Dr. Martins’s most recently published paper “Human Brain/Cloud Interface” was published in the world’s most cited journal in the field of Neuroscience, the journal Frontiers in Neuroscience. Frontiers of Neuroscience is the world’s most cited journal in the field of neuroscience, ahead of “Nature” and the journal “Neuron”. The paper has more views than 99% of all Frontiers Journals, and is the most viewed paper ever of Frontiers in Neuroscience section Neural Technology.
Abstract: The Internet comprises a decentralized global system that serves humanity’s collective effort to generate, process, and store data, most of which is handled by the rapidly expanding cloud. A stable, secure, real-time system may allow for interfacing the cloud with the human brain. One promising strategy for enabling such a system, denoted here as a “human brain/cloud interface” (“B/CI”), would be based on technologies referred to here as “neuralnanorobotics.” Future neuralnanorobotics technologies are anticipated to facilitate accurate diagnoses and eventual cures for the ~400 conditions that affect the human brain. Neuralnanorobotics may also enable a B/CI with controlled connectivity between neural activity and external data storage and processing, via the direct monitoring of the brain’s ~86 x 10^9 neurons and ~2 x 10^14 synapses. Subsequent to navigating the human vasculature, three species of neuralnanorobots (endoneurobots, gliabots, and synaptobots) could traverse the blood–brain barrier (BBB), enter the brain parenchyma, ingress into individual human brain cells, and autoposition themselves at the axon initial segments of neurons (endoneurobots), within glial cells (gliabots), and in intimate proximity to synapses (synaptobots). They would then wirelessly transmit up to ~6 x 10^16 bits per second of synaptically processed and encoded human–brain electrical information via auxiliary nanorobotic fiber optics (30 cm^3) with the capacity to handle up to 10^18 bits/sec and provide rapid data transfer to a cloud based supercomputer for real-time brain-state monitoring and data extraction. A neuralnanorobotically enabled human B/CI might serve as a personalized conduit, allowing persons to obtain direct, instantaneous access to virtually any facet of cumulative human knowledge. Other anticipated applications include myriad opportunities to improve education, intelligence, entertainment, traveling, and other interactive experiences. A specialized application might be the capacity to engage in fully immersive experiential/sensory experiences, including what is referred to here as “transparent shadowing” (TS). Through TS, individuals might experience episodic segments of the lives of other willing participants (locally or remote) to, hopefully, encourage and inspire improved understanding and tolerance among all members of the human family.
Citation: Martins NRB, Angelica A, Chakravarthy K, Svidinenko Y, Boehm FJ, Opris I, Lebedev MA, Swan M, Garan SA, Rosenfeld JV, Hogg T and Freitas RA Jr (2019) Human Brain/Cloud Interface. Front. Neurosci. 13:112. doi: 10.3389/fnins.2019.00112
Abstract: Neuronanorobotics is the application of medical nanorobots to the human brain. This paper proposes three specific classes of neuronanorobots, named endoneurobots, gliabots and synaptobots, which together can non-destructively map and monitor the structural changes occurring on the 86 x 109 neurons and the 2.42 x 1014 synapses in the human brain, while also recording the synaptic-processed 4.31 x 1015 spikes/sec carrying electrical functional information processed in the neuronal and synaptic network.
Citation: Nuno R. B. Martins, Wolfram Erlhagen, Robert A. Freitas Jr., “Human connectome mapping and monitoring using neuronanorobots”, Journal of Evolution and Technology – Vol. 26 Issue 1 – January 2016 – pgs 1-24.
Abstract: Neuronanorobotics, a key future medical technology that can enable the preservation of human brain information, requires appropriate nanosensors. Action potentials encode the most resource-intensive functional brain data. This paper presents a theoretical design for electrical nanosensors intended for use in neuronanorobots to provide non-destructive, in vivo, continuous, real-time, single-spike monitoring of action potentials initiated and processed within the ~86 × 109 neurons of the human brain as intermediated through the ~2.4 × 1014 human brain synapses. The proposed ~3375 nm3 FET-based neuroelectric nanosensors could detect action potentials with a temporal resolution of at least 0.1 ms, enough for waveform characterization even at the highest human neuron firing rates of 800 Hz.
Citation: Nuno R. B. Martins, Wolfram Erlhagen, Robert A. Freitas Jr., “Action Potential Monitoring Using Neuronanorobots: Neuroelectric Nanosensors”, Intl. J. Nanomaterials and Nanostructures 1(June 2015):20-41.
Abstract: Neuronanorobotics, a promising future medical technology, may provide the ultimate tool for achieving comprehensive non-destructive real-time in vivo monitoring of the many information channels in the human brain. This paper focuses on the electrical information channel and employs a novel electrophysiological approach to estimate the data rate requirements, calculated to be (5.52 ± 1.13) x 1016 bits/sec in an entire living human brain, for acquiring, transmitting, and storing single-neuron electrical information using medical nanorobots, corresponding to an estimated synaptic-processed spike rate of (4.31 ± 0.86) x 1015 spikes/sec.
Citation: Nuno R. B. Martins, Wolfram Erlhagen, Robert A. Freitas Jr., “Non-destructive whole-brain monitoring using nanorobots: Neural electrical data rate requirements”, Intl. J. Machine Consciousness 4(June 2012):109-140.