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The blue brain project: pioneering the frontier of brain simulation

Unlocking the mysteries of the human brain stands out as one of the most captivating scientific endeavors of the 21st century. In the last few decades, several inspirational projects have showcased groundbreaking scientific efforts and their potential impact on our understanding of complex systems such as the human brain. One such project is the Blue Brain Project, which is spearheaded by Henry Markram at the École Polytechnique Fédérale de Lausanne (EPFL) and has emerged as a groundbreaking scientific initiative since its inception in 2005. With its ambitious goal of creating a biologically accurate simulation of the human brain, the project has attracted attention from scientists, philosophers, and the general public alike [1] .

Containing billions of neurons and trillions of connections, the human brain remains one of the most complex and enigmatic systems known to humankind. Understanding the intricacies of brain function, cognition, and consciousness has long been a fundamental challenge in neuroscience. The Blue Brain Project carries immense significance as it endeavors to unravel these mysteries. By simulating the brain's structure and function, this project holds the potential to revolutionize our understanding of neurological disorders, inform the development of novel therapies, and shed light on the nature of consciousness itself [2] .

Over the years, the Blue Brain Project has achieved remarkable milestones, thereby advancing our knowledge of brain function. By combining experimental data from neuroscience research with sophisticated computational modeling techniques, the project has succeeded in constructing detailed models of specific brain regions. These models provide a deeper understanding of the electrical and chemical activity of neurons, synaptic plasticity, and neural coding. One notable achievement is the simulation of a rat neocortical column, which is a fundamental unit of the mammalian brain. [3] , [4] . By capturing the behavior of thousands of interconnected neurons within the column, the Blue Brain Project demonstrated the power of computational modeling to replicate the emergent properties and dynamics observed in real neural networks. See Figure 1 [5] , [12] . This milestone marks a significant step towards the project's ultimate goal of simulating larger brain regions and, potentially, the entire human brain.

Nevertheless, the Blue Brain Project raises critical ethical questions that must be carefully addressed. In the pursuit of groundbreaking scientific initiatives such as the Blue Brain Project, it is imperative to consider not only the remarkable advancements in our understanding of the human brain, but also the environmental impact associated with such endeavors. As a massive undertaking in computational neuroscience, the carbon footprint of the Blue Brain Project is a significant concern. This initiative, which relies on powerful supercomputers and energy-intensive data centers, generates substantial carbon emissions in the course of its operations. While the project holds enormous promise in unraveling the mysteries of the human brain, the associated carbon emissions should not be overlooked. It is crucial to address this environmental impact and explore strategies to mitigate it, thereby aligning the pursuit of scientific knowledge with a commitment to environmental responsibility. This balance between scientific goals and environmental stewardship will be pivotal in ensuring the sustainability and ethical conduct of projects of this magnitude [6] .

Another central concern is the potential emergence of consciousness within the simulated brain models. While the project's primary focus is on replicating the brain's structure and function, the question of whether conscious experience could arise within these simulations remains unresolved. This raises ethical dilemmas related to the creation and treatment of potentially conscious entities within the virtual realm. Striking the right balance between scientific exploration and ethical considerations is crucial to ensure responsible and accountable research practices. Another ethical consideration involves the project's reliance on animal experimentation to gather data and validate the models. Animal research has played a significant role in advancing our understanding of the brain; however, it also raises concerns regarding animal welfare and the ethics of using sentient beings for scientific purposes. Rigorous ethical oversight, transparency, and a commitment to minimizing animal suffering are essential aspects that must be upheld throughout the project [7] .

Looking ahead, the Blue Brain Project holds tremendous promise for expanding our understanding of the brain. As its computational power continues to advance, the project is poised to simulate larger brain regions and potentially move towards creating whole-brain models. Such advancements could enable unprecedented insights into the brain's functionality, network dynamics, and the mechanisms underlying complex cognitive processes. Furthermore, collaboration with other research initiatives, such as the Human Brain Project, fosters synergy and collaboration among scientists and institutions working towards a common goal of unraveling the mysteries of the brain. By sharing resources, knowledge, and expertise, these collaborations can accelerate progress, facilitate data integration, and provide a more comprehensive understanding of the brain's complexity. Additionally, the Blue Brain Project holds significant implications for the development of artificial intelligence (AI) and brain-inspired computing. The ability to simulate the brain's structure and function could provide valuable insights for designing more efficient and powerful AI systems. By mimicking the brain's neural networks and information processing strategies, researchers can potentially create AI models that better emulate human cognition and exhibit advanced capabilities such as pattern recognition, decision-making, and learning [7] .

Despite the significant achievements of the Blue Brain Project, several challenges and limitations must be acknowledged. The complexity of the human brain and the vast amount of data required for accurate simulations present both computational and technological hurdles. Creating a comprehensive and biologically accurate model of the entire human brain remains an immense undertaking that will require further advancements in computational power, data acquisition, and modeling techniques. However, data acquisition will be facilitated by the current advances that neuroimaging is currently undertaking, such as the development of multimodality and ultra-high-field MRI systems, as well as due to the increased integration of AI into radiology [8] , [9] , [10] . Another challenge lies in the validation and verification of the simulations. While the project strives for accuracy, it is essential to ensure that the simulated models faithfully represent real-life biological systems. Validating the simulated results against experimental data, addressing uncertainties, and continuously refining the models are critical aspects in maintaining scientific rigor and confidence in the project's findings. Moreover, the Blue Brain Project faces funding and resource constraints, as well as the need for collaboration and knowledge-sharing within the scientific community. Securing long-term financial support and fostering partnerships with other research institutions, industry stakeholders, and policymakers will be crucial to sustain the project's momentum and address the complex challenges it entails [11] .

The Blue Brain Project stands at the forefront of neuroscience research as a pioneering endeavor, holding immense potential to transform our understanding of the human brain. Its achievements in simulating brain regions and shedding light on fundamental aspects of brain function are commendable. However, ethical considerations surrounding consciousness emergence and animal experimentation must be thoughtfully addressed to ensure responsible scientific progress. As the project moves forward, it will be crucial to tackle the technical, computational, and validation challenges, alongside fostering collaborations and interdisciplinary partnerships. With continued advancements in computational power, increasing data availability, and advancements in neuroscientific research, the Blue Brain Project has the potential to revolutionize our understanding of the brain and pave the way for groundbreaking advancements in medicine, artificial intelligence, and our understanding of the complexities of the human mind.

Conflicts of interests: The author has no conflicts of interest to declare.

Blue brain technology - Artificial intelligence using brain Simulation

7 Pages Posted: 8 Oct 2023

Aakanksha Jadhav

Sinhgad Institutes - Sinhgad Institute of Technology and Science

Dr Ramesh D Jadhav

Sinhgad Institute of Management, Pune; Sinhgad Institute Of Management

Aditya Jadhav

SKN College Of Engineering Vadgaon Pune

Date Written: October 5, 2023

Technology is progressing at an unprecedented pace, and one notable endeavor is IBM's pursuit of the Blue Brain project, aiming to create a virtual brain. Blue Brain stands as the world's first virtual brain, a revolutionary concept seeking to replicate the cognitive abilities of the human brain through artificial intelligence. The essence of the Blue Brain project lies in the creation of a virtual brain that continues to function even after an individual's physical demise. This virtual brain will preserve and harness a person's information, intelligence, personality, emotions, and memories, contributing to the advancement of human society. The ultimate objective of this research is to enable the uploading of the human brain into a machine. The initial strategy for achieving this ambitious goal involves reverse-engineering the mammalian brain.. The outcome will be a functional, three-dimensional model capable of replicating the rapid electrochemical exchanges occurring within the brain. This modeling encompasses various aspects of brain functionality, including the understanding of brain dysfunctions such as mental conditions like depression and autism, as well as cognitive abilities like language, learning, perception, and memory. Subsequently, the scope of modeling will extend to cover additional brain regions.

