Whole-brain functional ultrasound imaging in awake head-fixed mice
Authors: Cl√©ment Brunner
Alan Urban
Emilie Mac√©
Gabriel Montaldo
Botond Roska
Micheline Grillet
Journal: Nature Protocols (2021)
Discipline: BIOLOGY & BIOCHEMISTRY
Keywords: brain-wide activity; functional ultrasound imaging; awake head-fixed mice; cerebral blood volume dynamics; chronic cranial window
Affiliations: Neuro-Electronics Research Flanders, Leuven, Belgium., VIB, Leuven, Belgium., Imec, Leuven, Belgium., Department of Neurosciences, KU Leuven, Leuven, Belgium., Institute of Molecular and Clinical Ophthalmology Basel, Basel, Switzerland., University of Basel, Basel, Switzerland., NCCR Molecular Systems Engineering, Basel, Switzerland., Neuro-Electronics Research Flanders, Leuven, Belgium. ., VIB, Leuven, Belgium. ., Imec, Leuven, Belgium. ., Department of Neurosciences, KU Leuven, Leuven, Belgium. ., Brain-Wide Circuits for Behavior Lab, Max Planck Institute of Neurobiology, Martinsried, Germany. .

Abstract:  Most brain functions engage a network of distributed regions. Full investigation of these functions thus requires assessment of whole brains; however, whole-brain functional imaging of behaving animals remains challenging. This protocol describes how to follow brain-wide activity in awake head-fixed mice using functional ultrasound imaging, a method that tracks cerebral blood volume dynamics. We describe how to set up a functional ultrasound imaging system with a provided acquisition software (miniScan), establish a chronic cranial window (timing surgery: ~3-4 h) and image brain-wide activity associated with a stimulus at high resolution (100 √ó 110 √ó 300 ¬µm and 10 Hz per brain slice, which takes ~45 min per imaging session). We include codes that enable data to be registered to a reference atlas, production of 3D activity maps, extraction of the activity traces of ~250 brain regions and, finally, combination of data from multiple sessions (timing analysis averages ~2 h). This protocol enables neuroscientists to observe global brain processes in mice. 

Retracted: No

PubPeer comments:
 In step 51: Run the function `map_statistics` (see `example06_multisession_map.m`) to compute the mean value $C_{mean}$, the standard deviation $sigma$ and the *t*-score $t_{score}$ of $C_i$ in each voxel $$C_{mean}(x, y, z) = frac{1}{N}sum_{i = 1}^N C_i(x, y, z),$$ $$sigma^2(x, y, z) = frac{1}{N}sum_{i = 1}^Nleft(C_i(x, y, z) - C_{mean}(x, y, z)right)^2,$$ $$t_{score}(x, y, z) = frac{C_{mean}(x, y, z)}{sigma(x, y, z)}.$$ Then, compute the *P* value with a Studentu2019s distribution $$p(x, y, z) = 1 - tcdf(t_{score}(x, y, z), N).$$ where $tcdf$ is the cumulative distribution function of the Studentu2019s *t* distribution. For a low number $N$, a pixel is considered significantly activated if $P 0.05$. For larger numbers, one should apply a post hoc multiple comparison of the *P* value (e.g., Bonferroni, false discovery rate) to avoid false positives. Looking at the given equations used to compute the activity maps, $N$ refers to the number of sessions, not the number of statistical tests. In fact, looking at the provided example in `example06_multisession_map.m` and associated data in `maps8sessions.mat`, activity maps should be of size $160times 228times 7$ (7 planes of $160times 228$ voxels). Thus, $160times 228times 7 = 255360$ *t*-tests would be performed to assess statistical significance of all voxels (less if the authors were to use a brain mask). Correction for multiple comparisons is mandatory for such a high amount of tests, as is the case in most other fMRI and fUS studies (see [this introduction] to Random Field Theory for a more sophisticated approach to multiple comparisons correction in fMRI data that can also be applied to fUS). If we were to use the Bonferroni correction, as the authors suggest, the *p*-value threshold would then be $p frac{0.05}{255360} approx 1.96times 10^{-7}$. Using this threshold, the mean activity map obtained in `example06_multisession_map.m` shows almost no significant voxels. ,