In a famous 1996 essay called Sorry, But Your Soul Just Died, writer Tom Wolfe predicted that the rapidly advancing field of neuroscience would soon destroy any notion of self or soul. The mind would be shown to be nothing more than brain processes, and the brain alone would be sufficient to generate the mind. It would be the final nail in the coffin for substance dualism, the view that the mind and the body are composed of different substances, where a substance is a constituent of reality.

What has twenty years of progress shown us? Has Wolfe’s prediction been realised?

According to Julien Musolino, the author of the The Soul Fallacy, published in 2015, the answer is an emphatic yes: “the current scientific consensus rejects any notion of soul or spirit as separate from the activity of the brain”.

Musolino is correct in his pronouncement – the current scientific consensus does seem to overwhelmingly reject a soul or spirit separate from the brain. But perhaps quoting the scientific consensus doesn’t properly address Wolfe’s prediction. After all, the scientific consensus in 1996 probably also rejected a separate soul or spirit as well. A more appropriate question is what evidence does neuroscience offer for science’s rejection of the soul? Or is this rejection primarily based on an a priori assumption of materialism?

To answer this question, we need to delve into neuroimaging, the technology used by neuroscience to explore the inner workings of the brain.

How neuroimaging works

One of the most frequently used neuroimaging techniques is functional magnetic resonance imaging (fMRI).

MRI is based on the principle of nuclear magnetic resonance. When certain atomic nuclei are placed in a magnetic field, they absorb and then emit characteristic electromagnetic radiation that can be measured. The frequency of this radiation depends on the nucleus and its environment. In MRI, hydrogen atoms are used as they are abundant in our bodies, being part of water and fat.

When neural activity in an area of the brain increases, neurons require more glucose for energy, and burning more glucose requires more oxygen. Blood flow to the area increases, bringing both glucose and oxygen, which is delivered via haemoglobin in red blood cells.

Haemoglobin has different magnetic properties depending on whether it is oxygenated or not, and these differences can be detected by MRI. This is known as blood oxygenation level dependent (BOLD) imaging.

Immediately after neural activation, blood oxygenation levels fall. It takes the vascular system several seconds to respond by increasing blood flow, which brings more oxygen. Oxygen levels peak after about six seconds before falling back to slightly below the initial levels.

The assumption behind fMRI is that the BOLD signal is linearly correlated with neural activity. During experiments, the subject’s head is placed in the MRI machine’s magnetic field, and it records the BOLD response throughout their brain for the duration of the experiment.

How experiments are conducted

In a typical experiment, participants perform an experimental task and a control task while brain activity is recorded. The control task and the experimental task share the same cognitive processes, but the experimental task has at least one additional process. For example, experimental participants might be shown a noun, and asked to state a verb that goes with the noun, while control participants are asked to repeat the noun. This is supposed to isolate the cognitive process that involves selecting an appropriate word from a different category.

The fMRI data of participants from each group is combined, and the brain activity responsible for the additional process is obtained by subtracting the activity from the control task, a technique known as cognitive subtraction.

Limitations of fMRI

Despite the widespread use of fMRI, we do not have a complete understanding of the relationship between BOLD signals and neural activity. Numerous factors are involved, and only broad correlations are currently possible. There are also a number of other limitations and caveats that are discussed below.

Not real-time

BOLD signals are at least five seconds behind the neural activity they are measuring. Temporal resolution is also constrained, as sampling frequencies add little information below one second. Neurons work many times faster, and so fMRI is currently of little help in understanding how brains work in real time.

Resolution

fMRI does not measure the activity of individual neurons. Instead, its spatial resolution is divided into voxels, three dimensional cubes ranging from 1 mm to 5 mm in size. A voxel contains millions of neurons and tens of millions of synapses.

Noise

As the BOLD signal is relatively weak, care must be taken to control sources of noise, which include random neural activity, body movement and noise from the scanner. It is difficult to control all background effects, and subjects themselves can have variation in their neural activity from trial to trial.