Keywords: Supercomputer, Blue Gene, Nanotechnology, Robotics, Virtual Machine, Brain Simulation

Suggested Citation: Suggested Citation

Aakanksha Jadhav (Contact Author)

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SKN College Of Engineering Vadgaon Pune ( email )

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Blue Brain solves a century-old neuroscience problem

© Blue Brain Project / EPFL 2019

In a front-cover paper published in Cerebral Cortex, EPFL’s Blue Brain Project, a Swiss Brain Research Initiative, explains how the shapes of neurons can be classified using mathematical methods from the field of algebraic topology. Neuroscientists can now start building a formal catalogue for all the types of cells in the brain. Onto this catalogue of cells, they can systematically map the function and role in disease of each type of neuron in the brain.

“For nearly 100 years, scientists have been trying to name cells. They have been describing them in the same way that Darwin described animals and trees. Now the Blue Brain Project has developed a mathematical algorithm to objectively classify the shapes of the neurons in the brain,” explains Professor Henry Markram, Blue Brain’s Founder and Director. “This will allow the development of a standardized taxonomy [classification of cells into distinct groups] of all cells in the brain, which will help researchers compare their data in a more reliable manner.”

The team, with lead scientist Lida Kanari, have developed an algorithm to distinguish the different shapes of the most common type of neuron in the neocortex – the pyramidal cells. Pyramidal cells are distinctively tree-like cells that make up 80% of the neurons in the neocortex and, like antennas, collect information from other neurons in the brain. Basically, they are the redwoods of the forests of trees in the brain. They are excitatory, sending waves of electrical activity through the network, as we perceive, act, and feel.

The father of modern neuroscience, Ramón y Cajal, first drew pyramidal cells over 100 years ago, by looking at them under a microscope. Yet, up until now, scientists have not reached a consensus on the types of pyramidal neurons. Anatomists have been assigning names and debating the different types for the past century, while neuroscience has been unable to tell for sure which types of neurons are subjectively characterized. Even for visibly distinguishable neurons, there is no common ground to consistently define morphological types.

Seventeen types of pyramidal cells

The study from Blue Brain proves for the first time that objective classification of these pyramidal cells is possible, by applying tools from algebraic topology, the branch of mathematics that studies the shape, connectivity, and the emergence of global structure from local constraints.

Blue Brain has pioneered the use of algebraic topology to tackle a wide range of neuroscience problems, and with this study has once again demonstrated its effectiveness. In collaboration with Professors Kathryn Hess at EPFL and Ran Levi from the University of Aberdeen, Blue Brain developed an algorithm, which they then used to objectively classify seventeen types of pyramidal cells in the rat somatosensory cortex. The topological classification does not require expert input, and is proven to be robust.

The structure of most neurons resembles a complex tree, with multiple branches connecting to other neurons and communicating via electrical signals. If we keep the longest (persistent) components of the neuron structure and decompose the smaller branches, we can transform its tree-like structure into a barcode – a mathematical object that can be used as input for any machine-learning algorithm that will classify the neurons into distinct groups.

“Species” of brain cells

Any neuron classification process is plagued by this question: are two cells that look different just part of a continuum of gradually changing differences (like different “strains” of a species, e.g. different types of dogs) or are they really different “species” of neurons (e.g. dogs, cats, elephants, etc.)? In other words, are they discrete or continuous morphological variations of each other? This can be answered by using the new topological classification and grouping the different “species” of brain cells, each with its own characteristic “strains”.

“The Blue Brain Project is digitally reconstructing and simulating the brain, and this research provides one of the solid foundations needed to put all the types of neurons together,” explains Kanari. “By removing the ambiguity of cell types, the process of identifying the morphological type of new cells will become fully automated.”

This breakthrough can benefit the entire neuroscience community, as it will provide a more sophisticated understanding of cell taxonomy, and a reliable comparative method. The objective definition of morphological types is an essential first step towards a better understanding of the brain’s basic building blocks: how their structure is related to their function, and how local properties of neurons are connected to their long-range projections. This method provides a universal descriptor of trees, meaning that it can be used for the consistent description of all cell types in the brain, including neurons of all brain regions and glia cells.

The authors gratefully acknowledge that this study was supported by general funding to the Blue Brain Project from the Swiss government’s ETH Board of the ETH Domain, and supported generally by EPFL as a research. Neuronal reconstruction work was also supported by the National Natural Science Foundation of China (Grant no.31070951).

Objective Morphological Classification of Neocortical Pyramidal Cells 

Lida Kanari Srikanth Ramaswamy Ying Shi Sebastien Morand Julie Meystre Rodrigo Perin Marwan Abdellah Yun Wang Kathryn Hess Henry Markram

Author Notes

Cerebral Cortex, Volume 29, Issue 4, 1 April 2019, Pages 1719–1735,  https://doi.org/10.1093/cercor/bhy339

For more information, please contact Blue Brain Communications – [email protected]

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Blue Brain Technology

• First Online: 04 March 2020

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• Akshay Tyagi 13 &
• Laxmi Ahuja 13  

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 103))

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After death, the human body gets destroyed, brain stops working and human eventually loses his/her knowledge of the brain. But this knowledge and information can be preserved and used for thousands of years. Blue brain is the name of the first virtual brain in the world. This technology helps this activity. This article contains information about the blue brain, its needs, blue brain-building strategies, strengths and weaknesses and more. Collect data on the many types of somatic cells. The analog squares measurements were published on a IBM blue-chip central computer, hence the name “Blue Brain.” This usually corresponds to the size of the bee’s brain. It is hoped that simulation of gallium in the rat brain (21 million neurons) is to be performed by 2014. If you receive enough money, a full simulation of the human brain (86 billion neurons) should be performed, here 2023.

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Acknowledgements

The authors express their deep sense of gratitude to the founding President of Amity University, Mr. Ashok K. Chauhan, for his great interest in promoting research at Amity University and for his motivation to reach new heights.

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Tyagi, A., Ahuja, L. (2020). Blue Brain Technology. In: Saini, H., Sayal, R., Buyya, R., Aliseri, G. (eds) Innovations in Computer Science and Engineering. Lecture Notes in Networks and Systems, vol 103. Springer, Singapore. https://doi.org/10.1007/978-981-15-2043-3_11

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New Release of Blue Brain Project Atlas Sheds Light on Neuron Types

Summary: The Blue Brain Project has released a new and enriched 3D digital cell atlas containing more neuron types than the previous version.

Source: EPFL

After four years of research, EPFL’s Blue Brain Project shares an enriched version of their 3D digital cell atlas of the mouse brain which includes more neuron types. The new approach can be extended to any other cell type, and provides a resource to build tissue-level models of the mouse brain.

Knowledge of the cell-type specific make-up of the brain is useful to understand the role of each cell type as part of the network, is necessary to tackle any large scale neural circuit simulation, and is key to Blue Brain’s long term goal of accurately building a digital model of the whole mouse brain.

Nonetheless, obtaining a global understanding of the cellular composition of the brain is an excessively complex task, not only because of the great variability inherent in the literature but also because of the numerous brain regions and cell types that make up the brain.

In 2018, EPFL’s Blue Brain Project presented the first model of a cell atlas which provided an estimate of the composition of the mouse brain. The release of Blue Brain’s Cell Atlas (BBCAv1) marked the first time a 3D digital atlas provided information on major cell types, numbers and positions in all the more than 700 regions of the mouse brain.

It provides the densities of neurons, the associated connective tissue cells (glia) and their subtypes for each region, all of this presented in a navigable and dynamic format, allowing researchers to contribute new data. “At the time, it filled the huge gap in our knowledge of 96% of the mouse’s brain regions,” says Blue Brain Founder and Director, Professor Henry Markram.

