Category Archives: Research

Increased learning and memory through neurogenesis has a likely upper limit: a Q&A with Neurocrates

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This post is a question-and-answer conversation with an imaginary scholar named Neurocrates.

It uses the Neurotic Method.

Stephen: Hello, Neurocrates.

Neurocrates: You named me that just to make a pun about methodology, didn’t you?

S: Maybe. Thank you for visiting here today. I understand that you study neurogenesis and its effects on cognitive performance.

N: Yes. Take what I say with a grain of salt.

S: Ok. Let’s start with the essentials. What is neurogenesis?

N: Neurogenesis is the creation of new neurons.

The brain has stem cells, just like other parts of the body, and new neurons come from neural stem cells. The neural stem cells produce a handful of progenitor cells, which then divide many times to amplify the population of new neuron. These neural stem cells are found in the olfactory bulb (which is responsible for your sense of smell) and the dentate gyrus of the hippocampus (which is involved in learning and memory).

Neurogenesis is interesting to researchers because it has been shown to cause significant increases in learning, memory, and cognitive performance. When we increase neurogenesis in normal rats, they become much better at solving puzzles and remembering things. 1

S: Okay, so we have a continual stream of new neurons that is generated from neural stem cells. What happens to these neurons as they mature and integrate into the existing neural network?

N: As these new neuron cells mature and begin to integrate into the network of surrounding older cells, about 80% of them are “pruned” and die off intentionally. This pruning is how a functional network is established – the neurons that survive are those that receive the most relevant data, and are activated the most times.

You can compare the formation of the brain’s functional network to sculpting a statue out of a block of stone: the network is what is left after carving out a lot of raw material. The remainder of the raw material – neurons, in this case, is what retains meaning. The function of the network is to parse information meaningfully. When neurons receive input, they do small parts of pattern detection, like finding edges. The most salient information is chiseled into the neural network, after lots of other less relevant data has passed through.

So the more neurons you have, the more features you can represent. I’ll give you a simple example. Here are three pictures of a toy dinosaur that are 50, 150, and 250 pixels across. You can see how pictures with more pixels can represent more details of the toy dinosaur.

walter-toy-dinosaur-real lowres walter-toy-dinosaur-real medreswalter-toy-dinosaur-real

S: The dentate gyrus in the hippocampus is one of the most dense cell layers. But new neurons are continually being added to it. How does it allow for new representations to integrate into a network that is already tightly packed?

N: Here’s one nifty thing about neurons:

After they have matured and incorporate into the network (about 4 weeks after progenation), they are more excitable for a short period of time. If there is new data entering the network that isn’t precisely represented by the old neurons, these newer, more excitable neurons are thus more likely to come to represent it. They will be recruited more often than their neighboring cells, and will form the basis for a unique sparse representation of the new data.

Therefore, at the behavioral level, there is a continual unique critical period for the small set of new cells in the hippocampus that have ‘come of age” and are ready to receive their representations from the outside world.

This also explains part of how we have temporal segregation of memory: I can roughly distinguish events that happened yesterday from events that happened two weeks ago, partially because there were new neurons that had ‘come of age’ and were representing the episodic information in different places.

S: What determines which neuron the new data gets sent to in the first place? What is the ‘routing function’ between sensory input and new neurons?

N: Each neuron detects a feature. So the more neurons you have, the higher resolution your network can detect things.

S: How do you test the relationship between neurogenesis on the biological level and “pattern separation” at the behavioral level?

N: One of the most common memory tasks in rodent studies is contextual spatial navigation. Rats are put into environments with slightly different decorations, and need to remember which hallway the food is stored in. As neurogenesis decreases, the rodent has less fine-grain resolution of contexts that they can distinguish.

But there are still unanswered questions. It could be the case that new neurons are increasing the overall plasticity in the network. Or, it could be the case that for any hippocampal task, the “resolution of pattern recognition” or other output is increased by new neurons, but it is hard to establish that.

S: Are these new neurons being generated at a constant rate, or is there something that makes them generate more or less?

N: Two of the main factors that influence neurogenesis are the level of stress in the environment, and the timing of development in the organism. Stressful environments cause a decrease in neurogenesis. Neurogenesis is especially high during childhood and decreases with age.

S: Cool. How does neurogenesis contribute to learning and forming new memories?

