The present method and system provides a neuromodulation therapy including receiving a plurality of input data relating to a patient, the input data including brain value measurements. The method and system includes analyzing the input data in reference to reference data generated based on machine learning operations associated with existing patient data and reference database data. Based thereon, the method and system includes electronically determining, a brain malady and a severity value for the patient and electronically generating a treatment protocol for the patient, the treatment protocol includes transcranial stimulation parameters. Therein, the method and system includes applying a transcranial stimulation using the transcranial stimulation parameters based on the treatment protocol.

In some examples, a method includes receiving a signal indicative of a blood pressure of a patient and identifying at least one first portion of the signal comprising a first characteristic of the signal exceeding a first threshold. The method also includes identifying at least one first portion of the signal comprising a second characteristic of the signal exceeding a second threshold, the first characteristic being different than the second characteristic. The method further includes determining a filtered signal indicative of the blood pressure of the patient by excluding the at least one first portion and the at least one second portion from the signal. The method includes determining a set of mean arterial pressure values based on the filtered signal and determining an autoregulation status of the patient based on the set of mean arterial pressure values.

A computer-implemented method and system includes accessing neurophysiological and neurovascular data recorded during sleep. A function mapping is executed from said neurophysiological and neurovascular data to a target that is one of a glymphatic flow marker, a molecular analysis marker of neurodegeneration, or a neuroimaging marker of neurodegeneration. A target prediction model is output based on the function mapping. The target prediction model can receive new neurophysiological and neurovascular data and output a predicted marker of neurodegeneration.

Cortical network structure that mediates response to brain stimulation, and associated systems and methods are disclosed herein. In one embodiment, a method for brain stimulation includes: delivering an input stimulus to an area of the brain, via a cortical implant; in response to delivering the input stimulus, generating neural signals in the brain; and generating a predicted outcome of the input stimulus. The predicted outcome is based on a set of data derived from a model that combines: protocol features that are brain agnostic, and network features that are based on interactions between neural nodes of the brain.

A computer-implemented method and system includes accessing neurophysiological and neurovascular data recorded during sleep. A function mapping is executed from said neurophysiological and neurovascular data to a target that is one of a glymphatic flow marker, a molecular analysis marker of neurodegeneration, or a neuroimaging marker of neurodegeneration. A target prediction model is output based on the function mapping. The target prediction model can receive new neurophysiological and neurovascular data and output a predicted marker of neurodegeneration.

A mental impairment detection system and non-invasive method of detecting mental impairment of a user are provided. A test (e.g., an inhibitory reflex test or a sustained attention test) is administered to the user, brain activity in a frontal lobe of the user is non-invasively detected while the test is administered to the user, and a level of mental impairment of the user is determined based on the brain activity detected in the frontal lobe of the user.

Provided are methods comprising presenting a sensory environment to an individual experiencing the effects of a psychoactive agent, monitoring the neural status, the physiological status, or both, of the individual, and presenting a modified sensory environment to the individual based on the monitoring. In certain embodiments, the agent is a psychedelic agent. According to some embodiments, presenting a sensory environment to the individual comprises presenting to the individual a visual stimulus, an auditory stimulus, a tactile stimulus, an olfactory stimulus, or any combination thereof. In certain embodiments, presenting a modified sensory environment to the individual comprises presenting a customized sensory environment to the individual in real-time based on the monitoring. In some embodiments, the individual is suffering from a mental health condition selected from depression, anxiety, post-traumatic stress disorder (PTSD), addiction, and any combination thereof. Systems that find use in practicing the methods of the present disclosure are also provided.

Provided herein are microelectrodes and methods of localizing and targeting the same. The microelectrodes include electrochemical or biological sensors, an array of electrical contacts along a long axis of the microelectrode, or both. The methods of localizing and targeting use statistical manipulations to reduce the errors inherent in spike train analyses.

A system for assessment of neurocognitive and neuromotor control performance, the system comprising a portable force plate configured to collect force plate data indicative of movement and postural control of a subject as the subject performs a task, a depth sensing device configured to, simultaneously with the collection of the force plate data, collect depth data of the subject as the subject performs the task, an interface board configured to, simultaneously with the collection of the force plate data and the collection of the depth data, generate stimuli to instruct the subject to perform a particular task and to generate interface board data indication of input received from the subject in response to the stimuli, and a computer-based controller configured to execute one or more neurocognitive and neuromotor control performance assessment program to analyze the force plate data, the depth data, and the interface board data.

In some embodiments, an apparatus includes providing a representation of a set of digital medical images to a first machine learning model to define a feature vector associated with a presence of an intracranial hemorrhage. A representation of the set of digital medical images is provided to a second machine learning model to define a second feature vector associated with a volume of the intracranial hemorrhage. Using a third machine learning model, a set of EMRs associated with risk factors for a predefined indication is analyzed to define a third feature vector. The first, second and third feature vectors are provided as inputs to a fourth machine learning model to determine a metric associated with an applicability of a specific treatment associated with a predefined indication. An alert is sent to relevant healthcare providers and relevant tests, procedures or bloodwork are ordered for the predefined indication.