Withdrawal symptoms of electrical brain stimulation in a probabilistic decision making task

Question – It has been shown that transcranial electrical brain stimulation (TES) can improve many aspects of cognition, including decision making and learning. However, it has not been studied whether brain is capable of adapting itself to perform at least equally well without TES, after initially learning the task under influence of TES. We used a probabilistic learning task to investigate this question. Methods – Participants (n = 10) took part in two groups of active (n = 5) and sham (n = 5) transcranial direct current stimulation (tDCS). Each participant attended two experimental sessions. In both sessions participants were asked to perform a probabilistic decision making task. In this task participants adapted to changes in reward contingencies. Participants were presented with two options of which one of them was designated as the better one, leading to higher possibility of rewarding than punishing feedback. Participants were asked to maximise their gain by choosing the better option. The contingencies changed over the course of the trials. Consequently participants had to adjust to the changes in the environment. In the first session, participants in the active and sham tDCS groups, received 15 minutes and 16 seconds of anodal tDCS over their left dorsolateral prefrontal cortex, respectively. For all participants sham stimulation was administered in the second session. Number of rewards in both sessions was recorded and their difference was considered for analysis. Results – Comparison of difference of acquired rewards between the two sessions showed that participants in the active group tend to perform worse than those in the sham group. Conclusions – This result shows that learning under the influence of TES leads to adaptation which induces changes that might not be efficient without TES in a later phase. In more general terms, this result indicates that learning a task under the influence of TES leads to creation of a model which might not be valid anymore without TES

Physical exercise improves long-term memory no less than transcranial direct current stimulation

Question – It has been shown that electrical brain stimulation, in particular transcranial direct current stimulation (tDCS), can improve memory performance. Physical exercise has also been shown to be able to improve different aspects of cognition. The aim of this study was to investigate which of these methods is more effective in improvement of long-term memory. Those tDCS and physical exercise protocols were chosen that have been shown to be effective in improvement of long-term memory: tDCS during memorisation (targeting encoding phase) and physical exercise after memorisation (targeting consolidation phase). We expected to see improvement following application of both methods. No prediction was made on which method is more effective. Methods – Participants (n = 24) took part in three experimental sessions. They were asked to memorise a set of images (‘encoding’) for a later old/new recognition task (‘recognition’). In one of the sessions participants were asked to cycle for 30 minutes on an exercise bike following encoding. In the other two sessions they received either 15 minutes (‘active’ stimulation) or 16 seconds (‘sham’ stimulation) of 1.5 mA anodal tDCS applied over the left dorsolateral prefrontal cortex (left-DLPFC). Performance of the participants in the recognition phase was recorded for analysis. Results – Both physical exercise and active stimulation led to significant improvement of long-term memory performance compared to sham stimulation (paired sample t-test p active tDCS). Conclusions – These results show that only 30 minutes of physical exercise can significantly improve long-term memory performance. Furthermore, this duration of physical exercise during consolidation was more effective than 15 minutes of tDCS during encoding. Considering that tentatively physical exercise lead to less adverse side effects as compared to electrical brain stimulation, physical exercise can be considered potentially a more effective method of cognitive enhancement, in particular in healthy participants

Investigating the role of parietal and prefrontal cortices in spatial working memory using tDCS

Question – Working memory involves the temporary storage, processing, and manipulation of information. Previous studies have suggested that the posterior parietal cortex (PPC), and dorsolateral prefrontal cortex (DLPFC) are involved in spatial working memory, and spatial and object working memory, respectively. The aim of the present pilot study was to investigate whether modulation of the activity of the left PPC and the left DLPFC changes spatial, and object working memory performance. Transcranial direct current stimulation (tDCS) was used for this purpose. Based on past literature we expected to see improvement of both spatial and object working memory after tDCS of the left DLPFC as well as improvement of spatial working memory after tDCS of the left PPC. Methods – Participants (n = 12) attended three experimental sessions with different stimulation conditions. Fifteen minutes of 1.5 mA anodal tDCS was applied over either the left PPC, left DLPFC or occipital lobe as control condition, beginning five minutes before the task. Participants were required to perform a 2-back spatial and object working memory task; i.e., they were required to pay attention to both objects and their location. Abstract objects were presented on either of an eight locations placed on a virtual circle around the centre of the screen. In addition to a 2-back object working memory task, occasionally participants were asked to indicate the location of the object they saw two screens previously. Performance in three different conditions was measured for analysis: (1) 2-back working memory task for the cases in which both cue and target objects were presented in the same location (OWM-same), (2) in different location (OWM-different) and (3) spatial working memory (SWM). Results – Preliminary results showed that performance in the OWM-different condition was lower than OWM-same. There, however, was no significant different between different stimulation conditions. Conclusions – These results suggest that anodal tDCS to the left PPC and left DLPFC might not be able to modulate spatial, and object working memory performance. Further studies are needed to investigate the differential role(s) of the DLPFC and PPC in spatial and working memory

A review of neurobiological factors underlying the selective enhancement of memory at encoding, consolidation, and retrieval

