Supplementary Figure 1

Filtering of the signal noise during fm-fUS imaging.

Intensity of the CBV signal recorded in the brain during a typical imaging session lasting 220 s before and after correction. The five large peaks observed in the CBV signal correspond to mechanical vibrations because of rapid head movements that occur sporadically.

Nature Methods: doi:10.1038/nmeth.3482

Supplementary Figure 2

Comparison of fluctuations observed in the hemodynamic signal between anesthetized and awake rats.

(a) CBV signal observed in the cortex in awake rats. (b) CBV signal observed in the thalamus in awake rats. (c) CBV signal observed in the cortex under 2% isoflurane anesthesia shows low frequency oscillations (LFOs) of weak amplitude (1.8 ± 0.9%) compared to awake rats (6.8 ± 1.7%).

Nature Methods: doi:10.1038/nmeth.3482

Supplementary Figure 3

Spatial and temporal evolution of the CBV signal in response to whisker stimulation.

Brain activation map of a single 7 s-long manual stimulus of the whiskers. Temporal evolution of the CBV signal in the BF cortex for fivesingle trials and average CBV signal measured in activated and control (dashed) ROIs. Arrowed white box correspond to activated ROI while dashed white boxes correspond to control ROI. Vertical bars (red) indicate stimulus duration. BF: primary somatosensory barrelcortex, M: motor cortex. Scale bar (white), coronal view, 2 mm.

Nature Methods: doi:10.1038/nmeth.3482

Supplementary Figure 4

Spatial and temporal specificity of the CBV response during whisker stimulations.

Brain activation maps elicited by alternative manual deflections (7 s, 10 deflections) of the left or right whiskers show that CBV response is restricted to contralateral hemisphere. Scale bar (white), 2 mm.

Nature Methods: doi:10.1038/nmeth.3482

Supplementary Figure 5

Characteristics of the hemodynamic response function observed for 7-s-long and 1-s-short manual stimuli or duringbehavioral tasks.

(a) Comparison of peak amplitude (PA), time at half-maximum (THM) and full width at half-maximum (FWHM) reported as mean values and standard deviations (b) Statistical analysis of the hemodynamic parameters observed for each experimental condition (Kruskal-Wallis test; *** P < 0.001; ns, non significant).

Nature Methods: doi:10.1038/nmeth.3482

Supplementary Figure 6

Spatial and temporal evolution of the CBV signal in response to visual stimulation.

Brain activation maps of a single 7 s-long visual stimulus. Temporal evolution of the CBV signal in the LGN thalamic nucleus for 5 single trials and average CBV signal measured in activated and control (dashed) ROIs. Arrowed white boxes correspond to activated ROIs while dashed white boxes correspond to control ROIs. Vertical bars (red) indicate stimulus duration. V2: secondary visual cortex, LGN: lateral geniculate thalamic nucleus. Scale bar (white), coronal view, 2 mm.

Nature Methods: doi:10.1038/nmeth.3482

Supplementary Figure 7

Running velocity and residency time for freely moving rats with or without head-mounted miniature ultrasound probe.

Measurement of running velocities by tracking animal movements using a camera under reduced illumination shows that the probeimposes minimal burden as confirmed by the slight reduction of the velocity (~25%) when the probe is connected. The residency time represents the delay during which vertical sticks placed in the reward zone activate whiskers. Statistical analysis of the hemodynamic parameters observed for each experimental condition (Kruskal-Wallis test; **** P < 0.0001 *** P < 0.001; * P < 0.05; ns, non significant).

Nature Methods: doi:10.1038/nmeth.3482

Supplementary Figure 8

Brain activation map observed in food-reinforced operant tasks.

A specific increase of the CBV in the BF is associated with whisker stimulation during reward collection (left panel) that disappears when whiskers are trimmed and sticks in the reward zone are removed (right panel). Scale bar (white), 2 mm.

Nature Methods: doi:10.1038/nmeth.3482

Supplementary Figure 9

Real-time decoding of brain activity during a visual task.

(a) Schematic workflow to decode brain activity based on analysis of the temporal CBV signal in a ROI in the LGN (white dashed line) corresponding to the most activated voxels for a 1s-short manual stimulus. A specific algorithm is used to classify in real time active (red) and inactive (blue) peaks in the CBV signal over or below a threshold, respectively (black line). (b) Distributions of active and inactive peaks in the CBV signal extracted from all experiments. Note that the 2 distributions are significantly different (P < 0.001). The back line with a black triangle shows the threshold that was selected during real time detection of brain activity. (c) ROC curve from the distribution presented in (b) showing the threshold (black triangle) that was chosen for brain decoding allowing detection of active peakswith 93% sensitivity and 95% specificity. Scale bar (white), 2 mm.

Nature Methods: doi:10.1038/nmeth.3482

Supplementary Figure 10

Schematic view of the data processing pipeline used for real-time fm-fUS imaging.

