One commonly used approach to image fluorescently reported neuronal dynamics is 2-photon microscopy30 (link). This technique utilizes low energy near infrared (IR) photons to penetrate highly light-scattering brain tissue up to 600–700 μm below the surface of the brain31 (link). A significant advantage of 2-photon microscopy is the ability to selectively excite fluorophores within a well-defined focal plane, resulting in a spatial resolution capable of resolving cellular activity within precisely defined anatomical sub-regions of neurons, such as dendrites and axonal boutons30 (link). Notably, although this imaging modality provides superior spatial resolution, it requires the head fixation of animals and, in the absence of a microendoscope or optical cannula, 2-photon imaging is limited to superficial layers of the brain32 (link),33 (link). Together, these behavioral and optical limitations greatly reduce the scope of scientific questions that can be examined with 2-photon microscopy.
Implantation of small, lightweight fiber optics above a region of interest, such as with fiber photometry, circumvents optical and behavioral limitations posed by 2-photon microscopy34 (link). However, unlike 2-photon microscopy, fiber photometry lacks cellular level resolution and provides only aggregate activity within the field of view (i.e., bulk changes in fluorescent signal)22 . Thus, this method is better suited for monitoring dynamic activity within neural projection fields35 (link). In addition to limitations in optical resolution, fiber photometry requires the test subject to be secured to a rigid fiber optic bundle, which can be difficult for small mammals, such as mice, to maneuver34 (link). Thus, while fiber photometry increases the depth in which neural activity can be monitored, it presents significant limitations in optical resolution, restricts the natural behavioral repertoire of an animal, and limits the animal models that can be optimally utilized.
Large-scale recordings of neural activity within freely behaving mammals36 (link) can also be conducted with techniques that do not rely on the use of fluorescence indicators of neural activity, such as in vivo electrophysiological recordings2 (link). Importantly, compared to in vivo Ca2+ imaging, electrophysiology provides superior temporal resolution, allowing for more accurate spike timing estimations17 (link),37 (link),38 (link) as well as the correlation of neural activity with precisely defined temporal events. In addition, in vivo electrophysiology can be combined with optogenetic perturbations of genetically defined neuronal populations to permit the identification (although not unequivocally) and manipulation of defined neuronal populations39 –41 (link). The ability to monitor and subsequently manipulate a circuit is particularly important to the study of brain function as it allows the causal role of identified computations to be elucidated. Thus, compared to freely behaving in vivo optical imaging methods, in vivo electrophysiology methods offer advantages in the domain of temporal resolution as well as technological integration. One notable limitation of this method is that the spatial location of monitored cells cannot be visualized, making it difficult to assert that an identified cell is similar or unique across recording sessions1 (link). Moreover, because in vivo electrophysiology relies on waveform shapes to differentiate individual cells from each other, it can be challenging to detect cells with sparse firing patterns or that are located within densely populated networks. Finally, the number of cells that can be detected with in vivo electrophysiology methods is often far less than the number of cells that can be monitored with the optical imaging methods described in this protocol29 (link),42 (link). Taken together, these limitations in cell identification and statistical power pose a significant disadvantage for studies that require chronic monitoring of neural activity.
Implantation of small, lightweight fiber optics above a region of interest, such as with fiber photometry, circumvents optical and behavioral limitations posed by 2-photon microscopy34 (link). However, unlike 2-photon microscopy, fiber photometry lacks cellular level resolution and provides only aggregate activity within the field of view (i.e., bulk changes in fluorescent signal)22 . Thus, this method is better suited for monitoring dynamic activity within neural projection fields35 (link). In addition to limitations in optical resolution, fiber photometry requires the test subject to be secured to a rigid fiber optic bundle, which can be difficult for small mammals, such as mice, to maneuver34 (link). Thus, while fiber photometry increases the depth in which neural activity can be monitored, it presents significant limitations in optical resolution, restricts the natural behavioral repertoire of an animal, and limits the animal models that can be optimally utilized.
Large-scale recordings of neural activity within freely behaving mammals36 (link) can also be conducted with techniques that do not rely on the use of fluorescence indicators of neural activity, such as in vivo electrophysiological recordings2 (link). Importantly, compared to in vivo Ca2+ imaging, electrophysiology provides superior temporal resolution, allowing for more accurate spike timing estimations17 (link),37 (link),38 (link) as well as the correlation of neural activity with precisely defined temporal events. In addition, in vivo electrophysiology can be combined with optogenetic perturbations of genetically defined neuronal populations to permit the identification (although not unequivocally) and manipulation of defined neuronal populations39 –41 (link). The ability to monitor and subsequently manipulate a circuit is particularly important to the study of brain function as it allows the causal role of identified computations to be elucidated. Thus, compared to freely behaving in vivo optical imaging methods, in vivo electrophysiology methods offer advantages in the domain of temporal resolution as well as technological integration. One notable limitation of this method is that the spatial location of monitored cells cannot be visualized, making it difficult to assert that an identified cell is similar or unique across recording sessions1 (link). Moreover, because in vivo electrophysiology relies on waveform shapes to differentiate individual cells from each other, it can be challenging to detect cells with sparse firing patterns or that are located within densely populated networks. Finally, the number of cells that can be detected with in vivo electrophysiology methods is often far less than the number of cells that can be monitored with the optical imaging methods described in this protocol29 (link),42 (link). Taken together, these limitations in cell identification and statistical power pose a significant disadvantage for studies that require chronic monitoring of neural activity.