In recent years, new datasets and tools have emerged, providing cell-type composition based on the specific proteins expressed within the cells. While comparatively quick, these molecular marker techniques alone do not always yield directly usable information on the morphologies (shape) and electrophysiological properties of neurons.

However, characterizing morpho-electrical properties of cells is extremely time-consuming and not suited to whole brain scans. It is therefore desirable to bring together and combine all the various available datasets in order to create one coherent framework with as much detailed information as possible.

Revealing inhibitory neuron density

One notable class of neurons for which very little data was available, and for which the method used to establish the BBCAv1 needed to be refined, is inhibitory neurons. Inhibitory neurons dampen the firing of other neurons and play a crucial role in packaging and transmitting information in the brain. They act like neuronal punctuation marks, and allow the brain to make sense of the influx of information.

Estimates of inhibitory neuron counts were collected from the literature and a framework was built in order to combine them consistently into the cell atlas. Using brain slice images, inhibitory neuron densities were also estimated in regions where no literature data was available. In total, the authors reveal that in the mouse brain 20% of all neurons are inhibitory.

“This sets the stage for subdividing inhibitory neurons into more fine-grained classes,” according to lead author, Blue Brain’s Dimitri Rodarie “and allows the neuroscience community to identify areas where current knowledge can be enhanced by additional constraints.”

Cross-species help for neuron models

The information mined from the Allen Institute for Brain Science provides essential data, allowing the creation of a catalog of neurons in the mouse brain according to their molecular, morphological and electrophysiological properties. However, in order to model brain regions, and more so a whole brain, not only is a global understanding of the cellular composition of the brain required, but detailed biophysical models of neurons must also be created.

In a previous publication, Blue Brain built models based on morpho-electric data from neurons of the juvenile rat somatosensory cortex. As the data is from different species—mouse vs. rat—and from a different developmental stage, the authors included normalization steps in order to map the models to the cell data from the Allen Institute. This step not only allowed them to assign a molecular identity to the neuron models, but also to populate the whole mouse cortex with detailed neuronal models.

“Our algorithm helps to draw parallels across species but also extends our understanding of less studied brain areas,” explains lead author, Blue Brain’s Yann Roussel, adding “This model will allow experimentalists to understand regional composition and allow computational neuroscientists to place defined cell types in their simulations.”

The new tools and methods used to refine the Cell Atlas and produce the BBCAv2, published in two companion papers in  PLOS Computational Biology , were extended to map well identified types to inhibitory neuron subclasses, paving the way for more accurate in silico reconstructions of brain tissues.

The data, algorithms, software, and results of the pipeline used to upgrade the Blue Brain Cell Atlas are all publicly available.

For Daniel Keller, leader of Blue Brain’s Molecular Systems team, “This version encompasses four years of studies and includes additional constraints from biological data to make the results more amenable to simulation. Using it for simulation allows us to identify areas for further refinement, thereby permitting improvement with every successive generation.”

“This project aims to involve the scientific community to contribute with open access to data, software and tools. We expect the BBCAv2 to be used for many purposes,” conclude the authors.

About this brain mapping research news

Author: Press Office Source: EPFL Contact: Press Office – EPFL Image: The image is credited to the Blue BrainProject/EPFL

Original Research: Open access. “ Mapping of morpho-electric features to molecular identity of cortical inhibitory neurons ” by Yann Roussel et al. PLOS Computational Biology

Mapping of morpho-electric features to molecular identity of cortical inhibitory neurons

Knowledge of the cell-type-specific composition of the brain is useful in order to understand the role of each cell type as part of the network.

Here, we estimated the composition of the whole cortex in terms of well characterized morphological and electrophysiological inhibitory neuron types (me-types).

We derived probabilistic me-type densities from an existing atlas of molecularly defined cell-type densities in the mouse cortex. We used a well-established me-type classification from rat somatosensory cortex to populate the cortex. These me-types were well characterized morphologically and electrophysiologically but they lacked molecular marker identity labels.

To extrapolate this missing information, we employed an additional dataset from the Allen Institute for Brain Science containing molecular identity as well as morphological and electrophysiological data for mouse cortical neurons.

We first built a latent space based on a number of comparable morphological and electrical features common to both data sources. We then identified 19 morpho-electrical clusters that merged neurons from both datasets while being molecularly homogeneous. The resulting clusters best mirror the molecular identity classification solely using available morpho-electrical features.

Finally, we stochastically assigned a molecular identity to a me-type neuron based on the latent space cluster it was assigned to.

The resulting mapping was used to derive inhibitory me-types densities in the cortex.

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—Human brain is the invaluable and quintessential creation of god, but search creation comes to end when a person reaches to the last phase of his life. The man acquires the knowledge and responds to the things because of the brain. In this research paper I used to describe how a human brain intelligence can be preserve for the future generation and how the Man-Machine-Man (M 3) interface is possible with the blue brain project. The main aim of this project is to upload human brain into machine. So, that man can think, take decision without any effort. After the death of the body, the virtual brain will act's as the man. So even after the death of a person we will not lose the knowledge, intelligence, personalities, feelings and memories of the man. That can be used for the development of the human society. This paper has a information about the stages, requirements of the modules to interface, merits and demerits of the technology for the human world.

Prof. Dr. SASIDHAR BABU SUVANAM

Human brain, the greatest creation of god which is package of unimaginative functions. A man is intelligent because of the brain. " Blue Brain " is world's first virtual brain. Pink brain is special because of that it can think, respond, take decision without any effort and keep anything in memory. Aim of the project is to archive features of Pink brain to a Digital system. In short, " Brain to a Digital System ". After death of a human, data including intelligence, knowledge, personality, memory and feelings can be used for further development of society. BB Storage space is an extracted concept from Blue brain project. Storing numerous and variety of data on memory is an advantage provided. By this concept, registers act as neurons and Electric signals as simulation impulses. Variation of data are identified based on signal variation that reach the registers. Registers mentioned here is same that a normal system maintains. Benefit 2126 Y.Vijayalakshmi et al focused by this concept of storage is storing data without deletion on real time as normal brain does. Attaching this concept to an expert system reflects drastic changes while it responds. To make the system more friendly a regional Language conversion using Natural Language Processing (NLP) is included with a voice recognition technique. In similar way, system should also respond using the experiences that it has been traveled through, in voice format. This is the output format of BB storage space. Nanobots on Blue brain which is used for information collection from neurons is replaced by real time experiences provided to the machine.

Saurav Poonia

We all are fascinated about how human brain works and why it is so superior and extraordinary. As some of the brains (Einstein, Ford, Edison and so on) in world are too resourceful and astonishing were also had the similar human brain but functioning is differ. To understand those workings, we require Blue brain. This technology is somewhere more state-of-the-art and groundbreaking than others. Even after the death of an individual, his/her brain will be alive virtually. In this paper an overview, modeling and recommendations for Blue brain has been presented for conceptual information. Through study it is also found that there are some challenges faced by this revolutionary technology. The simulation of human or mammalian brain with Blue brain is to identify the fundamental principles of brain structure and function in health and disease.

Ijariit Journal

Man is intelligent because of the brain. But the brain, all its knowledge, and power are destroyed after the death of the man. BLUE BRAIN, The name of the world's first virtual brain that means a machine that functions like a human brain. It can think. It can take a decision. It can response. It can store things in memory. The research involves studying slices of living brain tissue using microscopes and patch clamp electrodes. Data is collected about all the many different neuron types. This data is used to build biologically realistic models of neurons and networks of neurons in the cerebral cortex. The simulations are carried out on a Blue Gene Supercomputer built by IBM. In this paper, we concentrate on the application of Blue Brain for "Cracking Neural Code" as well as the use of Blue Brain in "Human memory loss". The neural code refers to how the human brain builds images using electrical patterns and cracking the neural code means finding the patterns and meaning in the noisy activity of the cell ensembles. Human memory loss includes conditions like 'Alzheimer' and 'short-term memory loss'.

