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Real-time imaging of brain activity in freely moving rats using functional ultrasound

Abstract

Innovative imaging methods help to investigate the complex relationship between brain activity and behavior in freely moving animals. Functional ultrasound (fUS) is an imaging modality suitable for recording cerebral blood volume (CBV) dynamics in the whole brain but has so far been used only in head-fixed and anesthetized rodents. We designed a fUS device for tethered brain imaging in freely moving rats based on a miniaturized ultrasound probe and a custom-made ultrasound scanner. We monitored CBV changes in rats during various behavioral states such as quiet rest, after whisker or visual stimulations, and in a food-reinforced operant task. We show that fUS imaging in freely moving rats could efficiently decode brain activity in real time.

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Figure 1: Miniaturized device for fUS in freely moving rats.
Figure 2: Functional connectivity addressed by fm-fUS imaging.
Figure 3: Spatial and temporal evolution of the CBV signal in response to whisker or visual stimulation.
Figure 4: fm-fUS imaging during a food-reinforced operant task.
Figure 5: Real-time decoding of brain activity in freely moving rats.

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Acknowledgements

We thank the Ecole Normale Supérieure de Lyon for its financial support of the 4th year study project of C. Dussaux. We thank L. Zamfirov and S. Raja for computer-assisted design and technical help with the fm-fUS implant. We also thank the Phenobrain platform of the “Centre de Psychiatrie & Neuroscience” for animal care. This work was supported by a grant from Agence Nationale de la Recherche, Paris.

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Correspondence to Alan Urban.

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The authors declare no competing financial interests.

Integrated supplementary information

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.

Source data

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%).

Source data

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 five single 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 barrel cortex, M: motor cortex. Scale bar (white), coronal view, 2 mm.

Source data

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.

Supplementary Figure 5 Characteristics of the hemodynamic response function observed for 7-s-long and 1-s-short manual stimuli or during behavioral 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).

Source data

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.

Source data

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 probe imposes 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).

Source data

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.

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 peaks with 93% sensitivity and 95% specificity. Scale bar (white), 2 mm.

Source data

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.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–10 and Supplementary Notes 1 and 2 (PDF 2898 kb)

Real-time decoding of brain activity in freely moving rats during a conditioned task.

Rats were trained to perform a task consisting of a round trip between a starting zone and a reward zone (reinforced round trip (RRT)) on an elevated corridor. Camera 1 shows the global view of animal movement while camera 2 offers a magnification of the reward zone including six vertical sticks to stimulate whiskers during reward collection. CBV signal is recorded and displayed in real-time. (MP4 2629 kb)

Supplementary Software

Quick guide for GPU processing of fm-fUS images including Matlab scripts and CUDA files for general-purpose processing of fm-fUS images on graphics processing units. (ZIP 423 kb)

Supplementary Data

Computer-aided design of the head plate, the probe holder and the head shield. Components were 3D-printed with biocompatible polylactate polymer (Sculpteo) after CAD with Sketchup software (Google). (ZIP 88 kb)

Source data

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Urban, A., Dussaux, C., Martel, G. et al. Real-time imaging of brain activity in freely moving rats using functional ultrasound. Nat Methods 12, 873–878 (2015). https://doi.org/10.1038/nmeth.3482

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