Analytic Methods

Modern techniques utilizing machine-learning and cloud-computing enable improved neuroscientific investigations. Our data science team at Omniscient Neurotechnology is keenly interested In discovering new methods of analysis and testing previous methods in neuroscientific settings


Prehabilitation and rehabilitation using data-driven, parcel-guided transcranial magnetic stimulation treatment for brain tumor surgery: proof of concept case report

May 14, 2022

A case review demonstrating the utility of o8t software alongside neurorehabilitation to assess functional recovery after glioma removal.

12 Plagues of AI in Healthcare: A Practical Guide to Current Issues With Using Machine Learning in a Medical Context

May 3, 2022

A review of the current applications of Machine Learning and AI in health science data, and how users can avoid common mistakes when handling data.

Eigenvector PageRank difference as a measure to reveal topological characteristics of the brain connectome for neurosurgery

February 4, 2022

An investigation of two graph theory metrics: Eigenvector and PageRank centrality, and how they together inform unique and neurosurgically meaningful topological characteristics of the brain

Connectivity-based parcellation of normal and anatomically distorted human cerebral cortex

November 28, 2021

As the basis for the creation of our patient-specific brain maps, this manuscript unveils the Structural Connectivity Atlas (SCA) methodology

Using Quicktome for Intracerebral Surgery: Early Retrospective Study and Proof of Concept

August 13, 2021

Using Quicktome, our team re-examined cases of intracerebral surgery and demonstrated a machine-learning approach to investigating the organization of compromised brain networks.

Hollow-tree Super: a directional and scalable approach for feature importance in boosted tree models

April 7, 2021

This manuscript unveils a novel method for investigating which brain regions are most responsible for greater scores on psychometric tests such as the PANSS for Schizophrenia - Hollow Tree Super.

The Frontal Aslant Tract and Supplementary Motor Area Syndrome: Moving towards a Connectomic Initiation Axis

March 5, 2021

This study provides a retrospective investigation of the utility of Diffusion Tensor Imaging (DTI) for neurosurgical planning of medial frontal gliomas.

Unexpected hubness: a proof‑of‑concept study of the human connectome using pagerank centrality and implications for intracerebral neurosurgery

November 4, 2020

By utilizing PageRank Centrality, a common algorithm for search engine optimization, we investigated the remapping of neural hubs in individuals suffering from Schizophrenia.

Beyond eloquence and onto centrality: a new paradigm in planning supratentorial neurosurgery

January 1, 2020

In this study we explore whether centrality metrics can be utilized to inform the location of surgically eloquent regions. We found PageRank centrality reliably predicted surgically eloquent.

Measuring graphical strength within the connectome: a neuroanatomic, parcellation-based study

October 9, 2019

This study explores the use common graph theory metrics for defining functionally important areas of the cortex. Those we identified heavily overlapped with those known to be surgically eloquent.

A simplified method of accurate postprocessing of diffusion tensor imaging for use in brain tumor resection

December 16, 2016

By assessing the operative results of 43 craniotomy patients, we report on the use and benefit of DTI implementation in surgical workflows.