Mark Hallett

Bio: Mark Hallett is an academic researcher from National Institutes of Health. The author has contributed to research in topics: Transcranial magnetic stimulation & Motor cortex. The author has an hindex of 186, co-authored 1170 publications receiving 123741 citations. Previous affiliations of Mark Hallett include Government of the United States of America & Armed Forces Institute of Pathology.

Characteristics of Bilateral Hand Function in Individuals With Unilateral Dystonia Due to Perinatal Stroke Sensory and Motor Aspects

Abstract: The authors assessed bilateral motor and sensory function in individuals with upper limb dystonia due to unilateral perinatal stroke and explored interrelationships of motor function and sensory ability. Reach kinematics and tactile sensation were measured in 7 participants with dystonia and 9 healthy volunteers. The dystonia group had poorer motor (hold time, reach time, shoulder/elbow correlation) and sensory (spatial discrimination, stereognosis) outcomes than the control group on the nondominant side. On the dominant side, only sensation (spatial discrimination, stereognosis) was poorer in the dystonia group compared with the control group. In the dystonia group, although sensory and motor outcomes were uncorrelated, dystonia severity was related to poorer stereognosis, longer hold and reach times, and decreased shoulder/elbow coordination. Findings of bilateral sensory deficits in dystonia can be explained by neural reorganization. Visual compensation for somatosensory changes in the nonstroke hemisphere may explain the lack of bilateral impairments in reaching.

Small effect size leads to reproducibility failure in resting-state fMRI studies

Abstract: Thousands of papers using resting-state functional magnetic resonance imaging (RS-fMRI) have been published on brain disorders. Results in each paper may have survived correction for multiple comparison. However, since there have been no robust results from large scale meta-analysis, we do not know how many of published results are truly positives. The present meta-analytic work included 60 original studies, with 57 studies (4 datasets, 2266 participants) that used a between-group design and 3 studies (1 dataset, 107 participants) that employed a within-group design. To evaluate the effect size of brain disorders, a very large neuroimaging dataset ranging from neurological to psychiatric disorders together with healthy individuals have been analyzed. Parkinson9s disease off levodopa (PD-off) included 687 participants from 15 studies. PD on levodopa (PD-on) included 261 participants from 9 studies. Autism spectrum disorder (ASD) included 958 participants from 27 studies. The meta-analyses of a metric named amplitude of low frequency fluctuation (ALFF) showed that the effect size (Hedges9g) was 0.19 - 0.39 for the 4 datasets using between-group design and 0.46 for the dataset using within-group design. The effect size of PD-off, PD-on and ASD were 0.23, 0.39, and 0.19, respectively. Using the meta-analysis results as the robust results, the between-group design results of each study showed high false negative rates (median 99%), high false discovery rates (median 86%), and low accuracy (median 1%), regardless of whether stringent or liberal multiple comparison correction was used. The findings were similar for 4 RS-fMRI metrics including ALFF, regional homogeneity, and degree centrality, as well as for another widely used RS-fMRI metric namely seed-based functional connectivity. These observations suggest that multiple comparison correction does not control for false discoveries across multiple studies when the effect sizes are relatively small. Meta-analysis on un-thresholded t-maps is critical for the recovery of ground truth. We recommend that to achieve high reproducibility through meta-analysis, the neuroimaging research field should share raw data or, at minimum, provide un-thresholded statistical images.

The sequence effect in de novo Parkinson's disease.

Abstract: Progressive slowness in speed or progressive decrease in amplitude of repetitive movements is unique in Parkinson’s disease (PD).1,2 It is referred to as the sequence effect (SE).3,4 Until now, it was well-demonstrated in only advanced PD.1–3 The SE might also be observed in drug-naive PD because the SE is a feature of bradykinesia, although measuring the SE has not been documented. Indeed, the SE might be difficult to identify in the drug-naive, early stage of PD because the SE might be too mild to detect. The characteristics of the repetitive movements in drug-naive PD might differ from that in advanced PD since the pattern of cerebral excitability is dissimilar between drug-naive and advanced PD5,6 and medication affects cortical plasticity in PD.7,8 With a computer-based, modified Purdue pegboard test, we reported that we measured the SE in advanced PD.3 At that time, we also conducted similar research with drug-naive PD, but we did not complete the study due to difficulty in recruiting drug-naive PD patients. Although we did not complete the study with de novo PD, we were able to see whether the SE could be measured in drug-naive PD.

