Recursive language and modern imagination were acquired simultaneously 70,000 years ago

The lion-man sculpture from Germany (dated to 37,000 years ago) must have been first imagined by the artist by mentally synthesizing parts of the man and beast together and then executing the product of this mental creation in ivory. The composite artworks provide a direct evidence that by 37,000 years ago humans have acquired prefrontal synthesis.
Image by JDuckeck
[Public domain, https://commons.wikimedia.org/wiki/File:Lion_man_photo.jpg, Wikimedia Commons]

A genetic mutation that slowed down the development of the prefrontal cortex (PFC) in two or more children may have triggered a cascade of events leading to acquisition of recursive language and modern imagination 70,000 years ago.

This new hypothesis, called Romulus and Remus and coined by Dr. Vyshedskiy, a neuroscientist from Boston University, might be able to solve the long-standing mystery of language evolution. It is published in the open-science journal Research Ideas and Outcomes (RIO).

Numerous archeological and genetic evidence have already convinced most paleoanthropologists that the speech apparatus has reached essentially modern configurations before the human line split from the Neanderthal line 600,000 years ago. Considering that the chimpanzee communication system already has 20 to 100 different vocalizations, it is likely that the modern-like remodeling of the vocal apparatus extended our ancestors’ range of vocalizations by orders of magnitude. In other words, by 600,000 years ago, the number of distinct verbalizations used for communication must have been on par with the number of words in modern languages.

On the other hand, artifacts signifying modern imagination, such as composite figurative arts, elaborate burials, bone needles with an eye, and construction of dwellings arose not earlier than 70,000 years ago. The half million-year-gap between the acquisition of the modern speech apparatus and modern imagination has baffled scientists for decades.

While studying acquisition of imagination in children, Dr. Vyshedskiy and his colleagues discovered a temporal limit for the development of a particular component of imagination. It became apparent that modern children who have not been exposed to full language in early childhood never acquire the type of active constructive imagination essential for juxtaposition of mental objects, known as Prefrontal Synthesis (PFS).

Dr. Vyshedskiy explains:

“To understand the importance of PFS, consider these two sentences: “A dog bit my friend” and “My friend bit a dog.” It is impossible to distinguish the difference in meaning using words or grammar alone, since both words and grammatical structure are identical in these two sentences. Understanding the difference in meaning and appreciating the misfortune of the 1st sentence and the humor of the 2nd sentence depends on the listener’s ability to juxtapose the two mental objects: the friend and the dog. Only after the PFC forms the two different images in front of the mind’s eye, are we able to understand the difference between the two sentences. Similarly, nested explanations, such as “a snake on the boulder to the left of the tall tree that is behind the hill,” force listeners to use PFS to combine objects (a snake, the boulder, the tree, and the hill) into a novel scene. Flexible object combination and nesting (otherwise known as recursion) are characteristic features of all human languages. For this reason, linguists refer to modern languages as recursive languages.”

Unlike vocabulary and grammar acquisition, which can be learned throughout one’s lifetime, there is a strong critical period for the development of PFS and individuals not exposed to conversations with recursive language in early childhood can never acquire PFS as adults. Their language is always lacking understanding of spatial prepositions and recursion that depend on the PFS ability. In a similar manner, pre-modern humans would not have been able to learn recursive language as adults and, therefore, would not be able to teach recursive language to their own children, who, as a result, would not acquire PFS. Thus, the existence of a strong critical period for PFS acquisition creates a cultural evolutionary barrier for acquisition of recursive language.

The second predicted evolutionary barrier was a faster PFC maturation rate and, consequently, a shorter critical period. In modern children the critical period for PFS acquisition closes around the age of five. If the critical period in pre-modern children was over by the age of two, they would have no chance of acquiring PFS. A longer critical period was imperative to provide enough time to train PFS via recursive conversations.

An evolutionary mathematical model, developed by Dr. Vyshedskiy, predicts that humans had to jump both evolutionary barriers within several generations since the “PFC delay” mutation that is found in all modern humans, but not in Neanderthals, is deleterious and is expected to be lost in a population without an associated acquisition of PFS and recursive language. Thus, the model suggests that the “PFC delay” mutation triggered simultaneous synergistic acquisition of PFS and recursive language.