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• 19 August 2024

Five ways the brain can age: 50,000 scans reveal possible patterns of damage

• Michael Eisenstein 0

Michael Eisenstein is a freelance writer based in Philadelphia, Pennsylvania.

You can also search for this author in PubMed   Google Scholar

Some parts of the brain tend to atrophy and deform in concert with other regions. Credit: Zephyr/SPL

An analysis of almost 50,000 brain scans 1 has revealed five distinct patterns of brain atrophy associated with ageing and neurodegenerative disease . The analysis has also linked the patterns to lifestyle factors such as smoking and alcohol consumption, as well as to genetic and blood-based markers associated with health status and disease risk.

The work is a “methodological tour de force” that could greatly advance researchers’ understanding of ageing, says Andrei Irimia, a gerontologist at the University of Southern California in Los Angeles, who was not involved in the work. “Prior to this study, we knew that brain anatomy changes with ageing and disease. But our ability to grasp this complex interaction was far more modest.”

The study was published on 15 August in Nature Medicine .

Wrinkles on the brain

Ageing can induce not only grey hair, but also changes in brain anatomy that are visible on magnetic resonance imaging (MRI) scans, with some areas shrivelling or undergoing structural alterations over time. But these transformations are subtle. “The human eye is not able to perceive patterns of systematic brain changes” associated with this decline, says Christos Davatzikos, a biomedical-imaging specialist at the University of Pennsylvania in Philadelphia and an author of the paper.

Previous studies have shown that machine-learning methods can extract the subtle fingerprints of ageing from MRI data. But these studies were often limited in scope and most included data from a relatively small number of people.

Older mouse brains rejuvenated by protein found in young blood

To identify broader patterns, Davatzikos’s team embarked on a study that took roughly eight years to complete and publish. They used a deep-learning method called Surreal-GAN that was developed by first author Zhijian Yang while he was a graduate student in Davatzikos’s laboratory. The scientists trained the algorithm on brain MRIs from 1,150 healthy people aged between 20 and 49, and 8,992 older adults, including many experiencing cognitive decline. This taught the algorithm to recognize recurring features of ageing brains, allowing it to create an internal model of anatomical structures that tend to change at the same time versus those that tend to change independently.

The researchers then applied the resulting model to MRI scans from almost 50,000 people participating in various studies of ageing and neurological health. This analysis yielded five discrete patterns of brain atrophy. The scientists linked various types of age-related brain degeneration to combinations of the five patterns, although there was some variability between individuals with the same condition.

Patterns of ageing

For example, dementia and its precursor, mild cognitive impairment , had links to three of the five patterns. Intriguingly, the researchers also found evidence that the patterns they identified could potentially be used to reveal the likelihood of more brain degeneration in the future. “If you want to predict progression from cognitively normal status to mild cognitive impairment, one [pattern] was the most predictive by far,” says Davatzikos. “At later stages, the addition of a second [pattern] enriches your prediction, which makes sense because this kind of captures the propagation of the pathology.” Other patterns were linked to conditions including Parkinson’s disease and Alzheimer’s disease , and one combination of three patterns was highly predictive of mortality.

The authors found clear associations between certain patterns of brain atrophy and various physiological and environmental factors, including alcohol intake and smoking, as well as various health-associated genetic and biochemical signatures. Davatzikos says that these results probably reflect the effect of overall physical well-being on neurological health, because damage to other organ systems can have consequences for the brain.

Davatzikos cautions that the study “doesn’t mean that everything can be boiled down to five numbers”, however, and his team is looking to work with data sets that include a broader range of neurological conditions and have greater racial and ethnic diversity.

doi: https://doi.org/10.1038/d41586-024-02692-z

Yang, Z. et al. Nature Med . https://doi.org/10.1038/s41591-024-03144-x (2024).

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A Dangerous Idea About How the Brain Works

The chemical-imbalance theory in mental health influenced the way we talk and think about these conditions. But is it right?

In July 1990, President George H. W. Bush issued a presidential proclamation to mark the dawn of a new and exciting era of neuroscience. The ’90s, Bush said, would be the “decade of the brain”—a 10-year scientific blitz that promised to render the human brain, “one of the most magnificent—and mysterious—wonders of creation,” a bit less mysterious.

The implications of success were enormous. The proclamation names Alzheimer’s, stroke, schizophrenia, autism, depressive disorders, Parkinson’s, Huntington’s, and addiction as targets to study. With use of the PET scan and MRI becoming more common—creating colorful images of the brain in action—scientists were hopeful the decade of the brain would yield results for the millions of patients affected by these conditions.

But the approach to mental illness inherent in Bush’s proclamation made its way out to the public before scientists could evaluate their efforts. And a new story of mental illness would fundamentally alter the way Americans thought—and still think—about mental health.

This episode follows both this scientific saga and the story of a family of three generations dealing with one diagnosis—and the question of what it means to get better.

This is part two of a new three-part miniseries from Radio Atlantic — Scripts—about the pills we take for our brains and the stories we tell ourselves about them.

Listen to the story here:

Subscribe here: Apple Podcasts | Spotify | YouTube | Overcast | Pocket Casts

The following is a transcript of the episode:

Hanna Rosin: This is Radio Atlantic . I’m Hanna Rosin. Today we have the second episode of Scripts , our three-part series exploring the pills we take for our brains, the stories we tell about them, and what happens when you combine the two.

This week’s episode is about a family—three generations dealing with one diagnosis— and the question of what it means to get better.

Reporter Ethan Brooks will take it from here.

Ethan Brooks: In the mid 1990s, somewhere in central Connecticut, Cooper Davis was on a school bus headed toward New York.

Davis: We had a field trip to go see The Scarlet Pimpernel on Broadway.

Brooks: I’m not familiar.

Davis: I wasn’t, and I didn’t get to see it, because of decisions that I made.

Brooks: Cooper didn’t get to see The Scarlet Pimpernel , because of what he packed in his bag for this field trip.

In the bag were two nips of Jack Daniels. Never had a drink before but he was curious, so why not?

Davis: I brought not just those. I also brought firecrackers, a hunting knife, a survival kit with those matches covered in phosphorus so you can light a match in the rain.

I just felt very cool because I had a backpack filled with gear, you know, in case the bus flips over in the wilderness.

Brooks: I just want to repeat the inventory: That’s an eighth grader carrying two nips of Jack Daniels, firecrackers, a hunting knife, and matches. Also, a white tank top.

Davis: Because it felt like that went with the other stuff.

Brooks: Yeah, that’s the outfit for the rest of your bag.

Davis: Exactly. ( Laughs .)

Brooks: Were you wearing it, or was it there in spirit?

Davis: No, no. It was there in case I needed to, like, express the whole picture.

Brooks: The whole picture ends up looking like this: Cooper pours the whiskey into a two-liter Coke bottle, passes it around the bus. At some point, he lights one of the matches because, you know, they’re cool and then struggles to put it out.

So now the school bus has a kind of speakeasy vibe, smells a bit smokey, full of tipsy eighth graders. And it doesn’t take long for the teachers to trace all this chaos directly back to Cooper.

So he spends the rest of the field trip sitting next to his teacher.

Davis: And so when we got back at the end of the night, literally my dad just physically picked me up the second I stepped off the bus. I got hit with, Why would you steal alcohol from your grandfather? Why would you bring weapons? Why would you do all of this? And for me, it was like, the reason why was because, impulsively, for one minute, I thought it would be a good idea.

Brooks: Mm-hmm.

Davis: And I said that, but no one believed me. And instead, there was sort of an insistence that I was disturbed. And that was when I sort of graduated from class clown into behavior problem.

Brooks: Class clown . Behavior problem . These are phrases people used for the better part of a century to describe what is now called ADHD.

