Almut Schüz

Lack of long-term cortical reorganization after macaque retinal lesions

Several aspects of cortical organization are thought to remain plastic into adulthood, allowing cortical sensorimotor maps to be modified continuously by experience. This dynamic nature of cortical circuitry is important for learning, as well as for repair after injury to the nervous system. Electrophysiology studies suggest that adult macaque primary visual cortex (V1) undergoes large-scale reorganization within a few months after retinal lesioning, but this issue has not been conclusively settled. Here we applied the technique of functional magnetic resonance imaging (fMRI) to detect changes in the cortical topography of macaque area V1 after binocular retinal lesions. fMRI allows non-invasive, in vivo, long-term monitoring of cortical activity with a wide field of view, sampling signals from multiple neurons per unit cortical area. We show that, in contrast with previous studies, adult macaque V1 does not approach normal responsivity during 7.5 months of follow-up after retinal lesions, and its topography does not change. Electrophysiology experiments corroborated the fMRI results. This indicates that adult macaque V1 has limited potential for reorganization in the months following retinal injury.

Cortical areas : unity and diversity

1. Introduction: Homogeneity and Heterogeneity of Cortical Structure: a Theme and its Variations Part 1. The Empirical Status of Cortical Maps 2. Cyto - and Myeloarchitectonics: their Relationship and Possible Functional Significance 3. Architectonic Mapping of the Human Cerebral Cortex 4. Topographical Variability of Cytoarchitectonic Areas 5. Mapping of Human Brain Function by Neuroimaging Methods Part 2. Cortical Areas: Correlation with Connectivity 6. Regional Dendritic Variation in Primate Cortical Pyramidal Cells 7. Intrinsic Connections in Mammalian Cerebral Cortex 8. Thalamic Systems and the Diversity of Cortical Areas 9. Cortical Areas and Patterns of Cortico-cortical Connections Part 3. Constancy and Variation Across Species 10. The Cerebral Cortex of Mammals: Diversity within Unity 11. Laminar Continuity between Neo- and Meso-cortex: the Hypothesis of the added Laminae in the Neocortex Part 4. Functional Equivalence Between Areas 12. Cross-Modal Plasticity as a Tool for Understanding the Ontogeny and Phylogeny of Cerebral Cortex 13. Do Primary Sensory Areas Play Analogous Roles in Different Sensory Modalities 14. Platic-adaptive Properties of Cortical Areas Part 5. Morphological Substrates of Segregation and Integration 15. Connectional Organisation and Function in the Macaque Cerebral Cortex 16. The Human Cortical White Matter: Quantitative Aspects of Corticocortical Long-range Connectivity 17. Fundamentals of Association Cortex 18. Wheels Within Wheels: Circuits for Integration of Neural Assemblies on Small and Large Scales Part 6. Discussion Section

Synapses on axon collaterals of pyramidal cells are spaced at random intervals: a Golgi study in the mouse cerebral cortex.

In this study we investigated the arrangement of synapses on local axon collaterals of Golgi-stained pyramidal neurons in the mouse cerebral cortex. As synaptic markers we considered axonal swellings visible at high magnification under the light microscope. Such axonal swellings coincide with synaptic boutons, as has been demonstrated in a number of combined light and electron microscopic studies. These studies also indicated that, in most cases, one bouton corresponds precisely to one synapse. Golgi-impregnated axonal trees of 20 neocortical pyramidal neurons were drawn with a camera lucida. Axonal swellings were marked on the drawings. Most swellings were ‘en passant’; occasionally, they were situated at the tip of short, spine-like processes. On axon collaterals, the average interval between swellings was 4.5 μm. On the axonal main stem, the swellings were always less densely packed than on the collaterals. Statistical analysis of the spatial distribution of the swellings did not reveal any special patterns. Instead, the arrangement of swellings on individual collaterals follows a Poisson distribution. Moreover, the same holds to a large extent for the entire collection of pyramidal cell collaterals. This suggests that a single Poisson process, characterized by only one rate parameter (number of synapses per unit length), describes most of the spatial distribution of synapses along pyramidal cell collaterals. These findings do not speak in favour of a pronounced target specificity of pyramidal neurons at the synaptic level. Instead, our results support a probabilistic model of cortical connectivity.

