Connectome records physiological measurements, not subjective scales. We use a non-invasive neuroimaging device that measures changes in oxygenated blood flow in the cortex (the top surface of the brain).

Connectome images the brain using Time-Domain functional Near-Infrared Spectroscopy (TD-fNIRS). This allows us to measure how the brain is functioning during specific cognitive tasks by tracking changes in cortical oxygenated blood flow, giving a physiological view of functional brain activity over time.

We measure changes in oxygenated blood flow across cortical regions, primarily in the prefrontal cortex. This area is involved in executive functions such as attention, working memory, and cognitive flexibility. The result is a signal of how the brain is activating under specific cognitive conditions.

We translate physiological signals into meaningful insights through three layers. First, we map how brain activity changes under specific conditions. Second, we build an individual's baseline by tracking how their brain activity changes over time. Third, we combine these measurements with contextual lifestyle information synced from wearables, such as sleep and activity, to explain the contributing factors linked to changes in an individual's brain activity.

We do not provide raw neuroimaging signals to the end user. Instead, we generate interpretable functional metrics — attentional control, working memory, and cognitive flexibility — designed to be stable within individuals and sensitive to change over time. Unlike cognitive testing, which focuses on performance outcomes, Connectome measures how the brain is functioning during those tasks.

Rating scales are subjective and can vary based on mood, perception, bias, or expectations. Connectome provides an objective physiological signal, giving clinicians and patients a more concrete and repeatable way to track change over time.

Wearables measure indirect signals such as heart rate, sleep, or activity and infer cognitive state from those proxies. Connectome measures the brain directly, then links those signals to broader behavioural or physiological data, which helps create a more grounded and personalised picture.

No. Connectome is not a diagnostic tool and is not intended to detect, classify, or rule out disease. It is designed to measure functional brain performance over time and support clinical interpretation, not replace diagnostic tools such as MRI or EEG.

MRI and EEG provide structural or electrical information, often as a snapshot at a single point in time. Connectome adds a functional, task-based, and longitudinal layer by showing how the brain is operating and changing over time. It is complementary rather than substitutive.

No, and that is not the goal. EEG serves diagnostic purposes in specific clinical contexts, whereas Connectome is designed for monitoring and understanding change within an individual over time.

The system is built on validated fNIRS hardware, established neuroscience methods, and ongoing longitudinal research. That said, it is not positioned as a regulated diagnostic tool, so outputs should be used as supportive functional insights rather than definitive clinical conclusions.

These markers are derived from physiological brain signals captured during structured tasks and translated into repeatable functional measures. Validation focuses on whether these outputs are stable within individuals, sensitive to change over time, and aligned with established neuroscience methods, rather than being treated as standalone diagnostic labels.

Connectome tracks three validated functional measures — attentional control, working memory, and cognitive flexibility — derived from a 100-person study conducted with Imperial College. Analysis to date shows a meaningful relationship between our physiological features and cognitive performance, including roughly a 60% correlation between a cortical blood-flow feature and reaction time, as well as sensitivity of these features to factors such as sleep and age. Further biomarkers and additional blood-flow characterisations are in our development pipeline.

Not yet in the form of formal clinical validation. Connectome does not currently run clinical cohorts or clinical evaluations, so we do not yet report correlations against instruments such as the MoCA. Our current analysis links our functional features to behavioural metrics such as reaction time using classification and correlation approaches, and reports strong test–retest reliability for stable features (often around ICC 0.8). Planned work includes dedicated cohorts, such as an ADHD cohort, and the addition of functional connectivity measures on our roadmap.

Yes. All of our research is conducted in partnership with Imperial College London (Centre for Neurotechnology and Department of Bioengineering). Our LUCID study — a longitudinal study of healthy adults combining wearable sleep and activity data with task-evoked prefrontal haemodynamics measured by TD-fNIRS — established prefrontal activation as a longitudinally stable, behaviourally relevant neural marker: activation tracked reaction time and was shaped by age and lifestyle. The full study is available as a preprint on bioRxiv. Our hardware foundation also has extensive published validation, our evidence pack has been independently reviewed by neurologists at Imperial College London, and we have a further study accepted into Nature (currently under embargo).Read the LUCID study on bioRxiv →

No. Connectome is designed to show observed changes and associations, with appropriate attention to confidence and uncertainty. It does not claim that a given intervention definitively caused a specific neural outcome.

We explicitly indicate when there is no reliable signal or when the available data is insufficient for interpretation. Not every input produces a strong result, and that is intentional, because uncertainty is part of a clinically honest output.

Connectome is positioned as a functional measurement and monitoring system rather than a diagnostic device. Its regulatory status and claims should be discussed in line with the intended market and use case, but it should not be framed as making diagnostic or therapeutic claims where those are not intended.

