Martin Lauterbach

A longitudinal study of neurological soft signs from late childhood into early adulthood.

Neurological examination of children includes the screening for soft neurological signs (NSS). There is little knowledge about their evolution during adolescence, except that their lasting presence has been associated with developmental, psychological, and cognitive disorders.

A randomized, rater-blinded, parallel trial of intensive speech therapy in sub-acute post-stroke aphasia: the SP-I-R-IT study.

BACKGROUND There is conflicting evidence regarding the benefits of intensive speech and language therapy (SLT), particularly because intensity is often confounded with total SLT provided. AIMS A two-centre, randomized, rater-blinded, parallel study was conducted to compare the efficacy of 100 h of SLT in a regular (RT) versus intensive (IT) treatment in sub-acute post-stroke aphasia. METHODS & PROCEDURES Consecutive patients with aphasia, within 3 months of a left hemisphere ischemic stroke, were randomized to IT (2 h per day × 5 days per week, 10 weeks) or RT (2 h per week × 50 weeks). Evaluations took place at 10, 50 and 62 weeks. Primary outcome was the frequency of responders, defined by 15% increase of Aphasia Quotient (AQ) from the baseline to 50 weeks. Secondary outcomes were changes from the baseline in AQ and functional communication profile (FCP) at 50 and 62 weeks and improvement stability between 50 and 62 weeks. OUTCOMES & RESULTS Thirty patients were randomized and 18 completed the study. No significant differences were found between groups in primary or secondary outcomes, although IT patients (N = 9) obtained higher scores in language measures between 10 and 62 weeks in per protocol analysis. The number of non-completions was identical between groups. CONCLUSIONS & IMPLICATIONS This study suggests that, in the sub-acute period following stroke and controlling for the number of hours of SLT provided, there is a trend for a greater improvement in language and functional communication measures with IT compared with RT. The lack of statistical significance in results was probably due to the small sample size.

Cross linguistic aphasia testing: the Portuguese version of the Aachen Aphasia Test (AAT).

We report the adaptation of the Aachen Aphasia Test (AAT) to the Portuguese language (PAAT) and the results of its standardization in 125 persons with aphasia and 153 healthy controls. Patients with aphasia had a previous syndromic diagnosis, obtained through a Portuguese aphasia battery, which served as a reference. The control group was stratified by age and educational level. Hierarchical cluster analyses showed good construct validity. The increasing degree of difficulty and complexity throughout the item sets comprising subtests was confirmed. The discriminatory power of the PAAT for the selection of aphasic from non-aphasic persons proved to be as high as for the AAT versions in other languages. Classification of standard aphasic syndromes by means of discriminant analyses was good. Internal consistency, measured by means of Cronbachs alpha coefficient, was high to very high for the different PAAT subtests. Performance differences caused by age or educational level among the healthy control persons emphasized the need for correction factors. In conclusion, the PAAT showed robust psychometric properties, comparable to the original German and to adaptations to other languages. It constitutes a useful tool for cross-linguistic and multicenter studies.

Neural physiological modeling towards a hemodynamic response function for fMRI

The BOLD signal provided by the functional MRI medical modality measures the ratio of oxy- to deoxy- haemoglobin at each location inside the brain. The detection of activated regions upon the application of an external stimulus, e.g., visual or auditive, is based on the comparison of the mentioned ratios of a rest condition (pre-stimulus) and of a stimulated condition (post-stimulus). Therefore, an accurate knowledge of the impulse response of the BOLD signal to neural stimulus in a given region is needed to design robust detectors that discriminate, with a high level of confidence activated from non activated regions. Usually, in the literature, the hemodynamic response has been modeled by known functions, e.g., gamma functions, fitting them, or not, to the experimental data. In this paper we present a different approach based on the physiologic behavior of the vascular and neural tissues. Here, a linear model based on reasonable physiological assumptions about oxygen consumption and vasodilatation processes are used to design a linear model from which a transfer function is derived. The estimation of the model parameters is performed by using the minimum square error (MSE) by forcing the adjustment of the stimulus response to the observations. Experimental results using real data have shown that the proposed model successfully explains the observations allowing to achieve small values for the fitting error.

Neurological subtle signs and cognitive development: A study in late childhood and adolescence

Introduction and Aim: Neurological subtle signs (NSS) are often observed during the neurological examination of children and tend to disappear with age. Their persistence into late adolescence or young adulthood has been related to psychiatric and neurocognitive disorders. To provide a better understanding of their functional basis, a longitudinal correlational study with neurocognitive measurements was performed. Method: We conducted multiple regression and correlation analyses of NSS with demographic and cognitive measures on a subset of 341 healthy children (56% males), taking part in a longitudinal dental study. Participants, whose ages ranged between 11–15 years, at first evaluation, undertook yearly, during 5 years, a 6-item NSS exam (producing a total score ranging between 0–18) and a comprehensive battery of neurocognitive tests. Effects of age, gender, IQ, and 7 neurocognitive factors on NSS were analyzed. Results: Over the years, NSS scores correlated consistently with selective attention (Stroop test), motor speed (finger tapping), and visuomotor speed (pegboard speed). Discussion: These results suggest that the disappearance of NSS in late childhood and adolescence occurs primarily in parallel with the development of motor and visuomotor functions and secondarily in relation to higher order functions such as selective attention (Stroop) and executive control (B-A Trails difference).

