Publications

Abstract

Language processing involves the ability to store and integrate pieces of
information in working memory over short periods of time. According to
the dominant view, information is maintained through sustained, elevated
neural activity. Other work has argued that short-term synaptic facilitation
can serve as a substrate of memory. Here, we propose an account where
memory is supported by intrinsic plasticity that downregulates neuronal
firing rates. Single neuron responses are dependent on experience and we
show through simulations that these adaptive changes in excitability pro-
vide memory on timescales ranging from milliseconds to seconds. On this
account, spiking activity writes information into coupled dynamic variables
that control adaptation and move at slower timescales than the membrane
potential. From these variables, information is continuously read back into
the active membrane state for processing. This neuronal memory mech-
anism does not rely on persistent activity, excitatory feedback, or synap-
tic plasticity for storage. Instead, information is maintained in adaptive
conductances that reduce firing rates and can be accessed directly with-
out cued retrieval. Memory span is systematically related to both the time
constant of adaptation and baseline levels of neuronal excitability. Inter-
ference effects within memory arise when adaptation is long-lasting. We
demonstrate that this mechanism is sensitive to context and serial order
which makes it suitable for temporal integration in sequence processing
within the language domain. We also show that it enables the binding of
linguistic features over time within dynamic memory registers. This work
provides a step towards a computational neurobiology of language.

Abstract

In this paper we explore the feasibility of artificial (formal) grammar recognition (AGR) using spiking neural networks. A biologically inspired minicolumn architecture is designed as the basic computational unit. A network topography is defined based on the minicolumn architecture, here referred to as nodes, connected with excitatory and inhibitory connections. Nodes in the network represent unique internal states of the grammar’s finite state machine (FSM). Future work to improve the performance of the networks is discussed. The modeling framework developed can be used by neurophysiological research to implement network layouts and compare simulated performance characteristics to actual subject performance.

Abstract

In a 2x2 event-related FMRI study we find support for the idea that the inferior frontal cortex, centered on Broca’s region and its homologue, is involved in constructive unification operations during the structure-building process in parsing for comprehension. Tentatively, we provide evidence for a role of the dorsolateral prefrontal cortex centered on BA 9/46 in the control component of the language system. Finally, the left temporo-parietal cortex, in the vicinity of Wernicke’s region, supports the interaction between the syntax of gender agreement and sentence-level semantics.

Abstract

Human implicit learning can be investigated with implicit artificial grammar learning, a simple model for aspects of natural language acquisition. In this paper we investigate the remaining effect of modality transfer in syntactic classification of an acquired grammatical sequence structure after implicit grammar acquisition. Participants practiced either on acoustically presented syllable sequences or visually presented consonant letter sequences. During classification we independently manipulated the statistical frequency-based and rule-based characteristics of the classification stimuli. Participants performed reliably above chance on the within modality classification task although more so for those working on syllable sequence acquisition. These subjects were also the only group that kept a significant performance level in transfer classification. We speculate that this finding is of particular relevance in consideration of an ecological validity in the input signal in the use of artificial grammar learning and in language learning paradigms at large.

Abstract

Both local discourse and world knowledge are known to influence sentence processing. We investigated how these two sources of information conspire in language comprehension. Two types of critical sentences, correct and world knowledge anomalies, were preceded by either a neutral or a local context. The latter made the world knowledge anomalies more acceptable or plausible. We predicted that the effect of world knowledge anomalies would be weaker for the local context. World knowledge effects have previously been observed in the left inferior frontal region (Brodmann's area 45/47). In the current study, an effect of world knowledge was present in this region in the neutral context. We also observed an effect in the right inferior frontal gyrus, which was more sensitive to the discourse manipulation than the left inferior frontal gyrus. In addition, the left angular gyrus reacted strongly to the degree of discourse coherence between the context and critical sentence. Overall, both world knowledge and the discourse context affect the process of meaning unification, but do so by recruiting partly different sets of brain areas.

