Abstract

A prominent goal of neuroscience is to improve our understanding of how brain structure and activity interact to produce perception, emotion, behavior, and cognition. The brain’s network activity is inherently organized in distinct spatiotemporal patterns that span scales from nanometer-sized synapses to meter-long nerve fibers and millisecond intervals between electrical signals to decades of memory storage. There is currently no single imaging method that alone can provide all the relevant information, but intelligent combinations of complementary techniques can be effective. Here, we thus present the latest advances in biomedical and biological engineering on photoacoustic neuroimaging in the context of complementary imaging techniques. A particular focus is placed on recent advances in whole-brain photoacoustic imaging in rodent models and its influential role in bridging the gap between fluorescence microscopy and more non-invasive techniques such as magnetic resonance imaging (MRI). We consider current strategies to address persistent challenges, particularly in developing molecular contrast agents, and conclude with an overview of potential future directions for photoacoustic neuroimaging to provide deeper insights into healthy and pathological brain processes.

Highlights

  • Understanding the mechanisms by which the brain gives rise to inner experience, cognition, and behavior remains a central objective of fundamental neuroscience, which will strongly foster advances in causal therapies of neuropsychiatric diseases.Mapping spatiotemporal patterns across the vastly different granularities of the brain becomes increasingly important for testing specific circuit models and monitoring pathological processes and therapeutic interventions (Friston, 1994; Sporns et al, 2005; Sporns, 2013).As a still younger imaging technique, photoacoustic imaging is entering a crowded field of specialized anatomical and functional imaging modalities

  • This review focuses mainly on photoacoustics’ current capabilities for preclinical brain imaging to extract physiological and molecular contrast and on how the modality can synergize with complementary neuroimaging techniques

  • It is useful to differentiate between the following molecular contrast agent classes with respect to which molecular state or process they indicate: (i) targetable labels that can map the biodistribution of a target structure, (ii) turn-on probes, whose signal can be irreversibly activated by a molecular interaction, and (iii) reversible sensors, which can dynamically adopt different signaling states in response to an analyte of interest (Figure 2, columns)

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Summary

Frontiers in Neuroscience

A prominent goal of neuroscience is to improve our understanding of how brain structure and activity interact to produce perception, emotion, behavior, and cognition. The brain’s network activity is inherently organized in distinct spatiotemporal patterns that span scales from nanometer-sized synapses to meter-long nerve fibers and millisecond intervals between electrical signals to decades of memory storage. There is currently no single imaging method that alone can provide all the relevant information, but intelligent combinations of complementary techniques can be effective. We present the latest advances in biomedical and biological engineering on photoacoustic neuroimaging in the context of complementary imaging techniques. We consider current strategies to address persistent challenges, in developing molecular contrast agents, and conclude with an overview of potential future directions for photoacoustic neuroimaging to provide deeper insights into healthy and pathological brain processes

INTRODUCTION
IMAGING BASED ON THE PHOTOACOUSTIC EFFECT
DETECTION GEOMETRIES FOR PHOTOACOUSTIC NEUROIMAGING
Volumetric PA
Ex vivo Anatomy
In vivo Anatomy
Neurodegenerative Diseases
IMAGING OF BRAIN HEMODYNAMICS
MOLECULAR CONTRAST FOR PHOTOACOUSTIC NEUROIMAGING
Desired Properties of Molecular Contrast Agents for PA
Intravascular Contrast Agents
Pigment relocalization sensors
Targetable Labels
Dynamic Sensors
TOWARD TRANSLATION TO CLINICAL PA NEUROIMAGING
Findings
CONCLUSIONS
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