Exploring two-photon optogenetics beyond 1100 nm for specific and effective all-optical physiology

The selfish network: how the brain preserves behavioral function through shifts in neuronal network state

Neuronal networks possess the ability to regulate their activity states in response to disruptions. How and when neuronal networks turn from physiological into pathological states, leading to the manifestation of neuropsychiatric disorders, remains largely unknown. Here, we propose that neuronal networks intrinsically maintain network stability even at the cost of neuronal loss. Despite the new stable state being potentially maladaptive, neural networks may not reverse back to states associated with better long-term outcomes. These maladaptive states are often associated with hyperactive neurons, marking the starting point for activity-dependent neurodegeneration. Transitions between network states may occur rapidly, and in discrete steps rather than continuously, particularly in neurodegenerative disorders. The self-stabilizing, metastable, and noncontinuous characteristics of these network states can be mathematically described as attractors. Maladaptive attractors may represent a distinct pathophysiological entity that could serve as a target for new therapies and for fostering resilience.

ViNe-Seg: deep-learning-assisted segmentation of visible neurons and subsequent analysis embedded in a graphical user interface

SUMMARY

Segmentation of neural somata is a crucial and usually the most time-consuming step in the analysis of optical functional imaging of neuronal microcircuits. In recent years, multiple auto-segmentation tools have been developed to improve the speed and consistency of the segmentation process, mostly, using deep learning approaches. Current segmentation tools, while advanced, still encounter challenges in producing accurate segmentation results, especially in datasets with a low signal-to-noise ratio. This has led to a reliance on manual segmentation techniques. However, manual methods, while customized to specific laboratory protocols, can introduce variability due to individual differences in interpretation, potentially affecting dataset consistency across studies. In response to this challenge, we present ViNe-Seg: a deep-learning-based semi-automatic segmentation tool that offers (i) detection of visible neurons, irrespective of their activity status; (ii) the ability to perform segmentation during an ongoing experiment; (iii) a user-friendly graphical interface that facilitates expert supervision, ensuring precise identification of Regions of Interest; (iv) an array of segmentation models with the option of training custom models and sharing them with the community; and (v) seamless integration of subsequent analysis steps.

AVAILABILITY AND IMPLEMENTATION

ViNe-Seg code and documentation are publicly available at https://github.com/NiRuff/ViNe-Seg and can be installed from https://pypi.org/project/ViNeSeg/.

Watt-level all polarization-maintaining femtosecond fiber laser source at 1100 nm

We demonstrate a compact watt-level all polarization-maintaining (PM) femtosecond fiber laser source at 1100 nm. The fiber laser source is seeded by an all PM fiber mode-locked laser employing a nonlinear amplifying loop mirror. The seed laser can generate stable pulses at a fundamental repetition rate of 40.71 MHz with a signal-to-noise rate of >100 dB and an integrated relative intensity noise of only ∼0.061%. After two-stage external amplification and pulse compression, an output power of ∼1.47 W (corresponding to a pulse energy of ∼36.1 nJ) and a pulse duration of ∼251 fs are obtained. The 1100 nm femtosecond fiber laser is then employed as the excitation light source for multicolor multi-photon fluorescence microscopy of Chinese hamster ovary (CHO) cells stably expressing red fluorescent proteins.

Network response of brain microvasculature to neuronal stimulation

Neurovascular coupling (NVC), or the adjustment of blood flow in response to local increases in neuronal activity is a hallmark of healthy brain function, and the physiological foundation for functional magnetic resonance imaging (fMRI). However, it remains only partly understood due to the high complexity of the structure and function of the cerebrovascular network. Here we set out to understand NVC at the network level, i.e. map cerebrovascular network reactivity to activation of neighbouring neurons within a 500×500×500 μm3 cortical volume (∼30 high-resolution 3-nL fMRI voxels). Using 3D two-photon fluorescence microscopy data, we quantified blood volume and flow changes in the brain vessels in response to spatially targeted optogenetic activation of cortical pyramidal neurons. We registered the vessels in a series of image stacks acquired before and after stimulations and applied a deep learning pipeline to segment the microvascular network from each time frame acquired. We then performed image analysis to extract the microvascular graphs, and graph analysis to identify the branch order of each vessel in the network, enabling the stratification of vessels by their branch order, designating branches 1-3 as precapillary arterioles and branches 4+ as capillaries. Forty-five percent of all vessels showed significant calibre changes; with 85 % of responses being dilations. The largest absolute CBV change was in the capillaries; the smallest, in the venules. Capillary CBV change was also the largest fraction of the total CBV change, but normalized to the baseline volume, arterioles and precapillary arterioles showed the biggest relative CBV change. From linescans along arteriole-venule microvascular paths, we measured red blood cell velocities and hematocrit, allowing for estimation of pressure and local resistance along these paths. While diameter changes following neuronal activation gradually declined along the paths; the pressure drops from arterioles to venules increased despite decreasing resistance: blood flow thus increased more than local resistance decreases would predict. By leveraging functional volumetric imaging and high throughput deep learning-based analysis, our study revealed distinct hemodynamic responses across the vessel types comprising the microvascular network. Our findings underscore the need for large, dense sampling of brain vessels for characterization of neurovascular coupling at the network level in health and disease.

