scholarly journals Spontaneous perception: a framework for task-free, self-paced perception

2021 ◽  
Vol 2021 (2) ◽  
Author(s):  
Shira Baror ◽  
Biyu J He
Keyword(s):  
Time Course ◽  
Visual Experience ◽  
Brain Activity ◽  
Human Perception ◽  
Future Research ◽  
Task Constraints ◽  
Spontaneous Brain Activity ◽  
The Brain ◽  
Coarse To Fine ◽  
Organizing Principles

Abstract Flipping through social media feeds, viewing exhibitions in a museum, or walking through the botanical gardens, people consistently choose to engage with and disengage from visual content. Yet, in most laboratory settings, the visual stimuli, their presentation duration, and the task at hand are all controlled by the researcher. Such settings largely overlook the spontaneous nature of human visual experience, in which perception takes place independently from specific task constraints and its time course is determined by the observer as a self-governing agent. Currently, much remains unknown about how spontaneous perceptual experiences unfold in the brain. Are all perceptual categories extracted during spontaneous perception? Does spontaneous perception inherently involve volition? Is spontaneous perception segmented into discrete episodes? How do different neural networks interact over time during spontaneous perception? These questions are imperative to understand our conscious visual experience in daily life. In this article we propose a framework for spontaneous perception. We first define spontaneous perception as a task-free and self-paced experience. We propose that spontaneous perception is guided by four organizing principles that grant it temporal and spatial structures. These principles include coarse-to-fine processing, continuity and segmentation, agency and volition, and associative processing. We provide key suggestions illustrating how these principles may interact with one another in guiding the multifaceted experience of spontaneous perception. We point to testable predictions derived from this framework, including (but not limited to) the roles of the default-mode network and slow cortical potentials in underlying spontaneous perception. We conclude by suggesting several outstanding questions for future research, extending the relevance of this framework to consciousness and spontaneous brain activity. In conclusion, the spontaneous perception framework proposed herein integrates components in human perception and cognition, which have been traditionally studied in isolation, and opens the door to understand how visual perception unfolds in its most natural context.

scholarly journals Altered Spontaneous Brain Activity in Schizophrenia: A Meta-Analysis and a Large-Sample Study

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Yongjie Xu ◽  
Chuanjun Zhuo ◽  
Wen Qin ◽  
Jiajia Zhu ◽  
Chunshui Yu
Keyword(s):  
Posterior Parietal Cortex ◽  
Brain Activity ◽  
Meta Analysis ◽  
Temporal Cortex ◽  
Likelihood Estimation ◽  
Occipital Cortex ◽  
Future Research ◽  
Similar Distribution ◽  
Large Sample ◽  
Spontaneous Brain Activity

Altered spontaneous brain activity as measured by ALFF, fALFF, and ReHo has been reported in schizophrenia, but no consensus has been reached on alternations of these indexes in the disorder. We aimed to clarify the regional alterations in ALFF, fALFF, and ReHo in schizophrenia using a meta-analysis and a large-sample validation. A meta-analysis of activation likelihood estimation was conducted based on the abnormal foci of ten studies. A large sample of 86 schizophrenia patients and 89 healthy controls was compared to verify the results of the meta-analysis. Meta-analysis demonstrated that the alternations in ALFF and ReHo had similar distribution in schizophrenia patients. The foci with decreased ALFF/fALFF and ReHo in schizophrenia were mainly located in the somatosensory cortex, posterior parietal cortex, and occipital cortex; however, foci with increased ALFF/fALFF and ReHo were mainly located in the bilateral striatum, medial temporal cortex, and medial prefrontal cortex. The large-sample study showed consistent findings with the meta-analysis. These findings may expound the pathophysiological hypothesis and guide future research.

scholarly journals Abnormal Baseline Brain Activity in Patients with Pulsatile Tinnitus: A Resting-State fMRI Study

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Lv Han ◽  
Liu Zhaohui ◽  
Yan Fei ◽  
Li Ting ◽  
Zhao Pengfei ◽  
...  
Keyword(s):  
Resting State ◽  
Structural Changes ◽  
Brain Activity ◽  
Inferior Frontal Gyrus ◽  
Low Frequency ◽  
Resting State Fmri ◽  
Pulsatile Tinnitus ◽  
Spontaneous Brain Activity ◽  
Fmri Study ◽  
The Brain