A single scan does not show whether a result is normal, meaningful, or changing for that individual. By measuring over time, Connectome establishes a personal baseline and helps detect when changes exceed expected variability.

Yes, this is one of the main use cases. By comparing measurements over time, Connectome can help show whether brain function appears to be changing after an intervention and whether that change looks meaningful within the individual. It provides supportive evidence of change, though results will depend on the person, the protocol, and the strength of the signal.

That is still useful information. It may indicate that the brain is stable, that an intervention is not having a measurable effect, or that more time or data is needed before a clearer signal emerges.

Practice effects are a real consideration in repeated testing. Connectome is designed to look beyond performance alone by measuring how the brain is functioning during the task, which helps distinguish simple familiarity from a more meaningful change in the underlying neural response.

The value is in adding an objective longitudinal layer alongside symptoms, biomarkers, and clinical judgement. This can help support decisions about whether to continue, adjust, compare, or stop an intervention based on whether brain function appears stable, improving, or unchanged over time.

It typically sits after diagnosis and during treatment, optimisation, or monitoring. A clinic establishes a baseline, introduces an intervention or programme, and then tracks change over time through follow-up scans. It is designed to sit alongside existing tools and workflows, such as MRI, EEG, blood testing, or treatment protocols, rather than replace them.

At least three scans are generally needed to begin building a useful baseline and interpreting change with more confidence. In practice, many programmes involve three to five scans over a few months, often aligned with existing revisit cycles.

This depends on the structure of the programme, but a common rhythm is baseline, mid-protocol, post-protocol, and follow-up. The ideal cadence depends on the intervention and how quickly meaningful physiological change is expected.

A standard scan takes around 20 to 25 minutes, including rest periods and several cognitive tasks, with about five minutes of setup, so the full appointment is typically about 30 minutes. The duration is standardised across patients so that measurements remain comparable over time. We are also developing a shorter 15-minute protocol that removes two tasks to focus on cognitive flexibility and working memory, giving a faster option where appropriate.

You don't need a specialist. Anyone can be trained to administer a scan in around 30 minutes, and the system handles all of the processing and analysis.

At present, Connectome is used in clinic. Patients come in for repeat measurements over time as part of a structured programme.

The experience is non-invasive and designed to fit comfortably within a clinical appointment. Patients wear the device and complete the protocol without the burden of an invasive procedure or complex preparation.

A typical journey starts with a baseline scan, followed by repeat scans at defined points during and after an intervention. This is usually built into an existing programme so that the measurement becomes part of ongoing monitoring rather than a one-off event.

There are two ways to work with us. On the commission route, your patient pays Connectome directly and you receive a referral fee for each baseline scan — no deposit and no admin on your side. On the referral wholesale route, you pay Connectome a wholesale rate and set your own price, keeping the client relationship and the margin. Full pricing and packages are on our partner page.See pricing & packages →

It is best suited to higher-value, proactive individuals in longevity, performance, optimisation, or functional health programmes. It is generally less suited to people with advanced neurodegenerative impairment where the model of use and signal interpretation may be different.

Most systems rely on one-off assessments and subjective follow-up. Connectome adds an objective, longitudinal layer that helps show how brain function is evolving over time and whether an intervention appears to be producing a measurable effect.

Connectome sits between measurement and interpretation. It does not replace MRI, EEG, wearables, or routine clinical assessment, but helps connect these inputs within a longitudinal framework focused on change over time.

No. Connectome does not make therapeutic claims and is designed for measurement and monitoring rather than treatment.

Early signals can sometimes be seen within the first one to two scans. More meaningful insights typically emerge once three or more timepoints are available, with clearer patterns often developing over six to eight weeks depending on the programme and intervention cadence.

Each metric is a functional measure derived from task-evoked changes in cortical oxygenated blood flow, primarily in prefrontal executive-control circuitry. Values reflect how strongly and reliably the control system engages under a given cognitive demand, measured relative to a lower-demand baseline within the same task.Attentional control: the magnitude and stability of task-evoked activation within executive-control circuitry during conditions that require selective attention and interference resolution, relative to a lower-control baseline from the same task. A higher value indicates stronger recruitment of goal-directed control processes — a measure of control-system engagement, not a direct synonym for accuracy or reaction time.Working memory: the sustained task-related engagement of prefrontal control systems across memory-demand periods, indexed over the full set of working-memory trials rather than a single-trial peak. Because the signal is averaged across trials, it captures ongoing engagement of the working-memory system while a person holds and updates information continuously.Cognitive flexibility: the degree of adaptive control-system engagement during periods that require updating, reconfiguration, or switching of task-relevant representations, relative to more stable task periods. A higher value indicates stronger neural engagement associated with adaptive reconfiguration — update-and-shift capability rather than simply behavioural switching speed.