Abstract

A fundamental and intensively discussed question is whether medial temporal lobe (MTL) processes that lead to non-associative item memories differ in their anatomical substrate from processes underlying associative memory formation. Using event-related functional magnetic resonance imaging, we implemented a novel design to dissociate brain activity related to item and associative memory formation not only by subsequent memory performance and anatomy but also in time, because the two constituents of each pair to be memorized were presented sequentially with an intra-pair delay of several seconds. Furthermore, the design enabled us to reduce potential differences in memory strength between item and associative memory by increasing task difficulty in the item recognition memory test. Confidence ratings for correct item recognition for both constituents did not differ between trials in which only item memory was correct and trials in which item and associative memory were correct. Specific subsequent memory analyses for item and associative memory formation revealed brain activity that appears selectively related to item memory formation in the posterior inferior temporal, posterior parahippocampal, and perirhinal cortices. In contrast, hippocampal and inferior prefrontal activity predicted successful retrieval of newly formed inter-item associations. Our findings therefore suggest that different MTL subregions indeed play distinct roles in the formation of item memory and inter-item associative memory as expected by several dual process models of the MTL memory system.

Abstract

PET and fMRI experiments have previously shown that several brain regions in the frontal and parietal lobe are involved in working memory maintenance. MEG and EEG experiments have shown parametric increases with load for oscillatory activity in posterior alpha and frontal theta power. In the current study we investigated whether the areas found with fMRI can be associated with these alpha and theta effects by measuring simultaneous EEG and fMRI during a modified Sternberg task This allowed us to correlate EEG at the single trial level with the fMRI BOLD signal by forming a regressor based on single trial alpha and theta
power estimates. We observed a right posterior, parametric alpha power increase, which was functionally related to decreases in BOLD in the primary visual cortex and in the posterior part of the right middle temporal gyrus. We relate this finding to the inhibition of neuronal activity that may interfere with WM maintenance. An observed parametric increase in frontal theta power was correlated to a decrease in BOLD in
regions that together form the default mode network. We did not observe correlations between oscillatory EEG phenomena and BOLD in the traditional WM areas. In conclusion, the study shows that simultaneous EEG fMRI recordings can be successfully used to identify the emergence of functional networks in the brain during the execution of a cognitive task.

Abstract

Sentence comprehension requires the retrieval of single word information from long-term memory, and the integration of this information into multiword representations. The current functional magnetic resonance imaging study explored the hypothesis that the left posterior temporal gyrus supports the retrieval of lexical-syntactic information, whereas left inferior frontal gyrus (LIFG) contributes to syntactic unification. Twenty-eight subjects read sentences and word sequences containing word-category (noun–verb) ambiguous words at critical positions. Regions contributing to the syntactic unification process should show enhanced activation for sentences compared to words, and only within sentences display a larger signal for ambiguous than unambiguous conditions. The posterior LIFG showed exactly this predicted pattern, confirming our hypothesis that LIFG contributes to syntactic unification. The left posterior middle temporal gyrus was activated more for ambiguous than unambiguous conditions (main effect over both sentences and word sequences), as predicted for regions subserving the retrieval of lexical-syntactic information from memory. We conclude that understanding language involves the dynamic interplay between left inferior frontal and left posterior temporal regions.