Numerous investigations studying the brain functional activity of the tinnitus patients have indicated that neurological changes are important findings of this kind of disease. However, the pulsatile tinnitus (PT) patients were excluded in previous studies because of the totally different mechanisms of the two subtype tinnitus. The aim of this study is to investigate whether altered baseline brain activity presents in patients with PT using resting-state functional magnetic resonance imaging (rs-fMRI) technique. The present study used unilateral PT patients (n=42) and age-, sex-, and education-matched normal control subjects (n=42) to investigate the changes in structural and amplitude of low-frequency (ALFF) of the brain. Also, we analyzed the relationships between these changes with clinical data of the PT patients. Compared with normal controls, PT patients did not show any structural changes. PT patients showed significant increased ALFF in the bilateral precuneus, and bilateral inferior frontal gyrus (IFG) and decreased ALFF in multiple occipital areas. Moreover, the increased THI score and PT duration was correlated with increased ALFF in precuneus and bilateral IFG. The abnormalities of spontaneous brain activity reflected by ALFF measurements in the absence of structural changes may provide insights into the neural reorganization in PT patients.

scholarly journals Attentionally modulated subjective images reconstructed from brain activity

2020 ◽  
Author(s):  
Tomoyasu Horikawa ◽  
Yukiyasu Kamitani
Keyword(s):  
Image Reconstruction ◽  
Visual Experience ◽  
Brain Activity ◽  
Visual Image ◽  
Neural Representation ◽  
Visual Images ◽  
Top Down ◽  
Neural Representations ◽  
Deep Image ◽  
The Brain

SummaryVisual image reconstruction from brain activity produces images whose features are consistent with the neural representations in the visual cortex given arbitrary visual instances [1–3], presumably reflecting the person’s visual experience. Previous reconstruction studies have been concerned either with how stimulus images are faithfully reconstructed or with whether mentally imagined contents can be reconstructed in the absence of external stimuli. However, many lines of vision research have demonstrated that even stimulus perception is shaped both by stimulus-induced processes and top-down processes. In particular, attention (or the lack of it) is known to profoundly affect visual experience [4–8] and brain activity [9–21]. Here, to investigate how top-down attention impacts the neural representation of visual images and the reconstructions, we use a state-of-the-art method (deep image reconstruction [3]) to reconstruct visual images from fMRI activity measured while subjects attend to one of two images superimposed with equally weighted contrasts. Deep image reconstruction exploits the hierarchical correspondence between the brain and a deep neural network (DNN) to translate (decode) brain activity into DNN features of multiple layers, and then create images that are consistent with the decoded DNN features [3, 22, 23]. Using the deep image reconstruction model trained on fMRI responses to single natural images, we decode brain activity during the attention trials. Behavioral evaluations show that the reconstructions resemble the attended rather than the unattended images. The reconstructions can be modeled by superimposed images with contrasts biased to the attended one, which are comparable to the appearance of the stimuli under attention measured in a separate session. Attentional modulations are found in a broad range of hierarchical visual representations and mirror the brain–DNN correspondence. Our results demonstrate that top-down attention counters stimulus-induced responses and modulate neural representations to render reconstructions in accordance with subjective appearance. The reconstructions appear to reflect the content of visual experience and volitional control, opening a new possibility of brain-based communication and creation.

Research on Processing the Brain Activity in BCI System

2017 ◽  
pp. 152-178
Author(s):  
Jaromir Svejda ◽  
Roman Zak ◽  
Roman Senkerik ◽  
Roman Jasek
Keyword(s):  
Brain Activity ◽  
Brain Computer Interface ◽  
Research Direction ◽  
Basic Knowledge ◽  
Future Research ◽  
Eeg Signal ◽  
Practical Applications ◽  
Output Device ◽  
The Brain ◽  
Bci System

The basic idea of BCI (Brain Computer Interface) is to connect brain waves with an output device through some interface. Human brain activity can be measured by many technologies. In our research, we use EEG (Electroencephalography) technology. This chapter will deal with processing of EEG signal and its utilization in practical applications using BCI technology mentioned above. This chapter is organized as follows. Firstly, the basic knowledge about EEG technology, brain and biometry is briefly summarized. Secondly, research of authors is presented. Finally, the future research direction is mentioned.

scholarly journals Individual Differences in Brain Responses: New Opportunities for Tailoring Health Communication Campaigns

2020 ◽  
Vol 14 ◽  
Author(s):  
Richard Huskey ◽  
Benjamin O. Turner ◽  
René Weber
Keyword(s):  
Individual Differences ◽  
Brain Activity ◽  
Brain Regions ◽  
Future Research ◽  
Message Processing ◽  
Response Patterns ◽  
Message Tailoring ◽  
Brain Responses ◽  
And Behavior ◽  
The Brain

