scholarly journals Effortless integration of probabilistic visual input

2021 ◽  
Author(s):  
Andrey Chetverikov ◽  
Árni Kristjánsson
Keyword(s):  
Probabilistic Models ◽  
Spatial Scales ◽  
Building Blocks ◽  
Visual Input ◽  
Summary Statistics ◽  
Visual Inputs ◽  
The World ◽  
Mean And Variance ◽  
Scene Processing ◽  
The Brain

Prominent theories of perception suggest that the brain builds probabilistic models of the world, assessing the statistics of the visual input to inform this construction. However, the evidence for this idea is often based on simple impoverished stimuli, and the results have often been discarded as an illusion reflecting simple "summary statistics" of visual inputs. Here we show that the visual system represents probabilistic distributions of complex heterogeneous stimuli. Importantly, we show how these statistical representations are integrated with representations of other features and bound to locations, and can therefore serve as building blocks for object and scene processing. We uncover the organization of these representations at different spatial scales by showing how expectations for incoming features are biased by neighboring locations. We also show that there is not only a bias, but also a skew in the representations, arguing against accounts positing that probabilistic representations are discarded in favor of simplified summary statistics (e.g., mean and variance). In sum, our results reveal detailed probabilistic encoding of stimulus distributions, representations that are bound with other features and to particular locations.

scholarly journals Determination of Dynamic Brain Connectivity via Spectral Analysis

2021 ◽  
Vol 15 ◽  
Author(s):  
Peter A. Robinson ◽  
James A. Henderson ◽  
Natasha C. Gabay ◽  
Kevin M. Aquino ◽  
Tara Babaie-Janvier ◽  
...  
Keyword(s):  
Spectral Analysis ◽  
Brain Structure ◽  
Brain Connectivity ◽  
Spatial Scales ◽  
Effective Connectivity ◽  
Physical Nature ◽  
Building Blocks ◽  
Brain Dynamics ◽  
Compact Representation ◽  
The Brain

Spectral analysis based on neural field theory is used to analyze dynamic connectivity via methods based on the physical eigenmodes that are the building blocks of brain dynamics. These approaches integrate over space instead of averaging over time and thereby greatly reduce or remove the temporal averaging effects, windowing artifacts, and noise at fine spatial scales that have bedeviled the analysis of dynamical functional connectivity (FC). The dependences of FC on dynamics at various timescales, and on windowing, are clarified and the results are demonstrated on simple test cases, demonstrating how modes provide directly interpretable insights that can be related to brain structure and function. It is shown that FC is dynamic even when the brain structure and effective connectivity are fixed, and that the observed patterns of FC are dominated by relatively few eigenmodes. Common artifacts introduced by statistical analyses that do not incorporate the physical nature of the brain are discussed and it is shown that these are avoided by spectral analysis using eigenmodes. Unlike most published artificially discretized “resting state networks” and other statistically-derived patterns, eigenmodes overlap, with every mode extending across the whole brain and every region participating in every mode—just like the vibrations that give rise to notes of a musical instrument. Despite this, modes are independent and do not interact in the linear limit. It is argued that for many purposes the intrinsic limitations of covariance-based FC instead favor the alternative of tracking eigenmode coefficients vs. time, which provide a compact representation that is directly related to biophysical brain dynamics.

scholarly journals Closed loop motor-sensory dynamics in human vision

2019 ◽  
Author(s):  
Liron Gruber ◽  
Ehud Ahissar
Keyword(s):  
Eye Movements ◽  
Visual Processing ◽  
Closed Loop ◽  
Open Loop ◽  
Visual Input ◽  
Human Vision ◽  
Visual Inputs ◽  
Eye Motion ◽  
Slow Eye Movements ◽  
The Brain

AbstractVision is obtained with a continuous motion of the eyes. The kinematic analysis of eye motion, during any visual or ocular task, typically reveals two (kinematic) components: saccades, which quickly replace the visual content in the retinal fovea, and drifts, which slowly scan the image after each saccade. While the saccadic exchange of regions of interest (ROIs) is commonly considered to be included in motor-sensory closed-loops, it is commonly assumed that drifts function in an open-loop manner, that is, independent of the concurrent visual input. Accordingly, visual perception is assumed to be based on a sequence of open-loop processes, each initiated by a saccade-triggered retinal snapshot. Here we directly challenged this assumption by testing the dependency of drift kinematics on concurrent visual inputs using real-time gaze-contingent-display. Our results demonstrate a dependency of the trajectory on the concurrent visual input, convergence of speed to condition-specific values and maintenance of selected drift-related motor-sensory controlled variables, all strongly indicative of drifts being included in a closed-loop brain-world process, and thus suggesting that vision is inherently a closed-loop process.Author summaryOur eyes do not function like cameras; it has long been known that we are actively scanning our visual environment in order to see. Moreover, it is commonly accepted that our fast eye movements, saccades, are controlled by the brain and are affected by the sensory input. However, our slow eye movements, the ocular drifts, are often ignored when visual acquisition is analyzed. Accordingly, visual processing is typically assumed to be based on computations performed on saccade-triggered snapshots of the retinal state. Our work strongly challenges this model and provides significant evidence for an alternative model, a cybernetic one. We show that the dynamics of the ocular drifts do not allow, and cannot be explained by, open loop visual acquisition. Instead, our results suggest that visual acquisition is part of a closed-loop process, which dynamically and continuously links the brain to its environment.

