Computational protocol: Spatial reversal learning defect coincides with hypersynchronous telencephalic BOLD functional connectivity in APPNL F/NL F knock in mice

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Protocol publication

[…] For the MRI handling procedures all mice were anesthetized with 2.5% isoflurane (IsoFlo, Abbott, Illinois, USA), which was administered in a mixture of 70% nitrogen (400 cc/min) and 30% oxygen (200 cc/min). During the rsfMRI imaging procedures, a combination of medetomidine (Domitor, Pfizer, Karlsruhe, Germany) and isoflurane was used to sedate the animals. After positioning of the animal in the scanner, medetomidine was administered subcutaneously as a bolus injection (0.3 mg/kg), after which the isoflurane level was immediately decreased to 1%. Ten minutes before the rsfMRI acquisition, isoflurane was decreased to 0.5%. RsfMRI scans were consistently acquired 40 min after the bolus injection, during which the isoflurane level was kept at 0.5%. After the imaging procedures, the effects of medetomidine were counteracted by subcutaneously injecting 0.1 mg/kg atipamezole (Antisedan, Pfizer, Karlsruhe, Germany). The physiological status of all animals was monitored throughout the imaging procedure. A pressure sensitive pad (MR-compatible Small Animal Monitoring and Gating system, SA Instruments, Inc.) was used to monitor breathing rate and a rectal thermistor with feedback controlled warm air circuitry (MR-compatible Small Animal Heating System, SA Instruments, Inc.) was used to maintain body temperature at 37.0 ± 0.5 °C.MRI procedures were performed on a 9.4 T Biospec MRI system (Bruker BioSpin, Germany) with the Paravision 5.1 software ( Images were acquired using a standard Bruker cross coil set-up with a quadrature volume coil and a quadrature surface coil for mice. Three orthogonal multi-slice Turbo RARE T2-weighted images were acquired to render slice-positioning uniform (repetition time 2000 ms, echo time 33 ms, 16 slices of 0.4 mm). Field maps were acquired for each animal to assess field homogeneity, followed by local shimming, which corrects for the measured inhomogeneity in a rectangular VOI within the brain. Resting-state signals were measured using a T2*-weighted single shot EPI sequence (repetition time 2000 ms, echo time 15 ms, 16 slices of 0.4 mm with a gap of 0.1 mm, 300 repetitions). The field-of-view was (20 × 20) mm2 and matrix size (128 × 64), resulting in voxel dimensions of (0.156 × 0.312 × 0.5) mm³. [...] Pre-processing of the rsfMRI data, including realignment, normalization and smoothing, was performed using SPM8 software (Statistical Parametric Mapping, First, all images within each session were realigned to the first image. This was done using a least-squares approach and a 6-parameter (rigid body) spatial transformation. For the rsfMRI data analyses, motion parameters resulting from the realignment were included as covariates to correct for possible movement that occurred during the scanning procedure. Second, all datasets were normalized to a study specific EPI template and co-registered to an anatomical T2-weighted template. The normalization steps consisted of a global 12-parameter affine transformation followed by the estimation of the nonlinear deformations. Finally, in plane smoothing was done using a Gaussian kernel with full width at half maximum of twice the voxel size (0.31 × 0.62) mm². All rsfMRI data were filtered between 0.01–0.25 Hz using the REST toolbox (REST1.7, [...] RsfMRI data were first analyzed with group independent component analysis (ICA) to determine which brain networks can be discerned using the GIFT-toolbox (Group ICA of fMRI toolbox version 2.0a: First the data of each individual animal was concatenated. Then group ICA was performed using the Infomax algorithm, followed by back reconstruction of the data to single-subject independent components and time courses. ICA was performed using a pre-set of 15 components, which was shown to be appropriate to identify networks in mice,. Masks containing the individual brain regions resulting from the ICA analyses were defined using MRicron software (MRicron version 6.6, 2013, and used for region-of-interest (ROI) correlation analyses, where pairwise correlation coefficients between each pair of ROIs were calculated and z-transformed using an in-house program developed in MATLAB (MATLAB R2013a, The MathWorks Inc. Natick, MA, USA). Mean z-transformed FC matrices were calculated for each group. For inter-network analyses, homologous ICA components were grouped and the resulting brain networks were then used for inter-network correlation analyses. Statistical analyses of the rsfMRI data included two-sample T-tests and two-way ANOVA with Sidak correction for multiple comparisons (p < 0.05).Additionally, seed-based analyses were performed by computing individual z-transformed FC-maps of the right hippocampus and right caudate putamen using REST toolbox, resulting in FC-maps for each of these seed regions for each group. FC between the seed-region and other regions on the FC-map were calculated by defining a mask containing the ROIs derived from the mean statistical FC-maps, and then calculating the z-values from these ROIs for each individual subject using REST-toolbox. Statistical analyses of the FC-maps included a one-sample T-test (p < 0.001, uncorrected, threshold 10 voxels) for within group analyses, and included a two-way ANOVA with Sidak correction for multiple comparisons (p < 0.05) for between group analyses of specific functional connections i.e. hippocampus bilateral, hippocampus-frontal, hippocampus-retrosplenial, caudate putamen-cingulate and caudate putamen-hippocampus. […]

Pipeline specifications

Software tools ParaVision, SPM, GIFT, MRIcron
Application Magnetic resonance imaging
Organisms Mus musculus
Diseases Alzheimer Disease, Amyloidosis, Sandhoff Disease