Publications

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

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

Abstract

A recurrently connected attractor neural network with a Hebbian learning rule is currently our best ANN analogy for a piece cortex. Functionally biological memory operates on a spectrum of time scales with regard to induction and retention, and it is modulated in complex ways by sub-cortical neuromodulatory systems. Moreover, biological memory networks are commonly believed to be highly distributed and engage many co-operating cortical areas. Here we focus on the temporal aspects of induction and retention of memory in a connectionist type attractor memory model of a piece of cortex. A continuous time, forgetful Bayesian-Hebbian learning rule is described and compared to the characteristics of LTP and LTD seen experimentally. More generally, an attractor network implementing this learning rule can operate as a long-term, intermediate-term, or short-term memory. Modulation of the print-now signal of the learning rule replicates some experimental memory phenomena, like e.g. the von Restorff effect.

Abstract

It has previously been suggested that the activity in sensory regions of the brain can be modulated by attentional mechanisms during parallel cognitive processing. To investigate whether such attention-related modulations are present in the processing of pain, the regional cerebral blood ¯ow was measured using [15O]butanol and positron emission tomography in conditions involving both pain and parallel cognitive demands. The painful stimulus consisted of the standard cold pressor test and the cognitive task was a computerised perceptual maze test. The activations during the maze test reproduced findings in previous studies of the same cognitive task. The cold pressor test evoked signi®cant activity in the contralateral S1, and bilaterally in the somatosensory association areas (including S2), the ACC and the mid-insula. The activity in the somatosensory association areas and periaqueductal gray/midbrain were significantly modified, i.e. relatively decreased, when the subjects also were performing the maze task. The altered activity was accompanied with significantly lower ratings of pain during the cognitive task. In contrast, lateral orbitofrontal regions showed a relative increase of activity during pain combined with the maze task as compared to only pain, which suggests the possibility of the involvement of frontal cortex in modulation of regions processing pain

Abstract

Capacity limited memory systems need to gradually forget old information in order to avoid catastrophic forgetting where all stored information is lost. This can be achieved by allowing new information to overwrite old, as in the so-called palimpsest memory. This paper describes a new such learning rule employed in an attractor neural network. The network does not exhibit catastrophic forgetting, has a capacity dependent on the learning time constant and exhibits recency e!ects in retrieval