There are a number of preprocessing steps performed to strip out noise prior to statistical analysis. For example, corrections are made for head motion, which moves voxels.

The data from each subject must also be normalised according to a standard brain “atlas” to eliminate structural variability between brains.

Statistical analysis

Interpreting raw experimental data to produce neuroimages is a complex statistical process. The infamous dead salmon study illustrated some of the issues. A salmon purchased from a store was shown photographs of people and asked to guess what the people were feeling. The researchers found that when the imaging data was analysed, a small part of the salmon’s brain showed activity in response to the photographs.

This is the multiple comparisons problem – if enough comparisons are performed, at least some of them will return positive results, even if they are false. Because fMRI scans divide the brain into 50,000 or more regions, they are very susceptible. Corrections can be made to account for the problem, but at the time of publication, 25-40% of fMRI studies were not doing so. Fortunately, this has dropped to around 10% by 2012 and is hopefully dropped further since, but it shows the complications involved.

Inhibitory neural activity

There are some indications that inhibitory neural activity may also increase the BOLD response, which obviously casts doubt on interpretation. More research is required in this area.

Cognitive subtraction

Recent research casts doubt on the technique of cognitive subtraction, used to isolate brain areas that contribute to a cognitive task in almost all brain mapping experiments. When subjects engage in an experiment, they suppress certain brain activity, and when they release the suppression, activity shoots up. So some parts of the brain show increased activity for less demanding tasks – a form of cognitive addition rather than subtraction.

Glial cells

Almost 90% of the brain is composed of glial cells, not neurons. For a long time glial cells were regarded merely as insulators for neurons, but research is now indicating that a type of glial cell called astrocytes may be involved in neuron signalling. Astrocytes have as many as 30,000 connections with surrounding cells, far more connections than neurons. According to researcher Andrea Volterra, “if glia are involved in signalling, processing in the brain turns out to be an order of magnitude more complex than previously expected”. For decades neurons have been the focus of brain research, and if astrocytes prove to be significant, a radical revision would be required. For now, their involvement is debated and being actively researched.

Are neuroimages photographs?

It should be clear from the explanation of fMRI above that neuroimages are not photographs of brain activity, despite similarities in their appearance.

fMRI does not directly measure brain activity, and data is not concurrent with the brain activity it represents. The data is highly preprocessed, and typically is a combination of results across multiple subjects, not a single brain. The end result is a statistical representation of a highly complex system.

1206 FMRI

The apparent similarities between neuroimages and photographs is problematic when it comes to interpretation by non-specialists.

According to Adina L. Roskies, “photography enjoys a privileged epistemic status”. Photographs are closely tied to reality, and accurately represent many of the qualities of their subjects. Importantly, we have a clear grasp of the causal relationship between photographs and their subjects. We regard a photograph as an objective representation, unaffected by the photographer’s beliefs.

Unfortunately, when non-specialists view neuroimages, they think they are seeing photographs of brain activity, and consequently find them compelling. They wrongly attribute the epistemic status of photographs to neuroimages, and develop an exaggerated concept of what they can tell us about the brain, which becomes part of popular culture.

What do neuroimages tell us?

As noted previously, neuroimages tell us little about how the brain works in real time. Instead, they provide information about which brain areas are correlated with particular mental events or stimuli. This is at a coarse level of millions of neurons, so if activity is occurring on a smaller scale, fMRI may not capture it. Given that it is difficult to discriminate between excitatory and inhibitory activity, we have little idea of what is going on at the level of individual neurons. That requires single-unit recordings, an invasive technique that involves inserting microelectrodes in the brain. For ethical and practical reasons, this can rarely be used, at least on humans.

Importantly, research so far shows that many regions of the brain have fairly general functions – a brain region may be engaged by many different cognitive processes. Specific cognitive processes involve networks of regions – they do not work independently. To determine the function of a particular region requires examining all of the cognitive processes that engage it. To exhaust all the possibilities for each region requires extensive research.

