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

Several studies have reported an association between dyslexia and implicit learning deficits. It has been suggested that the weakness in implicit learning observed in dyslexic individuals may be related to sequential processing and implicit sequence learning. In the present article, we review the current literature on implicit learning and dyslexia. We describe a novel, forced-choice structural "mere exposure" artificial grammar learning paradigm and characterize this paradigm in normal readers in relation to the standard grammaticality classification paradigm. We argue that preference classification is a more optimal measure of the outcome of implicit acquisition since in the preference version participants are kept completely unaware of the underlying generative mechanism, while in the grammaticality version, the subjects have, at least in principle, been informed about the existence of an underlying complex set of rules at the point of classification (but not during acquisition). On the basis of the "mere exposure effect," we tested the prediction that the development of preference will correlate with the grammaticality status of the classification items. In addition, we examined the effects of grammaticality (grammatical/nongrammatical) and associative chunk strength (ACS; high/low) on the classification tasks (preference/grammaticality). Using a balanced ACS design in which the factors of grammaticality (grammatical/nongrammatical) and ACS (high/low) were independently controlled in a 2 × 2 factorial design, we confirmed our predictions. We discuss the suitability of this task for further investigation of the implicit learning characteristics in dyslexia.

Abstract

Human implicit learning can be investigated with implicit artificial grammar learning, a paradigm that has been proposed as a simple model for aspects of natural language acquisition. In the present study we compared the typical yes–no grammaticality classification, with yes–no preference classification. In the case of preference instruction no reference to the underlying generative mechanism (i.e., grammar) is needed and the subjects are therefore completely uninformed about an underlying structure in the acquisition material. In experiment 1, subjects engaged in a short-term memory task using only grammatical strings without performance feedback for 5 days. As a result of the 5 acquisition days, classification performance was independent of instruction type and both the preference and the grammaticality group acquired relevant knowledge of the underlying generative mechanism to a similar degree. Changing the grammatical stings to random strings in the acquisition material (experiment 2) resulted in classification being driven by local substring familiarity. Contrasting repeated vs. non-repeated preference classification (experiment 3) showed that the effect of local substring familiarity decreases with repeated classification. This was not the case for repeated grammaticality classifications. We conclude that classification performance is largely independent of instruction type and that forced-choice preference classification is equivalent to the typical grammaticality classification.

Abstract

Cognitive neuroscience approaches the brain as a cognitive system: a system that functionally is conceptualized in terms of information processing. We outline some aspects of this concept and consider a physical system to be an information processing device when a subclass of its physical states can be viewed as representational/cognitive and transitions between these can be conceptualized as a process operating on these states by implementing operations on the corresponding representational structures. We identify a generic and fundamental problem in cognition: sequentially organized structured processing. Structured sequence processing provides the brain, in an essential sense, with its processing logic. In an approach addressing this problem, we illustrate how to integrate levels of analysis within a framework of adaptive dynamical systems. We note that the dynamical system framework lends itself to a description of asynchronous event-driven devices, which is likely to be important in cognition because the brain appears to be an asynchronous processing system. We use the human language faculty and natural language processing as a concrete example through out.

Abstract

Remembering complex, multidimensional information typically requires strategic memory retrieval, during which information is structured, for instance by spatial- or temporal associations. Although brain regions involved in strategic memory retrieval in general have been identified, differences in retrieval operations related to distinct retrieval strategies are not well-understood. Thus, our aim was to identify brain regions whose activity is differentially involved in spatial-associative and temporal-associative retrieval. First, we showed that our behavioral paradigm probing memory for a set of object-location associations promoted the use of a spatial-associative structure following an encoding condition that provided multiple associations to neighboring objects (spatial-associative condition) and the use of a temporal- associative structure following another study condition that provided predominantly temporal associations between sequentially presented items (temporal-associative condition). Next, we used an adapted version of this paradigm for functional MRI, where we contrasted brain activity related to the recall of object-location associations that were either encoded in the spatial- or the temporal-associative condition. In addition to brain regions generally involved in recall, we found that activity in higher-order visual regions, including the fusiform gyrus, the lingual gyrus, and the cuneus, was relatively enhanced when subjects used a spatial-associative structure for retrieval. In contrast, activity in the globus pallidus and the thalamus was relatively enhanced when subjects used a temporal-associative structure for retrieval. In conclusion, we provide evidence for differential involvement of these brain regions related to different types of strategic memory retrieval and the neural structures described play a role in either spatial-associative or temporal-associative memory retrieval.

