Summary
To date, neuroimaging has provided a wealth of information on how the human brain works in health and disease. With functional magnetic resonance imaging (fMRI), we can obtain spatially precise information about long-lasting brain activations whereas electro- and magnetoencephalography (EEG/MEG) can track transient cortical responses at millisecond resolution. However, none of these methods excel in time-resolved detection of sustained cortical activations, which are typically reflected as bursts of gamma-range (30–150 Hz) oscillations, frequently present in invasive recordings in patients. Although we have recently demonstrated that in exceptional situations MEG can detect even single gamma responses, their signal-to-noise ratio is usually prohibitively low, largely due to the substantial distance (4–5 cm) between cortex and sensors. Here, I propose to exploit recent advances in a novel magnetic sensor technology—atomic magnetometry—to construct a new kind of MEG system that allows capturing cerebral magnetic fields within millimetres from the scalp. Our simulations show that this proximity leads up to a 5-fold increase in the signal amplitude and an order-of-magnitude improvement of spatial resolution compared to conventional MEG. Therefore, a high-resolution MEG (HRMEG) system based on atomic magnetometers should enable non-invasive recordings of cortical activity at unprecedented sensitivity and detail level, which I propose to capitalize on by characterizing cortical responses, particularly gamma oscillations, during complex cognitive tasks. Additionally, since atomic magnetometers can recover within milliseconds from fields of several tesla, I also propose to combine transcranial magnetic stimulation (TMS) with MEG, leveraging the reciprocity of TMS and MEG and thus allowing better-than-ever characterization of TMS-evoked responses. This proposal comprises the research towards a HRMEG system and its application to study the working human brain in a new way.
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| Web resources: | https://cordis.europa.eu/project/id/678578 |
| Start date: | 01-09-2016 |
| End date: | 31-08-2022 |
| Total budget - Public funding: | 1 498 806,00 Euro - 1 498 806,00 Euro |
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Original description
To date, neuroimaging has provided a wealth of information on how the human brain works in health and disease. With functional magnetic resonance imaging (fMRI), we can obtain spatially precise information about long-lasting brain activations whereas electro- and magnetoencephalography (EEG/MEG) can track transient cortical responses at millisecond resolution. However, none of these methods excel in time-resolved detection of sustained cortical activations, which are typically reflected as bursts of gamma-range (30–150 Hz) oscillations, frequently present in invasive recordings in patients. Although we have recently demonstrated that in exceptional situations MEG can detect even single gamma responses, their signal-to-noise ratio is usually prohibitively low, largely due to the substantial distance (4–5 cm) between cortex and sensors. Here, I propose to exploit recent advances in a novel magnetic sensor technology—atomic magnetometry—to construct a new kind of MEG system that allows capturing cerebral magnetic fields within millimetres from the scalp. Our simulations show that this proximity leads up to a 5-fold increase in the signal amplitude and an order-of-magnitude improvement of spatial resolution compared to conventional MEG. Therefore, a high-resolution MEG (HRMEG) system based on atomic magnetometers should enable non-invasive recordings of cortical activity at unprecedented sensitivity and detail level, which I propose to capitalize on by characterizing cortical responses, particularly gamma oscillations, during complex cognitive tasks. Additionally, since atomic magnetometers can recover within milliseconds from fields of several tesla, I also propose to combine transcranial magnetic stimulation (TMS) with MEG, leveraging the reciprocity of TMS and MEG and thus allowing better-than-ever characterization of TMS-evoked responses. This proposal comprises the research towards a HRMEG system and its application to study the working human brain in a new way.Status
CLOSEDCall topic
ERC-StG-2015Update Date
27-04-2024
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