Log In Sign up
The largest database of trusted experimental protocols
> Physiology > Mental Process > Attention

Attention

Attention is the cognitive process of selectively concentrating on one aspect of the environment while ignoring others.
It is a key component of human cognition, enabling us to focus our mental resources on relevant information and tasks.
Attention plays a crucial role in perception, memory, decision-making, and other higher-order cognitive functions.
Reserach in this area has yielded valuable insights into the neurological and psychological mechanisms underlying attentional processes, and has applications in fields such as psychology, neuroscience, and cognitive science.
Understanding the complexities of attention can unlock new avenues for enhancing human performance and optimizing cognitive functioning.

Most cited protocols related to «Attention»

1
UK Biobank Genotyping Protocol
Ethics approval for the UK Biobank study was obtained from the North West Centre for Research Ethics Committee (11/NW/0382). Blood samples were collected from participants on their visit to a UK Biobank assessment centre and the samples are stored at the UK Biobank facility in Stockport, UK7 (link). Over a period of 18 months samples were retrieved, DNA was extracted, and 96-well plates of 94 × 50-μl aliquots were shipped to Affymetrix Research Services Laboratory for genotyping. Special attention was paid in the automated sample retrieval process at UK Biobank to ensure that experimental units such as plates or timing of extraction did not correlate systematically with baseline phenotypes such as age, sex, and ethnic background, or the time and location of sample collection. Full details of the UK Biobank sample retrieval and DNA extraction process were described previously34 (link).
On receipt of DNA samples, Affymetrix processed samples on the GeneTitan Multi-Channel (MC) Instrument in 96-well plates containing 94 UK Biobank samples and two control samples from the 1000 Genomes Project25 (link). Genotypes were then called from the array intensity data, in units called ‘batches’ which consist of multiple plates. Across the entire cohort, there were 106 batches of 4,700 UK Biobank samples each (Supplementary Information, Supplementary Table 12). Following the earlier interim data release, Affymetrix developed a custom genotype calling pipeline that is optimized for biobank-scale genotyping experiments, which takes advantage of the multiple-batch design35 . This pipeline was applied to all samples, including the 150,000 samples that were part of the interim data release. Consequently, some of the genotype calls for these samples may differ between the interim data release and this final data release (see below).
Routine quality checks were carried out during the process of sample retrieval, DNA extraction36 , and genotype calling37 . Any sample that did not pass these checks was excluded from the resulting genotype calls. The custom-designed arrays contain a number of markers that had not been previously typed using Affymetrix genotype array technology. As such, Affymetrix also applied a series of checks to determine whether the genotyping assay for a given marker was successful, either within a single batch, or across all samples. Where these newly attempted assays were not successful, Affymetrix excluded the markers from the data delivery (see Supplementary Information for details).
Bycroft C., Freeman C., Petkova D., Band G., Elliott L.T., Sharp K., Motyer A., Vukcevic D., Delaneau O., O’Connell J., Cortes A., Welsh S., Young A., Effingham M., McVean G., Leslie S., Allen N., Donnelly P, & Marchini J. (2018). The UK Biobank resource with deep phenotyping and genomic data. Nature, 562(7726), 203-209.
Publication 2018
Attention Biological Assay BLOOD Ethics Committees, Research Ethnicity Genome Obstetric Delivery Phenotype Specimen Collection
2
Housekeeping Gene Selection for qPCR
Primer and probe sequences are shown in table 2. These were synthesised by Applied Biosystems and included both customised primer and probe sets, designed via the Applied Biosystems Primer Express™ 2.0 software as well as pre-designed, gene-specific TaqMan® probe and primer sets (TaqMan® Gene Expression Assays, Applied Biosystems). Primers were used at 300 nM and probes at 200 nM in a 25 μl reaction. A selection of housekeeping genes were chosen, paying close attention to selecting genes that belong to different functional classes. This was aided by information provided by the human gene expression index database (HuGE) [21 (link)]. This was used to assess expression, variability and reproducibility of potential housekeeping genes.
Silver N., Best S., Jiang J, & Thein S.L. (2006). Selection of housekeeping genes for gene expression studies in human reticulocytes using real-time PCR. BMC Molecular Biology, 7, 33.
Publication 2006
Attention Biological Assay Gene Expression Genes Genes, Housekeeping Homo sapiens Oligonucleotide Primers
3
Transcript Quantification from RNA-seq
The initial step of an analysis is the alignment of the sequencing reads to the genome. Here, it is important to use a tool capable of properly handling reads that straddle introns. Then, transcriptome annotation with coordinates of exon boundaries is required. For model organisms, reference gene model databases as provided, e.g., by Ensembl (Flicek et al. 2011 (link)), may be used. In addition, such a reference may be augmented by information retrieved from the RNA-seq data set that is being studied. Garber et al. (2011) (link) review tools for the above tasks.
The central data structure for our method is a table that, in the simplest case, contains for each exon of each gene the number of reads in each sample that overlap with the exon. Special attention is needed, however, if an exon’s boundary is not the same in all transcripts. In such cases, we cut the exon in two or more parts (Fig. 1). We use the term “counting bin” to refer to exons or parts of exons derived in this manner. Note that a read that overlaps with several counting bins of the same gene is counted for each of these.