Prevention neuroscience investigates the brain basis of attitude and behavior change. Over the years, an increasingly structurally and functionally resolved “persuasion network” has emerged. However, current studies have only identified a small handful of neural structures that are commonly recruited during persuasive message processing, and the extent to which these (and other) structures are sensitive to numerous individual difference factors remains largely unknown. In this project we apply a multi-dimensional similarity-based individual differences analysis to explore which individual factors—including characteristics of messages and target audiences—drive patterns of brain activity to be more or less similar across individuals encountering the same anti-drug public service announcements (PSAs). We demonstrate that several ensembles of brain regions show response patterns that are driven by a variety of unique factors. These results are discussed in terms of their implications for neural models of persuasion, prevention neuroscience and message tailoring, and methodological implications for future research.

scholarly journals Application of functional near-infrared spectroscopy in the healthcare industry: A review

2019 ◽  
Vol 12 (06) ◽  
pp. 1930012 ◽  
Author(s):  
Keum-Shik Hong ◽  
M. Atif Yaqub
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Depressive Disorders ◽  
Near Infrared ◽  
Brain Activity ◽  
Autism Spectrum ◽  
Future Research ◽  
Functional Near Infrared Spectroscopy ◽  
Brain Hemodynamics ◽  
The Brain

Functional near-infrared spectroscopy (fNIRS), a growing neuroimaging modality, has been utilized over the past few decades to understand the neuronal behavior in the brain. The technique has been used to assess the brain hemodynamics of impaired cohorts as well as able-bodied. Neuroimaging is a critical technique for patients with impaired cognitive or motor behaviors. The portable nature of the fNIRS system is suitable for frequent monitoring of the patients who exhibit impaired brain activity. This study comprehensively reviews brain-impaired patients: The studies involving patient populations and the diseases discussed in more than 10 works are included. Eleven diseases examined in this paper include autism spectrum disorder, attention-deficit hyperactivity disorder, epilepsy, depressive disorders, anxiety and panic disorder, schizophrenia, mild cognitive impairment, Alzheimer’s disease, Parkinson’s disease, stroke, and traumatic brain injury. For each disease, the tasks used for examination, fNIRS variables, and significant findings on the impairment are discussed. The channel configurations and the regions of interest are also outlined. Detecting the occurrence of symptoms at an earlier stage is vital for better rehabilitation and faster recovery. This paper illustrates the usability of fNIRS for early detection of impairment and the usefulness in monitoring the rehabilitation process. Finally, the limitations of the current fNIRS systems (i.e., nonexistence of a standard method and the lack of well-established features for classification) and future research directions are discussed. The authors hope that the findings in this paper would lead to advanced breakthrough discoveries in the fNIRS field in the future.

scholarly journals Neural representations of covert attention across saccades: comparing pattern similarity to shifting and holding attention during fixation

2020 ◽  
Author(s):  
Xiaoli Zhang ◽  
Julie D Golomb
Keyword(s):  
Time Course ◽  
Brain Activity ◽  
Activity Patterns ◽  
Covert Attention ◽  
Attention Shift ◽  
Attention Condition ◽  
Initial Location ◽  
Pattern Similarity ◽  
The Brain ◽  
Attention Shifts

AbstractWe can focus visuospatial attention by covertly attending to relevant locations, moving our eyes, or both simultaneously. How does shifting versus holding covert attention during fixation compare with maintaining covert attention across saccades? We acquired fMRI data during a combined saccade and covert attention task. On Eyes-fixed trials, participants either held attention at the same initial location (“hold attention”) or shifted attention to another location midway through the trial (“shift attention”). On Eyes-move trials, participants made a saccade midway through the trial, while maintaining attention in one of two reference frames: The “retinotopic attention” condition involved holding attention at a fixation-relative location but shifting to a different screen-centered location, whereas the “spatiotopic attention” condition involved holding attention on the same screen-centered location but shifting relative to fixation. We localized the brain network sensitive to attention shifts (shift > hold attention), and used multivoxel pattern time course analyses to investigate the patterns of brain activity for spatiotopic and retinotopic attention. In the attention shift network, we found transient information about both whether covert shifts were made and whether saccades were executed. Moreover, in the attention shift network, both retinotopic and spatiotopic conditions were represented more similarly to shifting than to holding covert attention. An exploratory searchlight analysis revealed additional regions where spatiotopic was relatively more similar to shifting and retinotopic more to holding. Thus, maintaining retinotopic and spatiotopic attention across saccades may involve different types of updating that vary in similarity to covert attention “hold” and “shift” signals across different regions.Significance StatementTo our knowledge, this study is the first attempt to directly compare human brain activity patterns of covert attention (to a peripheral spatial location) across saccades and during fixation. We applied fMRI multivoxel pattern time course analyses to capture the dynamic changes of activity patterns, with specific focus on the critical timepoints related to attention shifts and saccades. Our findings indicate that both retinotopic and spatiotopic attention across saccades produce patterns of activation similar to “shifting” attention in the brain, even though both tasks could be interpreted as “holding” attention by the participant. The results offer a novel perspective to understand how the brain processes and updates spatial information under different circumstances to fit the needs of various cognitive tasks.

