Voltage-sensitive dye imaging: Technique review and models

The cortical areas processing periodontal ligament nociception in mice

OBJECTIVES

Toothaches are often poorly localized. Although periodontal pain is better localized, it can spread to other areas. Ultimately, the cerebral cortex processes nociception, with somatotopic organization possibly playing a role in localizing the origin. However, the exact cortical area in the periodontal ligament (PDL) remains unclear.

METHODS

This study examined cortical responses to electrical stimulation of the molar PDL in anesthetized male mice using in vivo optical imaging with a voltage-sensitive dye, autofluorescent flavin fluorescence, and immunohistochemistry for c-Fos protein expression.

RESULTS

On optical imaging, cortical responses to the stimulation of the ipsilateral and contralateral PDL of the upper and lower teeth were observed in the primary somatosensory cortex (S1) and area from the insular cortex (IC) to the ventral edge of the secondary somatosensory cortex (S2), defined as the area caudal to the middle cerebral artery (C-area). Responses in S1 were faint and unstable, but were consistent in the C-area. The initial response locations were similar regardless of which PDL was stimulated, and the activated areas in the C-area almost overlapped. Three-dimensional construction of c-Fos-immunopositive cells responding to upper or lower PDL stimulation revealed bilateral distribution in the cingulate gyrus, secondary auditory cortex, temporal association cortex, ectorhinal cortex, and IC, but not in the S1 and S2.

CONCLUSION

These results suggest that the somatotopic organization of the S1, S2, and IC cannot explain the localization of PDL nociception. The predominance of responses in the contralateral IC may provide clues for identifying the laterality.

Integration of partially observed multimodal and multiscale neural signals for estimating a neural circuit using dynamic causal modeling

Integrating multiscale, multimodal neuroimaging data is essential for a comprehensive understanding of neural circuits. However, this is challenging due to the inherent trade-offs between spatial coverage and resolution in each modality, necessitating a computational strategy that combines modality-specific information effectively. This study introduces a dynamic causal modeling (DCM) framework designed to address the challenge of combining partially observed, multiscale signals across a larger-scale neural circuit by employing a shared neural state model with modality-specific observation models. The proposed method achieves robust circuit inference by iteratively integrating parameter estimates from local microscale and global meso- or macroscale circuits, derived from signals across various scales and modalities. Parameters estimated from high-resolution data within specific regions inform global circuit estimation by constraining neural properties in unobserved regions, while large-scale circuit data help elucidate detailed local circuitry. Using a virtual ground truth system, we validated the method across diverse experimental settings, combining calcium imaging (CaI), voltage-sensitive dye imaging (VSDI), and blood-oxygen-level-dependent (BOLD) signals-each with distinct coverage and resolution. Our reciprocal and iterative parameter estimation approach markedly improves the accuracy of neural property and connectivity estimates compared to traditional one-step estimation methods. This iterative integration of local and global parameters presents a reliable approach to inferring extensive, complex neural circuits from partially observed, multimodal, and multiscale data, showcasing how information from different scales reciprocally enhances entire circuit parameter estimation.

Sequentially activated discrete modules appear as traveling waves in neuronal measurements with limited spatiotemporal sampling

Numerous studies have identified traveling waves in the cortex and suggested they play important roles in brain processing. These waves are most often measured using macroscopic methods that are unable to assess the local spiking activity underlying wave dynamics. Here, we investigated the possibility that waves may not be traveling at the single neuron scale. We first show that sequentially activating two discrete brain areas can appear as traveling waves in EEG simulations. We next reproduce these results using an analytical model of two sequentially activated regions. Using this model, we were able to generate wave-like activity with variable directions, velocities, and spatial patterns, and to map the discriminability limits between traveling waves and modular sequential activations. Finally, we investigated the link between field potentials and single neuron excitability using large-scale measurements from turtle cortex ex vivo. We found that while field potentials exhibit wave-like dynamics, the underlying spiking activity was better described by consecutively activated spatially adjacent groups of neurons. Taken together, this study suggests caution when interpreting phase delay measurements as continuously propagating wavefronts in two different spatial scales. A careful distinction between modular and wave excitability profiles across scales will be critical for understanding the nature of cortical computations.

Numerical investigation of a graphene-on-semiconductor device for optical monitoring of cell electrophysiology

Spatially resolved sensing devices for electrostatic potentials are extremely useful for characterization of living cells, however, many current techniques lack the speed necessary to capture spatially resolved, functional information of cells in real-time. Here, an optical sensing technique is proposed based on graphene on a semiconductor stack operating in the near-infrared spectrum. By modeling coherent interference of multiply reflected beam paths within the semiconductor stack, we demonstrate how the device produces a continuous reflectivity change in response to graphene Fermi energy which is ideal for sensing changes in local electrostatic fields produced by action potentials of living cells. By coupling the device with a high-speed camera, we propose this platform will allow for high-speed imaging of action potentials over a large sensing area with micron scale resolution.

Optical Mapping of Cardiomyocytes in Monolayer Derived from Induced Pluripotent Stem Cells

Optical mapping is a powerful imaging technique widely adopted to measure membrane potential changes and intracellular Ca2+ variations in excitable tissues using voltage-sensitive dyes and Ca2+ indicators, respectively. This powerful tool has rapidly become indispensable in the field of cardiac electrophysiology for studying depolarization wave propagation, estimating the conduction velocity of electrical impulses, and measuring Ca2+ dynamics in cardiac cells and tissues. In addition, mapping these electrophysiological parameters is important for understanding cardiac arrhythmia mechanisms. In this review, we delve into the fundamentals of cardiac optical mapping technology and its applications when applied to hiPSC-derived cardiomyocytes and discuss related advantages and challenges. We also provide a detailed description of the processing and analysis of optical mapping data, which is a crucial step in the study of cardiac diseases and arrhythmia mechanisms for extracting and comparing relevant electrophysiological parameters.

Genetically encoded fluorescent sensors for imaging neuronal dynamics in vivo

The brain relies on many forms of dynamic activities in individual neurons, from synaptic transmission to electrical activity and intracellular signaling events. Monitoring these neuronal activities with high spatiotemporal resolution in the context of animal behavior is a necessary step to achieve a mechanistic understanding of brain function. With the rapid development and dissemination of highly optimized genetically encoded fluorescent sensors, a growing number of brain activities can now be visualized in vivo. To date, cellular calcium imaging, which has been largely used as a proxy for electrical activity, has become a mainstay in systems neuroscience. While challenges remain, voltage imaging of neural populations is now possible. In addition, it is becoming increasingly practical to image over half a dozen neurotransmitters, as well as certain intracellular signaling and metabolic activities. These new capabilities enable neuroscientists to test previously unattainable hypotheses and questions. This review summarizes recent progress in the development and delivery of genetically encoded fluorescent sensors, and highlights example applications in the context of in vivo imaging.

