Publications by authors named "Masanori Shimono"

14 Publications

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Inhibitory neurons exhibit high controlling ability in the cortical microconnectome.

PLoS Comput Biol 2021 Apr 8;17(4):e1008846. Epub 2021 Apr 8.

Graduate Schools of Medicine, Kyoto University, Kyoto, Japan.

The brain is a network system in which excitatory and inhibitory neurons keep activity balanced in the highly non-random connectivity pattern of the microconnectome. It is well known that the relative percentage of inhibitory neurons is much smaller than excitatory neurons in the cortex. So, in general, how inhibitory neurons can keep the balance with the surrounding excitatory neurons is an important question. There is much accumulated knowledge about this fundamental question. This study quantitatively evaluated the relatively higher functional contribution of inhibitory neurons in terms of not only properties of individual neurons, such as firing rate, but also in terms of topological mechanisms and controlling ability on other excitatory neurons. We combined simultaneous electrical recording (~2.5 hours) of ~1000 neurons in vitro, and quantitative evaluation of neuronal interactions including excitatory-inhibitory categorization. This study accurately defined recording brain anatomical targets, such as brain regions and cortical layers, by inter-referring MRI and immunostaining recordings. The interaction networks enabled us to quantify topological influence of individual neurons, in terms of controlling ability to other neurons. Especially, the result indicated that highly influential inhibitory neurons show higher controlling ability of other neurons than excitatory neurons, and are relatively often distributed in deeper layers of the cortex. Furthermore, the neurons having high controlling ability are more effectively limited in number than central nodes of k-cores, and these neurons also participate in more clustered motifs. In summary, this study suggested that the high controlling ability of inhibitory neurons is a key mechanism to keep balance with a large number of other excitatory neurons beyond simple higher firing rate. Application of the selection method of limited important neurons would be also applicable for the ability to effectively and selectively stimulate E/I imbalanced disease states.
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http://dx.doi.org/10.1371/journal.pcbi.1008846DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8031186PMC
April 2021

3D Scanning Technology Bridging Microcircuits and Macroscale Brain Images in 3D Novel Embedding Overlapping Protocol.

J Vis Exp 2019 05 12(147). Epub 2019 May 12.

Graduate School of Medicine and Faculty of Medicine, Kyoto University;

The human brain, being a multiscale system, has both macroscopic electrical signals, globally flowing along thick white-matter fiber bundles, and microscopic neuronal spikes, propagating along axons and dendrites. Both scales complement different aspects of human cognitive and behavioral functions. At the macroscopic level, MRI has been the current standard imaging technology, in which the smallest spatial resolution, voxel size, is 0.1-1 mm. Also, at the microscopic level, previous physiological studies were aware of nonuniform neuronal architectures within such voxels. This study develops a powerful way to accurately embed microscopic data into a macroscopic map by interfacing biological scientific research with technological advancements in 3D scanning technology. Since 3D scanning technology has mostly been used for engineering and industrial design until now, it is repurposed for the first time to embed microconnectomes into the whole brain while preserving natural spiking in living brain cells. In order to achieve this purpose, first, we constructed a scanning protocol to obtain accurate 3D images from living bio-organisms inherently challenging to image due to moist and reflective surfaces. Second, we trained to keep speed to prevent the degradation of living brain tissue, which is a key factor in retaining better conditions and recording more natural neuronal spikes from active neurons in the brain tissue. Two cortical surface images, independently extracted from two different imaging modules, namely MRI and 3D scanner surface images, surprisingly show a distance error of only 50 μm as mode value of the histogram. This accuracy is comparable in scale to the microscopic resolution of intercellular distances; also, it is stable among different individual mice. This new protocol, the 3D novel embedding overlapping (3D-NEO) protocol, bridges macroscopic and microscopic levels derived by this integrative protocol and accelerates new scientific findings to study comprehensive connectivity architectures (i.e., microconnectome).
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http://dx.doi.org/10.3791/58911DOI Listing
May 2019

Author Correction: Efficient communication dynamics on macro-connectome, and the propagation speed.

