scholarly journals Semantic Grounding of Novel Spoken Words in the Primary Visual Cortex

2021 ◽  
Vol 15 ◽  
Author(s):  
Max Garagnani ◽  
Evgeniya Kirilina ◽  
Friedemann Pulvermüller
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Semantic Information ◽  
Word Meaning ◽  
Familiar Object ◽  
The Novel ◽  
Brain Responses ◽  
Spoken Words ◽  
First Time ◽  
The Brain

Embodied theories of grounded semantics postulate that, when word meaning is first acquired, a link is established between symbol (word form) and corresponding semantic information present in modality-specific—including primary—sensorimotor cortices of the brain. Direct experimental evidence documenting the emergence of such a link (i.e., showing that presentation of a previously unknown, meaningless word sound induces, after learning, category-specific reactivation of relevant primary sensory or motor brain areas), however, is still missing. Here, we present new neuroimaging results that provide such evidence. We taught participants aspects of the referential meaning of previously unknown, senseless novel spoken words (such as “Shruba” or “Flipe”) by associating them with either a familiar action or a familiar object. After training, we used functional magnetic resonance imaging to analyze the participants’ brain responses to the new speech items. We found that hearing the newly learnt object-related word sounds selectively triggered activity in the primary visual cortex, as well as secondary and higher visual areas.These results for the first time directly document the formation of a link between the novel, previously meaningless spoken items and corresponding semantic information in primary sensory areas in a category-specific manner, providing experimental support for perceptual accounts of word-meaning acquisition in the brain.

scholarly journals Semantic representations during language comprehension are affected by context

2021 ◽  
Author(s):  
Fatma Deniz ◽  
Christine Tseng ◽  
Leila Wehbe ◽  
Jack L Gallant
Keyword(s):  
Natural Language ◽  
Semantic Information ◽  
Brain Activity ◽  
Word Meaning ◽  
Brain Responses ◽  
Neuroimaging Data ◽  
The Brain ◽  
Model Approach ◽  
Prefrontal Cortices

The meaning of words in natural language depends crucially on context. However, most neuroimaging studies of word meaning use isolated words and isolated sentences with little context. Because the brain may process natural language differently from how it processes simplified stimuli, there is a pressing need to determine whether prior results on word meaning generalize to natural language. We investigated this issue by directly comparing the brain representation of semantic information across four conditions that vary in context. fMRI was used to record human brain activity while four subjects (two female) read words presented in four different conditions: narratives (Narratives), isolated sentences (Sentences), blocks of semantically similar words (Semantic Blocks), and isolated words (Single Words). Using a voxelwise encoding model approach, we find two clear and consistent effects of increasing context. First, stimuli with more context (Narratives, Sentences) evoke brain responses with substantially higher SNR across bilateral visual, temporal, parietal, and prefrontal cortices compared to stimuli with little context (Semantic Blocks, Single Words). Second, increasing context increases the representation of semantic information across bilateral temporal, parietal, and prefrontal cortices at the group level. However, in individual subjects, only natural language stimuli (Narratives) consistently evoke widespread representation of semantic information across the cortical surface. These results show that context has large effects on both the quality of neuroimaging data and on the representation of meaning in the brain, and they imply that the results of neuroimaging studies that use stimuli with little context may not generalize well to the natural regime.

scholarly journals Homeostatic plasticity mechanisms in mouse V1

2017 ◽  
Vol 372 (1715) ◽  
pp. 20160504 ◽  
Author(s):  
Megumi Kaneko ◽  
Michael P. Stryker
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Neuronal Activity ◽  
Dynamic Range ◽  
Ocular Dominance ◽  
Homeostatic Plasticity ◽  
Ocular Dominance Plasticity ◽  
The Brain

