Poster Session
- 1) Stable and efficient whole area scale simulations of visual cortical circuit dynamics (Constantin Lührmann, Göttingen University, CIDBN, Germany)
abstract…
The visual cortex contains neurons exhibiting an orientation preference. In primates and carnivores, the orientation preference changes smoothly in space except for singularities, called pinwheels, where all orientation preferences meet. The long-range interaction model describes a symmetry-based, process of self-organizing for the neuronal circuitry underlying orientation preference and its spatial organization in the visual cortex. It can be cast in the form of a neural field equation with a symmetry breaking instability and a nonlinearity that takes local and non-local interactions within cortex into account. Solutions of the model reproduce a single common design of orientation preference maps across different species and quantitatively accurately predict statistical features such as the pinwheel density. In order to study learning dynamics or optogenetic perturbations, simulations are required. Numerically, however, such simulations on regular grids are prone to arte-factual instabilities. I am developing a random grid by applying the finite element method to the solution of neural field equations that is expected to solve these issues and approach perturbation and optimization questions with a much more powerful toolbox.
- 2) Sparse chaos and localization in the dynamics of neuronal circuits (Mohammadreza Soltanipour, Göttingen University, CIDBN, Germany)
abstract…
Nerve impulses, the currency of information flows in the brain, are generated by an instability of the neuronal membrane potential dynamics. Neuronal circuits exhibit collective chaos that appears essential for learning, memory, sensory processing and motor control. What controls the nature and intensity of collective chaos in neuronal circuits, however, is not well understood. Here we use computational ergodic theory to demonstrate that basic features of nerve impulse generation profoundly affect collective chaos in neuronal circuits. Numerically exact calculations of Lyapunov Spectra, Kolmogorov-Sinai-entropy, and upper and lower bounds on attractor dimension show that changes in nerve impulse generation in individual neurons only moderately modify rate of information encoding but qualitatively transform phase space structure, reducing the number of unstable manifolds, Kolmogorov-Sinai-entropy, and attractor dimension by orders of magnitude. Beyond a critical point, marked by a localization transition of the leading covariant Lyapunov vector, the network exhibits sparse chaos: extended periods of near stable dynamics interrupted by short bursts of intense chaos. Analysis of large networks with more realistic structure indicate the generality of these findings. In cortical circuits biophysics appears tuned to this regime of episodic chaos. Our results demonstrate a tight link between fundamental features of single neuron biophysics and the collective dynamics of cortical circuits and suggest that the machinery of nerve impulse generation is tailored to enhance circuit controllability and information flow.
- 3) Extensive dimensionality of neural circuit manifolds associated with a salt-and-pepper organization of cortical stimulus preferences (Michael Sternbach, Göttingen University, CIDBN, Germany)
abstract…
In rodent sensory cortex, cortical circuits include a dense blanket of inhibition (Bopp et al. 2014). If cortical principal cells acquire their stimulus preferences by selecting afferent connections through Hebbian mechanisms. Then strong feedback inhibition can force neurons to adopt maximally dissimilar selectivities (Rubner&Schulten1990). Here we introduce and examine a set of idealized models to investigate manifolds of stable network configurations in inhibition dominated circuits.
Biological neural circuits are expected to converge to one of many stable network configurations. For the form vision core circuit of primate/carnivore V1 prior work indicates that stable network configurations form high-dimensional continua (Wolf 2005, Kaschube et al. 2010). Similar results for network configurations in rodents V1, called salt-and-pepper organizations (SaP), are currently not available. We utilize techniques from the study of spin liquid states (Chalker2015) to construct and examine mathematically tractable models with SaP optimal states.
We demonstrate that these models can exhibit ground state manifolds with extensive dimensionality for uniform, range-dependent and selectivity-dependent neuronal connectivity. This result is consistent with the general expectation that there are a very high number of equivalent SaP configurations. Disordered SaP states result even for dense and uniform connectivity patterns and do not require any structural source of disorder.
These studies expand the toolbox for analyzing the multiplicity of stable cortical circuit configurations. Our results suggest that the evolutionary transition from a rodent ancestral circuit configurations of V1 to a
primate/carnivore V1 architecture was accompanied by a radical reduction of the dimensionality of the cortical circuit state manifold.
