Benjamin M. Hampstead

Safety of Transcranial Direct Current Stimulation: Evidence Based Update 2016.

This review updates and consolidates evidence on the safety of transcranial Direct Current Stimulation (tDCS). Safety is here operationally defined by, and limited to, the absence of evidence for a Serious Adverse Effect, the criteria for which are rigorously defined. This review adopts an evidence-based approach, based on an aggregation of experience from human trials, taking care not to confuse speculation on potential hazards or lack of data to refute such speculation with evidence for risk. Safety data from animal tests for tissue damage are reviewed with systematic consideration of translation to humans. Arbitrary safety considerations are avoided. Computational models are used to relate dose to brain exposure in humans and animals. We review relevant dose-response curves and dose metrics (e.g. current, duration, current density, charge, charge density) for meaningful safety standards. Special consideration is given to theoretically vulnerable populations including children and the elderly, subjects with mood disorders, epilepsy, stroke, implants, and home users. Evidence from relevant animal models indicates that brain injury by Direct Current Stimulation (DCS) occurs at predicted brain current densities (6.3-13 A/m(2)) that are over an order of magnitude above those produced by conventional tDCS. To date, the use of conventional tDCS protocols in human trials (≤40 min, ≤4 milliamperes, ≤7.2 Coulombs) has not produced any reports of a Serious Adverse Effect or irreversible injury across over 33,200 sessions and 1000 subjects with repeated sessions. This includes a wide variety of subjects, including persons from potentially vulnerable populations.

Activation and Effective Connectivity Changes Following Explicit-Memory Training for Face–Name Pairs in Patients With Mild Cognitive Impairment A Pilot Study

Background. Mild cognitive impairment (MCI) is often a precursor to Alzheimer disease. Little research has examined the efficacy of cognitive rehabilitation in patients with MCI, and the relevant neural mechanisms have not been explored. The authors previously showed the behavioral efficacy of cognitive rehabilitation using mnemonic strategies for face–name associations in patients with MCI. Here, the authors used functional magnetic resonance imaging (fMRI) to test whether there were training-specific changes in activation and connectivity within memory-related areas. Methods. A total of 6 patients with amnestic, multidomain MCI underwent pretraining and posttraining fMRI scans, during which they encoded 90 novel face–name pairs and completed a 4-choice recognition memory test immediately after scanning. Patients were taught mnemonic strategies for half the face–name pairs during 3 intervening training sessions. Results. Training-specific effects comprised significantly increased activation within a widespread cerebral cortical network involving medial frontal, parietal, and occipital regions; the left frontal operculum and angular gyrus; and regions in the left lateral temporal cortex. Increased activation common to trained and untrained stimuli was found in a separate network involving inferior frontal, lateral parietal, and occipital cortical regions. Effective connectivity analysis using multivariate, correlation-purged Granger causality analysis revealed generally increased connectivity after training, particularly involving the middle temporal gyrus and foci in the occipital cortex and the precuneus. Conclusion. The authors’ findings suggest that the effectiveness of explicit-memory training in patients with MCI is associated with training-specific increases in activation and connectivity in a distributed neural system that includes areas involved in explicit memory.

Explicit memory training leads to improved memory for face–name pairs in patients with mild cognitive impairment: Results of a pilot investigation

Relatively few studies have examined the use of cognitive rehabilitation in patients with mild cognitive impairment (MCI), largely due to the assumption that training will not improve functioning in patients with progressive conditions. Face-name association, an ecologically valid task, is both dependent on the explicit memory system and difficult for MCI patients. During three hour-long sessions, eight patients diagnosed with MCI were trained in the use of explicit memory strategies with 45 face-name pairs. For each pair, they were taught to visually identify a facial feature, link a phonological cue to that feature, and recall the associated name. There was significant improvement in recognition accuracy, along with faster reaction times, for trained face-name pairs. Improved accuracy persisted when tested one month after training. Significant, but less, improvement was also found on untrained stimuli, raising the possibility of generalization of training strategies. Preliminary results suggest strategy-based cognitive rehabilitation may be beneficial in patients with MCI, though these results must be replicated with a control group to rule out practice effects.

