scholarly journals Neural Oscillations for Encoding and Decoding Declarative Memory using EEG Signals

2020 ◽  
Author(s):  
Jenifer Kalafatovich ◽  
Minji Lee
Keyword(s):  
Declarative Memory ◽  
Neural Oscillations ◽  
Eeg Signals

Working, Declarative, and Procedural Memory in Children With Developmental Language Disorder

2020 ◽  
Vol 63 (12) ◽  
pp. 4162-4178
Author(s):  
Emily Jackson ◽  
Suze Leitão ◽  
Mary Claessen ◽  
Mark Boyes
Keyword(s):  
Working Memory ◽  
Short Term Memory ◽  
Language Disorder ◽  
Declarative Memory ◽  
Memory Systems ◽  
Procedural Memory ◽  
Typically Developing ◽  
Short Term ◽  
Term Memory ◽  
Visual Spatial

Purpose Previous research into the working, declarative, and procedural memory systems in children with developmental language disorder (DLD) has yielded inconsistent results. The purpose of this research was to profile these memory systems in children with DLD and their typically developing peers. Method One hundred four 5- to 8-year-old children participated in the study. Fifty had DLD, and 54 were typically developing. Aspects of the working memory system (verbal short-term memory, verbal working memory, and visual–spatial short-term memory) were assessed using a nonword repetition test and subtests from the Working Memory Test Battery for Children. Verbal and visual–spatial declarative memory were measured using the Children's Memory Scale, and an audiovisual serial reaction time task was used to evaluate procedural memory. Results The children with DLD demonstrated significant impairments in verbal short-term and working memory, visual–spatial short-term memory, verbal declarative memory, and procedural memory. However, verbal declarative memory and procedural memory were no longer impaired after controlling for working memory and nonverbal IQ. Declarative memory for visual–spatial information was unimpaired. Conclusions These findings indicate that children with DLD have deficits in the working memory system. While verbal declarative memory and procedural memory also appear to be impaired, these deficits could largely be accounted for by working memory skills. The results have implications for our understanding of the cognitive processes underlying language impairment in the DLD population; however, further investigation of the relationships between the memory systems is required using tasks that measure learning over long-term intervals. Supplemental Material https://doi.org/10.23641/asha.13250180

Learning and Consolidation of Verbal Declarative Memory in Patients with Posttraumatic Stress Disorder

2010 ◽  
Vol 218 (2) ◽  
pp. 135-140 ◽  
Author(s):  
Slawomira J. Diener ◽  
Herta Flor ◽  
Michèle Wessa
Keyword(s):  
Posttraumatic Stress Disorder ◽  
Posttraumatic Stress ◽  
Verbal Memory ◽  
Stress Disorder ◽  
Declarative Memory ◽  
Memory Performance ◽  
Verbal Learning ◽  
Depression Scale ◽  
Learning Performance ◽  
Ptsd Symptoms

Impairments in declarative memory have been reported in posttraumatic stress disorder (PTSD). Fragmentation of explicit trauma-related memory has been assumed to impede the formation of a coherent memorization of the traumatic event and the integration into autobiographic memory. Together with a strong non-declarative memory that connects trauma reminders with a fear response the impairment in declarative memory is thought to be involved in the maintenance of PTSD symptoms. Fourteen PTSD patients, 14 traumatized subjects without PTSD, and 13 non-traumatized healthy controls (HC) were tested with the California Verbal Learning Test (CVLT) to assess verbal declarative memory. PTSD symptoms were assessed with the Clinician Administered PTSD Scale and depression with the Center of Epidemiological Studies Depression Scale. Several indices of the CVLT pointed to an impairment in declarative memory performance in PTSD, but not in traumatized persons without PTSD or HC. No group differences were observed if recall of memory after a time delay was set in relation to initial learning performance. In the PTSD group verbal memory performance correlated significantly with hyperarousal symptoms, after concentration difficulties were accounted for. The present study confirmed previous reports of declarative verbal memory deficits in PTSD. Extending previous results, we propose that learning rather than memory consolidation is impaired in PTSD patients. Furthermore, arousal symptoms may interfere with successful memory formation in PTSD.

Complexity Measures of Brain Electrophysiological Activity

2010 ◽  
Vol 24 (2) ◽  
pp. 131-135 ◽  
Author(s):  
Włodzimierz Klonowski ◽  
Pawel Stepien ◽  
Robert Stepien
Keyword(s):  
Brain Activity ◽  
Deterministic Chaos ◽  
Epileptic Seizures ◽  
Eeg Signal ◽  
Eeg Signals ◽  
Complexity Measures ◽  
Electrophysiological Activity ◽  
Signal Complexity ◽  
Physiological Sleep ◽  
The Brain

Over 20 years ago, Watt and Hameroff (1987 ) suggested that consciousness may be described as a manifestation of deterministic chaos in the brain/mind. To analyze EEG-signal complexity, we used Higuchi’s fractal dimension in time domain and symbolic analysis methods. Our results of analysis of EEG-signals under anesthesia, during physiological sleep, and during epileptic seizures lead to a conclusion similar to that of Watt and Hameroff: Brain activity, measured by complexity of the EEG-signal, diminishes (becomes less chaotic) when consciousness is being “switched off”. So, consciousness may be described as a manifestation of deterministic chaos in the brain/mind.

NON-INVASIVE BCI METHOD: EEG - ELECTROENCEPHALOGRAPHY

2019 ◽  
pp. 139-145
Author(s):  
Selma Büyükgöze
Keyword(s):  
Brain Computer Interface ◽  
Computer Interface ◽  
Electrode Placement ◽  
Eeg Signals ◽  
Non Invasive ◽  
Brain Signals ◽  
Brain States ◽  
The Brain

Brain Computer Interface consists of hardware and software that convert brain signals into action. It changes the nerves, muscles, and movements they produce with electro-physiological signs. The BCI cannot read the brain and decipher the thought in general. The BCI can only identify and classify specific patterns of activity in ongoing brain signals associated with specific tasks or events. EEG is the most commonly used non-invasive BCI method as it can be obtained easily compared to other methods. In this study; It will be given how EEG signals are obtained from the scalp, with which waves these frequencies are named and in which brain states these waves occur. 10-20 electrode placement plan for EEG to be placed on the scalp will be shown.

Modeling of EEG Signals Using Wavelets with Iterative Soft Thresholding

2011 ◽  
Vol 6 (4) ◽  
pp. 37-42
Author(s):  
B.krishna Kumar ◽  
◽  
K.V.S.V.R. Prasad ◽  
K. Kishan Rao ◽  
J. Sheshagiri Babu ◽  
...  
Keyword(s):  
Eeg Signals ◽  
Soft Thresholding ◽  
Iterative Soft Thresholding

Classification of EEG Signals using Genetic Programming

2017 ◽  
Author(s):  
Marco Antonio Meggiolaro ◽  
Felipe Rebelo Lopes
Keyword(s):  
Genetic Programming ◽  
Eeg Signals
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