Abstract
In the past decade, the idea that single populations of neurons support cognition and behavior has gradually given way to the realization that connectivity matters and that complex behavior results from interactions between remote yet anatomically connected areas that form specialized networks. In parallel, innovation in brain imaging techniques has led to the availability of a broad set of imaging tools to characterize the functional organization of complex networks. However, each of these tools poses significant technical challenges and faces limitations, which require careful consideration of their underlying anatomical, physiological, and physical specificity. In this review, we focus on emerging methods for measuring spontaneous or evoked activity in the brain. We discuss methods that can measure large-scale brain activity [directly or indirectly] with a relatively high temporal resolution, from milliseconds to seconds. We further focus on methods designed for studying the mammalian brain in preclinical models, specifically in mice and rats. This field has seen a great deal of innovation in recent years, facilitated by concomitant innovation in gene-editing techniques and the possibility of more invasive recordings. This review aims to give an overview of currently available preclinical imaging methods and an outlook on future developments. This information is suitable for educational purposes and for assisting scientists in choosing the appropriate method for their own research question.
Introduction
Galaxies of thought, cognition, and movement
The observation of natural phenomena is the basis of modern scientific thought, and a common approach to all scientific disciplines, from astronomy to neuroscience. Through observations, we can generate, confirm, extend or challenge theories and models of how nature works. And just as telescopes are the means of unlocking the secrets of outer space, our understanding of the brain depends on the methods we use to observe its constituent elements and study how they interact with each other, creating galaxies of thought, cognition and movement. While there is no single technique [yet] capable of observing all these phenomena, there are many technologies at our disposal to study brain activity across multiple temporal and spatial dimensions [Fig. 1].
Fig. 1: The spatiotemporal overview of imaging techniques used for studying rodent whole-brain function.
Each colored box represents the approximate spatiotemporal scope of the labeled technique. Light blue colored boxes represent techniques covered in this review, while gray boxes techniques are not covered. EEG electroencephalography, MEG magnetoencephalography, PET positron emission tomography, 2-DG 2-deoxyglucose, fUS functional ultrasound, fMRI functional magnetic resonance imaging.
Full size image
The basic substrate used by the brain to transmit information is represented by electrical events called neuronal spikes and the release of chemical neurotransmitters in the synaptic terminals. Decades of [electro]physiological research facilitated by in vitro preparations, neuronal cell cultures or organoids, and in vivo recordings have advanced our understanding of the mechanisms that drive neurons to fire and transmit their signals through the network. Although neuronal rhythmicity has an essential role in facilitating information processing across spatial and temporal hierarchies in the brain [1], individual neural spikes per se are too weak to influence complex behavior [with notable exceptions] [2]. If our cognition really depended on individual spikes, we would deal with a poorly defined, high-dimensional system, not suitable for life. According to this view, correlates between the activity of a single neuron and a specific cognitive process provide a limited description of the causal relationship between brain activity and behavior [3]. Thus, it seems increasingly likely that the brain does not use actual spike coding but population—or neural ensembles—coding that unfolds on a limited, low-dimensional portion of the full neural space [4, 5]. As information flows through the brain, population activity is further integrated into large-scale networks via the connectome [6]. The result is that large numbers of brain regions are active during every aspect of cognition and behavior.
Since one of the more tractable goals of quantitative neuroscience is to develop predictive models that relate brain activity to behavior, observing activity, and dynamics in neural networks—possibly in multiple brain areas—can get us closer to this goal. To do that, scientists and engineers have developed an array of methods capable of looking at whole-brain activity from a zoomed-out perspective. In this review, we aim to provide the reader with an overview of the emerging methods for observing system and network-level brain function in rodents. Although this article is not designed to provide a full review of the literature, history, and physics behind each method, we distill the nature and the unique features of each technique and comment on their use and potential for future expansion and of course, their limitations. We wrote this article for scientists who want to expand their view on preclinical imaging methods, are looking for the appropriate method to address their research question, and for didactical purposes.
Functional MRI
Functional magnetic resonance imaging [fMRI] is one of the leading techniques to study whole-brain function in humans. Its first description dates back to the early 1990s, when Ogawa and colleagues [7] described the principles of blood oxygen level-dependent [BOLD] magnetic resonance imaging [MRI]: local changes in the neuronal activity require a dynamic supply of oxygen and glucose, provided by a highly dense vascular system. More specifically, the process of neurovascular coupling, which entails the acute regulation of cerebral blood flow [CBF] via vasoactive molecules and neural messengers, ensures that this change in energetic demand is met [extensively reviewed in refs. [8,9,10,11]]. To this day, much research effort is directed to the identification of cellular and molecular messengers that communicate neuronal activity to the vasculature, helping us understand cerebrovascular regulation and more accurately interpret observed fMRI signals [12,13,14,15,16,17]. Ultimately, regional alterations in CBF influence the ratio of oxygenated vs deoxygenated hemoglobin, whose distinct magnetic properties give rise to the BOLD signal. It is the paramagnetic properties of the deoxyhemoglobin that cause magnetic susceptibility inside blood vessels and surrounding tissue, thus affecting the magnetic field and the spin-spin relaxation time [T2/T2*].
MRI sequences that are sensitive to the T2*, such as gradient echo [GRE] echo-planar imaging [EPI], are often used for studying the fast dynamics of hemodynamic responses with a spatial resolution of ~1–3 mm and with a temporal resolution of ~1–3 s [18, 19]. In 1995, Biswal et al. [20] showed that also slow [