Cooper is, and has always been, the poster child of ADHD. As a kid, he was a voracious reader, undeniably smart, but also just had rock-bottom-boredom tolerance, caused problems in class. The Scarlet Pimpernel incident is just one story of many. There’s also the Tiger Balm affair, the blue-tissue trouble, the desk debacle—the list goes on.

It was the mid 1990s, and everybody knew that Cooper had ADD. And a few years after this field trip, he would be put on a stimulant, Ritalin. But when Cooper took this drug, he also took in a story about how his own brain worked and who he was—an idea that, for Cooper, would eventually prove disastrous, an idea that is still very much with us, the millions of Americans who take medications for mental health.

This is Cooper’s story and the story of that idea.

When he was a kid, Cooper was always reading. If his parents wanted to punish him, they’d take away his books. Teachers too. But reading is reading, and he eventually found his way into a gifted-and-talented program at school.

Davis: And I loved it. I mean, I loved it. And it was all—it was just me and a little room of, like, mostly horse girls. There were a lot of them.

Brooks: You mean, like, just girls who love horses?

Davis: Exactly. I just have such a deep affinity for that particular type of person, and so that was a bright spot. Other than that, I was mercilessly bullied. I would’ve given it as hard as I got if I sort of had a crew to back me up, but I really didn’t.

Brooks: Where were the horse girls?

Davis: Yeah, they were galloping in a different part of the playground.

Brooks: Cooper’s time in the gifted-and-talented program didn’t last. He moved schools a lot because school was tough for Cooper. His grades were bad. His teachers disliked him because, as he describes it, he was exceptionally unhelpful in the classroom.

The teachers would send him to the principal, who would make him write sentences like, “I will not disrupt class,” over and over and over again like a real-life Bart Simpson.

And it wasn’t always the principal. Sometimes they’d send him to the nurse—just anything to get him out of the classroom. And the nurse’s office is where he notices something: There were a lot of kids in there picking up their meds.

Brooks: And the meds, in your understanding at the time, were stimulants?

Davis: Yeah. One hundred percent.

Brooks: How common was that?

Davis : I mean, anecdotally, to my very young mind, I would say in a class of 20 kids, maybe five—four or five.

Brooks: One of Cooper’s teachers thought he had ADD and told his parents he should get evaluated for Ritalin. Here’s Cooper’s mom, Trish.

Trish: Say there were eight boys in the class and, say, I don’t know how many girls, but there were eight boys. And she said, Well, six of these boys are already on Ritalin, and they’re fine .

Davis: Really? Six?

Trish: And in my head, it was like, Six boys out of eight? Like, I just couldn’t believe that statistic.

Brooks: If you look at the big-picture numbers from this time, they’re not as extreme. But they’re not not extreme. One study has prescriptions for Ritalin more than doubling between 1990 and 1995. The DEA had estimated a six-fold increase in that time period.

This is the period in American history when ADD is becoming an extremely popular diagnosis for kids. The 1.5 million kids being prescribed Ritalin then, leading the way to where we are now: As of 2022, over one in 10 kids in the U.S. has received an ADHD diagnosis. For boys, it’s 15 percent.

But something else was happening alongside those numbers. At the start of the ’90s, a new idea was taking hold in the field of psychiatry, an idea that would inform Trish’s decision whether or not to medicate Cooper—the same idea that would come to haunt Cooper 20 years later.

On July 17, 1990, President George H. W. Bush issued a presidential proclamation. The 1990s, Bush said, would be the “decade of the brain.”

Benjamin Fong: The decade of the brain, it’s a really terrifying declaration looking back at it.

Brooks: ( Laughs .) The decade of the brain.

Brooks: This is Benjamin Fong, a professor at Arizona State University. Fong says the decade of the brain started off with one very specific goal.

Fong: The hope was that with the development of these new drugs, we would start to tackle the different mental-health conditions that had so far eluded psychiatric practice.

Brooks: By 1990, psychiatry was at the tail end of a coup, and it was not bloodless. On one side, the psychoanalysts: disciples of Freud, who had dominated the field since World War II with ideas like the unconscious, repression, Oedipus complex—all the classics.

On the other side were the medical psychiatrists, who were tired and maybe a little embarrassed by all this Freudian stuff. They were doctors, after all. Psychiatry should be rooted in scientific rigor, in biology—not some Austrian guy’s ideas.

So by the time Cooper was noticing all the Ritalin kids in his class, the biology crowd had already won. The psychoanalysts lost standing, and the medical psychiatrists announced it would be the decade of the brain.

The idea was simple: In this decade, psychiatry would join up with the rest of medicine and discover the biology of mental illness. They would be able to look at something in your blood or your urine, or whatever, and say, See that? That’s your depression. That’s your ADD .

Anne Harrington: There was enormous optimism.

Brooks: This is Anne Harrington, history professor at Harvard.

Harrington: Sort of like, you know, a cardiologist can take an angiogram that they would be able to look at, like the brain of a schizophrenic person, and say, Aha!

Brooks: That aha moment, in 1990, felt inevitable. The PET scan and the MRI were becoming more common, creating detailed, colorful images of the brain in action. It felt like the biological basis for mental illness was just around the corner. And scientists figured that basis would be chemical. People have been taking chemical compounds for decades, and there was a theory about how they worked.

Harrington: There was often a comparison made between taking, say, an antidepressant if you have suffered from depression and taking insulin if you suffer from diabetes, and it’s simply correcting the chemical imbalance.

Brooks: Simply correcting the chemical imbalance—this was an idea with obvious appeal, and the start of the story that would change Cooper’s life.

Compared with old-school psychoanalysis, the idea of a chemical correction feels chiropractic—the same satisfaction, the same instant relief as a cracked neck. Soon enough, this idea was everywhere.

The FDA made it easier for prescription-drug makers to advertise directly to consumers. On TV, that rapid-fire list of side effects and phrases like “ask your doctor” began to feel normal, even though this type of advertising is not normal. To this day, it’s only the U.S. and New Zealand that allow this. It’s banned pretty much everywhere else on earth.

Anyway, it was, in part, through TV ads that the chemical-imbalance idea reached the public.

Advertisement:   You know when you feel the weight of sadness, you may feel exhausted, hopeless, and anxious.

Brooks: Take, for example, ads for the antidepressant Zoloft, which showed up a few years after the advertising rules were eased. The ads are in black and white, hand-drawn, simple animation. The ad opens with what can only be described as a sad blob groaning as rain pours down from a blob-sized cloud.

Advertisement:  These are some symptoms of depression, a serious medical condition affecting over 20 million Americans.

Brooks: Then the ad cuts to a new shot, this one of two synapses, one on each side of the frame, labeled nerve A and nerve B. Chemicals float between the two but drift decisively toward nerve A.

Harrington: But then they say, while they’re showing you this, the actual cause of depression is unknown.

Advertisement:  While the cause is unknown, depression may be related to an imbalance of natural chemicals between nerve cells in the brain. Prescription Zoloft works to correct this imbalance.

Brooks: The chemicals even out. Then the ad cuts back to the sad blob. The rain has stopped. A flower has sprouted next to the blob, who bounces along with a singing bluebird for company.

Advertisement:  Talk to your doctor about Zoloft.

Zoloft. When you know more about what’s wrong, you can help make it right.

Brooks: “When you know about what’s wrong, you can help make it right.” Zoloft could have shared that tagline with the new psychiatry, or at least their aspiration to find the biological basis of mental illness.

The Zoloft ads have been credited with bringing mass awareness to the symptoms of depression. Some people saw themselves in that sad blob and decided to get help. But the ads also helped solidify this mechanistic picture of mental health, something that just needed a few tweaks.

Back in Connecticut, by the time Cooper’s teacher is telling his mom about all the boys on Ritalin, the chemical-imbalance idea had arrived. Cooper’s teacher knew what was wrong. It was up to his mom, Trish, to help make it right.

