Neuropsychological model of the realization of information need

Moshfeghi, Yashar; Pollick, Frank E.

doi:10.1002/asi.24242

Cited by 16 publications

(13 citation statements)

References 65 publications

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“… Day (2010) explored the effectiveness of applying the Needleman–Wunsch algorithm in identifying decision-making strategies using eye movement data. Moshfeghi and Pollick (2019) analyzed consumer demand for information retrieval and discovered brain regions related to inform decision-making through brain activity-related data. This study aims to understand consumers’ demand for information.…”

Section: Resultsmentioning

confidence: 99%

Roles and Research Trends of Neuroscience on Major Information Systems Journal: A Bibliometric and Content Analysis

Lin

Chen²,

Jiang³

et al. 2022

Front. Neurosci.

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Over the past decade, neuroscience has been integrated into information systems as a new methodology and perspective to study and solve related problems. Therefore, NeuroIS has emerged as a new cutting-edge research field. This review aimed to identify, summarize, and classify existing NeuroIS publications through knowledge mapping and bibliometric analysis. To effectively understand the development trend of NeuroIS, this study referred to the journal selection index of the Association of Business Schools in 2021 and journals above three stars in the field of information management as the main selection basis. A total of 99 neuroscience papers and their citation data were included from 19 major information systems journals of SCI/SSCI. This study analyzed bibliometric data from 2010 to 2021 to identify the most productive countries, universities, authors, journals, and prolific publications in NeuroIS. To this end, VOSviewer was used to visualize mapping based on co-citation, bibliographic coupling, and co-occurrence. Keywords with strong citation bursts were also identified in this study. This signifies the evolution of this research field and may reveal potential research directions in the near future. In selecting research methods and analysis tools for NeuroIS, content analysis was used to further conclude and summarize the relevant trends. Moreover, a co-citation network analysis was conducted to help understand how the papers, journals, and authors in the field were connected and related, and to identify the seminal or pioneering major literature. For researchers, network maps visualized mainstream research and provided a structural understanding of NeuroIS. The review concludes by discussing potential research topics in this field.

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Section: Resultsmentioning

confidence: 99%

Roles and Research Trends of Neuroscience on Major Information Systems Journal: A Bibliometric and Content Analysis

Lin

Chen²,

Jiang³

et al. 2022

Front. Neurosci.

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“…A rise in adoption of neuroimaging techniques across the key areas of IS&R resulted in numerous NeuraSearch applications with the most notable being relevance judgment [46,47], IN realisation [20], search transitions [23] or query construction [48]. Commonly used neuroimaging techniques include electroencephalography (EEG) [46,[48][49][50][51][52], functional magnetic resonance imaging (fMRI) [20,22,49], magnetoencephalography (MEG) [53], functional Near Infrared Spectroscopy (fNIRS) [54,55]. The EEG studies manifested the effectivity of EEG to capture the brain activities of complex cognitive processes utilising its fine-grained temporal resolution.…”

Section: Relevant Workmentioning

confidence: 99%

“…To tackle this problem, new research has emerged employing neuroimaging techniques to directly monitor brain activity of subjects experiencing a realisation of IN [20][21][22]. This research has led to a discovery of cognitive processes and brain regions associated with the realisation of IN [22,23]. However, these studies have used fMRI technique which has a high spatial, but low temporal resolution.…”

Section: Introductionmentioning

confidence: 99%

Information Need Awareness

Michalkova

Parra

Moshfeghi

2022

Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval

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A fundamental goal of Information Retrieval (IR) is to satisfy search/ers' information need (IN). Advances in neuroimaging technologies have allowed for interdisciplinary research to investigate the brain activity associated with the realisation of IN. While these studies have been informative, they were not able to capture the cognitive processes underlying the realisation of IN and the interplay between them with a high temporal resolution. This paper aims to investigate this research question by inferring the variability of brain activity based on the contrast of a state of IN with the two other (no-IN) scenarios. To do so, we employed Electroencephalography (EEG) and constructed an Event-Related Potentials (ERP) analysis of the brain signals captured while participants experiencing a realisation of IN. In particular, the brain signals of 24 healthy participants were captured while performing a Question-Answering (Q/A) Task. Our results show a link between the early stages of processing, corresponding to awareness and the late activity, meaning memory control mechanisms. Our findings also show that participants exhibited early N1-P2 complex indexing awareness processes and indicate, thus, that the realisation of IN is manifested in the brain before it reaches the user's consciousness. This research contributes novel insights into a better understanding of IN and informs the design of IR systems to better satisfy it.

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“…A collection of fMRI studies by Moshfeghi and colleagues (Moshfeghi et al, 2013, 2016; Moshfeghi & Pollick, 2019, 2018; Moshfeghi, Triantafillou, & Pollick, 2019) has focused on using fMRI to understand the brain regions activated during relevance judgment and IN. Results from one study (Moshfeghi et al, 2013) revealed the brain regions that are activated during the relevance judgment process.…”

Section: Related Workmentioning

confidence: 99%

Neural Correlates of Realisation of Satisfaction in a Successful Search Process

Paisalnan

Moshfeghi

Pollick

2021

Proceedings of the Association for Information Science and Tech

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In a search process, searchers review documents to gather information relevant to their information need (IN). During this process, searchers may experience the satisfaction of their IN, indicating they have gathered adequate relevant information to answer their need. This complex concept of satisfaction is the ultimate goal of search systems. Most studies in Information Retrieval (IR) have been attempted to understand how searchers' needs are satisfied based on behavioural observation. However, the psychophysiological manifestation during the moment of satisfaction still remains unclear. Here, we use functional Magnetic Resonance (fMRI) to investigate which brain regions are involved during the moment of satisfaction. Twenty-six participants participated in the experiment, designed to represent a search process while being scanned. Our result shows the human brain regions involved during the moment of satisfaction. These findings provide an important step in unravelling the concept of satisfaction in a search process.

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Neuropsychological model of the realization of information need

Cited by 16 publications

References 65 publications

Roles and Research Trends of Neuroscience on Major Information Systems Journal: A Bibliometric and Content Analysis

Roles and Research Trends of Neuroscience on Major Information Systems Journal: A Bibliometric and Content Analysis

Information Need Awareness

Neural Correlates of Realisation of Satisfaction in a Successful Search Process

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