Abstract

We used simultaneously recorded EEG and fMRI to investigate in which areas the BOLD signal correlates with frontal theta power changes, while subjects were quietly lying resting in the scanner with their eyes open. To obtain a reliable estimate of frontal theta power we applied ICA on band-pass filtered (2–9 Hz) EEG data. For each subject we selected the component that best matched the mid-frontal scalp topography associated with the frontal theta rhythm. We applied a time-frequency analysis on this component and used the time course of the frequency bin with the highest overall power to form a regressor that modeled spontaneous fluctuations in frontal theta power. No significant positive BOLD correlations with this regressor were observed. Extensive negative correlations were observed in the areas that together form the default mode network. We conclude that frontal theta activity can be seen as an EEG index of default mode network activity.

Abstract

We investigated how the hippocampus and its adjacent mediotemporal structures contribute to contextual and noncontextual declarative memory retrieval by manipulating the amount of contextual information across two levels of the same contextual dimension in a source memory task. A first analysis identified medial temporal lobe (MTL) substructures mediating either contextual or noncontextual retrieval. A linearly weighted analysis elucidated which MTL substructures show a gradually increasing neural activity, depending on the amount of contextual information retrieved. A hippocampal engagement was found during both levels of source memory but not during item memory retrieval. The anterior MTL including the perirhinal cortex was only engaged during item memory retrieval by an activity decrease. Only the posterior parahippocampal cortex showed an activation increasing with the amount of contextual information retrieved. If one assumes a roughly linear relationship between the blood-oxygenation level-dependent (BOLD) signal and the associated cognitive process, our results suggest that the posterior parahippocampal cortex is involved in contextual retrieval on the basis of memory strength while the hippocampus processes representations of item-context binding. The anterior MTL including perirhinal cortex seems to be particularly engaged in familiarity-based item recognition. If one assumes departure from linearity, however, our results can also be explained by one-dimensional modulation of memory strength.

Abstract

The human capacity to implicitly acquire knowledge of structured sequences has recently been investigated in artificial grammar learning using functional magnetic resonance imaging. It was found that the left inferior frontal cortex (IFC; Brodmann's area (BA) 44/45) was related to classification performance. The objective of this study was to investigate whether the IFC (BA 44/45) is causally related to classification of artificial syntactic structures by means of an off-line repetitive transcranial magnetic stimulation (rTMS) paradigm. We manipulated the stimulus material in a 2 × 2 factorial design with grammaticality status and local substring familiarity as factors. The participants showed a reliable effect of grammaticality on classification of novel items after 5days of exposure to grammatical exemplars without performance feedback in an implicit acquisition task. The results show that rTMS of BA 44/45 improves syntactic classification performance by increasing the rejection rate of non-grammatical items and by shortening reaction times of correct rejections specifically after left-sided stimulation. A similar pattern of results is observed in FMRI experiments on artificial syntactic classification. These results suggest that activity in the inferior frontal region is causally related to artificial syntax processing.

Abstract

The acute neural effects of progesterone are mediated by its neuroactive metabolites allopregnanolone and pregnanolone. These neurosteroids potentiate the inhibitory actions of c-aminobutyric acid (GABA). Progesterone is known to produce anxiolytic effects in animals, but recent animal studies suggest that pregnanolone increases anxiety after a period of low allopregnanolone concentration. This effect is potentially mediated by the amygdala and related to the negative mood symptoms in humans that are observed during increased allopregnanolone levels. Therefore, we investigated with functional magnetic resonance imaging (MRI) whether a single progesterone administration to healthy young women in their follicular phase modulates the amygdala response to salient, biologically relevant stimuli. The progesterone administration increased the plasma concentrations of progesterone and allopregnanolone to levels that are reached during the luteal phase and early pregnancy. The imaging results show that progesterone selectively increased amygdala reactivity. Furthermore, functional connectivity analyses indicate that progesterone modulated functional coupling of the amygdala with distant brain regions. These results reveal a neural mechanism by which progesterone may mediate adverse effects on anxiety and mood.

Abstract

Visual episodic memory encoding was investigated using echoplanar magnetic resonance imaging at 2.0 x 2.0 mm2 resolution and 1.0 mm section thickness, which allows for functional mapping of hippocampal, parahippocampal, and ventral occipital regions with reduced magnetic susceptibility artifact. The memory task was based on 54 image pairs each consisting of a complex visual scene and the face of one of six different photographers. A second group of subjects viewed the same set of images without memory instruction as well as a reversing checkerboard. Apart from visual activation in occipital cortical areas, episodic memory encoding revealed consistent activation in the parahippocampal gyrus but not in the hippocampus proper. This ®nding was most prominently evidenced in sagittal maps covering the right hippocampal formation. Mean activated volumes were 432±293 µl and 259±179 µl for intentional memory encoding and non-instructed viewing, respectively. In contrast, the checkerboard paradigm elicited pure visual activation without parahippocampal involvement.

