Being left-handed and dyslexic, the first area of the brain that interested me, long ago, was Broca’s area. The theory that has been around for some time in various forms – that the evolution of language is connected to the evolution of fine motor skills with the hands – has intrigued me. A recent paper gives some evidence for the co-evolution of language and complex tool knapping (see citation below).

Knapping stone is not something that can be done in a scanner. The researchers used functional transcranial Doppler ultrasonography (fTCD) to measure brain blood flow lateralization patterns. This method allow the subjects to move more or less naturally. Competent knappers made stone tools and did language exercises while the difference in blood flow between the two hemispheres was measured. The language test was cued word generation; a letter was given and the subject generated a string of words beginning with that letter. The tool making was the production of Acheulean tools, an early but sophisticated style of knapping. They found a similarity in the blood flow pattern in the two tasks during the first 10 seconds. After that the pattern diverged with the language task having more blood flow to the left hemisphere and the knapping task having more to the right. In both tasks the first few seconds are used to ‘set up’ or plan the activity.

“Our participants showed correlated LIs (lateralization indices ) during the initial 10 seconds after task onset for cued word generation and handaxe production. A number of previous studies have directly correlated LI values for different tasks and shown that tasks which draw on shared neural processing sites, such as the three language tasks described by Bishop, result in highly correlated LI measures. In contrast, cognitive tasks that draw on disparate brain areas, such as language and visuo-spatial tasks like driving, visual attention, or visual memory, lead to uncorrelated LIs. Since Acheulean stone knapping is a highly visuo-spatial task , our finding of a correlation between knapping and language requires explanation.

Making an Acheulean handaxe requires both working memory and planning memory. This careful planning is dominant in the initial phase of each experimental block in our study. This action planning draws on brain areas that are shared with language tasks, such as the left-lateralized ventral premotor areas and Broca’s area. Our subject pool shows highly correlated individual brain blood flow lateralization in the early phases of task execution for both tasks. Our findings add empirical data to the hypothesis that action planning for tool-making and language draw on shared functional brain structures. The correlated time-signatures for Acheulean knapping and language, which remain significantly correlated within subjects despite variability between subjects, indicates that the same brain networks are being activated for both tasks. They suggest that tool-making and language share a basis in more general human capacities for complex, goal-directed action. ”

If tool making and language co-evolved then this says something about the age of language.

“… the network for complex action planning might have emerged in human evolution as part of our brain size increase and reorganization, leading to both language and tool-making . We suggest the start of the Acheulean techno-complex at 1.75 million years ago as a likely candidate for this because Acheulean knapping required more complex action planning than Oldowan technologies.”

This is not a new idea. There is an interesting paper by Greenfield (see citation below) from 12 years ago. Here is the abstract:

During the first two years of human life a common neural substrate (roughly Broca’s area) underlies the hierarchical organization of elements in the development of speech as well as the capacity to combine objects manually, including tool use. Subsequent cortical differentiation, beginning at age two, creates distinct, relatively modularized capacities for linguistic grammar and more complex combination of objects. An evolutionary homologue of the neural substrate for language production and manual action is hypothesized to have provided a foundation for the evolution of language before the divergence of the hominids and the great apes. Support comes from the discovery of a Broca’s area homologue and related neural circuits in contemporary primates. In addition, chimpanzees have an identical constraint on hierarchical complexity in both tool use and symbol combination. Their performance matches that of the two-year-old child who has not yet developed the neural circuits for complex grammar and complex manual combination of objects.

This points to a very long history for the development of language. Current estimates for the start of language vary from almost 2 million years ago to 50,000. The 50,000 figure is often quoted but is probably no longer accepted by most Evolutionary Biologists but only by ‘one-mighty-leap’ theorists.