Correlation, dependence and causation

fMRI studies have established correlations between mental functions and areas of the brain, not causation. How might causation be established? Would this refute the idea of an immaterial mind or soul?

Brain damage is one possibility. When a person’s brain is damaged, it seems that their mind is damaged. From our fMRI correlations, we can reliably predict which mental functions will be impaired by damage in different regions of the brain. Cases such as Phineas Cage demonstrate that even our personalities can be radically changed when certain injuries occur. It would seem this establishes a degree of dependence of mental functions on the brain as well as correlations, although rigorous investigation requires the ability to safely deactivate and reactivate regions of the brain.

Doesn’t this dependence demonstrate that the mind is identical with or caused solely by the brain?

Not according to substance dualists, who claim that the mind uses the brain to express its abilities. The interaction between mind and brain means that correlation and even dependence is expected. A damaged brain results in a damaged expression of mind, even though the mind remains intact. Very tentative support for this view can be found in the rare cases of terminal lucidity primarily in Alzheimer’s patients.

What about consciousness?

What does neuroscience’s current progress tell us about the existence of the soul, or on a more philosophical level, about whether the mind and the brain are separate substances? For substance dualists, the mind is the soul, and so if neuroscience can explain the mind in its entirety as brain processes, then the soul is generated by the brain. It cannot be a separate substance.

To explain the mind, neuroscience must explain consciousness.

A science of consciousness must describe and explain the principal features of consciousness, and this involves two different types of data. Third-person aspects of consciousness are the “easy” problems. When a conscious system is observed, there is a range of specific behaviour accompanied by neural phenomena. For example, take someone listening to music. The third-party data involves the music, the effects on the ear and the auditory cortex of the brain, and the responses of the subject. All these must be explained in terms of neural mechanisms. But in addition, there is the “hard” problem of consciousness – the problem of explaining the subject’s subjective experience of listening to music. This is the first-person aspect of consciousness.

Neuroscience is making progress on explaining the third-person data, although the issues involved are anything but “easy”, particularly given the current limitations of fMRI. But presumably technology will eventually improve to the point that we can accurately correlate neural activity with mental functions to the level of single neurons. At this point we would have an incredibly detailed, complex map of what neurons are associated with each cognitive process. We may even be able to demonstrate causality.

What about first-person data? It is difficult to gather first-person data, as it is only indirectly available. We must rely on subjects’ verbal reports, which are hard to report accurately for experiences that are rich in detail.

Even if we can successfully gather first-person data, we are still left with the the “hard” problem of explaining how neural activity creates our subjective experiences. This is often known as the explanatory gap, and it is an open question in philosophy whether it can be resolved. Philosophers of mind have proposed numerous strategies to bridge the gap. Proposals range from extremes such as denying we have subjective experiences at all, to views such as panpsychism, the view that consciousness is a universal feature of matter. Substance dualism, of course, does bridge the explanatory gap.

Conclusion

One of the primary technologies used in neuroscience is fMRI – a relatively crude tool whose theoretical basis is not fully understood. Interpretation of fMRI data is also a complicated process. There are also uncertainties surrounding the role of astrocytes, and future research could result in a significant revision of how they interact with neurons and contribute to brain processes. So caution is required in when it comes to claims of what neuroscience has proven about the mind.

Neuroscience has made some progress on the “easy” problems of consciousness, establishing a number of correlations between regions of the brain and specific mental functions, but there is much yet to learn. Brain damage and resultant impaired mental functions indicate dependence of the mind on the brain, but dualism does account for this.

The “hard” problem of consciousness – subjective experience – is largely unexplored, and there are severe obstacles in producing an adequate explanatory account. However if the mind is to be explained as processes generated entirely by the brain, such an account is required.

It is clear that currently neuroscience is a very long way from destroying the soul, and any claim to the contrary is vastly overstating its capabilities and achievements.

 

 

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