Fluorescence Imaging of Cell Membrane Potential: From Relative Changes to Absolute Values

Membrane potential is a fundamental property of biological cells. Changes in membrane potential characterize a vast number of vital biological processes, such as the activity of neurons and cardiomyocytes, tumorogenesis, cell-cycle progression, etc. A common strategy to record membrane potential changes that occur in the process of interest is to utilize organic dyes or genetically-encoded voltage indicators with voltage-dependent fluorescence. Sensors are introduced into target cells, and alterations of fluorescence intensity are recorded with optical methods. Techniques that allow recording relative changes of membrane potential and do not take into account fluorescence alterations due to factors other than membrane voltage are already widely used in modern biological and biomedical studies. Such techniques have been reviewed previously in many works. However, in order to investigate a number of processes, especially long-term processes, the measured signal must be corrected to exclude the contribution from voltage-independent factors or even absolute values of cell membrane potential have to be evaluated. Techniques that enable such measurements are the subject of this review.

Inhibition is a prevalent mode of activity in the neocortex around awake hippocampal ripples in mice

Coordinated peri-ripple activity in the hippocampal-neocortical network is essential for mnemonic information processing in the brain. Hippocampal ripples likely serve different functions in sleep and awake states. Thus, the corresponding neocortical activity patterns may differ in important ways. We addressed this possibility by conducting voltage and glutamate wide-field imaging of the neocortex with concurrent hippocampal electrophysiology in awake mice. Contrary to our previously published sleep results, deactivation and activation were dominant in post-ripple neocortical voltage and glutamate activity, respectively, especially in the agranular retrosplenial cortex (aRSC). Additionally, the spiking activity of aRSC neurons, estimated by two-photon calcium imaging, revealed the existence of two subpopulations of excitatory neurons with opposite peri-ripple modulation patterns: one increases and the other decreases firing rate. These differences in peri-ripple spatiotemporal patterns of neocortical activity in sleep versus awake states might underlie the reported differences in the function of sleep versus awake ripples.

An Overview of In Vitro Biological Neural Networks for Robot Intelligence

In vitro biological neural networks (BNNs) interconnected with robots, so-called BNN-based neurorobotic systems, can interact with the external world, so that they can present some preliminary intelligent behaviors, including learning, memory, robot control, etc. This work aims to provide a comprehensive overview of the intelligent behaviors presented by the BNN-based neurorobotic systems, with a particular focus on those related to robot intelligence. In this work, we first introduce the necessary biological background to understand the 2 characteristics of the BNNs: nonlinear computing capacity and network plasticity. Then, we describe the typical architecture of the BNN-based neurorobotic systems and outline the mainstream techniques to realize such an architecture from 2 aspects: from robots to BNNs and from BNNs to robots. Next, we separate the intelligent behaviors into 2 parts according to whether they rely solely on the computing capacity (computing capacity-dependent) or depend also on the network plasticity (network plasticity-dependent), which are then expounded respectively, with a focus on those related to the realization of robot intelligence. Finally, the development trends and challenges of the BNN-based neurorobotic systems are discussed.

Revisiting the cerebral hemodynamics of awake, freely moving rats with repeated ketamine self-administration using a miniature photoacoustic imaging system

SIGNIFICANCE

Revealing the dynamic associations between brain functions and behaviors is a significant challenge in neurotechnology, especially for awake subjects. Imaging cerebral hemodynamics in awake animal models is important because the collected data more realistically reflect human disease states.

AIM

We previously reported a miniature head-mounted scanning photoacoustic imaging (hmPAI) system. In the present study, we utilized this system to investigate the effects of ketamine on the cerebral hemodynamics of normal rats and rats subjected to prolonged ketamine self-administration.

APPROACH

The cortical superior sagittal sinus (SSS) was continuously monitored. The full-width at half-maximum (FWHM) of the photoacoustic (PA) A-line signal was used as an indicator of the SSS diameter, and the number of pixels in PA B-scan images was used to investigate changes in the cerebral blood volume (CBV).

RESULTS

We observed a significantly higher FWHM (blood vessel diameter) and CBV in normal rats injected with ketamine than in normal rats injected with saline. For rats subjected to prolonged ketamine self-administration, no significant changes in either the blood vessel diameter or CBV were observed.

CONCLUSIONS

The lack of significant change in prolonged ketamine-exposed rats was potentially due to an increased ketamine tolerance. Our device can reliably detect changes in the dilation of cortical blood vessels and the CBV. This study validates the utility of the developed hmPAI system in an awake, freely moving rat model for behavioral, cognitive, and preclinical cerebral disease studies.

Emerging Diamond Quantum Sensing in Bio-Membranes

Bio-membranes exhibit complex but unique mechanical properties as communicative regulators in various physiological and pathological processes. Exposed to a dynamic micro-environment, bio-membranes can be seen as an intricate and delicate system. The systematical modeling and detection of their local physical properties are often difficult to achieve, both quantitatively and precisely. The recent emerging diamonds hosting quantum defects (i.e., nitrogen-vacancy (NV) center) demonstrate intriguing optical and spin properties, together with their outstanding photostability and biocompatibility, rendering them ideal candidates for biological applications. Notably, the extraordinary spin-based sensing enable the measurements of localized nanoscale physical quantities such as magnetic fields, electrical fields, temperature, and strain. These nanoscale signals can be optically read out precisely by simple optical microscopy systems. Given these exclusive properties, NV-center-based quantum sensors can be widely applied in exploring bio-membrane-related features and the communicative chemical reaction processes. This review mainly focuses on NV-based quantum sensing in bio-membrane fields. The attempts of applying NV-based quantum sensors in bio-membranes to investigate diverse physical and chemical events such as membrane elasticity, phase change, nanoscale bio-physical signals, and free radical formation are fully overviewed. We also discuss the challenges and future directions of this novel technology to be utilized in bio-membranes.

Visual evoked feedforward-feedback traveling waves organize neural activity across the cortical hierarchy in mice

Sensory processing is distributed among many brain regions that interact via feedforward and feedback signaling. Neuronal oscillations have been shown to mediate intercortical feedforward and feedback interactions. Yet, the macroscopic structure of the multitude of such oscillations remains unclear. Here, we show that simple visual stimuli reliably evoke two traveling waves with spatial wavelengths that cover much of the cerebral hemisphere in awake mice. 30-50 Hz feedforward waves arise in primary visual cortex (V1) and propagate rostrally, while 3-6 Hz feedback waves originate in the association cortex and flow caudally. The phase of the feedback wave modulates the amplitude of the feedforward wave and synchronizes firing between V1 and parietal cortex. Altogether, these results provide direct experimental evidence that visual evoked traveling waves percolate through the cerebral cortex and coordinate neuronal activity across broadly distributed networks mediating visual processing.