Uomini NT, & Meyer GF (2013). Shared Brain Laterialization Patterns in Language and Acheulean Stone Tool Production: A Functional Transcranial Doppler Ultrasound Study. PLoS ONE, 8 (8) : 10.1371/journal.pone.0072693

Greenfield PM (1991). Language, tools and brain: the ontogeny and phylogeny of hierachically organized sequential behavior. Behavior & Brain Sciences, 14, 531-595

I have been called a couple of times over the word ‘consciousness’. Some think it is not a useful word but a confusing one and therefore should be avoided. My answer is that it is a perfectly clear word for a very particular thing. It is the word for our being aware and experiencing ourselves in the world. We all experience things when we are awake; we don’t have to be told what it is to be conscious. It would be fairly difficult to talk about thought or feeling or behaviour without having a word for consciousness.

The problem arises when we assume that consciousness means more than simply being aware and experiencing life as it happens. As soon as we leave the phenomenal area and look at other aspects that might be grouped in with the phenomenal, we start having problems. The problems come from the different ways that people view the world, people and brains.

Max Velmans in a paper, How to Define Consciousness – and How Not to Define Consciousness, Journal of Consciousness Studies 16(5) 2009, attempts to develop a working definition of consciousness. He starts with the simple phenomenal definition. This is the definition that I think forces us to use the word – we don’t have another word for it.

This everyday understanding of consciousness based on the presence or absence of experienced phenomena provides a simple place to start. A person, or other entity, is conscious if they experience something; conversely, if a person or entity experiences nothing they are not conscious. Elaborating slightly, we can say that when consciousness is present, phenomenal content (consciousness of something) is present. Conversely, when phenomenal content is absent, consciousness is absent. This stays very close to everyday usage and it provides a simple place of departure on which widely diverging theories can agree. It also makes sense to stay as close as possible to everyday, natural language usage for related terms.

it is important to reserve the term “mind” for psychological states and processes that may or may not be “conscious”. … restricting the phenomenology of “consciousness” to the phenomenology of “thought” is too narrow. … To allow a clear distinction between consciousness of oneself and consciousness of things other than oneself, it makes more sense to reserve the term “self-consciousness” for a special form of reflexive consciousness in which the object of consciousness is the self or some aspect of the self. … it is necessary to distinguish “consciousness” in the sense of “phenomenal consciousness” from wakefulness and other states of arousal … much knowledge is unconscious, or implicit (for example, the knowledge gained over a lifetime, stored in long-term memory). So consciousness and knowledge cannot be co-extensive.

More interesting is his take on ‘conscious processes’:

I have argued that the psychological and philosophical literature confounds three distinct senses in which a process might be said to be “conscious.” It might be conscious:

1. in the sense that one is conscious of the process

2. in the sense that the operation of the process is accompanied by consciousness (of its results) and

3. in the sense that consciousness enters into or causally influences the process.

the content of such thoughts and the sequence in which they appear does give some insight into the way the cognitive processes (of which they are manifestations) operate over time in problem solving, thinking, planning and so on. Consequently such cognitive processes are partly conscious in sense (1), but only in so far as their detailed operation is made explicit in conscious thoughts, thereby becoming accessible to introspection. Many psychological processes are conscious in sense (2), but not in sense (1) - that is, we are not conscious of how the processes operate, but we are conscious of their results. …Crucially, having an experience that gives some introspective access to a given process, or having the results of that process manifest in an experience, says nothing about whether that experience carries out that process. That is, whether a process is “conscious” in sense (1) or (2) needs to be distinguished from whether it is conscious in sense (3). … Consciousness of a physical process does not make consciousness responsible for the operation of that process (watching a kettle does not determine when it comes to the boil).

I avoid ‘conscious process’ because I believe that my readers might take the phrase to have meaning (3) which I reject completely and would never mean. I usually specify exactly what I mean when I am talking about consciousness of the results of a process as in (2). And, I usually call (1) guessing.

Mo Costandi has an excerpt from his book, 50 Human Brain Ideas You Really Need to Know, on his Guardian blog (here). The post is about mirror cells.

It can be summed up:

• Mirror neurons are cells that fire during both the execution and observation of a specific action.

• They have not actually been observed in humans although they have been inferred.

• What they actually do in the monkey brain is not clear.

• They have been hyped out of all proportion to the knowledge that we have of them.

So we have people proposing that autism is the result of the ‘mirror system’ not functioning properly, that mirror neurons allow us to understand the actions of others, that they are needed for imitation, that they allow us to understand action ‘from the inside’, that they are the foundation of empathy, etc. etc.