Echo data are first acquired with the ultrasound hardware and transferred to the workstation via a fast PCI-E bus. Then the image is beamformed by the GPU and finally filtered by the CPU. All steps are optimized to allow simultaneous processing hence reducing the delay between 2 images to only 0.7 s.

Nature Methods: doi:10.1038/nmeth.3482

Supplementary Note 1

Ultrasound probe for freely moving functional ultrasound (fm-fUS) Technical characteristics

• Provider: Imasonic – France

ACOUSTIC CHARACTERISTICS:

• Type: Linear array • Number of elements: 64 • Mechanic focalisation: cylinder R 6mm ±1mm • Elementary distance / pitch (p): 0.15 mm • Inter-element distance (e): 0.025 mm • Element height (h): 1.5 mm • Total active length (L): 9.575 mm • Central frequency (-6dB): 15 MHz • Bandwidth (-6dB): > 50%

MECHANICAL CHARACTERISTICS:

• Geometry: Parallelepiped • Bottom dimensions: 12 x 6.5 mm

(Length x large) • Top dimensions: 24 x 10 mm

(Length x large) • Probe height: 20 mm • Cable: 50 • Cable length: 2m ±0.1m • Cable connector: ITT Cannon

DLM5-260P

Nature Methods: doi:10.1038/nmeth.3482

Supplementary Note 2

Resolution of functional ultrasound (fUS) and influences of imaging depth There are 3 spatial resolutions to consider for fUS imaging: 1) the lateral resolution dx (parallel to the array dimension) 2) the resolution in depth dz (same direction than the ultrasound propagation) 3) the elevation resolution dy (out of plane) 1) LATERAL RESOLUTION The lateral resolution at a point of depth z can be obtained from the equation (1):

Dzdx λ=

(1)

where λ is the ultrasound wavelength, z the depth and D the aperture of the array. This equation must be corrected for a real array because the ratio z/D is limited by the maximal emission angle of the individual elements of the array. In our case z/D is >1.5. A second limit is imposed when the pixel is near the border of the image. If for example the pixel is in the border of the image at x=0, only half of the array must be active. According to these limitations, the resolution must be calculated by splitting the aperture D in two sub apertures (right and left) and by computing the limits of each one as detailed in (2):

⎩⎨⎧

≥−<−−

=

⎩⎨⎧

≥<

=

+=

2//22/

),(

2//22/

),(

),(),(

nzxLifnznzxLifxL

zxD

nzxifnznzxifx

zxD

zxDzxDzdx

l

r

lr

λ

(2)

where n is the maximal numerical aperture of the array (1/1.5 in our case) and L is the dimension of the array (9.6 mm). The Figure 1 below presents the resolution for each position of image. The best lateral resolution of 150 µm is achieved at the center of the image, while the resolution is 300 µm at the border of the image.

Figure 1: Lateral resolution of the ultrasound probe.

1 2 3 4 5 6 7 8 910

8

6

4

2

150µm

200µm

250µm

300µm

X direction (mm)

z di

rect

ion

(mm

)

Nature Methods: doi:10.1038/nmeth.3482

2) RESOLUTION IN DEPTH The resolution in depth is constant and can be obtained from the equation (3):

2/tcdz Δ= (3) where tΔ is the duration of the ultrasound impulsion andc the speed of sound. In our case the resolution in depth is 100 µm. 3) ELEVATION RESOLUTION The geometry of the transducers influences the out-of-plane resolution. Here, we chose transducers of 1.5 mm in size in the elevation direction. These elements are convex with a geometrical focusing at 6 mm which did not require a focusing lens and thus contributed to the miniaturization of the probe. The out of plane resolution (dy or thickness of the image) cannot be obtained from a simple analytical equation. To obtain this resolution we need to simulate the propagation field. This simulation computes the integral presented in (4):

dsrr

crrtrvr

S∫ −−−

=Φ0

00

)/,(21)(π (4)

where Φ is the velocity potential, 0r is the point where we calculate this potential, v is the velocity perpendicular to the surface of the transducer and c the speed of sound.

Figure 2: Elevation resolution of the ultrasound probe.

Figure 2a indicates maximum of the velocity potential in each point of the (z,y) plane. The resolution is computed as the half amplitude of 2Φ for each depth z (we used the square value because the array send the wave and also to receive it). Figure 2b indicates the resolution in the out of plane direction. By performing this simulation, we found an average elevation resolution of 400 µm with a maximal resolution of 220 µm at 4 mm of the probe and a minimal resolution of 800 µm at 2 mm of the probe.

0 0.5 1

2

3

4

5

6

7

8

2 3 4 5 6 7 80.2

0.4

0.6

0.8

1

Out of plane y (mm)

Dep

th z

(m

m)

Depth z (mm)

Out

of p

lane

res

olut

ion

(mm

)

0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

Ultrasound Probe a b

Nature Methods: doi:10.1038/nmeth.3482