Brain Regions

Biological clocks and memory

I’ve always been interested in the body’s clocks — and one of the most interesting things is that it is clocks, in the plural. It appears the main clock is located in a part of the brain structure called the hypothalamus (a very important structure in the brain, although not one of much importance to learning and memory). The part of the hypothalamus that regulates time is called the suprachiasmatic nuclei. These cells contain genes that switch on, off, and on again over a 24-hour period, and send electrical pulses and hormones through the body. This is the body’s master clock.

But it is not the only clock in the body. Each organ in the body uses the time signal from the master clock to set its own clock. As a consequence, different systems in the body operate on different schedules. Thus blood pressure peaks at one particular time of the day, and levels of the stress hormone cortisol rise and fall in accordance with the clock that governs this.

The effect of this is that certain physical disorders are more likely to occur at particular times, and, more significantly, that certain medications may be far more effective at certain times.

What does all this have to do with learning and memory?

Well, not a whole lot of research has been done on the effects of time of day on cognitive performance, but what has been done is reasonably consistent. It seems clear that, for many people (but not all), there are significant time of day effects. The most reliable is that, in general, teenagers and young adults perform best (mentally) in the afternoon, while older adults (seniors) perform best in the morning.

Having said that, let’s qualify it a little.

Let’s start with a table. Now, this represents the findings of one study [4], so let’s not get carried away with the illusion of precision cast by actual numbers. Nevertheless, it is interesting. These percentages represent the preferences reported by the young and old participants in the study. These preferences correlated with improved performance on a memory test.

  Young Old
Definite morning 0% 34%
Moderate morning 8% 49%
No preference 57% 10%
Moderate evening 29% 6%
Definite evening 6% 1%

Now the first thing to note is how marked the differences are between young and old. Of particular interest is how many of the younger adults had no preference. Compare this with that of older adults. The second finding of particular note is how pronounced the preference for the morning is in older adults — 83% preferred morning. And, most interesting of all, is a finding from another study by the same researchers [5]: when tested at their preferred time, older adults performed comparably to younger adults on a memory task. Younger adults, by contrast, seem able to perform well at all times.

There is also some evidence [3] that the deleterious effect of interference (the intrusion of irrelevant words, objects, events) is worse for older adults at those times of day when their performance is poorer. Older adults are more vulnerable to interference than younger adults.

The findings for teenagers and young adults may also apply to children. One study [2] found that below-grade-level students who received reading instruction in the afternoon improved their performance more than those students who received instruction in the morning.

But it must always be remembered that this general principle that morning is better for the aged, and afternoon better for the young, does not apply to each and every individual. As the table tells us, time of day affects some people more than others, and time preference is an individual matter, not entirely predicted by age. This is underscored by a study [1] that found improved performance when students were taught at times that matched their preferences. There was also some evidence that, for some students at least, achievement was greater when they were taught during their teacher's ideal time of day.

None of this is an argument that you should resign yourself to learning only at your preferred time of day! But you could use the information to modify your strategies. For example, by scheduling difficult work for your optimal time (assuming you have an optimal time, and are not one of those fortunate people who have no strong preference). You can also try and counteract the effect by, for example, drinking coffee during your nonoptimal time of day (this was found to be effective in one study with older adults [6]).

References: 
  1. Ammons, T.L., Booker, J.L. & Killmon, C.P. 1995. The effects of time of day on student attention and achievement. (ERIC Document Reproduction Service No. ED 384 592)
  2. Barron, B., Henderson, M. & Spurgeon, R. 1994. Effects of time of day instruction on reading achievement of below grade readers. Reading Improvement, 31(1), 56–60.
  3. Hasher, L., Chung, C., May, C.P. & Foong, N. 2002. Age, Time of Testing, and Proactive Interference. Canadian Journal of Experimental Psychology, 56, 200-207.
  4. Intons-Peterson, M.J., Rocchi, P., West, T., McLellan, K. and Hackney, A. 1998. Aging, optimal testing times, and negative priming.Journal of Experimental Psychology: Learning, Memory, and Cognition, 24(2), 362-376.
  5. Intons-Peterson, M.J., Rocchi, P., West, T., McLellan, K. and Hackney, A. 1999. Age, testing at preferred or nonpreferred times (testing optimality), and false memory. Journal of Experimental Psychology: Learning, Memory, and Cognition, 25(1), 23-40.
  6. Ryan, L., Hatfield, C. & Hofstetter, M. 2002. Caffeine Reduces Time-of-Day Effects on Memory Performance in Older Adults. Psychological Science, 13 (1), 68-71.
  7. West, R., Murphy, K.J., Armilio, M.L., Craik, F.I.M. & Stuss, D.T. 2002. Effects of Time of Day on Age Differences in Working Memory. Journals of Gerontology Series B, 57 (1), P3-P10

Evidence that IQ is rooted in two main brain networks

A very large online study helps decide between the idea of intelligence as a single factor (‘g’) versus having multiple domains.