- 4) Homeostasis of Mitochondrial Ca2+ Stores Is Critical for Signal Amplification in Drosophila melanogaster Olfactory Sensory Neurons (Eric Wiesel, Sabine Kaltofen, Bill S. Hansson, and Dieter Wicher, MPI for Chemical Ecology, Jena, Germany)
abstract…
Insects detect volatile chemosignals with olfactory sensory neurons (OSNs) that express olfactory receptors. Among them, the most sensitive receptors are the odorant receptors (ORs), which form cation channels passing Ca2+. OSNs expressing different groups of ORs show varying optimal odor concentration ranges according to environmental needs. Certain types of OSNs, usually attuned to high odor concentrations, allow for the detection of even low signals through the process of sensitization. By increasing the sensitivity of OSNs upon repetitive subthreshold odor stimulation, Drosophila melanogaster can detect even faint and turbulent odor traces during flight. While the influx of extracellular Ca2+ has been previously shown to be a cue for sensitization, our study investigates the importance of intracellular Ca2+ management. Using an open antenna preparation that allows observation and pharmacological manipulation of OSNs, we performed Ca2+ imaging to determine the role of Ca2+ storage in mitochondria. By disturbing the mitochondrial resting potential and induction of the mitochondrial permeability transition pore (mPTP), we show that effective storage of Ca2+ in the mitochondria is vital for sensitization to occur, and release of Ca2+ from the mitochondria to the cytoplasm promptly abolishes sensitization. Our study shows the importance of cellular Ca2+ management for sensitization in an effort to better understand the underlying mechanics of OSN modulation.
- 5) Does a developmental speed advantage favour primate and carnivore V1 circuit design? (Zoe Stawyskyj, Fred Wolf, Göttingen University, CIDBN, MPI for Dynamics and Self-Organization, Germany)
abstract…
In the V1 networks of orientation selective neurons it was discovered, and recently extended in primates (Ho 2021), that there is a common design with numerous quantitative invariances (Kaschube 2010). There is an abstract theory of cortical circuit self-organisation that is able to predict all these invariances (Wolf 2005, Kaschube 2010), but it is not well understood what functional advantage favours this architecture. Understanding this functional advantage is particularly relevant from an evolutionary perspective because in primates and carnivores this architecture presumably evolved independently, potentially by convergent evolution (Schmidt 2021). Understanding this necessitates that we identify at least one functional advantage.
This abstract framework can generate the common design while allowing for a larger model space in which also deviant architectures may emerge (Wolf 2005). We thus utilise this framework, within the larger model space, to ask a simple question: what is the kind of self-organising process for the circuit that converges the fastest? Obviously, this would go with a developmental speed advantage as then the circuit can become stable quickly.
We considered three times of reduced complexity models within this abstract framework and investigate this principle of fast convergence. For all these cases this principle puts the system exactly at a critical point where the maximum number of solutions are stable and covering as much of the solution space as possible having, in some cases, a larger solution set than previously hypothesised. We confirm the equivalence of our analytical method of optimisation, calculating the slowest gradient descent, and the concept of minimal turnover and fastest convergence using numerical methods.
This is, for the first time, a simple biological advantage that goes together with the common design. Further these results make it interesting to study in further depth how the convergence speed could be an evolutionary selection principle for and against certain designs.
References
Ho, C.L.A et al., Current Biology 31, 733–741 (2021)
Kaschube M., Schnabel M., Löwel S., Coppola D.M., White L.E., Wolf F. Universality in the evolution of orientation columns in the visual cortex Science, 330 (2010)
Schmidt, K.E. and Wolf F., Current Opinion Neurobiol. 71, 110-118 (2021)
Wolf, F. Symmetry, multistability and long-range interactions in brain development PRL, 95 (2005)
- 6) A two-way luminance gain control in the fly brain ensures luminance invariance in dynamic vision (Madhura Ketkar, University of Mainz, Germany)
abstract…
For visual perception to be unaffected by viewing conditions, animals must adapt their sensitivity to changing visual statistics, such as mean illumination. Consistently, photoreceptors in many species control their luminance gain and encode relative changes in luminance, termed contrast. However, this early gain control is insufficient for luminance-invariant contrast estimation, especially in dynamic conditions. Sudden transitions to dim or bright environment would lead to an erroneous, reduced or enhanced perception of contrasts, thus imposing a two-way challenge on contrast estimation. Yet, visual behaviors are luminance invariant, and we aim to understand how the brains achieve such invariance.
In fruit flies, a distinct visual pathway preserves luminance information past photoreceptors and enhances contrast estimation in sudden dim light. Here, we combine fly behavior, physiology and computational modelling approaches to show that the pathway implements a generalized gain correction at both fast and slow timescales to tackle the two-way contrast coding deficits. When blocking the output of the luminance-sensitive interneurons, the flies underestimate contrasts in a low luminance range and overestimate contrasts in high luminance range. Adding to this two-way deficit across absolute luminance, the flies further under- and overestimate contrasts in sudden dim and sudden bright light, respectively. We formulated an algorithmic model that captures the data with high accuracy and explains how the gain correction is implemented downstream of a single neuron type in these widely differing scenarios. In summary, our work demonstrates how post-receptor gain correction is key to perceptually relevant vision. Since visual systems of all behaving animals face similar challenges, the corrective gain control might be a universal strategy of visual systems.