Spatiotemporal receptive fields: a dynamical model derived from cortical architectonics

We assume that the mammalian neocortex is built up out of some six layers which differ in their morphology and their external connections. Intrinsic connectivity is largely excitatory, leading to a considerable amount of positive feedback. The majority of cortical neurons can be divided into two main classes: the pyramidal cells, which are said to be excitatory, and local cells (most notably the non-spiny stellate cells), which are said to be inhibitory. The form of the dendritic and axonal arborizations of both groups is discussed in detail. This results in a simplified model of the cortex as a stack of six layers with mutual connections determined by the principles of fibre anatomy. This stack can be treated as a multi-input-multi-output system by means of the linear systems theory of homogeneous layers. The detailed equations for the simulation are derived in the Appendix. The results of the simulations show that the temporal and spatial behaviour of an excitation distribution cannot be treated separately. Further, they indicate specific processing in the different layers and some independence from details of wiring. Finally, the simulation results are applied to the theory of visual receptive fields. This yields some insight into the mechanisms possibly underlying hypercomplexity, putative nonlinearities, lateral inhibition, oscillating cell responses, and velocity-dependent tuning curves.

Basic connectivity of the cerebral cortex and some considerations on the corpus callosum.

Studies on the connectivity of the cerebral cortex have lent strong support to the idea that the cortex is an associative network in which information is stored by ways of Hebbian cell assemblies. One of the main arguments for this is the elaborated system of cortico-cortical long-range connections which allows distant regions of the cortex to interact. Part of this system is the corpus callosum, which is responsible for the co-operation of the two cortical hemispheres. The following points are interesting with regard to interhemispheric co-operation: (1) the callosal system includes fewer neurons than the system of intrahemispheric long-range connections; (2) the mirror image activity induced by the callosal system may be advantageous for the ignition of cell assemblies; (3) the fibres of the corpus callosum differ considerably in thickness, which may be considered as anatomical evidence for more direct co-operation of the two hemispheres in some tasks rather than in others; and (4) a complex relationship between brain size and fibre thickness becomes evident in the corpus callosum, in which only some fibres seem to compensate for the longer conduction times in larger brains.

A modeler's view on the spatial structure of intrinsic horizontal connectivity in the neocortex

Most current computational models of neocortical networks assume a homogeneous and isotropic arrangement of local synaptic couplings between neurons. Sparse, recurrent connectivity is typically implemented with simple statistical wiring rules. For spatially extended networks, however, such random graph models are inadequate because they ignore the traits of neuron geometry, most notably various distance dependent features of horizontal connectivity. It is to be expected that such non-random structural attributes have a great impact, both on the spatio-temporal activity dynamics and on the biological function of neocortical networks. Here we review the neuroanatomical literature describing long-range horizontal connectivity in the neocortex over distances of up to eight millimeters, in various cortical areas and mammalian species. We extract the main common features from these data to allow for improved models of large-scale cortical networks. Such models include, next to short-range neighborhood coupling, also long-range patchy connections. We show that despite the large variability in published neuroanatomical data it is reasonable to design a generic model which generalizes over different cortical areas and mammalian species. Later on, we critically discuss this generalization, and we describe some examples of how to specify the model in order to adapt it to specific properties of particular cortical areas or species.

Basic features of cortical connectivity and some considerations on language

Any theory of the neural mechanisms of language requires an understanding of the cerebral cortex, for this organ undoubtedly plays a part in the production and perception of speech. The connectivity of the cortical network, in our opinion, is best described in statistical terms, since no suggestion of specific “wiring” of individual neurons in the cortex has ever gone beyond speculation. The statistical picture is that of a huge network of elements of one kind, the pyramidal cells, connected to each other by a special kind of synapse, residing on dendritic spines. These synapses are very numerous, very weak, excitatory and probably plastic. These four properties make it quite likely that the cortex is a structure which stores memory in an associative way. Also, such a structure would be ideally suited for embodying information in the form of cell assemblies, as suggested by Hebb. Bearing in mind this picture of the cortex, which is now widely accepted, it is intruiguing to imagine what happens there during the production and comprehension of language. One clue is provided by the much-studied visual areas where (thanks to the work of Hubel and Wiesel) it is now quite obvious that individual neurons do not correspond to anything on the level of morphemes in language, but rather signal events at the level of phonemes or probably even below. The generation of syllables is very likely a process involving large sets of neurons, and the chaining of syllables into sentences probably requires the cooperation of several other parts of the brain in addition to the cortex.

