Presentations

Abstract

Integrating sentence meaning over time requires memory ranging from milliseconds (words) to seconds (sentences) and minutes (discourse). How do transient events like action potentials in the human language system support memory at these different temporal scales? Here we investigate the nature of processing memory in a neurobiologically motivated model of sentence comprehension. The model was a recurrent, sparsely connected network of spiking neurons. Synaptic weights were created randomly and there was no adaptation or learning. As input the network received word sequences generated from construction grammar templates and their syntactic alternations (e.g., active/passive transitives, transfer datives, caused motion). The language environment had various features such as tense, aspect, noun/verb number agreement, and pronouns which created positional variation in the input. Similar to natural speech, word durations varied between 50ms and 0.5s of real, physical time depending on their length. The model's task was to incrementally interpret these word sequences in terms of semantic roles. There were 8 target roles (e.g., Agent, Patient, Recipient) and the language generated roughly 1,2m distinct utterances from which a sequence of 10,000 words was randomly selected and filtered through the network. A set of readout neurons was then calibrated by means of logistic regression to decode the internal network dynamics onto the target semantic roles. In order to accomplish the role assignment task, network states had to encode and maintain past information from multiple cues that could occur several words apart. To probe the circuit's memory capacity, we compared models where network connectivity, the shape of synaptic currents, and properties of neuronal adaptation were systematically manipulated. We found that task-relevant memory could be derived from a mechanism of neuronal spike-rate adaptation, modelled as a conductance that hyperpolarized the membrane following a spike and relaxed to baseline exponentially with a fixed time-constant. By acting directly on the membrane potential it provided processing memory that allowed the system to successfully interpret its sentence input. Near optimal performance was also observed when an exponential decay model of post-synaptic currents was added into the circuit, with time-constants approximating excitatory NMDA and inhibitory GABA-B receptor dynamics. Thus, the information flow was extended over time, creating memory characteristics comparable to spike-rate adaptation. Recurrent connectivity, in contrast, only played a limited role in maintaining information; an acyclic version of the recurrent circuit achieved similar accuracy. This indicates that random recurrent connectivity at the modelled spatial scale did not contribute additional processing memory to the task. Taken together, these results suggest that memory for language might be provided by activity-silent dynamic processes rather than the active replay of past input as in storage-and-retrieval models of working memory. Furthermore, memory in biological networks can take multiple forms on a continuum of time-scales. Therefore, the development of neurobiologically realistic, causal models will be critical for our understanding of the role of memory in language processing.

Abstract

Institute of Adaptive and Neural Computation, School of Informatics, University of Edinburgh, UK

Abstract

It is generally assumed that structure building processes in the spoken and written modalities are subserved by modality-independent lexical, morphological, grammatical, and conceptual processes. We present a large-scale neuroimaging study (N=204) on whether the unification of sentence structure is supramodal in this sense, testing if observations replicate across written and spoken sentence materials. The activity in the unification network should increase when it is presented with a challenging sentence structure, irrespective of the input modality. We build on the well-established findings that multiple non-local dependencies, overlapping in time, are challenging and that language users disprefer left- over right-branching sentence structures in written and spoken language, at least in the context of mainly right-branching languages such as English and Dutch. We thus focused our study with Dutch participants on a left-branching processing complexity measure. Supramodal effects of left-branching complexity were observed in a left-lateralized perisylvian network. The left inferior frontal gyrus (LIFG) and the left posterior middle temporal gyrus (LpMTG) were most clearly associated with left-branching processing complexity. The left anterior middle temporal gyrus (LaMTG) and left inferior parietal lobe (LIPL) were also significant, although less specifically. The LaMTG was increasingly active also for sentences with increasing right-branching processing complexity. A direct comparison between left- and right-branching processing complexity yielded activity in an LIFG ROI for left > right-branching complexity, while the right > left contrast showed no activation. Using a linear contrast testing for increases in the left-branching complexity effect over the sentence, we found significant activity in LIFG and LpMTG. In other words, the activity in these regions increased from sentence onset to end, in parallel with the increase of the left-branching complexity measure. No similar increase was observed in LIPL. Thus, the observed functional segregation during sentence processing of LaMTG and LIPL vs. LIFG and LpMTG is consistent with our observation of differential activation changes in sensitivity to left- vs. right-branching structure. While LIFG, LpMTG, LaMTG and LIPL all contribute to the supramodal unification processes, the results suggest that these regions differ in their respective contributions to the subprocesses of unification. Our results speak to the high processing costs of (1) simultaneous unification and (2) maintenance of constituents that are not yet attached to the already unified part of the sentence. Sentences with high left- (compared to right-) branching complexity impose an added load on unification. We show that this added load leads to an increased BOLD response in left perisylvian regions. The results are relevant for understanding the neural underpinnings of the processing difficulty linked to multiple, overlapping non-local dependencies. In conclusion, we used the left- and right branching complexity measures to index this processing difficulty and showed that the unification network operates with similar spatiotemporal dynamics over the course of the sentence, during unification of both written and spoken sentences.

