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Unified Granger causality analysis (uGCA) alters conventional two-stage Granger causality analysis into a unified code-length guided framework. We have presented several forms of uGCA methods to investigate ca...
Neuronal signals generally represent activation of the neuronal networks and give insights into brain functionalities. They are considered as fingerprints of actions and their processing across different struc...
Mental stress is a major individual and societal burden and one of the main contributing factors that lead to pathologies such as depression, anxiety disorders, heart attacks, and strokes. Given that anxiety d...
Annually, over three million people in North America suffer concussions. Every age group is susceptible to concussion, but youth involved in sporting activities are particularly vulnerable, with about 6% of al...
The Lateral Geniculate Nucleus (LGN) represents one of the major processing sites along the visual pathway. Despite its crucial role in processing visual information and its utility as one target for recently ...
Anaesthesia is a state of temporary controlled loss of awareness induced for medical operations. An accurate assessment of the depth of anaesthesia (DoA) helps anesthesiologists to avoid awareness during surge...
Memory, the process of encoding, storing, and maintaining information over time to influence future actions, is very important in our lives. Losing it, it comes with a great cost. Deciphering the biophysical m...
Multivariate prediction of human behavior from resting state data is gaining increasing popularity in the neuroimaging community, with far-reaching translational implications in neurology and psychiatry. Howev...
Subject motion can introduce noise into neuroimaging data and result in biased estimations of brain structure. In-scanner motion can compromise data quality in a number of ways and varies widely across develop...
Attention is an important commodity in the human skills set. It can be trained to overcome deficits in the short term which might be based on multiple cognitive complications to entail inability to keep focus ...
In this study, the relationship of orienting of attention, motor control and the Stimulus- (SDN) and Goal-Driven Networks (GDN) was explored through an innovative method for fMRI analysis considering all voxel...
Parents play an important role in the mental development of a child. In our previous work, we addressed how a narcissistic parent influences a child (online/offline) when (s)he is happy and admires the child. ...
The brain is a complex system, due to the heterogeneity of its structure, the diversity of the functions in which it participates and to its reciprocal relationships with the body and the environment. A system...
Major depressive disorder (MDD) is an issue that affects 350 million people worldwide. Traditional approaches have been to identify depressive symptoms in datasets, but recently, research is beginning to explo...
Seizure is an abnormal electrical activity of the brain. Neurologists can diagnose the seizure using several methods such as neurological examination, blood tests, computerized tomography (CT), magnetic resona...
Cognitive regulation of emotion has been proven to be effective to take control the emotional responses. Some cognitive models have also been proposed to explain the neural mechanism that underlies this proces...
Various machine-learning classification techniques have been employed previously to classify brain states in healthy and disease populations using functional magnetic resonance imaging (fMRI). These methods ge...
Neuroimaging text mining extracts knowledge from neuroimaging texts and has received widespread attention. Topic learning is an important research focus of neuroimaging text mining. However, current neuroimagi...
Here we provide evidence with an exploratory pilot study that through the use of a Gamma 40 Hz entrainment frequency, mood, memory and cognition can be improved with respect to a 9-participant cohort. Particip...
The mystery of aesthetics attracts scientists from various research fields. The topic of aesthetics, in combination with other disciplines such as neuroscience and computer science, has brought out the burgeon...
As a commonly used anesthetic agent, midazolam has the properties of water-soluble, rapid onset, and short duration of action. With the rapid development in the field of neuroimaging, numerous studies have inv...
Since manual tracing is time consuming and the performance of automatic tracing is unstable, it is still a challenging task to generate accurate neuron reconstruction efficiently and effectively. One strategy ...
By computerized analysis of cortical activity recorded via fMRI for pediatric epilepsy patients, we implement algorithmic localization of epileptic seizure focus within one of eight cortical lobes. Our innovat...
With the growing number of the aged population, the number of Parkinson’s disease (PD) affected people is also mounting. Unfortunately, due to insufficient resources and awareness in underdeveloped countries, ...
Neuroimaging, in particular magnetic resonance imaging (MRI), has been playing an important role in understanding brain functionalities and its disorders during the last couple of decades. These cutting-edge M...
Neuromarketing has become an academic and commercial area of interest, as the advancements in neural recording techniques and interpreting algorithms have made it an effective tool for recognizing the unspoken...
