scholarly journals Topology-preserving smoothing of retinotopic maps

2021 ◽  
Vol 17 (8) ◽  
pp. e1009216
Author(s):  
Yanshuai Tu ◽  
Duyan Ta ◽  
Zhong-Lin Lu ◽  
Yalin Wang
Keyword(s):  
Signal To Noise Ratio ◽  
Accurate Analysis ◽  
Visual Neuroscience ◽  
Retinotopic Mapping ◽  
Retinotopic Maps ◽  
Topological Condition ◽  
Visual Inputs ◽  
Human Connectome Project ◽  
Cortical Responses ◽  
Cortical Regions

Retinotopic mapping, i.e., the mapping between visual inputs on the retina and neuronal activations in cortical visual areas, is one of the central topics in visual neuroscience. For human observers, the mapping is obtained by analyzing functional magnetic resonance imaging (fMRI) signals of cortical responses to slowly moving visual stimuli on the retina. Although it is well known from neurophysiology that the mapping is topological (i.e., the topology of neighborhood connectivity is preserved) within each visual area, retinotopic maps derived from the state-of-the-art methods are often not topological because of the low signal-to-noise ratio and spatial resolution of fMRI. The violation of topological condition is most severe in cortical regions corresponding to the neighborhood of the fovea (e.g., < 1 degree eccentricity in the Human Connectome Project (HCP) dataset), significantly impeding accurate analysis of retinotopic maps. This study aims to directly model the topological condition and generate topology-preserving and smooth retinotopic maps. Specifically, we adopted the Beltrami coefficient, a metric of quasiconformal mapping, to define the topological condition, developed a mathematical model to quantify topological smoothing as a constrained optimization problem, and elaborated an efficient numerical method to solve the problem. The method was then applied to V1, V2, and V3 simultaneously in the HCP dataset. Experiments with both simulated and real retinotopy data demonstrated that the proposed method could generate topological and smooth retinotopic maps.

scholarly journals Heartbeat evokes a dynamically changing cortical theta-synchronized network in the resting state

2019 ◽  
Author(s):  
Jaejoong Kim ◽  
Bumseok Jeong
Keyword(s):  
Resting State ◽  
Phase Synchronization ◽  
Human Subjects ◽  
Predictive Coding ◽  
Regional Level ◽  
Human Connectome Project ◽  
Cortical Responses ◽  
Theta Frequency ◽  
Theta Phase ◽  
Cortical Regions

AbstractIn the resting state, heartbeats evoke cortical responses called heartbeat-evoked responses (HERs). While previous studies reported regional level HERs, researchers have not determined how heartbeat is processed at the cortical network level. Using resting-state magnetoencephalography data from 87 human subjects of both genders provided by the Human Connectome Project, we first showed that heartbeat increases the phase synchronization between cortical regions in the theta frequency, which forms a network structure, and we called this network a heartbeat-evoked network (HEN). The HEN was not an artefactual increase in phase synchronization. The HEN was partitioned into three modules with connector hubs in each module. The first module contained major interoception-related regions and thus was called a visceromotor-interoceptive network (VIN) displaying the strongest synchronization among modules, suggesting a major role for the VIN in processing heartbeat information. Two modules contained regions involved in the default mode network (DMN). The HEN structure was not fixed, but dynamically changed. The most prominent change was observed at approximately 200 ms after R-peak of the electrocardiogram, which was quantified based on the ‘flexibility’ of the network. Furthermore, the strongest synchronization within VIN was observed before heartbeat stimulated the cortex, which might be related to the prediction of an afferent heartbeat signal, thus supporting an interoceptive coding framework. Based on our results, the heartbeat is processed at the network level, and this result provides a useful framework that may potentially explain previous results of the regional level HER modulation through network-level processing.Significance statementThe resting-state network is composed of several networks supporting different functions. However, although the heartbeat is processed in the cortical regions, even in the resting state, the network supporting this function is unknown. Thus, we identified and investigated the heartbeat-evoked network (HEN), a network composed of significantly increased theta-phase synchronization between cortical regions after a heartbeat. The HEN comprised three modules. In particularly, the visceromotor-interoceptive network was likely to play a major role in network-level heartbeat processing and displayed the strongest synchronization immediately before the heartbeat enters the CNS, which supports an interoceptive predictive coding framework. These results provide a novel framework that may improve our understanding of cortical heartbeat processing from a network perspective.

scholarly journals Bayesian Analysis of Retinotopic Maps

2018 ◽  
Author(s):  
Noah C. Benson ◽  
Jonathan Winawer
Keyword(s):  
Natural Variation ◽  
Subjective Assessment ◽  
Measurement Noise ◽  
Fmri Data ◽  
Cortical Surface ◽  
Validation Data ◽  
Visual Neuroscience ◽  
Retinotopic Mapping ◽  
Retinotopic Maps ◽  
Bayesian Mapping

