Did Homo erectus speak?

Posted on May 9, 2021 by James Cross

Did Homo erectus speak? is a new article on Aeon by Daniel Everett. The author makes the argument that the evidence of fairly sophisticated culture and technology by Home erectus suggests that this predecessor of modern humans likely had some form of language. This would also mean Neanderthals and other descendants of Homo erectus also likely had language.

Erectus settlements show evidence of culture – values, knowledge structures and social structure. This evidence is important because all these elements enhance each other. Evidence from the erectus settlement studied at Gesher Benot Ya’aqov in Israel, for example, suggests not only that erectus controlled fire but that their settlements were planned. One area was used for plant-food processing, another for animal-material processing, and yet another for communal life. Erectus, incredibly, also made sea craft. Sea travel is the only way to explain the island settlements of Wallacea (Indonesia), Crete and, in the Arabian Sea, Socotra. None of these were accessible to erectus except by crossing open ocean, then and now. These island cultural sites demonstrate that erectus was capable of constructing seaworthy crafts capable of carrying 20 people or more. According to most archaeologists, 20 individuals would have been the minimum required to found the settlements discovered.

To build and operate boats, erectus needed to talk about what material to collect, where to collect it, how to put the material together and so on – just what we ourselves would need to talk about in order to build a raft. In addition to the assembly of a raft, the planning for the trip as a whole, the reasoning for the undertaking, would have all required language.

We can therefore conclude that erectus required language.

The author goes on to define language as the ability to communicate with symbols. Complex grammar is not required. He continues with a proposal for how language evolved from tool use through development of icons and symbols, and association of sounds with symbols.

It has been noted before that many of the same brain regions used in tool making are the same or closely related to the regions used for language, thus hinting at an association between tool making and language. I find it not likely a coincidence that humans are only species that make sophisticated tools and also have a sophisticated language.

I have doubted the idea of some linguists (Chomsky most notably) that language materialized with no predecessor ability about 70 thousands years. I do believe there was a major shift in cognitive ability that included the capability for sophisticated and recursive grammar in about that time frame. This I discussed that in a previous post. Prior to modern language capabilities, I suspect, there was a form of language intermediate between the primitive signaling found in other species and modern language. This language might have been sign language combined with something similar to the primitive pidgin languages that spontaneously arise when people, not sharing similar languages, are thrown together and forced to communicate.

Posted in Human Evolution, Intelligence | 9 Comments

The Other Simulation Hypothesis

Posted on April 27, 2021 by James Cross

The simulation hypothesis is mostly associated with Nick Bostrom and his paper Are You Living in a Computer Simulation? Bostrom argues that we likely are living in a simulation and Elon Musk agrees with him. Frankly I think it is unlikely we are living in a simulation in the way Bostrom’s means it, but at any rate, it is impossible to prove or know and, as far as I can tell, would make no practical difference. In the end, if reality is a simulation, then being in a simulation or not being in one becomes for all practical purposes the same. There is a different way from Bostrom’s that we might be living in a simulation. This way could account for the occasional unreality of things most of us sometimes experience. It could account in a deeper way for why Bostrom might have thought about arguing we are living in a simulation.

Xerxes D. Arsiwalla, a physicist in Spain, was the lead author on a paper Are Brains Computers, Emulators or Simulators? In the paper, he draws a contrast between the brain as a computer vs the brain as a simulator. If the brain is a computer, he argues that “all cognitive processes can be described by algorithms running on a universal Turing machine”. This implies that consciousness is computational. On the other hand, if consciousness is non-computational, then it would be based on what he terms “non-classical logic”. He goes on to state:

Machines implementing non-classical logic might be better suited for simulation rather than computation (a la Turing). It is thus reasonable to pit simulation as an alternative to computation and ask whether the brain, rather than computing, is simulating a model of the world in order to make predictions and guide behavior. If so, this suggests a hardware supporting dynamics more akin to a quantum many-body field theory.

The paper goes on to discuss the limitations of computationalist view. He cites the Turing Halting problem and the Penrose tiling problem which can’t be solved by computation. Then he provides a “third example of a non-computable problem is the collapse of the wave-function or the measurement problem in quantum physics, which evades an algorithmic description”. Not mentioned here is another class of problem. This would be a type of problem that might be solved computationally but one that requires so much computer resources that it cannot be solved in any given amount of time.

An emulator “can be defined as any machine that can be used to specify dynamical states transitions of another system”. Computers can do emulations; however, a computer emulation would be subject to the limits of computation. Emulators can also be what the paper terms “dynamical systems-based simulations” which are not computational. The difference between the two is:

The difference of say computing an explicit solution of a differential equation in order to determine the trajectory of a system in phase space versus mechanistically mimicking the given vector field of the equation within which an entity denoting the system is simply allowed to evolve thereby reconstructing its trajectory in phase space. The former involves explicit computational operations, whereas the latter simply mimics the dynamics of the system being simulated on a customized hardware. For complex problems involving a large number of variables and/or model uncertainly, the cost of inference by computation may scale very fast, whereas simulations generating outcomes of models or counterfactual models may be far more efficient.

We finally reach the key argument of the paper. Brains are not computers. They are simulators.