N: The most clear mechanism of new neurons is enabling better “pattern separation”. As more neurons are integrated into the functional network, the network can store higher resolution representations of new kinds of data. This pattern separation occurs with highest frequency in the dentate gyrus in the hippocampus.


S: Now for the key question: It seems like increasing the rate at which these new neurons form could increase the resolution of new information that could be represented in the network. More new information could be stored in the same amount of time. Is that true?

In other words, would simply linearly adding neurons increase learning?

N: Yes, but there is likely to be an upper limit. It’s possible that the rate of learning might plateau as you increased neurogenesis past a certain point. The reason is that  the large amount of new neurons might not fully integrate into the functional network. The neurons need to adjust to form a sparse representation and connect with existing neurons, and need time to do that.

It may be possible to overcome this effect by broadening the locations over which the new neurons are added (instead of adding them only to the hippocampus). It may also be possible to implant neural stem cells in other parts of the cortex to increase its growth.


S: So you’re suggesting that current models of how neurons integrate into the hippocampal network predict that there might be an upper limit to the gains realized by adding new neurons to the hippocampus. Are there ways to overcome that upper limit? Or might we realize significant gains before reaching that upper limit, such as to make it worthwhile to pursue?

N: In either case, one outstanding research question is the relationship between cognition and the size and rate of growth of both the hippocampus and cortex. Significant gains could be realized through linear increases in the growth of new neurons. As a very loose proxy, the the human brain is 4.8 times the size for a hypothetical monkey of the same body weight, and the human neocortex is 35% larger than predicted for a primate with as large a brain. Depending on the test, humans can arguably be much more than 4.8 times smarter than a monkey. 2

But that is a good question. The exact point of the upper limit of neurogenesis has never been tested. There are some things you could do if you wanted to research this more:

First, we could model this computationally! This would be an interesting research question: Based on a computational model of the hippocampus, what is the upper limit of the rate of neurogenesis that you can sustain, before it starts to interfere with the representations? What happens when the rate of neurogenesis is 2x, 5x, 20x the normal rate? Do the new neurons interfere with sparse coding or does the system scale? Does the  require higher amounts of input (as could be achieved through sensory extension) in order to scale, or can it sustainably increase the learning rate while the amount of incoming data stays constant?

If you like digging through literature, here is literature research question: You could find experiments that involve increasing neurogenesis in hippocampus, and find the corresponding % increase in performance on memory task. Then plot the increase of neurogenesis on the X-axis, and compare it to the increase in performance on the Y-axis. You would then ask how to extrapolate the line: would it plateau, stay linear, or curve upwards? This is a good computational question, depending on an accurate model of how the hippocampus works.

If you like playing in the lab, here is a biological experiment: What are the upper limits to the current methods for increasing neurogenesis? Is there a way to produce 5x more than has been done before?

Finally, here’s one more question, which I’m not sure how to answer:  if simply tweaking neurogenesis had big payoffs, wouldn’t evolution have already done it? Maybe not, or maybe the in-between steps to higher neurogenesis weren’t viable. It could be that the correct intervention couldn’t be produced through genetic tweaks – artificial interventions are needed. Also, humans haven’t had that much time to evolve, so the possibilities within our genome haven’t been fully explored.

S: Thanks for the feedback, Neurocrates!

N: No prob. May you spawn many new feature-detecting goo balls.


  • It is clear that adding more neurons to the hippocampus increases learning and memory. It is possible that the increase in learning and memory would asymptote after some point.
  • This asymptote is predicted by current models of how new neurons integrate into the new network: neurons form sparse representations, and there is not a neat one-to-one mapping between neurons and concepts.
  • However, there may still be significant gains realized before hitting this upper limit.



Can Stem Cells Be Used to Enhance Cognition? – A Survey

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In the recent article “Can Stem Cells Be Used to Enhance Cognition?” (2015) (html, pdf) , Goldberg and Blurton-Jones examine the potential to enhance cognition through (1) endogenous neurogenesis and (2) stem cell transplantation. This post is a summary of their findings.

This post goes into fairly deep technical detail. If you prefer, you can get the gist of the story in the summary section below.

An important but separate issue is whether neural stem cell implantation is ethical or desirable; social and ethical implications of this research are discussed elsewhere. 1  This post simply examines what is possible so far.