I assume that someday mirror neurons will be found in humans but that they will turn out to be the action equivalent of sensory cells that recognize particular objects, or particular places. The brain can recognize particular things by activity in particular groups of neurons: a kitchen chair, a friend’s back yard, Aunt Jane, and the action of reaching for something. There does not seem to be a special explanation required. The fact that mirror neurons have taken on a sort of mystical quality implies that there is something very important missing from many people’s understanding of the brain. Some gap that has to be bridged.

In some quotes found in other articles, there is a clue to what the gap seems to be. G. Rissolatti: “We are exquisitely social creatures. Our survival depends on understanding the actions, intentions and emotions of others. Mirror neurons allow us to grasp the minds of others not through conceptual reasoning but through direct simulation. By feeling, not by thinking.” P. Greenfield: “Mirror neurons provide a powerful biological foundation for the evolution of culture. Now we see that mirror neurons absorb culture directly, with each generation teaching the next by social sharing, imitation and observation.” M Iacoboni: “Mirror neurons suggest that we pretend to be in another person’s mental shoes. In fact, with mirror neurons we do not have to pretend, we practically are in another person’s mind.” So there is the problem – how do we know what other’s intentions are without some magical mind reading?

That does not seem a problem. We guess. Simple, we guess. We are smart guessers. First, we sometimes guess wrong. Two, the guessing skill is something that can be learned. Three, we have to guess our own intentions so why not others.

Consciousness does not have a direct knowledge of intent – we guess and we are not even conscious of our guessing. We are back to the awkward knowledge that what we feel consciously (first our intention, then our decision and then our action) is not what is actually happening. Our conscious thoughts are not the cause of the action. Our conscious thought is constructed after the events have taken place. We are guessing what our intent is. Libet’s experiment is not going to fade away. We have to face up to this. We have to get used to how our motivation really works rather than put a mystical, magical power into mirror neurons.

I notice that there are still a lot of people who assume that the brain is some type of general computer that can be modeled with a Turing machine. This idea cannot be assumed – it must be indicated if not proven. Just because a problem can be solved by a Turing machine and that problem is solved by the brain does not mean that the way the brain solved the problem is by a Turing machine type method. Nor is it clear (at least to me) that problems that are not framed in symbols of some sort and manipulations of those symbols, can all be solved by a Turing machine. An identity between a Turing machine and a brain has yet to be shown.

We have no reason to believe that brains are digital, that they deal with discrete states analogous to 1s and 0s, true and false, or yes and no. Everything points to the brain dealing with continuous values rather than discrete ones. We have no reason to believe that the brain uses algorithms, pre-formulated and step-wise methods of processing. In fact the physiology of brain cells is too slow for step-wise methods for most tasks. Everything points to massive overlapping loops, covering much of the brain at any instant, which settle quickly to momentarily stable configurations. We should forget about the brain being like a Turing type computer. We can entertain analogue computers or control systems but not general digital computers.

This should not be a surprise. Take the idea of a general computer. Why would our brains have general facilities rather than be ‘purpose built’? They are the product of evolution. They evolved as part of a slowly evolving body and slowly changing niches. What we need the brain to do, it is likely to do very well. And, what we don’t need it to do, it will not be able to do. It is very good at pattern recognition and very poor at complex mental mathematics. (We use calculators but not pattern recognizers.) We can push the envelop in certain new directions but only by using facilities evolved for something else.

How did it come to be that so many people had accepted the computer metaphor in its most literal form. I recently ran across a historical perspective in a discussion of amodal symbols, symbols that are not grounded in any mode like the senses, actions, situations or emotions etc. - the sort of symbols a Turing type machine might use, ungrounded and disembodied symbols, so to speak. Symbols that are very problematic from the biological point of view. The brain is after all a biological organ and our cognition is a biological function.