Sci Rep 2018 May 3;8(1):7217. Epub 2018 May 3.

Institute of Industrial Science, The University of Tokyo, Komaba 4-6-1, Meguro, Tokyo, 153-8505, Japan.

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has been fixed in the paper.
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http://dx.doi.org/10.1038/s41598-018-25172-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5934446PMC
May 2018

Efficient communication dynamics on macro-connectome, and the propagation speed.

Sci Rep 2018 02 6;8(1):2510. Epub 2018 Feb 6.

Institute of Industrial Science, The University of Tokyo, Komaba 4-6-1, Meguro, Tokyo, 153-8505, Japan.

Global communication dynamics in the brain can be captured using fMRI, MEG, or electrocorticography (ECoG), and the global slow dynamics often represent anatomical constraints. Complementary single-/multi-unit recordings have described local fast temporal dynamics. However, global fast temporal dynamics remain incompletely understood with considering of anatomical constraints. Therefore, we compared temporal aspects of cross-area propagations of single-unit recordings and ECoG, and investigated their anatomical bases. First, we demonstrated how both evoked and spontaneous ECoGs can accurately predict latencies of single-unit recordings. Next, we estimated the propagation velocity (1.0-1.5 m/s) from brain-wide data and found that it was fairly stable among different conscious levels. We also found that the shortest paths in anatomical topology strongly predicted the latencies. Finally, we demonstrated that Communicability, a novel graph-theoretic measure, is able to quantify that more than 90% of paths should use shortest paths and the remaining are non-shortest walks. These results revealed that macro-connectome is efficiently wired for detailed communication dynamics in the brain.
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http://dx.doi.org/10.1038/s41598-018-20591-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5802747PMC
February 2018

High-Degree Neurons Feed Cortical Computations.

PLoS Comput Biol 2016 05 9;12(5):e1004858. Epub 2016 May 9.

Department of Physics, Indiana University, Bloomington, Indiana, United States of America.

Recent work has shown that functional connectivity among cortical neurons is highly varied, with a small percentage of neurons having many more connections than others. Also, recent theoretical developments now make it possible to quantify how neurons modify information from the connections they receive. Therefore, it is now possible to investigate how information modification, or computation, depends on the number of connections a neuron receives (in-degree) or sends out (out-degree). To do this, we recorded the simultaneous spiking activity of hundreds of neurons in cortico-hippocampal slice cultures using a high-density 512-electrode array. This preparation and recording method combination produced large numbers of neurons recorded at temporal and spatial resolutions that are not currently available in any in vivo recording system. We utilized transfer entropy (a well-established method for detecting linear and nonlinear interactions in time series) and the partial information decomposition (a powerful, recently developed tool for dissecting multivariate information processing into distinct parts) to quantify computation between neurons where information flows converged. We found that computations did not occur equally in all neurons throughout the networks. Surprisingly, neurons that computed large amounts of information tended to receive connections from high out-degree neurons. However, the in-degree of a neuron was not related to the amount of information it computed. To gain insight into these findings, we developed a simple feedforward network model. We found that a degree-modified Hebbian wiring rule best reproduced the pattern of computation and degree correlation results seen in the real data. Interestingly, this rule also maximized signal propagation in the presence of network-wide correlations, suggesting a mechanism by which cortex could deal with common random background input. These are the first results to show that the extent to which a neuron modifies incoming information streams depends on its topological location in the surrounding functional network.
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http://dx.doi.org/10.1371/journal.pcbi.1004858DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4861348PMC
May 2016

Rich-Club Organization in Effective Connectivity among Cortical Neurons.

J Neurosci 2016 Jan;36(3):670-84

Department of Physics and.

