Light Beads Microscopy is a new method of two-photon microscopy optimized for volume imaging. It enables investigators to scan an entire volume in the rate that other conventional mesoscopes records just a single plane. This new technique makes use of columns of “Light Beads”, individual beams which are distinguishable in time and focus to different depths in the sample. Their novel approach uses 30 multiplexed beams, roughly an order of magnitude higher than any other previous temporal multiplexing approach demonstrated in vivo.  This quantum leap in imaging efficiency makes Light Beads Microscopy well suited for studying multi-regional encoding of sensory information and the dynamic interaction of brain networks at the single-neuron level.

Using Light Beads Microscopy and genetically encoded calcium indicators, Demas and colleagues imaged calcium transients in hundreds of thousands of cells in vivo, in portions of somatosensory-, visual-, posterior parietal-, and retro splenial–cortex, contained in a 3 mm X 5 mm area and a depth of 0.5 mm. The sampling rate of 5 Hz was per volume, not per plane. Stimuli used were whiskers perturbation and visual presentation of high-contrast drifting grates. Three sub-populations of neurons were identified that respond to whiskers stimuli, visual stimuli, or are spontaneously active. They also found evidence of mixed-selectivity in four anatomically separate clusters of cells, and of neurons that undergo distinct types of response modulation to one stimulus by the other located in separate anatomical locations.

To make the multiplexing happen, the laser light pulse is sent through two series of optical cavities that contain convex mirrors. The first cavity lets a small fraction of the energy of the laser pulse escape to the second cavity through a partially reflecting mirror (PRM) but sends the bulk of the laser energy back into the first cavity through a delay line loop created by the convex mirrors until it encounters the PRM again. The second cavity, which functions mainly as a delay line, splits the incoming pulse into two pulses. The first pulse is directed to the sample, while the second is delayed by the cavity before also being sent to the microscope. By travelling over and over in the first cavity and dividing pulses in the second one as described, a 90fs laser pulse is split into thirty ‘sub- pulses’ that occur only about 7ns apart from each other, with all 30 sub-pulses delivered to the sample in ~200ns.  MBF Bioscience engineers created the software for the Light Beads Microscope using ScanImage. This software was used to control the hardware and to receive and assemble the signals multiplexed in time and space from the photomultiplier tube.

Here at MBF Bioscience, thanks to a Small Business Innovation Research Grant from the NIMH, we are now working to commercialize this technology. We plan to optimize the hardware that creates the lights beads to reduce the overall microscope-system footprint and make it more versatile and easily adaptable to other laser-scanning microscopes and/or excitation wavelengths.

Light Beads Microscopy represents a major breakthrough in our ability to study the activity of large cell populations in the brain, and has the potential to revolutionize our understanding of how the brain encodes information.

Learn more about ScanImage and how it can help your research at: https://www.mbfbioscience.com/products/scanimage.

Reference:

Demas, J., Manley, J., Tejera, F. et al. High-speed, cortex-wide volumetric recording of neuroactivity at cellular resolution using light beads microscopy. Nat Methods 18, 1103–1111 (2021). https://doi.org/10.1038/s41592-021-01239-8

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The radical new advantage of the Mini2P microscope is its light weight and the flexibility of its laser-cable. With heavier microscopes, for instance when used for imaging neurons in the striatum (Maltese et al. 2021), animals are restricted to less active behaviors such as walking on a treadmill, but with the extremely light weight Mini2P, in-vivo imaging, for instance of ‘place-cells’ in the hippocampus, can be done on animals engaging in much more active behaviors, such as finding their way through a maze (Zong et al.).

ScanImage software gives efficient control of the Mirrorcle (Mirrorcle Technologies, Inc., Richmond CA) MEM scanner for XY imaging, the electronically-tunable µTlens for focusing, and laser beam power. ScanImage receives the resulting data from photo-multiplier-tubes (PMTs) and assembles images of functioning neurons. The input and output signals for this in-vivo imaging are controlled with and exchanged between ScanImage and the hardware via the VDAQ card and breakout board.