Discovering Microcircuit Secrets With Multi-Spot Imaging and Electrophysiological Recordings: The Example of Cerebellar Network Dynamics

The cerebellar cortex microcircuit is characterized by a highly ordered neuronal architecture having a relatively simple and stereotyped connectivity pattern. For a long time, this structural simplicity has incorrectly led to the idea that anatomical considerations would be sufficient to understand the dynamics of the underlying circuitry. However, recent experimental evidence indicates that cerebellar operations are much more complex than solely predicted by anatomy, due to the crucial role played by neuronal and synaptic properties. To be able to explore neuronal and microcircuit dynamics, advanced imaging, electrophysiological techniques and computational models have been combined, allowing us to investigate neuronal ensembles activity and to connect microscale to mesoscale phenomena. Here, we review what is known about cerebellar network organization, neural dynamics and synaptic plasticity and point out what is still missing and would require experimental assessments. We consider the available experimental techniques that allow a comprehensive assessment of circuit dynamics, including voltage and calcium imaging and extracellular electrophysiological recordings with multi-electrode arrays (MEAs). These techniques are proving essential to investigate the spatiotemporal pattern of activity and plasticity in the cerebellar network, providing new clues on how circuit dynamics contribute to motor control and higher cognitive functions.

Evaluation and Optimization of Methods for Generating High-Resolution Retinotopic Maps Using Visual Cortex Voltage-Sensitive Dye Imaging

The localization and measurement of neuronal activity magnitude at high spatial and temporal resolution are essential for mapping and better understanding neuronal systems and mechanisms. One such example is the generation of retinotopic maps, which correlates localized retinal stimulation with the corresponding specific visual cortex responses. Here we evaluated and compared seven different methods for extracting and localizing cortical responses from voltage-sensitive dye imaging recordings, elicited by visual stimuli projected directly on the rat retina by a customized projection system. The performance of these methods was evaluated both qualitatively and quantitatively by means of two cluster separation metrics, namely, the (adjusted) Silhouette Index (SI) and the (adjusted) Davies-Bouldin Index (DBI). These metrics were validated using simulated data, which showed that Temporally Structured Component Analysis (TSCA) outperformed all other analysis methods for localizing cortical responses and generating high-resolution retinotopic maps. The analysis methods, as well as the use of cluster separation metrics proposed here, can facilitate future research aiming to localize specific activity at high resolution in the visual cortex or other brain areas.

Nonlinear collision between propagating waves in mouse somatosensory cortex

How does cellular organization shape the spatio-temporal patterns of activity in the cortex while processing sensory information? After measuring the propagation of activity in the mouse primary somatosensory cortex (S1) in response to single whisker deflections with Voltage Sensitive Dye (VSD) imaging, we developed a two dimensional model of S1. We designed an inference method to reconstruct model parameters from VSD data, revealing that a spatially heterogeneous organization of synaptic strengths between pyramidal neurons in S1 is likely to be responsible for the heterogeneous spatio-temporal patterns of activity measured experimentally. The model shows that, for strong enough excitatory cortical interactions, whisker deflections generate a propagating wave in S1. Finally, we report that two consecutive stimuli activating different spatial locations in S1 generate two waves which collide sub-linearly, giving rise to a suppressive wave. In the inferred model, the suppressive wave is explained by a lower sensitivity to external perturbations of neural networks during activated states.

Visual stimulation with blue wavelength light drives V1 effectively eliminating stray light contamination during two-photon calcium imaging

BACKGROUND

Brain visual circuits are often studied in vivo by imaging Ca²⁺ indicators with green-shifted emission spectra. Polychromatic white visual stimuli have a spectrum that partially overlaps indicators´ emission spectra, resulting in significant contamination of calcium signals.

NEW METHOD

To overcome light contamination problems we choose blue visual stimuli, having a spectral composition not overlapping with Ca²⁺ indicator´s emission spectrum. To compare visual responsiveness to blue and white stimuli we used electrophysiology (visual evoked potentials -VEPs) and 3D acousto-optic two-photon (2P) population Ca²⁺ imaging in mouse primary visual cortex (V1).

RESULTS

VEPs in response to blue and white stimuli had comparable peak amplitudes and latencies. Ca²⁺ imaging in a Thy1 GP4.3 line revealed that the populations of neurons responding to blue and white stimuli were largely overlapping, that their responses had similar amplitudes, and that functional response properties such as orientation and direction selectivities were also comparable.

COMPARISON WITH EXISTING METHODS

Masking or shielding the microscope are often used to minimize the contamination of Ca²⁺ signal by white light, but they are time consuming, bulky and thus can limit experimental design, particularly in the more and more frequently used awake set-up. Blue stimuli not interfering with imaging allow to omit shielding.

CONCLUSIONS

Together, our results show that the selected blue light stimuli evoke responses comparable to those evoked by white stimuli in mouse V1. This will make complex designs of imaging experiments in behavioral set-ups easier, and facilitate the combination of Ca²⁺ imaging with electrophysiology and optogenetics.

In silico voltage-sensitive dye imaging reveals the emergent dynamics of cortical populations

Voltage-sensitive dye imaging (VSDI) is a powerful technique for interrogating membrane potential dynamics in assemblies of cortical neurons, but with effective resolution limits that confound interpretation. To address this limitation, we developed an in silico model of VSDI in a biologically faithful digital reconstruction of rodent neocortical microcircuitry. Using this model, we extend previous experimental observations regarding the cellular origins of VSDI, finding that the signal is driven primarily by neurons in layers 2/3 and 5, and that VSDI measurements do not capture individual spikes. Furthermore, we test the capacity of VSD image sequences to discriminate between afferent thalamic inputs at various spatial locations to estimate a lower bound on the functional resolution of VSDI. Our approach underscores the power of a bottom-up computational approach for relating scales of cortical processing.

Optical Imaging of Electrical and Mechanical Couplings between Cells

Intercellular communication plays a pivotal role in multicellular organisms. Studying the electrical and mechanical coupling among multiple cells has been a difficult task due to the lack of suitable techniques. In this study, we developed a label-free imaging method for monitoring the electrical-induced communications between connected cells. The method was based on monitoring subtle mechanical motions of the cells under electrical modulation of the membrane potential. We observed that connected cells responded to electrical modulation of neighboring cells with mechanical deformation of the membrane. We further investigated the mechanism of the coupling and confirmed that this mechanical response was induced by electrical signal communicated through the gap junction. Blocking the gap junction can temporally cease the mechanical signal, and this inhibition can be rescued after removing the inhibitor. This study sheds light on the mechanism of electrical coupling between neurons and provides a new method for studying intercellular communications.