The performance of complex networks, like the brain, depends on how effectively their elements communicate. Despite the importance of communication, it is virtually unknown how information is transferred in local cortical networks, consisting of hundreds of closely spaced neurons. To address this, it is important to record simultaneously from hundreds of neurons at a spacing that matches typical axonal connection distances, and at a temporal resolution that matches synaptic delays. We used a 512-electrode array (60 μm spacing) to record spontaneous activity at 20 kHz from up to 500 neurons simultaneously in slice cultures of mouse somatosensory cortex for 1 h at a time. We applied a previously validated version of transfer entropy to quantify information transfer. Similar to in vivo reports, we found an approximately lognormal distribution of firing rates. Pairwise information transfer strengths also were nearly lognormally distributed, similar to reports of synaptic strengths. Some neurons transferred and received much more information than others, which is consistent with previous predictions. Neurons with the highest outgoing and incoming information transfer were more strongly connected to each other than chance, thus forming a "rich club." We found similar results in networks recorded in vivo from rodent cortex, suggesting the generality of these findings. A rich-club structure has been found previously in large-scale human brain networks and is thought to facilitate communication between cortical regions. The discovery of a small, but information-rich, subset of neurons within cortical regions suggests that this population will play a vital role in communication, learning, and memory. Significance statement: Many studies have focused on communication networks between cortical brain regions. In contrast, very few studies have examined communication networks within a cortical region. This is the first study to combine such a large number of neurons (several hundred at a time) with such high temporal resolution (so we can know the direction of communication between neurons) for mapping networks within cortex. We found that information was not transferred equally through all neurons. Instead, ∼70% of the information passed through only 20% of the neurons. Network models suggest that this highly concentrated pattern of information transfer would be both efficient and robust to damage. Therefore, this work may help in understanding how the cortex processes information and responds to neurodegenerative diseases.
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http://dx.doi.org/10.1523/JNEUROSCI.2177-15.2016DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4719009PMC
January 2016

Functional Clusters, Hubs, and Communities in the Cortical Microconnectome.

Cereb Cortex 2015 Oct 21;25(10):3743-57. Epub 2014 Oct 21.

Indiana University Bloomington, Bloomington, IN 47405, USA.

Although relationships between networks of different scales have been observed in macroscopic brain studies, relationships between structures of different scales in networks of neurons are unknown. To address this, we recorded from up to 500 neurons simultaneously from slice cultures of rodent somatosensory cortex. We then measured directed effective networks with transfer entropy, previously validated in simulated cortical networks. These effective networks enabled us to evaluate distinctive nonrandom structures of connectivity at 2 different scales. We have 4 main findings. First, at the scale of 3-6 neurons (clusters), we found that high numbers of connections occurred significantly more often than expected by chance. Second, the distribution of the number of connections per neuron (degree distribution) had a long tail, indicating that the network contained distinctively high-degree neurons, or hubs. Third, at the scale of tens to hundreds of neurons, we typically found 2-3 significantly large communities. Finally, we demonstrated that communities were relatively more robust than clusters against shuffling of connections. We conclude the microconnectome of the cortex has specific organization at different scales, as revealed by differences in robustness. We suggest that this information will help us to understand how the microconnectome is robust against damage.
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http://dx.doi.org/10.1093/cercor/bhu252DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4585513PMC
October 2015

Behavior modulates effective connectivity between cortex and striatum.

PLoS One 2014 11;9(3):e89443. Epub 2014 Mar 11.

Program in Neuroscience, Indiana University, Bloomington, Indiana, United States of America; Department of Physics, Indiana University, Bloomington, Indiana, United States of America.

It has been notoriously difficult to understand interactions in the basal ganglia because of multiple recurrent loops. Another complication is that activity there is strongly dependent on behavior, suggesting that directional interactions, or effective connections, can dynamically change. A simplifying approach would be to examine just the direct, monosynaptic projections from cortex to striatum and contrast this with the polysynaptic feedback connections from striatum to cortex. Previous work by others on effective connectivity in this pathway indicated that activity in cortex could be used to predict activity in striatum, but that striatal activity could not predict cortical activity. However, this work was conducted in anesthetized or seizing animals, making it impossible to know how free behavior might influence effective connectivity. To address this issue, we applied Granger causality to local field potential signals from cortex and striatum in freely behaving rats. Consistent with previous results, we found that effective connectivity was largely unidirectional, from cortex to striatum, during anesthetized and resting states. Interestingly, we found that effective connectivity became bidirectional during free behaviors. These results are the first to our knowledge to show that striatal influence on cortex can be as strong as cortical influence on striatum. In addition, these findings highlight how behavioral states can affect basal ganglia interactions. Finally, we suggest that this approach may be useful for studies of Parkinson's or Huntington's diseases, in which effective connectivity may change during movement.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0089443PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3949668PMC
May 2015

