Neuroimaging Methods

Objective: This study aimed to investigate the cortical activity in focal right upper limb dystonia patients using functional near infrared spectroscopy (fNIRS) during writing.

Background: Techniques such as fMRI and PET impose important physical constraints. Latter advances in functional near infrared spectroscopy offer a new possibility for investigating cortical areas and the neural correlates of complex motor behaviors non‐invasively under naturalistic experimentation.

Methods: Twenty‐one patients with right upper limb idiopathic dystonia (6 with task‐specific dystonia) and twenty‐one healthy volunteers matched for age and years of education were submitted to a simple right‐hand writing task paradigm that consisted of 4 epochs of alternating writing/resting blocks. To test a priori hypotheses that brain activation to simple handwriting in cortical sensorimotor and supplementary motor regions would be less specific in patients than in controls, we defined right and left primary motor (M1) and somatosensory (S1) and supplementary motor area (SMA) ROIs. Differences between groups on changes in both deoxy and oxy‐Hemoglobin (HbO2) and for each ROI were then compared using Mann Whitney tests.

Results: Channels exhibiting increased HbO2 for the writing task compared to the resting condition in the patient and control groups are described in Fig. 1. In controls, a lateralization predominantly to the left side was observed in most of the central channels covering the primary motor and somatosensory cortices. A more bilateral pattern of activation was observed in patients. However, in a direct channel‐wise comparison between groups, no significant differences were observed in any channel. In the ROI‐based group analysis, between‐group differences were observed in two of the five ROIs: left M1 (p = 0.022) and S1 (p = 0.022) exhibited increased HbO2 in patients in relation to controls.

Conclusions: Overactivity findings on M1 as S1 are in agreement with previous studies of the writing task in non‐ecological conditions1,2,3, reinforcing the role of these areas in dystonia. As symptoms in dystonia are very specific to the task, we believe the pattern of brain activation is as much as specific, therefore the importance of an experimental set that mimics real life conditions. To our knowledge, this is the first study to measure cortical activity during ecological writing (subjects sited in anatomical position, in less noisy environment, using traditional paper and pen) in focal upper limb dystonia patients, outlining the potential of fNIRS for the study of the movement disorders in unconstrained environments.

Familiarity in music has been reported as an important factor modulating emotional and hedonic responses in the brain. Familiarity and repetition may increase the liking of a piece of music, thus inducing positive emotions. Neuroimaging studies have focused on identifying the brain regions involved in the processing of familiar and unfamiliar musical stimuli. However, the use of different modalities and experimental designs has led to discrepant results and it is not clear which areas of the brain are most reliably engaged when listening to familiar and unfamiliar musical excerpts. In the present study, we conducted a systematic review from three databases (Medline, PsychoINFO, and Embase) using the keywords (recognition OR familiar OR familiarity OR exposure effect OR repetition) AND (music OR song) AND (brain OR brains OR neuroimaging OR functional Magnetic Resonance Imaging OR Position Emission Tomography OR Electroencephalography OR Event Related Potential OR Magnetoencephalography). Of the 704 titles identified, 23 neuroimaging studies met our inclusion criteria for the systematic review. After removing studies providing insufficient information or contrasts, 11 studies (involving 212 participants) qualified for the meta-analysis using the activation likelihood estimation (ALE) approach. Our results did not find significant peak activations consistently across included studies. Using a less conservative approach (p < 0.001, uncorrected for multiple comparisons) we found that the left superior frontal gyrus, the ventral lateral (VL) nucleus of the left thalamus, and the left medial surface of the superior frontal gyrus had the highest likelihood of being activated by familiar music. On the other hand, the left insula, and the right anterior cingulate cortex had the highest likelihood of being activated by unfamiliar music. We had expected limbic structures as top clusters when listening to familiar music. But, instead, music familiarity had a motor pattern of activation. This could reflect an audio-motor synchronization to the rhythm which is more