Abstract

This paper presents a new approach to functional magnetic resonance imaging (FMRI) data analysis. The main difference lies in the view of what comprises an observation. Here we treat the data from one scanning session (comprising t volumes, say) as one observation. This is contrary to the conventional way of looking at the data where each session is treated as t different observations. Thus instead of viewing the v voxels comprising the 3D volume of the brain as the variables, we suggest the usage of the vt hypervoxels comprising the 4D volume of the brain-over-session as the variables. A linear model is fitted to the 4D volumes originating from different sessions. Parameter estimation and hypothesis testing in this model can be performed with standard techniques. The hypothesis testing generates 4D statistical images (SIs) to which any relevant test statistic can be applied. In this paper we describe two test statistics, one voxel based and one cluster based, that can be used to test a range of hypotheses. There are several benefits in treating the data from each session as one observation, two of which are: (i) the temporal characteristics of the signal can be investigated without an explicit model for the blood oxygenation level dependent (BOLD) contrast response function, and (ii) the observations (sessions) can be assumed to be independent and hence inference on the 4D SI can be made by nonparametric or Monte Carlo methods. The suggested 4D approach is applied to FMRI data and is shown to accurately detect the expected signal

Abstract

Recent functional brain imaging studies have shown that sensory-specific brain regions that are activated during perception/encoding of sensory-specific information are reactivated during memory retrieval of the same information. Here we used PET to examine whether verbal retrieval of action phrases is associated with reactivation of motor brain regions if the actions were overtly or covertly performed during encoding. Compared to a verbal condition, encoding by means of overt as well as covert activity was associated with differential activity in regions in contralateral somatosensory and motor cortex. Several of these regions were reactivated during retrieval. Common to both the overt and covert conditions was reactivation of regions in left ventral motor cortex and left inferior parietal cortex. A direct comparison of the overt and covert activity conditions showed that activation and reactivation of left dorsal parietal cortex and right cerebellum was specific to the overt condition. These results support the reactivation hypothesis by showing that verbal-explicit memory of actions involves areas that are engaged during overt and covert motor activity.

Abstract

The study of illiterate subjects, which for specific socio-cultural reasons did not have the opportunity to acquire basic reading and writing skills, represents one approach to study the interaction between neurobiological and cultural factors in cognitive development and the functional organization of the human brain. In addition the naturally occurring illiteracy may serve as a model for studying the influence of alphabetic orthography on auditory-verbal language. In this paper we have reviewed some recent behavioral and functional neuroimaging data indicating that learning an alphabetic written language modulates the auditory-verbal language system in a non-trivial way and provided support for the hypothesis that the functional architecture of the brain is modulated by literacy. We have also indicated that the effects of literacy and formal schooling is not limited to language related skills but appears to affect also other cognitive domains. In particular, we indicate that formal schooling influences 2D but not 3D visual naming skills. We have also pointed to the importance of using ecologically relevant tasks when comparing literate and illiterate subjects. We also demonstrate the applicability of a network approach in elucidating differences in the functional organization of the brain between groups. The strength of such an approach is the ability to study patterns of interactions between functionally specialized brain regions and the possibility to compare such patterns of brain interactions between groups or functional states. This complements the more commonly used activation approach to functional neuroimaging data, which characterize functionally specialized regions, and provides important data characterizing the functional interactions between these regions.

Abstract

The modulatory influence of literacy on the cognitive system of the human brain has been indicated in behavioral, neuroanatomic, and functional neuroimaging studies. In this study we explored the functional consequences of formal education and the acquisition of an alphabetic written language on two- and three-dimensional visual naming. The results show that illiterate subjects perform significantly worse on immediate naming of two-dimensional representations of common everyday objects compared to literate subjects, both in terms of accuracy and reaction times. In contrast, there was no significant difference when the subjects named the corresponding real objects. The results suggest that formal education and learning to read and to write modulate the cognitive process involved in processing two- but not three-dimensional representations of common everyday objects. Both the results of the reaction time and the error pattern analyses can be interpreted as indicating that the major influence of literacy affects the visual system or the interaction between the visual and the language systems. We suggest that the visual system in a wide sense and/or the interface between the visual and the language system are differently formatted in literate and illiterate subjects. In other words, we hypothesize that the pattern of interactions in the functional–anatomical networks subserving visual naming, that is, the interactions within and between the visual and language processing networks, differ in literate and illiterate subjects

Abstract

The strength of a memory trace is modulated by a variety of factors such as arousal, attention, context, type of processing during encoding, salience and novelty of the experience. Some of these factors can be modeled as a variable plasticity level in the memory system, controlled by arousal or relevance-estimating systems. We demonstrate that a Bayesian confidence propagation neural network with learning time constant modulated in this way exhibits enhanced recall of an item tagged as salient. Proactive and retroactive inhibition of other items is also demonstrated as well as an inverted U-shape response to overall plasticity