CELLULAR FEEDBACK NETWORKS AND THEIR RESILIENCE AGAINST MUTATIONS

Many tissues undergo a steady turnover, where cell divisions are on average balanced with cell deaths. Cell fate decisions such as stem cell (SC) differentiations, proliferations, or differentiated cell (DC) deaths, may be controlled by cell populations through cell-to-cell signaling. Here, we examine a class of mathematical models of turnover in SC lineages to understand engineering design principles of control (feedback) loops, that may operate in such systems. By using ordinary differential equations that describe the co-dynamics of SCs and DCs, we study the effect of different types of mutations that interfere with feedback present within cellular networks. For instance, we find that mutants that do not participate in feedback are less dangerous in the sense that they will not rise from low numbers, whereas mutants that do not respond to feedback signals could rise and replace the wild-type population. Additionally, we asked if different feedback networks can have different degrees of resilience against such mutations. We found that all minimal networks, that is networks consisting of exactly one feedback loop that is sufficient for homeostatic stability of the wild-type population, are equally vulnerable. Mutants with a weakened/eliminated feedback parameter might expand from lower numbers and either enter unlimited growth or reach an equilibrium with an increased number of SCs and DCs. Therefore, from an evolutionary viewpoint, it appears advantageous to combine feedback loops, creating redundant feedback networks. Interestingly, from an engineering prospective, not all such redundant systems are equally resilient. For some of them, any mutation that weakens/eliminates one of the loops will lead to a population growth of SCs. For others, the population of SCs can actually shrink as a result of “cutting” one of the loops, thus slowing down further unwanted transformations.

Layer 6A pyramidal cells subtypes form synaptic microcircuits with distinct functional and structural properties

Neocortical layer 6 plays a crucial role in sensorimotor coordination and integration through functionally segregated circuits linking intracortical and subcortical areas. However, because of the high neuronal heterogeneity and sparse intralaminar connectivity data on the cell-type specific synaptic microcircuits in layer 6 remain few and far between. To address this issue, whole-cell recordings combined with morphological reconstructions have been used to identify morphoelectric types of layer 6A pyramidal cells (PCs) in rat barrel cortex. Cortico-thalamic (CT), corticocortical (CC) and cortico-claustral (CCla) pyramidal cells have been distinguished based on to their distinct dendritic and axonal morphologies as well as their different electrophysiological properties. Here we demonstrate that these three types of layer 6A pyramidal cells innervate neighboring excitatory neurons with distinct synaptic properties: CT PCs establish weak facilitating synapses to other L6A PCs; CC PCs form synapses of moderate efficacy; while synapses made by putative CCla PCs display the highest release probability and a marked short-term depression. Furthermore, for excitatory-inhibitory synaptic connections in layer 6 we were able to show that both the presynaptic PC type and the postsynaptic interneuron type govern the dynamic properties of the of the respective synaptic connections. We have identified a functional division of local layer 6A excitatory microcircuits which may be responsible of the differential temporal engagement of layer 6 feed-forward and feedback networks. Our results provides a basis for further investigations on the long-range cortico-cortical, cortico-thalamic and cortico-claustral pathways.

Multiple concurrent feedforward and feedback streams in a cortical hierarchy

Visual stimuli evoke fast-evolving activity patterns that are distributed across multiple cortical areas. These areas are hierarchically structured, as indicated by their anatomical projections, but how large-scale feedforward and feedback streams are functionally organized in this system remains an important missing clue to understanding cortical processing. By analyzing visual evoked responses in laminar recordings from six cortical areas in awake mice, we established the simultaneous presence of two feedforward and two feedback networks, each with a distinct laminar functional connectivity profile, frequency spectrum, temporal dynamics and functional hierarchy. We furthermore identified a distinct role for each of these four processing streams, by leveraging stimulus contrast effects and analyzing receptive field convergency along functional interactions. Our results support a dynamic dual counterstream view of hierarchical processing and provide new insight into how separate functional streams can simultaneously and dynamically operate in visual cortex.

