Seppo P. Ahlfors

Assessing and improving the spatial accuracy in MEG source localization by depth-weighted minimum-norm estimates.

Cerebral currents responsible for the extra-cranially recorded magnetoencephalography (MEG) data can be estimated by applying a suitable source model. A popular choice is the distributed minimum-norm estimate (MNE) which minimizes the l2-norm of the estimated current. Under the l2-norm constraint, the current estimate is related to the measurements by a linear inverse operator. However, the MNE has a bias towards superficial sources, which can be reduced by applying depth weighting. We studied the effect of depth weighting in MNE using a shift metric. We assessed the localization performance of the depth-weighted MNE as well as depth-weighted noise-normalized MNE solutions under different cortical orientation constraints, source space densities, and signal-to-noise ratios (SNRs) in multiple subjects. We found that MNE with depth weighting parameter between 0.6 and 0.8 showed improved localization accuracy, reducing the mean displacement error from 12 mm to 7 mm. The noise-normalized MNE was insensitive to depth weighting. A similar investigation of EEG data indicated that depth weighting parameter between 2.0 and 5.0 resulted in an improved localization accuracy. The application of depth weighting to auditory and somatosensory experimental data illustrated the beneficial effect of depth weighting on the accuracy of spatiotemporal mapping of neuronal sources.

Mapping the Signal-To-Noise-Ratios of Cortical Sources in Magnetoencephalography and Electroencephalography

Although magnetoencephalography (MEG) and electroencephalography (EEG) have been available for decades, their relative merits are still debated. We examined regional differences in signal‐to‐noise‐ratios (SNRs) of cortical sources in MEG and EEG. Data from four subjects were used to simulate focal and extended sources located on the cortical surface reconstructed from high‐resolution magnetic resonance images. The SNR maps for MEG and EEG were found to be complementary. The SNR of deep sources was larger in EEG than in MEG, whereas the opposite was typically the case for superficial sources. Overall, the SNR maps were more uniform for EEG than for MEG. When using a noise model based on uniformly distributed random sources on the cortex, the SNR in MEG was found to be underestimated, compared with the maps obtained with noise estimated from actual recorded MEG and EEG data. With extended sources, the total area of cortex in which the SNR was higher in EEG than in MEG was larger than with focal sources. Clinically, SNR maps in a patient explained differential sensitivity of MEG and EEG in detecting epileptic activity. Our results emphasize the benefits of recording MEG and EEG simultaneously. Hum Brain Mapp 2009.

Cortical origin of middle-latency auditory evoked responses in man

We have recorded middle-latency magnetic evoked responses to 50-ms noise bursts, presented once every 0.9 s, over the right hemisphere of healthy humans. The measurements were carried out with a sensitive 7-channel SQUID gradiometer with a passband of 0.5-2000 Hz. The response consisted of peaks at about 30, 50 and 65 ms. The location of the equivalent source of the 30-ms deflection agrees with activation of the supratemporal auditory cortex, slightly anterior to the source area of the well-known 100-ms deflection.

The value of multichannel MEG and EEG in the presurgical evaluation of 70 epilepsy patients

OBJECTIVE To evaluate the sensitivity of a simultaneous whole-head 306-channel magnetoencephalography (MEG)/70-electrode EEG recording to detect interictal epileptiform activity (IED) in a prospective, consecutive cohort of patients with medically refractory epilepsy that were considered candidates for epilepsy surgery. METHODS Seventy patients were prospectively evaluated by simultaneously recorded MEG/EEG. All patients were surgical candidates or were considered for invasive EEG monitoring and had undergone an extensive presurgical evaluation at a tertiary epilepsy center. MEG and EEG raw traces were analysed individually by two independent reviewers. RESULTS MEG data could not be evaluated due to excessive magnetic artefacts in three patients (4%). In the remaining 67 patients, the overall sensitivity to detect IED was 72% (48/67 patients) for MEG and 61% for EEG (41/67 patients) analysing the raw data. In 13% (9/67 patients), MEG-only IED were recorded, whereas in 3% (2/67 patients) EEG-only IED were recorded. The combined sensitivity was 75% (50/67 patients). CONCLUSION Three hundred and six-channel MEG has a similarly high sensitivity to record IED as EEG and appears to be complementary. In one-third of the EEG-negative patients, MEG can be expected to record IED, especially in the case of lateral neocortical epilepsy and/or cortical dysplasia.

Sensitivity of MEG and EEG to source orientation.

An important difference between magnetoencephalography (MEG) and electroencephalography (EEG) is that MEG is insensitive to radially oriented sources. We quantified computationally the dependency of MEG and EEG on the source orientation using a forward model with realistic tissue boundaries. Similar to the simpler case of a spherical head model, in which MEG cannot see radial sources at all, for most cortical locations there was a source orientation to which MEG was insensitive. The median value for the ratio of the signal magnitude for the source orientation of the lowest and the highest sensitivity was 0.06 for MEG and 0.63 for EEG. The difference in the sensitivity to the source orientation is expected to contribute to systematic differences in the signal-to-noise ratio between MEG and EEG.