Stem cells are defined by two key attributes:
(i) they can self-renew, dividing to create near-perfect copies of themselves
(ii) they can differentiate to produce distinct mature cell types

The equilibrium between cell loss and cell replacement is well maintained by stem cells in most adult tissues, except for the pancreas, heart, and brain. As the brain gets older, its ability to maintain itself through producing new neurons is reduced.  (Rossi et al., 2008). This loss of this cell equilibrium in the brain is greatly correlated with age-related neurogenerative disorders like Parkinson’s and Alzheimer’s Disease.

Summary: multiple mechanisms connecting neurogenesis and cognition

Stem cells have direct and indirect influences on cognition through multiple mechanisms. 
Enhancing cognition through neural stem cells may more more complicated than “add new stem cells to your favorite areas of the brain to linearly improve their functioning.”
However, there is a growing body of evidence that transplantation of neural stem cells does indeed have reliable positive effects on cognition, and is a promising method for both treating neurological disorders and improving cognition in healthy adults. 2

Figure 8.2. Considerable evidence supports the notion that both adult neurogenesis and neural stem cell transplantation can contribute to cognition. Factors such as exercise, selective serotonin reuptake inhibitors (SSRIs), and inflammation can modulate adult neurogenesis, leading to enhanced or impaired cognition. BDNF, brain-derived neurotrophic factor; bFGF, basic fibroblast growth factor; ChAT, choline acetyltransferase; GDNF, glial cell–derived neurotrophic factor; IFN, interferon; IGF, insulin-like growth factor; IL, interleukin; TNF, tumor necrosis factor; NGF, nerve growth factor.

The Role of Endogenous Neurogenesis in Cognition

Until recently, scientists did not have strong evidence that the brain generates new neurons. Then, in 1998, Eriksson e. al.  demonstrated that humans exhibit adult neurogenesis in two key areas:

    • The dentate gyrus of the hippocampus
    • The Subventricular zone (SVZ) of the lateral ventricles 3

Areas of neurogenesis in the adult rat brain. Red – confirmed neurogenesis; pink – possible neurogenesis. From Gould (2007).

Since then, researchers have found that adult neurogenesis occurs in the hippocampus and SVZ throughout life 4, and that they form connections to other parts of the brain (emphasis is my own):

Furthermore, adult hippocampal neurogenesis seems to be substantial; roughly 700 new neurons are generated in each hippocampus per day and up to one third of all hippocampal granule cell neurons are replaced during one’s adult life. 5 
Ernst et al. (2014) most recently used the radiocarbon dating approach to provide compelling new data that SVZ-derived newborn neurons can also migrate into the adjacent striatum in humans, giving rise to cholinergic interneurons.

The existence of endogenous neural stem cells (NSCs) means that we can potentially insert new, healthy neurons where old neurons are dead or dysfunctional. It also means that we could add neurons to various regions of the brain to enhance their capability.

These profound discoveries continue to provoke the question, What are the functional consequences of adult neurogenesis?

The role of the adult neurogenesis in cognition, as studied in the dentate gyrus of the hippocampus

The hippocampus plays a critical role in encoding and retrieving memories. The hippocampus would be one of the places in the brain where it would be most practical for neurogenesis to occur, since newly-formed neurons integrate more readily into the surrounding functional network:

Support for this finding came in 2006, when studies showed that newborn granule cells of the dentate gyrus are more highly activaeed by a novel exploration task compared with mature neurons of the same region (Ramirez-Amaya et al., 2006). Possibly as a result of this increased excitability, newborn granule neurons also integrate more readily into memory-associated engrams than mature granule cells (Ge et al., 2007 and Tashiro et al., 2006)

Additionally, researchers found the corresponding expected negative correlation: patients with damaged hippocampi (from chemotherapy radiation) experienced significantly decreased neurogenesis, and this correlated with difficulty with memory, executive function, attention, and visuospatial function. 6

Endogenous Stem Cells in Aging and Disease

Neurogenesis seems to be modulated by chemokines (part of the immune system’s signaling proteins) in blood plasma. Age-related decline of neurogenesis seems to be partially caused by an increase in chemokine levels in the blood:

Villeda et al. (2011) showed that aged blood could reduce both neurogenesis and cognitive function in young mice. Furthermore, aged mice injected with the plasma of young mice exhibited increased hippocampal neurogenesis. Interestingly, the effects of old and young plasma seem to be mediated via specific chemokines such as CCL11: injection of this chemokine alone into young mice impaired both neurogenesis and cognition. Thus the peripheral immune system and changes in inflammatory state that occur with age seem to play a critical role in age-associated changes in neurogenesis.

