MR image-based measurement of rates of change in volumes of brain structures. Part II: Application to a study of Alzheimer's disease and normal aging

We present global and regional rates of brain atrophy measured on serially acquired Tl-weighted brain MR images for a group of Alzheimer's disease (AD) patients and age-matched normal control (NC) subjects using the analysis procedure described in Part I. Three rates of brain atrophy: the rate of atrophy in the cerebrum, the rate of lateral ventricular enlargement and the rate of atrophy in the region of temporal lobes, were evaluated for 14 AD patients and 14 age-matched NC subjects. All three rates showed significant differences between the two groups. However, the greatest separation of the two groups was obtained when the regional rates were combined. This application has demonstrated that rates of brain atrophy, especially in specific regions of the brain, based on MR images can provide sensitive measures for evaluating the progression of AD. These measures will be useful for the evaluation of therapeutic effects of novel therapies for AD.

A reproducible method for automated extraction of brain volumes from 3D human head MR images

An automated method for extracting brain volumes from three commonly acquired three-dimensional (3D) MR images (proton density, T1 weighted, and T2-weighted) of the human head is described. The procedure is divided into four levels: preprocessing, segmentation, scalp removal, and postprocessing. A user-provided reference point is the sole operator-dependent input required. The method's parameters were first optimized and then fixed and applied to 30 repeat data sets from 15 normal older adult subjects to investigate its reproducibility. Percent differences between total brain volumes (TBVs) for the subjects' repeated data sets ranged from .5% to 2.2%. We conclude that the method is both robust and reproducible and has the potential for wide application.

Brain network efficiency and topology depend on the fiber tracking method: 11 tractography algorithms compared in 536 subjects

As connectivity analyses become more popular, claims are often made about how the brain's anatomical networks depend on age, sex, or disease. It is unclear how results depend on tractography methods used to compute fiber networks. We applied 11 tractography methods to high angular resolution diffusion images of the brain (4-Tesla 105-gradient HARDI) from 536 healthy young adults. We parcellated 70 cortical regions, yielding 70×70 connectivity matrices, encoding fiber density. We computed popular graph theory metrics, including network efficiency, and characteristic path lengths. Both metrics were robust to the number of spherical harmonics used to model diffusion (4th-8th order). Age effects were detected only for networks computed with the probabilistic Hough transform method, which excludes smaller fibers. Sex and total brain volume affected networks measured with deterministic, tensor-based fiber tracking but not with the Hough method. Each tractography method includes different fibers, which affects inferences made about the reconstructed networks.

How does angular resolution affect diffusion imaging measures?

A key question in diffusion imaging is how many diffusion-weighted images suffice to provide adequate signal-to-noise ratio (SNR) for studies of fiber integrity. Motion, physiological effects, and scan duration all affect the achievable SNR in real brain images, making theoretical studies and simulations only partially useful. We therefore scanned 50 healthy adults with 105-gradient high-angular resolution diffusion imaging (HARDI) at 4T. From gradient image subsets of varying size (6 ≤ N ≤ 94) that optimized a spherical angular distribution energy, we created SNR plots (versus gradient numbers) for seven common diffusion anisotropy indices: fractional and relative anisotropy (FA, RA), mean diffusivity (MD), volume ratio (VR), geodesic anisotropy (GA), its hyperbolic tangent (tGA), and generalized fractional anisotropy (GFA). SNR, defined in a region of interest in the corpus callosum, was near-maximal with 58, 66, and 62 gradients for MD, FA, and RA, respectively, and with about 55 gradients for GA and tGA. For VR and GFA, SNR increased rapidly with more gradients. SNR was optimized when the ratio of diffusion-sensitized to non-sensitized images was 9.13 for GA and tGA, 10.57 for FA, 9.17 for RA, and 26 for MD and VR. In orientation density functions modeling the HARDI signal as a continuous mixture of tensors, the diffusion profile reconstruction accuracy rose rapidly with additional gradients. These plots may help in making trade-off decisions when designing diffusion imaging protocols.