Anders S., Reyes A, & Huber W. (2012). Detecting differential usage of exons from RNA-seq data. Genome Research, 22(10), 2008-2017.
Publication 2012
Attention Exons Genes Genome Introns RNA-Seq Sequence Alignment Transcriptome
4
Consensus Criteria for PET-Based Treatment Response
Selected articles obtained using Internet search tools, including PubMed and syllabi from meetings (e.g., Clinical PET and PET/CT syllabus, Radiological Society of North America, 2007), were identified. Publications resulting from database searches and including the main search terms RECIST, positron, FDG, ROI (region of interest), cancer, lymphoma, PET, WHO, and treatment response were included. The search strategy for relevant 18F-FDG PET studies articulated by Mijnhout et al. was also applied (34 (link),35 (link)). These were augmented by key references from those studies, as well as the authors' own experience with PET assessments of treatment response, informal discussions with experts on PET treatment response assessment, and pilot evaluations of clinical data from the authors' clinical practice. Limitations and strengths of the anatomic and functional methods to assess treatment response were evaluated with special attention to studies that had applied qualitative or quantitative imaging metrics, had determined the precision of the method, and had histologic correlate or outcome data available. On the basis of these data, proposed treatment response criteria including PET were formulated, drawing from both prior anatomic models (notably WHO, RECIST, and RECIST 1.1) and the EORTC PET response draft criteria (36 (link)). These conclusions were based on a consensus approach among the 4 authors. Thus, a systematic review and a limited Delphilike approach augmented by key data were undertaken to reach consensus in a small group. For demonstration purposes, 18F-FDG PET scans obtained at our institution on 1 of 2 GE Healthcare PET/CT scanners were analyzed with several tools, including a tool for response assessment.
Wahl R.L., Jacene H., Kasamon Y, & Lodge M.A. (2009). From RECIST to PERCIST: Evolving Considerations for PET Response Criteria in Solid Tumors. Journal of nuclear medicine : official publication, Society of Nuclear Medicine, 50(Suppl 1), 122S-150S.
Publication 2009
Attention CAT SCANNERS X RAY F18, Fluorodeoxyglucose Lymphoma Malignant Neoplasms Positron-Emission Tomography Radiography Scan, CT PET
5
Automated Prokaryotic Genome Annotation Pipeline
In addition to identifying structural components and establishing functional identification, PGAP produces reports in a wide variety of formats used by curators, submitters, as well as internal submission tools. Included in the reports produced are: (i) the primary annotated genome objects, represented in NCBI's ASN.1 data model and suitable for direct submission into GenBank; (ii) a report on annotation markup discrepancies requiring submitter or curator attention; (iii) genome annotation in GenBank flat file format ready for manual review and public display; and (iv) statistics from the annotation process along with citation of supporting evidence for each gene model. Concomitant with the ASN.1 markup produced in PGAP, we record the evidence selected for each model to support the selection of the specific start/stop site as well as evidence used to support the functional identification of each inferred object (e.g. Figure 6).
In recent years NCBI, in conjunction with INSDC, has developed validation procedures designed to ensure that the new records represent biologically valid and consistently formatted data. These quality control (QC) procedures have been incorporated into the PGAP pipeline. The quality of annotation of a prokaryotic genome can be assessed by several metrics. In an effort to develop standards for prokaryotic genome annotation, NCBI has established a collaboration with other major archive databases and major sequencing centers. This collaboration resulted in a set of annotation standards approved and accepted by all major annotation pipelines (20 (link)). Genome annotation should follow INSDC submission guidelines (GenBank/ENA/DDBJ), https://www.ncbi.nlm.nih.gov/genbank/genomesubmit/.
In addition to the standards for genomes mentioned above, PGAP implements rules defining complete genome annotation. Minimally complete annotation must contain the following genes with locus-tags: (i) at least one copy of rRNAs genes (5S, 16S, 23S); (ii) at least one copy of tRNAs for each amino acid; and (iii) for all protein coding genes with a corresponding CDS, protein naming should follow UniProt guidelines available at http://www.uniprot.org/docs/proknameprot.
The annotation process in PGAP incorporates multiple QC checks within the annotation pipeline itself. Results of these QC metrics are made available to curators and are used in automated decisions to accept or reject annotation based on quality standards. For GenBank submission, quality requirements are permissive to allow the majority of genome annotations to pass; only annotations with serious quality problems are filtered out. For RefSeq submission, rules are stricter, permitting RefSeq to represent a more trusted set of annotation of higher quality genomes.
Tatusova T., DiCuccio M., Badretdin A., Chetvernin V., Nawrocki E.P., Zaslavsky L., Lomsadze A., Pruitt K.D., Borodovsky M, & Ostell J. (2016). NCBI prokaryotic genome annotation pipeline. Nucleic Acids Research, 44(14), 6614-6624.
Publication 2016
Amino Acids Attention Genes Genome Prokaryotic Cells Proteins Ribosomal RNA Genes Staphylococcal Protein A Transfer RNA