Trish: And it was, you know, during conference, and she just suggested it, strongly. So I think I probably talked to the other moms that had the kids on Ritalin. But you had to be careful because the teacher shouldn’t have said, you know, who was on Ritalin. So it was complicated, and it was very lonely. I will tell you that it was a very lonely thing to go through.

Davis: Why?

Trish: Because I had a different perspective.

Brooks: Trish’s perspective was that she didn’t want Cooper on meds. She didn’t really even want him on sugar , so methylphenidate was sort of a stretch.

Instead, she moved him around: a brief stint in private school, another in catholic school, then back to public school. But as Cooper got older, into his teenage years—as the decade of the brain progressed and the chemical-imbalance idea found greater purchase—as doctor after doctor told her Cooper fit the bill for ADD, it wore her down.

Trish: I just didn’t know what to do. I was so tired of the pressure. And then I remember telling Cooper, When you’re 18, you can make that decision for yourself because I’m done .

Brooks: So around the time he turned 18, Cooper drove over to the doctor on his own and asked for meds.

Davis: And then he said, Well, I have a friend who’s a psychiatrist. I’m just going to give him a quick call . He calls the psychiatrist. Psychiatrist said whatever he said. He gets off the phone and says, Well, he says you fit. That should probably help you . So I’m gonna start you at 5 milligrams twice a day .

Brooks: That quick.

Davis: Bada bing. You know, he just did it cowboy style and just kind of got it done.

Brooks: Did anyone ever talk to you about coming off or how long you would be on stimulants?

Brooks: Did you ever think about it?

Davis: Not really.

Brooks: Cooper left the doctor with his prescription in hand. But it’s important to say, I think, he wasn’t really expecting much. He didn’t think of himself as having any sort of deficiency. Then he starts 5 milligrams of Ritalin twice a day, and that skepticism vanishes.

Davis: My initial experience with taking the drugs was revelatory. It did feel profound, and if I was a different type of a person, it would have brought me to tears. I had been, for years and years, sort of beleaguered by people telling me, Why can’t you just do what you’re supposed to do? You have so much intelligence. You have so much potential. Why do you choose to not do this?

And I never had a good answer for that. The drug gave me, sort of, freedom from that question. Like, I no longer have to be that way .

That was an enormous relief.

Brooks: This shift for Cooper, from having explainable deficiencies, like, I have ADD, but I don’t take meds, so be gentle , to simply not have those deficiencies—that is a profound change, a cure for unrealized potential.

And when you think about those terms it’s like, Who cares about the biology of mental illness? The treatment works, and that’s what matters .

Davis: So I will say that my grades—I do have the report card somewhere that shows the low B’s and mostly C’s one quarter, and then the next: straight A’s across the board.

Brooks: Wow. Really? You know, if you read about ADD and about medication, there are these phrases that come up, or metaphors that people use to kind of describe the experience of getting medicated for the first time.

Davis: Mm-hmm.

Brooks: People will say it feels like putting on glasses for the first time. There’s the thought of: This is how normal people feel . Did you have those thoughts? Did you think about it in those terms at all?

Davis: That thought entered my mind but was more like, Is this how normal people feel? I s this how the horse girls are able to just do their work and not to suffer through school? But even at that time, I did not have the sense that, like, This is correcting something for me .

It was more like a superpower. Like, it wasn’t fixing my brain; it was making my brain even better than the average brain. That was sort of my conception.

Brooks: As far as Cooper was concerned, his chemicals didn’t need rebalancing. Instead, the Ritalin was a tool—not a corrective, not glasses; more like X-ray vision. And by the time he’s starting on stimulants at the end of the decade of the brain, the idea of superpowers via psychiatry was gaining speed.

Fong: The phrase, “better than well” became commonplace in psychiatry circles.

Brooks: Again, historian Benjamin Fong.

Fong: The idea that you could be your optimized self, that was very much part of the dream as well.

Freud’s old dictum was that the whole point is to turn hysterical misery into common unhappiness. Well, that’s not a very American goal.

Brooks: Imagine if, at the end of that Zoloft commercial, after getting his chemicals rebalanced, if the blob was just a little less wet. No flowers. No bluebird. Just common unhappiness. I don’t think that would sell much Zoloft.

Fong: There’s a sort of culture of self-optimization, to be your best possible self at all times, and it’s a really difficult thing to do. It’s a really difficult thing to live up to. It’s an unrealizable ideal in a lot of ways.

Brooks: Whether the drugs were stimulants or antidepressants or anything else, the message was the same: that with the right balance of chemicals, you can be better than well. Cooper felt it too.

Davis: I became hyper-focused on inventorying how I’m feeling and, What can I do to adjust that or optimize it? It was not: What do I change externally? It’s: How do I change me?

Brooks: The Ritalin, though, came with a crash. So in high school, he smokes and drinks to take the edge off that crash, even though he didn’t really like being drunk or high. In college, he starts having anxiety, which led to a prescription for Ativan.

Davis: So I have this ability to really modulate exactly where I’m at, internally, to meet the moment.

Brooks: For Cooper, in an uncomplicated way, this rocks. He wants to go through life energized, confident, focused.

Brooks: In college, Cooper spends countless hours in the studio creating works that are detailed and impressive. He paints mandalas: intricate, radiating patterns rendered in minute detail. His teachers see energy, confidence, focus.

After college, there is an internship at a stop-motion studio in New York—more work in obsessive detail—then some time as a production assistant.

Over these years, the medications change but not too much. There are extended-release and immediate-release formulations of the stimulants. He tries out different stimulants—generic versions of Ritalin, Adderall, Dexedrine, Desoxyn—and in the sampling, the prescribed doses increase.

With the stimulants for focus and the Ativan for relaxing, Cooper is better than well.

Brooks: By his mid 20s, Cooper is working at a local paper on Martha’s Vineyard, and this job is tough. It’s stressful with constant deadlines but not unmanageable with the stimulants.

And it’s here, on this island, that things start to unravel. At the newspaper, it’s Cooper’s job to report on culture.

Davis: So the big part of my job was just, like—the whole cultural calendar for the entire island is my responsibility. It’s not my favorite part of the job, but it’s important.

Brooks: One day, when he makes the calendar, he forgets to include a local gallery’s event. The gallery calls him to complain, and he loses his temper. So Cooper is freaking out, yelling at this watercolor gallery over the phone. They call his boss, who calls Cooper into her office.

Davis: And all of a sudden, it’s a flashback to elementary school, like I’m getting called into the office, and she’s basically saying to me, like, I don’t know what the deal is with you, but you cannot do this. Something has happened to you .

And it feels like, you know, I’m in trouble.

Brooks: Cooper didn’t quite know it, but this was not the first time he had messed up in this job. And pretty soon after, he was fired.

When he looks back at this moment now, none of it really makes sense. Why was managing the cultural calendar on Martha’s Vineyard a high-stress job? How did he end up screaming at someone over the phone about watercolors?

Davis: Local watercolors—local.

Brooks: It was like he left the real world and instead was living somewhere much more bizarre.

Davis: I had created an alternate reality for myself where I had way more stress and pressure than I actually had. What I really had was a lack of maturity and an inability to manage my time. And that was partly because my attitude was, I don’t need to manage my time, because I have superpowers .

Brooks: And so it was at this point, after more than a decade of medication, it was clear that Cooper’s superpowers weren’t superpowers at all. The X-ray vision was, instead, something closer to a kaleidoscope: colorful, interesting, but also distorting his experiences.

Brooks: Without a job, Cooper eventually moved back to Connecticut and found himself lost. He tried freelancing and struggled to do it. He tried a lot of new prescriptions—mood stabilizers, sleeping pills, antidepressants. Those he could do.

The new medications came with side effects. His memory suffered. He went to bed at night and woke up feeling like a completely different person. He slept odd hours, made odd phone calls. His family told him they didn’t recognize this person he had become.

