scholarly journals The Human Brain encodes a Chronicle of Visual Events at each Instant of Time

2019 ◽  
Author(s):  
J-R. King ◽  
V. Wyart

AbstractThe human brain continuously processes streams of visual input. Yet, a single image typically triggers neural responses that extend beyond one second. To understand how such a slow computation copes with real-time processing, we recorded subjects’ electrical brain activity, while they watched ~5,000 rapidly-changing images. First, we show that each image can be decoded from brain activity for ~1 sec, and demonstrate that the brain simultaneously represents multiple images at each time instant. Second, dynamical system modeling reveals that these sustained representations can be explained by a specific chain of neural circuits, which consist of (i) a hidden maintenance mechanism, and (ii) an observable update mechanism. Third, this neural architecture is localized along the expected visual pathways. Finally, we show that the propagation of low-level representations across the visual hierarchy is a principle shared with deep convolutional networks. Together, these findings provide a general neural mechanism to simultaneously represent successive visual events.SignificanceOur retina are continuously bombarded with a rich flux of visual input. How our brain continuously processes such visual stream is a major challenge to neuroscience. Here, we developed techniques to decode and track, from human brain activity, multiple images flashed in rapid succession. Our results show that the brain simultaneously represents multiple successive images at each time instant. A hierarchy of neural assemblies which continuously propagate multiple visual contents explains our findings. Overall, this study sheds new light on the biological basis of our visual experience.

2021 ◽  
pp. 102-106
Author(s):  
Claudia Menzel ◽  
Gyula Kovács ◽  
Gregor U. Hayn-Leichsenring ◽  
Christoph Redies

Most artists who create abstract paintings place the pictorial elements not at random, but arrange them intentionally in a specific artistic composition. This arrangement results in a pattern of image properties that differs from image versions in which the same pictorial elements are randomly shuffled. In the article under discussion, the original abstract paintings of the author’s image set were rated as more ordered and harmonious but less interesting than their shuffled counterparts. The authors tested whether the human brain distinguishes between these original and shuffled images by recording electrical brain activity in a particular paradigm that evokes a so-called visual mismatch negativity. The results revealed that the brain detects the differences between the two types of images fast and automatically. These findings are in line with models that postulate a significant role of early (low-level) perceptual processing of formal image properties in aesthetic evaluations.


Author(s):  
V. A. Maksimenko ◽  
A. A. Harchenko ◽  
A. Lüttjohann

Introduction: Now the great interest in studying the brain activity based on detection of oscillatory patterns on the recorded data of electrical neuronal activity (electroencephalograms) is associated with the possibility of developing brain-computer interfaces. Braincomputer interfaces are based on the real-time detection of characteristic patterns on electroencephalograms and their transformation  into commands for controlling external devices. One of the important areas of the brain-computer interfaces application is the control of the pathological activity of the brain. This is in demand for epilepsy patients, who do not respond to drug treatment.Purpose: A technique for detecting the characteristic patterns of neural activity preceding the occurrence of epileptic seizures.Results:Using multi-channel electroencephalograms, we consider the dynamics of thalamo-cortical brain network, preceded the occurrence of an epileptic seizure. We have developed technique which allows to predict the occurrence of an epileptic seizure. The technique has been implemented in a brain-computer interface, which has been tested in-vivo on the animal model of absence epilepsy.Practical relevance:The results of our study demonstrate the possibility of epileptic seizures prediction based on multichannel electroencephalograms. The obtained results can be used in the development of neurointerfaces for the prediction and prevention of seizures of various types of epilepsy in humans. 


Author(s):  
M.N. Ustinin ◽  
S.D. Rykunov ◽  
A.I. Boyko ◽  
O.A. Maslova ◽  
K.D. Walton ◽  
...  

New method for the magnetic encephalography data analysis was proposed. The method transforms multichannel time series into the spatial structure of the human brain activity. In this paper we further develop this method to determine the dominant direction of the electrical sources of brain activity at each node of the calculation grid. We have considered the experimental data, obtained with three 275-channel magnetic encephalographs in New York University, McGill University and Montreal University. The human alpha rhythm phenomenon was selected as a model object. Magnetic encephalograms of the brain spontaneous activity were registered for 5-7 minutes in magnetically shielded room. Detailed multichannel spectra were obtained by the Fourier transform of the whole time series. For all spectral components, the inverse problem was solved in elementary current dipole model and the functional structure of the brain activity was calculated in the frequency band 8-12 Hz. In order to estimate the local activity direction, at the each node of calculation grid the vector of the inverse problem solution was selected, having the maximal spectral power. So, the 3D-map of the brain activity vector field was produced – the directional functional tomogram. Such maps were generated for 15 subjects and some common patterns were revealed in the directions of the alpha rhythm elementary sources. The proposed method can be used to study the local properties of the brain activity in any spectral band and in any brain compartment.


Author(s):  
Stephanie Hawes ◽  
Carrie R. H. Innes ◽  
Nicholas Parsons ◽  
Sean P.A. Drummond ◽  
Karen Caeyensberghs ◽  
...  