Most recents protocols related to «Attention»

1
Biochemical Markers for Alcohol Use
Not available on PMC !

Example 22

Clinicians can use several biochemical measurements to objectively assess patients' current or past alcohol use. Several more experimental markers hold promise for measuring acute alcohol consumption and relapse. These include certain alcohol byproducts, such as acetaldehyde, ethyl glucuronide (EtG), and fatty acid ethyl esters (FAEE), as well as two measures of sialic acid, a carbohydrate that appears to be altered in alcoholics (Peterson K, Alcohol Research and Health, 2005). Clinicians have had access to a group of biomarkers that indicate a person's alcohol intake. Several of these reflect the activity of certain liver enzymes: serum gamma-glutamyltransferase (GGT), aspartate aminotransferase (AST), alanine aminotransferase (ALT), and carbohydrate-deficient transferrin (CDT), a protein that has received much attention in recent years. Another marker, N-acetyl-β-hexosaminidase (beta-Hex), indicates that liver cells, as well as other cells, have been breaking down carbohydrates, which are found in great numbers in alcohol (Javors and Johnson 2003).

In some embodiments the disclosed device focuses on detecting markers associated with alcohol abuse from menstrual blood or cervicovaginal fluid.

US11864740B2. Sample collection and preservation devices, systems and methods (2024-01-09). NextGen Jane, Inc. [US]. Inventors: Ridhi Tariyal [US], Stephen K. Gire [US].
Patent 2024
Abuse, Alcohol Acetaldehyde Alcoholics Aspartate Transaminase Attention beta-N-Acetylhexosaminidase Biological Markers BLOOD carbohydrate-deficient transferrin Carbohydrates Cells D-Alanine Transaminase enzyme activity Esters Ethanol ethyl glucuronide Fatty Acids gamma-Glutamyl Transpeptidase Hepatocyte Liver Medical Devices Menstruation N-Acetylneuraminic Acid Patients Relapse Serum Staphylococcal Protein A
2
Comprehensive Assessment of Depression
Questionnaires will be completed through a secure, web-based survey system hosted by the research centre so that participants can complete questionnaires electronically, either at home or during their visit to the research centre. Online questionnaires are sent via a national secure mail platform used by citizens in regular correspondence with public institutions and the health care system.
Measures include several salient domains in the clinical characterisation of the patient, among others, assessments of demographics (e.g., ethnicity, education, and marital status); medical and psychiatric history; depressive symptoms and impact of depression behaviour and day-to-day life; treatment preferences and expectations, life experiences; and a broad range of state and trait psychometrics. Some questionnaires will only be given to patients in subcohorts I-II (Table 2).

