Does the semantic content of verbal categories influence categorical perception? An ERP study

Maier, Martin E.; Glage, Philipp; Hohlfeld, Annette; Rahman, Rasha Abdel

doi:10.1016/j.bandc.2014.07.008

Cited by 34 publications

(54 citation statements)

References 53 publications

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“…What is needed in order to ground either pictures or words in their referents is a mechanism that can recognize sensorimotor categories. Modeling the capacity for the learning, recognition, and representation of sensorimotor categories has become a rich and fertile field (Ashby & Maddox, ; De Vega et al., ; Folstein et al., ; Lupyan, ; Maier et al., ; Meteyard et al., ; Pezzulo et al., ). In a dual‐coding sensorimotor/symbolic model it is the sensorimotor module that needs to connect words to their referents.…”

Section: Discussionmentioning

confidence: 99%

“…The process of word grounding itself is the subject of a growing body of ongoing work on the sensorimotor learning of categories, by people as well as by computational models (Ashby & Maddox, ; Blondin Massé, Harnad, Picard, & St‐Louis, ; De Vega, Glenberg, & Graesser, ; Harnad, ; Kang, ; Maier, Glage, Hohlfeld, & Rahman, ; Meteyard, Cuadrado, Bahrami, & Vigliocco, ; Pezzulo et al., ; Van der Velde, ). Here, we just note that almost all the words in any dictionary (nouns, verbs, adjectives and adverbs) are “content” words, meaning that they are the names of categories (objects, individuals, kinds, states, actions, events, properties, relations) of various degrees of abstractness.…”

Section: Category Learningmentioning

confidence: 99%

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The Latent Structure of Dictionaries

Vincent-Lamarre

Massé

Lopes³

et al. 2016

Topics in Cognitive Science

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How many words—and which ones—are sufficient to define all other words? When dictionaries are analyzed as directed graphs with links from defining words to defined words, they reveal a latent structure. Recursively removing all words that are reachable by definition but that do not define any further words reduces the dictionary to a Kernel of about 10% of its size. This is still not the smallest number of words that can define all the rest. About 75% of the Kernel turns out to be its Core, a “Strongly Connected Subset” of words with a definitional path to and from any pair of its words and no word's definition depending on a word outside the set. But the Core cannot define all the rest of the dictionary. The 25% of the Kernel surrounding the Core consists of small strongly connected subsets of words: the Satellites. The size of the smallest set of words that can define all the rest—the graph's “minimum feedback vertex set” or MinSet—is about 1% of the dictionary, about 15% of the Kernel, and part‐Core/part‐Satellite. But every dictionary has a huge number of MinSets. The Core words are learned earlier, more frequent, and less concrete than the Satellites, which are in turn learned earlier, more frequent, but more concrete than the rest of the Dictionary. In principle, only one MinSet's words would need to be grounded through the sensorimotor capacity to recognize and categorize their referents. In a dual‐code sensorimotor/symbolic model of the mental lexicon, the symbolic code could do all the rest through recombinatory definition.

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Section: Discussionmentioning

confidence: 99%

Section: Category Learningmentioning

confidence: 99%

The Latent Structure of Dictionaries

Vincent-Lamarre

Massé

Lopes³

et al. 2016

Topics in Cognitive Science

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“…Effects should be clearly attributable to the top-down factor in question (i.e., linguistic categorization in the present study). Therefore, experimental designs must make sure to eliminate or control for low-level perceptual differences between conditions (Firestone & Scholl, 2015, Maier et al, 2014. Furthermore, effects should not be attributable to specific task demands or response biases (e.g., judging the steepness of a hill while wearing a heavy backpack in a research lab; Bhalla & Proffitt, 1999).…”

Section: Avoiding Experimental Confoundsmentioning

confidence: 99%

No matter how: Top-down effects of verbal and semantic category knowledge on early visual perception

