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In this study we used functional magnetic resonance imaging to investigate age-related changes in large-scale brain functional networks during memory encoding and recognition in 12 younger and 16 older adults. For each participant, functional brain networks were constructed by computing temporal correlation matrices of 90 brain regions and analyzed using graph theoretical approaches. We found the age-related changes mainly in the long-range connections with widespread reductions associated with aging in the fronto-temporal and temporo-parietal regions, and a few age-related increases in the posterior parietal regions. Graph theoretical analysis revealed that the older adults had longer path lengths linking different regions in the functional brain networks as compared to the younger adults. Further analysis indicated that the increases in shortest path length in the networks were combined with the loss of long-range connections. Finally, we showed that for older adults, frontal areas played reduced roles in the network (reduced regional centrality), whereas several default-mode regions played increased roles relative to younger subjects (increased regional centrality). Together, our results suggest that normal aging is associated with disruption of large-scale brain systems during the performance of memory tasks, which provides novel insights into the understanding of age-related decline in multiple cognitive functions.

Bright-light interventions have successfully been used to reduce depression symptoms in patients with seasonal affective disorder, a depressive disorder most frequently occurring during seasons with reduced daylight availability. Yet, little is known about how light exposure impacts human brain function, for instance on risk taking, a process affected in depressive disorders. Here we examined the modulatory effects of bright-light exposure on brain activity during a risk-taking task. Thirty-two healthy male volunteers living in the greater Copenhagen area received 3weeks of bright-light intervention during the winter season. Adopting a double-blinded dose-response design, bright-light was applied for 30minutes continuously every morning. The individual dose varied between 100 and 11.000lx. Whole-brain functional MRI was performed before and after bright-light intervention to probe how the intervention modifies risk-taking related neural activity during a two-choice gambling task. We also assessed whether inter-individual differences in the serotonin transporter-linked polymorphic region (5-HTTLPR) genotype influenced the effects of bright-light intervention on risk processing. Bright-light intervention led to a dose-dependent increase in risk-taking in the LA/LA group relative to the non-LA/LA group. Further, bright-light intervention enhanced risk-related activity in ventral striatum and head of caudate nucleus in proportion with the individual bright-light dose. The augmentation effect of light exposure on striatal risk processing was not influenced by the 5-HTTLPR-genotype. This study provides novel evidence that in healthy non-depressive individuals bright-light intervention increases striatal processing to risk in a dose-dependent fashion. The findings provide converging evidence that risk processing is sensitive to bright-light exposure during winter.

The model for functional organization of human auditory cortex is in part based on findings in non-human primates, where the auditory cortex is hierarchically delineated into core, belt and parabelt fields. This model envisions that core cortex directly projects to belt, but not to parabelt, whereas belt regions are a major source of direct input for auditory parabelt. In humans, the posteromedial portion of Heschl’s gyrus (HG) represents core auditory cortex, whereas the anterolateral portion of HG and the posterolateral superior temporal gyrus (PLST) are generally interpreted as belt and parabelt, respectively. In this scheme, response latencies can be hypothesized to progress in serial fashion from posteromedial to anterolateral HG to PLST. We examined this hypothesis by comparing response latencies to multiple stimuli, measured across these regions using simultaneous intracranial recordings in neurosurgical patients. Stimuli were 100 Hz click trains and the speech syllable /da/. Response latencies were determined by examining event-related band power in the high gamma frequency range. The earliest responses in auditory cortex occurred in posteromedial HG. Responses elicited from sites in anterolateral HG were neither earlier in latency from sites on PLST, nor more robust. Anterolateral HG and PLST exhibited some preference for speech syllable stimuli compared to click trains. These findings are not supportive of a strict serial model envisioning principal flow of information along HG to PLST. In contrast, data suggest that a portion of PLST may represent a relatively early stage in the auditory cortical hierarchy.

Recent evidence indicates subject-specific gyral folding patterns and white matter anisotropy uniquely shape electric fields generated by TMS. Current methods for predicting the brain regions influenced by TMS involve projecting the TMS coil position or center of gravity onto realistic head models derived from structural and functional imaging data. Similarly, spherical models have been used to estimate electric field distributions generated by TMS pulses delivered from a particular coil location and position. In the present paper we inspect differences between electric field computations estimated using the finite element method (FEM) and projection-based approaches described above. We then more specifically examined an approach for estimating cortical excitation volumes based on individualistic FEM simulations of electric fields. We evaluated this approach by performing neurophysiological recordings during MR-navigated motormapping experiments. We recorded motor evoked potentials (MEPs) in response to single pulse TMS using two different coil orientations (45° and 90° to midline) at 25 different locations (5×5 grid, 1cm spacing) centered on the hotspot of the right first dorsal interosseous (FDI) muscle in left motor cortex. We observed that motor excitability maps varied within and between subjects as a function of TMS coil position and orientation. For each coil position and orientation tested, simulations of the TMS-induced electric field were computed using individualistic FEM models and compared to MEP amplitudes obtained during our motormapping experiments. We found FEM simulations of electric field strength, which take into account subject-specific gyral geometry and tissue conductivity anisotropy, significantly correlated with physiologically observed MEP amplitudes (rmax=0.91, p=1.8×10(-5) rmean=0.81, p=0.01). These observations validate the implementation of individualistic FEM models to account for variations in gyral folding patterns and tissue conductivity anisotropy, which should help improve the targeting accuracy of TMS in the mapping or modulation of human brain circuits. peerReviewed

