Category: Cognitive Science/Neuroscience

Salk and Carnegie Mellon researchers developed a new model for building efficient networks by studying the rate at which the brain prunes back some of its connections during development. In this model, nodes (such as neurons or sensors) make too many connections (left) before pruning back to connections that are most relevant (right). The team applied their synaptic pruning-based algorithm to air flight patterns and found it was able to create routes to allow passengers to reach their destinations efficiently. (credit: Salk Institute and Carnegie Mellon University)

The developing brain prunes (eliminates) unneeded connections between neurons during early childhood. Now researchers from the Salk Institute for Biological Studies and Carnegie Mellon University have determined the rate at which that happens, and the implications of that finding for computational networks.

Neurons create networks through a process called pruning. At birth and throughout early childhood, the brain’s neurons make a vast number of connections — many more than the brain actually needs to function. So as the brain matures and learns, it begins to quickly cut away connections that aren’t being used. When the brain reaches adulthood, it has about 50 to 60 percent less synaptic connections than it had at its peak in childhood. Understanding how the network of neurons in the brain organizes to form its adult structure is key to understanding how the brain learns and functions.

“By thinking computationally about how the brain develops, we questioned how rates of synapse pruning may affect network topology and function,” says Saket Navlakha, assistant professor at the Salk Institute’s Center for Integrative Biology and a former postdoctoral researcher in Carnegie Mellon’s Machine Learning Department. “We have used the resulting insights to develop new algorithms for constructing adaptive and robust networks in other domains.” The findings were recently published in an open-access paper in PLOS Computational Biology,

But the processes the brain and network engineers conventionally use to learn the optimal network structure are very different. Computer science and engineering networks initially contain a small number of connections and then add more connections as needed.

An improved computer-network algorithm based on brain pruning

“Engineered networks are built by adding connections rather than removing them. You would think that developing a network using a pruning process would be wasteful,” says Ziv Bar-Joseph, associate professor in Carnegie Mellon’s Machine Learning and Computational Biology departments. “But as we showed, there are cases where such a process can prove beneficial for engineering as well.”

The researchers first determined key aspects of the pruning process by counting the number of synapses present in a mouse model’s somatosensory cortex over time. After counting synapses in more than 10,000 electron microscopy images, they found that synapses were rapidly pruned early in development, and then as time progressed, the pruning rate slowed.

The results of these experiments allowed the team to develop an algorithm for designing computational networks based on the brain pruning approach. Using simulations and theoretical analysis they found that the neuroscience-based algorithm produced computer networks that were much more efficient than the current engineering methods. The flow of information was more direct, and provided multiple paths for information to reach the same endpoint, minimizing the risk of network failure.

Optimizing airline routes as a test case

Delta U.S. routes (not the focus of this study) (credit: David Galvin/University of Notre Dame)

“We took this high-level algorithm that explains how neural structures are built during development and used that to inspire an algorithm for an engineered network,” says Alison Barth, professor in Carnegie Mellon’s Department of Biological Sciences and member of the university’s BrainHubSM initiative. “It turns out that this neuroscience-based approach could offer something new for computer scientists and engineers to think about as they build networks.”

Improving airline efficiency and robustness using pruning algorithms. Based on actual data of travel frequency among 122 popular cities from the 3rd quarter of 2013, researchers derived a comparison of efficiency (travel time in terms of number of hops) and robustness (number of alternative routes with the same number of hops) using different algorithms. Decreasing-rate pruning produced more efficient networks with similar robustness. (credit: Saket Navlakha1et al. PLOS Computational Biology)

As a test of how the algorithm could be used outside of neuroscience, Navlakha applied the algorithm to flight data from the U.S. Department of Transportation. He found that the synaptic pruning-based algorithm created the most effective routes to allow passengers to reach their destinations.

“We realize that it wouldn’t be cost effective to apply this to networks that require significant infrastructure, like railways or pipelines,” Navlakha said. “But for those that don’t, like wireless networks and sensor networks, this could be a valuable adaptive method to guide the formation of networks.”