Binary EEG Control for Two-Dimensional Cursor Movement: An Online Approach

Abstract: Electroencephalography (EEG) is an appealing basis for brain-computer interface technology because EEG is non-invasive. However, because EEG signals are spatially blurred and typically have very low signal-to-noise ratios, extracting relevant information in the single-event case is challenging. The most easily accessible information is one-dimensional (for example, mu rhythm amplitude, average hemispherical power, or presence of a P300 evoked potential). Many studies have attempted to use such one-dimensional parameters as a basis for control. Robust results may be obtained when control is restricted to answering "yes" or "no" questions, such as comparison of a value to a threshold. However, possible applications of such control have been limited, and more dimensions of control are desirable. This research presents a new technique for obtaining more dimensions of control from existing technology. Yes/no answers are taken sequentially in groups of n, and in combination designate a specific choice from 2^n possible values. This is homologous to the function of bits, and consequently has been termed "binary control." To demonstrate this approach, a two-dimensional cursor control paradigm was developed in MATLAB. Users move a cursor among squares of a grid towards a target while avoiding a trap. At each move, there are up to four positions into which the cursor may be directed (up, down, left, and right). In this embodiment, control is achieved by twice comparing average alpha-and beta-frequency power of each hemisphere during continuous imagined lateralized hand movement. The first comparison narrows the four choices to two, and the second uniquely determines the cursor movement. This paradigm was shown to be compatible with the Brain-Computer Interface-to-Virtual Reality (BCI2VR) software, and preliminary tests were run on normal volunteers. These tests demonstrated the feasibility of pursuing future research with binary control. Binary control is promising because of its robust underlying principles, and because it is easily expandable and adaptable. The source of control may be any EEG feature that can signal a yes/no answer, and the quantity of possible choices doubles with the addition of each answer "bit." This might provide means for more complex control, such as of a robotic arm or virtual keyboard. The binary approach might also prove more efficient than current EEG-based control methods, possibly with less computational demand.

Kinematic improvement following Botulinum Toxin-A injection in upper-limb spasticity due to stroke.

Abstract: Background Focal spasticity is a significant motor disorder following stroke, and Botulinum Toxin Type-A (BoNT-A) is a useful treatment for this. The authors evaluated kinematic modifications induced by spasticity, and whether or not there is any improvement following injection of BoNT-A. Methods Eight patients with stroke with upper-limb spasticity, showing a flexor pattern, were evaluated using kinematics before and after focal treatment with BoNT-A. A group of sex- and age-matched normal volunteers acted as a control group. Results Repeated-measures ANOVA showed that patients with stroke performed more slowly than the control group. Following treatment with BoNT-A, there was a significant improvement in kinematics in patients with stroke, while in the control group, performance remained unchanged. Conclusions Focal treatment of spasticity with BoNT-A leads to an adaptive change in the upper limb of patients with spastic stroke.

The Brain's Default Network Anatomy, Function, and Relevance to Disease

Abstract: Thirty years of brain imaging research has converged to define the brain’s default network—a novel and only recently appreciated brain system that participates in internal modes of cognition Here we synthesize past observations to provide strong evidence that the default network is a specific, anatomically defined brain system preferentially active when individuals are not focused on the external environment Analysis of connectional anatomy in the monkey supports the presence of an interconnected brain system Providing insight into function, the default network is active when individuals are engaged in internally focused tasks including autobiographical memory retrieval, envisioning the future, and conceiving the perspectives of others Probing the functional anatomy of the network in detail reveals that it is best understood as multiple interacting subsystems The medial temporal lobe subsystem provides information from prior experiences in the form of memories and associations that are the building blocks of mental simulation The medial prefrontal subsystem facilitates the flexible use of this information during the construction of self-relevant mental simulations These two subsystems converge on important nodes of integration including the posterior cingulate cortex The implications of these functional and anatomical observations are discussed in relation to possible adaptive roles of the default network for using past experiences to plan for the future, navigate social interactions, and maximize the utility of moments when we are not otherwise engaged by the external world We conclude by discussing the relevance of the default network for understanding mental disorders including autism, schizophrenia, and Alzheimer’s disease

Parallel Organization of Functionally Segregated Circuits Linking Basal Ganglia and Cortex

Abstract: Information about the basal ganglia has accumulated at a prodigious pace over the past decade, necessitating major revisions in our concepts of the structural and functional organization of these nuclei. From earlier data it had appeared that the basal ganglia served primarily to integrate diverse inputs from the entire cerebral cortex and to "funnel" these influences, via the ventrolateral thalamus, to the motor cortex (Allen & Tsukahara 1974, Evarts & Thach 1969, Kemp & Powell 1971). In particular, the basal

FieldTrip: open source software for advanced analysis of MEG, EEG, and invasive electrophysiological data

Abstract: This paper describes FieldTrip, an open source software package that we developed for the analysis of MEG, EEG, and other electrophysiological data. The software is implemented as a MATLAB toolbox and includes a complete set of consistent and user-friendly high-level functions that allow experimental neuroscientists to analyze experimental data. It includes algorithms for simple and advanced analysis, such as time-frequency analysis using multitapers, source reconstruction using dipoles, distributed sources and beamformers, connectivity analysis, and nonparametric statistical permutation tests at the channel and source level. The implementation as toolbox allows the user to perform elaborate and structured analyses of large data sets using the MATLAB command line and batch scripting. Furthermore, users and developers can easily extend the functionality and implement new algorithms. The modular design facilitates the reuse in other software packages.

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