Mechanisms thought of as homeostatic must exist to maintain neuronal activity in the brain within the dynamic range in which neurons can signal. Several distinct mechanisms have been demonstrated experimentally. Three mechanisms that act to restore levels of activity in the primary visual cortex of mice after occlusion and restoration of vision in one eye, which give rise to the phenomenon of ocular dominance plasticity, are discussed. The existence of different mechanisms raises the issue of how these mechanisms operate together to converge on the same set points of activity. This article is part of the themed issue ‘Integrating Hebbian and homeostatic plasticity’.

scholarly journals Decoding brain responses to pixelized images in the primary visual cortex: implications for visual cortical prostheses

2015 ◽  
Vol 10 (10) ◽  
pp. 1622 ◽  
Author(s):  
Wen-sheng Hou ◽  
Bing-bing Guo ◽  
Xiao-lin Zheng ◽  
Zhen-gang Lu ◽  
Xing Wang ◽  
...  
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Brain Responses ◽  
Visual Cortical

scholarly journals Subdomains within orientation columns of primary visual cortex

2019 ◽  
Vol 5 (6) ◽  
pp. eaaw0807 ◽  
Author(s):  
Ming Li ◽  
Xue Mei Song ◽  
Tao Xu ◽  
Dewen Hu ◽  
Anna Wang Roe ◽  
...  
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Accurate Method ◽  
Electrode Position ◽  
Tree Shrews ◽  
Form Processing ◽  
Orientation Columns ◽  
Relationship Of ◽  
First Time ◽  
The Relationship

In the mammalian visual system, early stages of visual form processing begin with orientation-selective neurons in primary visual cortex (V1). In many species (including humans, monkeys, tree shrews, cats, and ferrets), these neurons are organized in a beautifully arrayed pinwheel-like orientation columns, which shift in orientation preference across V1. However, to date, the relationship of orientation architecture to the encoding of multiple elemental aspects of visual contours is still unknown. Here, using a novel, highly accurate method of targeting electrode position, we report for the first time the presence of three subdomains within single orientation domains. We suggest that these zones subserve computation of distinct aspects of visual contours and propose a novel tripartite pinwheel-centered view of an orientation hypercolumn.

scholarly journals Blindsight and Unconscious Vision: What They Teach Us about the Human Visual System

2016 ◽  
Vol 23 (5) ◽  
pp. 529-541 ◽  
Author(s):  
Sara Ajina ◽  
Holly Bridge
Keyword(s):  
Visual Cortex ◽  
Visual System ◽  
Primary Visual Cortex ◽  
Neural Activity ◽  
Human Visual System ◽  
Visual Information ◽  
Visual Loss ◽  
Physiological Conditions ◽  
The World ◽  
The Brain

Damage to the primary visual cortex removes the major input from the eyes to the brain, causing significant visual loss as patients are unable to perceive the side of the world contralateral to the damage. Some patients, however, retain the ability to detect visual information within this blind region; this is known as blindsight. By studying the visual pathways that underlie this residual vision in patients, we can uncover additional aspects of the human visual system that likely contribute to normal visual function but cannot be revealed under physiological conditions. In this review, we discuss the residual abilities and neural activity that have been described in blindsight and the implications of these findings for understanding the intact system.

Do Rotation Coordinates Provide the Substrate for a Mental Protractor?

Perception ◽  
10.1068/p5338 ◽  
2005 ◽  
Vol 34 (11) ◽  
pp. 1339-1352 ◽  
Author(s):  
Ernest Greene ◽  
William Frawley
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Angular Position ◽  
Spatial Position ◽  
Angular Measure ◽  
Relative Angle ◽  
Brain Maps ◽  
The Subject ◽  
The Brain

