Interplay between BDNF,TrkB signalling and GABAergic inhibition in the visual cortex of mice

Der visuelle Kortex ist eine der attraktivsten Modellsysteme zur Untersuchung der molekularen Mechanismen der synaptischen Plastizität im Gehirn. Es hat sich gezeigt, dass der Wachstumsfaktor brain-derived-neurotrophic-factor (BDNF) und die GABAerge Hemmung während der Entwicklung eine essentielle Funktion in der Regulierung der synaptischen Plastizität im visuellen Kortex besitzen. BDNF bindet u.a. an TrkB Rezeptoren, die das Signal intrazellular an unterschiedliche Effektormoleküle weiter vermitteln. Außer BDNF sind auch andere TrkB-Rezeptor Agonisten in der Literatur beschrieben. Einer davon ist das kürzlich identifizierte Flavonoid 7,8-Dihydroxyflavone (7,8-DHF), welchem eine neurotrophe Wirkung zugeschrieben wird. Im ersten Abschnitt der vorliegenden Doktorarbeit wurde der Effekt dieses Agonisten auf die synaptische Übertragung und intrinsischen Zelleigenschaften im visuellen Kortex der Maus untersucht. Dies wurde mit Hilfe der whole-cell patch clamp Methode durchgeführt, wobei die synaptischen Eingänge der Pyramidalzellen der kortikalen Schicht 2/3 von besonderem Interesse waren.rnEine 30 minütige Inkubationszeit der kortikalen Schnitte mit 7,8 DHF (20µM) erzielte eine signifikante Reduktion der GABAergen Hemmung, während die glutamaterge synaptische Übertragung unverändert blieb. Des weiteren konnte in Gegenwart von 7,8 DHF eine Veränderung der intrinsischen neuronalen Zellmembraneigenschaften beobachtet werden. Dies wurde deutlich in der Erhöhung des Eingangwiderstandes und der Frequenz der induzierten Aktionspotentiale. Die chronische Applikation von 7,8 DHF in vivo bestätigte die selektive Wirkung von 7,8 DHF auf das GABAerge System. rnDie Rolle des BDNF-TrkB-Signalweges in der GABAergen Hemmung nach kortikalen Verletzungen ist bisher wenig verstanden. Eine häufig beschriebene elektrophysiologische Veränderung nach kortikaler Verletzung ist eine Reduktion in der GABAergen Hemmung. Im zweiten Abschnitt dieser Doktorarbeit wurde hierzu die Funktion des BDNF-TrkB-Signalweges auf die GABAerge Hemmung nach kortikaler Verletzung untersucht. Es wurde ein "ex-vivo/in-vitro“ Laser-Läsions Modell verwendet, wobei mittels eines Lasers im visuellen Kortex von WT und heterozygoten BDNF (+/−) Mäusen eine definierte, reproduzierbare Läsion induziert wurde. Nachfolgende elektrophysiologische Messungen ergaben, dass die Auswirkung einer Verletzung des visuellen Kortex auf die GABAerge Funktion signifikant von der basalen BDNF Konzentration im Kortex abhängt. Des weiteren konnte beobachtet werden, dass nach kortikaler Verletzung in WT Mäusen sowohl die Frequenz der basalen inhibitorischen, postsynaptischen Potentiale (mIPSCs) reduziert war, als auch ein erhöhtes Paired-Pulse Verhältnis vorlag. Diese Ergebnisse deuten auf Veränderungen der präsynaptischen Funktion inhibitorischer Synapsen auf Pyramidalneurone hin. Im Gegensatz dazu konnte in BDNF (+/−) mice Mäusen eine erhöhte und gleichzeitig verlängerte mIPSC-Amplitude beobachtet werden, induziert durch Reizung afferenter Nervenfasern. Hieraus lässt sich schließen, dass kortikale Verletzungen in BDNF (+/−) mice Mäusen Auswirkungen auf die Eigenschaften von postsynaptischen GABAA-Rezeptoren haben. Die nachfolgende Gabe eines TrkB-Rezeptor Antagonisten bestätigte diese Ergebnisse für das GABAerge System post-Läsion. Dies zeigt auch, dass die Änderungen der synaptischen Hemmung nicht auf eine Reduktion der BDNF-Konzentration zurückzuführen sind. Zusammengefasst zeigen die Ergebnisse der vorliegenden Arbeit, dass der BDNF-TrkB Signalweg eine wichtige Rolle in der Reorganisation der GABAergen Hemmung nach kortikalen Verletzungen spielt. So könnte ein TrkB-Rezeptor Agonist, wie das kürzlich entdeckte 7,8-DHF, über eine Modulation der BDNF-TrB Signalkaskade pharmakologisch die funktionelle Reorganisation des Kortex nach einer fokalen Gehirnverletzung fördern. rnrn

