Biology subjects

Dehaene, S.

Publications and source records attributed to Dehaene, S..

51 records · Page 3Linked to original sources

bioRxiv2021

A Spatiotemporal Map of Reading Aloud

Reading words aloud is a fundamental aspect of literacy. The rapid rate at which multiple distributed neural substrates are engaged in this process can only be probed via techniques with high spatiotemporal resolution. We probed this with direct intracranial recordings covering most of the left hemisphere in 46 humans as they read aloud regular, exception and pseudo-words. We used this to create a spatiotemporal map of word processing and to derive how broadband gamma activity varies with multiple word attributes critical to reading speed: lexicality, word frequency and orthographic neighborhood. We found that lexicality is encoded earliest in mid-fusiform (mFus) cortex and precentral sulcus, and is represented reliably enough to allow single-trial lexicality decoding. Word frequency is first represented in mFus and later in the inferior frontal gyrus (IFG) and inferior parietal sulcus (IPS), while orthographic neighborhood sensitivity resides solely in IPS. We thus isolate the neural correlates of the distributed reading network involving mFus, IFG, IPS, precentral sulcus and motor cortex and provide direct evidence for dual-route models of reading, with parallel processes via the lexical route from mFus to IFG, and the sub-lexical route from IPS and precentral sulcus to anterior IFG.

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bioRxiv2021

Simulating the emergence of the Visual Word Form Area: Recycling a convolutional neural network for reading

The visual word form area (VWFA) is a region of human inferotemporal cortex that emerges at a fixed location in occipitotemporal cortex during reading acquisition, and systematically responds to written words in literate individuals. According to the neuronal recycling hypothesis, this region arises through the repurposing, for letter recognition, of a subpart of the ventral visual pathway initially involved in face and object recognition. Furthermore, according to the biased connectivity hypothesis, its universal localization is due to pre-existing connections from this subregion to areas involved in spoken language processing. Here, we evaluate those hypotheses in an explicit computational model. We trained a deep convolutional neural network of the ventral visual pathway, first to categorize pictures, and then to recognize written words invariantly for case, font and size. We show that the model can account for many properties of the VWFA, particularly when a subset of units possesses a biased connectivity to word output units. The network develops a sparse, invariant representation of written words, based on a restricted set of reading-selective units. Their activation mimics several properties of the VWFA, and their lesioning causes a reading-specific deficit. Our simulation fleshes out the neuronal recycling hypothesis, and make several testable predictions concerning the neural code for written words.

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bioRxiv2020

Spatiotemporal Dynamics of Orthographic and Lexical Processing in the Ventral Visual Pathway

Reading is a rapid, distributed process that engages multiple components of the ventral visual stream. However, the neural constituents and their interactions that allow us to identify written words are not well understood. Using direct intracranial recordings in a large cohort of humans, we comprehensively isolated the spatiotemporal dynamics of visual word recognition across the entire left ventral occipitotemporal cortex. The mid-fusiform cortex is the first region that is sensitive to word identity and to both sub-lexical and lexical frequencies. Its activation, response latency and amplitude, are highly dependent on the statistics of natural language. Information about lexicality and word frequency propagates posteriorly from this region to traditional visual word form regions and to earlier visual cortex. This unique sensitivity of mid-fusiform cortex to the lexical characteristics of written words points to its central role as an orthographic lexicon, which accesses the long-term memory representations of visual word forms.

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bioRxiv2020

Rational arbitration between statistics and rules in human sequence learning

Detecting and learning temporal regularities is essential to accurately predict the future. A long-standing debate in cognitive science concerns the existence of a dissociation, in humans, between two systems, one for handling statistical regularities governing the probabilities of individual items and their transitions, and another for handling deterministic rules. Here, to address this issue, we used finger tracking to continuously monitor the online build-up of evidence, confidence, false alarms and changes-of-mind during sequence processing. All these aspects of behaviour conformed tightly to a hierarchical Bayesian inference model with distinct hypothesis spaces for statistics and rules, yet linked by a single probabilistic currency. Alternative models based either on a single statistical mechanism or on two non-commensurable systems were rejected. Our results indicate that a hierarchical Bayesian inference mechanism, capable of operating over distinct hypothesis spaces for statistics and rules, underlies the human capability for sequence processing.