Analyzing multi-fiber reconstruction in high angular resolution diffusion imaging using the tensor distribution function

High-angular resolution diffusion imaging (HARDI) can reconstruct fiber pathways in the brain with extraordinary detail, identifying anatomical features and connections not seen with conventional MRI. HARDI overcomes several limitations of standard diffusion tensor imaging, which fails to model diffusion correctly in regions where fibers cross or mix. As HARDI can accurately resolve sharp signal peaks in angular space where fibers cross, we studied how many gradients are required in practice to compute accurate orientation density functions, to better understand the tradeoff between longer scanning times and more angular precision. We computed orientation density functions analytically from tensor distribution functions (TDFs) which model the HARDI signal at each point as a unit-mass probability density on the 6D manifold of symmetric positive definite tensors. In simulated two-fiber systems with varying Rician noise, we assessed how many diffusionsensitized gradients were sufficient to (1) accurately resolve the diffusion profile, and (2) measure the exponential isotropy (EI), a TDF-derived measure of fiber integrity that exploits the full multidirectional HARDI signal. At lower SNR, the reconstruction accuracy, measured using the Kullback-Leibler divergence, rapidly increased with additional gradients, and EI estimation accuracy plateaued at around 70 gradients.

Lateralization of temporal lobe epilepsy based on resting-state functional magnetic resonance imaging and machine learning

Lateralization of temporal lobe epilepsy (TLE) is critical for successful outcome of surgery to relieve seizures. TLE affects brain regions beyond the temporal lobes and has been associated with aberrant brain networks, based on evidence from functional magnetic resonance imaging. We present here a machine learning-based method for determining the laterality of TLE, using features extracted from resting-state functional connectivity of the brain. A comprehensive feature space was constructed to include network properties within local brain regions, between brain regions, and across the whole network. Feature selection was performed based on random forest and a support vector machine was employed to train a linear model to predict the laterality of TLE on unseen patients. A leave-one-patient-out cross validation was carried out on 12 patients and a prediction accuracy of 83% was achieved. The importance of selected features was analyzed to demonstrate the contribution of resting-state connectivity attributes at voxel, region, and network levels to TLE lateralization.

Meta-analysis of structural imaging findings in Attention-Deficit/Hyperactivity Disorder

Background Although there are many structural neuroimaging studies of attention-deficit/hyperactivity disorder (ADHD) in children, there are inconsistencies across studies and no consensus regarding which brain regions show the most robust area or volumetric reductions relative to control subjects. Our goal was to statistically analyze structural imaging data via a meta-analysis to help resolve these issues. Methods We searched the MEDLINE and PsycINFO databases through January 2005. Studies must have been written in English, used magnetic resonance imaging, and presented the means and standard deviations of regions assessed. Data were extracted by one of the authors and verified independently by another author. Results Analyses were performed using STATA with metan, metabias, and metainf programs. A meta-analysis including all regions across all studies indicated global reductions for ADHD subjects compared with control subjects, standardized mean difference equal to .408, p less than .001. Regions most frequently assessed and showing the largest differences included cerebellar regions, the splenium of the corpus callosum, total and right cerebral volume, and right caudate. Several frontal regions assessed in only two studies also showed large significant differences. Conclusions This meta-analysis provides a quantitative analysis of neuroanatomical abnormalities in ADHD and information that can be used to guide future studies.

Turning gaming EEG peripherals into trainable brain computer interfaces

Companies such as NeuroSky and Emotiv Systems are selling non-medical EEG devices for human computer interaction. These devices are significantly more affordable than their medical counterparts, and are mainly used to measure levels of engagement, focus, relaxation and stress. This information is sought after for marketing research and games. However, these EEG devices have the potential to enable users to interact with their surrounding environment using thoughts only, without activating any muscles. In this paper, we present preliminary results that demonstrate that despite reduced voltage and time sensitivity compared to medical-grade EEG systems, the quality of the signals of the Emotiv EPOC neuroheadset is sufficiently good in allowing discrimina tion between imaging events. We collected streams of EEG raw data and trained different types of classifiers to discriminate between three states (rest and two imaging events). We achieved a generalisation error of less than 2% for two types of non-linear classifiers.

MEG Adaptation resolves the spatiotemporal characteristics of face-sensitive brain responses

An unresolved goal in face perception is to identify brain areas involved in face processing and simultaneously understand the timing of their involvement. Currently, high spatial resolution imaging techniques identify the fusiform gyrus as subserving processing of invariant face features relating to identity. High temporal resolution imaging techniques localize an early latency evoked component—the N/M170—as having a major generator in the fusiform region; however, this evoked component is not believed to be associated with the processing of identity. To resolve this, we used novel magnetoencephalographic beamformer analyses to localize cortical regions in humans spatially with trial-by-trial activity that differentiated faces and objects and to interrogate their functional sensitivity by analyzing the effects of stimulus repetition. This demonstrated a temporal sequence of processing that provides category-level and then item-level invariance. The right fusiform gyrus showed adaptation to faces (not objects) at ∼150 ms after stimulus onset regardless of face identity; however, at the later latency of ∼200–300 ms, this area showed greater adaptation to repeated identity faces than to novel identities. This is consistent with an involvement of the fusiform region in both early and midlatency face-processing operations, with only the latter showing sensitivity to invariant face features relating to identity.