Mnemonic strategy training partially restores hippocampal activity in patients with mild cognitive impairment

Learning and memory deficits typify patients with mild cognitive impairment (MCI) and are generally attributed to medial temporal lobe dysfunction. Although the hippocampus is perhaps the most commonly studied neuroanatomical structure in these patients, there have been few attempts to identify rehabilitative interventions that facilitate its functioning. Here, we present results from a randomized, controlled, single‐blind study in which patients with MCI and healthy elderly controls (HEC) were randomized to either three sessions of mnemonic strategy training (MS) or a matched‐exposure control group (XP). All participants underwent pre‐ and posttraining fMRI scanning as they encoded and retrieved object–location associations. For the current report, fMRI analyses were restricted to the hippocampus, as defined anatomically. Before training, MCI patients showed reduced hippocampal activity during both encoding and retrieval, relative to HEC. Following training, the MCI MS group demonstrated increased activity during both encoding and retrieval. There were significant differences between the MCI MS and MCI XP groups during retrieval, especially within the right hippocampus. Thus, MS facilitated hippocampal functioning in a partially restorative manner. We conclude that cognitive rehabilitation techniques may help mitigate hippocampal dysfunction in MCI patients.

Mnemonic strategy training improves memory for object location associations in both healthy elderly and patients with amnestic mild cognitive impairment: A randomized, single-blind study.

OBJECTIVE To evaluate the efficacy of mnemonic strategy training versus a matched-exposure control condition and to examine the relationship between training-related gains, neuropsychological abilities, and medial temporal lobe volumetrics in patients with amnestic mild cognitive impairment (aMCI) and age-matched healthy controls. METHOD Twenty-three of 45 screened healthy controls and 29 of 42 screened patients with aMCI were randomized to mnemonic strategy or matched-exposure groups. Groups were run in parallel, with participants blind to the other intervention. All participants completed five sessions within 2 weeks. Memory testing for object-location associations (OLAs) was performed during sessions one and five and at a 1-month follow-up. During Sessions 2-4, participants received either mnemonic strategy training or a matched number of exposures with corrective feedback for a total of 45 OLAs. Structural magnetic resonance imaging was performed in most participants, and medial temporal lobe volumetrics were acquired. RESULTS Twenty-one healthy controls and 28 patients with aMCI were included in data analysis. Mnemonic strategy training was significantly more beneficial than matched exposure immediately after training, p = .006, partial η2 = .16, and at 1 month, p < .001, partial η2 = .35, regardless of diagnostic group (healthy group or aMCI group). Although patients with aMCI demonstrated gains comparable to the healthy control groups, their overall performance generally remained reduced. Mnemonic strategy-related improvement was correlated positively with baseline memory and executive functioning and negatively with inferior lateral ventricle volume in patients with aMCI; no significant relationships were evident in matched-exposure patients. CONCLUSION Mnemonic strategies effectively improve memory for specific content for at least 1 month in patients with aMCI.

Where did I put that? Patients with amnestic mild cognitive impairment demonstrate widespread reductions in activity during the encoding of ecologically relevant object-location associations