Stimulus predictability reduces responses in primary visual cortex

In this functional magnetic resonance imaging study we tested whether the predictability of stimuli affects responses in primary visual cortex (V1). The results of this study indicate that visual stimuli evoke smaller responses in V1 when their onset or motion direction can be predicted from the dynamics of surrounding illusory motion. We conclude from this finding that the human brain anticipates forthcoming sensory input that allows predictable visual stimuli to be processed with less neural activation at early stages of cortical processing.

Callosal connections of primary visual cortex predict the spatial spreading of binocular rivalry across the visual hemifields

In binocular rivalry, presentation of different images to the separate eyes leads to conscious perception alternating between the two possible interpretations every few seconds. During perceptual transitions, a stimulus emerging into dominance can spread in a wave-like manner across the visual field. These traveling waves of rivalry dominance have been successfully related to the cortical magnification properties and functional activity of early visual areas, including the primary visual cortex (V1). Curiously however, these traveling waves undergo a delay when passing from one hemifield to another. In the current study, we used diffusion tensor imaging (DTI) to investigate whether the strength of interhemispheric connections between the left and right visual cortex might be related to the delay of traveling waves across hemifields. We measured the delay in traveling wave times (ΔTWT) in 19 participants and repeated this test 6 weeks later to evaluate the reliability of our behavioral measures. We found large interindividual variability but also good test-retest reliability for individual measures of ΔTWT. Using DTI in connection with fiber tractography, we identified parts of the corpus callosum connecting functionally defined visual areas V1-V3. We found that individual differences in ΔTWT was reliably predicted by the diffusion properties of transcallosal fibers connecting left and right V1, but observed no such effect for neighboring transcallosal visual fibers connecting V2 and V3. Our results demonstrate that the anatomical characteristics of topographically specific transcallosal connections predict the individual delay of interhemispheric traveling waves, providing further evidence that V1 is an important site for neural processes underlying binocular rivalry.

Auditory motion direction encoding in auditory cortex and high-level visual cortex

The aim of this functional magnetic resonance imaging (fMRI) study was to identify human brain areas that are sensitive to the direction of auditory motion. Such directional sensitivity was assessed in a hypothesis-free manner by analyzing fMRI response patterns across the entire brain volume using a spherical-searchlight approach. In addition, we assessed directional sensitivity in three predefined brain areas that have been associated with auditory motion perception in previous neuroimaging studies. These were the primary auditory cortex, the planum temporale and the visual motion complex (hMT/V5+). Our whole-brain analysis revealed that the direction of sound-source movement could be decoded from fMRI response patterns in the right auditory cortex and in a high-level visual area located in the right lateral occipital cortex. Our region-of-interest-based analysis showed that the decoding of the direction of auditory motion was most reliable with activation patterns of the left and right planum temporale. Auditory motion direction could not be decoded from activation patterns in hMT/V5+. These findings provide further evidence for the planum temporale playing a central role in supporting auditory motion perception. In addition, our findings suggest a cross-modal transfer of directional information to high-level visual cortex in healthy humans.

Orientation-selective functional magnetic resonance imaging adaptation in primary visual cortex revisited

The processing of orientations is at the core of our visual experience. Orientation selectivity in human visual cortex has been inferred from psychophysical experiments and more recently demonstrated with functional magnetic resonance imaging (fMRI). One method to identify orientation-selective responses is fMRI adaptation, in which two stimuli—either with the same or with different orientations—are presented successively. A region containing orientation-selective neurons should demonstrate an adapted response to the “same orientation” condition in contrast to the “different orientation” condition. So far, human primary visual cortex (V1) showed orientation-selective fMRI adaptation only in experimental designs using prolonged pre-adaptation periods (∼40 s) in combination with top-up stimuli that are thought to maintain the adapted level. This finding has led to the notion that orientation-selective short-term adaptation in V1 (but not V2 or V3) cannot be demonstrated using fMRI. The present study aimed at re-evaluating this question by testing three differently timed adaptation designs. With the use of a more sensitive analysis technique, we show robust orientation-selective fMRI adaptation in V1 evoked by a short-term adaptation design.

