Manipulating neural dynamics to tune motion detection

Neurons integrate excitatory and inhibitory signals to produce their outputs, but the role of input timing in this integration remains poorly understood. Motion detection is a paradigmatic example of this integration, since theories of motion detection rely on different delays in visual signals. These delays allow circuits to compare scenes at different times to calculate the direction and speed of motion. It remains untested how response dynamics of individual cell types drive motion detection and velocity sensitivity. Here, we sped up or slowed down specific neuron types in Drosophila's motion detection circuit by manipulating ion channel expression. Altering the dynamics of individual neurons upstream of motion detectors changed their integrating properties and increased their sensitivity to fast or slow visual motion, exposing distinct roles for dynamics in tuning directional signals. A circuit model constrained by data and anatomy reproduced the observed tuning changes. Together, these results reveal how excitatory and inhibitory dynamics jointly tune a canonical circuit computation.

The Role of Hub Neurons in Modulating Cortical Dynamics

Many neurodegenerative diseases are associated with the death of specific neuron types in particular brain regions. What makes the death of specific neuron types particularly harmful for the integrity and dynamics of the respective network is not well understood. To start addressing this question we used the most up-to-date biologically realistic dense neocortical microcircuit (NMC) of the rodent, which has reconstructed a volume of 0.3 mm3 and containing 31,000 neurons, ∼37 million synapses, and 55 morphological cell types arranged in six cortical layers. Using modern network science tools, we identified hub neurons in the NMC, that are connected synaptically to a large number of their neighbors and systematically examined the impact of abolishing these cells. In general, the structural integrity of the network is robust to cells’ attack; yet, attacking hub neurons strongly impacted the small-world topology of the network, whereas similar attacks on random neurons have a negligible effect. Such hub-specific attacks are also impactful on the network dynamics, both when the network is at its spontaneous synchronous state and when it was presented with synchronized thalamo-cortical visual-like input. We found that attacking layer 5 hub neurons is most harmful to the structural and functional integrity of the NMC. The significance of our results for understanding the role of specific neuron types and cortical layers for disease manifestation is discussed.

Quantification of neuron types in the rodent hippocampal formation by data mining and numerical optimization

Quantifying the population sizes of distinct neuron types in different anatomical regions is an essential step towards establishing a brain cell census. Although estimates exist for the total neuronal populations in different species, the number and definition of each specific neuron type are still intensively investigated. Hippocampome.org is an open-source knowledge base with morphological, physiological, and molecular information for 122 neuron types in the rodent hippocampal formation. While such framework identifies all known neuron types in this system, their relative abundances remain largely unknown. This work quantitatively estimates the counts of all Hippocampome.org neuron types by literature mining and numerical optimization. We report the number of neurons in each type identified by main neurotransmitter (glutamate or GABA) and axonal-dendritic patterns throughout 26 subregions and layers of the dentate gyrus, Ammons horn, subiculum, and entorhinal cortex. We produce by sensitivity analysis reliable numerical ranges for each type and summarize the amounts across broad neuronal families defined by biomarkers expression and firing dynamics. Study of density distributions indicates that the number of dendritic-targeting interneurons, but not of other neuronal classes, is independent of anatomical volumes. All extracted values, experimental evidence, and related software code are released on Hippocampome.org.

The role of hub neurons in modulating cortical dynamics

Many neurodegenerative diseases are associated with the death of specific neuron types in particular brain regions. What makes the death of specific neuron types particularly harmful for the integrity and dynamics of the respective network is not well understood. To start addressing this question we used the most up-to-date biologically-realistic dense neocortical microcircuit (NMC) of rodent, which has reconstructed a volume of 0.3 mm3 and containing 31,000 neurons, 36 million synapses, and 55 morphological cell types arranged in 6 cortical layers. Using modern network science tools, we identified ״hub-neurons״ in the NMC, that are connected synaptically to a large number of their neighbors and systematically examined the impact of abolishing these cells. In general, the structural integrity of the network is robust to cellsֿ' attack; yet, attacking hub neurons strongly impacted the ״small worldness״ topology of the network, whereas similar attacks on random neurons have a negligible effect. Such hub-specific attacks are also impactful on the network dynamics, both when the network is at its spontaneous synchronous state and when it was presented with synchronized thalamo-cortical visual-like input. We found that attacking layer 5 hub neurons are most harmful to the structural and functional integrity of the NMC. The significance of our results for understanding the role of specific neuron types and cortical layers for disease manifestation is discussed.

