scholarly journals Cognitive-vestibular interactions: A review of patient difficulties and possible mechanisms

2006 ◽  
Vol 16 (3) ◽  
pp. 75-91 ◽  
Author(s):  
Douglas A. Hanes ◽  
Gin McCollum
Keyword(s):  
Motor Coordination ◽  
Short Term Memory ◽  
Spatial Perception ◽  
Memory Loss ◽  
Vestibular Nuclei ◽  
Cognitive Effects ◽  
Wide Range ◽  
Scientific Attention ◽  
Balance Functions ◽  
Vestibular Influence

Cognitive deficits such as poor concentration and short-term memory loss are known by clinicians to occur frequently among patients with vestibular abnormalities. Although direct scientific study of such deficits has been limited, several types of investigations do lend weight to the existence of vestibular-cognitive effects. In this article we review a wide range of studies indicating a vestibular influence on the ability to perform certain cognitive functions. In addition to tests of vestibular patient abilities, these studies include dual-task studies of cognitive and balance functions, studies of vestibular contribution to spatial perception and memory, and works demonstrating a vestibular influence on oculomotor and motor coordination abilities that are involved in the performance of everyday cognitive tasks. A growing literature on the physiology of the vestibular system has demonstrated the existence of projections from the vestibular nuclei to the cerebral cortex. The goals of this review are to both raise awareness of the cognitive effects of vestibular disease and to focus scientific attention on aspects of cognitive-vestibular interactions indicated by a wide range of results in the literature.

Role of MicroRNA Genes miR-1000 and miR-375 in Forming Olfactory Conditional Memory in Drosophila melanogaster

MicroRNA ◽  
2020 ◽  
Vol 09 ◽  
Author(s):  
Sadniman Rahman ◽  
Chaity Modak ◽  
Mousumi Akter ◽  
Mohammad Shamimul Alam
Keyword(s):  
Learning And Memory ◽  
Short Term Memory ◽  
Memory Loss ◽  
Memory Formation ◽  
Neural Integration ◽  
Significant Difference ◽  
Locomotion Speed ◽  
Microrna Genes ◽  
With Memory

Background: Learning and memory is basic aspects in neurogenetics as most of the neurological disorders start with dementia or memory loss. Several genes associated with memory formation have been discovered. MicroRNA genes miR-1000 and miR-375 were reported to be associated with neural integration and glucose homeostasis in some insects and vertebrates. However, neuronal function of these genes is yet to be established in D. melanogaster. Objective: Possible role of miR-1000 and miR-375 in learning and memory formation in this fly has been explored in the present study. Methods: Both appetitive and aversive olfactory conditional learning were tested in the miR-1000 and miR-375 knockout (KO) strains and compared with wild one. Five days old third instar larvae were trained by allowing them to be associated with an odor with reward (fructose) or punishment (salt). Then, the larvae were tested to calculate their preferences to the odor trained with. Learning index (LI) values and larval locomotion speed were calculated for all strains. Results: No significant difference was observed for larval locomotion speed in mutant strains. Knockout strain of miR-1000 showed significant deficiency in both appetitive and aversive memory formation whereas miR-375 KO strain showed a significantly lower response only in appetitive one. Conclusion: The results of the present study indicate important role played by these two genes in forming short-term memory in D. melanogaster.

scholarly journals Global soil moisture data derived through machine learning trained with in-situ measurements

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Sungmin O. ◽  
Rene Orth
Keyword(s):  
Machine Learning ◽  
Soil Moisture ◽  
Large Scale ◽  
Short Term Memory ◽  
Temporal Dynamics ◽  
Soil Moisture Data ◽  
Wide Range ◽  
Global Soil

AbstractWhile soil moisture information is essential for a wide range of hydrologic and climate applications, spatially-continuous soil moisture data is only available from satellite observations or model simulations. Here we present a global, long-term dataset of soil moisture derived through machine learning trained with in-situ measurements, SoMo.ml. We train a Long Short-Term Memory (LSTM) model to extrapolate daily soil moisture dynamics in space and in time, based on in-situ data collected from more than 1,000 stations across the globe. SoMo.ml provides multi-layer soil moisture data (0–10 cm, 10–30 cm, and 30–50 cm) at 0.25° spatial and daily temporal resolution over the period 2000–2019. The performance of the resulting dataset is evaluated through cross validation and inter-comparison with existing soil moisture datasets. SoMo.ml performs especially well in terms of temporal dynamics, making it particularly useful for applications requiring time-varying soil moisture, such as anomaly detection and memory analyses. SoMo.ml complements the existing suite of modelled and satellite-based datasets given its distinct derivation, to support large-scale hydrological, meteorological, and ecological analyses.