New frontiers in translational research: Touchscreens, open science, and the mouse translational research accelerator platform

Many neurodegenerative and neuropsychiatric diseases and other brain disorders are accompanied by impairments in high-level cognitive functions including memory, attention, motivation, and decision-making. Despite several decades of extensive research, neuroscience is little closer to discovering new treatments. Key impediments include the absence of validated and robust cognitive assessment tools for facilitating translation from animal models to humans. In this review, we describe a state-of-the-art platform poised to overcome these impediments and improve the success of translational research, the Mouse Translational Research Accelerator Platform (MouseTRAP), which is centered on the touchscreen cognitive testing system for rodents. It integrates touchscreen-based tests of high-level cognitive assessment with state-of-the art neurotechnology to record and manipulate molecular and circuit level activity in vivo in animal models during human-relevant cognitive performance. The platform also is integrated with two Open Science platforms designed to facilitate knowledge and data-sharing practices within the rodent touchscreen community, touchscreencognition.org and mousebytes.ca. Touchscreencognition.org includes the Wall, showcasing touchscreen news and publications, the Forum, for community discussion, and Training, which includes courses, videos, SOPs, and symposia. To get started, interested researchers simply create user accounts. We describe the origins of the touchscreen testing system, the novel lines of research it has facilitated, and its increasingly widespread use in translational research, which is attributable in part to knowledge-sharing efforts over the past decade. We then identify the unique features of MouseTRAP that stand to potentially revolutionize translational research, and describe new initiatives to partner with similar platforms such as McGill's M3 platform (m3platform.org).

A simultaneous optical and electrical in-vitro neuronal recording system to evaluate microelectrode performance

Objectives

In this paper, we aim to detail the setup of a high spatio-temporal resolution, electrical recording system utilising planar microelectrode arrays with simultaneous optical imaging suitable for evaluating microelectrode performance with a proposed ′performance factor′ metric.

Methods

Techniques that would facilitate low noise electrical recordings were coupled with voltage sensitive dyes and neuronal activity was recorded both electrically via a customised amplification system and optically via a high speed CMOS camera. This technique was applied to characterise microelectrode recording performance of gold and poly(3,4-ethylenedioxythiophene)/polystyrene sulfonate (PEDOT/PSS) coated electrodes through traditional signal to noise (SNR) calculations as well as the proposed performance factor.

Results

Neuronal activity was simultaneously recorded using both electrical and optical techniques and this activity was confirmed via tetrodotoxin application to inhibit action potential firing. PEDOT/PSS outperformed gold using both measurements, however, the performance factor metric estimated a 3 fold improvement in signal transduction when compared to gold, whereas SNR estimated an 8 fold improvement when compared to gold.

Conclusion

The design and functionality of a system to record from neurons both electrically, through microelectrode arrays, and optically via voltage sensitive dyes was successfully achieved.

Significance

The high spatiotemporal resolution of both electrical and optical methods will allow for an array of applications such as improved detection of subthreshold synaptic events, validation of spike sorting algorithms and a provides a robust evaluation of extracellular microelectrode performance.

Time-Multiplexed Illumination for simultaneous Structural and Functional Voltage Sensitive Dye Recordings with a single Photo Sensor

The in-vivo optical imaging of the cortical surface provides the ability to record different types of biophysiological signals, e.g., structural information, intrinsic signals, like blood oxygenation coupled reflection changes as well as extrinsic properties of voltage sensitive probes, like fluorescent voltage-sensitive dyes. The recorded data sets have very high temporal and spatial resolutions on a meso- to macroscopic scale, which surpass conventional multi-electrode recordings. Both, intrinsic and functional data sets, each provide unique information about temporal and spatial dynamics of cortical functioning, yet have individual drawbacks. To optimize the informational value it would thus be opportune to combine different types of optical imaging in a near simultaneous recording.Due to the low signal-to-noise ratio of voltage-sensitive dyes it is necessary to reduce stray light pollution below the level of the camera's dark noise. It is thus impossible to record full-spectrum optical data sets. We address this problem by a time-multiplexed illumination, bespoke to the utilized voltage sensitive dye, to record an alternating series of intrinsic and extrinsic frames by a high-frequency CMOS sensor. These near simultaneous data series can be used to compare the mutual influence of intrinsic and extrinsic dynamics (with regards to extracorporeal functional imaging) as well as for motion compensation and thus for minimizing frame averaging, which in turn results in increased spatial precision of functional data and in a reduction of necessary experimental data sets (3R principle).

Neurophotonics Approaches for the Study of Pattern Separation

Successful memory involves not only remembering over time but also keeping memories distinct. Computational models suggest that pattern separation appears as a highly efficient process to discriminate between overlapping memories. Furthermore, lesion studies have shown that the dentate gyrus (DG) participates in pattern separation. However, these manipulations did not allow identifying the neuronal mechanism underlying pattern separation. The development of different neurophotonics techniques, together with other genetic tools, has been useful for the study of the microcircuit involved in this process. It has been shown that less-overlapped information would generate distinct neuronal representations within the granule cells (GCs). However, because glutamatergic or GABAergic cells in the DG are not functionally or structurally homogeneous, identifying the specific role of the different subpopulations remains elusive. Then, understanding pattern separation requires the ability to manipulate a temporal and spatially specific subset of cells in the DG and ideally to analyze DG cells activity in individuals performing a pattern separation dependent behavioral task. Thus, neurophotonics and calcium imaging techniques in conjunction with activity-dependent promoters and high-resolution microscopy appear as important tools for this endeavor. In this work, we review how different neurophotonics techniques have been implemented in the elucidation of a neuronal network that supports pattern separation alone or in combination with traditional techniques. We discuss the limitation of these techniques and how other neurophotonic techniques could be used to complement the advances presented up to this date.

Suppression of Superficial Microglial Activation by Spinal Cord Stimulation Attenuates Neuropathic Pain Following Sciatic Nerve Injury in Rats

We evaluated the mechanisms underlying the spinal cord stimulation (SCS)-induced analgesic effect on neuropathic pain following spared nerve injury (SNI). On day 3 after SNI, SCS was performed for 6 h by using electrodes paraspinally placed on the L4-S1 spinal cord. The effects of SCS and intraperitoneal minocycline administration on plantar mechanical sensitivity, microglial activation, and neuronal excitability in the L4 dorsal horn were assessed on day 3 after SNI. The somatosensory cortical responses to electrical stimulation of the hind paw on day 3 following SNI were examined by using in vivo optical imaging with a voltage-sensitive dye. On day 3 after SNI, plantar mechanical hypersensitivity and enhanced microglial activation were suppressed by minocycline or SCS, and L4 dorsal horn nociceptive neuronal hyperexcitability was suppressed by SCS. In vivo optical imaging also revealed that electrical stimulation of the hind paw-activated areas in the somatosensory cortex was decreased by SCS. The present findings suggest that SCS could suppress plantar SNI-induced neuropathic pain via inhibition of microglial activation in the L4 dorsal horn, which is involved in spinal neuronal hyperexcitability. SCS is likely to be a potential alternative and complementary medicine therapy to alleviate neuropathic pain following nerve injury.

Bridging Single Neuron Dynamics to Global Brain States

Biological neural networks produce information backgrounds of multi-scale spontaneous activity that become more complex in brain states displaying higher capacities for cognition, for instance, attentive awake versus asleep or anesthetized states. Here, we review brain state-dependent mechanisms spanning ion channel currents (microscale) to the dynamics of brain-wide, distributed, transient functional assemblies (macroscale). Not unlike how microscopic interactions between molecules underlie structures formed in macroscopic states of matter, using statistical physics, the dynamics of microscopic neural phenomena can be linked to macroscopic brain dynamics through mesoscopic scales. Beyond spontaneous dynamics, it is observed that stimuli evoke collapses of complexity, most remarkable over high dimensional, asynchronous, irregular background dynamics during consciousness. In contrast, complexity may not be further collapsed beyond synchrony and regularity characteristic of unconscious spontaneous activity. We propose that increased dimensionality of spontaneous dynamics during conscious states supports responsiveness, enhancing neural networks' emergent capacity to robustly encode information over multiple scales.

