Biology subjects

Hulten, A.

Publications and source records attributed to Hulten, A..

7 recordsLinked to original sources

bioRxiv2022

Cortical time-course of evidence accumulation during semantic processing

Our understanding of the surrounding world and communication with other people are tied to mental representations of concepts. In order for the brain to recognize an object, it must determine which concept to access based on information available from sensory inputs. In this study, we combine magnetoencephalography and machine learning to investigate how concepts are represented and accessed in the brain over time. Using brain responses from a silent picture naming task, we track the dynamics of semantic processing, and show that the brain gradually accumulates semantic information before eventually reaching a plateau. The timing of this plateau point varies across individuals, indicating differences in the temporal domain of semantic processing, a new dimension of individual variability in the faculty of language.

neuroscience↗

bioRxiv2020

Processing of a spoken narrative in the human brain is shaped by family cultural background

Using neuroimaging, we studied influence of family cultural background on processing of an audiobook in human brain. The audiobook depicted life of two young Finnish men, one with the Finnish and the other with the Russian family background. Shared family cultural background enhanced similarity of narrative processing in the brain at prelexical, word, sentence, and narrative levels. Similarity was also enhanced in brain areas supporting imagery. The cultural background was further reflected as semantic differences in word lists by which the subjects described what had been on their minds when they heard the audiobook during neuroimaging. Strength of social identity shaped word, sentence, and narrative level processing in the brain. These effects might enhance mutual understanding between persons who share family cultural background and social identity and, conversely, deteriorate between-group mutual understanding in modern multicultural societies wherein native speakers of a language may assume highly similar understanding.

neuroscience↗

bioRxiv2019

Stimulus-modality independent activation of the brain network for language

The meaning of a sentence can be understood, whether presented in written or spoken form. Therefore it is highly probable that brain processes supporting language comprehension are at least partly independent of sensory modality. To identify where and when in the brain language processing is independent of sensory modality, we directly compared neuromagnetic brain signals of 200 human subjects (102 males) either reading or listening to sentences. We used multiset canonical correlation analysis to align individual subject data in a way that boosts those aspects of the signal that are common to all, allowing us to capture word-by-word signal variations, consistent across subjects and at a fine temporal scale. Quantifying this consistency in activation across both reading and listening tasks revealed a mostly left hemispheric cortical network. Areas showing consistent activity patterns include not only areas previously implicated in higher-level language processing, such as left prefrontal, superior & middle temporal areas and anterior temporal lobe, but also parts of the control-network as well as subcentral and more posterior temporal-parietal areas. Activity in this supramodal sentence processing network starts in temporal areas and rapidly spreads to the other regions involved. The findings do not only indicate the involvement of a large network of brain areas in supramodal language processing, but also indicate that the linguistic information contained in the unfolding sentences modulates brain activity in a word-specific manner across subjects.

neuroscience↗

bioRxiv2019

Supramodal sentence processing in the human brain: fMRI evidence for the influence of syntactic complexity in more than 200 participants

This study investigated two questions. One is to which degree sentence processing beyond single words is independent of the input modality (speech vs. reading). The second question is which parts of the network recruited by both modalities is sensitive to syntactic complexity. These questions were investigated by having more than 200 participants read or listen to well-formed sentences or series of unconnected words. A largely left-hemisphere fronto-temporoparietal network was found to be supramodal in nature, i.e. independent of input modality. In addition, the left inferior frontal gyrus (LIFG) and the left posterior middle temporal gyrus (LpMTG) were most clearly associated with left-branching complexity. The left anterior middle temporal gyrus (LaMTG) showed the greatest sensitivity to sentences that differed in right-branching complexity. Moreover, activity in LIFG and LpMTG increased from sentence onset to end, in parallel with an increase of the left-branching complexity. While LIFG, bilateral anterior and posterior MTG and left inferior parietal lobe (LIPL) all contribute to the supramodal unification processes, the results suggest that these regions differ in their respective contributions to syntactic complexity related processing. The consequences of these findings for neurobiological models of language processing are discussed.

neuroscience↗

bioRxiv2018

Reconstructing meaning from bits of information

We can easily identify a dog merely by the sound of barking or an orange by its citrus scent. In this work, we study the neural underpinnings of how the brain combines bits of information into meaningful object representations. Modern theories of semantics posit that the meaning of words can be decomposed into a unique combination of individual semantic features (e.g., \"barks\", \"has citrus scent\"). Here, participants received clues of individual objects in form of three isolated semantic features, given as verbal descriptions. We used machine-learning-based neural decoding to learn a mapping between individual semantic features and BOLD activation patterns. We discovered that the recorded brain patterns were best decoded using a combination of not only the three semantic features that were presented as clues, but a far richer set of semantic features typically linked to the target object. We conclude that our experimental protocol allowed us to observe how fragmented information is combined into a complete semantic representation of an object and suggest neuroanatomical underpinnings for this process.

neuroscience↗

bioRxiv2018

Cracking the problem of neural representations of abstract words: grounding word meanings in language itself

In order to describe how humans represent meaning in the brain, one must be able to account for not just concrete words but, critically, also abstract words which lack a physical referent. Hebbian formalism and optimization are basic principles of brain function, and they provide an appealing approach for modeling word meanings based on word co-occurrences. Here, we built a model of the semantic space based on word statistics in a large text corpus, which was able to decode items from brain signals. In the model, word abstractness emerged from the statistical regularities of the language environment. This salient property of the model co-varied, at 280-420 ms after word presentation, with activity in the left-hemisphere frontal, anterior temporal and superior parietal cortex that have been linked with processing of abstract words. In light of these results, we propose that the neural encoding of word meanings is importantly grounded in language through statistical regularities.

neuroscience↗

bioRxiv2017

Frequency-specific directed interactions in the human brain network for language

The brains remarkable capacity for language requires bidirectional interactions between functionally specialized brain regions. We used magnetoencephalography to investigate interregional interactions in the brain network for language, while 102 participants were reading sentences. Using Granger causality analysis, we identified inferior frontal cortex and anterior temporal regions to receive widespread input, and middle temporal regions to send widespread output. This fits well with the notion that these regions play a central role in language processing. Characterization of the functional topology of this network, using data-driven matrix factorization, which allowed for partitioning into a set of subnetworks, revealed directed connections at distinct frequencies of interaction. Connections originating from temporal regions peaked at alpha frequency, whereas connections originating from frontal and parietal regions peaked at beta frequency. These findings indicate that processing different types of linguistic information may depend on the contributions of distinct brain rhythms.\n\nOne Sentence SummaryCommunication between language relevant areas in the brain is supported by rhythmic synchronization, where different rhythms reflect the direction of information flow.

neuroscience↗