“Man had always assumed that he was more intelligent than dolphins because he had achieved so much — the wheel, New York, wars and so on — whilst all the dolphins had ever done was muck about in the water having a good time. But conversely, the dolphins had always believed that they were far more intelligent than man — for precisely the same reasons….In fact there was only one species on the planet more intelligent than dolphins, and they spent a lot of their time in behavioural research laboratories running round inside wheels and conducting frighteningly elegant and subtle experiments on man. The fact that once again man completely misinterpreted this relationship was entirely according to these creatures’ plans.” – Douglas Adams, The Hitchhiker’s Guide to the Galaxy

As tempting as it may be to believe the science fiction version of the intelligence rankings, real-life science has spoken and suggests (much to my displeasure) that humans may actually be the highest on the intelligence scale.

Glia are non-neuronal cells found in the brain mainly described as performing “housekeeping” functions, for example, providing structural support to neurons, and providing them with nutrients. Astrocytes are a specific type of glia, and as one might hypothesize, they are bigger in humans than in mice. Was this just a consequence of humans having more complex brains, or do these astrocytes have different functions in humans beyond the basic housekeeping functions? To test this, scientists grafted human astrocyte progenitor cells into developing mouse brains to create chimeric mice.

Human astrocyte (green) and mouse astrocyte (red)

The human astrocytes that matured successfully matured as human cells; characteristics such as their size were unaffected by being in a mouse environment. But they did not remain completely foreign – they successfully formed electrical connections with the mouse cells. Their differing cellular properties were thus propagated into the mouse neural networks. Of particular interest is the hippocampus, the brain region important for learning and memory. Chimeric hippocampal slices had a higher level of baseline excitatory activity, and long-term potentiation (LTP), or synapse strengthening, was much greater. At the molecular level, this can be explained because the human cells express higher levels of a protein that promotes an increased number of glutamate receptors at the synapse.

There were also clear differences in the behavior of chimeric mice. Experiments were performed to test learning and memory abilities to corroborate the cellular results observed in the hippocampus. A classic fear conditioning experiment involves pairing a tone with a foot shock; mice learn to associate the two and exhibit freezing behavior after hearing a tone. Chimeras learned the association after only one tone/shock pairing. The learning persisted for several days, during which time control animals did not learn the initial association. The experiment was repeated as context fear conditioning, meaning that the mice were placed in different chambers that had varying floors and odors. Chimeric mice were able to differentiate between chambers significantly better than their control counterparts. In other learning and memory tasks, these mice learned their way through mazes faster and were better at familiar object recognition in novel contexts.

The results of this study show that glial cells have much more function beyond their basic housekeeping properties. A single cell graft manipulation was enough to significantly improve mouse performance on learning and memory tasks. Complexity of these cells has evolved with the brain, and this provides important new insight on how exactly this complexity has come to be. Future experiments could involve grafting chimpanzee or macaque glia, any differences observed could be key in outlining how our processing abilities evolved from our monkey fathers (I additionally support research with dolphin glia grafts, keeping on the theme of the three most intelligent species). Unfortunately, without the higher processing abilities made possible by human cells, mice likely cannot achieve the tasks and level of status they exhibit in the science fiction. It seems as though man has indeed correctly interpreted his relationship with the mouse.

So long, and thanks for all the fish.

-Reena Clements

References:

Human Brain Cells Boost Mouse Memory – ScienceNOW

Forebrain Engraftment by Human Glial Progenitor Cells Enhances Synaptic Plasticity and Learning in Adult Mice – Cell Stem Cell

In this post, I attempt to present two major metaphysical accounts of space by Kant and Leibniz, then present some recent findings from cognitive neuroscience about the neural basis of spatial cognition in an attempt to understand more about the nature of space and the possible connection of philosophical theories to empirical observations.