How is the strength of a memory determined? This review discusses three main factors that contribute to memory enhancement - 1) emotion, 2) targeted memory reactivation, and 3) neural reinstatement. Whilst the mechanisms through which memories become enhanced vary, this review demonstrates that activation of the basolateral amygdala and hippocampal formation are crucial for facilitating encoding, consolidation, and retrieval. Here we suggest methodological factors to consider in future studies, and discuss several unanswered questions that should be pursued in order to clarify selective memory enhancement

Exploring the neural correlates of dream phenomenology and altered states of consciousness during sleep

Do people routinely pre-activate the meaning and even the phonological form of upcoming words? The most acclaimed evidence for phonological prediction comes from a 2005 Nature Neuroscience publication by DeLong, Urbach and Kutas, who observed a graded modulation of electrical brain potentials (N400) to nouns and preceding articles by the probability that people use a word to continue the sentence fragment (‘cloze’). In our direct replication study spanning 9 laboratories (N=334), pre-registered replication-analyses and exploratory Bayes factor analyses successfully replicated the noun-results but, crucially, not the article-results. Pre-registered single-trial analyses also yielded a statistically significant effect for the nouns but not the articles. Exploratory Bayesian single-trial analyses showed that the article-effect may be non-zero but is likely far smaller than originally reported and too small to observe without very large sample sizes. Our results do not support the view that readers routinely pre-activate the phonological form of predictable words

Delayed, distant skin lesions after transcranial direct current stimulation

Non peer reviewe

Neural correlate of memory enhancement during physical exercise

It has been shown that physical exercise is beneficial for cognition, however, the neuronal mechanism underpinning this process is not yet clear. Therefore, we investigated the correlation of brain activity during physical exercise with memory performance. Eighteen participants were asked to memorise a set of stimuli. Subsequently they either cycled on an exercise bike for 30 minutes while their EEG was recorded, or sat on the exercise bike and watched a documentary for 30 minutes. After a 1.5 hour retention interval, they were asked to perform an old/new recognition task. In addition to improvement in memory performance (exercise 71.11% vs. rest 66.67%, p=0.02), the theta band activity of the DLPFC was correlated with the enhanced performance (r=-0.48, p=0.04)

Diagnosis of early mild cognitive impairment using a multiobjective optimization algorithm based on T1-MRI data

Alzheimer’s disease (AD) is the most prevalent form of dementia. The accurate diagnosis of AD, especially in the early phases is very important for timely intervention. It has been suggested that brain atrophy, as measured with structural magnetic resonance imaging (sMRI), can be an efficacy marker of neurodegeneration. While classification methods have been successful in diagnosis of AD, the performance of such methods have been very poor in diagnosis of those in early stages of mild cognitive impairment (EMCI). Therefore, in this study we investigated whether optimisation based on evolutionary algorithms (EA) can be an effective tool in diagnosis of EMCI as compared to cognitively normal participants (CNs). Structural MRI data for patients with EMCI (n = 54) and CN participants (n = 56) was extracted from Alzheimer’s disease Neuroimaging Initiative (ADNI). Using three automatic brain segmentation methods, we extracted volumetric parameters as input to the optimisation algorithms. Our method achieved classification accuracy of greater than 93%. This accuracy level is higher than the previously suggested methods of classification of CN and EMCI using a single- or multiple modalities of imaging data. Our results show that with an effective optimisation method, a single modality of biomarkers can be enough to achieve a high classification accuracy

Cortical and Subcortical Structural Segmentation in Alzheimer’s Disease

Purpose: Alzheimer’s disease is a neurodegenerative disease that begins before clinical symptoms emerge. Amyloid-beta plaques and tau neurofibrillary tangles are the hallmark lesions of Alzheimer’s Disease (AD). Amyloid-beta plaques deposition is associated with increased hippocampal volume loss. The tissue volume measures reflect multiple underlying pathologies contributing to neurodegeneration, of which are the most characteristics of AD. Anatomical atrophy, as evidenced using Magnetic Resonance Imaging (MRI), is one of the most validated, easily accessible and widely used biomarkers of AD. Measurements of whole brain and hippocampal atrophy rates from serial structural MRI are potential markers of the underlying neuroaxonal damage and disease progression in AD. In this study, we extract automatically subcortical brain structures in AD and control subjects. Materials and Methods: In this study we used 20 images (10 AD patients and 10 controls) taken from the Minimal Interval Resonance Imaging in Alzheimer's Disease (MIRIAD) dataset. We obtained volumes of Cerebrospinal Fluid (CSF), White Matter (WM), Grey Matter (GM), brain hemispheres, cerebellum and brainstem using volBrain pipeline. Subcortical brain structure segments and related volumes and label maps information were extracted. We compared left and right sides of some of the important brain area in AD for obtaining a biomarker with brain atrophy. Amygdala, caudate and hippocampus have shown to be undergone atrophy in AD. Results: We provided volume information of some intracranial areas such as brain hemispheres, cerebellum and brainstem. Conclusion: The results showed smaller hippocampal volume in AD patients compared to the controls. In addition to hippocampus, similar atrophy is also observable in amygdala and caudate