Improving Cognition by Enhancing Neurogenesis

Factors that modulate adult neurogenesis:

  • exercise 7
  • selective serotonin reuptake inhibitors (SSRIs) 8
  • inflammation 9

Things that are known to contribute to adult neurogenesis:

  • Chronic low levels of the microglial-derived insulin-like growth factor 1 (IGF-1) and interferon
  • Radial glia
  • Astrocyte-derived molecules
    • In addition to their direct involvement in neurogenesis, astrocyte-derived molecules also seem to make distinct contributions
    • S100B – infusion of S100B for 7 days led to a significant increase in both neurognesis and hippocampla ependnt function (Kleindienst et al 2005)
    • Reports have suggested, for example, that (CNS) central nervous system–specific T cells are required for spatial learning and the maintenance of hippocampal neurogenesis in adulthood (Ziv et al., 2006).
  • Antidepressants
    • SSRIs
      • However, evidence that the mood-improving effects of antidepressants did not depend on neurogenesis, but rather neuronal remodeling, arose in 2008; the blockade of neurogenesis failed to diminish the antidepressant activity of several SSRIs (Bessa et al., 2009).
  • Trophic Factors
    • Intrahippocampal infusion of BDNF also has been reported to increase neurogenesis in adult rats (Scharfman et al., 2005),
    • other studies have shown that BDNF infusion can improve cognition (Blurton-Jones et al., 2009)
    • HOWEVER the precise mechanistic relationship between BDNF neurogenesis and cognition has yet to be directly examined.
  • Noninvasive methods
  • BDNF and IGF-1 are thought to be the principle factors modulating the effects of exercise on learninga dn mood disorders,
    • IGF-1 and VEGF are more strongly implicated in hippocampal neurogenesis (Ding et al., 2006 and Nichol et al., 2009).
    • Both BDNF and IGF-1gene expression are elevated after only a few days of exercise in rats and are crucial to the cognitive benefits of exercise because blockade of growth factor signaling prevents exercise-induced improvements ( Berchtold et al., 2005 and Trejo et al., 2001)


Improving Cognition with Stem Cell Transplantation

Neural Stem Cell Transplantation in Aging

Injection of neural stem cells (NSCs) into the lateral ventricle improved spatial learning and memory in rats:

One of the first studies to examine the potential effect of NSC transplantation in aging injected human NSCs into the lateral ventricle of aged rats, leading to improved performance in spatial learning and memory as measured in the Morris water maze task (Qu et al., 2001).

Neural Stem Cell Transplantation in Neurological Disease

We found that murine NSC transplantation in the triple transgenic (3xTg-AD) model of AD improves cognition in Morris water maze and novel object recognition tasks via a BDNF-dependent mechanism (Blurton-Jones et al., 2009).

NSC transplantation can improve cognitive function following ablation of CA1 hippocampal neurons (Yamasaki et al., 2007)

Syngeneic NSCs were transplanted bilaterally into the striatum of aged α-synuclein mice, and 1 month later motor and cognitive behavior was examined. NSCs survive in the striatum and begin to differentiate into glia (glial fibrillary acidic protein) and neurons (doublecortin) (Figure 8.4). In these initial studies we found robust improvements not only in motor function but also in cognitive function, and, again, BDNF seems to be central to these improvements.

Stem Cell Transplantation in the Healthy Adult Brain

Until recently, few studies have shown an enhanced benefit of stem cell transplantation in regularly-functioning adult brains.

In 2013, Han et al. (2013) showed that human glial progenitor transplantation into the frontal cortex of immune-deficient neonatal mice led to significant enhancements in the cognitive function of adult and aged mice. In contrast, transplantation of murine glial progenitors had no such effect.

Question: Why did human glial progenitor cells improve cognition in mice but transplantation of the mouse-derived glial progenitor cells didn’t?

One potential explanation for the differential effect between human and murine progenitors may relate to species-specific differences in calcium wave propagation, a mechanism by which astrocytes communicate. Human glial progenitor calcium waves propagated at least threefold faster than did mouse cells, which may be attributable to their much larger size and structural complexity.

These differences also likely contributed to the heightened basal level of excitatory transmission and enhanced long-term potentiation that also were observed in this study.