AbstractHuman visual cortex is organized into multiple retinotopic maps. Characterizing the arrangement of these maps on the cortical surface is essential to many visual neuroscience studies. Typically, maps are obtained by voxel-wise analysis of fMRI data. This method, while useful, maps only a portion of the visual field and is limited by measurement noise and subjective assessment of boundaries. We developed a novel Bayesian mapping approach which combines observation–a subject’s retinotopic measurements from small amounts of fMRI time–with a prior–a learned retinotopic atlas. This process automatically draws areal boundaries, corrects discontinuities in the measured maps, and predicts validation data more accurately than an atlas alone or independent datasets alone. This new method can be used to improve the accuracy of retinotopic mapping, to analyze large fMRI datasets automatically, and to quantify differences in map properties as a function of health, development and natural variation between individuals.

scholarly journals Bayesian analysis of retinotopic maps

eLife ◽  
2018 ◽  
Vol 7 ◽  
Author(s):  
Noah C Benson ◽  
Jonathan Winawer
Keyword(s):  
Natural Variation ◽  
Subjective Assessment ◽  
Measurement Noise ◽  
Fmri Data ◽  
Cortical Surface ◽  
Validation Data ◽  
Visual Neuroscience ◽  
Retinotopic Mapping ◽  
Retinotopic Maps ◽  
Bayesian Mapping

Human visual cortex is organized into multiple retinotopic maps. Characterizing the arrangement of these maps on the cortical surface is essential to many visual neuroscience studies. Typically, maps are obtained by voxel-wise analysis of fMRI data. This method, while useful, maps only a portion of the visual field and is limited by measurement noise and subjective assessment of boundaries. We developed a novel Bayesian mapping approach which combines observation–a subject’s retinotopic measurements from small amounts of fMRI time–with a prior–a learned retinotopic atlas. This process automatically draws areal boundaries, corrects discontinuities in the measured maps, and predicts validation data more accurately than an atlas alone or independent datasets alone. This new method can be used to improve the accuracy of retinotopic mapping, to analyze large fMRI datasets automatically, and to quantify differences in map properties as a function of health, development and natural variation between individuals.

scholarly journals Diffeomorphic Registration for Retinotopic Maps of Multiple Visual Regions

2021 ◽  
Author(s):  
Yanshuai Tu ◽  
Zhong-Lin Lu ◽  
Yalin Wang
Keyword(s):  
Surface Registration ◽  
Clinical Settings ◽  
Cortical Surface ◽  
Vision Science ◽  
Visual Neuroscience ◽  
Diffeomorphic Registration ◽  
Retinotopic Maps ◽  
Evaluation Protocol ◽  
Visual Inputs

Abstract Retinotopic map, the mapping between visual inputs on the retina and neuronal responses on cortical surface, is one of the central topics in vision science. Typically, human retinotopic maps are constructed by analyzing functional magnetic resonance responses to designed visual stimuli on cortical surface. Although it is widely used in visual neuroscience, retinotopic maps are limited by measurement noise and resolution. One promising approach to improve the quality of retinotopic maps is to register individual subject’s retinotopic maps to a retinotopic template or atlas. However, none of the existing retinotopic registration methods has explicitly quantified the diffeomorphic condition, that is, retinotopic maps can be aligned by stretching/compressing but without tearing up. Here, we developed Diffeomorphic Registration for Retinotopic Maps (DRRM) to simultaneously align retinotopic maps in multiple visual regions under the diffeomorphic condition. Specifically, we used the Beltrami coefficient to model the diffeomorphic condition and performed surface registration based on retinotopic coordinates. The overall framework is simple and elegant and preserves topological condition defined in the atlas. We further developed a unique performance evaluation protocol and compared the performance of the new method with several existing image intensity-based registration methods on both synthetic and real datasets. The results showed that DRRM is superior to the existing methods in achieving diffeomorphic mappings in synthetic and empirical data from 3T and 7T magnets. DRRM may improve the interpretation of low-quality retinotopic maps and facilitate adoption of retinotopic maps in clinical settings.

scholarly journals Anatomical and functional organization of the human substantia nigra and its connections

eLife ◽  
2017 ◽  
Vol 6 ◽  
Author(s):  
Yu Zhang ◽  
Kevin Michel-Herve Larcher ◽  
Bratislav Misic ◽  
Alain Dagher
Keyword(s):  
Substantia Nigra ◽  
Functional Organization ◽  
Impulsive Choice ◽  
Behavioral Measures ◽  
Human Connectome Project ◽  
Motor Impulsivity ◽  
Cortical Regions ◽  
Value Coding ◽  
Decisional Impulsivity ◽  
Human Substantia Nigra

