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16+ results
Field: Cognitive Neuroscience

Change blindness: past, present, and future

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Daniel J. Simons, Ronald A. Rensink

Journal: Trends in Cognitive SciencesYear: 2004
Citations: 1154

Change blindness is the striking failure to see large changes that normally would be noticed easily. Over the past decade this phenomenon has greatly contributed to our understanding of attention, perception, and even consciousness. The surprising extent of change blindness explains its broad appeal...

Life SciencesNeuroscienceCognitive NeuroscienceOpen Access
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The default mode network in cognition: a topographical perspective

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Jonathan Smallwood, Boris C. Bernhardt, Robert Leech, Danilo Bzdok et al.

Journal: Nature reviews. NeuroscienceYear: 2021Citations: 953

The default mode network (DMN) is a set of widely distributed brain regions in the parietal, temporal and frontal cortex. These regions often show reductions in activity during attention-demanding tasks but increase their activity across multiple forms of complex cognition, many of which are linked ...

Life SciencesNeuroscienceCognitive NeuroscienceOpen Access
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Identifying objects by touch: An “expert system”

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Roberta L. Klatzky, Susan J. Lederman, Victoria A. Metzger

Journal: Perception & PsychophysicsYear: 1985Citations: 579
Life SciencesNeuroscienceCognitive NeuroscienceOpen Access
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Prevalence of comorbid psychiatric disorders among people with autism spectrum disorder: An umbrella review of systematic reviews and meta-analyses

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Md Mahbub Hossain, Nusrat Khan, Abida Sultana, Ping Ma et al.

Journal: Psychiatry ResearchYear: 2020Citations: 478

With ever-increasing prevalence of various mental disorders worldwide, a comprehensive evaluation of the prevalence of co-occurring psychiatric disorders among individuals with autism spectrum disorder (ASD) is needed to strengthen the knowledge base. This umbrella review aims to summarize the curre...

Life SciencesNeuroscienceCognitive Neuroscience
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Progress in Brain Computer Interface: Challenges and Opportunities

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Simanto Saha, Khondaker A. Mamun, Khawza Ahmed, Raqibul Mostafa et al.

Journal: Frontiers in Systems NeuroscienceYear: 2021Citations: 353

Brain computer interfaces (BCI) provide a direct communication link between the brain and a computer or other external devices. They offer an extended degree of freedom either by strengthening or by substituting human peripheral working capacity and have potential applications in various fields such...

Life SciencesNeuroscienceCognitive NeuroscienceOpen Access
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Topologically Convergent and Divergent Structural Connectivity Patterns between Patients with Remitted Geriatric Depression and Amnestic Mild Cognitive Impairment

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Feng Bai, Ni Shu, Yonggui Yuan, Yongmei Shi et al.

Journal: Journal of NeuroscienceYear: 2012Citations: 306

Alzheimer's disease (AD) can be conceptualized as a disconnection syndrome. Both remitted geriatric depression (RGD) and amnestic mild cognitive impairment (aMCI) are associated with a high risk for developing AD. However, little is known about the similarities and differences in the topological pat...

Life SciencesNeuroscienceCognitive NeuroscienceOpen Access
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Failure to Consolidate the Consolidation Theory of Learning for Sensorimotor Adaptation Tasks

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Graham Caithness, Rieko Osu, Paul M. Bays, Henry W. Chase et al.

Journal: Journal of NeuroscienceYear: 2004Citations: 282

An influential idea in human motor learning is that there is a consolidation period during which motor memories are transformed from a fragile to a permanent state, no longer susceptible to interference from new learning. The evidence supporting this idea comes from studies showing that the motor me...