scholarly journals A humán agyi aktivitás hálózatelemzési modellezése – Humán agyi hálózatok

2020 ◽  
Vol 1 (1) ◽  
pp. 21-28
Author(s):  
Brigitta Tóth ◽  
Ádám Boncz ◽  
Bálint File ◽  
István Winkler ◽  
Márk Molnár
Keyword(s):  
Short Term Memory ◽  
Early Stage ◽  
Brain Activity ◽  
Time Lag ◽  
Brain Network ◽  
Future Research ◽  
Speech Comprehension ◽  
High Plasticity ◽  
Healthy Elderly ◽  
The Brain

Összefoglalás. A hálózatkutatás idegtudományi alkalmazása áttörő eredményt hozott a humán kogníció és a neurális rendszerek közötti kapcsolat megértésében. Jelen tanulmány célja a neurális hálózatok néhány kutatási területét mutatja be a laborunkban végzett vizsgálatok eredményein keresztül. Bemutatjuk az agyi aktivitás mérésének és az agyi területek közötti kommunikációs hálózatok modellezésének technikáját. Majd kiemelünk két kutatási terület: 1) az agyi hálózatok életkori változásainak vizsgálatát, ami választ ad arra, hogy hogyan öregszik az emberi agy; 2) az emberi agyak közötti hálózat modelljének vizsgálatát, amely a hatékony emberi kommunikáció idegrendszeri mechanizmusait próbálja feltárni. Tárgyaljuk a humán kommunikációra képes mesterséges intelligencia fejlesztésének lehetőségét is. Végül kitérünk az agyi hálózatok kutatásának biztonságpolitikai vonatkozásaira. Summary. The human brain consists of 100 billion neurons connected by about 100 trillion synapses, which are hierarchically organized in different scales in anatomical space and time. Thus, it sounds reasonable to assume that the brain is the most complex network known to man. Network science applications in neuroscience are aimed to understand how human feeling, thought and behavior could emerge from this biological system of the brain. The present review focuses on the recent results and the future of network neuroscience. The following topics will be discussed: Modeling the network of communication among brain areas. Neural activity can be recorded with high temporal precision using electroencephalography (EEG). Communication strength between brain regions then might be estimated by calculating mathematical synchronization indices between source localized EEG time series. Finally, graph theoretical models can describe the relationship between system elements (i.e. efficiency of communication or centrality of an element). How does the brain age? While for a newborn the high plasticity of the brain provides the foundation of cognitive development, cognition declines with advanced age due to so far largely unknown neural mechanisms. In one of our studies, we demonstrated that there is a correlation between the anatomical development of the brain (at prenatal age) and its network topology. Specifically, the more developed the baby’s brain, the more functionally specialized/modular it was. In another study we found that in older adults, when compared to young adults, connectivity within modules of their brain network is decreased, with an associated decline in their short-term memory capacity. Moreover, Mild Cognitive Impairment patients (early stage of Alzheimer) were characterized with a significantly lower level of connectivity between their brain modules than the healthy elderly. Human communication via shared network of brain activity. In another study we recorded the brain activity of a speaker and multiple listeners. We investigated the brain network similarity across listeners and between the speaker and listeners. We found that brain activity was significantly correlated among listeners, providing evidence for the fact that the same content is processed via similar neural computations within different brains. The data also suggested that the more the brain activity synchronizes the more the mental state of the individuals overlap. We also found significantly synchronized brain activity between speaker and listeners. Specifically 1) listeners’ brain activity within the speech processing cortices was synchronized to speaker’s brain activity with a time lag, indicating that listeners’ speech comprehension processes replicated the speaker’s speech production processes; and 2) listeners’ frontal cortical activity was synchronized to speaker’s later brain activity, that is, listeners preceded the speaker, indicating that speech content is predicted by the listeners based on the context. Future challenges. Future research could target artificial intelligence development that is capable of human-like communication. To achieve this, the simultaneous recording of brain activity from listener and speaker is needed together with efficiency of the communication. These data could be then modelled via AI to detect biomarkers of communication efficiency. In general, neurotechnology has been rapidly developing within and outside of research and in clinical fields thus it is time for re-conceptualizing the corresponding human right law in order to avoid unwanted consequences of technological applications.