Remembering the location of objects in the environment is both important in everyday life and difficult for patients with amnestic mild cognitive impairment (aMCI), a clinical precursor to Alzheimers disease. To test the hypothesis that memory impairment for object location in aMCI reflects hippocampal dysfunction, we used an event-related functional magnetic resonance imaging paradigm to compare patients with aMCI and healthy elderly controls (HEC) as they encoded 90 ecologically relevant object-location associations (OLAs). Two additional OLAs, repeated a total of 45 times, served as control stimuli. Memory for these OLAs was assessed following a 1-h delay. The groups were well matched on demographics and brain volumetrics. Behaviorally, HEC remembered significantly more OLAs than did aMCI patients. Activity differences were assessed by contrasting activation for successfully encoded Novel stimuli vs. Repeated stimuli. The HEC demonstrated activity within object-related (ventral visual stream), spatial location-related (dorsal visual stream), and feature binding-related cortical regions (hippocampus and other memory-related regions) as well as in frontal cortex and associated subcortical structures. Activity in most of these regions correlated with memory test performance. Although the aMCI patients demonstrated a similar activation pattern, the HEC showed significantly greater activity within each of these regions. Memory test performance in aMCI patients, in contrast to the HEC, was correlated with activity in regions involved in sensorimotor processing. We conclude that aMCI patients demonstrate widespread cerebral dysfunction, not limited to the hippocampus, and rely on encoding-related mechanisms that differ substantially from healthy individuals.

Predictive Big Data Analytics: A Study of Parkinson's Disease Using Large, Complex, Heterogeneous, Incongruent, Multi-Source and Incomplete Observations.

Background A unique archive of Big Data on Parkinson’s Disease is collected, managed and disseminated by the Parkinson’s Progression Markers Initiative (PPMI). The integration of such complex and heterogeneous Big Data from multiple sources offers unparalleled opportunities to study the early stages of prevalent neurodegenerative processes, track their progression and quickly identify the efficacies of alternative treatments. Many previous human and animal studies have examined the relationship of Parkinson’s disease (PD) risk to trauma, genetics, environment, co-morbidities, or life style. The defining characteristics of Big Data–large size, incongruency, incompleteness, complexity, multiplicity of scales, and heterogeneity of information-generating sources–all pose challenges to the classical techniques for data management, processing, visualization and interpretation. We propose, implement, test and validate complementary model-based and model-free approaches for PD classification and prediction. To explore PD risk using Big Data methodology, we jointly processed complex PPMI imaging, genetics, clinical and demographic data. Methods and Findings Collective representation of the multi-source data facilitates the aggregation and harmonization of complex data elements. This enables joint modeling of the complete data, leading to the development of Big Data analytics, predictive synthesis, and statistical validation. Using heterogeneous PPMI data, we developed a comprehensive protocol for end-to-end data characterization, manipulation, processing, cleaning, analysis and validation. Specifically, we (i) introduce methods for rebalancing imbalanced cohorts, (ii) utilize a wide spectrum of classification methods to generate consistent and powerful phenotypic predictions, and (iii) generate reproducible machine-learning based classification that enables the reporting of model parameters and diagnostic forecasting based on new data. We evaluated several complementary model-based predictive approaches, which failed to generate accurate and reliable diagnostic predictions. However, the results of several machine-learning based classification methods indicated significant power to predict Parkinson’s disease in the PPMI subjects (consistent accuracy, sensitivity, and specificity exceeding 96%, confirmed using statistical n-fold cross-validation). Clinical (e.g., Unified Parkinsons Disease Rating Scale (UPDRS) scores), demographic (e.g., age), genetics (e.g., rs34637584, chr12), and derived neuroimaging biomarker (e.g., cerebellum shape index) data all contributed to the predictive analytics and diagnostic forecasting. Conclusions Model-free Big Data machine learning-based classification methods (e.g., adaptive boosting, support vector machines) can outperform model-based techniques in terms of predictive precision and reliability (e.g., forecasting patient diagnosis). We observed that statistical rebalancing of cohort sizes yields better discrimination of group differences, specifically for predictive analytics based on heterogeneous and incomplete PPMI data. UPDRS scores play a critical role in predicting diagnosis, which is expected based on the clinical definition of Parkinson’s disease. Even without longitudinal UPDRS data, however, the accuracy of model-free machine learning based classification is over 80%. The methods, software and protocols developed here are openly shared and can be employed to study other neurodegenerative disorders (e.g., Alzheimer’s, Huntington’s, amyotrophic lateral sclerosis), as well as for other predictive Big Data analytics applications.

