Publications

Abstract

The language faculty is physically realized in the neurobiological infrastructure of the human brain. Despite significant efforts, an integrated understanding of this system remains a formidable challenge. What is missing from most theoretical accounts is a specification of the neural mechanisms that implement language function. Computational models that have been put forward generally lack an explicit neurobiological foundation. We propose a neurobiologically informed causal modeling approach which offers a framework for how to bridge this gap. A neurobiological causal model is a mechanistic description of language processing that is grounded in, and constrained by, the characteristics of the neurobiological substrate. It intends to model the generators of language behavior at the level of implementational causality. We describe key features and neurobiological component parts from which causal models can be built and provide guidelines on how to implement them in model simulations. Then we outline how this approach can shed new light on the core computational machinery for language, the long-term storage of words in the mental lexicon and combinatorial processing in sentence comprehension. In contrast to cognitive theories of behavior, causal models are formulated in the “machine language” of neurobiology which is universal to human cognition. We argue that neurobiological causal modeling should be pursued in addition to existing approaches. Eventually, this approach will allow us to develop an explicit computational neurobiology of language.

Abstract

Neuron models with explicit dendritic dynamics have shed light on mechanisms for coincidence detection, pathway selection and temporal filtering. However, it is still unclear which morphological and physiological features are required to capture these phenomena. In this work, we introduce the Tripod neuron model and propose a minimal structural reduction of the dendritic tree that is able to reproduce these computations. The Tripod is a three-compartment model consisting of two segregated passive dendrites and a somatic compartment modelled as an adaptive, exponential integrate-and-fire neuron. It incorporates dendritic geometry, membrane physiology and receptor dynamics as measured in human pyramidal cells. We characterize the response of the Tripod to glutamatergic and GABAergic inputs and identify parameters that support supra-linear integration, coincidence-detection and pathway-specific gating through shunting inhibition. Following NMDA spikes, the Tripod neuron generates plateau potentials whose duration depends on the dendritic length and the strength of synaptic input. When fitted with distal compartments, the Tripod encodes previous activity into a dendritic depolarized state. This dendritic memory allows the neuron to perform temporal binding, and we show that it solves transition and sequence detection tasks on which a single-compartment model fails. Thus, the Tripod can account for dendritic computations previously explained only with more detailed neuron models or neural networks. Due to its simplicity, the Tripod neuron can be used efficiently in simulations of larger cortical circuits.

Abstract

Formal language hierarchy describes levels of increasing syntactic complexity (adjacent dependencies, nonadjacent nested, nonadjacent crossed) of which the transcription into a hierarchy of cognitive complexity remains under debate. The cognitive foundations of formal language hierarchy have been contradicted by two types of evidence: First, adjacent dependencies are not easier to learn compared to nonadjacent; second, crossed nonadjacent dependencies may be easier than nested. However, studies providing these findings may have engaged confounds: Repetition monitoring strategies may have accounted for participants’ high performance in nonadjacent dependencies, and linguistic experience may have accounted for the advantage of crossed dependencies. We conducted two artificial grammar learning experiments where we addressed these confounds by manipulating reliance on repetition monitoring and by testing participants inexperienced with crossed dependencies. Results showed relevant differences in learning adjacent versus nonadjacent dependencies and advantages of nested over crossed, suggesting that formal language hierarchy may indeed translate into a hierarchy of cognitive complexity

Abstract

Learning a specific skill during childhood may partly determine the functional organization of the adult brain. This hypothesis led us to study oral language processing in illiterate subjects who, for social reasons, had never entered school and had no knowledge of reading or writing. In a brain activation study using PET and statistical parametric mapping, we compared word and pseudoword repetition in literate and illiterate subjects. Our study confirms behavioural evidence of different phonological processing in illiterate subjects. During repetition of real words, the two groups performed similarly and activated similar areas of the brain. In contrast, illiterate subjects had more difficulty repeating pseudowords correctly and did not activate the same neural structures as literates. These results are consistent with the hypothesis that learning the written form of language (orthography) interacts with the function of oral language. Our results indicate that learning to read and write during childhood influences the functional organization of the adult human brain.

Abstract

A key function of attention is to select an appropriate subset of available information by facilitation of attended processes and/or inhibition of irrelevant processing. Functional imaging studies, using positron emission tomography, have during different experimental tasks revealed decreased neuronal activity in areas that process input from unattended sensory modalities. It has been hypothesized that these decreases reflect a selective inhibitory modulation of nonrelevant cortical processing. In this study we addressed this question using a continuous arithmetical task with and without concomitant disturbing auditory input (task-irrelevant speech). During the arithmetical task, irrelevant speech did not affect task-performance but yielded decreased activity in the auditory and midcingulate cortices and increased activity in the left posterior parietal cortex. This pattern of modulation is consistent with a top down inhibitory modulation of a nonattended input to the auditory cortex and a coexisting, attention-based facilitation of taskrelevant processing in higher order cortices. These findings suggest that task-related decreases in cortical activity may be of functional importance in the understanding of both attentional mechanisms and taskrelated information processing.