Hossein DiniAalborg University
Hossein Dini
phd
About
18
Publications
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57
Citations
Citations since 2017
Introduction
Additional affiliations
July 2020 - November 2020
Publications
Publications (18)
Past cognitive neuroscience studies using naturalistic stimuli have considered narratives holistically and focused on cognitive processes. In this study, we incorporated the narrative structure, the dramatic arc, as an object of investigation, to examine how engagement levels fluctuate across a narrative-aligned dramatic arc. We explored the possib...
Background
Dynamic functional network connectivity (dFNC) estimated from resting‐state functional magnetic resonance imaging (rs‐fMRI) is a potentially powerful approach to investigate human behavior and cognition. However, previous studies barely investigate the reproducibility of dFNC features links with cognition. This study aims to examine whet...
Introduction
The focus of cognitive and psychological approaches to narrative has not so much been on the elucidation of important aspects of narrative, but rather on using narratives as tools for the investigation of higher order cognitive processes elicited by narratives (e.g., understanding, empathy, etc.). In this study, we work toward a scalar...
In this study, the narrativity of pictures is evaluated using behavioral scales and subconscious processes. The narrative context of the stimulus pictures was classified into four different Levels. For eliciting evoked potentials (EPs), a P300-based picture ranking system was adopted. The EPs were analyzed on significant differences between seen/un...
Past cognitive neuroscience studies using naturalistic stimuli have considered narratives holistically and focused on cognitive processes. In this study, we incorporated the narrative structure—the dramatic arc—as an object of investigation, to examine how engagement levels fluctuate across a narrative-aligned dramatic arc. We explored the possibil...
The focus of cognitive and psychological approaches to narrative has not so much been on the elucidation of important aspects of narrative, but rather on using narratives as tools for the investigation of higher order cognitive processes elicited by narratives (e.g., understanding, empathy, etc.). In this study, we work toward a scalar model of nar...
Neuropsychiatric disorders affect millions of people worldwide every year. Recent studies showed that the symptomatic overlaps across neuropsychiatric disorders mislead schizophrenia and bipolar disorder diagnosis. Additionally, recent studies claimed that schizoaffective disorder as a condition overlapped with both schizophrenia and bipolar disord...
XR technologies are increasingly considered as expressive media with special qualities for narrative representation. In this chapter, we chart some of the major challenges inherent in the implementation of digital narratives in XR. For this purpose, we consider the intersections between different research domains like classical and post‐structural...
Neuroimaging and behavioral studies have shown that brands convey meaning to consumers. To investigate the immediate reactions of the brain to brand logos, followed either by congruent or incongruent pictorial brand-related cues, can deepen understanding of the semantic processing of brands, and perhaps how consolidated the logo is in consumers’ mi...
Functional network connectivity has previously been shown to distinguish patient groups from healthy controls (HC). However, the overlap across schizophrenia (SZ), bipolar (BP), and schizoaffective disorder (SAD) is not clear yet. This study focuses on finding overlap across these three psychotic disorders using dynamic FNC (dFNC) and compares it w...
In this paper, we propose an interdisciplinary theoretical and empirical framework to investigate the particular faculties related to human “narrative cognition”, in general, and in relation to MRT in particular. In order to contextualize our approach, we shortly review the cognitive turn in narratology, as well as state of the art in different dom...
Background: Electroconvulsive therapy (ECT) is one of the most effective treatments for major depressive disorder. Recently, there has been increasing attention to evaluate the effect of ECT on resting-state functional magnetic resonance imaging (rs-fMRI). This study aims to compare rs-fMRI of depressive disorder (DEP) patients with healthy partici...
Background
Electroconvulsive Therapy (ECT) is one of the most effective treatments for major depressive disorder (DEP). There is recently increasing attention to evaluate ECT’s effect on resting-state functional magnetic resonance imaging (rs-fMRI). This study aims to compare rs-fMRI of DEP patients with healthy participants, investigate whether dy...
ADHD defects the recognition of facial emotions. This study assesses the neurophysiological differences between children with ADHD and matched healthy controls during a face emotional recognition task. The study also explores how brain connectivity is affected by ADHD. Electroencephalogram (EEG) signals were recorded from 64 scalp electrodes. Event...
Attention Hyperactivity Disorder (ADHD) is endorsed between 4% and 10% of the children. Despite being a well-studied disorder, its neurological-cognitive correlates remain unclear.(yurtbasi, 2018,journal of attention disorders).
The difficulty in recognizing the emotions of others leads to an experience of social infertility in the ADHD group. so t...
Questions
Questions (9)
Hi All
I am conducting an experiment using Vive pro Virtual Reality Glass and EEG simultaneously.
I figured out that there is a 20 Hz activity in the power spectrum density of EEG signals while using virtual reality glass compared to the EEG only condition.
Now, I do not know whether this activity is because of the electromagnetic activity of the VR device have some other reasons.
Is there anyone who had such an experience? would please tell me what are possible noises while using VR or may you introduce me to related sources?
Thank you so much in advance.
Hossein
Hi, i have a MEG-EEG dataset ta collected simultaneously, the size of dataset is 2GB. i try brainstorm toolbox, but it can't load the data completely, after loading there is no event on the dataset and also i can't see the signals in brain storm. in addition, loading procedures takes about 20 minutes that seem too be very long. is there any one can help me?
thanks,
we konw that to reduce the number of time series in nalysing EEG data it is better to use PCA what is mathematical approach to use PCA?
in some parts of applying ICA to an EEG data we have blind source seperation problem. how can we solve this problem?
I have two questions
1. what is the definition of neuro-feedback method?
2.if I wan to use this method for EEG data recorded from ADHD children what properties should my data have? should I record data again and again in different times?
how can we combine Fuzzy with the concept of synchronization likelihood?
as you know to investigate Functional connectivity we can use coherence and synchronization likelihood. I want to know which one of these methods are accurate and suitable for EEG data to diagnose ADHD?
I have an EEG data recorded form ADHD children. I want to know which approaches are suitable for this data?