In this paper, a novel approach that is based on two-stepped majority voting is proposed for efficient EEG-based emotion classification. Emotion recognition is important for human–machine interactions. Facial ...
Interpretation of brain activity responses using motor imagery (MI) paradigms is vital for medical diagnosis and monitoring. Assessed by machine learning techniques, identification of imagined actions is hinde...
This paper proposes a novel feature selection method utilizing Rényi min-entropy-based algorithm for achieving a highly efficient brain–computer interface (BCI). Usually, wavelet packet transformation (WPT) is...
Epilepsy and psychogenic non-epileptic seizures (PNES) often show over-lap in symptoms, especially at an early disease stage. During a PNES, the electrical activity of the brain remains normal but in case of a...
Epilepsy is a serious chronic neurological disorder, can be detected by analyzing the brain signals produced by brain neurons. Neurons are connected to each other in a complex way to communicate with human org...
The electroencephalogram (EEG) is a tool for diagnosing epilepsy; by analyzing it, neurologists can identify alterations in brain activity associated with epilepsy. However, this task is not always easy to per...
In recent days, deep learning technologies have achieved tremendous success in computer vision-related tasks with the help of large-scale annotated dataset. Obtaining such dataset for medical image analysis is...
Research advancements in neuroscience entail the production of a substantial amount of data requiring interpretation, analysis, and integration. The complexity and diversity of neuroscience data necessitate th...
To improve the efficiency of the structural optimization design in truss calculation, an improved fruit fly optimization algorithm was proposed for truss structure optimization. The fruit fly optimization algo...
It is important to identify brain-based biomarkers that progressively deteriorate from healthy to mild cognitive impairment (MCI) to Alzheimer’s disease (AD). Cortical thickness, amyloid-ß deposition, and grap...
As an advanced function of the human brain, emotion has a significant influence on human studies, works, and other aspects of life. Artificial Intelligence has played an important role in recognizing human emo...
Alzheimer’s disease is the most common neurodegenerative disease and is characterized by the accumulation of amyloid-beta peptides leading to the formation of plaques and tau protein tangles in brain. These n...
While it is well established that cortical morphology differs in relation to a variety of inter-individual factors, it is often characterized using estimates of volume, thickness, surface area, or gyrification...
With both knowing more and more details about how neurons and complex neural networks work and having serious demand for making performable huge artificial networks, more and more efforts are devoted to build ...
Enhanced resolution of 7 T magnetic resonance imaging (MRI) scanners has considerably advanced our knowledge of structure and function in human and animal brains. Post-industrialized countries are particularly...
The perception of an external stimulus not only depends upon the characteristics of the stimulus but is also influenced by the ongoing brain activity prior to its presentation. In this work, we directly tested...
With the increase in system complexity, the intelligent heuristic optimization methods have received more and more attention on system reliability analysis. However, the objective functions and constraint cond...
Although the objective depression evaluation is a hot topic in recent years, less is known concerning developing a pervasive and objective approach for quantitatively evaluating depression. Driven by the Wisdo...
This literature survey attempts to clarify different approaches considered to study the impact of the musical stimulus on the human brain using EEG Modality. Glancing at the field through various aspects of su...
Imaging genetics deals with relationships between genetic variation and imaging variables, often in a disease context. The complex relationships between brain volumes and genetic variants have been explored wi...
We revisit the side-channel attacks with brain–computer interfaces (BCIs) first put forward by Martinovic et al. at the USENIX 2012 Security Symposium. For this purpose, we propose a comprehensive investigatio...
Detection of epileptic seizure activities from long-term multi-channel electroencephalogram (EEG) signals plays a significant role in the timely treatment of the patients with epilepsy. Visual identification o...
In the original publication of this article [1], the spelling of second author was incorrect.
The original article was published in Brain Informatics 2018 5:8
Models of time perception share an element of scalar expectancy theory known as the internal clock, containing specific mechanisms by which the brain is able to experience time passing and function effectively...
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Brain Informatics and Health (Editors-in-Chief: Zhong, Ning, Kikinis, Ron; Series Editors: Cai, W., Müller, H., Onoe, H., Pujol, S., Yu, P.S.)