Immanuel Kant’s account of space in his Prolegomena serves as a cornerstone for his thought and comes about in a discussion of the transcendental principles of mathematics that precedes remarks on the possibility of natural science and metaphysics. Kant begins his inquiry concerning the possibility of ‘pure’ mathematics with an appeal to the nature of mathematical knowledge, asserting that it rests upon no empirical basis, and thus is a purely synthetic product of pure reason (§6). He also argues that mathematical knowledge (pure mathematics) has the unique feature of first exhibiting its concepts in a priori intuition which in turn makes judgments in mathematics ‘intuitive’ (§7.281). For Kant, intuition is prior to our sensibility and the activity of reason since the former does not grasp ‘things in themselves,’ but rather only the things that can be perceived by the senses. Thus, what we can perceive is based on the form of our a priori intuition (§9). As such, we are only able to intuit and perceive things in the world within the framework naturally provided by the capabilities and character (literally the under–standing) of our understanding. Kant then takes our intuitions of space (and time) as concepts integral to pure mathematics and as necessary components of our intuition (§10.91).

Kant develops that geometry is based on this pure intuition of space (and arithmetic on that of time) and advances that even after removing all sensations and empirical intuitions, the intuitions of space and time remain, proving them as the a priori intuitions that precede any form of empirical experience or sensation (ibid.103). Thus, our experience of space and the means by which we do geometry is a component of our intuition for Kant and does not require the existence of direct objects of experience. Rather, our awareness of things as they appear in space is woven into our intuition and is a basic characteristic of our experience. Kant goes on to describe space as the “form of outer intuition of our sensibility” in that it is the thing in which we perceive things, i.e. that it is a transcendental condition for sensation (§13.317). By this, we arrive at our understanding of the arrangements of objects in the world not by an empirical encounter, but by the form of our intuition. Therefore, Kant’s account makes geometry an intuitive practice that utilizes a basic component of our pure a priori intuition as opposed to our rational activity. In support, Kant offers that we determine a geometrical concept, e.g. congruency, not through concepts formed by reason, but through relations that are apparent as a result of our pure intuition (ibid.325).

Kant’s theory stands in stark contrast to that of Leibniz, whose account of space is intelligible through arguments in his Discourse on Metaphysics and Monadology. In the former Leibniz foreshadows the concept of the monad in arguing, “each singular substance expresses the universe in its own way,” which develops that the constituent, most fundamental components of reality itself are unique and infinite in number and contain all things present, past and possible (DM.9). In the latter work, Leibniz reiterates that each monad must be different from each other because no two monads can be identical, further establishing the notion of an infinite number of infinite substances that make up the universe (M8-9). Accordingly, objects in the world are made up of monads, which are self contained and distinct from one another. Based on Leibniz’s theory, we arrive at a higher order reality in which everything is separate, distinct and self-contained and therefore, space comes about as a consequence of the existence of objects. That is, when we perceive Leibnizian space, we perceive a thing produced as a result of the existence of two other separate objects.

Leibniz’s account of space also has implications for geometry. By his theory, our perceptions of congruent things for example, become a comparison of two objects made in perception and understood actively by reason. Evidence for this can be found in Leibniz’s arguments concerning physics and causality. Leibniz believes that God constructed the world (with monads) and everything in it in the best possible way (M1,3). As such, the universe carries a predetermined and pre-established order of cause and effect (M6,7) and Leibniz argues that we come to understand nature by finding causes from effects by the use of reason (DM19). Therefore, geometry becomes a rational activity when viewed from a Leibnizian perspective because it is an investigation of that which exists. For Leibniz, we must necessarily invoke our understanding of the nature of objects in the world to do geometry, and this conflicts with the intuitive nature that Kant ascribes to geometry. For Kant, our knowledge (or ‘cognition’) of space is a result of the form of our intuition that comes before sensibility, which makes our understanding of geometry intuitive. For Leibniz, space exists only because discrete objects exist in the world and our understanding of geometry comes from rational manipulations of those objects. Nevertheless, both Kant and Leibniz provide accounts for space that necessarily involve an a priori component rather than perception alone.