Non-uniformity of cell density and networks in the monkey brain.

Authors:
Masanori Shimono

Sci Rep 2013 ;3:2541

Dept. of Physics, Indiana University, Swain Hall West, 727 E. 3rd St., Bloomington, IN, 47405-7105, U.S.A.

The brain is a very complex structure. Over the past several decades, many studies have aimed to understand how various non-uniform variables relate to each other. The current study compared the whole-brain network organization and global spatial distribution of cell densities in the monkey brain. Wide comparisons between 27 graph theoretical measures and cell densities revealed that only participation coefficients (PCs) significantly correlated with cell densities. Interestingly, PCs did not show a significant correlation with spatial coordinates. Furthermore, the significance of the correlation between cell densities and spatial coordinates disappeared only with the removal of the visual module, while the significance of the correlation between cell densities and PCs disappeared with the removal of any one module. Taken together, these results suggested the presence of a combinatorial effect of modular architectures in the network organization related to the non-uniformity of cell densities additional to the spatially monotonic change.
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http://dx.doi.org/10.1038/srep02541DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3756338PMC
June 2014

Global mapping of the whole-brain network underlining binocular rivalry.

Brain Connect 2013 ;3(2):212-21

Department of Physics, Indiana University, Bloomington, Indiana 47405-7105, USA.

We investigated how the structure of the brain network relates to the stability of perceptual alternation in binocular rivalry. Historically, binocular rivalry has provided important new insights to our understandings in neuroscience. Although various relationships between the local regions of the human brain structure and perceptual switching phenomena have been shown in previous researches, the global organization of the human brain structural network relating to this phenomenon has not yet been addressed. To approach this issue, we reconstructed fiber-tract bundles using diffusion tensor imaging and then evaluated the correlations between the speeds of perceptual alternation and fractional anisotropy (FA) values in each fiber-tract bundle integrating among 84 brain regions. The resulting comparison revealed that the distribution of the global organization of the structural brain network showed positive or negative correlations between the speeds of perceptual alternation and the FA values. First, the connections between the subcortical regions stably were negatively correlated. Second, the connections between the cortical regions mainly showed positive correlations. Third, almost all other cortical connections that showed negative correlations were located in one central cluster of the subcortical connections. This contrast between the contribution of the cortical regions to destabilization and the contribution of the subcortical regions to stabilization of perceptual alternation provides important information as to how the global architecture of the brain structural network supports the phenomenon of binocular rivalry.
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http://dx.doi.org/10.1089/brain.2012.0129DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3634138PMC
November 2013

Universal critical dynamics in high resolution neuronal avalanche data.

Phys Rev Lett 2012 May 16;108(20):208102. Epub 2012 May 16.

Department of Physics, University of Illinois at Urbana-Champaign, 1110 West Green Street, Urbana, Illinois 61801, USA.

The tasks of neural computation are remarkably diverse. To function optimally, neuronal networks have been hypothesized to operate near a nonequilibrium critical point. However, experimental evidence for critical dynamics has been inconclusive. Here, we show that the dynamics of cultured cortical networks are critical. We analyze neuronal network data collected at the individual neuron level using the framework of nonequilibrium phase transitions. Among the most striking predictions confirmed is that the mean temporal profiles of avalanches of widely varying durations are quantitatively described by a single universal scaling function. We also show that the data have three additional features predicted by critical phenomena: approximate power law distributions of avalanche sizes and durations, samples in subcritical and supercritical phases, and scaling laws between anomalous exponents.
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http://dx.doi.org/10.1103/PhysRevLett.108.208102DOI Listing
May 2012

The brain structural hub of interhemispheric information integration for visual motion perception.