An online study open to anyone, that ended up involving over 100,000 people of all ages from around the world, put participants through 12 cognitive tests, as well as questioning them about their background and lifestyle habits. This, together with a small brain-scan data set, provided an immense data set to investigate the long-running issue: is there such a thing as ‘g’ — i.e. is intelligence accounted for by just a single general factor; is it supported by just one brain network? — or are there multiple systems involved?

Brain scans of 16 healthy young adults who underwent the 12 cognitive tests revealed two main brain networks, with all the tasks that needed to be actively maintained in working memory (e.g., Spatial Working Memory, Digit Span, Visuospatial Working Memory) loading heavily on one, and tasks in which information had to transformed according to logical rules (e.g., Deductive Reasoning, Grammatical Reasoning, Spatial Rotation, Color-Word Remapping) loading heavily on the other.

The first of these networks involved the insula/frontal operculum, the superior frontal sulcus, and the ventral part of the anterior cingulate cortex/pre-supplementary motor area. The second involved the inferior frontal sulcus, inferior parietal cortex, and the dorsal part of the ACC/pre-SMA.

Just a reminder of individual differences, however — when analyzed by individual, this pattern was observed in 13 of the 16 participants (who are not a very heterogeneous bunch — I strongly suspect they are college students).

Still, it seems reasonable to conclude, as the researchers do, that at least two functional networks are involved in ‘intelligence’, with all 12 cognitive tasks using both networks but to highly variable extents.

Behavioral data from some 60,000 participants in the internet study who completed all tasks and questionnaires revealed that there was no positive correlation between performance on the working memory tasks and the reasoning tasks. In other words, these two factors are largely independent.

Analysis of this data revealed three, rather than two, broad components to overall cognitive performance: working memory; reasoning; and verbal processing. Re-analysis of the imaging data in search of the substrate underlying this verbal component revealed that the left inferior frontal gyrus and temporal lobes were significantly more active on tasks that loaded on the verbal component.

These three components could also be distinguished when looking at other factors. For example, while age was the most significant predictor of cognitive performance, its effect on the verbal component was much later and milder than it was for the other two components. Level of education was more important for the verbal component than the other two, while the playing of computer games had an effect on working memory and reasoning but not verbal. Chronic anxiety affected working memory but not reasoning or verbal. Smoking affected working memory more than the others. Unsurprisingly, geographical location affected verbal more than the other two components.

A further test, involving 35 healthy young adults, compared performance on the 12 tasks and score on the Cattell Culture Fair test (a classic pen and paper IQ test). The working memory component correlated most with the Cattell score, followed by the reasoning component, with the Verbal component (unsurprisingly, given that this is designed to be a ‘culture-fair’ test) showing the smallest correlation.

All of this is to say that this is decided evidence that what is generally considered ‘intelligence’ is based on the functioning of multiple brain networks rather than a single ‘g’, and that these networks are largely independent. Thus, the need to focus on and maintain task-relevant information maps onto one particular brain network, and is one strand. Another network specializes in transforming information, regardless of source or type. These, it would seem, are the main processes involved in fluid intelligence, while the Verbal component most likely reflects crystallized intelligence. There are also likely to be other networks which are not perhaps typically included in ‘general intelligence’, but are nevertheless critical for task performance (the researchers suggest the ability to adapt plans based on outcomes might be one such function).

The obvious corollary of all this is that similar IQ scores can reflect different abilities for these strands — e.g., even if your working memory capacity is not brilliant, you can develop your reasoning and verbal abilities. All this is consistent with the growing evidence that, although fundamental WMC might be fixed (and I use the word ‘fundamental’ deliberately, because WMC can be measured in a number of different ways, and I do think you can, at the least, effectively increase your WMC), intelligence (because some of its components are trainable) is not.