This model calls for:

  • two or more children with extended critical period due to “PFC delay” mutation;
  • these children spending a lot of time talking to each other;
  • inventing the recursive elements of language, such as spatial prepositions;
  • acquiring recursive-conversations-dependent PFS;
  • teaching recursive language to their offsprings.

The hypothesis is named after the celebrated twin founders of Rome, Romulus and Remus. Similar to legendary Romulus and Remus, whose caregiver was a wolf, the real children’s caregivers had an animal-like communication system with many words, but no recursion. Their parents could not have taught them spatial prepositions or recursion; children had to invent recursive elements of language themselves. Such an invention of a new recursive language has been observed in contemporary children, for example among deaf children in Nicaragua.

“The acquisition of PFS and recursive language 70,000 years ago resulted in what was in essence a behaviorally new species: the first behaviorally modern Homo sapiens,” concludes Dr. Vyshedskiy. “This newly acquired power for fast juxtaposition of mental objects in the process of PFS dramatically facilitated mental prototyping and led to fast acceleration of technological progress. Armed with the unprecedented ability to mentally simulate any plan and equally unprecedented ability to communicate it to their companions, humans were poised to quickly become the dominant species.”

Humans acquired an ability to trap large animals and therefore gained a major nutritional advantage. As the population grew exponentially, humans diffused out of Africa and quickly settled in the most habitable areas of the planet, arriving in Australia around 50,000 years ago. These humans were very much like modern humans since they possessed both components of full language: the culturally transmitted recursive language along with the innate predisposition towards PFS, enabled by the “PFC delay” mutation.

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Original source:

Vyshedskiy A (2019) Language evolution to revolution: the leap from rich-vocabulary non-recursive communication system to recursive language 70,000 years ago was associated with acquisition of a novel component of imagination, called Prefrontal Synthesis, enabled by a mutation that slowed down the prefrontal cortex maturation simultaneously in two or more children – the Romulus and Remus hypothesis. Research Ideas and Outcomes 5: e38546. https://doi.org/10.3897/rio.5.e38546

New collection in RIO Journal devoted to neuroscience projects from 2016 Brainhack events

A new collection devoted to neuroscience projects from 2016 Brainhack events has been launched in the open access journal Research Ideas and Outcomes (RIO). At current count, the “Brainhack 2016 Project Reports” collection features eight Project Reports, whose authors are applying open science and collaborative research to advance our understanding of the brain.

Seeking to provide a forum for open, collaborative projects in brain science the Brainhack organization has found a like-minded partner in the innovative open science journal RIO. The editor of the series is Dr. R. Cameron Craddock, Computational Neuroimaging Lab, Child Mind Institute and Nathan S. Kline Institute for Psychiatric Research, USA. He is joined by co-editors Dr. Pierre Bellec, Unité de neuroimagerie fonctionnelle, Centre de recherche de l’institut de gériatrie de Montréal, Canada, Dr. Daniel S. Margulies, Max Planck Research Group “Neuroanatomy & Connectivity“, Max Planck Institute for Human Cognitive and Brain Sciences, Dr. Nolan Nichols, Genetech, USA, and Dr. Jörg Pfannmöller, University of Greifswald, Germany.

The first project description published in the collection is a Software Management Plan presenting a comprehensive set of neuroscientific software packages demonstrating the huge potential of Gentoo Linux in neuroscience. The team of Horea-Ioan Ioanas, Dr. Bechara John Saab and Prof. Dr. Markus Rudin, affiliated with ETH and University of Zürich, Switzerland, make use of the flexibility of Gentoo’s environment to address many of the challenges in neuroscience software management, including system replicability, system documentation, data analysis reproducibility, fine-grained dependency management, easy control over compilation options, and seamless access to cutting-edge software release. The packages are available for the wide family of Gentoo distributions and derivatives. “Via Gentoo-prefix, these neuroscientific software packages are, in fact, also accessible to users of many other operating systems,” explain the researchers.