High-resolution VSDI retinotopic mapping via a DLP-based projection system

High-resolution recording of visual cortex activity is an important tool for vision research. Using a customized digital mirror device (DMD) - based system equipped with retinal imaging, we projected visual stimuli directly on the rat retina and recorded cortical responses by voltage-sensitive dye imaging. We obtained robust cortical responses and generated high-resolution retinotopic maps at an unprecedented retinal resolution of 4.6 degrees in the field of view, while further distinguishing between normal and pathological retinal areas. This system is a useful tool for studying the cortical response to localized retinal stimulation and may shed light on various cortical plasticity processes.

Interaction of Cortical and Amygdalar Synaptic Input Modulates the Window of Opportunity for Information Processing in the Rhinal Cortices

The perirhinal (PER) and lateral entorhinal (LEC) cortex function as a gateway for information transmission between (sub)cortical areas and the hippocampus. It is hypothesized that the amygdala, a key structure in emotion processing, can modulate PER-LEC neuronal activity before information enters the hippocampal memory pathway. This study determined the integration of synaptic activity evoked by simultaneous neocortical and amygdala electrical stimulation in PER-LEC deep layer principal neurons and parvalbumin (PV) interneurons in mouse brain slices. The data revealed that both deep layer PER-LEC principal neurons and PV interneurons receive synaptic input from the neocortical agranular insular cortex (AiP) and the lateral amygdala (LA). Furthermore, simultaneous stimulation of the AiP and LA never reached the firing threshold in principal neurons of the PER-LEC deep layers. PV interneurons however, mainly showed linear summation of simultaneous AiP and LA inputs and reached their firing threshold earlier. This early PV firing was reflected in the forward shift of the evoked inhibitory conductance in principal neurons, thereby creating a more precise temporal window for coincidence detection, which likely plays a crucial role in information processing.

Optogenetics in Brain Research: From a Strategy to Investigate Physiological Function to a Therapeutic Tool

Dissecting the functional roles of neuronal circuits and their interaction is a crucial step in basic neuroscience and in all the biomedical field. Optogenetics is well-suited to this purpose since it allows us to study the functionality of neuronal networks on multiple scales in living organisms. This tool was recently used in a plethora of studies to investigate physiological neuronal circuit function in addition to dysfunctional or pathological conditions. Moreover, optogenetics is emerging as a crucial technique to develop new rehabilitative and therapeutic strategies for many neurodegenerative diseases in pre-clinical models. In this review, we discuss recent applications of optogenetics, starting from fundamental research to pre-clinical applications. Firstly, we described the fundamental components of optogenetics, from light-activated proteins to light delivery systems. Secondly, we showed its applications to study neuronal circuits in physiological or pathological conditions at the cortical and subcortical level, in vivo. Furthermore, the interesting findings achieved using optogenetics as a therapeutic and rehabilitative tool highlighted the potential of this technique for understanding and treating neurological diseases in pre-clinical models. Finally, we showed encouraging results recently obtained by applying optogenetics in human neuronal cells in-vitro.

Optical recording reveals topological distribution of functionally classified colorectal afferent neurons in intact lumbosacral DRG

Neuromodulation as a non-drug alternative for managing visceral pain in irritable bowel syndrome (IBS) may target sensitized afferents of distal colon and rectum (colorectum), especially their somata in the dorsal root ganglion (DRG). Developing selective DRG stimulation to manage visceral pain requires knowledge of the topological distribution of colorectal afferent somata which are sparsely distributed in the DRG. Here, we implemented GCaMP6f to conduct high-throughput optical recordings of colorectal afferent activities in lumbosacral DRG, that is, optical electrophysiology. Using a mouse ex vivo preparation with distal colorectum and L5-S1 DRG in continuity, we recorded 791 colorectal afferents' responses to graded colorectal distension (15, 30, 40, and 60 mmHg) and/or luminal shear flow (20-30 mL/min), then functionally classified them into four mechanosensitive classes, and determined the topological distribution of their somata in the DRG. Of the 791 colorectal afferents, 90.8% were in the L6 DRG, 8.3% in the S1 DRG, and only 0.9% in the L5 DRG. L6 afferents had all four classes: 29% mucosal, 18.4% muscular-mucosal, 34% low-threshold (LT) muscular, and 18.2% high-threshold (HT) muscular afferents. S1 afferents only had three classes: 19.7% mucosal, 34.8% LT muscular, and 45.5% HT muscular afferents. All seven L5 afferents were HT muscular. In L6 DRG, somata of HT muscular afferents were clustered in the caudal region whereas somata of the other classes did not cluster in specific regions. Outcomes of this study can directly inform the design and improvement of next-generation neuromodulation devices that target the DRG to alleviate visceral pain in IBS patients.

Suppressive Traveling Waves Shape Representations of Illusory Motion in Primary Visual Cortex of Awake Primate

How does the brain link visual stimuli across space and time? Visual illusions provide an experimental paradigm to study these processes. When two stationary dots are flashed in close spatial and temporal succession, human observers experience a percept of apparent motion. Large spatiotemporal separation challenges the visual system to keep track of object identity along the apparent motion path, the so-called "correspondence problem." Here, we use voltage-sensitive dye imaging in primary visual cortex (V1) of awake monkeys to show that intracortical connections within V1 can solve this issue by shaping cortical dynamics to represent the illusory motion. We find that the appearance of the second stimulus in V1 creates a systematic suppressive wave traveling toward the retinotopic representation of the first. Using a computational model, we show that the suppressive wave is the emergent property of a recurrent gain control fed by the intracortical network. This suppressive wave acts to explain away ambiguous correspondence problems and contributes to precisely encode the expected motion velocity at the surface of V1. Together, these results demonstrate that the nonlinear dynamics within retinotopic maps can shape cortical representations of illusory motion. Understanding these dynamics will shed light on how the brain links sensory stimuli across space and time, by preformatting population responses for a straightforward read-out by downstream areas.SIGNIFICANCE STATEMENT Traveling waves have recently been observed in different animal species, brain areas, and behavioral states. However, it is still unclear what are their functional roles. In the case of cortical visual processing, waves propagate across retinotopic maps and can hereby generate interactions between spatially and temporally separated instances of feedforward driven activity. Such interactions could participate in processing long-range apparent motion stimuli, an illusion for which no clear neuronal mechanisms have yet been proposed. Using this paradigm in awake monkeys, we show that suppressive traveling waves produce a spatiotemporal normalization of apparent motion stimuli. Our study suggests that cortical waves shape the representation of illusory moving stimulus within retinotopic maps for a straightforward read-out by downstream areas.