Determinants of vascular cognitive impairment : White matter lesions, brain atrophy and their neuropsychological correlates

The concept of vascular cognitive impairment (VCI) covers a wide spectrum of cognitive dysfunctions related to cerebrovascular disease. Among the pathophysiological determinants of VCI are cerebral stroke, white matter lesions and brain atrophy, which are known to be important risk factors for dementia. However, the specific mechanisms behind the brain abnormalities and cognitive decline are still poorly understood. The present study investigated the neuropsychological correlates of particular magnetic resonance imaging (MRI) findings, namely, medial temporal lobe atrophy (MTA), white matter hyperintensities (WMH), general cortical atrophy and corpus callosum (CC) atrophy in subjects with cerebrovascular disease. Furthermore, the cognitive profile of subcortical ischaemic vascular disease (SIVD) was examined. This study was conducted as part of two large multidisciplinary study projects, the Helsinki Stroke Aging Memory (SAM) Study and the multinational Leukoaraiosis and Disability (LADIS) Study. The SAM cohort consisted of 486 patients, between 55 and 85 years old, with ischaemic stroke from the Helsinki University Hospital, Helsinki, Finland. The LADIS Study included a mixed sample of subjects (n=639) with age-related WMH, between 65 and 84 years old, gathered from 11 centres around Europe. Both studies included comprehensive clinical and neuropsychological assessments and detailed brain MRI. The relationships between the MRI findings and the neuropsychological test performance were analysed by controlling for relevant confounding factors such as age, education and other coexisting brain lesions. The results revealed that in elderly patients with ischaemic stroke, moderate to severe MTA was specifically related to impairment of memory and visuospatial functions, but mild MTA had no clinical relevance. Instead, WMH were primarily associated with executive deficits and mental slowing. These deficits mediated the relationship between WMH and other, secondary cognitive deficits. Cognitive decline was best predicted by the overall degree of WMH, whereas the independent contribution of regional WMH measures was low. Executive deficits were the most prominent cognitive characteristic in SIVD. Compared to other stroke patients, the patients with SIVD also presented more severe memory deficits, which were related to MTA. The cognitive decline in SIVD occurred independently of depressive symptoms and, relative to healthy control subjects, it was substantial in severity. In stroke patients, general cortical atrophy also turned out to be a strong predictor of cognitive decline in a wide range of cognitive domains. Moreover, in elderly subjects with WMH, overall CC atrophy was related to reduction in mental speed, while anterior CC atrophy was independently associated with frontal lobe-mediated executive functions and attention. The present study provides cross-sectional evidence for the involvement of WMH, MTA, general cortical atrophy and CC atrophy in VCI. The results suggest that there are multifaceted pathophysiological mechanisms behind VCI in the elderly, including both vascular ischaemic lesions and neurodegenerative changes. The different pathological changes are highly interrelated processes and together they may produce cumulative effects on cognitive decline.

Social perception and cognition : processing of gestures, postures and facial expressions in the human brain

Humans are a social species with the internal capability to process social information from other humans. To understand others behavior and to react accordingly, it is necessary to infer their internal states, emotions and aims, which are conveyed by subtle nonverbal bodily cues such as postures, gestures, and facial expressions. This thesis investigates the brain functions underlying the processing of such social information. Studies I and II of this thesis explore the neural basis of perceiving pain from another person s facial expressions by means of functional magnetic resonance imaging (fMRI) and magnetoencephalography (MEG). In Study I, observing another s facial expression of pain activated the affective pain system (previously associated with self-experienced pain) in accordance with the intensity of the observed expression. The strength of the response in anterior insula was also linked to the observer s empathic abilities. The cortical processing of facial pain expressions advanced from the visual to temporal-lobe areas at similar latencies (around 300 500 ms) to those previously shown for emotional expressions such as fear or disgust. Study III shows that perceiving a yawning face is associated with middle and posterior STS activity, and the contagiousness of a yawn correlates negatively with amygdalar activity. Study IV explored the brain correlates of interpreting social interaction between two members of the same species, in this case human and canine. Observing interaction engaged brain activity in very similar manner for both species. Moreover, the body and object sensitive brain areas of dog experts differentiated interaction from noninteraction in both humans and dogs whereas in the control subjects, similar differentiation occurred only for humans. Finally, Study V shows the engagement of the brain area associated with biological motion when exposed to the sounds produced by a single human being walking. However, more complex pattern of activation, with the walking sounds of several persons, suggests that as the social situation becomes more complex so does the brain response. Taken together, these studies demonstrate the roles of distinct cortical and subcortical brain regions in the perception and sharing of others internal states via facial and bodily gestures, and the connection of brain responses to behavioral attributes.

