Understanding Thought – Part 2, The Neuroscience of Thought

What is thought?

We’re all familiar with thought, to be sure, just like we’re familiar with our own bodies. But just because we know our own bodies doesn’t make us all doctors. In the same way, we might know our own thoughts well, but that doesn’t make us experts in the science of thought.

But understanding thought is important. If we don’t know what thoughts are, then it’s very easy to be conned into believing the myriad of myths about thought perpetuated about them by every pop-psychologist and B-grade life coach. This series of blogs is taken from my book Hold That Thought: Reappraising the work of Dr Caroline Leaf.

We’ve looked at some basic neurobiology, and today we’ll look at the neurobiology of thought itself. Later we’ll discuss some psychological models of our thought processing, and finally we’ll discuss the common brain states and functions that are usually confused with thought.

Neuroscience of thought

Global Workspace / Intelligent Distribution Agent Model

Building on Baddeley’s model of working memory, Baars proposed the Global Workspace theory [1], and Baars and Franklin went further by adding the Intelligent Distribution Agent model [2]. Central to this model is the “Cognitive cycle”, a nine-step description of the underlying process from perception through to action. In the model, implicit neural information processing is considered to be a continuing stream of cognitive cycles, overlapping so they act in parallel. The conscious broadcast of our thought stream is limited to a single cognitive cycle at any given instant, so while these thought cycles run in in parallel, our awareness of them is in the serial, sometimes disparate, streams of words or pictures in our minds. Baars and Franklin suggests that as many as ten cycles could be running per second [3], and since working-memory tasks occur on the order of seconds, several cognitive cycles may be needed for any given working memory task, especially if it has conscious components such as mental rehearsal [2].

In recent years, the Global Workspace/Intelligent Distribution Agent hypothesis has been updated to help facilitate the quest to create different forms of artificial intelligence. The LIDA (“Learning Intelligent Distribution Agent”) model incorporates the Global Workspace theory with the concepts of memory formation to create a single, broad, systems-level model of the mind.

Franklin et al summarise the process, “During each cognitive cycle the LIDA agent first makes sense of its current situation as best as it can by updating its representation of its current situation, both external and internal. By a competitive process, as specified by Global Workspace Theory, it then decides what portion of the represented situation is the most salient, the most in need of attention. Broadcasting this portion, the current contents of consciousness, enables the agent to chose an appropriate action and execute it, completing the cycle.” [4] Information within the cognitive cycle is broadcast to our consciousness in order to recruit a wider area of the brain to enhance the processing of that information [2, 5]. It’s the broadcasting of this portion of the information flow that renders it “conscious”.

Thought, therefore, is simply a broadcast of one part of a deeper flow of information. This is very important, as it means that thought is not an instigator or a controlling force. It’s not a case of, “I think, therefore, I am”, but, “I am, therefore, I think.”

Neural networks involved in the neurobiology of thought?

There is good evidence that working memory, and the attention required to select the information streams that fill the global workspace at any one moment, are intrinsically linked to a group of brain regions tagged as the Prefrontal Parietal Network [6]. Disease or damage to the PPN or impairment of the PPN in the lab impairs normal conscious function. Research-level brain imaging studies have strongly implicated the PPN in perceptual transitions, the conscious detection of stimuli in a range of modalities, sustaining percepts, and in metacognitive decisions (awareness of awareness) on those percepts. Finally, a reduction of conscious level when under general anesthesia is associated with a reduced lateral prefrontal activity [6].

Other neural networks have been defined that are also important in the neurophysiology of conscious awareness. When there are no external stimuli, the brain doesn’t just turn off. Some parts of the brain become even more active. The same parts of the brain are active when we daydream (what researchers call “stimulus independent thought”).

We have all experienced this at some point. Our body will be doing something while our brain is off somewhere else. I find this happens to me when I’m driving home from work. Going the same route every day means that I often drift into autopilot as I’m thinking about the events of the day or my stomach reminds me that I’m hungry, and five minutes later I pay attention to my surroundings and realise that I’m nearly home.

There are many other sentinel neurocognitive networks, among them: the default mode network, the central executive network, and the salience network. The central executive network is involved in actively working on an external task, which we think of as attention. The default mode network is involved in autobiographical retrieval and self-monitoring activity, the “stimulus independent thought”, or day-dreaming. The salience network acts as a switch between the two, figuring out which external stimuli need active attention and switching on the central executive network [7]. Whichever one of these networks is active at the time, that network is actively feeding information into the working memory, which is what we perceive as “thought”.