Proof of concept is shown in, ‘Large-scale two-photon calcium imaging in freely moving mice,’ by Zong et al., published this year: ScanImage … fully supports the hardware control and data acquisition of MINI2P. Following the wiring illustration and the operation manual in Methods S1, Section 9, the system can be run directly without further modification. (Zong et al., Control and Acquisition, p. e9)

The just three-gram 2P miniscope with its flexible fiber laser cable attached was shown to be light enough for active behavorial experiments. Three-dimensional imaging of fluorescence indicating cellular calcium concentration in visual cortex, hippocampus archicortex, and hippocampus was done at 7.5 Hz. The mice were so unencumbered as to be considered freely moving, and ‘place-cells’ in the hippocampus were seen to undergo changes in calcium concentration correlated with the animals’ position in the maze.

How does ScanImage accomplish control and acquisition? The mirrorcle resonant scanner driver is intended for use with a MEMS mirror device. This driver enables one of the axes, the X axis, of the mirror to be used in resonant scanning mode. To use the second axis, the Y axis, of the mirror, an Analog Galvo device is added to ScanImage. ScanImage takes the information about the fast X axis mirror position and uses it to calculate and send the signal for the relatively slow Y axis mirror. Two analog outputs of vDAQ send the MEMS scanning control signal (fast axial and slow axial) to the mirror device. A third analog output sends the control signal to the µTlens driver (Thorlabs, Newton, NJ). A fourth analog output sends the laser power control signal to the laser controller. The laser source was a compact, single-wavelength, fiber-based femtosecond laser (FemtoFiber Ultra 920, Toptica, Munich, Germany). For acquisition, the signals from two-channel PMTs are connected to two high-speed (125 MHz) analog inputs of the vDAQ card. A maximum of 4 channels can be acquired simultaneously. ScanImage organizes the PMT data to form the images.

The process of imaging functioning neurons in freely behaving animals is incredibly powerful, but also exceedingly complex. ScanImage software can simplify these procedures and make the control of in-vivo image acquisition easily executable.

To learn more about how ScanImage controls the Mini2P, click here to see the workshop given by ScanImage product manager, Mitchell Sandoe.

Reference:

Maltese, Marta, Jeffrey R March, Alexander G Bashaw, Nicolas X Tritsch, 2021, Dopamine differentially modulates the size of projection neuron ensembles in the intact and dopamine-depleted striatum.  https://doi.org/10.7554/eLife.68041

Zong, Weijian, Horst A Obenhaus , Emilie R Skytøen, Hanna Eneqvist, Nienke L de Jong, Ruben Vale, Marina R Jorge, May-Britt Moser, Edvard I Moser, 2022, Large-scale two-photon calcium imaging in freely moving mice. Cell, 185(7):1240-1256.e30. doi: 10.1016/j.cell.2022.02.017. Epub 2022 Mar 18.

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Dopamine (DA) is well known to enable nerve cells to communicate with each other in the brain. In an effort to go deeper into understanding this process, the research team led by Dr. Marta Maltese, used two-photon calcium imaging to monitor activity in the brains of mice. As the mice ran on a treadmill, the scientists observed activity among the two types of neurons — the ones that incited movement, and the ones that directed a muscle to be still.

“This research is amazing because the activity of the neurons that create a balance between moving a muscle and not moving a muscle can be seen through the microscope while the mouse is moving on the treadmill,” says MBF Bioscience Research Liaison Dr. Dan Peruzzi. “Not only could they see the activity of the neurons, they could also differentiate which neurons activate the ‘do not move the muscle’ instructions and which neurons send signals to ‘move the muscle’.

Imaging striatal activity using two-photon microscopy or photometry.

The researchers found that when the mouse was on the treadmill, an equal number of both types of neurons were activated. But when they introduced drugs that reduced dopamine levels, mimicking what happens in Parkinson’s disease, the balance was upset — more of the neurons that tell a muscle not to move were activated.