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bioRxiv2020

An abstract language of thought for spatial sequences in humans

How does the human brain store sequences of spatial locations? The standard view is that each consecutive item occupies a distinct slot in working memory. Here, we formulate and test the alternative hypothesis that the human brain compresses the whole sequence using an abstract, language-like code that captures the numerical and geometrical regularities of the sequence at multiple nested levels. We exposed participants to spatial sequences of fixed length but variable regularity, and asked them to remember the sequence in order to detect deviants, while their brain activity was recorded using magneto-encephalography. Using multivariate decoders, each successive location could be decoded from brain signals, and upcoming locations were anticipated prior to their actual onset. Crucially, sequences with lower complexity, defined as the minimal description length provided by the formal language, and whose memory representation was therefore predicted to be more compressed, led to lower error rates and to increased anticipations. Furthermore, neural codes specific to the numerical and geometrical primitives of the postulated language could be detected, both in isolation and within the sequences. These results suggest that the human brain detects sequence regularities at multiple nested levels and uses them to compress long sequences in working memory.

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bioRxiv2019

Shared anomalies in cortical reading networks in Chinese and French dyslexic children

Are the brain mechanisms of reading acquisition similar across writing systems? And do similar brain anomalies underlie reading disabilities in alphabetic and ideographic reading systems? In a cross-cultural paradigm, we measured the fMRI responses to words, faces and houses of 96 Chinese and French 10-year-old children, half of whom struggle with reading. We observed a reading circuit which was strikingly similar across languages and consisting of the left fusiform gyrus, superior temporal gyrus/sulcus, precentral and middle frontal gyri. Activations in some of these areas were modulated either by language or by reading ability, but without interaction between those factors. In various regions previously associated with dyslexia, reading difficulty affected activation similarly in Chinese and French readers, including the middle frontal gyrus, a region previously described as specifically altered in Chinese. Our analyses reveal a large degree of cross-cultural invariance in the neural correlates of reading acquisition and reading disabilities.

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bioRxiv2019

A potential cortical precursor of visual word form recognition in untrained monkeys

Skilled human readers can readily recognize written letters and letter strings. This domain of visual recognition, known as orthographic processing, is foundational to human reading, but it is unclear how it is supported by neural populations in the human brain. Behavioral research has shown that non-human primates (baboons) can learn to distinguish written English words from pseudo-words (lexical decision), successfully generalize that behavior to novel strings, and exhibit behavioral error patterns that are consistent with humans. Thus, non-human primate models, while not capturing the entirety of human reading abilities, may provide a unique opportunity to investigate the neuronal mechanisms underlying orthographic processing. Here, we investigated the neuronal representation of letters and letter strings in the ventral visual stream of naive macaque monkeys, and asked to what extent these representations could support visual word recognition. We recorded the activity of hundreds of neurons at the top two levels of the ventral visual form processing pathway (V4 and IT) while monkeys passively viewed images of letters, English words, and non-word letter strings. Linear decoders were used to probe whether those neural responses could support a battery of orthographic processing tasks such as invariant letter identification and lexical decision. We found that IT-based decoders achieved baboon-level performance on these tasks, with a pattern of errors highly correlated to the previously reported primate behavior. This capacity to support orthographic processing tasks was also present in the high-layer units of state-of-the-art artificial neural network models of the ventral stream, but not in the low-layer representations of those models. Taken together, these results show that the IT cortex of untrained monkeys contains a reservoir of precursor features from which downstream brain regions could, with some supervised instruction, learn to support the visual recognition of written words. This suggests that the acquisition of reading in humans did not require a full rebuild of visual processing, but rather the recycling of a brain network evolved for other visual functions.

