Human vs. Mouse: Are Human Cells Smarter?

In his book The Hitchhiker’s Guide to the Galaxy, Douglas Adams claims that mice are the most intelligent species in the galaxy, but as much as I love his works, as a neuroscientist, I want to refute this claim.

The brains of humans and mice are similar to such extent that mice are often used to model and research human diseases and behaviors. However, humans are dealing with more complex environments and performing behaviors requiring higher cognitive abilities, such as creating and appreciating art, mental time traveling, control of facial expressions, and understanding symbolic concepts. These behaviors and higher cognitive abilities are difficult to establish in mice. Interestingly, this might be traced back to differences in each species’ neurons and the complex signals their networks encode. So to say, the differences of mice and men.

Neurons, no matter the species, have projections from their cell bodies called axons and dendrites (Fig. 1 & cover art). You can imagine a neuron in the brain’s cortex, or anywhere else in the body, as a city with incoming freight road networks. Neurons have quite a few inward-bound roads (dendrites) packed with electrical signal freight. The signals converge near their city centers (the cell body), but there is mostly one exit highway (the axon). These communicate with other neurons in the network, and thus encode complex behaviors.

Figure 1: Neuron like city analogy.

Dendritic projections receive many small electrical inputs from neighboring cells and relay the signal to the cell body. If enough signals coincide at the cell body, then an all-or-nothing pulse known as an action potential (AP) is generated and transmitted along the outward travelling axon to convey information to the next destination cells. This input-output system is highly preserved across organisms and is essential for many biological processes.

So are the neural systems of humans and mice really just encoded differently, or is it just a question of more efficient and reliable processing that accounts for the higher cognitive abilities seen in humans? This is what we have been researching during my internship at the Integrative Neurophysiology (INF) department, CNCR (VU Amsterdam).

Functional and structural differences

To assess characteristic differences between neurons, researchers use neurophysiological measurements such as repetitive firing. It is like assessing how well a city’s infrastructure can handle high amounts of incoming traffic (stimuli) by measuring the speed of the outgoing traffic (APs). In this case we artificially stimulated cortical brain neurons at high frequencies using an electrode on their surface, while recording the neuronal responses (APs) with the same electrode. We applied input pulses at different frequencies, where each pulse successfully initiated an AP. There are many features of the AP shape that encode information, here we looked at AP duration because it’s informative about the abilities of human and mice neurons to adapt to high-frequency stimulations.

“Properties of human neurons that allow for faster processing are related to intelligence”.

We observed that human neurons were better able to keep up with incoming inputs at high frequencies as the duration of their output signals (APs) remained more constant. In both human and mouse neurons the duration or ‘half-width’ (Fig. 2B) of the APs depended on both the number (firing history) and frequency of previously initiated APs, as seen in Figure 2D. You can see in the human neurons (red) that even when the stimulation frequency increased to 70 Hz, the duration of their output barely changed. In contrast, in mouse neurons (blue) frequencies higher than 40 Hz resulted in an increase of AP half-width. This increase of duration affects subsequent APs as they also show increased duration. In turn, this corresponds to delayed response to a fast-incoming stimulus, which might have consequences for information transfer. Even though both human and mouse neurons managed to track high-frequency inputs, human APs showed more consistent responses over time, which suggests that they are better adapted for functioning at higher frequencies for longer (i.e.; demanding conditions). 

These functional differences seem related to differences in the shape or morphology of the dendrites of human and mouse neurons [1]. Dendrites of human neurons are longer and with increased arbors [2]. So just as a city with more complex organization of its inward-bound roads would allow it to fine-tune and more reliably transit more freight, we see that human neurons are better able to keep up at high-frequency input. 

In all, this is just one piece of evidence that leads us to thinking that human neurons are structurally and functionally better suited for more advanced information processing, which may be necessary to support highly complex cognitive abilities. 

