, 5]-particularly in DMN regions [6-8]. Mechanistic support for the DMN's role in memory consolidation might come from investigation of large deflections (sharp-waves) in the hippocampal local field potential that co-occur with high-frequency (>80 Hz) oscillations called ripples-both during sleep [9, 10] and awake deliberative periods [11-13]. Ripples are ideally suited for memory consolidation [14, 15], since the reactivation of hippocampal place cell ensembles occurs during ripples [16-19]. Moreover, the number of ripples after learning predicts subsequent memory performance in rodents [20-22] and humans [23], whereas electrical stimulation of the hippocampus after learning interferes with memory consolidation [24-26]. A recent study in macaques showed diffuse fMRI neocortical activation and subcortical deactivation specifically after ripples [27]. Yet it is unclear whether ripples and other hippocampal neural events influence endogenous fluctuations in specific RSNs-like the DMN-unitarily. Here, we examine fMRI datasets from anesthetized monkeys with simultaneous hippocampal electrophysiology recordings, where we observe a dramatic increase in the DMN fMRI signal following ripples, but not following other hippocampal electrophysiological events. Crucially, we find increases in ongoing DMN activity after ripples, but not in other RSNs. Our results relate endogenous DMN fluctuations to hippocampal ripples, thereby linking network-level resting fMRI fluctuations with behaviorally relevant circuit-level neural dynamics.

Illumination condition is one of the most important factors in imaging. Due to the relatively complex interaction occurring when an incident light is irradiated on the surface of an object, it has been a topic of researches and studies for quite a while now. In this study, its influence on the reconstruction of spectral reflectance and image stitching was explored. A traditional Japanese painting was used as the target. Spectral reflectance was estimated using pseudoinverse model from multispectral images captured with seven different filters with spectral features covering 380-850 nm wavelengths. It was observed that the accuracy of the estimation is dependent on the quality of multispectral images, which are greatly influenced by lighting conditions. High specular reflection on the target yielded large amount of estimation errors. In addition, the spectral feature of the filters was shown to be important. Data from at (cast four filters are necessary to get a satisfactory reconstruction. On the other hand, it was observed that in addition to specular reflection, the distribution of light highly affects image stitching. Image stitching is important especially when acquiring images of large objects. It was shown that multispectral images could be used for the analytical imaging of artworks.

We proposed an improved method for camera metamer density estimation. Camera metamer is a set of spectral reflectance of object surface which induce an identical RGB response of a color imaging devices such as a digital color camera and scanner. It is desirable for high fidelity color correction to calculate the set of metamers and then choose the optimal value in a standard color space. Previous methods adopted too simple models to represent the constraint of spectral reflectance. The set of metamers were over-estimated and it declined the accuracy of color correction. We modeled the constraint of spectral reflectance as an identical ellipsoidal Gaussian mixture distribution, and tested and compared the proposed model and two conventional models in a numerical experiment. It was found that the proposed model can represent accurately the underlying caved patterns within the given dataset and avoid generating inappropriate camera metamers. The accuracy of color correction was also evaluated supposing two commercial cameras and two standard illuminants. It was shown that higher accuracy color correction was achieved by adopting the proposed model.