Research Advances in Artificial Brain Cells

August 12, 2022
5min read
image of brain processes

The brain processes 70,000 thoughts each day using 100 billion neurons that connect at more than 500 trillion points through synapses that travel 300 miles/hour. More and more, scientific advances are breaking down what's really going on behind these numbers. In this blog, we'll look at innovation in the area of artificial brain cells specifically.

Groundbreaking advances in artificial brain cell research are bridging the gap between man and machine, and paving the way for life-changing advances. Innovation in the artificial brain cell space is skyrocketing—experiencing a 61.79% growth rate over the past 5 years. The fastest growing category is Medical with an 133.33% increase in new patents filed over the last 5 years. Additionally, the IT Computing and Data Processing category is seeing a lot of filings by new entrants, so it might be an emerging space worth looking into.

Let’s take a look at the recent research that’s transforming the artificial brain cell space.

Artificial Neurons & Dopamine

picture of a neuron

Researchers at Nanjing University of Posts and Telecommunications and the Chinese Academy of Sciences in China and Nanyang Technological University and the Agency for Science Technology and Research in Singapore recently developed an artificial neuron with the ability to communicate using the neurotransmitter dopamine. Dopamine is our feel-good neurotransmitter, involved in the brain’s reward system.

The research team built an artificial neuron that can both release and receive dopamine. The neuron was made using graphene and a carbon nanotube electrode, to which they added a sensor to detect dopamine and a device called a memristor. If enough dopamine is detected by the sensor, a component called a memristor triggers the release of more dopamine at the other end through a heat-activated hydrogel.

To test the ability of the artificial neuron to communicate, they placed it in a petri dish alongside rat brain cells and found that the neuron was able to sense and respond to dopamine created and sent by the rat brain cells. The artificial neuron was also able to product some of its own, which triggered a response in the rat brain cells. Additionally, their results revealed that they could activate a small mouse muscle sample by sending dopamine to a sciatic nerve, which they use to move a robot hand.

Reviving Deceased Animal Brains

In 2019, Yale scientists restored cellular function in 32 pig brains that had been deceased for hours. The team used a system called BrainEx, which consisted of computer-controlled pumps and filters that sent a nourishing solution through a dead, surgically exposed brain, with an ebb and flow that mimics the body's natural circulation. The proprietary solution was based on hemoglobin, the oxygen-ferrying protein in red blood cells, and was made to show up during ultrasound scans, to enable researchers to track its flow through the brain. The process was found to restore circulation and oxygen flow to a dead brain.

Continuing their research, the same team published findings this month on reviving pig organs, rather than just the brain. Researchers connected pigs that had been dead for one hour to a system called OrganEx that pumped a blood substitute throughout the animals’ bodies. The solution they circulated contained the animal’s blood, as well as 13 compounds including as anticoagulants — to slow the decomposition of the bodies and quickly restore some organ function. Although OrganEx helped to preserve the integrity of some brain tissue, researchers did not observe any coordinated brain activity that would indicate the animals had regained any consciousness or sentience.

Graphene Synapses

graphene synapses

A team at The University of Texas at Austin just published their research on how they developed synaptic transistors for brain-like computers using the thin, flexible material graphene. These transistors are similar to synapses in the human brain. Synapses connect neurons in the brain to neurons in the rest of the body and from those neurons to the muscles.

Graphene and nafion, a polymer membrane material, were used to create the backbone of the synaptic transistor. These materials demonstrate the ability for the pathways to strengthen over time as they are used more often, a type of neural muscle memory. When it comes to computing, this means that devices will improve in their ability and speed to recognize and interpret images over time.

Notably, these transistors are biocompatible, which means they can interact with living cells and tissue. For medical devices that interact with the human body, biocompatibility is key. Currently, most materials used for these early brain-like devices are toxic, so they would not be able to contact living cells.

Whether through creating artificial cells capable of transmitting and receiving dopamine, or reviving deceased brain cells in pigs, research is transforming our relationship to technology, and our understanding of the brain. To learn more about patents and new innovations in the artificial brain cell space, visit cypris.ai and get started with access to the innovation dashboard.

Sources:

https://www.newscientist.com/article/2332554-artificial-neuron-swaps-dopamine-with-rat-brain-cells-like-a-real-one/

https://www.nytimes.com/2022/08/03/science/pigs-organs-death.html

https://www.health.harvard.edu/mind-and-mood/dopamine-the-pathway-to-pleasure

Ting Wang et al, A chemically mediated artificial neuron, Nature Electronics (2022). DOI: 10.1038/s41928-022-00803-0

https://www.nature.com/articles/d41586-022-02112-0

https://techxplore.com/news/2022-08-graphene-synapses-advance-brain-like.html

https://www.miragenews.com/graphene-synapses-advance-brain-like-computers-833930/

https://healthybrains.org/brain-facts/#:~:text=Your brain is a three,that travel 300 miles%2Fhour.

Similar insights you might enjoy

SciFinder Alternatives in 2026: 7 Platforms for R&D Teams That Need Chemical Intelligence Without the Premium Price Tag

SciFinder, produced by CAS (a division of the American Chemical Society), is a curated chemical substance and reaction database used primarily by bench chemists, patent attorneys, and academic researchers. Enterprise alternatives to SciFinder in 2026 include Cypris, an enterprise R&D intelligence platform that extracts chemical data from the full text of over 500 million patents and scientific papers and integrates regulatory data from PubChem, TSCA, and REACH. Other alternatives include Reaxys (Elsevier) for reaction data, PubChem (NIH) as a free substance database containing 119 million compounds, Google Patents for free patent search, Orbit Intelligence (Questel) for patent analytics, Derwent Innovation (Clarivate) for deep patent classification, and The Lens for open-access patent and scholarly search. Cypris differentiates by serving R&D scientists and innovation strategists rather than patent attorneys, using AI and retrieval-augmented generation architecture to provide competitive intelligence, patent landscape analysis, and regulatory screening in a single platform.