Modeling and simulating the adaptive electrical properties of stochastic polymeric 3D networks

Memristors are passive two-terminal circuit elements that combine resistance and memory. Although in theory memristors are a very promising approach to fabricate hardware with adaptive properties, there are only very few implementations able to show their basic properties. We recently developed stochastic polymeric matrices with a functionality that evidences the formation of self-assembled three-dimensional (3D) networks of memristors. We demonstrated that those networks show the typical hysteretic behavior observed in the ‘one input-one output’ memristive configuration. Interestingly, using different protocols to electrically stimulate the networks, we also observed that their adaptive properties are similar to those present in the nervous system. Here, we model and simulate the electrical properties of these selfassembled polymeric networks of memristors, the topology of which is defined stochastically. First, we show that the model recreates the hysteretic behavior observed in the real experiments. Second, we demonstrate that the networks modeled indeed have a 3D instead of a planar functionality. Finally, we show that the adaptive properties of the networks depend on their connectivity pattern. Our model was able to replicate fundamental qualitative behavior of the real organic 3D memristor networks; yet, through the simulations, we also explored other interesting properties, such as the relation between connectivity patterns and adaptive properties. Our model and simulations represent an interesting tool to understand the very complex behavior of self-assembled memristor networks, which can finally help to predict and formulate hypotheses for future experiments.

Stochastic hybrid 3D matrix: learning and adaptation of electrical properties

Memristive devices are electronic elements with memory properties. This feature marks them out as possible candidates for mimicking synapse properties. Development of systems capable of performing simple brain operations demands a high level of integration of elements and their 3D organization into networks. Here, we demonstrate the formation and electrical properties of stochastic polymeric matrices. Several features of the network revealed similarities with those of the nervous system. In particular, applying different training protocols, we obtained two kinds of learning comparable to the “baby” and “adult” learning in animals and humans. To mimic “adult” learning, multi-task training was applied simultaneously resulting in the formation of few parallel pathways for a given task, modifiable by successive training. To mimic “baby” learning (imprinting), single task training was applied at one time, resulting in the formation of multiple parallel signal pathways, scarcely influenced by successive training.

Vascularization of Cytochrome Oxidase-Rich Blobs in the Primary Visual Cortex of Squirrel and Macaque Monkeys

The close correlation between energy supply by blood vessels and energy consumption by cellular processes in the brain is the basis of blood flow-related functional imaging techniques. Regional differences in vascular density can be detected using high-resolution functional magnetic resonance imaging. Therefore, inhomogeneities in vascularization might help to identify anatomically distinct areas noninvasively in vivo. It was reported previously that cytochrome oxidase-rich blobs in the striate cortex of squirrel monkeys are characterized by a notably higher vascular density (42% higher than interblob regions). However, blobs have so far never been identified in vivo on the basis of their vascular density. Here, we analyzed blobs of the primary visual cortex of squirrel monkeys and macaques with respect to the relationship between vascularization and cytochrome oxidase activity. By double staining with cytochrome oxidase enzyme histochemistry to define the blobs and collagen type IV immunohistochemistry to quantify the blood vessels, a close correlation between oxidative metabolism and vascularization was confirmed and quantified in detail. The vascular length density in cytochrome oxidase blobs was on average 4.5% higher than in the interblob regions, a difference almost one order of magnitude smaller than previously reported. Thus, the vascular density that is closely associated with local average metabolic activity is a structural equivalent of cerebral metabolism and blood flow. However, the quantitative differences in vascularization between blob and interblob regions are small and below the detectability threshold of the noninvasive hemodynamic imaging methods of today.