Cereb Cortex 2012 Feb 13;22(2):337-44. Epub 2011 Jun 13.

Graduate School of Education, University of Tokyo, Tokyo 113-0033, Japan.

We investigated the key anatomical structures mediating interhemispheric integration during the perception of apparent motion across the retinal midline. Previous studies of commissurotomized patients suggest that subcortical structures mediate interhemispheric transmission but the specific regions involved remain unclear. Here, we exploit interindividual variations in the propensity of normal subjects to perceive horizontal motion, in relation to vertical motion. We characterize these differences psychophysically using a Dynamic Dot Quartet (an ambiguous stimulus that induces illusory motion). We then tested for correlations between a tendency to perceive horizontal motion and fractional anisotropy (FA) (from structural diffusion tensor imaging), over subjects. FA is an indirect measure of the orientation and integrity of white matter tracts. Subjects who found it easy to perceive horizontal motion showed significantly higher FA values in the pulvinar. Furthermore, fiber tracking from an independently identified (subject-specific) visual motion area converged on the pulvinar nucleus. These results suggest that the pulvinar is an anatomical hub and may play a central role in interhemispheric integration.
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http://dx.doi.org/10.1093/cercor/bhr108DOI Listing
February 2012

Neural processes for intentional control of perceptual switching: a magnetoencephalography study.

Hum Brain Mapp 2011 Mar;32(3):397-412

Cognitive Neuroscience Group, Neuroscience Research Institute, AIST, Tsukuba Central 2, Tsukuba, Ibaraki 305-8568, Japan.

This article reports an interesting link between the psychophysical property of intentional control of perceptual switching and the underlying neural activities. First, we revealed that the timing of perceptual switching for a dynamical dot quartet can be controlled by the observers' intention, without eye movement. However, there is a clear limitation to this control, such that each animation frame of the stimulus must be presented for a sufficiently long time length; in other words, the frequency of the stimulus alternation must be sufficiently slow for the control. The typical stimulus onset asynchrony for a 50% level of success was about 275 ms for an average of 10 observers. On the basis of psychophysical property, we designed three experiments for investigating the neural process with a magnetoencephalography. They revealed that: (1) a peak component occurring about 300 ms after a reversal was stronger when the direction of perceived motion was switched intentionally than when it was not switched, and (2) neural components about 30-40 ms and 240-250 ms after the reversal of the stimulus animation were stronger when perception was altered intentionally than when it was switched unintentionally. The 300 ms component is consistent with a previous study about passive perceptual switching (Struber and Herrmann [ 2002]: Cogn Brain Res 14:370-382), but the intentional effect was seemed to be a different component from the well-known P300 component.
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http://dx.doi.org/10.1002/hbm.21022DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6870169PMC
March 2011

Functional modulation of power-law distribution in visual perception.

Phys Rev E Stat Nonlin Soft Matter Phys 2007 May 4;75(5 Pt 1):051902. Epub 2007 May 4.

Laboratory for Biological Complex Systems, Department of Complexity Science and Engineering, Graduate School of Frontier Science, The University of Tokyo, 5-1-5, Kashiwanoha, Kashiwa-Shi, Chiba, Japan.

Neuronal activities have recently been reported to exhibit power-law scaling behavior. However, it has not been demonstrated that the power-law component can play an important role in human perceptual functions. Here, we demonstrate that the power spectrum of magnetoencephalograph recordings of brain activity varies in coordination with perception of subthreshold visual stimuli. We observed that perceptual performance could be better explained by modulation of the power-law component than by modulation of the peak power in particular narrow frequency ranges. The results suggest that the brain operates in a state of self-organized criticality, modulating the power spectral exponent of its activity to optimize its internal state for response to external stimuli.
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http://dx.doi.org/10.1103/PhysRevE.75.051902DOI Listing
May 2007