In previous studies, we have found that the accuracy in judging collinearity of lines or dots varies considerably from one subject to another as a function of the relative angle of the stimulus elements. A model of errors generally shows large excursions across several subranges of angular position. These do not appear to be motor errors, at least not ones that are well separated from perceptual mechanisms. The errors are most likely generated at primary visual cortex, or beyond. We examined and modeled accuracy in judging collinearity of dot pairs, varying the angular position of the dots through 360°, the distance between the dots (stimulus span), and the distance at which the subject was required to respond (response span). Subjects manifested idiosyncratic profiles of error across angular positions, as reported previously. But across the tested range of spans, from 4 to 8 deg, the errors tended to be the same, irrespective of stimulus or response span. This suggests that the judgments are based on a radial (angular) measure of spatial position. We discuss these results in the context of proposals that the brain maps spatial position using rotation coordinates. These new data are consistent with the hypothesis that subjects use the z-axis coordinates as a mental protractor for judging angular position and collinearity.

Equalization and decorrelation in primary visual cortex

2014 ◽  
Vol 112 (3) ◽  
pp. 501-503 ◽  
Author(s):  
Koen V. Haak ◽  
Elizabeth Fast ◽  
Yihwa Baek ◽  
Juraj Mesik
Keyword(s):  
Visual Cortex ◽  
Recent Work ◽  
Primary Visual Cortex ◽  
Neuronal Population ◽  
Neural Adaptation ◽  
First Time

There are many theories on the purpose of neural adaptation, but evidence remains elusive. Here, we discuss the recent work by Benucci et al. ( Nat Neurosci 16: 724–729, 2013), who measured for the first time the immediate effects of adaptation on the overall activity of a neuronal population. These measurements confirm two long-standing hypotheses about the purpose of adaptation, namely that adaptation counteracts biases in the statistics of the environment, and that it maintains decorrelation in neuronal stimulus selectivity.

scholarly journals Perceived and mentally rotated contents are differentially represented in cortical depth of V1

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Polina Iamshchinina ◽  
Daniel Kaiser ◽  
Renat Yakupov ◽  
Daniel Haenelt ◽  
Alessandro Sciarra ◽  
...  
Keyword(s):  
Visual Cortex ◽  
High Resolution ◽  
Mental Rotation ◽  
Primary Visual Cortex ◽  
External Input ◽  
General Strategy ◽  
Cortical Layers ◽  
Early Visual Cortex ◽  
Feedback Connections ◽  
The Brain

AbstractPrimary visual cortex (V1) in humans is known to represent both veridically perceived external input and internally-generated contents underlying imagery and mental rotation. However, it is unknown how the brain keeps these contents separate thus avoiding a mixture of the perceived and the imagined which could lead to potentially detrimental consequences. Inspired by neuroanatomical studies showing that feedforward and feedback connections in V1 terminate in different cortical layers, we hypothesized that this anatomical compartmentalization underlies functional segregation of external and internally-generated visual contents, respectively. We used high-resolution layer-specific fMRI to test this hypothesis in a mental rotation task. We found that rotated contents were predominant at outer cortical depth bins (i.e. superficial and deep). At the same time perceived contents were represented stronger at the middle cortical bin. These results identify how through cortical depth compartmentalization V1 functionally segregates rather than confuses external from internally-generated visual contents. These results indicate that feedforward and feedback manifest in distinct subdivisions of the early visual cortex, thereby reflecting a general strategy for implementing multiple cognitive functions within a single brain region.

scholarly journals Prior expectations evoke stimulus-specific activity in the deep layers of the primary visual cortex

PLoS Biology ◽  
2020 ◽  
Vol 18 (12) ◽  
pp. e3001023
Author(s):  
Fraser Aitken ◽  
Georgios Menelaou ◽  
Oliver Warrington ◽  
Renée S. Koolschijn ◽  
Nadège Corbin ◽  
...  
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Specific Activity ◽  
Predictive Processing ◽  
Cortical Layers ◽  
Computational Architecture ◽  
Deep Layers ◽  
Flow Through ◽  
The Brain ◽  
The Way