Robust brain activation detection in functional MRI

Functional Magnetic Resonance Imaging (MRI) is today one of the most important non-invasive tools to study the brain from a functional point of view. The blood-oxygenation-level-dependent (BOLD) signal is used to detect the activated regions based on the assumption that in these regions the metabolic activity increases. The normal procedure is the application of known sequences of stimulus and find out the brain regions whose activation sequence is correlated with the applied stimulus. This inference problem is difficult because the BOLD signal is very week and noisy. The underlying information is embedded in a large number of other signal related with the normal brain activity and in the noise introduced by the MRI scanner. Furthermore, the hemodynamic impulse response function (HRF), needed to know the expected BOLD response to a given stimulus, is usually unknown and is not constant across the whole brain. In this paper a robust Bayesian algorithm is proposed to detect regions where the activation patterns are correlated with the applied stimulus. The activation process is modeled by using binary explicative variables and the HRF is estimated at each location according to a physiological model proposed by the authors in [1]. Monte Carlo tests using synthetic data are performed to evaluate the performance of the algorithm and results with real data are compared with the ones obtained by a neurologist with the commercial package BrainVoyager.

fMRI binary detection of brain activated regions with graph-cuts

The functional Magnetic Resonance Imaging (fMRI) is a technique with increasing applications in studying the brain function. The blood-oxygenation-level-dependent (BOLD) is a fMRI method that allows the detection of brain activated regions after the application of an external stimulus, e.g., visual or auditive. This technique is based on the assumption that the metabolism increases in activated areas as well as the oxygen uptake. Analising this information is a challenging problem because the BOLD signal is very noisy and its changes due to the application of a stimulus are very weak. Therefore, the detection of temporal correlations with the applied stimulus requires sophisticated statistical algorithms to understand if the changes on the BOLD signal are pure noise or are related with the applied stimulus, called paradigm in the fMRI scope.

Recovering from acquired childhood aphasia (ACA) – 20 years later, learning about the neuroplasticity of language

Language is at the core of human cognitive abilities and the mechanisms associated with neural recovery from aphasia are still largely unknown. Important insights have been reported, such as: i) Significantly better recovery occurs, if the brain lesions leading to aphasia were suffered during childhood (ACA); ii) that perilesional map expansion and transference of language functions to homologue areas in the contralateral hemisphere are thought to be two main processes sustaining this neuroplasticity [1]. From the study of peri-natal brain lesions of left hemisphere is known that they are often associated with language transfer to the right hemisphere [2–4]. We investigated if potential factors underlying the neuroplasticity of language (such as the developmental linguistic stage at onset of aphasia and size of the lesion) would significantly contribute to determine the recovery strategy. We report the a follow-up study of three cases of left frontal subcortical isquemic strokes about 20 years after onset of aphasia.

Joint Bayesian detection of brain activated regions and local HRF estimation in functional MRI

The blood-oxygenation-level-dependent (BOLD) signal, measured with the magnetic resonance imaging (MRI), is currently used to detect the activation of brain regions with a stimulus application, e.g., visual or auditive. In a block design approach, the stimuli (called paradigm in the fMRI scope) are designed to detect activated and non activated brain regions with maximized certainty. However, corrupting noise in MRI volumes acquisition, patient motion and the normal brain activity interference makes this detection a difficult task. In this paper a new Bayesian method, called SPM-MAP, is proposed where a joint detection of brain activated regions and estimation of the underlying hemodynamic impulse response function (HRF) is proposed. Monte Carlo tests on its error probability and HRF estimation with synthetic data are performed and presented.

Comparison of two different approaches for brain activity detection in fMRI: SPM-MAP and SPM-GLM

The functional MRI {Magnetic Resonance Imaging), fMRI, is today a widespread tool to study and evaluate the brain from a functional point of view. The blood-oxygenation-level-dependent (BOLD) signal is currently used to detect the activation of brain regions with a stimulus application, e.g., visual or auditive. In a block design approach the stimuli (called paradigm in the fMRI scope) are designed to detect activated and non activated brain regions with maximized certainty. However, corrupting noise in MRI volumes acquisition, patient motion and the normal brain activity interference makes this detection a difficult task. The most used activation detection fMRI algorithm, here called SPM-GLM [1] uses a conventional statistical inference methodology based on the t-statistics In this paper we propose a new Bayesian approach, by modeling the data acquisition noise as additive white Gaussian noise (AWGN) and the activation indicators as binary unknowns that must be estimated. Monte Carlo tests using both methods have shown that the Bayesian method, here called SPM-MAP, outperforms the traditional one, here called SPM-GLM, for almost all conditions of noise and number of paradigm epochs tested.