If you want to participate in this research, a new version of the tests is available at http://www.cambridgebrainsciences.com/theIQchallenge

Reference: 

[3214] Hampshire, A., Highfield R. R., Parkin B. L., & Owen A. M. (2012).  Fractionating Human Intelligence. Neuron. 76(6), 1225 - 1237.

Advice vs. experience: Genes predict learning style

Three gene variants governing dopamine response in the prefrontal cortex and the striatum affect how likely we are to persist with inaccurate beliefs in the face of contradictory experience.

We learn from what we read and what people tell us, and we learn from our own experience. Although you would think that personal experience would easily trump other people’s advice, we in fact tend to favor abstract information against our own experience. This is seen in the way we commonly distort what we experience in ways that match what we already believe. But there is probably good reason for this tendency (reflected in confirmation bias), even if it sometimes goes wrong.

But of course individuals vary in the extent to which they persist with bad advice. A new study points to genes as a critical reason. Different brain regions are involved in the processing of these two information sources (advice vs experience): the prefrontal cortex and the striatum. Variants in the genes DARPP-32 and DRD2 affect the response to dopamine in the striatum. Variation in the gene COMT, on the other hand, affects dopamine response in the prefrontal cortex.

In the study, over 70 people performed a computerized learning task in which they had to pick the "correct" symbol, which they learned through trial and error. For some symbols, subjects were given advice, and sometimes that advice was wrong.

COMT gene variants were predictive of the degree to which participants persisted in responding in accordance with prior instructions even as evidence against their correctness grew. Variants in DARPP-32 and DRD2 predicted learning from positive and negative outcomes, and the degree to which such learning was overly inflated or neglected when outcomes were consistent or inconsistent with prior instructions.

Reference: 

The importance of the cerebellum for intelligence and age-related cognitive decline

A new study of older adults indicates atrophy of the cerebellum is an important factor in cognitive decline for men, but not women.

Shrinking of the frontal lobe has been associated with age-related cognitive decline for some time. But other brain regions support the work of the frontal lobe. One in particular is the cerebellum. A study involving 228 participants in the Aberdeen Longitudinal Study of Cognitive Ageing (mean age 68.7) has revealed that there is a significant relationship between grey matter volume in the cerebellum and general intelligence in men, but not women.

Additionally, a number of other brain regions showed an association between gray matter and intelligence, in particular Brodmann Area 47, the anterior cingulate, and the superior temporal gyrus. Atrophy in the anterior cingulate has been implicated as an early marker of Alzheimer’s, as has the superior temporal gyrus.

The gender difference was not completely unexpected — previous research has indicated that the cerebellum shrinks proportionally more with age in men than women. More surprising was the fact that there was no significant association between white memory volume and general intelligence. This contrasts with the finding of a study involving older adults aged 79-80. It is speculated that this association may not develop until greater brain atrophy has occurred.

It is also interesting that the study found no significant relationship between frontal lobe volume and general intelligence — although the effect of cerebellar volume is assumed to occur via its role in supporting the frontal lobe.

The cerebellum is thought to play a vital role in three relevant areas: speed of information processing; variability of information processing; development of automaticity through practice.

Better reading may mean poorer face recognition

Evidence that illiterates use a brain region involved in reading for face processing to a greater extent than readers do, suggests that reading may have hijacked the network used for object recognition.

An imaging study of 10 illiterates, 22 people who learned to read as adults and 31 who did so as children, has confirmed that the visual word form area (involved in linking sounds with written symbols) showed more activation in better readers, although everyone had similar levels of activation in that area when listening to spoken sentences. More importantly, it also revealed that this area was much less active among the better readers when they were looking at pictures of faces.

Other changes in activation patterns were also evident (for example, readers showed greater activation in the planum temporal in response to spoken speech), and most of the changes occurred even among those who acquired literacy in adulthood — showing that the brain re-structuring doesn’t depend on a particular time-window.

The finding of competition between face and word processing is consistent with the researcher’s theory that reading may have hijacked a neural network used to help us visually track animals, and raises the intriguing possibility that our face-perception abilities suffer in proportion to our reading skills.

Brain hub helps us switch attention

The intraparietal sulcus appears to be a hub for connecting the different sensory-processing areas as well as higher-order processes, and may be key to attention problems.