scholarly journals Case of early-onset Alzheimer’s disease with atypical manifestation

2021 ◽  
Vol 34 (1) ◽  
pp. e100283
Author(s):  
Lin Zhu ◽  
Limin Sun ◽  
Lin Sun ◽  
Shifu Xiao
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Clinical Manifestation ◽  
Early Onset ◽  
Short Term Memory ◽  
Brain Mri ◽  
Memory Loss ◽  
Amyloid Β ◽  
Amyloid Β Protein ◽  
Fluent Aphasia

Short-term memory decline is the typical clinical manifestation of Alzheimer’s disease (AD). However, early-onset AD usually has atypical symptoms and may get misdiagnosed. In the present case study, we reported a patient who experienced symptoms of memory loss with progressive non-fluent aphasia accompanied by gradual social withdrawal. He did not meet the diagnostic criteria of AD based on the clinical manifestation and brain MRI. However, his cerebrospinal fluid examination showed a decreased level of beta-amyloid 42, and increased total tau and phosphorylated tau. Massive amyloid β-protein deposition by 11C-Pittsburgh positron emission tomography confirmed the diagnosis of frontal variant AD. This case indicated that early-onset AD may have progressive non-fluent aphasia as the core manifestation. The combination of individual and precision diagnosis would be beneficial for similar cases.

Short-Term Memory Loss Associated with Rosuvastatin

2006 ◽  
Vol 26 (8) ◽  
pp. 1190-1192 ◽  
Author(s):  
Laura Galatti ◽  
Giovanni Polimeni ◽  
Francesco Salvo ◽  
Marcello Romani ◽  
Aurelio Sessa ◽  
...  
Keyword(s):  
Short Term Memory ◽  
Memory Loss ◽  
Short Term ◽  
Term Memory

scholarly journals Channel-independent recreation of artefactual signals in chronically recorded local field potentials using machine learning

2022 ◽  
Vol 9 (1) ◽  
Author(s):  
Marcos Fabietti ◽  
Mufti Mahmud ◽  
Ahmad Lotfi
Keyword(s):  
Machine Learning ◽  
Open Access ◽  
Short Term Memory ◽  
The Body ◽  
Data Sets ◽  
Additional Information ◽  
Machine Learning Model ◽  
Signal Characteristics ◽  
Wide Range ◽  
Memory Network

AbstractAcquisition of neuronal signals involves a wide range of devices with specific electrical properties. Combined with other physiological sources within the body, the signals sensed by the devices are often distorted. Sometimes these distortions are visually identifiable, other times, they overlay with the signal characteristics making them very difficult to detect. To remove these distortions, the recordings are visually inspected and manually processed. However, this manual annotation process is time-consuming and automatic computational methods are needed to identify and remove these artefacts. Most of the existing artefact removal approaches rely on additional information from other recorded channels and fail when global artefacts are present or the affected channels constitute the majority of the recording system. Addressing this issue, this paper reports a novel channel-independent machine learning model to accurately identify and replace the artefactual segments present in the signals. Discarding these artifactual segments by the existing approaches causes discontinuities in the reproduced signals which may introduce errors in subsequent analyses. To avoid this, the proposed method predicts multiple values of the artefactual region using long–short term memory network to recreate the temporal and spectral properties of the recorded signal. The method has been tested on two open-access data sets and incorporated into the open-access SANTIA (SigMate Advanced: a Novel Tool for Identification of Artefacts in Neuronal Signals) toolbox for community use.

scholarly journals Polygenic Scores for Cognitive Abilities and their Association with Different Aspects of General Intelligence – a Deep Phenotyping Approach

2020 ◽  
Author(s):  
Erhan Genç ◽  
Caroline Schlüter ◽  
Christoph Fraenz ◽  
Larissa Arning ◽  
Huu Phuc Nguyen ◽  
...  
Keyword(s):  
Cognitive Abilities ◽  
Large Scale ◽  
Short Term Memory ◽  
Life Outcomes ◽  
Short Term ◽  
Polygenic Scores ◽  
Wide Range ◽  
Dna Variants ◽  
Trait Prediction ◽  
Deep Phenotyping