Years passed like this: unable to work, relationships falling away, living on unemployment and a bit of money his grandfather left him. For Cooper, there would be no rock bottom—just a gradual erosion until it felt like all the meaning had disappeared from his life.

Brooks: And then, suddenly, there was meaning. One day, his partner at the time told him that she was pregnant. Cooper was going to be a father.

Davis: And it was at that moment that, all of a sudden, the facts of my life became abundantly clear to me for the first time.

Brooks: Why do you think that was?

Davis: Because I was suddenly not the main character in my story. This baby, this child, this person, What kind of dad are they gonna have? W hat kind of dad do I want them to have?

And then, sort of looking at myself, appraising myself, through that lens, like, I am a drug-addled, unemployed mess with no friends, no real contacts, no prospects , I think my first thought was, Whatever it’s going to take to get past this is probably going to involve cutting back on the amount of drugs that I’m taking .

Brooks: Over the next year, Cooper would come off everything. What had started with 5 milligrams of Ritalin had ended up as a lot of a lot of stuff.

As it happened, Cooper wasn’t the only one getting away from psych drugs. Major drug manufacturers were making their exit too. According to Anne Harrington, around 2010, companies like AstraZeneca and GlaxoSmithKline moved their focus away from psychiatric medications.

Harrington: The National Institute of Mental Health invested billions. Billions. But the breakthroughs never happened.

There may have been some amazing research. There was some amazing research, but it didn’t translate into the kinds of material gains for patients that the public had been promised.

Brooks: In her book, Harrington writes about Tom Insel, the man who had been the director of the National Institute of Mental Health. In 2017, after he had retired, he said this:

“I don’t think we moved the needle in reducing suicide, reducing hospitalizations, improving recovery for the tens of millions of people who have mental illness. I hold myself accountable for that.”

The goal that psychiatry had set at the start of the ’90s, to map the biological basis of mental illness, never came to pass. Patients never got the benefits that were promised in the decade of the brain. What they got, instead, was a story—a story about chemical imbalance that never quite passed muster but grew deep roots into the American understanding of mental illness anyway. The science fell away, but the story remains.

Brooks: Cooper Davis’s kid, the one whose existence inspired him to come off his meds, is now 10 years old. They live in a house not far from Cooper’s old high school. There’s a sign outside of his room that says no parents allowed.

Recently, the school psychologist devised a jar of interesting facts for him: Behave well, and you get a fact .

Davis: So these would be rolled up like scrolls.

Brooks: Like Cooper, he’s struggling in school—sometimes daydreaming, sometimes misbehaving. In any case, it’s hard. He needs help, which is why Cooper took him in for a psychological evaluation. At the eval, he met with doctors.

Davis: Saying, okay, This is what he has, and these are our recommendations . Medication is the first one that is named, and then they tell me, The way these medications work is they correct a chemical imbalance in the brain .

Brooks: They said that?

Davis: Yes.

Brooks: The first time I spoke to Cooper, when he told me that he’d need to decide whether or not to put his kid on stimulants, I had a lot of questions. Here was a person for whom stimulant medication had been both wonderful and terrible now, through his son, getting the opportunity to go back and decide again: Yes or no?

Cooper told me he was wracked with guilt and doubt over this decision, not unlike his mom 30 years ago—the same decision around the same drug made across three generations of one family. And in all that time, very little has changed.

We often tell the same simplified story about chemical imbalances and deficiencies. And our scientific understanding also hasn’t changed meaningfully. What has changed is the sheer number of people taking these medications. From 2018 to 2022, prescriptions of stimulants rose 30 percent for people aged 20 to 39. There is plenty of evidence that stimulants make people feel better. There’s a reason they are so popular.

But for so many people to be starting life-changing medications with ideas that aren’t clearly supported by evidence, like the chemical-imbalance theory or the expectation to be “better than well,” that distorts our expectations and sets us up to struggle more than we need to.

After his kid’s psych eval, Cooper made the same decision his mom did when he was 10: His son won’t get stimulants. And when Cooper explains this decision to his son, he tries to tell him a different story, maybe a complicated one for a 10-year-old but closer to true.

Davis: What I tell him that I, like you, was diagnosed even younger than you with this. And in my own case, they were very helpful to me at first in certain ways. But the ways in which they changed me over time started to take me to a life that I didn’t feel like I had a lot of control over , and that, When you don’t feel like you have control over your life, your life is out of control .

I thought the only tool that I had, really, to control what was happening around me was drugs that allowed me to change how I showed up for the world, and that actually wasn’t true and was never true.

The villain in that story is not the drugs; it was the way I was thinking about them and maybe the way that other people in my life were encouraging me to think about them. The drugs were not the villain.

Brooks: Mm-hmm. What does he think about that story?

Davis: I mean, this is one area where he has unlimited attention.

Brooks: Cooper Davis helps run the Inner Compass Initiative, a nonprofit that helps people make informed choices about taking and withdrawing from psychiatric medications.

Scripts is produced and reported by me, Ethan Brooks. Editing by Jocelyn Frank and Hanna Rosin. Original music by Rob Smierciak, Engineering by Erica Huang. Fact-checking by Sam Fentress. Claudine Ebeid is the executive producer of Atlantic audio. Andrea Valdez is our managing editor.

If you want to learn more on this topic, Benjamin Fong’s book is called Quick Fixes ; Anne Harrington’s book is called Mind Fixers .

Next week: a story about the highs and lows of being prescribed ketamine online. See you then.

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Large Study Confirms Significant Frequency of Undetected Responsiveness in Severe Brain Injury

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Command following responses can be detected in patients with cognitive-motor dissociation (CMD) using functional MRI (fMRI), which measures blood flow to active brain regions. Top left: composite fMRI of healthy volunteers told to imagine themselves swimming; bottom left, single volunteer subject response. Top and bottom right: two views of the brain scan of a patient given the same instructions showing a positive response. Insets show a time series in which activity in the supplementary motor area (SMA) of the cortex is overlaid onto the task blocks (blue, sports imagery; grey, rest).  Credit: Adapted from Bardin et al., 2011 , one of the many studies contributing to the NEJM analysis.

With surprising frequency, patients with severe brain injury can show clear signs of cognitive function on brain scans in response to requests to carry out complex mental work, even when they can’t move or speak, according to an international study co-led by Weill Cornell Medicine and NewYork-Presbyterian investigators.

The study , published Aug. 14 in the New England Journal of Medicine, was the largest-ever investigation of the prevalence of this condition, which is called cognitive-motor dissociation. The researchers observed that among 241 patients in a coma or vegetative state who could not make visible responses to bedside commands, one-fourth had sustained and relevant cognitive responses as shown on electroencephalography (EEG) readouts or functional magnetic resonance imaging (fMRI) scans. The patients were tested with consent from a surrogate at six academic medical centers, all part of a larger consortium that undertook the study.

“We find that this kind of sharp dissociation of retained cognitive capabilities and no behavioral evidence of them is not uncommon,” said study corresponding author Dr. Nicholas Schiff, the Jerold B. Katz Professor of Neurology and Neuroscience in the Feil Family Brain and Mind Research Institute at Weill Cornell Medicine, a neurologist at NewYork-Presbyterian/Weill Cornell Medical Center and administrative lead of the consortium. “I think we now have an ethical obligation to engage with these patients, to try to help them connect to the world.”

The patients in the study were evaluated at NewYork-Presbyterian/Weill Cornell Medical Center, NewYork-Presbyterian/Columbia University Irving Medical Center, The Rockefeller University Hospital and Massachusetts General Hospital in the United States, and in medical centers at the University of Cambridge, the University of Liege, and the University of Paris. The Icahn School of Medicine at Mount Sinai served as the coordinating center of the study and conducted the statistical analysis of the patient data.