Extracellular glucose-dependent IPSC enhancement by leptin in fast-spiking to pyramidal neuron connections via JAK2-PI3K pathway in the rat insular cortex

Leptin is produced in the adipocytes and plays a pivotal role in regulation of energy balance by controlling appetite and metabolism. Leptin receptors are widely distributed in the brain, especially in the hypothalamus, hippocampus, and neocortex. The insular cortex (IC) processes gustatory and visceral information, which functionally correlate to feeding behavior. However, it is still an open issue whether and how leptin modulates IC neural activities. Our paired whole-cell patch-clamp recordings using IC slice preparations demonstrated that unitary inhibitory postsynaptic currents (uIPSCs) but not uEPSCs were potentiated by leptin in the connections between pyramidal (PNs) and fast-spiking neurons (FSNs). The leptin-induced increase in uIPSC amplitude was accompanied by a decrease in paired-pulse ratio. Under application of inhibitors of JAK2-PI3K but not MAPK pathway, leptin did not change uIPSC amplitude. Variance-mean analysis revealed that leptin increased the release probability but not the quantal size and the number of release site. These electrophysiological findings suggest that the leptin-induced uIPSC increase is mediated by activation of JAK2-PI3K pathway in presynaptic FSNs. An in vivo optical imaging revealed that leptin application decreased excitatory propagation in IC induced by electrical stimulation of IC. These leptin-induced effects were not observed under the low energy states: low glucose concentration (2.5 mM) in vitro and one-day-fasting condition in vivo. However, leptin enhanced uIPSCs under application of low glucose with an AMPK inhibitor. These results suggest that leptin suppresses IC excitation by facilitating GABA release in FSN→PN connections, which may not occur under a hunger state.

The next-generation sphingosine-1 receptor modulator BAF312 (siponimod) improves cortical network functionality in focal autoimmune encephalomyelitis

Autoimmune diseases of the central nervous system (CNS) like multiple sclerosis (MS) are characterized by inflammation and demyelinated lesions in white and grey matter regions. While inflammation is present at all stages of MS, it is more pronounced in the relapsing forms of the disease, whereas progressive MS (PMS) shows significant neuroaxonal damage and grey and white matter atrophy. Hence, disease-modifying treatments beneficial in patients with relapsing MS have limited success in PMS. BAF312 (siponimod) is a novel sphingosine-1-phosphate receptor modulator shown to delay progression in PMS. Besides reducing inflammation by sequestering lymphocytes in lymphoid tissues, BAF312 crosses the blood-brain barrier and binds its receptors on neurons, astrocytes and oligodendrocytes. To evaluate potential direct neuroprotective effects, BAF312 was systemically or locally administered in the CNS of experimental autoimmune encephalomyelitis mice with distinct grey- and white-matter lesions (focal experimental autoimmune encephalomyelitis using an osmotic mini-pump). Ex-vivo flow cytometry revealed that systemic but not local BAF312 administration lowered immune cell infiltration in animals with both grey and white matter lesions. Ex-vivo voltage-sensitive dye imaging of acute brain slices revealed an altered spatio-temporal pattern of activation in the lesioned cortex compared to controls in response to electrical stimulation of incoming white-matter fiber tracts. Here, BAF312 administration showed partial restore of cortical neuronal circuit function. The data suggest that BAF312 exerts a neuroprotective effect after crossing the blood-brain barrier independently of peripheral effects on immune cells. Experiments were carried out in accordance with German and EU animal protection law and approved by local authorities (Landesamt für Natur, Umwelt und Verbraucherschutz Nordrhein-Westfalen; 87-51.04.2010.A331) on December 28, 2010.

Multimodal Modeling of Neural Network Activity: Computing LFP, ECoG, EEG, and MEG Signals With LFPy 2.0

Recordings of extracellular electrical, and later also magnetic, brain signals have been the dominant technique for measuring brain activity for decades. The interpretation of such signals is however nontrivial, as the measured signals result from both local and distant neuronal activity. In volume-conductor theory the extracellular potentials can be calculated from a distance-weighted sum of contributions from transmembrane currents of neurons. Given the same transmembrane currents, the contributions to the magnetic field recorded both inside and outside the brain can also be computed. This allows for the development of computational tools implementing forward models grounded in the biophysics underlying electrical and magnetic measurement modalities. LFPy (LFPy.readthedocs.io) incorporated a well-established scheme for predicting extracellular potentials of individual neurons with arbitrary levels of biological detail. It relies on NEURON (neuron.yale.edu) to compute transmembrane currents of multicompartment neurons which is then used in combination with an electrostatic forward model. Its functionality is now extended to allow for modeling of networks of multicompartment neurons with concurrent calculations of extracellular potentials and current dipole moments. The current dipole moments are then, in combination with suitable volume-conductor head models, used to compute non-invasive measures of neuronal activity, like scalp potentials (electroencephalographic recordings; EEG) and magnetic fields outside the head (magnetoencephalographic recordings; MEG). One such built-in head model is the four-sphere head model incorporating the different electric conductivities of brain, cerebrospinal fluid, skull and scalp. We demonstrate the new functionality of the software by constructing a network of biophysically detailed multicompartment neuron models from the Neocortical Microcircuit Collaboration (NMC) Portal (bbp.epfl.ch/nmc-portal) with corresponding statistics of connections and synapses, and compute in vivo-like extracellular potentials (local field potentials, LFP; electrocorticographical signals, ECoG) and corresponding current dipole moments. From the current dipole moments we estimate corresponding EEG and MEG signals using the four-sphere head model. We also show strong scaling performance of LFPy with different numbers of message-passing interface (MPI) processes, and for different network sizes with different density of connections. The open-source software LFPy is equally suitable for execution on laptops and in parallel on high-performance computing (HPC) facilities and is publicly available on GitHub.com.

Protective and reversal actions of a novel peptidomimetic against a pivotal toxin implicated in Alzheimer's disease

Despite the many attempts to understand the aetiology of Alzheimer's disease, the basic mechanisms accounting for the progressive cycle of neuronal loss are still unknown. Previous work has suggested that the pivotal molecule mediating neurodegeneration could be an independently acting peptide cleaved from acetylcholinesterase. This previously unidentified agent acts as a signalling molecule in selectively vulnerable groups of cells where erstwhile developmental mechanisms are activated inappropriately to have a toxic effect in the context of the mature brain. We have previously shown that the toxic actions of this peptide, whose level is doubled in the Alzheimer brain, can be blocked by a cyclised variant (NBP14). However, the size and properties of NBP14 would render it unlikely as a feasible therapeutic candidate. Here therefore we test a synthetic peptidomimetic (NB-0193), modelled on the binding of NBP14 to the target alpha-7 nicotinic receptor, and benchmarked against it to screen for reversal effects using real-time optical imaging in rat brain slices. The blocking action of NB-0193 was confirmed by testing its effect against peptide-induced calcium influx in cell cultures, where it showed a dose-dependent profile over a trophic-toxic range. Moreover, NB-0193 presented promising pharmacokinetic characteristics and could therefore prompt a new therapeutic approach against Alzheimer's disease.