If our brains are full of clusters of neurons resolutely only responding to specific features (as suggested in my earlier report), how do we bring it all together, and how do we switch from one point of interest to another? A new study using resting state data from 58 healthy adolescents and young adults has found that the intraparietal sulcus, situated at the intersection of visual, somatosensory, and auditory association cortices and known to be a key area for processing attention, contains a miniature map of all the things we can pay attention to (visual, auditory, motor stimuli etc).

Moreover, this map is copied in at least 13 other places in the brain, all of which are connected to the intraparietal sulcus. Each copy appears to do something different with the information. For instance, one map processes eye movements while another processes analytical information. This map of the world may be a fundamental building block for how information is represented in the brain.

There were also distinct clusters within the intraparietal sulcus that showed different levels of connectivity to auditory, visual, somatosensory, and default mode networks, suggesting they are specialized for different sensory modalities.

The findings add to our understanding of how we can shift our attention so precisely, and may eventually help us devise ways of treating disorders where attention processing is off, such as autism, attention deficit disorder, and schizophrenia.

Reference: 

[1976] Anderson, J. S., Ferguson M. A., Lopez-Larson M., & Yurgelun-Todd D. (2010).  Topographic maps of multisensory attention. Proceedings of the National Academy of Sciences. 107(46), 20110 - 20114.

Brain area organized by color and orientation

Object perception rests on groups of neurons that respond to specific attributes.

New imaging techniques used on macaque monkeys explains why we find it so easy to scan many items quickly when we’re focused on one attribute, and how we can be so blind to attributes and objects we’re not focused on.

The study reveals that a region of the visual cortex called V4, which is involved in visual object recognition, shows extensive compartmentalization. There are areas for specific colors; areas for specific orientations, such as horizontal or vertical. Other groups of neurons are thought to process more complex aspects of color and form, such as integrating different contours that are the same color, to achieve overall shape perception.

Reference: 

[1998] Tanigawa, H., Lu H. D., & Roe A. W. (2010).  Functional organization for color and orientation in macaque V4. Nat Neurosci. 13(12), 1542 - 1548.

Damage to amygdala can be compensated by another region

A memory function thought to require a specific brain region called the amygdala has now been found to be able to be performed by another region, if the amygdala is impaired.

A number of studies in recent years have revealed the amazing ability of the human brain to compensate for damage down to its part. In the latest of these, it’s been found that loss of the amygdala doesn’t have to mean that new memories will be void of emotion. Instead, it appears, a region called the bed nuclei can step in to take its place. The bed nuclei are slower to process information than the amygdala, and in normal circumstances are inhibited by the amygdala. The study looked specifically at fear conditioning, for which the amygdala has been considered crucial.

The finding offers the hope that therapies to promote compensatory shifts in function might help those who have suffered damage to parts of their brain.

Brain system behind general intelligence identified

Data from brain-lesion patients supports the idea that general intelligence depends on the brain's ability to integrate several different kinds of processing, and resides in a distributed network.

Using a large data set of 241 brain-lesion patients, researchers have mapped the location of each patient's lesion and correlated that with each patient's IQ score to produce a map of the brain regions that influence intelligence. Consistent with other recent findings, and with the theory that general intelligence depends on the brain's ability to integrate several different kinds of processing, they found general intelligence was determined by a distributed network in the frontal and parietal cortex, critically including white matter association tracts and frontopolar cortex. They suggest that general intelligence draws on connections between regions that integrate verbal, visuospatial, working memory, and executive processes.

Reference: 

[173] Gläscher, J., Rudrauf D., Colom R., Paul L. K., Tranel D., Damasio H., et al. (2010).  Distributed neural system for general intelligence revealed by lesion mapping. Proceedings of the National Academy of Sciences. 107(10), 4705 - 4709.

The mediotemporal lobe

The mediotemporal lobe is critically involved in both initial learning of facts and events and their later consolidation.

Dysfunction in the mediotemporal lobe is a major factor in age-related cognitive decline.

The most significant component of the MTL is the hippocampus.

The hippocampus contains specialized neurons that categorize incoming sensory information, and others that are involved in the forming of new associations.

The hippocampus is crucial for episodic memory - the remembering of specific events and experiences. It is also particularly involved in spatial memory.

The hippocampus appears to be involved in consolidation processes, but only in the initial stages and for the first few years.