Cognitive-motor dissociation is thought to be closer to the better-known “locked-in” state that isolates an intact brain, typically through either strokes or degeneration of only the motor neurons in amyotrophic lateral sclerosis. But it is seen in patients with more extensive brain injuries who otherwise seem mostly or entirely unaware of their surroundings.

For the study, the researchers enrolled a total of 353 adults with “disorders of consciousness,” usually stemming from severe traumatic brain injuries or interrupted oxygen supply to the brain following strokes or heart attacks. Most were under care at home or in long-term care facilities, and the median time from injury was about eight months.

The researchers repeatedly asked each patient to perform a series of continuous motor tasks (e.g., “keep wiggling your toes”), as well as motor-related cognitive tasks (“keep imagining wiggling your toes”) for multiple bouts of 15 to 30 seconds of performance separated by equal length rest periods, using rigorous protocols the investigators had designed and validated to avoid false positives.

Of the 241 patients who were unable to demonstrate bedside command following, 25% were able to perform the cognitive tasks—matching patterns of EEG- and/or fMRI-measured brain activity seen in healthy subjects in response to the same commands.

While a higher percentage (38%) of the 112 patients who demonstrated motor response to spoken commands at the bedside performed these cognitive tasks, the majority of these patient controls did not demonstrate the cognitive performance. This further dissociation emphasizes that the fMRI and EEG mental imagery tasks demand the sustained use of several cognitive resources, such as short-term memory, that are not required for following bedside commands or even simple communication. The fact that one quarter of the motor-unresponsive patients with cognitive-motor dissociation successfully performed the tasks suggests that many seemingly unconscious patients may be aware and capable of cognition, the researchers said.

“Some patients with severe brain injury do not appear to be processing their external world. However, when they are assessed with advanced techniques such as task-based fMRI and EEG, we can detect brain activity that suggests otherwise,” said lead study author Dr. Yelena Bodien , an investigator for the Spaulding-Harvard Traumatic Brain Injury Model Systems and Massachusetts General Hospital’s Center for Neurotechnology and Neurorecovery . “These results bring up critical ethical, clinical and scientific questions – such as, how can we harness that unseen cognitive capacity to establish a system of communication and promote further recovery?”

In the United States alone, the number of people estimated to be in a chronic vegetative state ranges from 5,000 – 42,000, while estimates for those in a minimally conscious state range from 112,000 to 280,000 individuals.

The findings are likely to lead to several new lines of research. One is to investigate easier methods of detecting this dissociation—methods that, unlike task-based fMRI and EEG, could be used in a greater variety of clinics.

Another is to explore the potential clinical value of detecting cognitive-motor dissociation, since prior studies suggest that patients with this condition may have a greater chance of recovery compared with those who cannot perform cognitive tasks.

“Just knowing that a patient has this ability to respond cognitively can be a game-changer in terms of life-support decisions and the degree of engagement of caregivers and family members,” Dr. Schiff said.

He added that the findings should also lead to studies of specific interventions—likely including brain-computer interfaces—to improve the quality of life for these patients and further boost their chances of recovery.

“What we need here is what we in our consortium have been trying to get started for 20 years: a sustained effort to benefit patients who have disorders of consciousness with systematic medical research, technology development and better clinical infrastructure,” Dr. Schiff said.

Dr. Barry Coller , physician-in-chief of The Rockefeller University Hospital, led the effort to develop a model clinical infrastructure to support the research and credits Dr. Schiff and Dr. Joseph J. Fins , the E. William Davis, Jr., MD Professor of Medical Ethics at Weill Cornell Medicine and chief of the Division of Medical Ethics at Weill Cornell Medicine and NewYork-Presbyterian/Weill Cornell Medical Center, with conceiving the study. “I realized the importance of bringing hope to these patients and their loved ones,” Dr. Coller said. “We are proud to be a part of this pioneering research, which has creatively harnessed all of the power of modern science, and we are very gratified by the results.”

The research reported in this story was primary funded by two large grants from the James S. McDonnell Foundation ; additional funding included support from the NIH Director’s Office through grant number DP2HD101400; the National Institute of Neurological Disorder and Stroke and the Eunice Kennedy Shriver National Institute of Child Health and Human Development, both part of the National Institutes of Health, through grant numbers R01NS106014, R03NS112760, R01HD051912; the National Institute on Disability and Rehabilitation Research, through grant number H133A120085; the National Institute on Disability, Independent Living, and Rehabilitation Research, through grant numbers 90DPTB0011 and 90DPTB0027; and the  National Center for Advancing Translational Sciences, part of the National Institutes of Health, through grant numbers UL1TR002384 and UL1TR001866.

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Understanding the brain is vital, not just to understand the biological mechanisms which give us our thoughts and emotions and which make us human, but for practical reasons. Understanding how the brain processes information can make a fundamental contribution to the development of new computing technology – neurorobotics and neuromorphic computing. More important still, understanding the brain is essential to understanding, diagnosing and treating brain diseases that are imposing a rapidly increasing burden on the world’s ageing populations.

Even a brain that is much smaller than the human brain, like the brain of a mouse, is so complex that it may never be possible to exhaustively measure all its anatomical features or to fully characterize the physiological interactions within and between its different levels of organization. But this may not be necessary. The structure of the brain and the physiology of its components are subject to tight biological constraints, which are reflected in experimental measurements. The Blue Brain exploits these interdependencies to build comprehensive digital reconstructions from the sparse experimental data that is available and to refine these reconstructions as the data improve. This ability makes the Blue Brain approach inherently scalable.

Simulations suggest that our reconstructions can accurately reproduce many phenomena reported in previous laboratory experiments – without changing the parameters of the reconstruction. As digital reconstructions are refined, expanded, and validated for new kinds of experiment, they can become an ever more valuable resource for neuroscience research, allowing experiments and providing insights that would not be possible with alternative approaches.

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Conflicts of Interest

• Sepahvand, T.; Power, K.D.; Qin, T.; Yuan, Q. The Basolateral Amygdala: The Core of a Network for Threat Conditioning, Extinction, and Second-Order Threat Conditioning. Biology 2023 , 12 , 1274. [ Google Scholar ] [ CrossRef ] [ PubMed ]
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• Lawson, L.; Spivak, S.; Webber, H.; Yasin, S.; Goncalves, B.; Tarrio, O.; Ash, S.; Ferrol, M.; Ibragimov, A.; Olivares, A.G.; et al. Alterations in Brain Activity Induced by Transcranial Magnetic Stimulation and Their Relation to Decision Making. Biology 2023 , 12 , 1366. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Nguyen, G.H.; Oh, S.; Schneider, C.; Teoh, J.Y.; Engstrom, M.; Santana-Gonzalez, C.; Porter, D.; Quevedo, K. Neurofeedback and Affect Regulation Circuitry in Depressed and Healthy Adolescents. Biology 2023 , 12 , 1399. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Pham, T.Q.; Matsui, T.; Chikazoe, J. Evaluation of the Hierarchical Correspondence between the Human Brain and Artificial Neural Networks: A Review. Biology 2023 , 12 , 1330. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Zhang, R.; Zeng, Y.; Tong, L.; Yan, B. Specific Neural Mechanisms of Self-Cognition and the Application of Brainprint Recognition. Biology 2023 , 12 , 486. [ Google Scholar ] [ CrossRef ] [ PubMed ]

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Keenan, J.P. The Science and Philosophy of the Brain and the Future of Neuroscience. Biology 2024 , 13 , 607. https://doi.org/10.3390/biology13080607

Keenan JP. The Science and Philosophy of the Brain and the Future of Neuroscience. Biology . 2024; 13(8):607. https://doi.org/10.3390/biology13080607

Keenan, Julian Paul. 2024. "The Science and Philosophy of the Brain and the Future of Neuroscience" Biology 13, no. 8: 607. https://doi.org/10.3390/biology13080607

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