biology

Neuro-Information-Systems

Neuro-Information-Systems is a biology topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Neuro-Information-Systems rather than just read about it. In short: Neuro-Information-Systems (NeuroIS) is a subfield of the information systems (IS) discipline, which relies on neuroscience and neurophysiological knowledge and tools to better understand the development, use, and impact of information and communication technologies. The field has been formally established at the International Conference on Information Systems (ICIS) in 2007.

Key takeaways

Neuro-Information-Systems belongs to biology; place it in that map before memorising details.
Learn the definition first, then one example that makes the definition concrete.
Connect Neuro-Information-Systems to a quantity you can measure, compute or draw — that is where exam questions come from.
Reproduce the core statement of Neuro-Information-Systems from memory before moving on to harder problems.

Reference excerpt

Neuro-Information-Systems (NeuroIS) is a subfield of the information systems (IS) discipline, which relies on neuroscience and neurophysiological knowledge and tools to better understand the development, use, and impact of information and communication technologies. The field has been formally established at the International Conference on Information Systems (ICIS) in 2007.

Aims and scope Research evidence supports the idea that human behavior is influenced by individual factors (e.g., genetic predisposition) and environmental factors. These influences affect the brain (e.g., its structure and processing mechanisms) which subsequently impacts the way in which information is processed. By acknowledging this relationship of individual characteristics (e.g., experiences with e-commerce platforms that have led to changes in the brain due to learning processes), environmental influences (e.g., characteristics of an IT artifact such as the usability of an e-commerce platform) and human behavior (e.g., purchasing behavior in an e-commerce context), NeuroIS seeks to understand the internal processes that are involved in the formation of human behavior related to information systems. By applying theories and tools from neuroscience and related fields, NeuroIS strives to make a number of important contributions, including but not limited to:

Inform the design of IT artifacts and IS investigations in general Introduce a biological level of analysis as mediator between IT artifact and IT behavior Shed light on theoretical mechanisms underlying the influence of the IT artifact on IT behavior Offer additional avenues for IT artifact evaluation (e.g., using brain activity) Enable the measurement of constructs that cannot be reliably measured using self-report techniques (e.g., questionnaires, interviews) Offer additional predictive power for certain outcome variables (e.g., user health) Enable investigations into how physiology (e.g., brain structure) is affected by the use of IT artifacts Offer additional input for adaptive systems (e.g., based on real-time assessments of physiological well-being) Offer additional input for users to reflect on their behavior (e.g., biofeedback) Offer additional input for human-computer interaction (e.g., brain-computer interfaces for physically-impaired individuals) Applying theories and tools from neuroscience, NeuroIS also draws from other reference disciplines and shares a close connection with sister disciplines that have also added these theories and instruments to their set of methods. Reference disciplines and sister disciplines for NeuroIS include, but are not limited to:

Neuropyschology and Cognitive Neuroscience Neuroeconomics, Decision Neuroscience and Social Neuroscience Neuromarketing and Consumer Neuroscience Neuroergonomics Affective Computing and Brain-Computer Interaction

Data collection methods Two commonly used types of neurophysiological data collection methods are applied in NeuroIS research:

Psychophysiological tools that focus on the capture of activity related to the autonomic nervous system and Brain imaging tools that focus on the capture of activity in the central nervous system.

Psychophysiological tools The most commonly used psychophysiological tools in NeuroIS include the measurement of eye gaze behavior and pupil dilation (eye tracking), the measurement of electrodermal activity (skin conductance response), the measurement of muscular activity (electromyography) and the measurement of heart-related activity (electrocardiogram).

Brain imaging tools The main brain imaging tools that are used in NeuroIS include functional magnetic resonance imaging (fMRI) and Electroencephalography (EEG).

Conferences and groups Since 2009 an annual conference is taking place in Austria to support NeuroIS research. From 2009 to 2017 this conference has been called the Gmunden Retreat on NeuroIS and took place in Gmunden, Austria. Since 2018, it is being called the NeuroIS Retreat and takes place in Vienna, Austria. In 2018, a society called the NeuroIS Society has been founded in Austria to further support the growth of the field and the collaboration amongst NeuroIS researchers.

References

Worked examples

Example 1 — a first encounter with Neuro-Information-Systems

Start with the simplest possible case. Write down what Neuro-Information-Systems claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In biology, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Neuro-Information-Systems before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Neuro-Information-Systems ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Neuro-Information-Systems

In research: Neuro-Information-Systems appears in biology research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry: Engineering practice reuses Neuro-Information-Systems in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom: Neuro-Information-Systems is common in secondary-school and first-year university syllabi. It links to neighbouring topics Information systems, so understanding it makes those chapters shorter.
In everyday life: Look for Neuro-Information-Systems outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study Neuro-Information-Systems in 20 minutes

Read the reference excerpt below once, without taking notes.
Close the page and write down what Neuro-Information-Systems means in your own words.
Compare your version with the excerpt and mark what you missed.
Work through the three examples above with pen and paper.
Explain Neuro-Information-Systems out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Neuro-Information-Systems in simple terms?

Why does Neuro-Information-Systems matter?

Because it connects several biology ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Neuro-Information-Systems?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Neuro-Information-Systems.