Human brain mechanisms of auditory and audiovisual selective attention

Selective attention refers to the process in which certain information is actively selected for conscious processing, while other information is ignored. The aim of the present studies was to investigate the human brain mechanisms of auditory and audiovisual selective attention with functional magnetic resonance imaging (fMRI), electroencephalography (EEG) and magnetoencephalography (MEG). The main focus was on attention-related processing in the auditory cortex. It was found that selective attention to sounds strongly enhances auditory cortex activity associated with processing the sounds. In addition, the amplitude of this attention-related modulation was shown to increase with the presentation rate of attended sounds. Attention to the pitch of sounds and to their location appeared to enhance activity in overlapping auditory-cortex regions. However, attention to location produced stronger activity than attention to pitch in the temporo-parietal junction and frontal cortical regions. In addition, a study on bimodal attentional selection found stronger audiovisual than auditory or visual attention-related modulations in the auditory cortex. These results were discussed in light of Näätänen s attentional-trace theory and other research concerning the brain mechanisms of selective attention.

Sleep deprivation and brain energy metabolism : in vivo studies in rats and humans

Sleep deprivation leads to increased subsequent sleep length and depth and to deficits in cognitive performance in humans. In animals extreme sleep deprivation is eventually fatal. The cellular and molecular mechanisms causing the symptoms of sleep deprivation are unclear. This thesis was inspired by the hypothesis that during wakefulness brain energy stores would be depleted, and they would be replenished during sleep. The aim of this thesis was to elucidate the energy metabolic processes taking place in the brain during sleep deprivation. Endogenous brain energy metabolite levels were assessed in vivo in rats and in humans in four separate studies (Studies I-IV). In the first part (Study I) the effects of local energy depletion on brain energy metabolism and sleep were studied in rats with the use of in vivo microdialysis combined with high performance liquid chromatography. Energy depletion induced by 2,4-dinitrophenol infusion into the basal forebrain was comparable to the effects of sleep deprivation: both increased extracellular concentrations of adenosine, lactate, and pyruvate, and elevated subsequent sleep. This result supports the hypothesis of a connection between brain energy metabolism and sleep. The second part involved healthy human subjects (Studies II-IV). Study II aimed to assess the feasibility of applying proton magnetic resonance spectroscopy (1H MRS) to study brain lactate levels during cognitive stimulation. Cognitive stimulation induced an increase in lactate levels in the left inferior frontal gyrus, showing that metabolic imaging of neuronal activity related to cognition is possible with 1H MRS. Study III examined the effects of sleep deprivation and aging on the brain lactate response to cognitive stimulation. No physiologic, cognitive stimulation-induced lactate response appeared in the sleep-deprived and in the aging subjects, which can be interpreted as a sign of malfunctioning of brain energy metabolism. This malfunctioning may contribute to the functional impairment of the frontal cortex both during aging and sleep deprivation. Finally (Study IV), 1H MRS major metabolite levels in the occipital cortex were assessed during sleep deprivation and during photic stimulation. N-acetyl-aspartate (NAA/H2O) decreased during sleep deprivation, supporting the hypothesis of sleep deprivation-induced disturbance in brain energy metabolism. Choline containing compounds (Cho/H2O) decreased during sleep deprivation and recovered to alert levels during photic stimulation, pointing towards changes in membrane metabolism, and giving support to earlier observations of altered brain response to stimulation during sleep deprivation. Based on these findings, it can be concluded that sleep deprivation alters brain energy metabolism. However, the effects of sleep deprivation on brain energy metabolism may vary from one brain area to another. Although an effect of sleep deprivation might not in all cases be detectable in the non-stimulated baseline state, a challenge imposed by cognitive or photic stimulation can reveal significant changes. It can be hypothesized that brain energy metabolism during sleep deprivation is more vulnerable than in the alert state. Changes in brain energy metabolism may participate in the homeostatic regulation of sleep and contribute to the deficits in cognitive performance during sleep deprivation.

