1,241 research outputs found
Reorganization of columnar architecture in the growing visual cortex
Many cortical areas increase in size considerably during postnatal
development, progressively displacing neuronal cell bodies from each other. At
present, little is known about how cortical growth affects the development of
neuronal circuits. Here, in acute and chronic experiments, we study the layout
of ocular dominance (OD) columns in cat primary visual cortex (V1) during a
period of substantial postnatal growth. We find that despite a considerable
size increase of V1, the spacing between columns is largely preserved. In
contrast, their spatial arrangement changes systematically over this period.
While in young animals columns are more band-like, layouts become more
isotropic in mature animals. We propose a novel mechanism of growth-induced
reorganization that is based on the `zigzag instability', a dynamical
instability observed in several inanimate pattern forming systems. We argue
that this mechanism is inherent to a wide class of models for the
activity-dependent formation of OD columns. Analyzing one member of this class,
the Elastic Network model, we show that this mechanism can account for the
preservation of column spacing and the specific mode of reorganization of OD
columns that we observe. We conclude that neurons systematically shift their
selectivities during normal development and that this reorganization is induced
by the cortical expansion during growth. Our work suggests that cortical
circuits remain plastic for an extended period in development in order to
facilitate the modification of neuronal circuits to adjust for cortical growth.Comment: 8+13 pages, 4+8 figures, paper + supplementary materia
Developmental Changes in GABAergic Mechanisms in Human Visual Cortex Across the Lifespan
Functional maturation of visual cortex is linked with dynamic changes in synaptic expression of GABAergic mechanisms. These include setting the excitationâinhibition balance required for experience-dependent plasticity, as well as, intracortical inhibition underlying development and aging of receptive field properties. Animal studies have shown that there is developmental regulation of GABAergic mechanisms in visual cortex. In this study, we show for the first time how these mechanisms develop in the human visual cortex across the lifespan. We used Western blot analysis of postmortem tissue from human primary visual cortex (n = 30, range: 20 days to 80 years) to quantify expression of eight pre- and post-synaptic GABAergic markers. We quantified the inhibitory modulating cannabinoid receptor (CB1), GABA vesicular transporter (VGAT), GABA synthesizing enzymes (GAD65/GAD67), GABAA receptor anchoring protein (Gephyrin), and GABAA receptor subunits (GABAAα1, GABAAα2, GABAAα3). We found a complex pattern of different developmental trajectories, many of which were prolonged and continued well into the teen, young adult, and even older adult years. These included a monotonic increase or decrease (GABAAα1, GABAAα2), a biphasic increase then decrease (GAD65, Gephyrin), or multiple increases and decreases (VGAT, CB1) across the lifespan. Comparing the balances between the pre- and post-synaptic markers we found three main transition stages (early childhood, early teen years, aging) when there were rapid switches in the composition of the GABAergic signaling system, indicating that functioning of the GABAergic system must change as the visual cortex develops and ages. Furthermore, these results provide key information for translating therapies developed in animal models into effective treatments for amblyopia in humans
Imaging plasticity and structure of cortical maps in cat and mouse visual cortex
The study reported in the first part of this thesis utilized optical imaging of intrinsic signals to
visualize changes in orientation maps in cat visual cortex induced by pairing a visual stimulus
with an intracortical electrical stimulation. We found that the direction of plasticity within
orientation maps depends critically on the relative timing between visual and electrical
stimulation on a millisecond time scale: a shift in orientation preference towards the paired
orientation was observed if the cortex was first visually and then electrically stimulated. In
contrast, the cortical response to the paired orientation was diminished if the electrical preceded
the visual cortical stimulation. Spike-time-dependent plasticity has been observed in single cell
studies; however, our results demonstrate an analogous effect at the systems level in the live
animal. Thus, timing-dependent plasticity needs to be incorporated into our conception of cortical
map development.
While the pairing paradigm induced pronounced shifts in orientation preference, the general setup
of the orientation preference map remained unaltered. In order to unravel potential factors
contributing to this overall stability, we determined the distribution of plasticity across the cortical
surface. We found that pinwheel centers, points were domains of all orientation meet, exhibited
less plasticity than other regions of the orientation map. The resistance of pinwheel centers to
changes in orientation preference may support maintenance of the general structure of the
orientation map.