Abstract

Introduction: Natural communication is not only literal, but to a large extent also inferential. For example, sometimes people say "It is hard to give a good presentation" to actually mean "Your talk was a mess!", and listeners need to infer the speaker’s hidden message. In spite of the pervasiveness of this phenomenon in everyday communication, and even though the hidden meaning is often what it’s all about, very little is known about how the brain supports the comprehension of indirect language. What are the neural systems involved in the inferential process , and how are they different from those involved in word- and sentence-level meaning processing? We investigated the neural correlates of this so-called pragmatic inferencing in an fMRI study involving natural spoken dialogue. Methods: As a test case, we focused on the inferences needed to understand indirect replies. 18 native listeners of Dutch listened to dialogues ending in a question-answer (QA) pair. The final and critical utterance, e.g., "It is hard to give a good presentation", had different meanings depending on the dialogue context and the immediately preceding question: (1) Direct reply: Q: "How is it to give a good presentation?" A: "It is hard to give a good presentation" (2) Indirect reply, neutral: Q: "Will you give a presentation at the conference?" (rather than a poster) A: "It is hard to give a good presentation" (3) Indirect reply, face-saving: Q: "Did you like my presentation?" A: "It is hard to give a good presentation" While one of the indirect conditions was neutral, the other involved a socio-emotional aspect, as the reason for indirectness was to 'save one’s face' (as in excuses or polite refusals). Participants were asked to pay attention to the dialogues and, to ensure the latter, occasionally received a comprehension question (on filler items only). No other task demands were imposed. Results: Relative to direct replies in exchanges like (1), the indirect replies in exchanges like (2) and (3) activated brain structures associated with theory of mind and inferencing: right angular gyrus (TPJ), right DM prefrontal / frontal cortex (SMA, ACC). Both types of indirect replies also bilaterally activated the insula, an area known to be involved in empathy and affective processing. Moreover, both types of indirect replies recruited bilateral inferior frontal gyrus, thought to play a role in situation model updating. The comparison between neutral (2) and face-saving (3) indirect replies revealed that the presumed affective load of the face-saving replies activated just one additional area: right inferior frontal gyrus; we did not see any activation in classic affect-related areas. Importantly, we used the same critical sentences in all conditions. Our results can thus not be explained by lexico-semantic or other (e.g. syntactic, word frequency) factors. Conclusions: To extend neurocognitive research on meaning in language beyond the level of straightforward literal utterances, we investigated the neural correlates of pragmatic inferencing in an fMRI study involving indirect replies in natural spoken dialogue. Our findings reveal that the areas used to infer the intended meaning of an implicit message are partly different from the classic language network. Furthermore, the identity of the areas involved is consistent with the idea that inferring hidden meanings requires taking the speaker’s perspective. This confirms the importance of perspective taking in language comprehension, even in a situation where the listener is not the one addressed. Also, as the areas recruited by indirect replies generally do not light up in standard fMRI sentence comprehension paradigms, our study testifies to the importance of studying language understanding in richer contexts in which we can tap aspects of pragmatic processing, beyond the literal code.