We investigated the anatomical and functional organization of the human substantia nigra (SN) using diffusion and functional MRI data from the Human Connectome Project. We identified a tripartite connectivity-based parcellation of SN with a limbic, cognitive, motor arrangement. The medial SN connects with limbic striatal and cortical regions and encodes value (greater response to monetary wins than losses during fMRI), while the ventral SN connects with associative regions of cortex and striatum and encodes salience (equal response to wins and losses). The lateral SN connects with somatomotor regions of striatum and cortex and also encodes salience. Behavioral measures from delay discounting and flanker tasks supported a role for the value-coding medial SN network in decisional impulsivity, while the salience-coding ventral SN network was associated with motor impulsivity. In sum, there is anatomical and functional heterogeneity of human SN, which underpins value versus salience coding, and impulsive choice versus impulsive action.

scholarly journals Cytoarchitectonic similarity is a wiring principle of the human connectome

2016 ◽  
Author(s):  
Alexandros Goulas ◽  
René Werner ◽  
Sarah F Beul ◽  
Dennis Säring ◽  
Martijn van den Heuvel ◽  
...  
Keyword(s):  
Cerebral Cortex ◽  
Cortical Thickness ◽  
State Of The Art ◽  
Human Cerebral Cortex ◽  
Wiring Diagram ◽  
Classic Work ◽  
Human Connectome Project ◽  
Fundamental Challenge ◽  
Cortical Regions

AbstractUnderstanding the wiring diagram of the human cerebral cortex is a fundamental challenge in neuroscience. Elemental aspects of its organization remain elusive. Here we examine which structural traits of cortical regions, particularly their cytoarchitecture and thickness, relate to the existence and strength of inter-regional connections. We use the architecture data from the classic work of von Economo and Koskinas and state-of-the-art diffusion-based connectivity data from the Human Connectome Project. Our results reveal a prominent role of the cytoarchitectonic similarity of supragranular layers for predicting the existence and strength of connections. In contrast, cortical thickness similarity was not related to the existence or strength of connections. These results are in line with findings for non-human mammalian cerebral cortices, suggesting overarching wiring principles of the mammalian cerebral cortex. The results invite hypotheses about evolutionary conserved neurobiological mechanisms that give rise to the relation of cytoarchitecture and connectivity in the human cerebral cortex.

scholarly journals Topographic connectivity reveals task-dependent retinotopic processing throughout the human brain.

2020 ◽  
Author(s):  
Tomas Knapen
Keyword(s):  
Visual System ◽  
Spatial Organization ◽  
Brain Regions ◽  
Retinotopic Mapping ◽  
Visual Spatial ◽  
Retinotopic Maps ◽  
Sensory Predictions ◽  
Visual Organization ◽  
The Brain

The human visual system is organized as a hierarchy of maps that share the retina's topography. Although retinotopic maps have been identified throughout the brain, how much of the brain is visually organized remains unknown. Here we demonstrate widespread stable visual organization beyond the traditional visual system by analyzing topographic connectivity with primary visual cortex during moviewatching, rest, and retinotopic mapping. Detailed visual-spatial organization derived from retinotopic connectivity is modulated by experimental condition. Specifically, traditionally visual regions alternate with default mode network and hippocampus in preferentially representing the center of the visual field. This visual role of hippocampus would allow it to implement sensory predictions by interfacing between abstract memories and concrete perceptions. These results indicate that pervasive sensory coding facilitates the communication between far-flung brain regions.

scholarly journals The HCP 7T Retinotopy Dataset: Description and pRF Analysis

2018 ◽  
Author(s):  
Noah C. Benson ◽  
Keith W. Jamison ◽  
Michael J. Arcaro ◽  
An Vu ◽  
Matthew F. Glasser ◽  
...  
Keyword(s):  
Visual Processing ◽  
Large Scale ◽  
Individual Variability ◽  
7 Tesla ◽  
Individual Subject ◽  
Retinotopic Mapping ◽  
Human Connectome Project ◽  
The Brain ◽  
Model Based Analysis

AbstractAbout a quarter of human cerebral cortex is dedicated mainly to visual processing. The large-scale organization of visual cortex can be measured with functional magnetic resonance imaging (fMRI) while subjects view spatially modulated visual stimuli, also known as ‘retinotopic mapping’. One of the datasets collected by the Human Connectome Project (HCP) involved ultra-high-field (7 Tesla) fMRI retinotopic mapping in 181 healthy young adults (1.6-mm resolution), yielding the largest freely available collection of retinotopy data. Here, we describe the experimental paradigm and the results of model-based analysis of the fMRI data. These results provide estimates of population receptive field position and size. Our analyses include both results from individual subjects as well as results obtained by averaging fMRI time-series across subjects at each cortical and subcortical location and then fitting models. Both the group-average and individual-subject results reveal robust signals across much of the brain, including occipital, temporal, parietal, and frontal cortex as well as subcortical areas. The group-average results agree well with previously published parcellations of visual areas. In addition, split-half analyses show strong within-subject reliability, further demonstrating the high quality of the data. We make publicly available the analysis results for individual subjects and the group average, as well as associated stimuli and analysis code. These resources provide an opportunity for studying fine-scale individual variability in cortical and subcortical organization and the properties of high-resolution fMRI. In addition, they provide a set of observations that can be compared with other HCP measures acquired in these same participants.