Optogenetics 2.0: challenges and solutions towards a quantitative probing of neural circuits

To exploit the full potential of optogenetics, we need to titrate and tailor optogenetic methods to emulate naturalistic circuit function. For that, the following prerequisites need to be met: first, we need to target opsin expression not only to genetically defined neurons per se, but to specifically target a functional node. Second, we need to assess the scope of optogenetic modulation, i.e. the fraction of optogenetically modulated neurons. Third, we need to integrate optogenetic control in a closed loop setting. Fourth, we need to further safe and stable gene expression and light delivery to bring optogenetics to the clinics. Here, we review these concepts for the human and rodent brain.

Effects of optogenetic inhibition of a small fraction of parvalbumin-positive interneurons on the representation of sensory stimuli in mouse barrel cortex

Inhibitory interneurons play central roles in the modulation of spontaneous network activity and in processing of neuronal information. In sensory neocortical areas, parvalbumin-positive (PV+) GABAergic interneurons control the representation and processing of peripheral sensory inputs. We studied the functional role of PV+ interneurons in the barrel cortex of anesthetized adult PVCre mice by combining extracellular multi-electrode recordings with optogenetic silencing of a small fraction of PV+ interneurons. In all cortical layers, optogenetic inhibition caused an increase in spontaneous network activity from theta to gamma frequencies. The spatio-temporal representation of sensory inputs was studied by stimulating one or two whiskers at different intervals and analyzing the resulting local field potential (LFP) and single unit (SU) response. Silencing PV+ interneurons caused an increase in LFP response to sensory stimulation and a decrease in temporal discrimination of consecutive whisker deflections. The combined effect of whisker deflection and optogenetic inhibition was highly similar to the linear sum of the individual effects of these two manipulations. SU recordings revealed that optogenetic silencing reduced stimulus detectability by increasing stimulus-evoked firing rate by a constant offset, suggesting that PV+ interneurons improve signal-to-noise ratio by reducing ongoing spiking activity, thereby sharpening the spatio-temporal representation of sensory stimuli.

Beyond correlation: functional OPTO-MAgnetic Integration Concept (OPTOMAIC) to reveal the brain-wide signature of local neuronal signals-of-interest

Significance: Due to the vascular origin of the fMRI signal, the spatiotemporally precise interpretation of the blood oxygen level-dependent (BOLD) response as brain-wide correlate of neuronal activity is limited. Optical fiber-based neuronal calcium recordings provide a specific and temporally highly resolved signal yet lacking brain-wide coverage. The cross-modal integration of both modalities holds the potential for unique synergies. Aim: The OPTO-MAgnetic Integration Concept (OPTOMAIC) extracts the very fraction of the BOLD response that reacts to optically recorded neuronal signals-of-interest. Approach and Results: First, OPTOMAIC identifies the trials containing neuronal signal-of-interest (SoI) in the optical recordings. The long duration of the BOLD response is considered by calculating and thresholding neuronal interevent intervals. The resulting optical regression vector is probed for a positive BOLD response with single-event and single-voxel resolution, generating a BOLD response matrix containing only those events and voxels with both a neuronal SoI and a positive fMRI signal increase. Last, the onset of the BOLD response is being quantified, representing the section of the BOLD response most reliably reporting at least components of the neuronal signal. Conclusions: The seven OPTOMAIC steps result in a brain-wide BOLD signature reflecting the underlying neuronal SoI with utmost cross-modal integration depth and taking full advantage of the specific strengths of each method.

Pipeline for 2-photon all-optical physiology in mouse: From viral titration and optical window implantation to binarization of calcium transients

2-photon all-optical physiology combines in vivo 2-photon calcium imaging and optogenetics, which enables both the read out and manipulation of neuronal microcircuits with single-cell resolution. Here, we describe a protocol for achieving optimized co-expression of calcium indicator and opsin. To enable longitudinal designs, we introduce a template for virus injection and chronic window implantation. We also highlight key aspects of performing 2-photon imaging and suggest an analysis algorithm for the binarization of putatively action-potential (AP)-related calcium transients. For complete details on the use and execution of this protocol, please refer to Fu et al. (2021).