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bioRxiv2019

Attentional amplification of neural codes for number independent of other quantities along the dorsal visual stream

Humans and other animals base important decisions on estimates of number, and intraparietal cortex is thought to provide a crucial substrate of this ability. However, it remains debated whether an independent neuronal processing mechanism underlies this 'number sense', or whether number is instead judged indirectly on the basis of other quantitative features. We performed high-resolution 7 Tesla fMRI while adult human volunteers attended either to the numerosity or to an orthogonal dimension (average item size) of visual dot arrays. Numerosity explained a significant amount of variance in activation patterns, above and beyond non-numerical dimensions. Its representation was progressively enhanced along the dorsal visual pathway and was selectively amplified by attention when task relevant. These results reveal a dedicated extraction mechanism for numerosity that operates independently of other quantitative dimensions of the stimuli, and suggest that later stages along the dorsal stream are most important for the explicit manipulation of numerical quantity.

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bioRxiv2018

Probing the limits of activity-silent non-conscious working memory

Two types of working memory (WM) have recently been proposed: conscious active WM, depending on sustained neural activity, and activity-silent WM, requiring neither conscious awareness nor accompanying neural activity. However, whether both states support identical forms of information processing is unknown. Theory predicts that activity-silent states are confined to passive storage and cannot operate on stored information. To determine whether an explicit reactivation is required prior to the manipulation of information in WM, we evaluated whether participants could mentally rotate brief visual stimuli of variable subjective visibility. Behaviorally, even for unseen targets, subjects reported the rotated location above chance after several seconds. As predicted, however, such blindsight performance was accompanied by neural signatures of conscious reactivation at the time of mental rotation, including a sustained desynchronization in alpha/beta frequency and a decodable representation of participants guess and response. Our findings challenge the concept of genuine non-conscious \"working\" memory, argue that activity-silent states merely support passive short-term memory, and provide a cautionary note for purely behavioral studies of non-conscious information processing.

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bioRxiv2018

Asymmetrical interference between number and item size perception provide evidence for a domain specific impairment in dyscalculia

Dyscalculia, a specific learning disability that impacts arithmetical skills, has previously been associated to a deficit in the precision of the system that estimates the approximate number of objects in visual scenes (the so called number sense system). However, because in tasks involving numerosity comparisons dyscalculics judgements appears disproportionally affected by continuous quantitative dimensions (such as the size of the items), an alternative view linked dyscalculia to a domain-general difficulty in inhibiting task-irrelevant responses.\n\nTo arbitrate between these views, we evaluated the degree of reciprocal interference between numerical and non-numerical quantitative dimensions in adult dyscalculics and matched controls. We used a novel stimulus set orthogonally varying in mean item size and numerosity, putting particular attention into matching both features perceptual discriminability. Participants compared those stimuli based on each of the two dimensions. While control subjects showed no significant size interference when judging numerosity, dyscalculics numerosity judgments were strongly biased by the unattended size dimension. Importantly however, both groups showed the same degree of interference from number when judging mean size. Moreover, only the ability to discard the irrelevant size information when comparing numerosity (but not the reverse) significantly predicted calculation ability across subjects.\n\nOverall, our results show that numerosity discrimination is less prone to interference than discrimination of another quantitative feature (mean item size) when the perceptual discriminability of these features is matched, as here in control subjects. By quantifying, for the first time, dyscalculic subjects degree of interference on another orthogonal dimension of the same stimuli, we are able to exclude a domain-general inhibition deficit as explanation for their poor / biased numerical judgement. We suggest that enhanced reliance on non-numerical cues during numerosity discrimination can represent a strategy to cope with a less precise number sense.

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bioRxiv2017

Discriminability of numerosity-evoked fMRI activity patterns in human intra-parietal cortex reflects behavioral numerical acuity

Areas of the primate intraparietal cortex have been identified as an important substrate of numerical cognition. In human fMRI studies, activity patterns in these and other areas have allowed researchers to read out the numerosity a subject is viewing, but the relation of such decodable information with behavioral numerical proficiency remains unknown.\n\nHere, we estimated the precision of behavioral numerosity discrimination (internal Weber fraction) in twelve adult subjects based on psychophysical testing in a delayed numerosity comparison task outside the scanner. FMRI data were then recorded during a similar task, to obtain the accuracy with which the same sample numerosities could be read out from evoked brain activity patterns, as a measure of the precision of the neuronal representation. Sample numerosities were decodable in both early visual and intra-parietal cortex with approximately equal accuracy on average. In parietal cortex, smaller numerosities were better discriminated than larger numerosities of the same ratio, paralleling smaller behavioral Weber fractions for smaller numerosities. Furthermore, in parietal but not early visual cortex, fMRI decoding performance was correlated with behavioral number discrimination acuity across subjects (subjects with a more precise behavioral Weber fraction measured prior to scanning showed greater discriminability of fMRI activity patterns in intraparietal cortex, and more specifically, the right LIP region).\n\nThese results suggest a crucial role for intra-parietal cortex in supporting a numerical representation which is explicitly read out for numerical decisions and behavior.