Pelvic schwannoma

GYNECOLOGY ◽  
2020 ◽  
Vol 22 (5) ◽  
pp. 84-86
Author(s):  
Sergei P. Sinchikhin ◽  
Sarkis G. Magakyan ◽  
Oganes G. Magakyan
Keyword(s):  
Auditory Nerve ◽  
World Literature ◽  
Morphological Study ◽  
Clinical Observation ◽  
Nerve Trunk ◽  
Practical Case ◽  
Surgical Volume ◽  
The World ◽  
Brain And Spinal Cord ◽  
The Brain

Relevance.A neoplasm originated from the myelonic sheath of the nerve trunk is called neurinoma or neurilemmoma, neurinoma, schwannoglioma, schwannoma. This tumor can cause compression and dysfunction of adjacent tissues and organs. The most common are the auditory nerve neurinomas (1 case per 100 000 population per year), the brain and spinal cord neurinomas are rare. In the world literature, there is no information on the occurrences of this tumor in the pelvic region. Description.Presented below is a clinical observation of a 30-year-old patient who was scheduled for myomectomy. During laparoscopy, an unusual tumor of the small pelvis was found and radically removed. A morphological study allowed to identify the remote neoplasm as a neuroma. Conclusion.The presented practical case shows that any tumor can hide under a clinical mask of another disease. The qualification of the doctor performing laparoscopic myomectomy should be sufficient to carry out, if necessary, another surgical volume.

Consciousness, law of nature, and nomological determinism

2018 ◽  
Author(s):  
Xiaoyang Yu
Keyword(s):  
Free Will ◽  
Important Thing ◽  
Law Of Nature ◽  
The World ◽  
The Law ◽  
The Brain

Nomological determinism does not mean everything is predictable. It just means everything follows the law of nature. And the most important thing Is that the brain and consciousness follow the law of nature. In other words, there is no free will. Without life, brain and consciousness, the world follows law of nature, that is clear. The life and brain are also part of nature, and they follow the law of nature. This is due to scientific findings. There are not enough scientific findings for consciousness yet. But I think that the consciousness is a nature phenomenon, and it also follows the law of nature.

Exploring the abnormal signal transduction mediated internet addiction and gaming disorders

2020 ◽  
Vol 15 ◽  
Author(s):  
Bhumika Chauhan ◽  
Sisir Nandi
Keyword(s):  
Signal Transduction ◽  
Internet Addiction ◽  
Internet Gaming Disorder ◽  
Online Data ◽  
Abnormal Signal ◽  
Internet Gaming ◽  
The World ◽  
Loss Of Appetite ◽  
Sleeping Disorder ◽  
The Brain

: The world is connected by the internet. It is very useful because we use Google to find out any new topic, to search new places, to quest updated research, and to get knowledge for learnng. The person around the world can communicate with each other through the Google video conference talk. Internet is frequently used in smartphones, laptops, desktop, and tablet. Excessive affinity towards internet-based online data collection, downloading pictures, videos, cyber relationships, and social media may produce addiction disorders followed by different symptoms such as behaviors change, mind disturbance, depression, anxiety, loss of appetite hyperactivity, sleeping disorder, headache, visual fatigueness, trafficking of memory, attention-deficit, loss of efficiency in work and social detachment which may be caused by an imbalance of neurotransmitters. This is very difficult to control because of abnormal signal transduction in the brain. The present study is an attempt to discuss internet addiction disorder (IAD), internet gaming disorder (IGD), and give awareness to society to get rid of this addiction.

scholarly journals On Russell’s 1927 Book The Analysis of Matter

Philosophies ◽  
2021 ◽  
Vol 6 (2) ◽  
pp. 40
Author(s):  
Said Mikki
Keyword(s):  
General Relativity ◽  
Quantum Mechanics ◽  
Building Blocks ◽  
Bertrand Russell ◽  
Important Work ◽  
Philosophy Of Nature ◽  
Foundations Of Physics ◽  
The World ◽  
Ordinal Space ◽  
Historical Fact

The goal of this article is to bring into wider attention the often neglected important work by Bertrand Russell on the philosophy of nature and the foundations of physics, published in the year 1927. It is suggested that the idea of what could be named Russell space, introduced in Part III of that book, may be viewed as more fundamental than many other types of spaces since the highly abstract nature of the topological ordinal space proposed by Russell there would incorporate into its very fabric the emergent nature of spacetime by deploying event assemblages, but not spacetime or particles, as the fundamental building blocks of the world. We also point out the curious historical fact that the book The Analysis of Matter can be chronologically considered the earliest book-length generic attempt to reflect on the relation between quantum mechanics, just emerging by that time, and general relativity.