From Barsalou, L. (2008). Grounded cognition. Annual Review of Psychology, 59, 617-645

“Perhaps surprisingly, grounded cognition has been the dominant view of cognition for most of recorded history. Nearly all prescientific views of the human mind going to back to ancient philosophers (e.g., Epicurus 341–270 B.C.E.) assumed that modal representations and imagery represent knowledge analogous to current simulation views. Even nativists, such as Kant (1787/1965) and Reid (1785/1969), frequently discussed modal images in knowledge (among other constructs).

In the early twentieth century, behaviorists attacked late nineteenth-century studies of introspection, banishing imagery from much of psychology for not being sufficiently scientific, along with other cognitive constructs. When cognitive constructs reemerged during the Cognitive Revolution of the mid-twentieth century, imagery was not among them, probably for two reasons. First, the new cognitivists remembered Watson’s attacks on imagery and wanted to avoid the same criticisms. Second, they were enthralled with new forms of representation inspired by major developments in logic, linguistics, statistics, and computer science. As a result, theories of knowledge adopted a wide variety of amodal representations, including feature lists, semantic networks, and frames.

When early findings for mental imagery were reported in the 1960s, the new cognitivists dismissed and discredited them. Nevertheless, the behavioral and neural evidence for imagery eventually became so overwhelming that imagery is now accepted as a basic cognitive mechanism. …amodal symbols were adopted largely because they provided elegant and powerful formalisms for representing knowledge, because they captured important intuitions about the symbolic character of cognition, and because they could be implemented in artificial intelligence.”

I do find the idea of left-brained and right-brained types to be unconvincing. When I first encountered the idea I was intrigued and tested the theory out in my family, friends and myself. What I found in my tiny sample was a lack of a pattern. I found people who were very logical and also very creative – which came more to the fore depended on what they were doing. There were people who showed the one strength more than the other, but still seemed to have some of the other when it was really needed. And of course, there were a few that were both fairly illogical and fairly uncreative – one might say they were not that bright. To me, the idea that there are two kinds of people is in the eye of the beholder. Scientists tend to be creative even though they must be logical; novelists tend to be logical even though they must be creative. Why are these cast as opposites?

Think about it, why would we have evolved, not an optimal archetype, but instead, a pair of sub-optimal archetypes. Why would we not be able to think logically when that was what would solve a problem, think creatively when that was what would work, or think both ways if that was required. The two hemispheres having different functions appears to be an ancient structural feature – maybe to do with a division of labour between immediate tasks and general lookout for danger. But the idea that the hemispheres can not work together at the same time on different cognitive tasks is not very believable.

The notion that there are “two types of people in the world, those that x and those that y”, seems to be an easy trap to fall into. So get your antenna tuned to notice when the world is being divided into opposites, types, domains, dimensions and the like, and be extra skeptical. The division may work well or it may be just pretty and simplistic.

Recent research (see citation below) has failed to find left-brained and right-brained people in a sample of more than a 1000 scans of neural connections in a resting state. There are networks that are restricted to one hemisphere (more or less), but the strength of these connections does not show the x-brain effect.

“we demonstrate that left- and right-lateralized networks are homogeneously stronger among a constellation of hubs in the left and right hemispheres, but that such connections do not result in a subject-specific global brain lateralization difference that favors one network over the other (i.e. left-brained or right-brained). Rather, lateralized brain networks appear to show local correlation across subjects with only weak changes from childhood into early adulthood and very small if any differences with gender.”

Here is the abstract:

Lateralized brain regions subserve functions such as language and visuospatial processing. It has been conjectured that individuals may be left-brain dominant or right-brain dominant based on personality and cognitive style, but neuroimaging data has not provided clear evidence whether such phenotypic differences in the strength of left-dominant or right-dominant networks exist. We evaluated whether strongly lateralized connections covaried within the same individuals. Data were analyzed from publicly available resting state scans for 1011 individuals between the ages of 7 and 29. For each subject, functional lateralization was measured for each pair of 7266 regions covering the gray matter at 5-mm resolution as a difference in correlation before and after inverting images across the midsagittal plane. The difference in gray matter density between homotopic coordinates was used as a regressor to reduce the effect of structural asymmetries on functional lateralization. Nine left- and 11 right-lateralized hubs were identified as peaks in the degree map from the graph of significantly lateralized connections. The left-lateralized hubs included regions from the default mode network (medial prefrontal cortex, posterior cingulate cortex, and temporoparietal junction) and language regions (e.g., Broca Area and Wernicke Area), whereas the right-lateralized hubs included regions from the attention control network (e.g., lateral intraparietal sulcus, anterior insula, area MT, and frontal eye fields). Left- and right-lateralized hubs formed two separable networks of mutually lateralized regions. Connections involving only left- or only right-lateralized hubs showed positive correlation across subjects, but only for connections sharing a node. Lateralization of brain connections appears to be a local rather than global property of brain networks, and our data are not consistent with a whole-brain phenotype of greater “left-brained” or greater “right-brained” network strength across individuals. Small increases in lateralization with age were seen, but no differences in gender were observed.