The study that forms the second part employs optical imaging to visualize the retinotopy in mouse
visual cortex. We were able to resolve the pattern of retinotopic activity with high precision and
reliability in the primary visual cortex (area 17). Functional imaging of the position, size and
shape of area 17 corresponded exactly to the location of this area in stained histological sections.
The imaged maps were also confirmed with electrophysiological recordings. The retinotopic
structure of area 17 showed very low inter-animal variability, thus allowing averaging maps
across animals and therefore statistical analysis. These averaged maps greatly facilitated the
identification of at least four extrastriate visual areas. In addition, we detected decreases in the
intrinsic signal below baseline with a shape and location reminiscent of lateral inhibition. This
decrease of the intrinsic signal was shown to be correlated with a decrease in neuronal firing rate
below baseline.
Both studies were facilitated by the development of a signal analysis technique (part III), which
improves the quality of optical imaging data. Intrinsic signal fluctuations originating from blood
vessels were minimized based on their correlation with the actual superficial blood vessel pattern.
These fluctuation components were then extracted from images obtained during sensory stimulation. This method increases the reproducibility of functional maps from cat, rat, and mouse
visual cortex significantly and might also be applied to high resolution imaging using voltage
sensitve dyes or functional magnetic resonance
Coverage, Continuity and Visual Cortical Architecture
The primary visual cortex of many mammals contains a continuous
representation of visual space, with a roughly repetitive aperiodic map of
orientation preferences superimposed. It was recently found that orientation
preference maps (OPMs) obey statistical laws which are apparently invariant
among species widely separated in eutherian evolution. Here, we examine whether
one of the most prominent models for the optimization of cortical maps, the
elastic net (EN) model, can reproduce this common design. The EN model
generates representations which optimally trade of stimulus space coverage and
map continuity. While this model has been used in numerous studies, no
analytical results about the precise layout of the predicted OPMs have been
obtained so far. We present a mathematical approach to analytically calculate
the cortical representations predicted by the EN model for the joint mapping of
stimulus position and orientation. We find that in all previously studied
regimes, predicted OPM layouts are perfectly periodic. An unbiased search
through the EN parameter space identifies a novel regime of aperiodic OPMs with
pinwheel densities lower than found in experiments. In an extreme limit,
aperiodic OPMs quantitatively resembling experimental observations emerge.
Stabilization of these layouts results from strong nonlocal interactions rather
than from a coverage-continuity-compromise. Our results demonstrate that
optimization models for stimulus representations dominated by nonlocal
suppressive interactions are in principle capable of correctly predicting the
common OPM design. They question that visual cortical feature representations
can be explained by a coverage-continuity-compromise.Comment: 100 pages, including an Appendix, 21 + 7 figure
Fractals in the Nervous System: conceptual Implications for Theoretical Neuroscience
This essay is presented with two principal objectives in mind: first, to
document the prevalence of fractals at all levels of the nervous system, giving
credence to the notion of their functional relevance; and second, to draw
attention to the as yet still unresolved issues of the detailed relationships
among power law scaling, self-similarity, and self-organized criticality. As
regards criticality, I will document that it has become a pivotal reference
point in Neurodynamics. Furthermore, I will emphasize the not yet fully
appreciated significance of allometric control processes. For dynamic fractals,
I will assemble reasons for attributing to them the capacity to adapt task
execution to contextual changes across a range of scales. The final Section
consists of general reflections on the implications of the reviewed data, and
identifies what appear to be issues of fundamental importance for future
research in the rapidly evolving topic of this review
Genetic determination and layout rules of visual cortical architecture
The functional architecture of the primary visual cortex is set up by neurons that preferentially respond to visual stimuli with contours of a specific orientation in visual space. In primates and placental carnivores, orientation preference is arranged into continuous and roughly repetitive (iso-) orientation domains. Exceptions are pinwheels that are surrounded by all orientation preferences. The configuration of pinwheels adheres to quantitative species-invariant statistics, the common design. This common design most likely evolved independently at least twice in the course of the past 65 million years, which might indicate a functionally advantageous trait. The possible acquisition of environment-dependent functional traits by genes, the Baldwin effect, makes it conceivable that visual cortical architecture is partially or redundantly encoded by genetic information. In this conception, genetic mechanisms support the emergence of visual cortical architecture or even establish it under unfavorable environments. In this dissertation, I examine the capability of genetic mechanisms for encoding visual cortical architecture and mathematically dissect the pinwheel