Methods for dynamic study of the biological neural network at the cellular level using computer processing

The study of the principles of formation and development of the structure of the brain is necessary to replenish fundamental knowledge both in the field of neurophysiology and in medicine. A detailed description of all the features of the brain will allow you to choose the most effective therapy method, or check the effectiveness of the drugs being developed. The basis for creating a model of a biological neural network is a map of nerve cells and their connections. To obtain it, it is necessary to carry out microscopy of the cell culture. This will produce a low-contrast image. The study of these images is a difficult task therefore a computational method for processing images based on the Shearlet transform algorithm with contrast using color coding has been developed, designed to improve the process of creating a neural network model. To assess the functional characteristics of each cell a modified version of the MEA method is proposed. The new version will have movable microelectrodes capable of homing to the desired coordinates in accordance with the data from the analyzed microscopic images and interacting with a specific neuron. The contact of a microelectrode with a single cell allows one to study its individual adhesions with minimal noise from the excitation of neighboring cells.

Rigorous anterograde trans-monosynaptic tracing of genetic defined neurons with retargeted HSV1 H129

Neuroanatomical tracing technology is fundamental for unraveling the complex network of brain connectome. Tracing tools that could spread between neurons are urgently needed, especially the rigorous trans-monosynaptic anterograde tracer is still lacking. HSV1 strain H129 was proved to be an anterograde tracer and has been used to trace neuronal networks in several reports. However, H129 has a serious defect that it was demonstrated to infect neurons via axon terminals. Thus, when using H129 to dissect output neural circuit, its terminal take up capacity should be carefully considered. Here, we report a recombinant H129 that carrying the anti-Her2 scFv in glycoprotein D to target genetically defined neurons. With the usage of helper virus complementarily expressing Her2 and gD, we can realize the elucidation of direct projection regions of either a given brain nucleus or a specific neuron type. The retargeted H129 system complements the current neural circuit tracer arsenal, which provides a rigorous and practical anterograde trans-monosynaptic tool.

Molecular and genetic approaches for assaying human cell type synaptic connectivity

ABSTRACTProspective and post-hoc molecular identification of specific neuron types is essential for functional studies of cellular and synaptic properties. We demonstrate a thick brain slice mFISH technique applied to multi-patch-clamp recordings in human cortical slices obtained from neurosurgical-excised tissue to reveal the molecular and morpho-electric properties of synaptically connected neurons, both with and without prospective AAV based genetic labeling. This “quadruple modality” methodology should be extensible to other local brain circuits in many organisms.

Fast retrograde access to projection neuron circuits underlying vocal learning in songbirds

SummaryUnderstanding the structure and function of neural circuits underlying speech and language is a vital step towards better treatments for diseases of these systems. Songbirds, among the few animal orders that share with humans the ability to learn vocalizations from a conspecific, have provided many insights into the neural mechanisms of vocal development. However, research into vocal learning circuits has been hindered by a lack of tools for rapid genetic targeting of specific neuron populations to meet the quick pace of developmental learning. Here, we present a new viral tool that enables fast and efficient retrograde access to projection neuron populations. In zebra finches, Bengalese finches, canaries, and mice, we demonstrate fast retrograde labeling of cortical or dopaminergic neurons. We further demonstrate the suitability of our construct for detailed morphological analysis, for in vivo imaging of calcium activity, and for multicolor brainbow labeling.