The part of the hippocampus called the dentate gyrus is crucial for encoding new information (and is thus implicated in working memory). The dentate gyrus is one of the few brain regions in which new nerve cells can be created in adult brains.

The main processing part of the hippocampus, the cornu ammonis, is distinguished by a high number of neurons which loop back on themselves - enabling the output of the neuron to influence its input; this may be critical for associative power.

Other components of the mediotemporal lobe include the rhinal cortex and the amygdala.

The entorhinal cortex appears to be involved in long-term memory consolidation beyond the first few years. It is one of the first regions damaged in Alzheimer's.

The perirhinal cortex is crucial for object recognition.

The amygdala is primarily responsible for processing emotional responses. The connection between hippocampus and amygdala underlies the role of emotion in memory.

The mediotemporal lobe (MTL) is a concept rather than a defined brain structure. It includes the hippocampus, the amygdala, and the entorhinal and perirhinal cortices - all structures within the medial area of the temporal lobe.The temporal lobe is in general primarily concerned with sensory experience - specifically, with hearing, and with the integration of information from multiple senses. Part of the temporal lobe also plays a role in memory processing. It is situated below the frontal and parietal lobes, and above the hindbrain.

Originally conceived as an integrated memory system with a common function, this view of the MTL has recently been questioned. For one thing, the region didn’t evolve as one unit — the different regions arose at different times during primate evolution. Therefore, can it really be an integrated system with a common function? Work with rhesus monkeys suggests rather that these different parts may serve cooperative and even competitive functions.

This question, however, is really one for the specialist. As far as most of us are concerned, the concept of a "mediotemporal lobe" serves as a handy label for a group of connected brain structures that are all absolutely crucial for learning and memory (and reminds us of the location of these structures).

It should also be remembered that brain structures are notoriously "fuzzy" — different researchers will use different names, and group different structures. For example, one report has contrasted the functions of the MTL with that of the basal ganglia, although the amygdala is a member of both. Other studies talk of the hippocampus AND the dentate gyrus, although others put the dentate gyrus as a substructure of the hippocampus. I mention this only to warn you, if you find trawl through various reports and find such discrepancies. They can be confusing. I have tried to integrate such discrepancies into a consistent description that seems to make most sense. Just bear in mind that dividing the brain into separate structures is not an exact science.

Functions of the MTL

The MTL has been particularly implicated in the process of memory consolidation - the process by which new memories become progressively more stable (see my article on consolidation for more details). Lesions in the MTL typically produce amnesia characterized by the disproportionate loss of recently acquired memories. A recent imaging study confirms this view by showing temporally graded changes in MTL activity in healthy older adults.

Progressive atrophy in the mediotemporal lobe also appears to be the most significant predictor of cognitive decline in seniors. Elderly persons with a poor memory have less activity in the mediotemporal lobe when storing new information than elderly persons with a normally functioning memory.

The MTL also appears to be particularly important during initial learning. Research has found rapid modulation of activity in the MTL at the beginning of learning, with this activity rapidly declining with training.

All this indicates that the MTL is not only hugely important, but that it covers a quite extraordinary range of functions. The reason for this lies in the fact that the MTL is not a single brain structure.

Components of the MTL

It is probably fair to say that the original concept of the MTL was, at least in part, a reflection of the inability of early researchers to "see" the activity in the brain in very much detail. Now, of course, neurological techniques have progressed to the point of being able to pinpoint activity to a quite fantastic level. It is therefore now possible to some degree to disentangle the functions of the various components of the MTL.

The most significant of the individual components of the MTL is the hippocampus. The hippocampus, one of the oldest parts of the brain, is important for the forming, and perhaps long-term storage, of associative and episodic memories. It is thus absolutely critical for learning and memory, and a brain region much studied by researchers.

The hippocampus

In recent years, the hippocampus has been specifically implicated in (among other things) the encoding of face-name associations, the retrieval of face-name associations, the encoding of events, the recall of personal memories in response to smells. It may also be involved in the processes by which memories are consolidated during sleep.

A variety of specialized neurons have been found in the hippocampus. For example,

  • "categorizing cells", which streamline and simplify sensory information, markedly reducing the brain's workload, by categorizing stimuli into various classes (categories that have been acquired through experience).
  • "changing cells", which appear to be involved in the initial formation of new associative memories, and may also, in some cases, be involved in the eventual storage of the associations in long-term memory.
  • "place cells", which become active in response to specific spatial locations; some of these cells also seem to be sensitive to recent or impending events, thus enabling you to place location within a temporal context (e.g., is this somewhere I've just been, or somewhere I intended to go?).

