A new perspective for the training assessment: Machine learning-based neurometric for augmented user's evaluation

Inappropriate training assessment might have either high social costs and economic impacts, especially in high risks categories, such as Pilots, Air Traffic Controllers, or Surgeons. One of the current limitations of the standard training assessment procedures is the lack of information about the amount of cognitive resources requested by the user for the correct execution of the proposed task. In fact, even if the task is accomplished achieving the maximum performance, by the standard training assessment methods, it would not be possible to gather and evaluate information about cognitive resources available for dealing with unexpected events or emergency conditions. Therefore, a metric based on the brain activity (neurometric) able to provide the Instructor such a kind of information should be very important. As a first step in this direction, the Electroencephalogram (EEG) and the performance of 10 participants were collected along a training period of 3 weeks, while learning the execution of a new task. Specific indexes have been estimated from the behavioral and EEG signal to objectively assess the users' training progress. Furthermore, we proposed a neurometric based on a machine learning algorithm to quantify the user's training level within each session by considering the level of task execution, and both the behavioral and cognitive stabilities between consecutive sessions. The results demonstrated that the proposed methodology and neurometric could quantify and track the users' progresses, and provide the Instructor information for a more objective evaluation and better tailoring of training programs. © 2017 Borghini, Aricò, Di Flumeri, Sciaraffa, Colosimo, Herrero, Bezerianos, Thakor and Babiloni

After-effects of 10 Hz tACS over the prefrontal cortex on phonological word decisions

Introduction Previous work in the language domain has shown that 10 Hz rTMS of the left or right posterior inferior frontal gyrus (pIFG) in the prefrontal cortex impaired phonological decision-making, arguing for a causal contribution of the bilateral pIFG to phonological processing. However, the neurophysiological correlates of these effects are unclear. The present study addressed the question whether neural activity in the prefrontal cortex could be modulated by 10 Hz tACS and how this would affect phonological decisions. Methods In three sessions, 24 healthy participants received tACS at 10 Hz or 16.18 Hz (control frequency) or sham stimulation over the bilateral prefrontal cortex before task processing. Resting state EEG was recorded before and after tACS. We also recorded EEG during task processing. Results Relative to sham stimulation, 10 Hz tACS significantly facilitated phonological response speed. This effect was task-specific as tACS did not affect a simple control task. Moreover, 10 Hz tACS significantly increased theta power during phonological decisions. The individual increase in theta power was positively correlated with the behavioral facilitation after 10 Hz tACS. Conclusion Our results show a facilitation of phonological decisions after 10 Hz tACS over the bilateral prefrontal cortex. This might indicate that 10 Hz tACS increased task-related activity in the stimulated area to a level that was optimal for phonological performance. The significant correlation with the individual increase in theta power suggests that the behavioral facilitation might be related to increased theta power during language processing

Noninvasive brain stimulation techniques can modulate cognitive processing

Recent methods that allow a noninvasive modulation of brain activity are able to modulate human cognitive behavior. Among these methods are transcranial electric stimulation and transcranial magnetic stimulation that both come in multiple variants. A property of both types of brain stimulation is that they modulate brain activity and in turn modulate cognitive behavior. Here, we describe the methods with their assumed neural mechanisms for readers from the economic and social sciences and little prior knowledge of these techniques. Our emphasis is on available protocols and experimental parameters to choose from when designing a study. We also review a selection of recent studies that have successfully applied them in the respective field. We provide short pointers to limitations that need to be considered and refer to the relevant papers where appropriate