A Matrix Approach for Analyzing Signal Flow Graph

Mason’s gain formula can grow factorially because of growth in the enumeration of paths in a directed graph. Each of the (n − 2)! permutation of the intermediate vertices includes a path between input and output nodes. This paper presents a novel method for analyzing the loop gain of a signal flow graph based on the transform matrix approach. This approach only requires matrix determinant operations to determine the transfer function with complexity O(n3) in the worst case, therefore rendering it more efficient than Mason’s gain formula. We derive the transfer function of the signal flow graph to the ratio of different cofactor matrices of the augmented matrix. By using the cofactor expansion, we then obtain a correspondence between the topological operation of deleting a vertex from a signal flow graph and the algebraic operation of eliminating a variable from the set of equations. A set of loops sharing the same backward edges, referred to as a loop group, is used to simplify the loop enumeration. Two examples of feedback networks demonstrate the intuitive approach to obtain the transfer function for both numerical and computer-aided symbolic analysis, which yields the same results as Mason’s gain formula. The transfer matrix offers an excellent physical insight, because it enables visualization of the signal flow.

Multistage feedback driven compartmental dynamics of hematopoiesis

Human hematopoiesis is surprisingly resilient to disruptions, providing suitable responses to severe bleeding, long lasting immune activation, and even bone marrow transplants. Still, many blood disorders exist which push the system past its natural plasticity, resulting in abnormalities in the circulating blood. While proper treatment of such diseases can benefit from understanding the underlying cell dynamics, these are non-trivial to predict due to the hematopoietic system’s hierarchical nature and complex feedback networks. To characterize the dynamics following different types of perturbations we investigate a model representing hematopoiesis as a sequence of compartments covering all maturation stages – from stem to mature cells – where feedback regulates cell production to ongoing necessities. We find that a stable response to perturbations requires the simultaneous adaptation of cell differentiation and self-renewal rates, and show that under conditions of continuous disruption – as found in chronic hemolytic states – compartment cell numbers evolve to novel stable states.

Light-mediated strong coupling between a mechanical oscillator and atomic spins 1 meter apart

Engineering strong interactions between quantum systems is essential for many phenomena of quantum physics and technology. Typically, strong coupling relies on short-range forces or on placing the systems in high-quality electromagnetic resonators, which restricts the range of the coupling to small distances. We used a free-space laser beam to strongly couple a collective atomic spin and a micromechanical membrane over a distance of 1 meter in a room-temperature environment. The coupling is highly tunable and allows the observation of normal-mode splitting, coherent energy exchange oscillations, two-mode thermal noise squeezing, and dissipative coupling. Our approach to engineering coherent long-distance interactions with light makes it possible to couple very different systems in a modular way, opening up a range of opportunities for quantum control and coherent feedback networks.

Anticipatory responses along motion trajectories in awake monkey area V1

ABSTRACTWhat are the neural mechanisms underlying motion integration of translating objects? Visual motion integration is generally conceived of as a feedforward, hierarchical, information processing. However, feedforward models fail to account for many contextual effects revealed using natural moving stimuli. In particular, a translating object evokes a sequence of transient feedforward responses in the primary visual cortex but also propagations of activity through horizontal and feedback pathways. We investigated how these pathways shape the representation of a translating bar in monkey V1. We show that, for long trajectories, spiking activity builds-up hundreds of milliseconds before the bar enters the neurons’ receptive fields. Using VSDI and LFP recordings guided by a phenomenological model of propagation dynamics, we demonstrate that this anticipatory response arises from the interplay between horizontal and feedback networks driving V1 neurons well ahead of their feedforward inputs. This mechanism could subtend several perceptual contextual effects observed with translating objects.HighlightsOur hypothesis is that lateral propagation of activity in V1 contributes to the integration of translating stimuliConsistent with this hypothesis, we find that a translating bar induces anticipatory spiking activity in V1 neurons.A V1 model describes how this anticipation can arise from inter and intra-cortical lateral propagation of activity.The dynamic of VSDi and LFP signals in V1 is consistent with the predictions made by the model.The intra-cortical origin is further confirmed by the fact that a bar moving from the ipsilateral hemifield does not evoke anticipation.Horizontal and feedback input are not only modulatory but can also drive spiking responses in specific contexts.