 Another study (Park et al 2013) modified NSCs to overexpress choline acetyltransferase (ChAT), which contributes to acetylcholine synthesis. Results:

Interestingly, this group found significant improvements in passive avoidance, Morris water maze performance, and spontaneous locomotor activity in aged mice receiving ChAT-expressing stem cells.

However, it is unknown how much the immune system plays a complicating factor in these studies.

Contribution of Different Transplanted Cell Types to Cognition

Neuronal Replacement

  • The traditional goal of NSC was to replace dead/ dysfunctional neurons for neurological disorders. In the context of Parkinsons Disease, this has been disappointing, yielding only mild effects on motor movement and no significant effects on cognition.
  • Arguments can be made for transplantation of NSCs and progenitors of other cell types (like astrocytes) that might influence cognition via more indirect mechanisms. (Again, see the complicating figure).

Glial Precursor and Astrocyte Transplantation

Most studies of glial progenitor transplantation focused on spinal cord disease and injury.

One exception: Bruckner and Arendt, (1992) compared capacity of fetal brain tissue and purified astrocytes to improve ethanol-induced cognitive deficits.

  • Found that astrocytes, but not fetal brain tissue grafts, could restore memory (as measured via radial arm maze). 10
  • Bradbury et al 1995 reported – astrocyte-induced cognitive imporvements likely resulted from altered immune and trophic activity.
  • Finally, recent developments in cell reprogramming research have identified that astrocytes may be a more useful parent cell type than the commonly used skin fibroblast (Tian et al., 2011).

Remaining Risks

  • Tumorigenesis. Because the neural stem cells replicate, they could be the seed of a tumor.
  • Delivering Stem Cells to the Brain. There is no easy way to do it.


There are two currently-known methods for adapting neural stem cells to enhance cognition:
  • increasing endogenous neurogenesis
  • directly transplanting stem cells into the brain
Further research aims to safely adapt these methods for clinical use.

Stem cells have direct and indirect influences on cognition through multiple mechanisms. There is a growing body of evidence that transplantation of neural stem cells does indeed have reliable positive effects on cognition, and is a promising method for both treating neurological disorders and improving cognition in healthy adults.

In future posts, I will examine more potential methods for inducing neurogenesis and neuroplasticity, and their potential effects on cognition.


  1. For an initial look at the ethics of neural stem cell transplantation, see Master 2007. A framework for assessing the ethics of general cognitive enhancement is here
  2. For example, Wu et. al (2008) found that neural stem cells with transgenic expression of human nerve growth factor (hNGF) implanted into rat brains showed remarkably improved capacity to integrate into host tissue, and continued secretion of neurotrophic factor over time. For more details on their hNGF-expressing neural stem cells, see my rough notes from the paper.
  3.  Along with the subgranular zone of dentate gyrus, the subventricular zone serves as a source of neural stem cells in the process of adult neurogenesis. It harbors the largest population of proliferating cells in the adult brain of rodents, monkeys and humans. – Gates (2004) 
  4.  (Ernst et al., 2014 and Spalding et al., 2013)
  5.  Ernst et al. (2014)
  6.  Raffa et al., 2006 and Staat and Segatore, 2005
  7.  reviewed by Cotman et al., 2007, Cotman and Berchtold, 2002, van Praag, 2008 and van Praag et-al, 2005
  8.  (Madsen et al., 2000, Perera et al., 2007, Li et al., 2009 and Peng et al., 2008 
  9.  Belarbi et al., 2012
  10.  Bruckner and Arendt, (1992) 

Research Agenda, Round 1: an initial survey

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You can view this post in the html text below, or the nicely-formatted pdf here: Research Agenda Version 1: Initial Survey.pdf

This post is a list of questions about various technologies that send information into or out of a brain, or change the way the brain processes information. By defining these questions, I hope to develop a better understanding of the large possibility space in modern brain technology. 1

Background Motivation

One potential way to increase human effectiveness would be to improve the functioning of the certain parts of the human brain. 2 We could examine the input, processing, and output stages of the information flow, and look for ways to understand, improve, and extend each of those stages. Eventually, we may be able to create tools that improve the parts of the brain that make good decisions, solve tough problems, invent new ideas, understand moral reasoning, or experience empathy. If human brains became better at such mental abilities, I believe it would have positive ripple effects into many other areas of human activity.