Post-training load-related changes of auditory working memory: An EEG study

Working memory (WM) refers to the temporary retention and manipulation of information, and its capacity is highly susceptible to training. Yet, the neural mechanisms that allow for increased performance under demanding conditions are not fully understood. We expected that post-training efficiency in WM performance modulates neural processing during high load tasks. We tested this hypothesis, using electroencephalography (EEG) (N = 39), by comparing source space spectral power of healthy adults performing low and high load auditory WM tasks. Prior to the assessment, participants either underwent a modality-specific auditory WM training, or a modality-irrelevant tactile WM training, or were not trained (active control). After a modality-specific training participants showed higher behavioral performance, compared to the control. EEG data analysis revealed general effects of WM load, across all training groups, in the theta-, alpha-, and beta-frequency bands. With increased load theta-band power increased over frontal, and decreased over parietal areas. Centro-parietal alpha-band power and central beta-band power decreased with load. Interestingly, in the high load condition a tendency toward reduced beta-band power in the right medial temporal lobe was observed in the modality-specific WM training group compared to the modality-irrelevant and active control groups. Our finding that WM processing during the high load condition changed after modality-specific WM training, showing reduced beta-band activity in voice-selective regions, possibly indicates a more efficient maintenance of task-relevant stimuli. The general load effects suggest that WM performance at high load demands involves complementary mechanisms, combining a strengthening of task-relevant and a suppression of task-irrelevant processing

Working memory revived in older adults by synchronizing rhythmic brain circuits

Published in final edited form as: Nat Neurosci. 2019 May ; 22(5): 820–827. doi:10.1038/s41593-019-0371-x.Understanding normal brain aging and developing methods to maintain or improve cognition in older adults are major goals of fundamental and translational neuroscience. Here we show a core feature of cognitive decline—working-memory deficits—emerges from disconnected local and long-range circuits instantiated by theta–gamma phase–amplitude coupling in temporal cortex and theta phase synchronization across frontotemporal cortex. We developed a noninvasive stimulation procedure for modulating long-range theta interactions in adults aged 60–76 years. After 25 min of stimulation, frequency-tuned to individual brain network dynamics, we observed a preferential increase in neural synchronization patterns and the return of sender–receiver relationships of information flow within and between frontotemporal regions. The end result was rapid improvement in working-memory performance that outlasted a 50 min post-stimulation period. The results provide insight into the physiological foundations of age-related cognitive impairment and contribute to groundwork for future non-pharmacological interventions targeting aspects of cognitive decline.Accepted manuscrip

Making Waves in the Brain: What Are Oscillations, and Why Modulating Them Makes Sense for Brain Injury.

Traumatic brain injury (TBI) can result in persistent cognitive, behavioral and emotional deficits. However, the vast majority of patients are not chronically hospitalized; rather they have to manage their disabilities once they are discharged to home. Promoting recovery to pre-injury level is important from a patient care as well as a societal perspective. Electrical neuromodulation is one approach that has shown promise in alleviating symptoms associated with neurological disorders such as in Parkinson's disease (PD) and epilepsy. Consistent with this perspective, both animal and clinical studies have revealed that TBI alters physiological oscillatory rhythms. More recently several studies demonstrated that low frequency stimulation improves cognitive outcome in models of TBI. Specifically, stimulation of the septohippocampal circuit in the theta frequency entrained oscillations and improved spatial learning following TBI. In order to evaluate the potential of electrical deep brain stimulation for clinical translation we review the basic neurophysiology of oscillations, their role in cognition and how they are changed post-TBI. Furthermore, we highlight several factors for future pre-clinical and clinical studies to consider, with the hope that it will promote a hypothesis driven approach to subsequent experimental designs and ultimately successful translation to improve outcome in patients with TBI

EEG, MEG and neuromodulatory approaches to explore cognition: Current status and future directions

Neural oscillations and their association with brain states and cognitive functions have been object of extensive investigation over the last decades. Several electroencephalography (EEG) and magnetoencephalography (MEG) analysis approaches have been explored and oscillatory properties have been identified, in parallel with the technical and computational advancement. This review provides an up-to-date account of how EEG/MEG oscillations have contributed to the understanding of cognition. Methodological challenges, recent developments and translational potential, along with future research avenues, are discussed. Keywords: Cognition; Electrophysiology; Event-related-potentials; Neural oscillations; Neural synchronisation; Neuromodulatio