Cognitive Rehabilitation of Memory for Mild Cognitive Impairment: A Methodological Review and Model for Future Research

Several recent reviews have suggested that cognitive rehabilitation may hold promise in the treatment of memory deficits experienced by patients with mild cognitive impairment. In contrast to the previous reviews that mainly focused on outcome, the current review examines key methodological challenges that are critical for designing and interpreting research studies and translating results into clinical practice. Using methodological details from 36 studies, we first examine diagnostic variability and how the use of cutoffs may bias samples toward more severely impaired patients. Second, the strengths and limitations of several common rehabilitative techniques are discussed. Half of the reviewed studies used a multi-technique approach that precludes the causal attribution between any specific technique and subsequent improvement. Third, there is a clear need to examine the dose-response relationship since this information was strikingly absent from most studies. Fourth, outcome measures varied widely and frequently depended on neuropsychological tests with little theoretical justification or ecological relevance. Fifth, we discuss how the variability in each of these other four areas complicates efforts to examine training generalization. Overall, future studies should place greater emphasis on ecologically relevant treatment approaches and outcome measures and we propose a hierarchical model that may aid in this pursuit.

Resting-state fMRI reveals enhanced functional connectivity in spatial navigation networks after transcranial direct current stimulation

A number of studies have established that transcranial direct current stimulation (tDCS) modulates cortical excitability. We previously demonstrated polarity dependent changes in parietal lobe blood oxygen level dependent (BOLD) fMRI in a group of young adults during a spatial navigation task [15]. Here we used resting state functional connectivity (rsFC) to examine whether analogous changes were also evident during the resting state. Participants were randomized to either a parietal-anodal, frontal-cathodal (P+F-) or the opposite montage (P-F+) and received 20min of tDCS (2mA) before undergoing resting-state fMRI. rsFC was evaluated between the groups by placing a seed in the medial superior parietal lobule (mSPL), which was under the target electrode. rsFC between the mSPL and a number of other areas involved in spatial navigation, scene processing, and sensorimotor processing was significantly higher in the P+F- than the P-F+ group. Thus, the modulatory effects of tDCS were evident during rest and suggest that stimulation primes not just the underlying neocortex but an extended network that can be recruited as necessary during active task performance.

Transcranial direct current stimulation modulates activation and effective connectivity during spatial navigation.

BACKGROUND Allocentric navigation declines with age and neurologic disease whereas egocentric navigation does not; differences that likely arise from maladaptive changes in brain regions mediating spatial (parietal cortex; hippocampus) but not procedural processing (caudate nucleus). Transcranial direct current stimulation (tDCS) holds promise for treating such decline given its ability to modulate neuronal excitability, but its effects have yet to be examined on spatial navigation. OBJECTIVES/HYPOTHESES Using healthy young adults as a model, Study 1 intended to validate a novel spatial navigation paradigm using functional magnetic resonance imaging (fMRI). Using these data to determine targets for tDCS, Study 2 aimed to determine if 1) stimulation modulates activation in a polarity-specific manner; 2) stimulation results in global and/or task-specific activation changes; 3) activation changes are accompanied by changes in effective connectivity. METHODS All participants underwent fMRI while learning allocentric and egocentric environments. Twelve participants completed Study 1. In Study 2, 16 participants were randomized to 20 min of tDCS (2 mA) using a montage with the anode over PZ and cathode over AF4 (P+F-) or the reverse montage (P-F+). RESULTS Study 1 revealed that distinct networks preferentially mediate allocentric and egocentric navigation. Study 2 revealed polarity-dependent changes in activation and connectivity. The P+F- montage increased these measures in spatial regions, especially during allocentric navigation, and the caudate nucleus. Conversely, the P-F+ montage increased activation and connectivity in lateral prefrontal cortices and posterior hippocampus. CONCLUSIONS These findings support the neuromodulatory effects of tDCS in non-motor areas and demonstrate proof-of-principle for ameliorating age- and disease-related decline in navigational abilities.