 Breadth-First Approach

This article examines many possible pathways to that target. The initial approach is take an even survey of the potential tools to add to our toolbox. Our investigation will hold off on getting attached to specific solutions, or discarding broad classes of solutions for lack of known specifics.

It’s organized in rough order of levels of information: perception, language, motion, physiology, cellular biology; then macro- and micro- circuit systems in the brain. 3 Finally, there is an initial list of items to be understood in ethics and strategy.

Giving shape to a possibility space

A larger goal in this document is to provide a starting framework for researching technologies at multiple levels. I think that answers to these questions will help us start to navigate and define the possibility space in  brain technology.

 The questions and categories in this post don’t form a complete survey- they’re the the ones that are fruitful for conversation, conservative enough to post on the internet, and known to me at the time of writing this. 4

Over time, I may return to this post and continue to add more specific questions or categories.




Information- Software [Input + Output]

What are core design principles for software that harnesses group intelligence?

  •         Prediction Markets
  •         Large-scale citizen science i.e. Eyewire, Foldit
  •         Wikis/Forums

Perception [Input]

“Immersive Media” = Virtual Reality + Gesture Tracking + Haptic Feedback

Virtual Reality

  • Are there good examples (prototypes, concept sketches, or from science fiction) of using Virtual Reality or Augmented Reality for the following:
    • Information visualization
    • Data analysis
    • Life and physical science education (biology, chemistry, physics)
    • Math education (linear algebra with actual 4D vectors)
    • Medical operations
    • Clinical psychology
    • Rationality training / real world cognitive bias or puzzle solving exercises
    • Formal research experiments in social psychology or perception
  • Are there efforts to combine avatar control with natural language processing and generation, to create a platform for artificially intelligent character avatars? This could be a service/engine for building many kinds of games / applications.


  • Timelines for contact lenses, optical projection.

Natural Language Understanding and Generation [ Input + Output ]


  • Given a long piece of text, ability to generate a natural-sounding summary of most important ideas of the text.
  • Given a psychographic profile, ability to generate a simple story from the perspective of the character.
  • Upcoming milestones.

Motion Sensors [Output]

  • Gesture Tracking: Kinect, Leap, etc.
  • Worn on body: Myo

Motion Actuators [Output]

  • After refining/solving the vision problem (Rift C1?) Haptic feedback will be the bottleneck to immersive VR.
    • Alternative/creative attempts to to glove or suit? Air compression, Sound waves, Nanomaterials?
  • Have there been studies on using haptic feedback for mood regulation, neuroplastic training in healthy adults to develop extra senses, or just information “data sensualization”?


External Bio Sensors [Output]

  • Wearables – ECG, Respiration, etc.
    • Low information bandwidth, high amount of maker activity already.

Question: Biosensors:

Is it the case that (1) combinations of today’s external sensors (EEG, ECG…) along with Virtual Reality/ haptics can be used in radically different ways? Or is it the case that (2) their applications are confined to ‘meditation / neurofeedback / focus training’, and more advanced types of applications must wait for smaller BioMEMS or implantables? Right now, (2) seems more likely given the amount of people exploring vs. amount of actually new potential applications.

Question: Parasympathetic Nervous System – Regulation

What studies show the benefits of moderating physiology on cognition (as can be done with current biosensors)? Can this actually help people focus better? What is the highest recorded percent increase in concentration, creativity problem solving or related metrics in healthy adults, using biofeedback?


Bio-MEMS [Input + Output]


  • Can BioMEMS also act as actuators/controllers/builders (or are they mostly sensors?)
  • Bioengineering [Input, Processing, Output]

    • What types of genes / how many genes are addressable with modern gene therapy?
    • What kinds of neural tissues have had success with stem cell therapy?
    • Exploratory engineering: the hippocampus continuously generates new cells (neurogenesis). Could an increase in the rate of hippocampal neurogenesis influence its higher-level performance (say, spatial learning)? An initial study shows the brain is resilient to decreased neurogenesis, but the door remains open to experiments that increase neurogenesis.

Synthetic Bio [Input + Output]


Chemicals [Processing]

(There are a number of chemicals that affect mood and mental state, more and less common. I do not necessarily believe they should be used, but find it useful to understand the principles behind their effects.)

  • Are there studies on the combination of chemical stimulants with macro-scale stimulation ie tMS?
  • What about with immersive media, virtual reality, video games, group therapy circles, CBT, or other high-level psychological interventions?

