NeuroImage
-
Automatic hippocampal segmentation in temporal lobe epilepsy: impact of developmental abnormalities.
In drug-resistant temporal lobe epilepsy (TLE), detecting hippocampal atrophy on MRI is important as it allows defining the surgical target. The performance of automatic segmentation in TLE has so far been considered unsatisfactory. In addition to atrophy, about 40% of patients present with developmental abnormalities (referred to as malrotation) characterized by atypical morphologies of the hippocampus and collateral sulcus. ⋯ In addition, they tended to lateralize the seizure focus less accurately in the presence of malrotation (manual: 64%; ANIMAL-multi: 55%, p = 0.4; SACHA: 50%, p = 0.1; FreeSurfer: 41%, p = 0.05). Hippocampal developmental anomalies and atrophy had a negative impact on the segmentation performance of three state-of-the-art automated methods. These shape variants should be taken into account when designing segmentation algorithms.
-
Structural connectivity research in the human brain in vivo relies heavily on fiber tractography in diffusion-weighted MRI (DWI). The accurate mapping of white matter pathways would gain from images with a higher resolution than the typical ~2mm isotropic DWI voxel size. Recently, high field gradient echo MRI (GE) has attracted considerable attention for its detailed anatomical contrast even within the white and gray matter. ⋯ The STIFT method improves the anatomical accuracy of tractography of various fiber tracts, such as the optic radiation and cingulum. Furthermore, it has been demonstrated that STIFT can differentiate between kissing and crossing fiber configurations. Future investigations are required to establish the applicability in more white matter pathways.
-
We investigated the neural underpinnings of timbral, tonal, and rhythmic features of a naturalistic musical stimulus. Participants were scanned with functional Magnetic Resonance Imaging (fMRI) while listening to a stimulus with a rich musical structure, a modern tango. We correlated temporal evolutions of timbral, tonal, and rhythmic features of the stimulus, extracted using acoustic feature extraction procedures, with the fMRI time series. ⋯ While timbral feature processing was associated with activations in cognitive areas of the cerebellum, and sensory and default mode network cerebrocortical areas, musical pulse and tonality processing recruited cortical and subcortical cognitive, motor and emotion-related circuits. In sum, by combining neuroimaging, acoustic feature extraction and behavioral methods, we revealed the large-scale cognitive, motor and limbic brain circuitry dedicated to acoustic feature processing during listening to a naturalistic stimulus. In addition to these novel findings, our study has practical relevance as it provides a powerful means to localize neural processing of individual acoustical features, be it those of music, speech, or soundscapes, in ecological settings.
-
MRI estimates of brain iron concentration in normal aging using quantitative susceptibility mapping.
Quantifying tissue iron concentration in vivo is instrumental for understanding the role of iron in physiology and in neurological diseases associated with abnormal iron distribution. Herein, we use recently-developed Quantitative Susceptibility Mapping (QSM) methodology to estimate the tissue magnetic susceptibility based on MRI signal phase. To investigate the effect of different regularization choices, we implement and compare ℓ1 and ℓ2 norm regularized QSM algorithms. ⋯ However, QSM values are influenced by factors such as the myelin content, whereas FDRI is a more specific indicator of iron content. Hence, FDRI demonstrated higher specificity to iron yet yielded noisier data despite longer scan times and lower spatial resolution than QSM. The robustness, practicality, and demonstrated ability of predicting the change in iron deposition in adult aging suggest that regularized QSM algorithms using single-field-strength data are possible alternatives to tissue iron estimation requiring two field strengths.
-
Connectivity-based segmentation has been used to identify functional gray matter subregions that are not discernable on conventional magnetic resonance imaging. However, the accuracy and reliability of this technique has only been validated using indirect means. In order to provide direct electrophysiologic validation of connectivity-based thalamic segmentations within human subjects, we assess the correlation of atlas-based thalamic anatomy, connectivity-based thalamic maps, and somatosensory evoked thalamic potentials in two adults with medication-refractory epilepsy who were undergoing intracranial EEG monitoring with intrathalamic depth and subdural cortical strip electrodes. ⋯ This study provides direct electrophysiologic validation of probabilistic tractography-based thalamic segmentation. Importantly, this study provides an electrophysiological basis for using connectivity-based segmentation to further study subcortical anatomy and physiology while also providing the clinical basis for targeting deep brain nuclei with therapeutic stimulation. Finally, these direct recordings from human thalamus confirm early inferences of a sensory thalamic component of the N18 waveform in somatosensory evoked potentials.