AbstractSleep can intrude into the awake human brain when sleep deprived or fatigued, even while performing cognitive tasks. However, how the brain activity associated with sleep onset can co-exist with the activity associated with cognition in the awake humans remains unexplored. Here, we used simultaneous fMRI and EEG to generate fMRI activity maps associated with EEG theta (4-7 Hz) activity associated with sleep onset. We implemented a method to track these fMRI activity maps in individuals performing a cognitive task after well-rested and sleep-deprived nights. We found frequent intrusions of the fMRI maps associated with sleep-onset in the task-related fMRI data. These sleep events elicited a pattern of transient fMRI activity, which was spatially distinct from the task-related activity in the frontal and parietal areas of the brain. They were concomitant with reduced arousal as indicated by decreased pupil size and increased response time. Graph theoretical modelling showed that the activity associated with sleep onset emerges from the basal forebrain and spreads anterior-posteriorly via the brain’s structural connectome. We replicated the key findings in an independent dataset, which suggests that the approach can be reliably used in understanding the neuro-behavioural consequences of sleep and circadian disturbances in humans.


2003 ◽  
Vol 26 (6) ◽  
pp. 672-673
Author(s):  
Valéria Csépe

Brain activity data prove the existence of qualitatively different structures in the brain. However, the question is whether the human brain acts as linguists assume in their models. The modular architecture of grammar that has been claimed by many linguists raises some empirical questions. One of the main questions is whether the threefold abstract partition of language (into syntactic, phonological, and semantic domains) has distinct neural correlates.


1995 ◽  
Vol 18 (2) ◽  
pp. 365-366
Author(s):  
Rumyana Kristeva-Feige ◽  
Bernd Feige

AbstractPosner & Raichle's (1994) book is a fascinating and readable account of the studies the authors have conducted on the localization of cognitive functions in the brain mainly using PET and EEC evoked potential methods. Our criticism concerns the underrepresentation of some imaging techniques (magnetoencephalography) and some forms of brain activity (spontaneous activity). Furthermore, the book leaves the reader with the impression that the brain only responds to external events.


1976 ◽  
Vol 4 (4) ◽  
pp. 211-222 ◽  
Author(s):  
U J Jovanović

Changes in the electro-encephalogram, and in the electro-oculogram electromyogram, ECG, blood supply, blood pressure, electrical skin activity and neurological/psychiatric findings, were investigated in 100 patients given single administrations of 200 mg of pentoxifylline (BL 191). It is concluded from the changes in the EEG wave patterns that pentoxifylline produces a beneficial effect on the cerebral processes contributing to bio-electrical brain activity. Pentoxifylline can be classed as a substance with microcirculatory/metabolic effects on the brain, which lead to stimulation of psychomotor behaviour.


2020 ◽  
Author(s):  
Sreejan Kumar ◽  
Cameron T. Ellis ◽  
Thomas O’Connell ◽  
Marvin M Chun ◽  
Nicholas B. Turk-Browne

AbstractThe extent to which brain functions are localized or distributed is a foundational question in neuroscience. In the human brain, common fMRI methods such as cluster correction, atlas parcellation, and anatomical searchlight are biased by design toward finding localized representations. Here we introduce the functional searchlight approach as an alternative to anatomical searchlight analysis, the most commonly used exploratory multivariate fMRI technique. Functional searchlight removes any anatomical bias by grouping voxels based only on functional similarity and ignoring anatomical proximity. We report evidence that visual and auditory features from deep neural networks and semantic features from a natural language processing model are more widely distributed across the brain than previously acknowledged. This approach provides a new way to evaluate and constrain computational models with brain activity and pushes our understanding of human brain function further along the spectrum from strict modularity toward distributed representation.


2015 ◽  
Vol 112 (49) ◽  
pp. E6798-E6807 ◽  
Author(s):  
Maxwell A. Bertolero ◽  
B. T. Thomas Yeo ◽  
Mark D’Esposito

Network-based analyses of brain imaging data consistently reveal distinct modules and connector nodes with diverse global connectivity across the modules. How discrete the functions of modules are, how dependent the computational load of each module is to the other modules’ processing, and what the precise role of connector nodes is for between-module communication remains underspecified. Here, we use a network model of the brain derived from resting-state functional MRI (rs-fMRI) data and investigate the modular functional architecture of the human brain by analyzing activity at different types of nodes in the network across 9,208 experiments of 77 cognitive tasks in the BrainMap database. Using an author–topic model of cognitive functions, we find a strong spatial correspondence between the cognitive functions and the network’s modules, suggesting that each module performs a discrete cognitive function. Crucially, activity at local nodes within the modules does not increase in tasks that require more cognitive functions, demonstrating the autonomy of modules’ functions. However, connector nodes do exhibit increased activity when more cognitive functions are engaged in a task. Moreover, connector nodes are located where brain activity is associated with many different cognitive functions. Connector nodes potentially play a role in between-module communication that maintains the modular function of the brain. Together, these findings provide a network account of the brain’s modular yet integrated implementation of cognitive functions.


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