Some have said that free will is an illusion (e.g., Wegner, 2002). And some free will skeptics base their claims on evidence that experimenters can predict our decisions before we are aware of making the decision or forming an intention. This leap from pre-decision prediction to free will skepticism seems intuitive at first. Upon reflection, however, it seems odd. In this post, I’ll explain.
One of my favorite researchers is Chandra Sripada. Sripada is a professor of both philosophy and psychiatry. My research also crosses the humanities-science divide(s). So, I often wonder how to replicate a multi-disciplinary career like Sripada’s. A look at Sripada’s CV reveals a career path involving multiple advanced degrees, internships/residencies, etc. If you are like me, then you (or your partner) might want a more efficient path to a career. In this post, I share advice about how to obtain multi-disciplinary training from philosophy graduate programs. Continue reading Multi-disciplinary Philosophy PhD Programs
One of the things that cognitive scientists do is look for, identify, and describe mechanisms. For example, cognitive scientists are interested in our ability (or proclivity) to ascribe mental states to others things and creatures. So, some posit a “theory of mind” mechanism. But, intuitively, there will not be a mechanism for every one of our abilities or behaviors. For example, it would be surprising if there were mechanism for driving a car. But if that is right, then we need principled reasons to think so. Or, at the very least, we need a story about why some of our abilities have mechanisms and others don’t. In this post, I’ll briefly consider four such stories. One of the take-aways will be that it is not obvious why some abilities (like driving a car) do not have mechanisms. Another take-away will be that it is not obvious what scientists mean by ‘mechanism’. Continue reading On Inferring Mechanisms In Cognitive Science
You might be familiar with what philosophers call an “appeal to nature“. It is a claim that something is good or bad because of how natural it is. Sometimes an appeal to nature is a fallacy. In this post, I discuss the possibility that an appeal to intuition is that kind of fallacy.
If our judgments are dependent on the brain, then maybe we can understand our judgments by studying our brains. Further, maybe we can understand our philosophical judgments by studying our brains. What do you think? Can neuroscience help us understand philosophy? Here are some studies which suggest that it can.
1. Two Opposing Neural Networks/Judgments
Consider two different networks in the brain: the Default Mode Network (DMN) and the Task Positive Network (TPN). These networks are mutually inhibitory. When one network’s activity increases, the other network’s activity decreases. It’s a bit like a seesaw (Jack et al 2013).
Methamphetamine use is on the rise (Drug Enforcement Administration 2015). And so are crystal-meth-related drug convictions (see “State Sentencing…”). So what do we know about crystal meth? In particular, what does crystal meth do to your body and brain? The South Shore Recovery Center has some answers. In fact, they’ve done us the favor of turning those answers into the infographic below.
Continue reading Crystal Meth & Your Brain: An Infographic
Michael Bishop outlines a network theory of well-being in which well-being is constituted by positive causal networks and their fragments (2012, 2015). ‘Positive’ refers to — among other things — experiences that have positive hedonic tones, the affirmation or fulfilment of one’s values, and success in achieving goals. So according to Bishop’s view, we flourish when certain positive causal networks are robust and self-reinforcing. For example, something good happens to us and that improves our motivation and mood, which then helps us achieve more, which improves our motivation and mood even more, and so on.
Bishop’s network account musters philosophical rigor by providing a systematic and coherent account of wellbeing that satisfies many common sense judgments about well-being. But lots of philosophical accounts can do that. So Bishop’s account does even more. It unifies and makes sense of a huge swath of the science. This provides some reason to think that Bishop’s account is superior to its competition.
So what’s this got to do with exercise and neuroscience?
I am largely persuaded by Bishop’s arguments for the network account of well-being, so I will skip my criticism of the project. Rather, I will add to it. Specifically, I will show how well is makes sense of the neuroscience. While I will not be able to review all of neuroscience, I can accomplish a more modest goal. I can review one part of neuroscience: the effect of exercise on the brain.