configuration under measurement noise as well as in different geometries. First, I theoretically explore possible roles of genetic mechanisms in visual cortical development that were previously excluded from theoretical research, mostly because the information capacity of the genome appeared too small to contain a blueprint for wiring up the cortex. For the first time, I provide a biologically plausible scheme for quantitatively encoding functional visual cortical architecture by genetic information that circumvents the alleged information bottleneck. Key ingredients for this mechanism are active transport and trans-neuronal signaling as well as joined dynamics of morphogens and connectome. This theory provides predictions for experimental tests and thus may help to clarify the relative importance of genes and environments on complex human traits. Second, I disentangle the link between orientation domain ensembles and the species-invariant pinwheel statistics of the common design. This examination highlights informative measures of pinwheel configurations for model benchmarking. Third, I mathematically investigate the susceptibility of the pinwheel configuration to measurement noise. The results give rise to an extrapolation method of pinwheel densities to the zero noise limit and provide an approximated analytical expression for confidence regions of pinwheel centers. Thus, the work facilitates high-precision measurements and enhances benchmarking for devising more accurate models of visual cortical development. Finally, I shed light on genuine three-dimensional properties of functional visual cortical architectures. I devise maximum entropy models of three-dimensional functional visual cortical architectures in different geometries. This theory enables the examination of possible evolutionary transitions between different functional architectures for which intermediate organizations might still exist
Emergence of Functional Specificity in Balanced Networks with Synaptic Plasticity
In rodent visual cortex, synaptic connections between orientation-selective neurons are unspecific at the time of eye opening, and become to some degree functionally specific only later during development. An explanation for this two-stage process was proposed in terms of Hebbian plasticity based on visual experience that would eventually enhance connections between neurons with similar response features. For this to work, however, two conditions must be satisfied: First, orientation selective neuronal responses must exist before specific recurrent synaptic connections can be established. Second, Hebbian learning must be compatible with the recurrent network dynamics contributing to orientation selectivity, and the resulting specific connectivity must remain stable for unspecific background activity. Previous studies have mainly focused on very simple models, where the receptive fields of neurons were essentially determined by feedforward mechanisms, and where the recurrent network was small, lacking the complex recurrent dynamics of large-scale networks of excitatory and inhibitory neurons. Here we studied the emergence of functionally specific connectivity in large-scale recurrent networks with synaptic plasticity. Our results show that balanced random networks, which already exhibit highly selective responses at eye opening, can develop feature-specific connectivity if appropriate rules of synaptic plasticity are invoked within and between excitatory and inhibitory populations. If these conditions are met, the initial orientation selectivity guides the process of Hebbian learning and, as a result, functionally specific and a surplus of bidirectional connections emerge. Our results thus demonstrate the cooperation of synaptic plasticity and recurrent dynamics in large-scale functional networks with realistic receptive fields, highlight the role of inhibition as a critical element in this process, and paves the road for further computational studies of sensory processing in neocortical network models equipped with synaptic plasticity
Correlated Activity and Corticothalamic Cell Function in the Early Mouse Visual System
Vision has long been the model for understanding cortical function. Great progress has been made in understanding the transformations that occur within some primary visual cortex (V1) layers, like the emergence of orientation selectivity in layer 4. Less is known about other V1 circuit elements, like the shaping of V1 input via corticothalamic projections, or the population structure of the cortico-cortical output in layer 2/3. Here, we use the mouse early visual system to investigate the structure and function of circuit elements in V1. We use two approaches: comparative physiology and optogenetics. We measured the structure of pairwise correlations in the output layer 2/3 using extracellular recordings. We find that despite a lack of organization in mouse V1 seen in other species, the specificity of connections preserves a correlation structure on multiple timescales. To investigate the role of corticogeniculate projections, we utilize a transgenic mouse line to specifically and reversibly manipulate these projections with millisecond precision. We find that activity of these cells results a mix of inhibition and excitation in the thalamus, is not spatiotemporally specific, and can affect correlated activity. Finally, we classify mouse thalamic cells according to stimuli used for cell classification in primates and cats, finding some, but not complete, homology to the processing streams of primate thalamus and further highlighting fundamentals of mammalian visual system organization
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