VIOLA-A Multi-Purpose and Web-Based Visualization Tool for Neuronal-Network Simulation Output

Neuronal network models and corresponding computer simulations are invaluable tools to aid the interpretation of the relationship between neuron properties, connectivity, and measured activity in cortical tissue. Spatiotemporal patterns of activity propagating across the cortical surface as observed experimentally can for example be described by neuronal network models with layered geometry and distance-dependent connectivity. In order to cover the surface area captured by today's experimental techniques and to achieve sufficient self-consistency, such models contain millions of nerve cells. The interpretation of the resulting stream of multi-modal and multi-dimensional simulation data calls for integrating interactive visualization steps into existing simulation-analysis workflows. Here, we present a set of interactive visualization concepts called views for the visual analysis of activity data in topological network models, and a corresponding reference implementation VIOLA (VIsualization Of Layer Activity). The software is a lightweight, open-source, web-based, and platform-independent application combining and adapting modern interactive visualization paradigms, such as coordinated multiple views, for massively parallel neurophysiological data. For a use-case demonstration we consider spiking activity data of a two-population, layered point-neuron network model incorporating distance-dependent connectivity subject to a spatially confined excitation originating from an external population. With the multiple coordinated views, an explorative and qualitative assessment of the spatiotemporal features of neuronal activity can be performed upfront of a detailed quantitative data analysis of specific aspects of the data. Interactive multi-view analysis therefore assists existing data analysis workflows. Furthermore, ongoing efforts including the European Human Brain Project aim at providing online user portals for integrated model development, simulation, analysis, and provenance tracking, wherein interactive visual analysis tools are one component. Browser-compatible, web-technology based solutions are therefore required. Within this scope, with VIOLA we provide a first prototype.

Voltage-sensitive dye delivery through the blood brain barrier using adenosine receptor agonist regadenoson

Optical imaging of brain activity has mostly employed genetically manipulated mice, which cannot be translated to clinical human usage. Observation of brain activity directly is challenging due to the difficulty in delivering dyes and other agents through the blood brain barrier (BBB). Using fluorescence imaging, we have demonstrated the feasibility of delivering the near-infrared voltage-sensitive dye (VSD) IR-780 perchlorate to the brain tissue through pharmacological techniques, via an adenosine agonist (regadenoson). Comparison of VSD fluorescence of mouse brains without and with regadenoson showed significantly increased residence time of the fluorescence signal in the latter case, indicative of VSD diffusion into the brain tissue. Dose and timing of regadenoson were varied to optimize BBB permeability for VSD delivery.

Rapid Voltage Sensing with Single Nanorods via the Quantum Confined Stark Effect

Properly designed colloidal semiconductor quantum dots (QDs) have already been shown to exhibit high sensitivity to external electric fields via the quantum confined Stark effect (QCSE). Yet, detection of the characteristic spectral shifts associated with the effect of the QCSE has traditionally been painstakingly slow, dramatically limiting the sensitivity of these QD sensors to fast transients. We experimentally demonstrate a new detection scheme designed to achieve shot-noise-limited sensitivity to emission wavelength shifts in QDs, showing feasibility for their use as local electric field sensors on the millisecond time scale. This regime of operation is already potentially suitable for detection of single action potentials in neurons at a high spatial resolution.

A Multidisciplinary Approach Reveals an Age-Dependent Expression of a Novel Bioactive Peptide, Already Involved in Neurodegeneration, in the Postnatal Rat Forebrain

The basal forebrain has received much attention due to its involvement in multiple cognitive functions, but little is known about the basic neuronal mechanisms underlying its development, nor those mediating its primary role in Alzheimer’s disease. We have previously suggested that a novel 14-mer peptide, ‘T14’, could play a pivotal role in Alzheimer’s disease, via reactivation of a developmental signaling pathway. In this study, we have characterized T14 in the context of post-natal rat brain development, using a combination of different techniques. Ex-vivo rat brain slices containing the basal forebrain, at different stages of development, were used to investigate large-scale neuronal network activity in real time with voltage-sensitive dye imaging. Subsequent Western blot analysis revealed the expression profile of endogenous T14, its target alpha7 nicotinic receptor and the familiar markers of Alzheimer’s: amyloid beta and phosphorylated Tau. Results indicated maximal neuronal activity at the earliest ages during development, reflected in a concomitant profile of T14 peptide levels and related proteins. In conclusion, these findings show that the peptide, already implicated in neurodegenerative events, has an age-dependent expression, suggesting a possible contribution to the physiological mechanisms underlying brain maturation.

Evaluating the potential of using quantum dots for monitoring electrical signals in neurons

Success in the projects aimed at providing an advanced understanding of the brain is directly predicated on making critical advances in nanotechnology. This Perspective addresses the unique interface of neuroscience and nanomaterials by considering the foundational problem of sensing neuron membrane voltage and offers a potential solution that may be facilitated by a prototypical nanomaterial. Despite substantial improvements, the visualization of instantaneous voltage changes within individual neurons, whether in cell culture or in vivo, at both the single-cell and network level at high speed remains complex and problematic. The unique properties of semiconductor quantum dots (QDs) have made them powerful fluorophores for bioimaging. What is not widely appreciated, however, is that QD photoluminescence is exquisitely sensitive to proximal electric fields. This property should be suitable for sensing voltage changes that occur in the active neuronal membrane. Here, we examine the potential role of QDs in addressing the important challenge of real-time optical voltage imaging.

Imaging voltage in zebrafish as a route to characterizing a vertebrate functional connectome: promises and pitfalls of genetically encoded indicators

Neural circuits are non-linear dynamical systems that transform information based on the pattern of input, current state and functional connectivity. To understand how a given stimulus is processed, one would ideally record neural activity across the entire brain of a behaving animal, at cellular or even subcellular resolution, in addition to characterizing anatomical connectivity. Given their transparency and relatively small size, larval zebrafish provide a powerful system for brain-wide monitoring of neural activity. Genetically encoded calcium indicators have been used for this purpose, but cannot directly report hyperpolarization or sub-threshold activity. Voltage indicators, in contrast, have this capability. Here, we test whether two different genetically encoded voltage reporters, ASAP1 and Bongwoori, can be expressed and report activity in the zebrafish brain, using widefield, two-photon and light sheet microscopy. We were unable to express ASAP1 in neurons. Bongwoori, in contrast expressed well, and because of its membrane localization, allowed visualization of axon trajectories in 3D. Bongwoori displayed stimulus-evoked changes in fluorescence, which could be detected in single trials. However, under high laser illumination, puncta on neural membranes underwent spontaneous fluctuations in intensity, suggesting that the probe is susceptible to blinking artefacts. These data indicate that larval zebrafish can be used to image electrical activity in the brain of an intact vertebrate at high resolution, although care is needed in imaging and analysis. Recording activity across the whole brain will benefit from further developments in imaging hardware and indicators.

