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Biomedical subjects

Seppo P Ahlfors

Publications and source records attributed to Seppo P Ahlfors.

8 recordsLinked to original sources

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.

Adult↗

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.

Adult↗

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.

Brain Mapping↗

Biasing the brain's attentional set: I. cue driven deployments of intersensory selective attention.

Brain activity associated with directing attention to one of two possible sensory modalities was examined using high-density mapping of human event-related potentials. The deployment of selective attention was based on visually presented symbolic cue-words instructing subjects on a trial-by-trial basis, which sensory modality to attend. We measured the spatio-temporal pattern of activation in the approximately 1 second period between the cue-instruction and a subsequent compound auditory-visual imperative stimulus. This allowed us to assess the flow of processing across brain regions involved in deploying and sustaining inter-sensory selective attention, prior to the actual selective processing of the compound audio-visual target stimulus. Activity over frontal and parietal areas showed sensory specific increases in activation during the early part of the anticipatory period (~230 ms), probably representing the activation of fronto-parietal attentional deployment systems for top-down control of attention. In the later period preceding the arrival of the "to-be-attended" stimulus, sustained differential activity was seen over fronto-central regions and parieto-occipital regions, suggesting the maintenance of sensory-specific biased attentional states that would allow for subsequent selective processing. Although there was clear sensory biasing in this late sustained period, it was also clear that both sensory systems were being prepared during the cue-target period. These late sensory-specific biasing effects were also accompanied by sustained activations over frontal cortices that also showed both common and sensory specific activation patterns, suggesting that maintenance of the biased state includes top-down inputs from generators in frontal cortices, some of which are sensory-specific regions. These data support extensive interactions between sensory, parietal and frontal regions during processing of cue information, deployment of attention, and maintenance of the focus of attention in anticipation of impending attentionally relevant input.

Acoustic Stimulation↗

Application of magnetoencephalography in epilepsy patients with widespread spike or slow-wave activity.

PURPOSE: To examine whether magnetoencephalography (MEG) can be used to determine patterns of brain activity underlying widespread paroxysms of epilepsy patients, thereby extending the applicability of MEG to a larger population of epilepsy patients. METHODS: We studied two children with symptomatic localization-related epilepsy. Case 1 had widespread spikes in EEG with an operation scar from a resection of a brain tumor; Case 2 had hemispheric slow-wave activity in EEG with sensory auras. MEG was collected with a 204-channel helmet-shaped sensor array. Dynamic statistical parametric maps (dSPMs) were constructed to estimate the cortical distribution of interictal discharges for these patients. Equivalent current dipoles (ECDs) also were calculated for comparison with the results of dSPM. RESULTS: In case 1 with widespread spikes, dSPM presented the major activity at the vicinity of the operation scar in the left frontal lobe at the peak of the spikes, and some activities were detected in the left temporal lobe just before the peak in some spikes. In case 2 with hemispheric slow waves, the most active area was located in the left parietal lobe, and additional activity was seen at the ipsilateral temporal and frontal lobes in dSPM. The source estimates correlated well with the ictal manifestation and interictal single-photon emission computed tomography (SPECT) findings for this patient. In comparison with the results of ECDs, ECDs could not express a prior activity at the left temporal lobe in case 1 and did not model well the MEG data in case 2. CONCLUSIONS: We suggest that by means of dSPM, MEG is useful for presurgical evaluation of patients, not only with localized epileptiform activity, but also with widespread spikes or slow waves, because it requires no selections of channels and no time-point selection.

Adolescent↗

Dynamic statistical parametric mapping for analyzing the magnetoencephalographic epileptiform activity in patients with epilepsy.

Our current purpose is to evaluate the applicability of dynamic statistical parametric mapping, a novel method for localizing epileptiform activity recorded with magnetoencephalography in patients with epilepsy. We report four pediatric patients with focal epilepsies. Magnetoencephalographic data were collected with a 306-channel whole-head helmet-shaped sensor array. We calculated equivalent current dipoles and dynamic statistical parametric mapping movies of the interictal epileptiform discharges that were based in the minimum-L2 norm estimate, minimizing the square sum of the dipole element amplitudes. The dynamic statistical parametric mapping analysis of interictal epileptiform discharges can demonstrate the rapid change and propagation of interical epileptiform discharges. According to these findings, specific epileptogenic lesion-focal cortical dysplasia could be found and patients could be operated on successfully. The presurgical analysis of interictal epileptiform discharges using dynamic statistical parametric mapping seems to be promising in patients with a possible underlying focal cortical dysplasia and might help to guide the placement of invasive electrodes.

Adolescent↗

Increased MEG activation in OCD reflects a compensatory mechanism specific to the phase of a visual working memory task.

We examined spatio-temporal patterns of evoked magnetoencephalographic signals (MEG) in patients with obsessive-compulsive disorder (OCD) during the Encoding, Retention, and Retrieval phases of a Delayed Matching-to-Sample working memory task (DMST). The question was whether the mechanisms of abnormally increased cortical excitability, frequently reported in OCD, relate to a global cortical disinhibition and unselective over-processing of stimuli or, alternatively, to a compensatory mechanism of effortful enhanced inhibitory control. The DMST-related network of activation in OCD was found similar to that of Controls, and to that reported in other neuroimaging studies. The pattern of increased MEG activation in OCD patients was phase specific. During the Encoding phase, the activation was enhanced in the region of anterior insula and reduced in the posterior-inferior parietal cortex. During Retention, the activation was reduced in the occipital, parietal, superior temporal sulcus, and dorsolateral prefrontal cortex (BA 6/8/9). During Retrieval, a significant increase of activation was found in the right anterior insula extending towards the orbital region and right superior temporal sulcus, along with reduced activation in the left parietal cortex. The performance accuracy was high in OCD and comparable to Controls, although the RTs were prolonged. The results are discussed as being consistent with the hypothesis of a compensatory mechanism of effortful inhibitory control. This mechanism may be a major contributor to the increased cortical activation during Encoding and, in particular, Retrieval of the DMST task in patients suffering OCD. The findings do not support the concept of a faulty working memory mechanism per se in OCD.

Adult↗

Geometrical interpretation of fMRI-guided MEG/EEG inverse estimates.

Magneto- and electroencephalography (MEG/EEG) and functional magnetic resonance imaging (fMRI) provide complementary information about the functional organization of the human brain. An important advantage of MEG/EEG is the millisecond time resolution in detecting electrical activity in the cerebral cortex. The interpretation of MEG/EEG signals, however, is limited by the difficulty of determining the spatial distribution of the neural activity. Functional MRI can help in the MEG/EEG source analysis by suggesting likely locations of activity. We present a geometric interpretation of fMRI-guided inverse solutions in which the MEG/EEG source estimate minimizes a distance to a subspace defined by the fMRI data. In this subspace regularization (SSR) approach, the fMRI bias does not assume preferred amplitudes for MEG/EEG sources, only locations. Characteristic dependence of the source estimates on the regularization parameters is illustrated with simulations. When the fMRI locations match the true MEG/EEG source locations, they serve to bias the underdetermined MEG/EEG inverse solution toward the fMRI loci. Importantly, when the fMRI loci do not match the true MEG/EEG loci, the solution is insensitive to those fMRI loci.

Algorithms↗