Abstract

In an event-related fMRI study, we examined the overlap between the implicit processing of structured sequences, generated by a simple right-linear artificial unification grammar, with natural syntax related variability in the same subjects. Research investigating rule learning of potential linguistic relevance through artificial syntax often uses performance feedback and/or explicit instruction concerning the underlying rules. It is assumed that this approach ensures the right type of ''rule-following''because the rules are either explicitly provided to the subjects or explicitly discovered by the subjects during trial-and-error learning with feedback. In this work, we use a novel implicit preference classification task based on the structural mere exposure effect. Under conditions that in important respects are similar to those of natural language development (i. e., no explicit learning or teaching instruction, and no performance feedback), 32 subjects were exposed for 5 days to grammatical sequences during an immediate short-term memory task. On day 5, a preference classification test was administered, in which new sequences were presented. In addition, natural language data was acquired in the same subjects. Implicit preference classification was sensitive enough to show robust behavioral and fMRI effects. Preference classification of structured sequences activated Broca's region (BA 44/45) significantly, and was further activated by artificial syntactic violations. The effects related to artificial syntax in BA 44/45 were identical when we masked these with activity related to natural syntax processing. Moreover, the medial temporal lobe was deactivated during artificial syntax processing, consistent with the view that implicit processing does not rely on declarative memory mechanisms supported by the medial temporal lobe. In summary, we show that implicit acquisition of structured sequence knowledge results in the engagement of Broca's region during structured sequence processing. We conclude that Broca's region is a generic on-line sequence processor integrating information, in an incremental and recursive manner, independent of whether the sequences processed are structured by a natural or an artificial syntax.

Abstract

Repetition suppression is generally accepted as the neural correlate of behavioural priming and is often used to selectively identify the neuronal representations associated with a stimulus. However, this does not explain the large number of repetition enhancement effects observed under very similar conditions. Based on a review of a large set of studies we propose several variables biasing repetition effects towards enhancement instead of suppression. On the one hand, there are stimulus variables which influence the direction of repetition effects: visibility, e. g. in the case of degraded stimuli perceptual learning occurs; novelty, e. g. in case of unfamiliar stimuli a novel network formation process occurs; and timing intervals, e. g. repetition effects are sensitive to stimulus onset asynchronies. On the other hand, repetition effects are not solely automatic processes, triggered by particular types or sequences of stimuli. The brain is continuously and actively filtering, attending to and interpreting the information provided by our senses. Consequently, internal state variables like attention, expectation and explicit memory modulate repetition effects towards enhancement versus suppression. Current models i.e. the accumulation, fatigue and sharpening models of repetition suppression have so far left out top-down factors and cannot or can only partially account for repetition enhancement effects. Instead we propose that models which incorporate both stimulus bottom-up and cognitive top-down factors are called for in order to better understand repetition effects. A good candidate is the predictive coding model in which sensory evidence is interpreted according to subjective biases and statistical accounts of past encounters.

Abstract

Speaking is a complex, multilevel process, in which the first step is to compute the message that can be syntactically and phonologically encoded. Computing the message requires constructing a mental representation of what we want to express (the reference). This reference is then mapped onto linguistic concepts stored in memory, by which the meaning of the utterance (the sense) is constructed. We used fMRI adaptation to investigate brain areas sensitive to reference and sense in overt speech. By independently manipulating repetition of reference and sense across subsequently produced sentences in a picture description task, we distinguished sets of regions sensitive to these two steps in speaking. Encoding reference involved the bilateral inferior parietal lobes (BA 39) and right inferior frontal gyrus (BA 45), suggesting a role in constructing a non-linguistic mental representation. Left middle frontal gyrus (BA 6), bilateral superior parietal lobes and bilateral posterior temporal gyri (BA 37)) were sensitive to both sense and reference processing. These regions thus seem to support semantic encoding, the process of mapping reference onto sense. Left inferior frontal gyrus (BA 45), left middle frontal gyrus (BA44) and left angular gyrus (BA 39) showed adaptation to sense, and therefore appear sensitive to the output of semantic encoding. These results reveal the neural architecture for the first steps in producing an utterance. In addition, they show the feasibility of studying overt speech at a detailed level of analysis in fMRI studies.