I assume that the left or right brain description of individuals will die a very slow death and years from now people will be using the labels – too bad, that’s life.

Nielsen JA, Zielinski BA, Ferguson MA, Lainhart JE, & Aderson JS (2013). An Evaluation of the Left-Brain vs. Right-Brain Hypothesis with Resting State Functional Connectivity Magnetic Resonance Imaging PLoS ONE, 8 (8) : 10.1371/journal.pone.0071275

ScienceDaily has an item (here) about a paper: Cole, Reynolds, Power, Repovs, Anticevic, Braver; “Multi-task connectivity reveals flexible hubs for adaptive task control” inNature Neuroscience 2013; dealing with a theory about the brain’s flexibility.

The basic idea is that the cortex has 300 or so areas with special cognitive abilities; these areas are connected through hub neurons; and the hubs form a dozen or so large networks by mutual interconnections, such as the visual, motor, or attention networks. For any particular cognitive task, certain areas will have abilities that are needed for the task and hubs must be connected to allow these areas to work together. These areas may be spread across several networks. The ability to flexibly connect hubs allows us to do novel tasks, switch between tasks quickly, re-use techniques for a different task and learn from verbal/visual instruction. This research looks at the lateral prefrontal cortex and the posterior parietal cortex as a network that can flexibly connect areas of the brain to different cognitive tasks. (In other publications they also mention the basal ganglia and thalamus being involved in the mechanism of these flexible connections.)

“Acting as a central switching station for cognitive processing, this fronto-parietal brain network funnels incoming task instructions to those brain regions most adept at handling the cognitive task at hand, coordinating the transfer of information among processing brain regions to facilitate the rapid learning of new skills, the study finds.”

“This study proposes and provides strong evidence for a “flexible hub” theory of brain function in which the fronto-parietal network is composed of flexible hubs that help to organize and coordinate processing among the other specialized networks…This study provide strong support for the flexible hub theory in two key areas…First, the study yielded new evidence that when novel tasks are processed flexible hubs within the fronto-parietal network make multiple, rapidly shifting connections with specialized processing areas scattered throughout the brain…Second, by closely analyzing activity patterns as the flexible hubs connect with various brain regions during the processing of specific tasks, researchers determined that these connection patterns include telltale characteristics that can be decoded and used to identify which specific task is being implemented by the brain.”

“The flexible hub theory suggests this is possible because flexible hubs build up a repertoire of task component connectivity patterns that are highly practiced and can be reused in novel combinations in situations requiring high adaptivity.”

Flexible hubs differ from other hubs in that they are connected to many hubs outside their network (rather than having most of their connections within their network) and the strength of these connections can be varied quickly.

ScienceDaily (here) and (in more detail) a blog by Ed Yong (here) discuss a paper by Jimo Borjigin and others; “Surge of Neurophysiological Coherence and Connectivity in the Dying Brain” in PNAS. The paper is about near-death experiences.