Questionaries Additional questionnaires for the subcohort I-II only are in bold

Symptom profile and SeverityCognitive styleUpbringing and life historyFunctioning and quality of life
Inventory of Depressive Symptomatology – self-report (IDS-SR) [34 (link)]Mentalisation Questionnaire (MZQ) [35 (link)]Online Stimulant and Family History Assessment Module (OS-FHAM) [11 (link)]Cognitive Complaints in Bipolar Disorder Rating Assessment (COBRA) [36 (link)]
Dimension of Anger Reactions (DAR-5) [37 (link)]Ruminative Response Scale (RRS) [38 (link)]Child abuse and trauma scale (CATS) [39 (link)]Modified Sheehan Disability Score (mSDS)
Generalised Anxiety Disorder 7-item (GAD-7) [40 (link)]Perth Alexithymia Questionnaire (PAQ) [41 (link)]Parental Bonding Instrument (PBI) [42 (link)]WHO 5 wellbeing index (WHO-5)
Cohen's Perceived Stress Scale (PSS) [43 (link)]Mindful Attention Awareness Scale (MAAS) [44 (link)]Stressful Life Events (SLE) [45 (link)]Changes in Sexual Functioning Questionnaire (CSFQ) [46 (link)]
Brief Symptom Inventory (BSI) [47 (link)]Short form of Metacognitions Questionnaire (MCQ-30) [48 (link)]Questions from the Copenhagen Aging and Midlife Biobank (CAMB) [49 (link)]
Symptom checklist (SCL-10) [50 (link)]Coping Self-Efficacy Scale (CSES) [51 (link)]Revised Sociosexual Orientation Inventory (SOI-R) [52 (link)]
Snaith-Hamilton Pleasure Scale (SHAPS) [53 (link)]
Pittsburgh Sleep Quality Index (PSQI) [54 (link)]
Jensen K.H., Dam V.H., Ganz M., Fisher P.M., Ip C.T., Sankar A., Marstrand-Joergensen M.R., Ozenne B., Osler M., Penninx B.W., Pinborg L.H., Frokjaer V.G., Knudsen G.M, & Jørgensen M.B. (2023). Deep phenotyping towards precision psychiatry of first-episode depression — the Brain Drugs-Depression cohort. BMC Psychiatry, 23, 151.
Publication 2023
Abuse, Child Alexithymia Anger Anxiety Disorders Attention Awareness Cognition Disorders Depressive Symptoms Disabled Persons Ethnicity Life Experiences Mentalization Metacognition Mindfulness Parent Patients Pleasure Psychometrics Rumination, Digestive Wounds and Injuries
3
Measuring Cognitive Functions with WMS-R
Cognitive functions were assessed using the Wechsler Memory Scale – Revised (WMS-R) [12 ]. The test was administered during a routine visit to the general practitioner and it required around 1 h to complete. The WMS-R is a neuropsychological test designed to measure different memory functions such as verbal, visual memory, attention/concentration and delayed memory. The psychometric characteristics of the WMS-R are evaluated and related to its clinical utility in the Romanian population [13 , 14 (link)]. The weighted scores (weighted raw score summaries) were calculated according to the scoring system from in the WMS-R administrative and scoring manual, with a higher score indicating better functioning.
Kálcza Jánosi K, & Lukács A. (2023). Independent and interactive effect of type 2 diabetes and hypertension on memory functions in middle aged adults. BMC Endocrine Disorders, 23, 59.
Publication 2023
Attention Cognition Delayed Memory Memory Neuropsychological Tests Psychometrics Vision
4
Domestic Abuse Narratives and Homelessness
Repeated experiences of domestic abuse were apparent in the biographies of almost all women though it was not always perceived as such. Relationships were often idealised in the first few months then quickly descended into abuse:

You think you find the right person, you think they’re so nice and everything’s perfect for the first 6 to 12 months and then after 12 months it just goes pfffft. Like woah. And by the time that’s happened you’re just too far involved. And then you end up the one that’s out on the street (Rosa).