scholarly journals Extending the extended consciousness debate: perception, imagination, and the common kind assumption

2021 ◽  
Author(s):  
James Deery
Keyword(s):  
Perceptual Experience ◽  
Phenomenal Consciousness ◽  
Psychological Theory ◽  
Predictive Processing ◽  
Mental Event ◽  
The World ◽  
Predictive Approach ◽  
The Common ◽  
The Relationship ◽  
The Brain

AbstractFor some, the states and processes involved in the realisation of phenomenal consciousness are not confined to within the organismic boundaries of the experiencing subject. Instead, the sub-personal basis of perceptual experience can, and does, extend beyond the brain and body to implicate environmental elements through one’s interaction with the world. These claims are met by proponents of predictive processing, who propose that perception and imagination should be understood as a product of the same internal mechanisms. On this view, as visually imagining is not considered to be world-involving, it is assumed that world-involvement must not be essential for perception, and thus internalism about the sub-personal basis is true. However, the argument for internalism from the unity of perception and imagination relies for its strength on a questionable conception of the relationship between the two experiential states. I argue that proponents of the predictive approach are guilty of harbouring an implicit commitment to the common kind assumption which does not follow trivially from their framework. That is, the assumption that perception and imagination are of the same fundamental kind of mental event. I will argue that there are plausible alternative ways of conceiving of this relationship without drawing internalist metaphysical conclusions from their psychological theory. Thus, the internalist owes the debate clarification of this relationship and further argumentation to secure their position.

The brain as a mediator of the mind and the world

Cortex ◽  
2009 ◽  
Vol 45 (7) ◽  
pp. 904-905
Author(s):  
Zhicheng Lin
Keyword(s):  
The World ◽  
The Mind ◽  
The Brain

scholarly journals Vision and the representation of the surroundings in spatial memory

2011 ◽  
Vol 366 (1564) ◽  
pp. 596-610 ◽  
Author(s):  
Benjamin W. Tatler ◽  
Michael F. Land
Keyword(s):  
Spatial Memory ◽  
Visual Environment ◽  
Coding Scheme ◽  
Perceptual Stability ◽  
The World ◽  
Scene Viewing ◽  
Memory Representations ◽  
The Brain ◽  
Allocentric Representations ◽  
And Task

One of the paradoxes of vision is that the world as it appears to us and the image on the retina at any moment are not much like each other. The visual world seems to be extensive and continuous across time. However, the manner in which we sample the visual environment is neither extensive nor continuous. How does the brain reconcile these differences? Here, we consider existing evidence from both static and dynamic viewing paradigms together with the logical requirements of any representational scheme that would be able to support active behaviour. While static scene viewing paradigms favour extensive, but perhaps abstracted, memory representations, dynamic settings suggest sparser and task-selective representation. We suggest that in dynamic settings where movement within extended environments is required to complete a task, the combination of visual input, egocentric and allocentric representations work together to allow efficient behaviour. The egocentric model serves as a coding scheme in which actions can be planned, but also offers a potential means of providing the perceptual stability that we experience.

scholarly journals Inferring brain-computational mechanisms with models of activity measurements

2016 ◽  
Vol 371 (1705) ◽  
pp. 20160278 ◽  
Author(s):  
Nikolaus Kriegeskorte ◽  
Jörn Diedrichsen
Keyword(s):  
Computational Models ◽  
Brain Activity ◽  
Visual Object ◽  
Visual Object Recognition ◽  
Summary Statistics ◽  
Activity Data ◽  
Individual Measurement ◽  
Activity Measurements ◽  
The Brain ◽  
The Way

High-resolution functional imaging is providing increasingly rich measurements of brain activity in animals and humans. A major challenge is to leverage such data to gain insight into the brain's computational mechanisms. The first step is to define candidate brain-computational models (BCMs) that can perform the behavioural task in question. We would then like to infer which of the candidate BCMs best accounts for measured brain-activity data. Here we describe a method that complements each BCM by a measurement model (MM), which simulates the way the brain-activity measurements reflect neuronal activity (e.g. local averaging in functional magnetic resonance imaging (fMRI) voxels or sparse sampling in array recordings). The resulting generative model (BCM-MM) produces simulated measurements. To avoid having to fit the MM to predict each individual measurement channel of the brain-activity data, we compare the measured and predicted data at the level of summary statistics. We describe a novel particular implementation of this approach, called probabilistic representational similarity analysis (pRSA) with MMs, which uses representational dissimilarity matrices (RDMs) as the summary statistics. We validate this method by simulations of fMRI measurements (locally averaging voxels) based on a deep convolutional neural network for visual object recognition. Results indicate that the way the measurements sample the activity patterns strongly affects the apparent representational dissimilarities. However, modelling of the measurement process can account for these effects, and different BCMs remain distinguishable even under substantial noise. The pRSA method enables us to perform Bayesian inference on the set of BCMs and to recognize the data-generating model in each case. This article is part of the themed issue ‘Interpreting BOLD: a dialogue between cognitive and cellular neuroscience’.

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