- 7) Tsallis Entropy-based Statistical Study of Human Emotions through EEG Signals (Pragati Patel, Pondicherry University, Puducherry, India)
abstract…
Since emotions have such a significant part in people's everyday lives, the necessity and relevance of an automated emotion recognition system has risen with the growing aspects of brain-computer interface (BCI) applications and e-healthcare systems. Non-physiological signals/datasets such as texts, audio, or facial expression could be used to identify and classify different emotions. However, our present work focuses on the statistical study of "inner" emotions from physiological data like an electroencephalogram (EEG). Human emotion identification based on the EEG dataset is a challenging yet promising field of research. Furthermore, information-theoretical approaches have appeared as a potentially beneficial means to gauge variations in the EEG datasets.
We aimed to examine the statistical characteristics of one such information-theoretical approach- Tsallis entropy, to gauge the positive, neutral and negative emotion variations using the SEED dataset. Statistical features like mean value and the variance of Tsallis entropy provide excellent specificity to different emotions. Contrary to negative emotion, positive emotion has a decreased entropy mean and a greater entropy variance. Different channels from the anterior part of the brain are considered in the study. The result shows that the frontal and temporal lobes could be prioritized over other electrodes to study human emotion. FT7 exhibits contrast variation in the entropy mean and variance of different emotions. Our study of non-extensive Tsallis entropy and its statistical characteristics adds to a new quantitative EEG method for evaluating different brain states, which could build better real-time EEG-based emotion identification systems when further combined with a classifier.
- 8) Dynamic Gain Analysis of Axon Initial Segment Function in High-Bandwidth Encoding
(Neil Wesch, Göttingen University, CIDBN, Germany)
abstract…
Cortical neutrons generate action potentials (APs) in the axon initial segment (AIS), a specialized compartment with high concentration of voltage-dependent ion channels organized into a nanoscale clustering pattern. This AIS molecular architecture is a vertebrate-specific innovation coinciding with the evolution of large brains. Spike initiation in the AIS occurs with sub-millisecond precision, but description of the exact mechanism remains lacking.
Herein we present the results from in vitro manipulation of Na+V channel clustering in the AIS. Mutation of a cytoskeletal anchoring protein (βIV-spectrin) maintains the nanoscale structure while decreasing the overall density. This cellular-level property strongly affects population-level response.
We quantify the effect of AP timing precision in the AIS on high-bandwidth population encoding using dynamic gain. Dynamic gain is a spectrally resolved measure of a neuronal population's encoding capacity; effectively quantifying the input/output response.
Mathematical decomposition of dynamic gain provides a direct connection between system features and cellular properties. The sub-threshold dynamics are dominated by attenuation due to somato-dendritic filtering. Conversely, peri-threshold axonal dynamics show strong signal boosting.
This paradigm of experimental network-level characterization and theoretical modelling of cell-level properties is a powerful way to probe the structure and function of ion channels in the AIS.
- 9) Recapitulating the evolutionary transformation of visual cortex architecture in a tabletop experiment (Julian Vogel, Friedrich Schwarz, Göttingen University, CIDBN, Germany)
abstract…
In the visual cortex of primates and carnivores orientation selective neurons are organized into functional domains that are arranged around so called pinwheels. This structure most likely emerged from a prior rodent-like salt-and-pepper layout. We designed a synthetic biology approach in which we implemented evolutionary transition scenarios by switching between different wiring schemes for thalamic afferents.
We used neuronal interface technology to connect a computational model of the retino-thalamic pathway to an in-vitro model of cortical input layer 4 (L4). The latter contained channelrhodopsin expressing principal neurons, either as a primary culture of cortical neurons or an acute brain slice. The two stages were connected via optogenetic holographic stimulation emulating thalamo-cortical synaptic input to L4. We recorded neural activity either with a multielectrode array or by calcium imaging.
In the feed-forward model orientation selection in L4 is a result of convergent thalamic input. We implemented such a feed-forward scheme in our system with variable size of orientation domains. We then explored the consequences of scaling the size of orientation domains down to the size of single neurons. Furthermore, we implemented a random wiring scheme.
We found that the fraction of orientation selective neurons only weakly decreased with shrinking domain size and even for random thalamo-cortical connections a considerable level of orientation selectivity was maintained. In this case the arrangement of orientation selective cells resembled a sparse salt-and-pepper layout. Our results indicate that evolutionary scaling of orientation domain sizes can induce a self-organized transition to and from a salt-and-pepper layout.
To test these possible effects not only during acute but also after prolonged (chronic) stimulation, we additionally developed a system providing arbitrary spatiotemporally structured optical input to cultured neurons inside an incubator for months. Wavelength and light power density allow robust stimulation of neurons photosensitized via channelrhodopsin expression. In combination with an incubator-compatible multielectrode array platform (MEA2100-Mini, MultiChannel Systems), we can routinely perform simultaneous optogenetic stimulation and electrophysiological extracellular recordings over many hours and days. Custom-made protocols allow us to register stimulus patterns and recordings with microsecond precision.