Neurocognitive and emotional regulatory deficits in substance users are often attributed to misuse; however most studies do not include a substance-naïve baseline to justify that conclusion. The etiological literature suggests that pre-existing deficits may contribute to the onset and escalation of use that are then exacerbated by subsequent use. To address this, there is burgeoning interest in conducting prospective, longitudinal neuroimaging studies to isolate neurodevelopmental precursors and consequences of adolescent substance misuse, as reflected in recent initiatives such as the NIH-led Adolescent Brain Cognitive Development (ABCD) study and the National Consortium on Alcohol and Neurodevelopment (NCANDA). To distinguish neurodevelopmental precursors from the consequences of adolescent substance use specifically, prospective, longitudinal neuroimaging studies with substance-naïve pre-adolescents are needed. The exemplar described in this article—i.e., the ongoing Adolescent Development Study (ADS)—used a targeted recruitment strategy to bolster the numbers of pre-adolescent individuals who were at increased risk of substance use (i.e., " high-risk ") in a sample that was relatively small for longitudinal studies of similar phenomena, but historically large for neuroimaging (i.e., N = 135; 11–13 years of age). At baseline participants underwent MRI testing and a large complement of cognitive and behavioral assessments along with genetics, stress physiology and interviews. The study methods include repeating these measures at three time points (i.e., baseline/Wave 1, Wave 2 and Wave 3), 18 months apart. In this article, rather than outlining specific study outcomes, we describe the breadth of the numerous complexities and challenges involved in conducting this type of prospective, longitudinal neuroimaging study and " lessons learned " for subsequent efforts are discussed. While these types of large longitudinal neuroimaging studies present a number of logistical and scientific challenges, the wealth of information obtained about the precursors and consequences of adolescent substance use Frontiers in Human Neuroscience | www.frontiersin.org

Alzheimer’s disease (AD) is a devastating disorder of increasing prevalence in modern society. Mild cognitive impairment (MCI) is considered a transitional stage between normal aging and AD; however, not all subjects with MCI progress to AD. Prediction of conversion to AD at an early stage would enable an earlier, and potentially more effective, treatment of AD. Electroencephalography (EEG) biomarkers would provide a non-invasive and relatively cheap screening tool to predict conversion to AD; however, traditional EEG biomarkers have not been considered accurate enough to be useful in clinical practice. Here, we aim to combine the information from multiple EEG biomarkers into a diagnostic classification index in order to improve the accuracy of predicting conversion from MCI to AD within a 2-year period. We followed 86 patients initially diagnosed with MCI for 2 years during which 25 patients converted to AD. We show that multiple EEG biomarkers mainly related to activity in the beta-frequency range (13–30Hz) can predict conversion from MCI to AD. Importantly, by integrating six EEG biomarkers into a diagnostic index using logistic regression the prediction improved compared with the classification using the individual biomarkers, with a sensitivity of 88% and specificity of 82%, compared with a sensitivity of 64% and specificity of 62% of the best individual biomarker in this index. In order to identify this diagnostic index we developed a data mining approach implemented in the Neurophysiological Biomarker Toolbox (http://www.nbtwiki.net/). We suggest that this approach can be used to identify optimal combinations of biomarkers (integrative biomarkers) also in other modalities. Potentially, these integrative biomarkers could be more sensitive to disease progression and response to therapeutic intervention.

A variety of approaches has been used to minimize head movement during functional brain imaging studies in awake laboratory animals. Many laboratories expend substantial effort and time training animals to remain essentially motionless during such studies. We could not locate an “off-the-shelf” automated training system that suited our needs.

We developed a time- and labor-saving automated system to train animals to hold still for extended periods of time. The system uses a personal computer and modest external hardware to provide stimulus cues, monitor movement using commercial video surveillance components, and dispense rewards. A custom computer program automatically increases the motionless duration required for rewards based on performance during the training session but allows changes during sessions. This system was used to train cynomolgus monkeys (Macaca fascicularis) for awake neuroimaging studies using positron emission tomography (PET) and functional magnetic resonance imaging (fMRI).

The automated system saved the trainer substantial time, presented stimuli and rewards in a highly consistent manner, and automatically documented training sessions. We have limited data to prove the training system's success, drawn from the automated records during training sessions, but we believe others may find it useful. The system can be adapted to a range of behavioral training/recording activities for research or commercial applications, and the software is freely available for non-commercial use.