Helmut Heinsen

Bio: Helmut Heinsen is an academic researcher from University of São Paulo. The author has contributed to research in topics: Basal forebrain & Neurodegeneration. The author has an hindex of 48, co-authored 180 publications receiving 7983 citations. Previous affiliations of Helmut Heinsen include RWTH Aachen University & Icahn School of Medicine at Mount Sinai.

Increased iron (III) and total iron content in post mortem substantia nigra of parkinsonian brain.

Abstract: Significant differences in the content of iron (III) and total iron were found in post mortem substantia nigra of Parkinson's disease There was an increase of 176% in the levels of total iron and 255% of iron (III) in the substantia nigra of the parkinsonian patients compared to age matched controls In the cortex (Brodmann area 21), hippocampus, putamen, and globus pallidus there was no significant difference in the levels of iron (III) and total iron Thus the changes in total iron, iron (III) and the iron (II)/iron (III) ratio in the parkinsonian substantia nigra are likely to be involved in the pathophysiology and treatment of this disorder

Minicolumnar abnormalities in autism

Abstract: Autism is characterized by qualitative abnormalities in behavior and higher order cognitive functions. Minicolumnar irregularities observed in autism provide a neurologically sound localization to observed clinical and anatomical abnormalities. This study corroborates the initial reports of a minicolumnopathy in autism within an independent sample. The patient population consisted of six age-matched pairs of patients (DSM-IV-TR and ADI-R diagnosed) and controls. Digital micrographs were taken from cortical areas S1, 4, 9, and 17. The image analysis produced estimates of minicolumnar width (CW), mean interneuronal distance, variability in CW (V (CW)), cross section of Nissl-stained somata, boundary length of stained somata per unit area, and the planar convexity. On average CW was 27.2 microm in controls and 25.7 microm in autistic patients (P = 0.0234). Mean neuron and nucleolar cross sections were found to be smaller in autistic cases compared to controls, while neuron density in autism exceeded the comparison group by 23%. Analysis of inter- and intracluster distances of a Delaunay triangulation suggests that the increased cell density is the result of a greater number of minicolumns, otherwise the number of cells per minicolumns appears normal. A reduction in both somatic and nucleolar cross sections could reflect a bias towards shorter connecting fibers, which favors local computation at the expense of inter-areal and callosal connectivity.

Locus coeruleus volume and cell population changes during Alzheimer's disease progression: A stereological study in human postmortem brains with potential implication for early-stage biomarker discovery

Abstract: Introduction Alzheimer's disease (AD) progression follows a specific spreading pattern, emphasizing the need to characterize those brain areas that degenerate first. The brainstem's locus coeruleus (LC) is the first area to develop neurofibrillary changes (neurofibrillary tangles [NFTs]). Methods The methods include unbiased stereological analyses in human brainstems to estimate LC volume and neuronal population in controls and individuals across all AD stages. Results As the Braak stage increases by 1 unit, the LC volume decreases by 8.4%. Neuronal loss started only midway through AD progression. Age-related changes spare the LC. Discussion The long gap between NFT accumulation and neuronal loss suggests that a second trigger may be necessary to induce neuronal death in AD. Imaging studies should determine whether LC volumetry can replicate the stage-wise atrophy observed here and how these changes are specific to AD. LC volumetry may develop into a screening biomarker for selecting high-yield candidates to undergo expensive and less accessible positron emission tomography scans and to monitor AD progression from presymptomatic stages.

Neurons in the fusiform gyrus are fewer and smaller in autism

Abstract: Abnormalities in face perception are a core feature of social disabilities in autism. Recent functional magnetic resonance imaging studies showed that patients with autism could perform face perception tasks. However, the fusiform gyrus (FG) and other cortical regions supporting face processing in controls are hypoactive in patients with autism. The neurobiological basis of this phenomenon is unknown. Here, we tested the hypothesis that the FG shows neuropathological alterations in autism, namely alterations in neuron density, total neuron number and mean perikaryal volume. We investigated the FG (analysing separately layers II, III, IV, V and VI), in seven post-mortem brains from patients with autism and 10 controls for volume, neuron density, total neuron number and mean perikaryal volume with high-precision design-based stereology. To determine whether these results were specific for the FG, the same analyses were also performed in the primary visual cortex and in the cortical grey matter as a whole. Compared to controls, patients with autism showed significant reductions in neuron densities in layer III, total neuron numbers in layers III, V and VI, and mean perikaryal volumes of neurons in layers V and VI in the FG. None of these alterations were found in the primary visual cortex or in the whole cerebral cortex. Although based on a relatively small sample of post-mortem brains from patients with autism and controls, the results of the present study may provide important insight about the cellular basis of abnormalities in face perception in autism.