Abstract of Decreasing-rate Pruning Optimizes the Construction of Efficient and Robust Distributed Networks

Robust, efficient, and low-cost networks are advantageous in both biological and engineered systems. During neural network development in the brain, synapses are massively over-produced and then pruned-back over time. This strategy is not commonly used when designing engineered networks, since adding connections that will soon be removed is considered wasteful. Here, we use this process as inspiration for a new network design algorithm, which also led to a new experimental hypothesis. In particular, we show that for large distributed routing networks, network function is markedly enhanced by hyper-connectivity followed by aggressive pruning and that the global rate of pruning, a developmental parameter not previously studied by experimentalists, plays a critical role in optimizing network structure. We first used high-throughput image analysis techniques to quantify the rate of pruning in the mammalian neocortex across a broad developmental time window and found that the rate is decreasing over time. Based on these results, we analyzed a model of computational routing networks and show using both theoretical analysis and simulations that decreasing rates lead to more robust and efficient networks compared to other rates. We also present an application of this strategy to improve the distributed design of airline networks. This inspiration from neural network formation suggests effective ways to design distributed networks across several domains.

A human brain organoid showing complex internal organization, with immature proliferating cells (red) and a surrounding layer of maturing neurons (green) (credit: Jessica Mariani)

Taking a radical research approach to understanding autism, Yale School of Medicine researchers converted skin cells from autism patients into stem cells and then grew them into tiny brains in a dish — revealing unexpected mechanisms of the disease.

The study was published in an open-access paper today (July 16) in the journal Cell.

Most autism research has taken the approach of combing through patient genomes for mutations that may underlie the disorder and then using animal or cell-based models to study the genes and their possible roles in brain development. That has left more than 80% of autism cases with no clear genetic cause.

“Instead of starting from genetics, we’ve started with the biology of the disorder itself to try to get a window into the genome,” says senior author Flora Vaccarino the Harris Professor of Child Psychiatry and Professor or Neurobiology at Yale.

The clinical characteristics of autism are complex and wide-ranging, making the prospect of finding common underlying factors slim. So the researchers focused on the approximately one-fifth of autism patients that share a distinctive feature correlated with disease severity — an enlarged brain.

Unexpected neuron-type imbalance

The “brain organoids” that resulted are just a few millimeters about a fifth of a millimeter in diameter but mimic the basics of early human brain development, roughly corresponding to the first few months of gestation. When the researchers analyzed the patient organoids, they uncovered altered expression networks for genes controlling neuronal development.

The patient organoids showed an unexpected overproduction of inhibitory neurons that quiet down neural activity, while those that excite the partners they’re wired to were unaffected, leading to an imbalance in neuron type. Remarkably, by suppressing the expression of a single gene whose expression was abnormally increased in patient organoids, the authors were able to correct this bias, suggesting that it may be possible to intervene clinically to restore neuronal balance.

The authors are now using their data to home in on the difficult-to-find mutations or epigenetic changes responsible for the gene expression alterations and neuronal imbalance observed in the study. Efforts to extend their growth to later embryonic stages are also under way by a number of groups and will allow even further insights into the disease mechanisms.

“This study speaks to the importance of using human cells and using them in an assay that could bring a better understanding of the pathophysiology of autism and with that, possibly better treatments,” according to Vaccarino.

The success of the approach also suggests that similar methods might be used to gain important insights into other human developmental diseases that have until now been difficult to crack open.

Abstract of FOXG1-Dependent Dysregulation of GABA/Glutamate Neuron Differentiation in Autism Spectrum Disorders

Autism spectrum disorder(ASD) is a disorder of brain development. Most cases lack a clear etiology or genetic basis, and the difficulty of re-enacting human brain development has precluded understanding of ASD pathophysiology. Here we use three-dimensional neural cultures (organoids) derived from induced pluripotent stem cells (iPSCs) to investigate neurodevelopmental alterations in individuals with severe idiopathic ASD. While no known underlying genomic mutation could be identified, transcriptome and gene network analyses revealed upregulation of genes involved in cell proliferation, neuronal differentiation, and synaptic assembly. ASD-derived organoids exhibit an accelerated cell cycle and overproduction of GABAergic inhibitory neurons. Using RNA interference, we show that overexpression of the transcription factor FOXG1 is responsible for the overproduction of GABAergic neurons. Altered expression of gene network modules and FOXG1 are positively correlated with symptom severity. Our data suggest that a shift toward GABAergic neuron fate caused by FOXG1 is a developmental precursor of ASD.