When the brain is engaged in a new or difficult task requiring active attention, the executive parts of the brain overtake the default mode network. But when attention is not actively required such as well-practiced tasks, or if our attention diminishes as with boring tasks, the Default Mode Network becomes dominant again. The switch between attention and the default mode network is strongly related to the neurotransmitter dopamine [8]. These networks heavily overlap with the Prefrontal Parietal Network and the global workspace model.

Recent neurobiological evidence confirms the role the default mode network in thought processing, specifically the part of the brain called the cingulate cortex.   This has been confirmed in studies in healthy subjects [9], and in people with formal thought disorders (especially auditory verbal hallucinations) [10]. Specifically, the DMN is often the part of the brain that is the most active in remembering the past, and using similar mechanisms, also the simulations of the future. It is linked to daydreaming and creativity especially when a problem is allowed to “incubate” for a while, while the brain is involved in another task that is more menial, or low stress. It’s theorised that the attentional and implicit networks in the brain are brought into a closer proximity and allowed to interact, which improved the likelihood that a novel solution would be discovered [11].

Research into the topics of thought and consciousness is ever-growing and expanding, and if you want to read more about these topic, they have been very well covered in a two part series from De Sousa, [12] and [13].


  1. Baars, B.J., A cognitive theory of consciousness. 1988, Cambridge University Press, Cambridge England ; New York:
  2. Baars, B.J. and Franklin, S., How conscious experience and working memory interact. Trends Cogn Sci, 2003. 7(4): 166-72 http://www.ncbi.nlm.nih.gov/pubmed/12691765 ; http://bit.ly/1a3ytQT
  3. Madl, T., et al., The timing of the cognitive cycle. PLoS One, 2011. 6(4): e14803 doi: 10.1371/journal.pone.0014803
  4. Franklin, S., et al., Conceptual Commitments of the LIDA Model of Cognition. Journal of Artificial General Intelligence, 2013. 4(2): 1-22
  5. Baars, B.J., Global workspace theory of consciousness: toward a cognitive neuroscience of human experience. Progress in brain research, 2005. 150: 45-53
  6. Bor, D. and Seth, A.K., Consciousness and the prefrontal parietal network: insights from attention, working memory, and chunking. Front Psychol, 2012. 3: 63 doi: 10.3389/fpsyg.2012.00063
  7. Meehan, T.P. and Bressler, S.L., Neurocognitive networks: findings, models, and theory. Neurosci Biobehav Rev, 2012. 36(10): 2232-47 doi: 10.1016/j.neubiorev.2012.08.002
  8. de Wit, S., et al., Reliance on habits at the expense of goal-directed control following dopamine precursor depletion. Psychopharmacology (Berl), 2012. 219(2): 621-31 doi: 10.1007/s00213-011-2563-2
  9. Shackman, A.J., et al., The integration of negative affect, pain and cognitive control in the cingulate cortex. Nat Rev Neurosci, 2011. 12(3): 154-67 doi: 10.1038/nrn2994
  10. Lutterveld, R.v., et al., Network analysis of auditory hallucinations in nonpsychotic individuals, in Auditory verbal hallucinations and the brain, Lutterveld, R.v., (Ed). 2013, University Medical Center Utrecht: The Netherlands. p. 117-37.
  11. Baird, B., et al., Inspired by distraction: mind wandering facilitates creative incubation. Psychol Sci, 2012. 23(10): 1117-22 doi: 10.1177/0956797612446024
  12. De Sousa, A., Towards an integrative theory of consciousness: part 1 (neurobiological and cognitive models). Mens Sana Monogr, 2013. 11(1): 100-50 doi: 10.4103/0973-1229.109335
  13. De Sousa, A., Towards an integrative theory of consciousness: part 2 (an anthology of various other models). Mens Sana Monogr, 2013. 11(1): 151-209 doi: 10.4103/0973-1229.109341

One thought on “Understanding Thought – Part 2, The Neuroscience of Thought

  1. Pingback: Dr Caroline Leaf and the Me-Too approach to mental health | Dr C. Edward Pitt

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