Measurement of basal forebrain atrophy in Alzheimer's disease using MRI

Abstract: Alzheimer’s disease is characterized by the degeneration and loss of cholinergic neurones in the nucleus basalis Meynert, located within the substantia innominata at the ventral surface of the basal forebrain. An in vivo measure of morphological changes in the nucleus basalis Meynert would be of high relevance to better understand the structural correlate of cholinergic dysfunction in Alzheimer’s disease. In this study, we applied a newly developed automated technique of image regression analysis, implemented through code written in Matlab 5.3 (MathWorks, Natick, MA), to the analysis of proton density weighted structural MRI of the basal forebrain from 13 patients with Alzheimer’s disease (mean age = 77.5 years, SD = 4.4 years, 8 women) and 12 healthy elderly subjects (mean age = 62.3 years, SD = 5.6 years, 6 women). This technique allows searching a large portion of the substantia innominata for signal changes. We used corresponding MRI and histological sections of a post mortem brain to map the locations of basal forebrain cholinergic nuclei into the MRI standard space. Additionally, we used voxel-based morphometry, implemented in SPM2 (Wellcome Department of Imaging Neuroscience, London, UK) to determine correlations between signal changes in the substantia innominata and cortical grey matter atrophy in the patients with Alzheimer’s disease. When matching the locations of signal reductions in the in vivo MRI to the template of basal nuclei based on the postmortem brain, signal intensity was decreased in areas corresponding to anterior lateral and anterior medial nucleus basalis Meynert and increased in the third ventricle, the transverse fissure and the optic tract in patients with Alzheimer’s disease compared with controls. The reduction of the signal intensity in an area corresponding to the anterior lateral nucleus basalis Meynert was significantly correlated with reduced grey matter concentration in the bilateral prefrontal cortex, inferior parietal lobule and cingulate gyrus. Our findings suggest that signal changes occur in patients with Alzheimer’s disease in the substantia innominata which may be related to the loss or degeneration of cholinergic neurones and correspond to regional cortical grey matter atrophy. If replicated in an independent sample, our technique may be useful to detect degeneration of basal forebrain cholinergic neurones in vivo.

Pattern Recognition and Machine Learning

Abstract: Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

Principles of Neural Science

Abstract: I have developed "tennis elbow" from lugging this book around the past four weeks, but it is worth the pain, the effort, and the aspirin. It is also worth the (relatively speaking) bargain price. Including appendixes, this book contains 894 pages of text. The entire panorama of the neural sciences is surveyed and examined, and it is comprehensive in its scope, from genomes to social behaviors. The editors explicitly state that the book is designed as "an introductory text for students of biology, behavior, and medicine," but it is hard to imagine any audience, interested in any fragment of neuroscience at any level of sophistication, that would not enjoy this book. The editors have done a masterful job of weaving together the biologic, the behavioral, and the clinical sciences into a single tapestry in which everyone from the molecular biologist to the practicing psychiatrist can find and appreciate his or

Neuropathological Alterations in Alzheimer Disease

Abstract: The neuropathological hallmarks of Alzheimer disease (AD) include “positive” lesions such as amyloid plaques and cerebral amyloid angiopathy, neurofibrillary tangles, and glial responses, and “negative” lesions such as neuronal and synaptic loss. Despite their inherently cross-sectional nature, postmortem studies have enabled the staging of the progression of both amyloid and tangle pathologies, and, consequently, the development of diagnostic criteria that are now used worldwide. In addition, clinicopathological correlation studies have been crucial to generate hypotheses about the pathophysiology of the disease, by establishing that there is a continuum between “normal” aging and AD dementia, and that the amyloid plaque build-up occurs primarily before the onset of cognitive deficits, while neurofibrillary tangles, neuron loss, and particularly synaptic loss, parallel the progression of cognitive decline. Importantly, these cross-sectional neuropathological data have been largely validated by longitudinal in vivo studies using modern imaging biomarkers such as amyloid PET and volumetric MRI.