Each of the five panels shows a memory snapshot created by hundreds of place cells while the rat was physically stationary at the top of the 1.8 m track (black). The time difference between the first and last snapshot is a mere one-fifth of a second; the positions represented by the neurons are shown in bright colors. (credit: Reprinted with permission from Pfeiffer and Foster, Science, 349:180)(2015)

How do you visualize your memory? As a continuous video recording, or as a series of snapshots strung together?

According to Johns Hopkins scientists, who actually watched nerve cells firing in the brains of rats as they planned where to go next, it’s a series of snapshots — more like jumping across stepping stones than walking across a bridge.

“Our data from rats suggest that our memories are actually organized that way, with one network of neurons responsible for the snapshots and another responsible for the string that connects them,” says David Foster, Ph.D., an assistant professor of neuroscience at the Johns Hopkins University School of Medicine.

A summary of their experiments, published in the journal Science on July 10, sheds light on what memories are and how they form,and how the system could fail.

The 2014 Nobel Prize in Physiology or Medicine was awarded for the discovery of a positioning system in the brain. Grid cells, together with other cells in the entorhinal cortex of the brain that recognize the direction of the head and the border of the room, form networks with the place cells in the hippocampus. This circuitry constitutes a comprehensive positioning system in the brain that appears to have components similar to those of the rat brain. (Credit: Mattias Karlén/The Nobel Committee for Physiology or Medicine)

Foster and his team focused their experiments on a group of nerve cells in the hippocampus of the brain known — in animals and people — for creating a mental “map” of experiences, or memories. The cells are called place cells because they each develop a preferred place in an environment and mainly fire only when the animal is in that place.

In previous experiments, Foster’s group learned that when a rat wants to get from point A to point D, it maps out its route mentally before starting on its journey. They could “see” this happen by implanting many tiny wires in the brains of the rats so that they could monitor the activity of more than 200 place cells at a time. By doing so, they found that the place cells representing point A would fire first, followed by those for point B, then C and D.

Maps of gaps

Their latest work, says Foster, is essentially a higher resolution “map” of the same process, which revealed gaps in between points A, B, C and D, corresponding to actual “gaps”  between discrete “memories” in the rats’ brains.

“The trajectories that the rats reconstructed weren’t smooth,” says Foster. “We were able to see that neural activity ‘hovers’ in one place for about 20 milliseconds before ‘jumping’ to another place, where it hovers again before moving on to the next point.”

He says that what seems to be happening during the hovering phase is an individual memory is being strengthened or focused. “At first, you get a ‘blurry’ representation of point A because a bunch of place cells all around point A fire, but, as time passes, the activity becomes more focused on A,” he explains. Then the activity jumps to a “blurry” version of B, which then gets focused.

“We think that there is a whole network of cells dedicated to this process of fine-tuning and jumping,” says Foster. “Without it, memory retrieval would be even messier than it is.”

In the future, the group plans to see what happens when certain memories within a path go missing, hoping to learn more about what memories are and how we can preserve them in those suffering from Alzheimer’s disease and other cognitive disorders.