Dynamic population coding in primary visual cortex

More than a century ago Ramon y Cajal pioneered the description of neural circuits. Currently, new techniques are being developed to streamline the characterization of entire neural circuits. Even if this 'connectome' approach is successful, it will represent only a static description of neural circuits. Thus, a fundamental question in neuroscience is to understand how information is dynamically represented by neural populations. In this thesis, I studied two main aspects of dynamical population codes. ^ First, I studied how the exposure or adaptation, for a fraction of a second to oriented gratings dynamically changes the population response of primary visual cortex neurons. The effects of adaptation to oriented gratings have been extensively explored in psychophysical and electrophysiological experiments. However, whether rapid adaptation might induce a change in the primary visual cortex's functional connectivity to dynamically impact the population coding accuracy is currently unknown. To address this issue, we performed multi-electrode recordings in primary visual cortex, where adaptation has been previously shown to induce changes in the selectivity and response amplitude of individual neurons. We found that adaptation improves the population coding accuracy. The improvement was more prominent for iso- and orthogonal orientation adaptation, consistent with previously reported psychophysical experiments. We propose that selective decorrelation is a metabolically inexpensive mechanism that the visual system employs to dynamically adapt the neural responses to the statistics of the input stimuli to improve coding efficiency. ^ Second, I investigated how ongoing activity modulates orientation coding in single neurons, neural populations and behavior. Cortical networks are never silent even in the absence of external stimulation. The ongoing activity can account for up to 80% of the metabolic energy consumed by the brain. Thus, a fundamental question is to understand the functional role of ongoing activity and its impact on neural computations. I studied how the orientation coding by individual neurons and cell populations in primary visual cortex depend on the spontaneous activity before stimulus presentation. We hypothesized that since the ongoing activity of nearby neurons is strongly correlated, it would influence the ability of the entire population of orientation-selective cells to process orientation depending on the prestimulus spontaneous state. Our findings demonstrate that ongoing activity dynamically filters incoming stimuli to shape the accuracy of orientation coding by individual neurons and cell populations and this interaction affects behavioral performance. In summary, this thesis is a contribution to the study of how dynamic internal states such as rapid adaptation and ongoing activity modulate the population code accuracy. ^

On nonlinearity in neural encoding models applied to the primary visual cortex

Within the regression framework, we show how different levels of nonlinearity influence the instantaneous firing rate prediction of single neurons. Nonlinearity can be achieved in several ways. In particular, we can enrich the predictor set with basis expansions of the input variables (enlarging the number of inputs) or train a simple but different model for each area of the data domain. Spline-based models are popular within the first category. Kernel smoothing methods fall into the second category. Whereas the first choice is useful for globally characterizing complex functions, the second is very handy for temporal data and is able to include inner-state subject variations. Also, interactions among stimuli are considered. We compare state-of-the-art firing rate prediction methods with some more sophisticated spline-based nonlinear methods: multivariate adaptive regression splines and sparse additive models. We also study the impact of kernel smoothing. Finally, we explore the combination of various local models in an incremental learning procedure. Our goal is to demonstrate that appropriate nonlinearity treatment can greatly improve the results. We test our hypothesis on both synthetic data and real neuronal recordings in cat primary visual cortex, giving a plausible explanation of the results from a biological perspective.

A model of the mammalian retina and the visual cortex. Disorders of vision

A model of the mammalian retina and the behavior of the first layers in the visual cortex is reported. The building blocks are optically programmable logic cells. A model of the retina, similar to the one reported by Dowling (1987) is presented. From the model of the visual cortex obtained, some types of symmetries and asymmetries are possible to be detected

Image characterisation based on the mammalian visual cortex

A proposal for a model of the primary visual cortex is reported. It is structured with the basis of a simple unit cell able to perform fourteen pairs of different boolean functions corresponding to the two possible inputs. As a first step, a model of the retina is presented. Different types of responses, according to the different possibilities of interconnecting the building blocks, have been obtained. These responses constitute the basis for an initial configuration of the mammalian primary visual cortex. Some qualitative functions, as symmetry or size of an optical input, have been obtained. A proposal to extend this model to some higher functions, concludes the paper.

An approach to visual cortex operation: optical neuron model

Several works have been published in the last years concerning the modelling and implementation of the visual cortex operation. Most of them present simple neurons with just two different responses, namely inhibitory and excitatory. Some of the different types of visual cortex cells are simulated in these configurations.