The following sections are organized according to the general types of neuroengineering technologies in Ed Boyden’s MIT class.

Brain – Macro Circuit Reading [Output]

Noninvasive mapping and measurement.

  • PET, photoacoustic, MEG, EEG, fMRI, infrared imaging, x-rays.

Brain – Macro Circuit Stimulation [Input, Processing ]

Macrocircuit control.

  • Magnetic, electrical, ultrasonic, chemical, pharmacological/pharmacogenetic, thermal.

Brain – Micro Circuit Reading [Output]

Development of invasive mapping and measurement.

  • Electrodes
  • nanoprobes, nanoparticles
  • optical imaging and optical microscopy
  • endoscopy,
  • multiphoton microscopy, electron microscopy, light scattering,
  • bioluminscence,

Brain – Micro Circuit Stimulation [Input, Processing ]

Development of microcircuit control.

  • DBS, infrared optical stimulation, optogenetics,
  • nanoparticle-mediated control, uncaging
  • signaling control.

Ethics and Strategy

  • What is an appropriate target demographic for different levels of brain technology?
    • For discussions specific to cognitive enhancement, this book (Cognitive Enhancement, Hildt and Franke, 2013) offers an excellent, detailed discussion on the ethics of cognitive enhancement from multiple views. The introductory chapter offers an overview discussion.
  • Examine the relationship between neuroscience, intelligence amplification, and artificial intelligence safety.
    • Likelihood of neuro research to contribute to neuromorphic AI (seems likely).
    • Likelihood of various fields in neuroscience to lead to amplification of various forms of intelligence.
      • Opportunities to bolster moral reasoning / empathy in parallel with or before other forms of intelligence. (This would become very important as the strength of the intelligence amplification (IA) technology increases).
      • Amount of overlap between research contributing to intelligence amplification and research contributing to neuromorphic AI (some research areas may be completely separate and safer to pursue).
    • Likelihood of intelligence amplification to lead to improvements in AI safety (seems unlikely by itself, better chance when combined with improved moral reasoning / rationality).
    • Are there feasible ways to make IA tools available only available to select research scientists (such as those advancing technology safety).
      • Advancing activity in all fields in science and technology equally could have a neutral or negative effect, because of the high risks from some emerging technologies.
    • Overall benefits or costs of IA neuro research.
    • See also: Luke Muehlhauser on Intelligence Amplification and Friendly AI
  • Estimating the actual value of technological development, and the replaceability of a particular project.
    • If one desires to make a large social impact, they must take into account expected value of making particular technologies, when (1) very similar things could be made by others a few years down the road, and/or (2) their functionality may eventually be replaced by more advanced technologies. (Example: creating wearables now vs. personally working on biomems now vs waiting for biomems to arrive while doing something else.)
      • Consideration: The value of the project is the value of having the information or use of the tool sooner than we would have otherwise. 5
        • However, counterfactuals (and relative impact) are hard or impossible to compute well.
        • There may be some arguments for why this is not a well-founded concern, or even if it is well-founded, that it may not be practical to give it a lot of weight. For now, I believe this consideration does matter when determining what to prioritize.


Notes 6

  1. If you are interested in answering some of these questions, and are meticulous enough to read footnotes, you might be an excellent person to write or coauthor future posts on this blog. Drop me a line if that sounds interesting to you. 🙂
  2. It is my working hypothesis that strategic implementation of technologies that improve brain function would make humans more effective at the activities that matter (and would otherwise have a net positive effect), but this is not guaranteed. The second section on “Ethics and Strategy” offers some initial reasons this might not be true.
  3. A common ordering of levels in neuroscience is Cognitive > Systems > Cellular > Molecular.
  4. Disclaimer: I will acknowledge some potential reasons not to publish a blog post like this one. A detailed discussion about creating certain brain technologies could pose an information hazard (specifically, idea or attention hazards). Another potential pitfall is that it might distract myself or other people from more important activities that we could be doing otherwise (opportunity cost). Because the topics are relatively well-known and the blog has little social momentum, these disclaimers don’t concern me for now, but they may be revisited in the future.
  5. This view is described the first few pages of Chapter 15 in Nick Bostrom’s “Superintelligence.”
  6. Thanks to Madeeha Ghori for helpful feedback on this post.