Abstract of Autoassociative dynamics in the generation of sequences of hippocampal place cells

Neuronal circuits produce self-sustaining sequences of activity patterns, but the precise mechanisms remain unknown. Here we provide evidence for autoassociative dynamics in sequence generation. During sharp-wave ripple (SWR) events, hippocampal neurons express sequenced reactivations, which we show are composed of discrete attractors. Each attractor corresponds to a single location, the representation of which sharpens over the course of several milliseconds, as the reactivation focuses at that location. Subsequently, the reactivation transitions rapidly to a spatially discontiguous location. This alternation between sharpening and transition occurs repeatedly within individual SWRs and is locked to the slow-gamma (25 to 50 hertz) rhythm. These findings support theoretical notions of neural network function and reveal a fundamental discretization in the retrieval of memory in the hippocampus, together with a function for gamma oscillations in the control of attractor dynamics.

(credit: Newmarket Films)

Gerald Burgess, a University of Leicester lecturer in clinical psychology, has described treating an individual who suffered a “Memento/Before I Go to Sleep“-style anterograde amnesia memory loss after a treatment at a dentist — “like nothing we have ever seen before.”

Since the one-hour root-canal treatment, during which the a 38-year-old man from the UK was given a local anesthetic, the individual cannot remember anything beyond 90 minutes.

He is fully aware of his identity and his personality did not change, says Burgess, but every day the man thinks it is the day of his dental appointment. He has to manage his life through an electronic diary and access to prompts.

Burgess has now described the study, done a decade ago, in an open-access paper published in May in the journal Neurocase. He is also appealing for people who know of someone who might have suffered similar symptoms of memory loss, or medical or allied health professionals working with someone like this, to contact him to build up knowledge and evidence in this field of study.

Possible explanations

Burgess notes that “what we did know about from decades of research and hundreds of case studies, is that bilateral damage to the hippocampal and/or diencephalon structures causes profound amnesia … [but] we should perhaps not be so stuck in thinking that profound amnesia only occurs in the context of visible damage to the brain’s hippocampal and/or diencephalon structures.

“Those structures appear just to be needed for the initial holding or retention of information before engrams then proceed slowly through several other neuro-electrical and neuro-chemical events, before finally permanent memories are stored, and that something can occur at some later point in this process to vanquish the memory trace permanently.

“An acquired or manifest deficiency of protein synthesis, required for permanent re-structuring of synapses in the brain, seemed an intriguing speculation, and one we hope there might be further human research into. This speculation was sparked by two seemingly key coincidences of one, timing when this protein synthesis stage occurs coincides with the patient’s forgetting at 90 minutes or thereabouts, and two, both ‘episodic’ and ‘procedural’ memories appear to require successful protein synthesis to occur for long-term memory permanence, and the patient cannot retain any new either episodic or procedural memories — and this is unusual compared to traditional cases of amnesia.”

The work was done in collaboration with Bhanu Chadalavada Consultant Psychiatrist at Northamptonshire Healthcare Foundation NHS Trust.

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A man creates a strange system to help him remember things; so he can hunt for the murderer of his wife without his short-term memory loss being an obstacle.

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A woman wakes up every day, remembering nothing as a result of a traumatic accident in her past. One day, new terrifying truths emerge that force her to question everyone around her.

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A man afraid of commitment thinks he’s finally found the girl of his dreams, until he discovers she has short-term memory loss and forgets him the very next day.

Abstract of Profound anterograde amnesia following routine anesthetic and dental procedure: a new classification of amnesia characterized by intermediate-to-late-stage consolidation failure?

Anterograde amnesia caused by bilateral hippocampal or diencephalon damage manifests in characteristic symptoms of preserved intellect and implicit learning, and short span of awareness with complete and rapid forgetting of episodic material. A new case, WO, 38-year-old male with anterograde amnesia, in the absence of structural brain changes or psychological explanation is presented, along with four comparison cases from the extant literature that share commonalities between them including preserved intellect, span of awareness greater than working memory, and complete forgetting within hours or days following successful learning, including notably for both explicit and implicit material. WO’s amnesia onset coincided with anesthetic injection and root canal procedure, with extended vasovagal-like incident. The commonalities between the five cases presented may suggest a shared biological mechanism involving the breakdown of intermediate-to-late-stage consolidation that does not depend on the structural integrity of the hippocampi. Speculation on the mechanism of consolidation breakdown and diagnostic implications are discussed.