scholarly journals Neural Measures of Pitch Processing in EEG Responses to Running Speech

2021 ◽  
Vol 15 ◽  
Author(s):  
Florine L. Bachmann ◽  
Ewen N. MacDonald ◽  
Jens Hjortkjær
Keyword(s):  
Speech Signal ◽  
Signal To Noise Ratio ◽  
Auditory Brainstem ◽  
Auditory Brainstem Responses ◽  
Speech Stimuli ◽  
Relative Pitch ◽  
Cortical Responses ◽  
Brainstem Response ◽  
Signal Yield ◽  
Model Predictor

Linearized encoding models are increasingly employed to model cortical responses to running speech. Recent extensions to subcortical responses suggest clinical perspectives, potentially complementing auditory brainstem responses (ABRs) or frequency-following responses (FFRs) that are current clinical standards. However, while it is well-known that the auditory brainstem responds both to transient amplitude variations and the stimulus periodicity that gives rise to pitch, these features co-vary in running speech. Here, we discuss challenges in disentangling the features that drive the subcortical response to running speech. Cortical and subcortical electroencephalographic (EEG) responses to running speech from 19 normal-hearing listeners (12 female) were analyzed. Using forward regression models, we confirm that responses to the rectified broadband speech signal yield temporal response functions consistent with wave V of the ABR, as shown in previous work. Peak latency and amplitude of the speech-evoked brainstem response were correlated with standard click-evoked ABRs recorded at the vertex electrode (Cz). Similar responses could be obtained using the fundamental frequency (F0) of the speech signal as model predictor. However, simulations indicated that dissociating responses to temporal fine structure at the F0 from broadband amplitude variations is not possible given the high co-variance of the features and the poor signal-to-noise ratio (SNR) of subcortical EEG responses. In cortex, both simulations and data replicated previous findings indicating that envelope tracking on frontal electrodes can be dissociated from responses to slow variations in F0 (relative pitch). Yet, no association between subcortical F0-tracking and cortical responses to relative pitch could be detected. These results indicate that while subcortical speech responses are comparable to click-evoked ABRs, dissociating pitch-related processing in the auditory brainstem may be challenging with natural speech stimuli.

scholarly journals Retrosplenial and postsubicular head direction cells compared during visual landmark discrimination

2017 ◽  
Vol 1 ◽  
pp. 239821281772185 ◽  
Author(s):  
Yave Roberto Lozano ◽  
Hector Page ◽  
Pierre-Yves Jacob ◽  
Eleonora Lomi ◽  
James Street ◽  
...  
Keyword(s):  
Cell Activity ◽  
Place Cell ◽  
Retrosplenial Cortex ◽  
Head Direction ◽  
Visual Landmarks ◽  
Tuning Curves ◽  
Visual Inputs ◽  
Visual Areas ◽  
Cortical Regions ◽  
Rapid Processing

Background: Visual landmarks are used by head direction (HD) cells to establish and help update the animal’s representation of head direction, for use in orientation and navigation. Two cortical regions that are connected to primary visual areas, postsubiculum (PoS) and retrosplenial cortex (RSC), possess HD cells: we investigated whether they differ in how they process visual landmarks. Methods: We compared PoS and RSC HD cell activity from tetrode-implanted rats exploring an arena in which correct HD orientation required discrimination of two opposing landmarks having high, moderate or low discriminability. Results: RSC HD cells had higher firing rates than PoS HD cells and slightly lower modulation by angular head velocity, and anticipated actual head direction by ~48 ms, indicating that RSC spiking leads PoS spiking. Otherwise, we saw no differences in landmark processing, in that HD cells in both regions showed equal responsiveness to and discrimination of the cues, with cells in both regions having unipolar directional tuning curves and showing better discrimination of the highly discriminable cues. There was a small spatial component to the signal in some cells, consistent with their role in interacting with the place cell navigation system, and there was also slight modulation by running speed. Neither region showed theta modulation of HD cell spiking. Conclusions: That the cells can immediately respond to subtle differences in spatial landmarks is consistent with rapid processing of visual snapshots or scenes; similarities in PoS and RSC responding may be due either to similar computations being performed on the visual inputs, or to rapid sharing of information between these regions. More generally, this two-cue HD cell paradigm may be a useful method for testing rapid spontaneous visual discrimination capabilities in other experimental settings.

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