AbstractIntelligence is a highly polygenic trait and GWAS have identified thousands of DNA variants contributing with small effects. Polygenic scores (PGS) can aggregate those effects for trait prediction in independent samples. As large-scale light-phenotyping GWAS operationalized intelligence as performance in rather superficial tests, the question arises which intelligence facets are actually captured. We used deep-phenotyping to investigate the molecular determinantes of individual differences in cognitive ability. We therefore studied the association between PGS of educational attainment (EA-PGS) and intelligence (IQ-PGS) with a wide range of intelligence facets in a sample of 320 healthy adults. EA-PGS and IQ-PGS had the highest incremental R2s for general (3.25%; 1.78%), verbal (2.55%; 2.39%) and numerical intelligence (2.79%; 1.54%) and the weakest for non-verbal intelligence (0.50%; 0.19%) and short-term memory (0.34%; 0.22%). These results indicate that PGS derived from light-phenotyping GWAS do not reflect different facets of intelligence equally well, and thus should not be interpreted as genetic indicators of intelligence per se. The findings refine our understanding of how PGS are related to other traits or life outcomes.

scholarly journals Transient Global Amnesia Associated with an Acute Infarction at the Cingulate Gyrus

2014 ◽  
Vol 2014 ◽  
pp. 1-4 ◽  
Author(s):  
Alejandro Gallardo-Tur ◽  
Jorge Romero-Godoy ◽  
Carlos de la Cruz Cosme ◽  
Adriá Arboix
Keyword(s):  
Limbic System ◽  
Short Term Memory ◽  
Memory Loss ◽  
Brain Magnetic Resonance Imaging ◽  
Transient Global Amnesia ◽  
Cingulate Gyrus ◽  
Clinical Disorder ◽  
Acute Infarction ◽  
Maximal Diameter ◽  
Global Amnesia

Background. Transient global amnesia (TGA) is a syndrome of sudden, unexplained isolated short-term memory loss. In the majority of TGA cases, no causes can be identified and neuroimaging, CSF studies and EEG are usually normal. We present a patient with TGA associated with a small acute infarct at the cingulate gyrus.Case Report. The patient, a 62 year-old man, developed two episodes of TGA. He had hypertension and hypercholesterolemia. He was found to have an acute ischemic stroke of small size (15 mm of maximal diameter) at the right cerebral cingulate gyrus diagnosed on brain magnetic resonance imaging. No lesions involving other limbic system structures such as thalamus, fornix, corpus callosum, or hippocampal structures were seen. The remainder of the examination was normal.Conclusion. Unilateral ischemic lesions of limbic system structures may result in TGA. We must bear in mind that TGA can be an associated clinical disorder of cingulate gyrus infarct.

scholarly journals High methionine, low folate and low vitamin B6/B12 (HM-LF-LV) diet causes neurodegeneration and subsequent short-term memory loss

2018 ◽  
Vol 33 (6) ◽  
pp. 1923-1934 ◽  
Author(s):  
Mohammed Nuru ◽  
Nino Muradashvili ◽  
Anuradha Kalani ◽  
David Lominadze ◽  
Neetu Tyagi
Keyword(s):  
Vitamin B6 ◽  
Short Term Memory ◽  
Memory Loss ◽  
Short Term ◽  
Term Memory

Executing CNN-LSTM Algorithm for Recognizable Proof of Cervical Spondylosis Infection on Spinal Cord MRI Image

2021 ◽  
pp. 468-484
Author(s):  
Sasank V. V. S. ◽  
Kranthi Kumar Singamaneni ◽  
A. Sampath Dakshina Murthy ◽  
S. K. Hasane Ahammad
Keyword(s):  
Neural Network ◽  
Cervical Spondylosis ◽  
Short Term Memory ◽  
Life Experience ◽  
Programming Approach ◽  
Physical Test ◽  
Term Memory ◽  
Wide Range ◽  
Long Short Term Memory ◽  
Mri Image

Various estimating mechanisms are present for evaluating the regional agony, neck torment, neurologic deficiencies of the sphincters at the stage midlevel of cervical spondylosis. It is necessary for the cervical spondylosis that the survey necessitates wide range of learning skills about the systemized life, experience, and ability of the expertise for learning the capability, life system, and experience. Doctors check the analysis of situation through MRI and CT scan, but additional interesting facts have been discovered in the physical test. For this, a programming approach is not available. The authors thereby propose a novel framework that accordingly inspects and investigates the cervical spondylosis employing computation of CNN-LSTM. Machine learning methods such as long short-term memory (LSTM) in fusion with convolution neural networks (CNNs), a kind of neural network (NN), are applied to this strategy to evaluate for making the systematization in various applications.

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