The existence of place cells is supported by other evidence for the role of the hippocampus in spatial navigation and memory. For example, London taxi drivers (famous for their extensive knowledge of London - a spatial task) have been found to have, on average, significantly bigger hippocampuses than "ordinary motorists". In similar vein, the chickadee, a tiny songbird, gathers and stores seeds in the fall, and at this time its hippocampus expands in volume by some 30% by adding new nerve cells. It shrinks back in the spring.

The role of the hippocampus in episodic (event) memory is underscored by findings that deficiencies in the hippocampus play a key role in alcoholism-related Korsakoff's syndrome (a memory disorder), as well as Alzheimer's disease.

The hippocampus has also been implicated in memory consolidation processes, but evidence now suggests the hippocampus may participate only in consolidation processes lasting a few years. It is probably critical for the initial consolidation of memories that appears to take place during sleep (see my article on sleep and memory for more detail on this). Rat studies have found that, during sleep (mostly the slow-wave phase), the thalamus at the base of their brains produced bursts of electrical activity, which were then detected in the somatosensory neocortex. Some 50 msec later, the hippocampus responded with a pulse of electricity. It’s suggested that this pulse is the hippocampus sending back compressed waves of the information learned during the day to the neocortex where they are filed away for future reference.

The evidence that some memories might be held in the hippocampus for several years, only to move on, as it were, to another region, is an interesting complication to our earlier simple view of memory dividing into "short-term memory" and "long-term memory". It seems that long-term memory, now better labeled as permanent memory, is far from being the straightforward storage system that we once envisaged. Not only do memories become reconstructed, but they become, it would seem, re-filed. The implications of this, still speculative, relocation, are as yet unknown. Perhaps memories in this "permastore" are more resistant to change.

Substructures of the hippocampus

There are several substructures within the hippocampus. It is only very recently that researchers have been able to go inside the hippocampus, as it were, and pinpoint hippocampal activity to particular substructures.

  • the dentate gyrus: is the main entry point for nerve fibers into the hippocampal formation. Rat studies suggest that the dentate gyrus is crucial for the acquiring of new information, and the functioning of working memory. Most recently, it has been implicated with the cornu ammonis as being highly active during encoding offace-name pairs. The dentate gyrus is one of the very few regions in the adult brain that appears to allow neurogenesis (creation of new nerve cells). Neurogenesis in the dentate gyrus has been found to be significantly reduced in marmoset monkeys when exposed to stress. Dysfunction in the dentate gyrus appears to be linked to cognitive deficits in those suffering from Alzheimer's. The granule cells in the dentate gyrus project to the pyramidal cells in the cornu ammonis.
  • the cornu ammonis: is thought to be the main site of memory processing in the hippocampal formation. Most recently, it has been implicated with the dentate gyrus as being highly active during encoding offace-name pairs. Part of the cornu ammonis (CA3) has been of special interest due to its high number of recursive neurons (nerve fibers which loop back on themselves - enabling the output of the neuron to influence its input). Most recently, the CA3 has been found to be crucial for recalling memories from partial representations of the original stimulus (for example, when memories are triggered by smells).
  • the subiculum: can be thought of as the "last stage" of processing in the hippocampal formation. It is the primary target of the pyramidal cells in CA1. The subiculum is connected to the perirhinal, entorhinal and prefrontal cortices, and thus is in a position to integrate information from several sources and pass this information on. The subiculum however has been much less studied than the other substructures of the hippocampal formation. Recently, it has been found to be active during the retrieval of newly learned face-name associations.

The rhinal cortex

The entorhinal cortex is a region upon which nerve fibers from many sensory systems converge. It is the main input to the hippocampus, and also the main output. This is why damage to this region is so serious. The entorhinal cortex is one of the first regions damaged in the early stages of Alzheimer's.

It has also been suggested that the entorhinal cortex handles “incremental learning” — learning that requires repeated experiences. “Episodic learning” — memories that are stored after only one occurrence — might be mainly stored in the hippocampus.

While the hippocampus appears to participate in memory consolidation processes only for the first few years, the entorhinal cortex seems to be associated with temporally graded changes extending up to 20 years - suggesting that it is the entorhinal cortex, rather than the hippocampus, that participates in memory consolidation over decades.