Here is the abstract:

The brain is assumed to be hypoactive during cardiac arrest. However, the neurophysiological state of the brain immediately following cardiac arrest has not been systematically investigated. In this study, we performed continuous electroencephalography in rats undergoing experimental cardiac arrest and analyzed changes in power density, coherence, directed connectivity, and cross-frequency coupling. We identified a transient surge of synchronous gamma oscillations that occurred within the first 30 s after cardiac arrest and preceded isoelectric electroencephalogram. Gamma oscillations during cardiac arrest were global and highly coherent; moreover, this frequency band exhibited a striking increase in anterior–posterior-directed connectivity and tight phase-coupling to both theta and alpha waves. High-frequency neurophysiological activity in the near-death state exceeded levels found during the conscious waking state. These data demonstrate that the mammalian brain can, albeit paradoxically, generate neural correlates of heightened conscious processing at near-death.

The neural correlates of consciousness are synchronized gamma waves connecting distant parts across the cortex together and involving a loop with the thalamus. What they seem to have found is a short period strong synchronized gamma waves, indicating consciousness during the first half second of cardiac arrest, with strong coupling to theta and alpha waves – a super level of consciousness fitting with the very vivid memories of near-death experiences in humans.

There are still questions of what the mechanism is for this burst of conscious activity. Is something being released by the brain cells as they die that enhances activity for a short period? Is some brake on extreme activity released? Is the brain actually (unlikely as it may be) trying to think a way out of death? Is there an attempt to re-establish a balance that is disappearing?

Of course, some people have found it hard to accept that rats might have near-death experiences, or that near-death experiences could be explained as brain activity with no super-natural cause. But, that is to be expected. Near-death experiences were one of the only refuges left for the idea of a form of consciousness that could be independent of the body.

Starting with Libet’s work in 1985, a body of evidence has been built up suggesting that actions can be initiated unconsciously and unintentionally. This evidence questions the idea of complete conscious control over behavior, and the philosophical idea of free will.

The idea of ‘free won’t', however remained. According to some influential theories, unconscious behaviours are the inflexible reproduction of well-learned associations. To understand consciousness we need to discover what processes need consciousness and which don’t. Is consciousness required to inhibit actions?

Experiments seemed to show that subliminal signals could inhibit action. Then the theories on unconscious engagement of inhibition suggests that (a) consciousness is in fact required for inhibitory control in that the stimuli were first consciously associated with inhibition before being used subliminally and (b) willful conscious intent is also required to form a goal or desire to modulate inhibition. Also it was thought that unconscious inhibition might be the result of modulation of motor control processes rather than normal inhibitory control processes.

A recent paper by Hepler and Albarracin (see citation) tackle this question. They found a method of using word primes that suggested action or inaction (as opposed to a specific action) and used the P3 wave strength to gauge the inhibitory processes. The experiments side-step the three possibilities of the arguments against unconscious inhibition of actions.

“This research represents a critical finding in the scientific study of consciousness because it demonstrates that inhibitory self-control mechanisms can operate unconsciously and unintentionally, without prior conscious input – that is, inhibition processes can be engaged by motivationally relevant stimuli that have never been consciously or unconsciously paired with specific, task-relevant responses. Although previous work has demonstrated similar effects on behavior, behavioral inhibition can occur as the result of multiple cognitive processes other than the engagement of inhibitory control mechanisms. Thus, the present research is the first to demonstrate that inhibitory control mechanisms can be modulated completely outside of conscious control. ”

This should be the end of the free-won’t model.

Justin Hepler, & Dolores Albarracin (2013). Complete unconscious control: Using (in)action primes to demonstrate completely unconscious activation of inhibitory control mechanisms Cognition, 128 (3) : 10.1016/j.cognition.2013.04.012

ScienceDaily (here) has an item: Lee, Blumenfeld, D’Esposito; Disruption of Dorsolateral But Not Ventrolateral Prefrontal Cortex Improves Unconscious Perceptual Memories; inJournal of Neuroscience, 2013. It looks at the mechanism of over-thinking.

There are two types of memory (at least): explicit, conscious memory, also called declarative; and, implicit, not conscious memory, also called procedural. It has been noted for some time that preformance in sports, music and the like suffers when the performer thinks consciously too much. Procedural memory works best if the action is just done without trying to consciously control the action.

“Two previous brain studies have shown that taxing explicit memory resources improved recognition memory without awareness. The results suggest that implicit perceptual memory can aid performance on recognition tests. So Lee and his colleagues decided to test whether the effects of the attentional control processes associated with explicit memory could directly interfere with implicit memory.”

