Brain Computer Interface (BCI), especially systems for recognizing brain signals using deep learning after characterizing these signals as EEG (Electroencephalography), is one of the important research topics that arouse the interest of many research
ers currently. Convolutional Neural Nets (CNN) is one of the most important deep learning classifiers used in this recognition process, but the parameters of this classifier have not yet been precisely defined so that it gives the highest recognition rate and the lowest possible training and recognition time.
This research proposes a system for recognizing EEG signals using the CNN network, while studying the effect of changing the parameters of this network on the recognition rate, training time, and recognition time of brain signals, as a result the proposed recognition system was achieved 76.38 % recognition rate, And the reduction of classifier training time (3 seconds) by using Common Spatial Pattern (CSP) in the preprocessing of IV2b dataset, and a recognition rate of 76.533% was reached by adding a layer to the proposed classifier.
Recent evidence supports a role for coreference processing in guiding human expectations about upcoming words during reading, based on covariation between reading times and word surprisal estimated by a coreference-aware semantic processing model (Ja
ffe et al. 2020).The present study reproduces and elaborates on this finding by (1) enabling the parser to process subword information that might better approximate human morphological knowledge, and (2) extending evaluation of coreference effects from self-paced reading to human brain imaging data. Results show that an expectation-based processing effect of coreference is still evident even in the presence of the stronger psycholinguistic baseline provided by the subword model, and that the coreference effect is observed in both self-paced reading and fMRI data, providing evidence of the effect's robustness.
A popular approach to decompose the neural bases of language consists in correlating, across individuals, the brain responses to different stimuli (e.g. regular speech versus scrambled words, sentences, or paragraphs). Although successful, this model
-free' approach necessitates the acquisition of a large and costly set of neuroimaging data. Here, we show that a model-based approach can reach equivalent results within subjects exposed to natural stimuli. We capitalize on the recently-discovered similarities between deep language models and the human brain to compute the mapping between i) the brain responses to regular speech and ii) the activations of deep language models elicited by modified stimuli (e.g. scrambled words, sentences, or paragraphs). Our model-based approach successfully replicates the seminal study of Lerner et al. (2011), which revealed the hierarchy of language areas by comparing the functional-magnetic resonance imaging (fMRI) of seven subjects listening to 7min of both regular and scrambled narratives. We further extend and precise these results to the brain signals of 305 individuals listening to 4.1 hours of narrated stories. Overall, this study paves the way for efficient and flexible analyses of the brain bases of language.
Background and objectives: The advent of high-resolution MRI with a dedicated epilepsy protocol improves the ability to identify possible structural abnormalities that underlie seizure disorders. The aims of this study were to evaluate the diagnostic
efficacy of standard MRI, identify whether there is an increase in the diagnostic yield with the addition of dedicated seizure protocol, and compare the diagnostic yields of MRI and electroencephalogram (EEG) individually and in combination. Subjects and Methods: This was a cross-sectional analytic study, included 100 cases who presented with seizure over 18 months. Patients underwent complete neurological examination, EEG, and MRI with a standard and dedicated epilepsy protocol. Results: We found epileptogenic lesions in MRI in 55.5. Mesial temporal lobe sclerosis was the most common epileptogenic lesion (45.5%). The diagnostic efficacy of MRI had increased with dedicated epilepsy protocol compared to standard protocol. Abnormal MRI and EEG were compatible in 21%. Conclusion and implications: Dedicated epilepsy protocol increased the diagnostic efficacy of brain MRI in detecting a structural epileptogenic lesion, with 100% of mesial temporal sclerosis, the most common lesion in our study, was detected only in dedicated epilepsy protocol and missed in standard protocol.
This paper studies 60 Patients with cerebral hydrocephalus (34 Mal, 26 females).
Their age ranged between 6 months and 72 years. They were treatment with VP shunts
with laparoscopic insertion of the peritoneal end.
The main indication was hydrocep
halus following trauma (28.3%), followed by
Sylvius canal stenosis(25%), after intracerebral hemorrhage (20%), meningocele(15%) and
finally by tumor- associated hydrocephalus (11.6%).
55% of patients had no previous abdominal operations and 45% have previous an
abdominal procedure.
The results showed that 81.6 of cases had op-duration less than one hour. Length of
abdominal incision was in 88.3% less than 1.5 cm. the hospitalization was significantly
shorter than open method, and so were the complications: only 3.3% had wound infection,
and 8.3 had shunt obstruction.
These findings support the importance of using endoscopic methods in the
implantation of the distal end of catheter, as they contribute to shortening the duration of
the work and reduce the length of surgical incision and shorten the period of
hospitalization of patients . it is also associated with a small percentage of complication.
This research aimed to recognition the effectiveness of program
proposed according to brainstorming method with using color print
images to acquiring the fourth grade students critical thinking
skills/classification, explanation, conclusion/ in social education .
This study has been conducted to adapt a quantitative RT-QPCR to
detect the least amount of virus and tissue culture pathogenic dose
(TCID50) of CAEV showed cytopathogenic effect (CPE) from
clinical samples.
There is Some evidence to suggest that the systemic inflammatory response syndrome
(SIRS) contributes to the poor outcome of cirrhotic patients. We studied 95 cirrhotic patients admitted
to Almouassat and Al-assad University Hospitals assessing prevalence of SIRS and its relationship
with short term outcome.
The purpose of this reseated is to estimate cerebral blood flow in the cerebral
microvasculature beds by measuring the change of the intensity gray scale levels in dynamic
angiographic images which have been acquired by Digital Subtraction Angiography (DSA).
A number of patients who had undergone to craniotomies for tumor resection,
re- intubated in ICU as urgent procedure. This may result in poor prognosis, overloading the staff, and
high cost.
The goal is looking for clinical, surgical, and laborato
ry risk factors helping in early detection of cases
which require keep ETT in place and maintaining of ventilation.