One of the most harmful aspects of domestic abuse is detachment from social networks, thus further deepening exclusion. Here, Sally describes being isolated her from family and friends and eventually her children: Nobody knew what was going on. So I eventually left, and unknown to me … I was made out to be the bad person, like a complete weirdo (Sally).
Several women described long term physical and mental health impact resulting from injuries caused by their partner. Dee was using heroin to manage chronic pain caused by physical injuries as well as trauma from abuse: “I was married once. And I’d never do it again. He was a woman batterer. Steel plate in my head. He was so violent” (Dee).
Other women described how their partner provided resources but also perpetuated further trauma:

he used to say “you’ve got nobody. You’ll never go hungry if you stay with me...” And it’s just hard like. I struggle every day. So it’s like I’m either, it’s easier for food, I’d get lifts if I needed to go to places or I’m not being with that person and struggle. Erm, but not arguing and not fighting. It’s just hard (Sienna).

Michelle describes how her relationship commands a lot of her attention and energy, with expressions of affection interspersed with mental turmoil and uncertainty:

Me partner who lives with me, [name], he’s really well known here. He got kicked out of a hostel a while ago and that’s how I met him... he’s playing us [me] along saying he loves me and wants to be with me, and it’s ripping me to bits, my head’s battered. … he doesn’t have a good word for us. Constantly puts us down. I don’t know. But he walked away a couple of month ago when he got paid, spent £750 left me with not a penny and went away for a week and come back when he had nothing. I knew then, he didn’t love me. No-one who loved someone would do that to them. You know. I couldn’t see the lad on the streets, I just couldn’t (Michelle).

Amongst the women who had exited homelessness, many chose to live alone: “I mean I just don’t intend getting into a relationship to discover how to have one. I’m done. I’ve had enough bad ones. I’ve loved, and I’ve been loved back a couple of times. But it hurts even harder when they’re the ones that try to kill you” (Tracy).
Most of the women who had successfully exited homelessness actively avoided situations where they might meet a new partner and expressed no desire for intimate relationships. This perhaps relates to not only their overwhelmingly bad experiences of relationships, but provides context to their perception of relationships primarily driven by necessity to obtain shelter, protection and resources.
McGrath J., Crossley S., Lhussier M, & Forster N. (2023). Social capital and women’s narratives of homelessness and multiple exclusion in northern England. International Journal for Equity in Health, 22, 41.
Publication 2023
Attention Child Chronic Pain Drug Abuse ErbB Receptors Food Friend Head Heroin Hunger Injuries Mental Health Physical Examination Rosa Steel Woman Wounds Wounds and Injuries
5
Assessing Cognitive Function with MMSE
The Mini-Mental State Examination (MMSE) was used to assess global cognition [60 ]. It consists of 30 brief questions (verbal and pen/paper based) which are designed to measure a range of cognitive domains including attention and concentration, memory, language, visuo-constructional skills, calculations and orientation. The MMSE took approximately 5 min to administer. A score (out of 30) based on performance across the 11 components of the test (orientation to time, orientation to place, registration, attention and calculation, recall, naming, repetition, comprehension, reading, writing and drawing) was calculated for each participant. Total scores ranged between 0 and 30, with lower scores indicative of more severe cognitive impairment and scores of 25 or over indicating no cognitive impairment.
Neville C.E., Young I.S., Kee F., Hogg R.E., Scott A., Burns F., Woodside J.V, & McGuinness B. (2023). Northern Ireland Cohort for the Longitudinal Study of Ageing (NICOLA): health assessment protocol, participant profile and patterns of participation. BMC Public Health, 23, 466.
Publication 2023
Attention Cognition Disorders, Cognitive Memory Mental Recall Mini Mental State Examination

Top products related to «Attention»