A single diffusion MRI streamline fiber tracking dataset may contain hundreds of thousands, and often millions of streamlines and can take up to several gigabytes of memory. This amount of data is not only heavy to compute, but also difficult to visualize and hard to store on disk (especially when dealing with a collection of brains). These problems call for a fiber-specific compression format that simplifies its manipulation. As of today, no fiber compression format has yet been adopted and the need for it is now becoming an issue for future connectomics research. In this work, we propose a new compression format, .zfib, for streamline tractography datasets reconstructed from diffusion magnetic resonance imaging (dMRI). Tracts contain a large amount of redundant information and are relatively smooth. Hence, they are highly compressible. The proposed method is a processing pipeline containing a linearization, a quantization and an encoding step. Our pipeline is tested and validated under a wide range of DTI and HARDI tractography configurations (step size, streamline number, deterministic and probabilistic tracking) and compression options. Similar to JPEG, the user has one parameter to select: a worst-case maximum tolerance error in millimeter (mm). Overall, we find a compression factor of more than 96% for a maximum error of 0.1mm without any perceptual change or change of diffusion statistics (mean fractional anisotropy and mean diffusivity) along bundles. This opens new opportunities for connectomics and tractometry applications.

Multivariate pattern analysis (MVPA) in fMRI has been used to extract information from distributed cortical activation patterns, which may go undetected in conventional univariate analysis. However, little is known about the physical and physiological underpinnings of MVPA in fMRI as well as about the effect of spatial smoothing on its performance. Several studies have addressed these issues, but their investigation was limited to the visual cortex at 3T with conflicting results. Here, we used ultra-high field (7T) fMRI to investigate the effect of spatial resolution and smoothing on decoding of speech content (vowels) and speaker identity from auditory cortical responses. To that end, we acquired high-resolution (1.1mm isotropic) fMRI data and additionally reconstructed them at 2.2 and 3.3mm in-plane spatial resolutions from the original k-space data. Furthermore, the data at each resolution were spatially smoothed with different 3D Gaussian kernel sizes (i.e. no smoothing or 1.1, 2.2, 3.3, 4.4, or 8.8mm kernels). For all spatial resolutions and smoothing kernels, we demonstrate the feasibility of decoding speech content (vowel) and speaker identity at 7T using support vector machine (SVM) MVPA. In addition, we found that high spatial frequencies are informative for vowel decoding and that the relative contribution of high and low spatial frequencies is different across the two decoding tasks. Moderate smoothing (up to 2.2mm) improved the accuracies for both decoding of vowels and speakers, possibly due to reduction of noise (e.g. residual motion artifacts or instrument noise) while still preserving information at high spatial frequency. In summary, our results show that - even with the same stimuli and within the same brain areas - the optimal spatial resolution for MVPA in fMRI depends on the specific decoding task of interest.

Dopaminergic neurotransmission in extrastriatal regions may play a crucial role in the pathophysiology and treatment of neuropsychiatric disorders. The high-affinity radioligands [(11)C]FLB 457, [(123)I]epidepride, and [(18)F]fallypride are now used in clinical studies to measure these low-density receptor populations in vivo. However, a single determination of the regional binding potential (BP) does not differentiate receptor density (B(max)) from the apparent affinity (K(D)). In this positron emission tomography (PET) study, we measured extrastriatal dopamine D2 receptor density (B(max)) and apparent affinity (K(D)) in 10 healthy subjects using an in vivo saturation approach. Each subject participated in two to three PET measurements with different specific radioactivity of [(11)C]FLB 457. The commonly used simplified reference tissue model (SRTM) was used in a comparison of BP values with the B(max) values obtained from the saturation analysis. The calculated regional receptor density values were of the same magnitude (0.33-1.68 nM) and showed the same rank order as reported from postmortem studies, that is, in descending order thalamus, lateral temporal cortex, anterior cinguli, and frontal cortex. The affinity ranged from 0.27 to 0.43 nM, that is, approximately 10-20 times the value found in vitro (20 pM). The area under the cerebellar time activity curve (TAC) was slightly lower (11 +/- 8%, mean +/- SD, P = 0.004, n = 10) after injection of low as compared with high specific radioactivity, indicating sensitivity to the minute density of dopamine D2 receptors in the this region. The results of the present study support that dopamine D2 receptor density and affinity can be differentiated in low-density regions using a saturation approach. There was a significant (P < 0.001) correlation between the binding potential calculated with SRTM and the receptor density (B(max)), which supports the use of BP in clinical studies where differentiation of B(max) and K(D) is not required. In such studies, the mass of FLB 457 has to be less than 0.5 microg injected to avoid a mass effect of the radioligand itself.

The APOE e4 allele, which confers an increased risk of developing dementia in older adulthood, has been associated with enhanced cognitive performance in younger adults. An objective of the current study was to compare task-related behavioural and neural signatures for e4 carriers (e4+) and non-e4 carriers (e4-) to help elucidate potential mechanisms behind such cognitive differences. On two measures of attention, we recorded clear behavioural advantages in young adult e4+ relative to e4-, suggesting that e4+ performed these tasks with a wider field of attention. Behavioural advantages were associated with increased task-related brain activations detected by fMRI (BOLD). In addition, behavioural measures correlated with structural measures derived from a former DTI analysis of white matter integrity in our cohort. These data provide clear support for an antagonistic pleiotropy hypothesis - that the e4 allele confers some cognitive advantage in early life despite adverse consequences in old age. The data implicate differences in both structural and functional signatures as complementary mediators of the behavioural advantage.