Cognitive neuroscientists are now suggesting that spatial cognition is a complex interaction of multiple brain circuits in parallel that make use of both allocentric and egocentric processing of the external world. A pivotally important concept in understanding spatial cognition has been the investigation of representation in the brain. “Representation” is a term that has been used in philosophy for centuries, and science is now using the term to refer to the neural picture of the external world as observed by our brain monitoring and imaging technology. The investigation of representation in the brain essentially involves solving the puzzle of how the world itself is represented physically in the brain. With respect to spatial cognition, the discovery of grid cells in 2005 suggests that a euclidean space is encoded in the brain itself by neurons, and that activation and deactivation of grid cells plays a major role in representing the spatiality of the external world to the perceiver. The discovery of grid cells also suggested a mechanism for the perception of one’s own location that is continually updated by input from the external world, suggesting that, similar to visual perception, the representation of space in the brain itself is an active phenomenon that varies just as much as the visual field.

Most, if not all, of the work on spatial perception and grid cells is performed on rats and conclusions made are inductively applied to humans, which makes us doubt how accurately these mechanisms can apply to the human brain. I say this because while many other studies of physiological phenomena in rats or mice (e.g. those on the cardiovascular and immune systems) may be stronger due to the increased homology to humans present in those systems. In other words, I think that the human and the mouse/rat brain differ quite significantly, perhaps more so than other organs and that this reduces the strength of our inductive conclusions. However, interesting studies are now being performed on humans which place a subject in a virtual maze through a computer program and measure brain activity through noninvasive methods such as functional MRI (fMRI). Many recent studies are pointing to the hippocampus as a major player in way finding and general navigation through virtual mazes, which suggests that our spatial perception is an evolutionarily refined phenomenon, but also one that is fundamental to our basic neural make up. Interestingly, the neural phenomena change when scientists investigate spatial cognition relative to landmarks (i.e. objects) as compared to studies in simple maze navigation. In these object-centric experiments, subjects navigated mazes and were cued with objects present in the virtual environment that they had to collect and place in a distinct virtual location, either at a specific landmark or in a general bounded area. Brain scans in these studies showed both hippocampal and striatal activation during the performed tasks, with hippocampal activity associated with the boundary task and striatal activity associated with the landmark task. Further, separate studies in rats performing similar spatial boundary tasks reveal that the activation of hippocampal “place cells” fire in boundary-space tasks, which scientists think are creating a matched representation of distances and angles relative to the boundaries in the visual field. Results from striatal activation are still unclear and are being more closely investigated. It has also been suggested that the hippocampal and striatal circuits act in parallel rather than in series or in combination. This makes sense given that spatial cognition may involve both boundary and landmark elements, as when we have to hammer a nail into a specific location or plug something into a power outlet.

Relating the philosophy and neuroscience presented in this post, it seems that both Kantian and Leibnizian conceptions of space are compatible with neuroscientific findings about spatial cognition. Kant’s theory applies to the current understanding of hippocampal, boundary influenced tasks in that both suggest a holistic conception of space – that is, space can be understood as object independent. On the other hand, Leibnizian conceptions of space and the landmark results suggest a more object-dependent framework for spatial cognition. As spatial cognition and perception are our most direct means to accessing and interacting with the external world, both scientists and philosophers of the future ought to work together on this enormously complex problem in an effort to postulate how spatial phenomena as presented to us by the mind relate to neural phenomena in the brain. Perhaps then we will move closer to filling the explanatory gap between the mind and brain.

Prolegomena – Kant
Discourse on Metaphysics – Leibniz
The Monadology – Leibniz
Spatial Cognition and the Brain – Neil Burgess

Do you ever wonder how you are able to remember the name of your third-grade teacher, or the skills you use to ride a bike, or even lines from your favorite movie?  Well, if you haven’t then you should, because it takes the workings of many regions of our brain to combine all the different aspects of one memory into a cohesive unit.

The first step in this complex process deals with our perceptions and senses.  Think about the last time you visited the beach.  Recall the sound of the wind and birds, the sight of the sun and ocean, the smell of the salt water and the feeling of the hot sand and shells underfoot.  Your brain merges all of these different perceptions together, crafting them into the “memory” that we are able to recall.