An approach to a model of the visual cortex: disorders of vision

One of the most challenging problems that must be solved by any theoretical model purporting to explain the competence of the human brain for relational tasks is the one related with the analysis and representation of the internal structure in an extended spatial layout of múltiple objects. In this way, some of the problems are related with specific aims as how can we extract and represent spatial relationships among objects, how can we represent the movement of a selected object and so on. The main objective of this paper is the study of some plausible brain structures that can provide answers in these problems. Moreover, in order to achieve a more concrete knowledge, our study will be focused on the response of the retinal layers for optical information processing and how this information can be processed in the first cortex layers. The model to be reported is just a first trial and some major additions are needed to complete the whole vision process.

Photonic processing subsystem based on visual cortex architecture

Optical signal processing in any living being is more complex than the one obtained in artificial systems. Cortex architecture, although only partly known, gives some useful ideas to be employed in communications. To analyze some of these structures is the objective of this paper. One of the main possibilities reported is handling signals in a parallel way. As it is shown, according to the signal characteristics each signal impinging onto a single input may be routed to a different output. At the same time, identical signals, coming to different inputs, may be routed to the same output without internal conflicts. This is due to the change of some of their characteristics in the way out when going through the intermediate levels. The simulation of this architecture is based on simple logic cells. The basis for the proposed architecture is the five layers of the mammalian retina and the first levels of the visual cortex.

Bidirectional, experience-dependent regulation of N-methyl-d-aspartate receptor subunit composition in the rat visual cortex during postnatal development

In the visual cortex, as elsewhere, N-methyl-d-aspartate receptors (NMDARs) play a critical role in triggering long-term, experience-dependent synaptic plasticity. Modifications of NMDAR subunit composition alter receptor function, and could have a large impact on the properties of synaptic plasticity. We have used immunoblot analysis to investigate the effects of age and visual experience on the expression of different NMDAR subunits in synaptoneurosomes prepared from rat visual cortices. NMDARs at birth are comprised of NR2B and NR1 subunits, and, over the first 5 postnatal weeks, there is a progressive inclusion of the NR2A subunit. Dark rearing from birth attenuates the developmental increase in NR2A. Levels of NR2A increase rapidly (in <2 hr) when dark-reared animals are exposed to light, and decrease gradually over the course of 3 to 4 days when animals are deprived of light. These data reveal that NMDAR subunit composition in the visual cortex is remarkably dynamic and bidirectionally regulated by sensory experience. We propose that NMDAR subunit regulation is a mechanism for experience-dependent modulation of synaptic plasticity in the visual cortex, and serves to maintain synaptic strength within an optimal dynamic range.

Excitatory–inhibitory network in the visual cortex: Psychophysical evidence

At early stages in visual processing cells respond to local stimuli with specific features such as orientation and spatial frequency. Although the receptive fields of these cells have been thought to be local and independent, recent physiological and psychophysical evidence has accumulated, indicating that the cells participate in a rich network of local connections. Thus, these local processing units can integrate information over much larger parts of the visual field; the pattern of their response to a stimulus apparently depends on the context presented. To explore the pattern of lateral interactions in human visual cortex under different context conditions we used a novel chain lateral masking detection paradigm, in which human observers performed a detection task in the presence of different length chains of high-contrast-flanked Gabor signals. The results indicated a nonmonotonic relation of the detection threshold with the number of flankers. Remote flankers had a stronger effect on target detection when the space between them was filled with other flankers, indicating that the detection threshold is caused by dynamics of large neuronal populations in the neocortex, with a major interplay between excitation and inhibition. We considered a model of the primary visual cortex as a network consisting of excitatory and inhibitory cell populations, with both short- and long-range interactions. The model exhibited a behavior similar to the experimental results throughout a range of parameters. Experimental and modeling results indicated that long-range connections play an important role in visual perception, possibly mediating the effects of context.

Brain activity in visual cortex predicts individual differences in reading performance

The relationship between brain activity and reading performance was examined to test the hypothesis that dyslexia involves a deficit in a specific visual pathway known as the magnocellular (M) pathway. Functional magnetic resonance imaging was used to measure brain activity in dyslexic and control subjects in conditions designed to preferentially stimulate the M pathway. Dyslexics showed reduced activity compared with controls both in the primary visual cortex and in a secondary cortical visual area (MT+) that is believed to receive a strong M pathway input. Most importantly, significant correlations were found between individual differences in reading rate and brain activity. These results support the hypothesis for an M pathway abnormality in dyslexia and imply a strong relationship between the integrity of the M pathway and reading ability.