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The only way to access the
consumer decision-making process
test
The only way
to access the consumer
decision-making process
Functional Magnetic Resonance Imaging (fMRI) allows us to observe the entire brain, from cortical areas to deep subcortical nuclei. This technique provides a unique window into regions critically involved in reward processing, reinforcement learning, and action selection, helping us understand the neural mechanisms that underlie human decisions.
Accelerating success across industries
From brain insights
to market impact
We minimise launch risks and maximise success by aligning your innovations with consumer expectations.
Predict Market Success
Anticipate consumer choices and strengthen brand attachment by decoding unconscious decision-making processes.
Fall Less, Win More
Invest more securely in R&D by identifying winning concepts early and cutting failures to drive product success.
Strengthen Brand Attachment
Reveal hidden consumer engagement through brain decoding and turn it into lasting brand attachment.
Different techniques, one goal
Contrast analysis in fMRI involves statistically comparing brain responses across conditions (e.g., A vs. B) to identify regions with significantly different hemodynamic activity.
RS-fMRI measures spontaneous brain activity at rest, typically before and after a task or stimulation. It enables assessment of intrinsic functional connectivity and long-lasting effects of interventions, allowing testing of various products or conditions outside the MRI
By combining fMRI with neurotransmitter concentration maps, we can identify brain regions where spontaneous neural activity correlates with key chemical signals, such as dopamine, serotonin, or GABA. This approach provides valuable insights for cosmetics, helping to link formulations with their potential impact on the brain’s chemical activity and overall user experience
Functional connectivity shows which regions interact, the strength and direction of these interactions, and changes in communication efficiency. Mapping these circuits reveals information flow, identifies pathways driving decisions, and measures how interventions strengthen or weaken specific connections, providing actionable insights.
What you get
Data collection
Gathering raw behavioral, contextual, and other relevant data to your goals.
Signal Processing
Structuring and cleaning the data to prepare it for analysis.
Feature extraction
Identifying key variables and patterns that drive behavior.
Model Development
Building and training deep learning models on the extracted features.
LLM integration
Embedding insights into a Large Language Model (LLM) for natural language interaction.