Abstract

Difficulties with pragmatic aspects of communication are universal across individuals with autism spectrum disorders (ASDs). Here we focused on an aspect of pragmatic language comprehension that is relevant to social interaction in daily life: the integration of speaker characteristics inferred from the voice with the content of a message. Using functional magnetic resonance imaging (fMRI), we examined the neural correlates of the integration of voice-based inferences about the speaker’s age, gender or social background, and sentence content in adults with ASD and matched control participants. Relative to the control group, the ASD group showed increased activation in right inferior frontal gyrus (RIFG; Brodmann area 47) for speakerincongruent sentences compared to speaker-congruent sentences. Given that both groups performed behaviourally at a similar level on a debriefing interview outside the scanner, the increased activation in RIFG for the ASD group was interpreted as being compensatory in nature. It presumably reflects spill-over processing from the language dominant left hemisphere due to higher task demands faced by the participants with ASD when integrating speaker characteristics and the content of a spoken sentence. Furthermore, only the control group showed decreased activation for speaker-incongruent relative to speaker-congruent sentences in right ventral medial prefrontal cortex (vMPFC; Brodmann area 10), including right anterior cingulate cortex (ACC; Brodmann area 24/32). Since vMPFC is involved in self-referential processing related to judgments and inferences about self and others, the absence of such a modulation in vMPFC activation in the ASD group possibly points to atypical default self-referential mental activity in ASD. Our results show that in ASD compensatory mechanisms are necessary in implicit, low-level inferential processes in spoken language understanding. This indicates that pragmatic language problems in ASD are not restricted to high-level inferential processes, but encompass the most basic aspects of pragmatic language processing.

Abstract

When interpreting a message, a listener takes into account several sources of linguistic and extralinguistic information. Here we focused on one particular form of extralinguistic information, certain speaker characteristics as conveyed by the voice. Using functional magnetic resonance imaging, we examined the neural structures involved in the unification of sentence meaning and voice-based inferences about the speaker's age, sex, or social background. We found enhanced activation in the inferior frontal gyrus bilaterally (BA 45/47) during listening to sentences whose meaning was incongruent with inferred speaker characteristics. Furthermore, our results showed an overlap in brain regions involved in unification of speaker-related information and those used for the unification of semantic and world knowledge information [inferior frontal gyrus bilaterally (BA 45/47) and left middle temporal gyrus (BA 21)]. These findings provide evidence for a shared neural unification system for linguistic and extralinguistic sources of information and extend the existing knowledge about the role of inferior frontal cortex as a crucial component for unification during language comprehension.

Abstract

A dominant hypothesis in empirical research on the evolution of language is the following: the fundamental difference between animal and human communication systems is captured by the distinction between regular and more complex non-regular grammars. Studies reporting successful artificial grammar learning of nested recursive structures and imaging studies of the same have methodological shortcomings since they typically allow explicit problem solving strategies and this has been shown to account for the learning effect in subsequent behavioral studies. The present study overcomes these shortcomings by using subtle violations of agreement structure in a preference classification task. In contrast to the studies conducted so far, we use an implicit learning paradigm, allowing the time needed for both abstraction processes and consolidation to take place. Our results demonstrate robust implicit learning of recursively embedded structures (context-free grammar) and recursive structures with cross-dependencies (context-sensitive grammar) in an artificial grammar learning task spanning 9 days. Keywords: Implicit artificial grammar learning; centre embedded; cross-dependency; implicit learning; context-sensitive grammar; context-free grammar; regular grammar; non-regular grammar

Abstract

Theeffects of spatial filtering in functional magnetic resonance imaging were investigated by reevaluating the data of a previous study of episodic memory encoding at 2 × 2 × 4-mm3 resolution with use of a SPM99 analysis involving a Gaussian kernel of 8-mm full width at half maximum. In addition, a multisubject analysis of activated regions was performed by normalizing the functional images to an approximate Talairach brain atlas. In individual subjects, spatial filtering merged activations in anatomically separated brain regions. Moreover, small foci of activated pixels which originated from veins became blurred and hence indistinguishable from parenchymal responses. The multisubject analysis resulted in activation of the hippocampus proper, a finding which could not be confirmed by the activation maps obtained at high resolution. It is concluded that the validity of multisubject fMRI analyses can be considerably improved by first analyzing individual data sets at optimum resolution to assess the effects of spatial filtering and minimize the risk of signal contamination by macroscopically visible vessels.