1
Matlab by MathWorks
Sourced in United States, United Kingdom, Germany, Canada, Japan, Sweden, Austria, Morocco, Switzerland, Australia, Belgium, Italy, Netherlands, China, France, Denmark, Norway, Hungary, Malaysia, Israel, Finland, Spain
MATLAB is a high-performance programming language and numerical computing environment used for scientific and engineering calculations, data analysis, and visualization. It provides a comprehensive set of tools for solving complex mathematical and computational problems.
2
Presentation software by Neurobehavioral Systems
Sourced in United States, Canada, Japan
Presentation software is a computer program designed to create and display visual presentations. It allows users to organize and present information, such as text, images, and multimedia, in a structured format. The core function of this software is to facilitate the creation and display of digital slides or pages that can be used for various purposes, including business meetings, educational lectures, and public speaking events.
3
E prime 2 by Psychology Software Tools
Sourced in United States, Panama
E-Prime 2.0 is a software suite designed for creating and running psychological experiments. It provides a comprehensive set of tools for designing, presenting, and collecting data from a variety of studies. The core function of E-Prime 2.0 is to facilitate the creation and execution of psychological experiments, enabling researchers to collect accurate and reliable data for their research.
4
Sas 9 by SAS Institute
Sourced in United States, Austria, Japan, Belgium, United Kingdom, Cameroon, China, Denmark, Canada, Israel, New Caledonia, Germany, Poland, India, France, Ireland, Australia
SAS 9.4 is an integrated software suite for advanced analytics, data management, and business intelligence. It provides a comprehensive platform for data analysis, modeling, and reporting. SAS 9.4 offers a wide range of capabilities, including data manipulation, statistical analysis, predictive modeling, and visual data exploration.
5
Sas version 9 by SAS Institute
Sourced in United States, Austria, Japan, Cameroon, Germany, United Kingdom, Canada, Belgium, Israel, Denmark, Australia, New Caledonia, France, Argentina, Sweden, Ireland, India
SAS version 9.4 is a statistical software package. It provides tools for data management, analysis, and reporting. The software is designed to help users extract insights from data and make informed decisions.
6
Spss version 22 by IBM
Sourced in United States, Japan, United Kingdom, Austria, Germany, Czechia, Belgium, Denmark, Canada
SPSS version 22.0 is a statistical software package developed by IBM. It is designed to analyze and manipulate data for research and business purposes. The software provides a range of statistical analysis tools and techniques, including regression analysis, hypothesis testing, and data visualization.
7
E prime software by Psychology Software Tools
Sourced in United States
E-Prime is a software package designed for developing and running psychological experiments. It provides a comprehensive set of tools for creating, presenting, and collecting data from a variety of experimental paradigms. The software is primarily used in research settings by psychologists, cognitive scientists, and other behavioral researchers.
8
E prime by Psychology Software Tools
Sourced in United States
E-Prime is a software package for designing and running psychological experiments. It provides tools for creating, presenting, and collecting data from a variety of experiment types. E-Prime supports the integration of hardware devices and the creation of complex experimental paradigms.
9
Spss version 25 by IBM
Sourced in United States, United Kingdom, Japan, Austria, Germany, Denmark, Czechia, Belgium, Sweden, New Zealand, Spain
SPSS version 25 is a statistical software package developed by IBM. It is designed to analyze and manage data, providing users with a wide range of statistical analysis tools and techniques. The software is widely used in various fields, including academia, research, and business, for data processing, analysis, and reporting purposes.

More about "Attention"

Attention is the cognitive process of selectively focusing on specific stimuli or information while filtering out other irrelevant details.
This essential component of human cognition enables us to concentrate our mental resources on relevant tasks and make informed decisions.
The study of attention has yielded valuable insights into the neurological and psychological mechanisms underlying these attentional processes, with applications across various fields, including psychology, neuroscience, and cognitive science.
Attention plays a crucial role in perception, memory, and higher-order cognitive functions.
Researchers have utilized tools like MATLAB, Presentation software, E-Prime 2.0, SAS 9.4, and SPSS version 22.0 to investigate the complexities of attention and its impact on human performance.
By understanding the intricacies of attentional processes, we can unlock new avenues for enhancing cognitive functioning and optimizing human capabilities.
The concept of attention encompasses a range of related terms, such as focus, concentration, vigilance, and selective processing.
These terms describe the ability to maintain focus on specific information or tasks while filtering out distractions.
The research in this field has shed light on the neurological mechanisms underlying attention, including the role of brain regions like the prefrontal cortex, parietal cortex, and thalamus.
Enhancing attention and cognitive control can have far-reaching benefits, from improving academic and professional performance to optimizing decision-making and problem-solving skills.
By leveraging the insights gained from tools like E-Prime software, SPSS version 25, and SAS version 9.4, researchers can unlock new strategies for improving attention and unlocking human potential.