The way we perceive the world is strongly influenced by our expectations. In line with this, much recent research has revealed that prior expectations strongly modulate sensory processing. However, the neural circuitry through which the brain integrates external sensory inputs with internal expectation signals remains unknown. In order to understand the computational architecture of the cortex, we need to investigate the way these signals flow through the cortical layers. This is crucial because the different cortical layers have distinct intra- and interregional connectivity patterns, and therefore determining which layers are involved in a cortical computation can inform us on the sources and targets of these signals. Here, we used ultra-high field (7T) functional magnetic resonance imaging (fMRI) to reveal that prior expectations evoke stimulus-specific activity selectively in the deep layers of the primary visual cortex (V1). These findings are in line with predictive processing theories proposing that neurons in the deep cortical layers represent perceptual hypotheses and thereby shed light on the computational architecture of cortex.

scholarly journals Specific excitatory connectivity for feature integration in mouse primary visual cortex

2016 ◽  
Author(s):  
Dylan R Muir ◽  
Patricia Molina-Luna ◽  
Morgane M Roth ◽  
Fritjof Helmchen ◽  
Björn M Kampa
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Visual Processing ◽  
Visual Stimuli ◽  
Visual Representations ◽  
Feature Binding ◽  
Local Network ◽  
Visual Responses ◽  
Visual Properties ◽  
The Brain

AbstractLocal excitatory connections in mouse primary visual cortex (V1) are stronger and more prevalent between neurons that share similar functional response features. However, the details of how functional rules for local connectivity shape neuronal responses in V1 remain unknown. We hypothesised that complex responses to visual stimuli may arise as a consequence of rules for selective excitatory connectivity within the local network in the superficial layers of mouse V1. In mouse V1 many neurons respond to overlapping grating stimuli (plaid stimuli) with highly selective and facilitatory responses, which are not simply predicted by responses to single gratings presented alone. This complexity is surprising, since excitatory neurons in V1 are considered to be mainly tuned to single preferred orientations. Here we examined the consequences for visual processing of two alternative connectivity schemes: in the first case, local connections are aligned with visual properties inherited from feedforward input (a ‘like-to-like’ scheme specifically connecting neurons that share similar preferred orientations); in the second case, local connections group neurons into excitatory subnetworks that combine and amplify multiple feedforward visual properties (a ‘feature binding’ scheme). By comparing predictions from large scale computational models with in vivo recordings of visual representations in mouse V1, we found that responses to plaid stimuli were best explained by a assuming ‘feature binding’ connectivity. Unlike under the ‘like-to-like’ scheme, selective amplification within feature-binding excitatory subnetworks replicated experimentally observed facilitatory responses to plaid stimuli; explained selective plaid responses not predicted by grating selectivity; and was consistent with broad anatomical selectivity observed in mouse V1. Our results show that visual feature binding can occur through local recurrent mechanisms without requiring feedforward convergence, and that such a mechanism is consistent with visual responses and cortical anatomy in mouse V1.Author summaryThe brain is a highly complex structure, with abundant connectivity between nearby neurons in the neocortex, the outermost and evolutionarily most recent part of the brain. Although the network architecture of the neocortex can appear disordered, connections between neurons seem to follow certain rules. These rules most likely determine how information flows through the neural circuits of the brain, but the relationship between particular connectivity rules and the function of the cortical network is not known. We built models of visual cortex in the mouse, assuming distinct rules for connectivity, and examined how the various rules changed the way the models responded to visual stimuli. We also recorded responses to visual stimuli of populations of neurons in anaesthetised mice, and compared these responses with our model predictions. We found that connections in neocortex probably follow a connectivity rule that groups together neurons that differ in simple visual properties, to build more complex representations of visual stimuli. This finding is surprising because primary visual cortex is assumed to support mainly simple visual representations. We show that including specific rules for non-random connectivity in cortical models, and precisely measuring those rules in cortical tissue, is essential to understanding how information is processed by the brain.

Sign in / Sign up

Export Citation Format

Share Document