Abstract

There is much evidence for the existence of multiple memory systems. However, it has been argued that tasks assumed to reflect different memory systems share basic processing components and are mediated by overlapping neural systems. Here we used multivariate analysis of PET-data to analyze similarities and differences in brain activity for multiple tests of working memory, semantic memory, and episodic memory. The results from two experiments revealed between-systems differences, but also between-systems similarities and within-system differences. Specifically, support was obtained for a task-general working-memory network that may underlie active maintenance. Premotor and parietal regions were salient components of this network. A common network was also identified for two episodic tasks, cued recall and recognition, but not for a test of autobiographical memory. This network involved regions in right inferior and polar frontal cortex, and lateral and medial parietal cortex. Several of these regions were also engaged during the working-memory tasks, indicating shared processing for episodic and working memory. Fact retrieval and synonym generation were associated with increased activity in left inferior frontal and middle temporal regions and right cerebellum. This network was also associated with the autobiographical task, but not with living/non-living classification, and may reflect elaborate retrieval of semantic information. Implications of the present results for the classification of memory tasks with respect to systems and/or processes are discussed.

Abstract

It has been suggested that placebo analgesia involves both higher order cognitive networks and endogenous opioid systems. The rostral anterior cingulate cortex (rACC) and the brainstem are implicated in opioid analgesia, suggesting a similar role for these structures in placebo analgesia. Using positron emission tomography, we confirmed that both opioid and placebo analgesia are associated with increased activity in the rACC. We also observed a covariation between the activity in the rACC and the brainstem during both opioid and placebo analgesia, but not during the pain-only condition. These findings indicate a related neural mechanism in placebo and opioid analgesia.

Abstract

It has been suggested that placebo analgesia involves both higher order cognitive networks and endogenous opioid systems. The rostral anterior cingulate cortex (rACC) and the brainstem are implicated in opioid analgesia, suggesting a similar role for these structures in placebo analgesia. Using positron emission tomography, we confirmed that both opioid and placebo analgesia are associated with increased activity in the rACC. We also observed a covariation between the activity in the rACC and the brainstem during both opioid and placebo analgesia, but not during the pain-only condition. These findings indicate a related neural mechanism in placebo and opioid analgesia.

Abstract

Several functional imaging studies of pain, using a number of different experimental paradigms and a variety of reference states, have failed to detect activations in the somatosensory cortices, while other imaging studies of pain have reported significant activations in these regions. The role of the somatosensory areas in pain processing has therefore been debated. In the present study the left hand was immersed in painfully cold water (standard cold pressor test) and in nonpainfully cold water during 2 min, and PET-scans were obtained either during the first or the second minute of stimulation. We observed no significant increase of activity in the somatosensory regions when the painful conditions were directly compared with the control conditions. In order to better understand the role of the primary somatosensory cortex (S1) in pain processing we used a regression analysis to study the relation between a ROI (region of interest) in the somatotopic S1-area for the stimulated hand and other regions known to be involved in pain processing. We hypothesized that although no increased activity was observed in the S1 during pain, this region would change its covariation pattern during noxious input as compared to the control stimulation if it is involved in or affected by the processing of pain. In the nonpainful cold conditions widespread regions of the ipsilateral and contralateral somatosensory cortex showed a positive covariation with the activity in the S1-ROI. However, during the first and second minute of pain this regression was significantly attenuated. During the second minute of painful stimulation there was a significant positive covariation between the activity in the S1-ROI and the other regions that are known to be involved in pain processing. Importantly, this relation was significantly stronger for the insula and the orbitofrontal cortex bilaterally when compared to the nonpainful state. The results indicate that the S1-cortex may be engaged in or affected by the processing of pain although no differential activity is observed when pain is compared with the reference condition.

Abstract

A realtime online learning system with capacity limits needs to gradually forget old information in order to avoid catastrophic forgetting. This can be achieved by allowing new information to overwrite old, as in a so-called palimpsest memory. This paper describes an incremental learning rule based on the Bayesian confidence propagation neural network that has palimpsest properties when employed in an attractor neural network. The network does not suffer from catastrophic forgetting, has a capacity dependent on the learning time constant and exhibits faster convergence for newer patterns.