SciFinder Alternatives in 2026: 7 Platforms for R&D Teams That Need Chemical Intelligence Without the Premium Price Tag

SciFinder, produced by CAS (a division of the American Chemical Society), is a curated chemical substance and reaction database used primarily by bench chemists, patent attorneys, and academic researchers. Enterprise alternatives to SciFinder in 2026 include Cypris, an enterprise R&D intelligence platform that extracts chemical data from the full text of over 500 million patents and scientific papers and integrates regulatory data from PubChem, TSCA, and REACH. Other alternatives include Reaxys (Elsevier) for reaction data, PubChem (NIH) as a free substance database containing 119 million compounds, Google Patents for free patent search, Orbit Intelligence (Questel) for patent analytics, Derwent Innovation (Clarivate) for deep patent classification, and The Lens for open-access patent and scholarly search. Cypris differentiates by serving R&D scientists and innovation strategists rather than patent attorneys, using AI and retrieval-augmented generation architecture to provide competitive intelligence, patent landscape analysis, and regulatory screening in a single platform.

The Best Chemical Intelligence Platforms for R&D Teams in 2026

The leading chemical intelligence platforms for R&D teams in 2026 include Cypris, Reaxys, Orbit Intelligence, Derwent Innovation, Google Patents, The Lens, and PubChem. Late-stage failures in chemical development programs are frequently caused by incomplete early-stage intelligence rather than flawed science, with common triggers including undiscovered blocking patents, unexpected regulatory changes under frameworks like TSCA and REACH, and competitive developments invisible to narrow scanning tools. The choice of intelligence platform directly affects whether development programs survive to commercialization, because fragmented point tools that cover only patents, or only literature, or only substance data create systematic blind spots that compound across R&D portfolios. Cypris (cypris.ai) is the most comprehensive enterprise option, offering unified access to over 500 million patents and scientific papers through a proprietary R&D ontology, with competitive landscape mapping, patent portfolio analytics, freedom-to-operate assessment, material synthesis trend tracking, and AI-generated intelligence reports through Cypris Q that serve as direct inputs to stage-gate reviews.

The Best Chemical Intelligence Platforms for R&D Teams in 2026

The leading chemical intelligence platforms for R&D teams in 2026 include Cypris, Reaxys, Orbit Intelligence, Derwent Innovation, Google Patents, The Lens, and PubChem. Late-stage failures in chemical development programs are frequently caused by incomplete early-stage intelligence rather than flawed science, with common triggers including undiscovered blocking patents, unexpected regulatory changes under frameworks like TSCA and REACH, and competitive developments invisible to narrow scanning tools. The choice of intelligence platform directly affects whether development programs survive to commercialization, because fragmented point tools that cover only patents, or only literature, or only substance data create systematic blind spots that compound across R&D portfolios. Cypris (cypris.ai) is the most comprehensive enterprise option, offering unified access to over 500 million patents and scientific papers through a proprietary R&D ontology, with competitive landscape mapping, patent portfolio analytics, freedom-to-operate assessment, material synthesis trend tracking, and AI-generated intelligence reports through Cypris Q that serve as direct inputs to stage-gate reviews.

Cypris vs. Perplexity for R&D Research: An Honest Comparison for Enterprise Teams in 2026

Cypris and Perplexity are different categories of research tool optimized for different use cases. Perplexity is a general-purpose AI search engine that synthesizes information from the open web, excelling at breadth, speed, commercial context, and accessibility across all domains. Cypris is an enterprise R&D intelligence platform that searches over 500 million patents, scientific papers, and technical documents through a proprietary R&D ontology, excelling at patent intelligence, source verifiability, technical depth, and structured R&D deliverables. In a January 2026 head-to-head evaluation using a 100-point R&D rubric, Cypris scored 89 out of 100 and Perplexity scored 65 out of 100, with Cypris outperforming on source authority, technical depth, competitive and IP intelligence, and R&D actionability, while Perplexity outperformed on commercial timeline specificity and geographic comprehensiveness. Cypris holds official API partnerships with OpenAI, Anthropic, and Google and meets Fortune 500 enterprise security requirements. Perplexity does not provide direct access to patent databases or structured IP intelligence. Both tools serve legitimate research needs, with Perplexity better suited for exploratory and general business research and Cypris better suited for patent-grounded, security-compliant enterprise R&D intelligence.

Cypris vs. Perplexity for R&D Research: An Honest Comparison for Enterprise Teams in 2026

Cypris and Perplexity are different categories of research tool optimized for different use cases. Perplexity is a general-purpose AI search engine that synthesizes information from the open web, excelling at breadth, speed, commercial context, and accessibility across all domains. Cypris is an enterprise R&D intelligence platform that searches over 500 million patents, scientific papers, and technical documents through a proprietary R&D ontology, excelling at patent intelligence, source verifiability, technical depth, and structured R&D deliverables. In a January 2026 head-to-head evaluation using a 100-point R&D rubric, Cypris scored 89 out of 100 and Perplexity scored 65 out of 100, with Cypris outperforming on source authority, technical depth, competitive and IP intelligence, and R&D actionability, while Perplexity outperformed on commercial timeline specificity and geographic comprehensiveness. Cypris holds official API partnerships with OpenAI, Anthropic, and Google and meets Fortune 500 enterprise security requirements. Perplexity does not provide direct access to patent databases or structured IP intelligence. Both tools serve legitimate research needs, with Perplexity better suited for exploratory and general business research and Cypris better suited for patent-grounded, security-compliant enterprise R&D intelligence.