Figure 2: Visualization of neurons, AP shapes and the differences in their duration in human and mouse neurons. A. Labelled human and moue cortical neurons. The scaling is different in the two images, human neurons are bigger and with increased arbor. B. Visualization of the AP shape and measure of AP halfwidth (duration) in human (red) and mouse (blue). C. Relative measure of AP halfwidth (AP#/AP#1) in response to varying stimlation frequencies and firing history (number of previous APs).

Intelligent networks?

Evidence suggests that the properties of human neurons that allow for faster processing are related to intelligence, which integrates cognitive functions such as perception, attention, memory, language, and planning. Neurons from people with higher IQ scores also respond more accurately and sustainably to high-frequency inputs. It’s also been observed that higher dendritic complexity of human neurons is associated with high IQ scores and higher cortical thickness [3]. The field now anticipates that these differences in the neuronal organization and communication arise and likely explain some of the observable differences in cognitive abilities. 

Can neuronal complexity be traced through evolution?

Across other species, higher cognitive abilities are also supported by bigger and more complex cortical microcircuits. Just as in electronics, a microcircuit in the brain refers to a processing unit of interconnected neurons that bridges neuronal function to behavior – the output of the whole system. 

Development of higher complexity in behaviors and structures might be connected to the addition of more processing units with higher inter connectivity. During evolution the outermost layer of the cortex – the neocortex – underwent a species-specific expansion, which saw an increase in complexity as it allowed for the addition of more microcircuits [4]. As visualized in Fig. 3, the mouse cortex has no folding, thus, there is  limited space available for the development of microcircuit complexity. In contrast, the cortex of humans and chimpanzees have more folding, which is an efficient structural adaptation supporting the function of a higher number of interconnected processing units. In turn, evidence suggests that human microcircuits relay more information [5], which might also be related to why humans also exhibit more elaborate behaviors and higher cognitive abilities.

Figure 3: Variability of brain size and external topography in human, chimpanzee, and mouse [4].

Altogether, even though mice are extensively used in science as a model organism, here we suggest that there are differences in how mouse and human neurons respond to high-frequency stimulation. Model organisms help scientists understand how neurons and circuits work, but as our own experiments show, human and mouse neurons are different, and so their utility for understanding complex human-specific characteristics should continue to be critically assessed. Furthermore, human neuronal communication could be better approached if we took these functional differences into account with computational simulation and our research models.

So I’m still working to refute the claim that human neurons are really smarter than mouse neurons due to their stable AP shapes. To achieve this, we might need to design smart experiments, unlike the one Frankie mouse and Benjy mouse employed with our planet in The Hitchhiker’s Guide to the Galaxy

Bibliography

1.    Eyal, G., et al., Dendrites impact the encoding capabilities of the axon. J Neurosci, 2014. 34(24): p. 8063-71. DOI: 10.1523/JNEUROSCI.5431-13.2014 

2.    Mohan, H., et al., Dendritic and Axonal Architecture of Individual Pyramidal Neurons across Layers of Adult Human Neocortex. Cereb Cortex, 2015. 25(12): p. 4839-53. DOI: 10.1093/cercor/bhv188 

3.    Goriounova, N.A., et al., Large and fast human pyramidal neurons associate with intelligence. Elife, 2018. 7. DOI: 10.7554/eLife.41714

4.     DeFelipe, J., The evolution of the brain, the human nature of cortical circuits, and intellectual creativity. Front Neuroanat, 2011. 5: p. 29. DOI: 10.3389/fnana.2011.00029 

5.    Testa-Silva, G., et al., High bandwidth synaptic communication and frequency tracking in human neocortex. PLoS Biol, 2014. 12(11): p. E1002007. DOI: 10.1371/journal.pbio.100200

Cover image courtesy: Lalitha Veleti

Verjinia is a second-year neuroscience master student at VU, studying the effects of high-frequency stimulations on  human and mouse neurons.

Verjinia is a second-year neuroscience master student at the VU. She studied the effects of high frequency stimulations on human and mouse neurons at INF, CNCR. As she fell in love with electrophysiology, now she’s headed for a PhD in the lab of Dietmar Schmitz in Berlin.