Abstract

Speaking is a complex, multilevel process, in which the first step is to compute the message that can be syntactically and phonologically encoded. Computing the message requires constructing a mental representation of what we want to express (the reference). This referent is mapped onto linguistic concepts stored in memory, by which the meaning of the utterance (the sense) is constructed. So far, one study targeted semantic encoding in sentence production (Menenti, Segaert & Hagoort, submitted) and none dissected this process further. We used fMRI adaptation to investigate brain areas sensitive to reference and sense in overt speech. fMRI adaptation is a phenomenon whereby repeating a stimulus property changes the BOLD-response in regions sensitive to that property. By independently manipulating repetition of reference and sense across subsequently produced sentences in a picture description task we distinguished sets of areas sensitive to these steps in semantic encoding in speaking. Methods: In a picture description paradigm, the described situation (the reference) and the linguistic semantic structure (the sense) of subsequently produced sentences were independently repeated across trials. Participants described pictures depicting events involving transitive verbs such as hit, kiss, greet, and two actors colored in different colors with sentences such as ‘The red man greets the green woman’. In our factorial design, the same situation involving the same actors could subsequently be described by two different sentences (repeated reference, novel sense) or the same sentence could subsequently be used to describe two different situations (novel reference, repeated sense). For reference, we controlled for the repetition of actors. For sense, we controlled for the repetition of individual words. See figure 1 for design and stimuli. To correct for increased movement and susceptibility artifacts due to speech, we scanned using 3T-fMRI parallel-acquired inhomogeneity-desensitized fMRI (Poser, Versluis, Hoogduin et al. 2006). Five images were acquired per TR and combined based on local T2* (Buur, Poser and Norris 2009). Results: The behavioral data (response onset, response duration and total time to complete the responses) showed effects of both sense and reference. In the fMRI analyses we looked for areas sensitive to only sense, only reference, or showing a conjunction of both factors. Encoding reference involved the bilateral inferior parietal lobes (BA 39), which showed repetition suppression, and right inferior frontal gyrus (BA 45), which showed repetition enhancement. Left inferior frontal gyrus (BA 45) showed suppression to repetition of sense, while left middle frontal gyrus (BA44) and left angular gyrus (BA 39) showed enhancement. Left middle frontal gyrus (BA 6), bilateral superior parietal lobes and bilateral posterior temporal gyri (BA 37)) showed repetition suppression to both sense and reference processing (conjunction analysis with conjunction null). See figure 2 for the results (p<.05 FWE corrected for multiple comparisons at cluster-level, maps thresholded at p<.001 uncorrected voxel-level.) Conclusions: The input to semantic encoding is construction of a referent, a mental representation that the utterance is about. The bilateral temporo-parietal junctions are involved in this process as they show sensitivity to repetition of reference but not sense. RIFG shows enhancement and may therefore be involved in constructing a more comprehensive model spanning several utterances. Semantic encoding itself requires mapping of the reference onto the sense. This involves large parts of the language network: bilateral posterior temporal lobes and upper left inferior frontal gyrus were sensitive to both reference and sense. Finally, sense recruits left inferior frontal gyrus (BA 45). This area is sensitive to syntactic encoding (Bookheimer 2002), the next step in speaking. These results reveal the neural architecture for the first steps in producing an utterance. In addition, they show the feasibility of studying overt speech at a detailed level of analysis in fMRI studies. References: Bookheimer, S. (2002), 'Functional MRI of language: new approaches to understanding the cortical organization of semantic procesing', Annual review of neuroscience, vol. 25, pp. 151-188. Buur, P. (2009), 'A dual echo approach to removing motion artefacts in fMRI time series', Magnetic Resonance in Medicine, vol. 22, no. 5, pp. 551-560. Menenti, L. (submitted), 'The neuronal infrastructure of speaking'. Poser, B. (2006), 'BOLD contrast sensitivity enhancement and artifact reduction with multiecho EPI: parallel-acquired inhomogeneity desensitized fMRI', Magnetic Resonance in Medicine, vol. 55, pp. 1227-1235.