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bioRxiv2017

Impaired conscious access and abnormal attentional amplification in schizophrenia

Previous research suggests that the conscious perception of a masked stimulus is impaired in schizophrenia, while unconscious bottom-up processing of the same stimulus, as assessed by subliminal priming, can be preserved. Here, we test this postulated dissociation between intact bottom-up and impaired top-down processing and evaluate its brain mechanisms using high-density recordings of event-related potentials. Sixteen patients with schizophrenia and sixteen controls were exposed to peripheral digits with various degrees of visibility, under conditions of either focused attention or distraction by another task. In the distraction condition, the brain activity evoked by masked digits was drastically reduced in both groups, but early bottom-up visual activation could still be detected and did not differ between patients and controls. By contrast, under focused top-down attention, a major impairment was observed: in patients, contrary to controls, the late non-linear ignition associated with the P3 component was reduced. Interestingly, the patients showed an essentially normal attentional amplification of the PI and N2 components. These results suggest that some but not all top-down attentional amplification processes are impaired in schizophrenia, while bottom-up processing seems to be preserved.

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bioRxiv2017

A random-matrix theory of the number sense

Number sense, a spontaneous ability to process approximate numbers, has been documented in human adults, infants and newborns, and many other animals. Species as distant as monkeys and crows exhibit number-selective neuronal activity. How number sense can emerge in the absence of learning or fine tuning is currently unknown. We introduce a random matrix theory of self-organised neural states where numbers are coded by vectors of activation across multiple units, and where the vector codes for successive integers are obtained through multiplication by a fixed but random matrix. This cortical implementation of the \"von Mises\" algorithm explains many otherwise disconnected observations ranging from neural tuning curves in monkeys to looking times in neonates and cortical numerotopy in adults. The theory clarifies the origin of Weber-Fechners law and yields a novel and empirically validated prediction of multi-peak number neurons. Random matrices constitute a novel mechanism for the emergence of brain states coding for quantity.

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bioRxiv2017

Bayesian Selection Of Grammar Productions For The Language Of Thought

Probabilistic proposals of Language of Thoughts (LoTs) can explain learning across different domains as statistical inference over a compositionally structured hypothesis space. While frameworks may differ on how a LoT may be implemented computationally, they all share the property that they are built from a set of atomic symbols and rules by which these symbols can be combined. In this work we show how the set of productions of a LoT grammar can be effectively selected from a broad repertoire of possible productions by an inferential process starting from experimental data. We then test this method in the language of geometry, a specific LoT model (Amalric et al., 2017). Finally, despite the fact of the geometrical LoT not being a universal (i.e. Turing-complete) language, we show an empirical relation between a sequences probability and its complexity consistent with the theoretical relationship for universal languages described by Levins Coding Theorem.

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bioRxiv2016

A theory of working memory without consciousness or sustained activity

Working memory and conscious perception are thought to share similar brain mechanisms, yet recent reports of non-conscious working memory challenge this view. Combining visual masking with magnetoencephalography, we demonstrate the reality of non-conscious working memory and dissect its neural mechanisms. In a spatial delayed-response task, participants reported the location of a subjectively unseen target above chance-level after a long delay. Conscious perception and conscious working memory were characterized by similar signatures: a sustained desynchronization in the alpha/beta band over frontal cortex, and a decodable representation of target location in posterior sensors. During non-conscious working memory, such activity vanished. Our findings contradict models that identify working memory with sustained neural firing, but are compatible with recent proposals of activity-silent working memory. We present a theoretical framework and simulations showing how slowly decaying synaptic changes allow cell assemblies to go dormant during the delay, yet be retrieved above chance-level after several seconds.

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