All of these separate sensations travel to the part of our brain called the hippocampus.  Along with the frontal cortex, the hippocampus plays a huge part in our memory system.  These two regions decide what is worth remembering and then store this information throughout the brain.

Perception starts the processes leading up to encoding and storage, which takes place through our brains’ synapses (or the gaps between neurons).  Through these synapses, neurons are able to electrically and chemically transmit information between themselves.  When an electric pulse is fired across the gap, it triggers the release of chemical messengers called neurotransmitters.

Here is a clear view of communication between neurons through the releasing of neurotransmitters over the synapse.

From there, the spread of information begins.  The neurotransmitters diffuse to neighboring cells and attach to them, forming thousands of links.  All of these cells process and organize the information as a network.  Similar areas of information are connected and are constantly being reorganized as our brain processes more and more.

Changes are reinforced with use.  So let’s say you are learning to play a sport.  The more you practice, the stronger the rewiring and connections will become, thus allowing the brain to do less work as the initiation of pulses becomes easier with repetitive firing.  This is how you get better at a certain task and are able to perform at a higher level without making as many mistakes.  But again, because our brain never stops the process of input and output, practice needs to be constant in order to promote strong information retention.

Knowing all of this, it probably comes as no surprise that the most basic function for ensuring proper memory encoding is to pay specific attention to what you are doing.  We are exposed to thousands of things in very short amounts of time, so the majority of it is ignored.  If we pay more attention to select, specific bits of information, we’ll have a higher potential to remember certain things (try it out for yourself in lecture).

Since the actual process has been discussed, we’ll go into greater detail about the types of memory we have and how they differ.  There are three basic memory types that act as a filter systems for what we find important.  This is based on what we need to know and for how long we need to know it.

The first is sensory memory, which is basically ultra-short-term memory.  It is based off of input from the five senses and usually lasts a few seconds or so.  An example would be looking at a car that passes by and remembering what color it was based on that split second intake.  The effect is vaguely lingering, and is forgotten almost instantly.

Short-term memory is the next category.  People sometimes refer to it as “the brain’s Post-it note”.  It has the ability to retain around seven items of information for about less than a minute.  Some examples would include telephone numbers or even a sentence that you quickly glance over (such as this one).  You have to remember what is being said at the beginning to understand the context.  Likewise, numbers are usually better remembered, and have longer staying power in the brain, when split up (800-493-2751 instead of 8004932751 for instance).

Repetition and conscious effort to retain information leads to the transformation of short-term memory into long-term memory.  By rehearsing information without interference or disturbances, one is better able to remember things and ingrain them into his/her brain.  This is a gradual process, but it proves why studying is important!  Unlike the other two memory categories, long-term memory has the ability to retain unlimited amounts of information for a seemingly indefinite amount of time.

This diagram shows a more complex view of the major memory types and their subdivisions.

A  piece of information must pass from both sensory and short-term memory to successfully be encoded in long-term memory.  Failure to do so generally leads to the phenomenon known as “forgetting”, something that many of us are all too familiar with ironically enough!

To give a common example of long-term encoding and memory retrieval, consider trying to recall where you have put your keys down.  First, you must register where you are putting your keys and attention while putting them down so that you can remember later.  Accomplishing all of this helps a memory to be stored, retained, and ready for retrieval when necessary.

Forgetting may deal with distraction, or simply just failure to properly retrieve a memory.  That being said, it should be noted that there is no predisposition to having a “good” or a “bad” memories.  Most people are good at remembering certain things (numbers, procedures and mechanisms for example) better than others (names, phrases, or even entire plays) and vice versa.  It all depends on where you are able to focus your interests and your attention.

Hopefully, you will be able to remember some of this so that you can use your understanding of the complexities of the brain and memory encoding to your advantage.  After all, your brain does all the hard work for you!  Now you just need to pay attention and focus on what you find important and what you want to remember to best suit your own needs.

How Human Memory Works – Discovery Health

Types of Memory – The Human Memory

How Does Human Memory Work? – USATODAY.com