Investigating the relationship between pharmacological MRI and electrophysiology using Canonical Correlation Analysis

Pharmacological MRI (phMRI) is a rapidly advancing field whose goal it is to map the modulatory effects of pharmacological agents on the large-scale brain networks that underlie cognition. However, the relation between these effects on functional imaging signals and the underlying neural activity is unclear. We have combined phMRI with electrophysiological recordings of neural activity to link effects at the level of imaging signals to those observed in electrical recordings from neuronal populations. During fMRI acquisition, we recorded the broad-band comprehensive neuronal signal, and extract from it time courses of four relevant frequency bands: low (1-12Hz), medium (12-24Hz) gamma (24-90) and multi-unit-activity (400-3000Hz). At the same time we registered BOLD activity in a region of interest around the electrode tip, placed in the primary visual cortex. Scans were about 40 minutes long, during which we delivered a visual stimulus for periods of 30 seconds followed by blank periods of equal length. During visual stimulation we then locally applied either an inhibitory neurotransmitter (GABA), an excitatory neuromodulator (ACh) or just saline solution. We used a recently proposed algorithm for performing Canonical Correlation Analysis (CCA) between fMRI data and electrophysiological activity. Preliminary results show, that CCA robustly finds dependencies between groups of voxels in the fMRI data and frequency bands in the electrophysiological data. For example, a component dominated by the MUA signal was associated with voxels that tended to cluster near the injector and showed inhibitory effects for GABA injection and excitatory effects for ACh injection. These findings suggest that CCA is a promising candidate for revealing relations between neural activity and the fMRI signal during pharmacological manipulations