Developmental neural networks in children performing a Categorical N-Back Task

The prefrontal and temporal networks subserving object working memory tasks in adults have been reported as immature in young children; yet children are adequately capable of performing such tasks. We investigated the basis of this apparent contradiction using a complex object working memory task, a Categorical n-back (CN-BT). We examined whether the neural networks engaged by the CN-BT in children consist of the same brain regions as those in adults, but with a different magnitude of activation, or whether the networks are qualitatively different. Event-related fMRI was used to study differences in brain activation between healthy children ages 6 and 10 years, and young adults (20-28 years). Performance accuracy and RTs in 10-year-olds and adults were comparable, but the performance in 6-year-olds was lower. In adults, the CN-BT was highly effective in engaging the bilateral (L>R) ventral prefrontal cortex, the bilateral fusiform gyrus, posterior cingulate and precuneus, thus suggesting an involvement of the ventral visual stream, with related feature extraction and semantic labeling strategies. In children, the brain networks were distinctly different. They involved the premotor and parietal cortex, anterior insula, caudate/putamen, and the cerebellum, thus suggesting a predominant involvement of the visual dorsal and sensory-motor pathways, with related visual-spatial and action cognitive strategies. The findings indicate engagement of developmental networks in children reflecting task-effective brain activation. The age-related pattern of fMRI activation suggests a working hypothesis of a developmental shift from reliance on the dorsal visual stream and premotor/striatal/cerebellar networks in young children to reliance on the ventral prefrontal and inferior temporal networks in adults.

Lexical influences on speech perception: a Granger causality analysis of MEG and EEG source estimates.

Behavioral and functional imaging studies have demonstrated that lexical knowledge influences the categorization of perceptually ambiguous speech sounds. However, methodological and inferential constraints have so far been unable to resolve the question of whether this interaction takes the form of direct top-down influences on perceptual processing, or feedforward convergence during a decision process. We examined top-down lexical influences on the categorization of segments in a /s/-/integral/ continuum presented in different lexical contexts to produce a robust Ganong effect. Using integrated MEG/EEG and MRI data we found that, within a network identified by 40 Hz gamma phase locking, activation in the supramarginal gyrus associated with wordform representation influences phonetic processing in the posterior superior temporal gyrus during a period of time associated with lexical processing. This result provides direct evidence that lexical processes influence lower level phonetic perception, and demonstrates the potential value of combining Granger causality analyses and high spatiotemporal resolution multimodal imaging data to explore the functional architecture of cognition.

Large-area low-noise seven-channel dc SQUID magnetometer for brain research

The design, construction, and performance of a new high‐sensitivity dc SQUID magnetometer, covering a circular area of 93‐mm diameter, is described. The device, now used routinely in our brain research, comprises seven asymmetric first‐order gradiometers, located on a spherical surface of 125‐mm radius and with the symmetry axis tilted 30° with respect to the vertical. The pickup coil diameter is 20 mm, and the channels are separated by 36.5 mm from each other in a hexagonal array. The overall field sensitivity of the system, measured inside our magnetically shielded room, is 5 fT/(Hz)1/2, mainly limited by the thermal noise in the radiation shields of the Dewar. The optimization of the coil configuration and the measurement system is discussed in detail, and a system to determine automatically the position and orientation of the Dewar with respect to certain fixed points on the subject’s head is described. Finally, some examples of measurements carried out with the new device are given.

Dynamic magnetic resonance inverse imaging of human brain function.

MRI is widely used for noninvasive hemodynamic‐based functional brain imaging. In traditional spatial encoding, however, gradient switching limits the temporal resolution, which makes it difficult to unambiguously identify possible fast nonhemodynamic changes. In this paper we propose a novel reconstruction approach, called dynamic inverse imaging (InI), that is capable of providing millisecond temporal resolution when highly parallel detection is used. To achieve an order‐of‐magnitude speedup in generating time‐resolved contrast estimates and dynamic statistical parametric maps (dSPMs), the spatial information is derived from an array of detectors rather than by time‐consuming gradient‐encoding methods. The InI approach was inspired by electroencephalography (EEG) and magnetoencephalography (MEG) source localization techniques. Dynamic MR InI was evaluated by means of numerical simulations. InI was also applied to measure BOLD hemodynamic time curves at 20‐ms temporal resolution in a visual stimulation experiment using a 90‐channel head array. InI is expected to improve the time resolution of MRI and provide increased flexibility in the trade‐off between spatial and temporal resolution for studies of dynamic activation patterns in the human brain. Magn Reson Med, 2006.

Attention-driven auditory cortex short-term plasticity helps segregate relevant sounds from noise

How can we concentrate on relevant sounds in noisy environments? A “gain model” suggests that auditory attention simply amplifies relevant and suppresses irrelevant afferent inputs. However, it is unclear whether this suffices when attended and ignored features overlap to stimulate the same neuronal receptive fields. A “tuning model” suggests that, in addition to gain, attention modulates feature selectivity of auditory neurons. We recorded magnetoencephalography, EEG, and functional MRI (fMRI) while subjects attended to tones delivered to one ear and ignored opposite-ear inputs. The attended ear was switched every 30 s to quantify how quickly the effects evolve. To produce overlapping inputs, the tones were presented alone vs. during white-noise masking notch-filtered ±1/6 octaves around the tone center frequencies. Amplitude modulation (39 vs. 41 Hz in opposite ears) was applied for “frequency tagging” of attention effects on maskers. Noise masking reduced early (50–150 ms; N1) auditory responses to unattended tones. In support of the tuning model, selective attention canceled out this attenuating effect but did not modulate the gain of 50–150 ms activity to nonmasked tones or steady-state responses to the maskers themselves. These tuning effects originated at nonprimary auditory cortices, purportedly occupied by neurons that, without attention, have wider frequency tuning than ±1/6 octaves. The attentional tuning evolved rapidly, during the first few seconds after attention switching, and correlated with behavioral discrimination performance. In conclusion, a simple gain model alone cannot explain auditory selective attention. In nonprimary auditory cortices, attention-driven short-term plasticity retunes neurons to segregate relevant sounds from noise.