Beyond this example of the motor system, if the brain is indeed tasked with estimating the dynamics of a complex world filled with uncertainties, including hidden psychological states of other agents… then in order to act and achieve its goals, relying on pure computational inference would arguably be extremely costly and slow, whereas implementing simulations of world models as described above, on its cellular and molecular hardware would be a more viable alternative. These simulation engines are customized during the process of learning and development to acquire models of the world. The simulated dynamics of these models lead to predictions as well as counterfactual hypotheses, which can then be passed through feedback control loops to correct for prediction errors. Note that these dynamics-based simulations differ from computer simulations. In the former, no specific function is being computed. Instead, as in control engineering, a model of the process is encoded (or learnt) in the network’s connectivity and is used to generate subsequent state transitions. More complex models require more complex network architectures and multi-scale biophysical dynamics, rather than heavy computational algorithms, which is presumably not what we see the brain to be designed for.

This explains much about the evolutionary origin of consciousness. Compared to actual computers, the brain and nervous systems must make the best with a relatively small amount of energy and a relatively slow computational speed. In simple organisms those limitations may not be fatal. However, the evolution of greater adaptive capability, the integration of more sensory data, and the development of broader repertoire of behaviors would eventually hit a computational barrier. The brain could not compute quickly enough to provide an selection advantage if it relied solely on a computational approach. The evolutionary response would be development of a simulation on top of a computational base. Unsurprisingly , our consciousness feels occasionally exactly like a simulation, although for the most part we think the simulation is real.

Posted in Consciousness, Human Evolution, Information | 47 Comments

Secret Ingredient?

Posted on April 20, 2021 by James Cross

Most great recipes have a secret ingredient. This is the spice that your grandmother leaves out of the recipe when she writes it down. The secret ingredients of Coca-Cola supposedly are only known to two people who are not allowed to travel together, but they have also been written down and stored in a vault. I listened to a cook on the radio swear that a single bay leaf made all the difference in the flavor of a particular recipe.

Does consciousness have a secret ingredient? If you think I’m talking about EM fields, not this time. Actually it may be something more obvious, not really all that secret, but something that actually gives us some insight on the evolution of consciousness, its nature, and how Friston’s theories fit into all of it.

In my comments on my last post, I mentioned there seemed to be a lack of clarity about how Friston’s free energy principle (FEP) related to consciousness. Since it seemed to be a theory as much or more about life itself, what made consciousness something unique in it? He didn’t seem to be claiming all life was conscious but he did seem to be claiming all life followed FEP. So, there must be something more than FEP by itself to explain consciousness. Both Friston and Solms called attention to learning but how do learning and consciousness connect? What is it about learning that needs consciousness or would create it? In a separate comment, I called attention to the yet previous post on electrical low frequency oscillations primarily in the Hydra but also in life in general. The paper discussed in that post does call out Friston as well as Buszáki in discussing low-frequency oscillations in the brain.

Let me speculate some and try to put some of the pieces together:

If the main goal of life is to maintain a stable internal state in the face of a changing external environment (part of FEP per my understanding), then maybe the best way of doing this is with electrical low-frequency oscillations. Think of a spinning top as a rough analogy. (Note: I understand the physics is not the same. This is an analogy.) The spinning top is stable but also in a slow motion of precession. If the top is tipped slightly, the top will adjust to account for change in gravity. There is also a rotational inertia that keeps the top stable when perturbed by outside bumps. Think now of an organism trying to maintain its form by using electrical oscillations to coordinate its different parts. There may be slow changes in form analogous to precession in the top and larger changes in response to external forces, but there is also a general resistance to change. The oscillations provide stability and structure to what might otherwise disintegrate into a dead, motionless mass. Hanson in the paper I referenced earlier conjectures that electrical low-frequency oscillations “may be the ultimate organism-wide electrical information integrators and communicators in all biological systems at all levels of scale, making them critical for maintenance of organism unity and coherent, adaptive behavior”.

As more complex organisms evolve, the same mechanisms are used resulting eventually in the development of brains and nervous systems with highly specialized cells involved in the low-frequency oscillations. These cells not provide for coordination in the body (basic things like heart and respiration rates), but also allow for movement and primitive reflexes in simple animals. According to the view of Simona Ginsburg and Eva Jablonka, as consciousness appears in more complex organisms, it correlates with complex learning.

Let me repeat a question I asked earlier: What is it about learning that needs consciousness or would create it? Or, to put it another way, what do we need to add to oscillating neurons to make complex learning possible?

Let me answer that it is simply memory that is the missing ingredient.

Solms makes his consciousness and feelings argument by saying (debatably) that feelings are always conscious. Let me make a similar statement. Consciousness does not exist when there is no ability to recall or create memories. When we are sound asleep and not dreaming, we cannot create memories. When we are completely anesthetized (assuming no resistance), we cannot create memories. Learning is impossible without an ability to store the results of the learning, and storing representations of sensual impressions, associations, motor actions is exactly what memory is.

Consciousness may be all about recalling memories, matching memories to current experience, and adjusting the internal memories to match the current experience. The matching of internal models with the external world is what FEP is all about. To be clear I am not talking about episodic memory (which does play a role with humans and maybe some other animals) but about more fundamental memory like memory we accumulated when we learned to see, walk, and ride a bicycle. I am also not suggesting that we might not be born with certain memories. Buszáki thinks that our brains come pre-wired with patterns of firing and consciousness is involved with matching and refining these patterns with experience of the real world. It is the same or similar process in either case. We are recalling patterns, matching them with the world, and refining them.

Consciousness exists to recall memories, match them with current experience, adjust them if necessary, and create new ones when required. The prediction and interference engine that is the brain could not do what it does with an ability to recall and store information. For some reason, consciousness is critical, maybe identical, to this process.

Posted in Consciousness, Friston, Memory | 55 Comments