While quantifying lesions in a robust manner is fundamental for studying the effects of neuroanatomical changes in the post-stroke brain while recovering, manual lesion segmentation has been found to be a challenging and often subjective process. This is where the Semi-automated Robust Quantification of Lesions (SRQL) Toolbox comes in. Developed at the University of Southern California, Los Angeles, it optimizes quantification of lesions across research sites. “Specifically, this toolbox improves the performance of statistical analysis on lesions through standardizing lesion masks with white matter adjustment, reporting descriptive lesion statistics, and normalizing adjusted lesion masks to standard space,” explain scientists Kaori L. Ito, Julia M. Anglin, and Dr. Sook-Lei Liew.

Called Mindcontrol, an open-source web-based dashboard application lets users collaboratively quality control and curate neuroimaging data. Developed by the team of Anisha Keshavan and Esha Datta, both of University of California, San Francisco, Dr. Christopher R. Madan, Boston College, and Dr. Ian M. McDonough, The University of Alabama, Mindcontrol provides an easy-to-use interface, and allows the users to annotate points and curves on the volume, edit voxels, and assign tasks to other users. “We hope to build an active open-source community around Mindcontrol to add new features to the platform and make brain quality control more efficient and collaborative,” note the researchers.

At University of California, San Francisco, Anisha Keshavan, Dr. Arno Klein, and Dr. Ben Cipollini, created the open-source Mindboggle package, which serves to improve the labeling and morphometry estimates of brain imaging data. Using inspirations and feedback from a Brainhack hackathon, they built-up on Mindboggle to develop a web-based, interactive, brain shape 3D visualization of its outputs. Now, they are looking to expand the visualization, so that it covers other data besides shape information and enables the visual evaluation of thousands of brains.

Processing neuroimaging data on the cortical surface traditionally requires dedicated heavy-weight software suites. However, a team from Max Planck Institute for Human Cognitive and Brain Sciences, Free University Berlin, and the NeuroSpin Research Institute, France, have come up with an alternative. Operating within the neuroimaging data processing toolbox Nilearn, their Python package allows loading and plotting functions for different surface data formats with minimal dependencies, along with examples of their application. “The functions are easy to use, flexibly adapt to different use cases,” explain authors Julia M. Huntenburg, Alexandre Abraham, Joao Loula, Dr. Franziskus Liem, and Dr. Gaël Varoquaux. “While multiple features remain to be added and improved, this work presents a first step towards the support of cortical surface data in Nilearn.”

To further address the increasing necessity for tools specialised to process huge high-resolution brain imaging data in their anatomical detail, Julia M. Huntenburg gathers a separate team to work on another Python-based software. Being a user-friendly standalone package, this subset of CBSTools requires no additional installations, and allows for interactive data exploration at each processing stage.

Developed at the University of California, San Francisco, Cluster-viz is a web application that provides a platform for cluster-based interactive quality control of tractography algorithm outputs, explain the team of Kesshi M. Jordan, Anisha Keshavan, Dr. Maria Luisa Mandelli, and Dr. Roland G. Henry. It.

A project from the University of Warwick, United Kingdom, aims to extend the functionalities of the FSL neuroimaging software package in order to generate and report peak and cluster tables for voxel-wise inference. Dr. Camille Maumet and Prof. Thomas E. Nichols believe that the resulting extension “will be useful in the development of standardized exports of task-based fMRI results.”

More 2016 Brainhack projects are to be added to the collection.

Open neuroscience: Collaborative Neuroimaging Lab finalist for the Open Science Prize

Despite the abundance of digital neuroimaging data, shared thanks to all funding, data collection, and processing efforts, but also the goodwill of thousands of participants, its analysis is still falling behind. As a result, the insight into both mental disorders and cognition is compromised.

The Open Neuroimaging Laboratory framework, promises a collaborative and transparent platform to optimise both the quantity and quality of this invaluable brain data, ultimately gaining a greater insight into both mental disorders and cognition.

