PURPOSE: To develop a non-invasive method for exploring seizure initiation and propagation in the brain of intact experimental animals. METHODS: We have developed and applied a model-independent statistical method--Hierarchical Cluster Analysis (HCA)--for analyzing BOLD-fMRI data following administration of pentylenetetrazol (PTZ) to intact rats. HCA clusters voxels into groups that share similar time courses and magnitudes of signal change, without any assumptions about when and/or where the seizure begins. RESULTS: Epileptiform spiking activity was monitored by EEG (outside the magnet) following intravenous PTZ (IV-PTZ; n=4) or intraperitoneal PTZ administration (IP-PTZ; n=5). Onset of cortical spiking first occurred at 29+/-16 s (IV-PTZ) and 147+/-29 s (IP-PTZ) following drug delivery. HCA of fMRI data following IV-PTZ (n=4) demonstrated a single dominant cluster, involving the majority of the brain and first activating at 27+/-23s. In contrast, IP-PTZ produced multiple, relatively small, clusters with heterogeneous time courses that varied markedly across animals (n=5); activation of the first cluster (involving cortex) occurred at 130+/-59 s. With both routes of PTZ administration, the timing of the fMRI signal increase correlated with onset of EEG spiking. CONCLUSIONS: These experiments demonstrate that fMRI activity associated with seizure activity can be analyzed with a model-independent statistical method. HCA indicated that seizure initiation in the IV- and IP-PTZ models involves multiple regions of sensitivity that vary with route of drug administration and that show significant variability across animal subjects. Even given this heterogeneity, fMRI shows clear differences that are not apparent with typical EEG monitoring procedures, in the activation patterns between IV and IP-PTZ models. These results suggest that fMRI can be used to assess different models and patterns of seizure activation.
PURPOSE: To develop a non-invasive method for exploring seizure initiation and propagation in the brain of intact experimental animals. METHODS: We have developed and applied a model-independent statistical method--Hierarchical Cluster Analysis (HCA)--for analyzing BOLD-fMRI data following administration of pentylenetetrazol (PTZ) to intact rats. HCA clusters voxels into groups that share similar time courses and magnitudes of signal change, without any assumptions about when and/or where the seizure begins. RESULTS: Epileptiform spiking activity was monitored by EEG (outside the magnet) following intravenous PTZ (IV-PTZ; n=4) or intraperitoneal PTZ administration (IP-PTZ; n=5). Onset of cortical spiking first occurred at 29+/-16 s (IV-PTZ) and 147+/-29 s (IP-PTZ) following drug delivery. HCA of fMRI data following IV-PTZ (n=4) demonstrated a single dominant cluster, involving the majority of the brain and first activating at 27+/-23s. In contrast, IP-PTZ produced multiple, relatively small, clusters with heterogeneous time courses that varied markedly across animals (n=5); activation of the first cluster (involving cortex) occurred at 130+/-59 s. With both routes of PTZ administration, the timing of the fMRI signal increase correlated with onset of EEG spiking. CONCLUSIONS: These experiments demonstrate that fMRI activity associated with seizure activity can be analyzed with a model-independent statistical method. HCA indicated that seizure initiation in the IV- and IP-PTZ models involves multiple regions of sensitivity that vary with route of drug administration and that show significant variability across animal subjects. Even given this heterogeneity, fMRI shows clear differences that are not apparent with typical EEG monitoring procedures, in the activation patterns between IV and IP-PTZ models. These results suggest that fMRI can be used to assess different models and patterns of seizure activation.
Authors: Antti M Airaksinen; Juha-Pekka Niskanen; Ryan Chamberlain; Joanna K Huttunen; Jari Nissinen; Michael Garwood; Asla Pitkänen; Olli Gröhn Journal: Magn Reson Med Date: 2010-10 Impact factor: 4.668
Authors: Pablo Bascuñana; Julián Javela; Mercedes Delgado; Rubén Fernández de la Rosa; Ahmed Anis Shiha; Luis García-García; Miguel Ángel Pozo Journal: Mol Imaging Biol Date: 2016-10 Impact factor: 3.488