“Our imaging approach therefore offers the ability to simultaneously monitor and compare the activity of hundreds of striatal neurons (mean ± SEM: 327 ± 13 per field of view, range: 131–442) belonging to both direct and indirect pathways with high spatial resolution during a simple behavior… Our results reveal that, in addition to its effects on firing rates, DA regulates striatal output by reconfiguring its movement-related ensemble code.” (Maltese et.al., 2021)

Maltese, M., March, J. R., Bashaw, A. G., & Tritsch, N. X. (2021). Dopamine differentially modulates the size of projection neuron ensembles in the intact and dopamine-depleted striatum. eLife, 10, e68041. https://doi.org/10.7554/eLife.68041

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However, a new study published in Nature, challenges Hebb’s theory. Conducted by researchers at the Max Planck Florida Institute for Neuroscience, the authors demonstrate that synapse size is not correlated with the response similarity between input and output and suggest that neural response properties reflect the total number of active synapses, both weak and strong.

Combining in vivo two-photon synaptic imaging and electron microscopy, the scientists measured the strength of excitatory inputs contacting pyramidal neurons in the primary visual cortex of the ferret brain. “These findings were made possible by the RMR scanner and ScanImage software, which allowed flexible and simultaneous in vivo recording of a large number of synapses,” explained Dr. Scholl. “In particular, this technology allowed sampling from long dendritic segments, recording multiple dendritic locations simultaneously, at synaptic resolution.”

a, In vivo two-photon synaptic imaging of L2/3 cortical neurons in ferret visual cortex expressing GCaMP6s is performed under visual stimulation.

Using electron microscopy reconstruction of individual synapses as a metric of strength, we find no evidence that strong synapses have a predominant role in the selectivity of cortical neuron responses to visual stimuli. Instead, selectivity appears to arise from the total number of synapses activated by different stimuli. Moreover, spatial clustering of co-active inputs appears to be reserved for weaker synapses, enhancing the contribution of weak synapses to somatic responses. Our results challenge the role of Hebbian mechanisms in shaping neuronal selectivity in cortical circuits, and suggest that selectivity reflects the co-activation of large populations of presynaptic neurons with similar properties and a mixture of strengths. (Scholl, et.al. 2021)

For more about how ScanImage can help with your research, visit our website.

Citation:

Scholl, B., Thomas, C.I., Ryan, M.A. et al. Cortical response selectivity derives from strength in numbers of synapses. Nature 590, 111–114 (2021). https://doi.org/10.1038/s41586-020-03044-3

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A recent paper by Wilson et. al (Nature Neuroscience, 2016) used elegant 2-photon imaging studies to shed new light on the complex mechanisms of visual cortex response to visual stimuli. The now classic studies by Hubel and Wiesel in the 1960s established that there are orientation selective neuronal responses arranged in columnar systems within the visual cortex of cats and monkeys. This work has been extended by other investigators into additional species and detailed neuronal maps have been created documenting the physical location of neurons that respond selectively to the orientation of edges. Over the decades several studies have attempted to elucidate the mechanism by which this type of selective neuronal activity can arise in response to visual stimuli. Like other studies, work by Wilson et. al at The Max Planck Florida Institute for Neuroscience confirmed that both neuronal soma and spines demonstrate orientation selective activity. As the authors noted, “The orientation preference of the summed spine inputs strongly predicted somatic orientation preference…” However, orientation selectivity was not completely explained by a simple summation of synaptic inputs. Through detailed imaging studies the authors demonstrated that the activity and clustering of co-tuned synaptic inputs within dendritic branches was a critical component of the mechanism that gives rise to selective somatic activity.

Dendritic spine imaging using ScanImage

The data that supports the conclusions in the Wilson et. al paper resulted from imaging more than 2,000 dendritic spines in eight animals using ScanImage on a Thorlabs b-scope.(add Figure here) The ScanImage, b-scope combination provides several technical advantages when performing this type of experiment. First, the 2 inch optical path of the b-scope provides exceptional light gathering and resolving capabilities allowing small synaptic structures to be nicely resolved. In addition, ScanImage provides the fast and sensitive data acquisition pipeline necessary not only for producing a crisp image but also for synchronizing with external data streams that are necessary for performing the overall experiment. In order to determine orientation selective somatic or spine activity, accurate time synchronization has to be maintained between imaging and the visual stimulus display. Wilson et. al. also described using ScanImage frame triggers to synchronize experimental workflow with the electrophysiology software Spike2. Vidrio engineers have invested 100’s of hours working directly with scientists to understand and optimize how ScanImage handles complex workflows like that described by Wilson et. al.

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