Neural field model to reconcile structure with function in primary visual cortex

Voltage-sensitive dye imaging experiments in primary visual cortex (V1) have shown that local, oriented visual stimuli elicit stable orientation-selective activation within the stimulus retinotopic footprint. The cortical activation dynamically extends far beyond the retinotopic footprint, but the peripheral spread stays non-selective-a surprising finding given a number of anatomo-functional studies showing the orientation specificity of long-range connections. Here we use a computational model to investigate this apparent discrepancy by studying the expected population response using known published anatomical constraints. The dynamics of input-driven localized states were simulated in a planar neural field model with multiple sub-populations encoding orientation. The realistic connectivity profile has parameters controlling the clustering of long-range connections and their orientation bias. We found substantial overlap between the anatomically relevant parameter range and a steep decay in orientation selective activation that is consistent with the imaging experiments. In this way our study reconciles the reported orientation bias of long-range connections with the functional expression of orientation selective neural activity. Our results demonstrate this sharp decay is contingent on three factors, that long-range connections are sufficiently diffuse, that the orientation bias of these connections is in an intermediate range (consistent with anatomy) and that excitation is sufficiently balanced by inhibition. Conversely, our modelling results predict that, for reduced inhibition strength, spurious orientation selective activation could be generated through long-range lateral connections. Furthermore, if the orientation bias of lateral connections is very strong, or if inhibition is particularly weak, the network operates close to an instability leading to unbounded cortical activation.

Reconstruction and visualization of large-scale volumetric models of neocortical circuits for physically-plausible in silico optical studies

BACKGROUND

We present a software workflow capable of building large scale, highly detailed and realistic volumetric models of neocortical circuits from the morphological skeletons of their digitally reconstructed neurons. The limitations of the existing approaches for creating those models are explained, and then, a multi-stage pipeline is discussed to overcome those limitations. Starting from the neuronal morphologies, we create smooth piecewise watertight polygonal models that can be efficiently utilized to synthesize continuous and plausible volumetric models of the neurons with solid voxelization. The somata of the neurons are reconstructed on a physically-plausible basis relying on the physics engine in Blender.

RESULTS

Our pipeline is applied to create 55 exemplar neurons representing the various morphological types that are reconstructed from the somatsensory cortex of a juvenile rat. The pipeline is then used to reconstruct a volumetric slice of a cortical circuit model that contains ∼210,000 neurons. The applicability of our pipeline to create highly realistic volumetric models of neocortical circuits is demonstrated with an in silico imaging experiment that simulates tissue visualization with brightfield microscopy. The results were evaluated with a group of domain experts to address their demands and also to extend the workflow based on their feedback.

CONCLUSION

A systematic workflow is presented to create large scale synthetic tissue models of the neocortical circuitry. This workflow is fundamental to enlarge the scale of in silico neuroscientific optical experiments from several tens of cubic micrometers to a few cubic millimeters.

AMS SUBJECT CLASSIFICATION

Modelling and Simulation.

Motion invariant contrast enhancement of optical imaging data in the gradient domain

Functional optical imaging (OI) of intrinsic signals (like blood oxygenation coupled reflection changes) and of extrinsic properties of voltage sensitive probes (like voltage-sensitive dyes (VSD)) forms a group of neuroimaging techniques that possess up to date highest temporal and spatial resolution on a meso-to macroscopic scale. An inherent problem of OI is a very low signal to noise ratio (SNR), which restricts the recordings to be completely motionless and requires detailed knowledge of the properties of the different noise sources. In our experiments we performed a durectomy and did not use an imaging chamber to allow us future joint electroencephalography-optical imaging (EEG-OI) measures, which resulted in movement artifacts. With the goal of motion compensation in OI recordings and magnification of signal changes, we present a novel processing pipeline, which is based on optic flow guided denoising and gradient domain tone mapping for spatiotemporal contrast enhancement.

Catching the voltage gradient-asymmetric boost of cortical spread generates motion signals across visual cortex: a brief review with special thanks to Amiram Grinvald

Wide-field voltage imaging is unique in its capability to capture snapshots of activity-across the full gradient of average changes in membrane potentials from subthreshold to suprathreshold levels-of hundreds of thousands of superficial cortical neurons that are simultaneously active. Here, I highlight two examples where voltage-sensitive dye imaging (VSDI) was exploited to track gradual space-time changes of activity within milliseconds across several millimeters of cortex at submillimeter resolution: the line-motion condition, measured in Amiram Grinvald's Laboratory more than 10 years ago and-coming full circle running VSDI in my laboratory-another motion-inducing condition, in which two neighboring stimuli counterchange luminance simultaneously. In both examples, cortical spread is asymmetrically boosted, creating suprathreshold activity drawn out over primary visual cortex. These rapidly propagating waves may integrate brain signals that encode motion independent of direction-selective circuits.

Visual stimulation quenches global alpha range activity in awake primate V4: a case study

Increasing evidence suggests that sensory stimulation not only changes the level of cortical activity with respect to baseline but also its structure. Despite having been reported in a multitude of conditions and preparations (for instance, as a quenching of intertrial variability, Churchland et al., 2010), such changes remain relatively poorly characterized. Here, we used optical imaging of voltage-sensitive dyes to explore, in V4 of an awake macaque, the spatiotemporal characteristics of both visually evoked and spontaneously ongoing neuronal activity and their difference. With respect to the spontaneous case, we detected a reduction in large-scale activity ([Formula: see text]) in the alpha range (5 to 12.5 Hz) during sensory inflow accompanied by a decrease in pairwise correlations. Moreover, the spatial patterns of correlation obtained during the different visual stimuli were on the average more similar one to another than they were to that obtained in the absence of stimulation. Finally, these observed changes in activity dynamics approached saturation already at very low stimulus contrasts, unlike the progressive, near-linear increase of the mean raw evoked responses over a wide range of contrast values, which could indicate a specific switching in the presence of a sensory inflow.

Pyramid approach for the reduction of parallax-related artefacts in optical recordings of moving translucent volumes

Functional optical imaging (OI) of intrinsic signals (like blood oxygenation coupled reflection changes) and of extrinsic properties of voltage sensitive probes (like voltage-sensitive dyes (VSD)) forms a group of invasive neuroimaging techniques, that possess up to date the highest temporal and spatial resolution on a meso- to macroscopic scale. There are different sources that contribute to the OI signal of which many are noise. In our previous works, we have used dense optical flow for the reduction of movement artefacts. The translucent surface of the cortex allows contributions from multiple depths. Due to the depth offield (DOF) effect, we get an implicit relation of depth and 2D frequency components. In this work, we introduce registration on the levels of a Laplacian pyramid to remove movement artefacts which have different motion components in different spatial frequency bands. This aims to resolve artefacts that remain after normal registration and are caused e.g. by parallax motion, dead pixels or dust on the sensor and other high frequent, moving particles on the cortex surface without the compromise of using high smoothness weights.