Intersubject Synchronisation Analysis of Brain Activity Associated with the Instant Effects of Acupuncture: An Fmri Study

2018 ◽  
Vol 36 (1) ◽  
pp. 14-20 ◽  
Author(s):  
Lingmin Jin ◽  
Jinbo Sun ◽  
Ziliang Xu ◽  
Xuejuan Yang ◽  
Peng Liu ◽  
...  
Keyword(s):  
Time Course ◽  
Brain Activity ◽  
Brain Regions ◽  
Pain Modulation ◽  
Acupuncture Stimulation ◽  
Brain Responses ◽  
Time Courses ◽  
The Brain ◽  
Stimulation Pattern ◽  
De Qi

Objective To use a promising analytical method, namely intersubject synchronisation (ISS), to evaluate the brain activity associated with the instant effects of acupuncture and compare the findings with traditional general linear model (GLM) methods. Methods 30 healthy volunteers were recruited for this study. Block-designed manual acupuncture stimuli were delivered at SP6, and de qi sensations were measured after acupuncture stimulation. All subjects underwent functional MRI (fMRI) scanning during the acupuncture stimuli. The fMRI data were separately analysed by ISS and traditional GLM methods. Results All subjects experienced de qi sensations. ISS analysis showed that the regions activated during acupuncture stimulation at SP6 were mainly divided into five clusters based on the time courses. The time courses of clusters 1 and 2 were in line with the acupuncture stimulation pattern, and the active regions were mainly involved in the sensorimotor system and salience network. Clusters 3, 4 and 5 displayed an almost contrary time course relative to the stimulation pattern. The brain regions activated included the default mode network, descending pain modulation pathway and visual cortices. GLM analysis indicated that the brain responses associated with the instant effects of acupuncture were largely implicated in sensory and motor processing and sensory integration. Conclusion The ISS analysis considered the sustained effect of acupuncture and uncovered additional information not shown by GLM analysis. We suggest that ISS may be a suitable approach to investigate the brain responses associated with the instant effects of acupuncture.

scholarly journals Neurophysiology of visually guided eye movements: critical review and alternative viewpoint

2018 ◽  
Vol 120 (6) ◽  
pp. 3234-3245 ◽  
Author(s):  
Laurent Goffart ◽  
Clara Bourrelly ◽  
Jean-Charles Quinton
Keyword(s):  
Eye Movements ◽  
Time Course ◽  
Brain Activity ◽  
Physical World ◽  
Population Coding ◽  
Critical Examination ◽  
Transmission Delays ◽  
Pursuit Eye Movements ◽  
Neurophysiological Studies ◽  
The Brain

In this article, we perform a critical examination of assumptions that led to the assimilation of measurements of the movement of a rigid body in the physical world to parameters encoded within brain activity. In many neurophysiological studies of goal-directed eye movements, equivalence has indeed been made between the kinematics of the eyes or of a targeted object and the associated neuronal processes. Such a way of proceeding brings up the reduction encountered in projective geometry when a multidimensional object is being projected onto a one-dimensional segment. The measurement of a movement indeed consists of generation of a series of numerical values from which magnitudes such as amplitude, duration, and their ratio (speed) are calculated. By contrast, movement generation consists of activation of multiple parallel channels in the brain. Yet, for many years, kinematic parameters were supposed to be encoded in brain activity, even though the neuronal image of most physical events is distributed both spatially and temporally. After explaining why the “neuronalization” of such parameters is questionable for elucidating the neural processes underlying the execution of saccadic and pursuit eye movements, we propose an alternative to the framework that has dominated the last five decades. A viewpoint is presented in which these processes follow principles that are defined by intrinsic properties of the brain (population coding, multiplicity of transmission delays, synchrony of firing, connectivity). We propose reconsideration of the time course of saccadic and pursuit eye movements as the restoration of equilibria between neural populations that exert opposing motor tendencies.

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