Lee disrupted activity in two parts of the prefrontal cortex to see which affected recognition. Disrupting the dorsolateral PFC improved memory. This pointed to explicit memory processing taking control of visual information processing and so interfering with implicit memory processes using the same visual information.

Here is the abstract:

Attentive encoding often leads to more accurate responses in recognition memory tests. However, previous studies have described conditions under which taxing explicit memory resources by attentional distraction improved perceptual recognition memory without awareness. These findings lead to the hypothesis that explicit memory processes mediated by the prefrontal cortex (PFC) can interfere with memory processes necessary for implicit recognition memory. The present study directly tested this hypothesis by applying transcranial magnetic stimulation separately over either dorsolateral (DLPFC) or ventrolateral PFC (VLPFC) in humans before performance of a visual memory task. Disruption of DLPFC function led to improvement in recognition accuracy only in responses in which the participant’s awareness of memory retrieval was absent. However, disruption of VLPFC function led to subtle shifts in recollection and familiarity accuracy. We conclude that explicit memory processes mediated by the DLPFC can indirectly interfere with implicit recognition memory.

I have just read a short article by Bradley, Moulin and Kvavilashvili in the March 2013 edition of The Psychologist, the BPS offical publication called Involuntary autobiographical memories.

Involuntary autobiographical memories (IAMs), pop into our minds without any deliberate attempt at retrieving them. They have been proposed as the result of ecphory, an automatic memory process where events, words or objects in the environment match stored information and bring a related memory into consciousness without any ‘request’ for its retrieval. Although they are very common and normal, they can be troublesome in PTSD flashbacks, epilepsy and under some drugs.

The IAMs that people notice and make note of seem to occur when they are not concentrating on a task but instead doing something like walking or eating. But with other methodology they can occur more often. One method is to record subjects as they generate continuous free word associations for half a minute and then play them the tape and have them report any autobiographical memories that had come to mind during the chain of associations. About 90% had IAMs. So they are probably much more common than we notice.

“IAMs are more likely to be of a specific event, and come to mind significantly faster than voluntary autobiographical memories. They are also more likely to result in bodily reactions and impact on current mood than voluntary memories. However, no differences were observed in terms of perspective experienced in memory (field vs. observer) and the accuracy (measured by participants’ own confidence ratings) of recorded memories.”

“According to Conway and Pleydell- Pearce’s influential model of autobiographical memory, during involuntary recall ‘ecphoric’ cues can bypass the usual top-down strategic retrieval pathway, involving activation of the left frontal lobe, resulting in a rapid formation of memory.”

When Penfield stimulated the temporal lobe - “The resulting phenomena included sights, sounds and emotions of past events, which the patients recognised spontaneously as personal experiences, and noted that their ‘vividness or wealth of detail and the sense of immediacy that goes with them serves to set them apart from the ordinary process of recollection’ .”

“Hall carried out a PET study in healthy controls, using emotionally charged pictorial cues, and found that involuntary memory retrieval by-passed the initial search process, mediated by the prefrontal cortex, which occurs in conscious voluntary retrieval. This concurs with Conway … that involuntary retrieval can bypass the pathway involving activation of the left prefrontal lobe. ”

“Because of the automatic nature of retrieval, involuntary memories may not require any working memory input. ”

The authors of this article and their sources appear to treat IAMs as common but not that common and fairly vivid. These are the ones people are aware of, anyway. But I am inclined to think that this automatic presentation of memories is going on much of the time. And much of it would not be surprising or noteworthy . Computers have procedures to guess what the CPU is going to want fetched next on the basis of what the last few fetches were. Many systems (car suspensions for example on expensive cars) have ways to look ahead and prepare for future demands. This is a common method of increasing efficiency. Why would our memories not have an automatic ‘lookahead’? Clues that we encounter should give us access to past experiences that may be helpful in the near future, and should do it immediately and without us realizing we needed that help. Those that are exceptional memories for one reason or another would become prominent in the stream of consciousness and if it is not obvious that the memory was prompted by this or that item in consciousness then it would appear to ‘pop’ in.