Life SciencesNeuroscienceCognitive NeuroscienceOpen Access
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Computer-aided sleep staging using Complete Ensemble Empirical Mode Decomposition with Adaptive Noise and bootstrap aggregating

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Ahnaf Rashik Hassan, Mohammed Imamul Hassan Bhuiyan

Journal: Biomedical Signal Processing and ControlYear: 2015Citations: 271
Life SciencesNeuroscienceCognitive Neuroscience
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A Machine Learning-Based Big EEG Data Artifact Detection and Wavelet-Based Removal: An Empirical Approach

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Shalini Stalin, Vandana Roy, Prashant Kumar Shukla, Atef Zaguia et al.

Journal: Mathematical Problems in EngineeringYear: 2021Citations: 264

The electroencephalogram (EEG) signals are a big data which are frequently corrupted by motion artifacts. As human neural diseases, diagnosis and analysis need a robust neurological signal. Consequently, the EEG artifacts’ eradication is a vital step. In this research paper, the primary motion artif...

Life SciencesNeuroscienceCognitive NeuroscienceOpen Access
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Brain-Computer Interface: Advancement and Challenges

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M. F. Mridha, Sujoy Chandra Das, Md. Mohsin Kabir, Aklima Akter Lima et al.

Journal: SensorsYear: 2021Citations: 253

Brain-Computer Interface (BCI) is an advanced and multidisciplinary active research domain based on neuroscience, signal processing, biomedical sensors, hardware, etc. Since the last decades, several groundbreaking research has been conducted in this domain. Still, no comprehensive review that cover...

Life SciencesNeuroscienceCognitive NeuroscienceOpen Access
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Detection of Seizure and Epilepsy Using Higher Order Statistics in the EMD Domain

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Samiul Alam, M. I. H. Bhuiyan

Journal: IEEE Journal of Biomedical and Health InformaticsYear: 2013Citations: 250

In this paper, a method using higher order statistical moments of EEG signals calculated in the empirical mode decomposition (EMD) domain is proposed for detecting seizure and epilepsy. The appropriateness of these moments in distinguishing the EEG signals is investigated through an extensive analys...

Life SciencesNeuroscienceCognitive Neuroscience
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A decision support system for automatic sleep staging from EEG signals using tunable Q-factor wavelet transform and spectral features

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Ahnaf Rashik Hassan, Mohammed Imamul Hassan Bhuiyan

Journal: Journal of Neuroscience MethodsYear: 2016Citations: 249

Background Automatic sleep scoring is essential owing to the fact that conventionally a large volume of data have to be analyzed visually by the physicians which is onerous, time-consuming and error-prone. Therefore, there is a dire need of an automated sleep staging scheme. New method In this work,...

Life SciencesNeuroscienceCognitive Neuroscience
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Which outcomes are most important to people with aphasia and their families? an international nominal group technique study framed within the ICF

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Sarah J. Wallace, Linda Worrall, Tanya Rose, Guylaine Le Dorze et al.

Journal: Disability and RehabilitationYear: 2016Citations: 243

PURPOSE: To identify important treatment outcomes from the perspective of people with aphasia and their families using the ICF as a frame of reference. METHODS: The nominal group technique was used with people with aphasia and their family members in seven countries to identify and rank important tr...

Life SciencesNeuroscienceCognitive NeuroscienceOpen Access
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Automated identification of sleep states from EEG signals by means of ensemble empirical mode decomposition and random under sampling boosting

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Ahnaf Rashik Hassan, Mohammed Imamul Hassan Bhuiyan

Journal: Computer Methods and Programs in BiomedicineYear: 2016Citations: 236

Background and objective Automatic sleep staging is essential for alleviating the burden of the physicians of analyzing a large volume of data by visual inspection. It is also a precondition for making an automated sleep monitoring system feasible. Further, computerized sleep scoring will expedite l...

Life SciencesNeuroscienceCognitive Neuroscience
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A decision support system for automated identification of sleep stages from single-channel EEG signals

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Ahnaf Rashik Hassan, Abdülhamit Subaşı

Journal: Knowledge-Based SystemsYear: 2017Citations: 234
Life SciencesNeuroscienceCognitive Neuroscience
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