There is a wealth of evidence suggesting that regular physical activity and exercise forms an important part of one’s positive causal network of well-being by, among other things, increasing positive affect (Harte, Eifert, and Smith 1995), increasing confidence (Klem, Wing, McGuire, Seagle, and Hill 1997), reducing stress, relieving depression (Blumenthal et al 1999; Motl et al 2005) and preventing more than a dozen chronic diseases (Booth, Gordon, Carlson and Hamilton 2000; see also Biddle, Fox and Boutcher 2000 for a review of relationships between exercise and well-being). The mechanisms for all of these results are not entirely clear. But neuroscience is providing, in broad strokes at least, some clues about the mechanisms that can explain, in part, why exercise produces a series of positive effects in a well-being network (e.g., Meeusen 1995, Farooqui 2014).
The Positive Effects in the Brain
Let’s start with how exercise produces direct positive effects in the brain. Firstly, exercise and regular physical activity directly improve the brain’s synaptic structure by improving potentiating synaptic strength (Cotman, Berchtold, Christie 2007). Secondly, exercise and regular physical activity strengthen systems that underlie neural plasticity—e.g., neurogenesis, the growth of new neural tissue (ibid., Praag et al 2014). These changes in the brain cause “growth factor cascades” which improve overall “brain health and function” (ibid.; Kramer and Erickson 2007).
Now consider how exercise has indirect positive effects in the brain by producing ancillary positive circumstances. Generally speaking, “exercise reduces peripheral risk factors for cognitive decline” by preventing—among other things—neurodegeneration, neurotrophic resistance, hypertension, and insulin resistance (ibid.; see also Mattson 2014). By preventing these threats to neural and cognitive health, exercise is, indirectly, promoting brain health and function.
Positive Causal Networks
It requires no stretch of the imagination to see how these positive effects will reinforce positive causal networks and thereby increase well-being. Even so, I will do you a favor by trying to demonstrate a connection between exercise, the brain, and the larger network of well-being.
We have already seen how exercise results in, among other things, increased plasticity. And increased plasticity results in improved learning (Geinisman 2000; Rampon and Tsien 2000). Also, the increased plasticity that results in improved learning can produce other positive outcomes: increased motivation, increased opportunities for personal relationships in learning environments, etc. (Zelazo and Carlson 2012, 358). Further, increased motivation and social capital can — coming full circle — result in further motivation (Wing and Jeffery 1999).
That right there is what we call a self-reinforcing positive causal network or positive feedback loop. And that, according to Bishop, is how we increase well-being (see figure 1).
This causal model shows how the neuroscience we just discussed implies a causal network. The nodes and causal connections in this model show how well-being is a matter of positive causal networks.
3. What about Ill-being?
Obviously, I’ve only mentioned the neuroscience of well-being. But if we want to promote well-being, then we also have to decrease ill-being, right? Right. And once again, the network theory of well-being will fit nicely with the research on ill-being. For example, the research on emotion regulation (see Livingston et al 2015) implies some causal networks that can inhibit ill-being. The same can be said of the research about using deep brain stimulation in treatment-resistance depression (Bewernick et al 2010; Lozano et al 2008; Mayberg et al 2005; Neuner et al 2010).
4. A Concern: Fitness
You might object by positing that Bishop’s theory of well-being will not fit neuroscience as well as it fits positive psychology. This objection can be dismissed in a few ways. Here are two ways.
First, we can safely accept that Bishop’s network theory of well-being will not fit neuroscience as well as it fits positive psychology. After all, Bishop’s network theory was designed to fit positive psychology, not neuroscience. It’s hardly a fault for a theory to not do what is was not intended to do.
Second, neuroscience is a larger domain than positive psychology. So of course it is harder for a theory to fit it. Allow me to explain. As the domain of discourse increases in scope, it becomes increasingly difficult for us to find a theory that fits all of it. So, because neuroscience is a larger domain than positive psychology, the challenge of providing a theory that fits neuroscience is always more difficult than providing a theory that fits positive psychology. So the fitness objection doesn’t necessarily reflect badly on Bishop’s theory. It might only reflect a difference between positive psychology and neuroscience.
Let me summarize. I mentioned a few cases in which Bishop’s theory of well-being can unifies and makes sense of neuroscience. Then I proposed a few more cases in which Bishop’s theory might do the same. And then I addressed a skeptical worry about the project I propose. So Bishop’s theory of well-being can accomplish even more than Bishop intended.