The project was submitted for the Open Science Prize competition by Katja Heuer, Max Planck Institute for Human Cognitive and Brain Sciences, Germany, Dr Satrajit S. Ghosh, Massachusetts Institute of Technology (MIT), USA, Amy Robinson Sterling, EyeWire, USA, and Dr Roberto Toro, Institut Pasteur, France. Amongst 96 submissions from all around the globe, it was chosen as one of six teams to compete in the second and final phase of the Prize.

Simply having access and being able to download brain magnetic resonance imaging (MRI) data is not enough to reap all potential benefits. In order for it to be turned into insight and knowledge, it needs to also be queried, pre-processed and analysed, which requires a substantial amount of human curation, visual quality assessment and manual editing. With research being rather patchy, a lot of efforts are currently redundant and unreliable.

On the other hand, the Open Neuroimaging Laboratory aims to aggregate annotated brain imaging data from across various resources, thus improving its searchability and potential for reuse. It is to also develop a tool that will facilitate and encourage the creation of distributed teams of researchers to collaborate together in the analysis of this open data in real time.

“Our project will help transform the massive amount of static brain MRI data readily available online into living matter for collaborative analysis,” explain the researchers.

“We will allow a larger number of researchers to have access to this data by lowering the barriers that prevent their analysis: no data will have to be downloaded or stored, no software will have to be installed, and it will be possible to recruit a large, distributed, group of collaborators online.”

“By working together in a distributed and collaborative way, sharing our work and our analyses, we should improve transparency, statistical power and reproducibility,” they elaborate. “Our aim is to provide to everyone the means to share effort, learn from each other, and improve quality of and trust in scientific output.”Untitled

Having already developed a functional prototype of the BrainBox web application, which provides an interactive online space for collaborative data analyses and discussions, the team will now turn it into a first version with an improved user experience, stability and documentation. Planned for the Open Science Prize Phase 2 are furthering the type of analyses and exploring the development of interfaces for database-wise statistical analyses.

In the spirit of the competition, the scientists have decided to release their code open source on GitHub to facilitate bug fixes, extension and maintainability.

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Original source:

Heuer K, Ghosh S, Robinson Sterling A, Toro R (2016) Open Neuroimaging Laboratory.Research Ideas and Outcomes 2: e9113. doi: 10.3897/rio.2.e9113

Mental synthesis experiment could teach us more about our imagination

While there is general consensus that the ability to imagine a never-before-seen object or concept is a unique and distinctive human trait, there is little that we know about the neurological mechanism behind it. Neuroscientist Dr. Andrey Vyshedskiy proposes a straightforward experiment that could test whether the ability to imagine a novel object involves the synchronization of groups of neurons, known as neuronal ensembles. Since the process involves mentally combining familiar images, scenes or concepts, Dr. Vyshedskiy proposes calling this process ‘mental synthesis.’ His research idea is published in the open-access Research Idea and Outcomes (RIO) Journal.

In the past scientists have managed to isolate and record from individual neurons that fire only when a particular object (e.g. an apple) is shown or imagined. Now, Dr. Andrey Vyshedskiy, Boston University, USA, and Rita Dunn, ImagiRation, USA, suggest an experiment that utilizes currently available methods for isolating so-called “object neurons” in the human brain.

Dr. Vyshedskiy proposes extending this experimental paradigm by isolating any two object neurons and monitoring their neuronal activity when these two objects are imagined together for the very first time. If two object neurons that fire only when a particular object is imagined can be identified, then the current experiment would seek to measure the firing activity when these two objects are imagined together. For example, an apple on top of a dolphin.

According to this Mental Synthesis Theory, the subject’s brain will trigger an increased firing rate in both object neurons and, more importantly, a synchronization of their activities would occur. “Understanding the basis of mental synthesis can shed light on the evolution of the brain in general and on the evolution of language in particular,” the authors point out.

“Since researchers can often identify several object-selective neurons within a single patient, multiple novel pairings of objects can be studied,” author Dr. Andrey Vyshedskiy explains. “Furthermore, morphing of more than two objects into one mental frame can also be investigated”.

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Original source:

Vyshedskiy A, Dunn R (2015) Mental synthesis involves the synchronization of independent neuronal ensembles. Research Idea and Outcomes (RIO) Journal: doi: 10.3897/rio.1.e7642