Functional imaging of peripheral vision and dorsal stream function in the human cerebral cortex

Visual information processing in brain proceeds in both serial and parallel fashion throughout various functionally distinct hierarchically organised cortical areas. Feedforward signals from retina and hierarchically lower cortical levels are the major activators of visual neurons, but top-down and feedback signals from higher level cortical areas have a modulating effect on neural processing. My work concentrates on visual encoding in hierarchically low level cortical visual areas in human brain and examines neural processing especially in cortical representation of visual field periphery. I use magnetoencephalography and functional magnetic resonance imaging to measure neuromagnetic and hemodynamic responses during visual stimulation and oculomotor and cognitive tasks from healthy volunteers. My thesis comprises six publications. Visual cortex forms a great challenge for modeling of neuromagnetic sources. My work shows that a priori information of source locations are needed for modeling of neuromagnetic sources in visual cortex. In addition, my work examines other potential confounding factors in vision studies such as light scatter inside the eye which may result in erroneous responses in cortex outside the representation of stimulated region, and eye movements and attention. I mapped cortical representations of peripheral visual field and identified a putative human homologue of functional area V6 of the macaque in the posterior bank of parieto-occipital sulcus. My work shows that human V6 activates during eye-movements and that it responds to visual motion at short latencies. These findings suggest that human V6, like its monkey homologue, is related to fast processing of visual stimuli and visually guided movements. I demonstrate that peripheral vision is functionally related to eye-movements and connected to rapid stream of functional areas that process visual motion. In addition, my work shows two different forms of top-down modulation of neural processing in the hierachically lowest cortical levels; one that is related to dorsal stream activation and may reflect motor processing or resetting signals that prepare visual cortex for change in the environment and another local signal enhancement at the attended region that reflects local feed-back signal and may perceptionally increase the stimulus saliency.

Children and adolescents in full-time special education : an epidemiological and magnetic resonance imaging study

The need for special education (SE) is increasing. The majority of those whose problems are due to neurodevelopmental disorders have no specific aetiology. The aim of this study was to evaluate the contribution of prenatal and perinatal factors and factors associated with growth and development to later need for full-time SE and to assess joint structural and volumetric brain alterations among subjects with unexplained, familial need for SE. A random sample of 900 subjects in full-time SE allocated into three levels of neurodevelopmental problems and 301 controls in mainstream education (ME) provided data on socioeconomic factors, pregnancy, delivery, growth, and development. Of those, 119 subjects belonging to a sibling-pair in full-time SE with unexplained aetiology and 43 controls in ME underwent brain magnetic resonance imaging (MRI). Analyses of structural brain alterations and midsagittal area and diameter measurements were made. Voxel-based morphometry (VBM) analysis provided detailed information on regional grey matter, white matter, and cerebrospinal fluid (CSF) volume differences. Father’s age ≥ 40 years, low birth weight, male sex, and lower socio-economic status all increased the probability of SE placement. At age 1 year, one standard deviation score decrease in height raised the probability of SE placement by 40% and in head circumference by 28%. At infancy, the gross motor milestones differentiated the children. From age 18 months, the fine motor milestones and those related to speech and social skills became more important. Brain MRI revealed no specific aetiology for subjects in SE. However, they had more often ≥ 3 abnormal findings in MRIs (thin corpus callosum and enlarged cerebral and cerebellar CSF spaces). In VBM, subjects in full-time SE had smaller global white matter, CSF, and total brain volumes than controls. Compared with controls, subjects with intellectual disabilities had regional volume alterations (greater grey matter volumes in the anterior cingulate cortex bilaterally, smaller grey matter volume in left thalamus and left cerebellar hemisphere, greater white matter volume in the left fronto-parietal region, and smaller white matter volumes bilaterally in the posterior limbs of the internal capsules). In conclusion, the epidemiological studies emphasized several factors that increased the probability of SE placement, useful as a framework for interventional studies. The global and regional brain MRI findings provide an interesting basis for future investigations of learning-related brain structures in young subjects with cognitive impairments or intellectual disabilities of unexplained, familial aetiology.