Maier

Rahman

2019

Cogn Affect Behav Neurosci

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Language is assumed to augment human cognition. But can language also affect basic mechanisms of perception, suggesting cognitive penetrability of perception? This idea is highly controversial: linguistic categorization may induce top-down effects on ongoing perceptual processing. Alternatively, such effects may not concern perception proper, but pre-perceptual shifts of attention or downstream processes, such as perceptual judgment. This study provides a critical test of these views by investigating categorical perception (CP) of novel objects in a balanced learning design, controlling for perceptual experience and low-level visual differences. To better understand which linguistic representations induce CP, we manipulated the type of information categories were based on: bare verbal labels, in-depth semantic knowledge, or the combined information from labels associated with semantic knowledge. We used event-related brain potentials (ERPs) derived from the EEG in a visual search task to localize CP effects at perceptual or pre/post-perceptual stages. The results replicated behavioral CP with facilitated visual search when target and distractors belonged to different linguistic categories. ERPs revealed CP effects in the P1 and N1 components, associated with early visual processing. Attentional selection, reflected in the N2, also was influenced by linguistic categories. The N2 and the N400, a measure of high-level semantic processing, were sensitive to the depth of semantic knowledge associated with objects. CP, however, did not differ between category types, suggesting that any linguistic categorization can lead to CP. The findings support cognitive penetrability of perception, with linguistic categories informing perceptual predictions down to the processing of low-level visual features.

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“…Yet, the time course of imagery and the timing of the involvement of early visual cortex are still open questions. In line with predictive processing accounts one hypothesis holds that perception engages top-down predictions even during low-level processing 25,26,31,47 , and that imagery might share this mechanism.…”

Section: Discussionmentioning

confidence: 82%

“…This is achieved by manipulating the semantic knowledge associated with a given object. Knowledge stored in semantic memory, for example, about the functions of objects 24,27,31,46 , and categories defined by the language we speak 25,26,28,[47][48][49] , have all been shown to influence early visual processes.…”

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confidence: 99%

Conceptual knowledge affects early stages of visual mental imagery and object perception

Maier

Frömer

et al. 2020

Preprint

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When we imagine an object and when we actually see that object, similar brain regions become active. Yet, the time course of neurocognitive mechanisms that support imagery is still largely unknown. The current view holds that imagery does not share early perceptual mechanisms, but starts with high-level visual representations. However, evidence of early shared mechanisms is difficult to obtain because imagery and perception tasks typically differ in visual input. We therefore tracked electrophysiological brain responses while fully controlling visual input, (1) comparing imagery and perception of objects with varying amounts of associated knowledge, and (2) comparing the time courses of successful and incomplete imagery. Imagery and perception were similarly influenced by knowledge already at early stages, revealing shared mechanisms during low-level visual processing. It follows that imagery is not merely perception in reverse; instead, both are active and constructive processes, based on shared mechanisms starting at surprisingly early stages. Keywords: mental imagery, early visual processing, event-related potentials, semantic knowledge, P1 component MENTAL IMAGERY: TIME COURSE, COGNITIVE MECHANISMS 3 Time course and shared neurocognitive mechanisms of mental imagery and visual perception A growing body of research suggests that seeing something with the mind's eyemental imagery-may not be all that different from seeing something with one's physical eyes. Indeed, imagery and perception recruit overlapping neural circuits, including primary visual areas 1-8 , and the vividness of imagination correlates with the similarity of brain activities accompanying imagery and perception 9 . Predictive processing accounts posit that perception arises from hierarchical Bayesian predictions-essentially imaginations-that are constrained by bottom-up sensory input 10-14 .This theoretical framework is neurally plausible 15-20 and supported by evidence that even early stages of perception are subject to top-down influences 15,[21][22][23][24][25][26][27][28][29][30][31] . This suggests that initial aspects of imagery could be fast enough to generate early top-down effects.This suggestion contrasts with alternative accounts assuming that perception first runs through a strictly hierarchical succession of increasingly complex visual representations, with early stages mainly driven by bottom-up sensory processes. At later stages, recurrent feedback from higher-level brain areas is assumed to enable stabilization of visual representations and, eventually, conscious access 32,33 . Based on this account of perception, recent work has mapped out how visual imagery could follow a reverse hierarchy of activation compared to perception 6,7,[34][35][36] . Under these assumptions, imagery would not rely on early perceptual mechanisms like feature processing but start relatively late, with entire visual representations that bring several levels of the visual hierarchy into concert 6,7,35 . In support of this idea, Dijkstra, et al. 35 found ...

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Does the semantic content of verbal categories influence categorical perception? An ERP study

Cited by 34 publications

References 53 publications

The Latent Structure of Dictionaries

The Latent Structure of Dictionaries

No matter how: Top-down effects of verbal and semantic category knowledge on early visual perception

Conceptual knowledge affects early stages of visual mental imagery and object perception

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