The perirhinal cortex has been a largely neglected region. It is adjacent to the visual processing area, as well as the entorhinal cortex, and recent research demonstrates that it is important for recognizing objects. In particular, it is crucial for recognizing the many features of an object, while still recognizing it as a single entity. The perirhinal cortex also appears to be involved in associating objects with other objects, and even with abstractions such as a goal. Unsurprisingly, in view of its involvement in recognition memory, it appears to play a critical role in establishing the familiarity of an item.

While the hippocampus is also involved in object recognition, the functions of the two regions appear quite different.

The amygdala

The amygdala is part of the basal ganglia, large "knots" of nerve cells deep in the cerebrum, thought to be involved in various aspects of motor behavior (Parkinson's disease, for example, is an affliction of the basal ganglia). The amygdala has many connections with other parts of the brain, and is critically involved in computing the emotional significance of events. Recent research indicates it is responsible for the influence of emotion on perception, through its connections with those brain regions that process sensory experiences. Rat studies also suggest that the amygdala, in tandem with the orbitofrontal cortex, is involved in the forming of new associations between cues and outcomes - in other words, it is the work of the amygdala to teach us what happens to us when we do something.

The connection between the amygdala and the hippocampus helps explain why emotion can have such powerful effect on learning and memory (to put it crudely, the amygdala remembers the feelings, and the hippocampus remembers what event elicited those feelings). (see article on emotion and memory)

The brain is a network

It must always be remembered that no structure within the brain acts on its own. This is reinforced by a recent study that found that, as subjects studied word lists, clusters of neurons in the rhinal cortex and the hippocampus fired synchronized electrical bursts, with this coordinated activity plummeting for a fraction of a second just after participants remembered a word from the list. This has led to speculation that memory relies more on the timing (coordination) than on the strength of neural activity.

We still know very little about the ways in which these structures interact; only as we gain more knowledge about this will we know whether we are justified in talking about a "mediotemporal lobe". Nevertheless, this region of the brain is undoubtedly vital for what we might term "stereotypical" memory - the memory domains we are most likely to be thinking of when we think of memory.

References: 
  • Anderson, A.K. & Phelps, E.A. 2001. Lesions of the human amygdala impair enhanced perception of emotionally salient events. Nature, 411, 305-309.
  • Ekstrom, A.D., Kahana, M.J., Caplan, J.B., Fields, T.A., Isham, E.A., Newman, E.L. & Fried, I. 2003. Cellular networks underlying human spatial navigation.Nature, 425 (6954), 184-7.
  • Fell, J., Klaver, P., Lehnertz, K., Grunwald, T., Schaller, C., Elger, C.E. & Fernández, G. 2001. Human memory formation is accompanied by rhinal-hippocampal coupling and decoupling. Nature Neuroscience 4(12), 1259-1264.
  • Haist, F., Gore, J.B. & Mao, H. 2001. Consolidation of human memory over decades revealed by functional magnetic resonance imaging. Nature neuroscience, 4 (11), 1139-1145.
  • Hampson, R.E., Pons, T.P., Stanford, T.R. & Deadwyler, S.A. 2004. Categorization in the monkey hippocampus: A possible mechanism for encoding information into memory. PNAS, 101, 3184-3189.
  • McLeod, P., Plunkett, K. & Rolls, E.T. 1998. Introduction to Connectionist Modelling of Cognitive Processes. Oxford: Oxford University Press.
  • Nakazawa, K., Quirk, M.C., Chitwood, R.A., Watanabe, M., Yeckel, M.F., Sun, L.D., Kato, A., Carr, C.A., Johnston, D., Wilson, M.A. & Tonegawa, S. 2002. Requirement for Hippocampal CA3 NMDA Receptors in Associative Memory Recall. Science 297, 211-218.
  • Poldrack, R.A., Clark, J., Paré-blagoev, E.J., Shohamy, D., Moyano, J.C., Myers, C. & Gluck, M.A. 2001. Interactive memory systems in the human brain. Nature, 414, 546-550.
  • Ribeiro, S., Gervasoni, D., Soares, E.S., Zhou, Y., Lin, S-C., Pantoja, J., Lavine, M. & Nicolelis, M.A.L. 2004. Long-Lasting Novelty-Induced Neuronal Reverberation during Slow-Wave Sleep in Multiple Forebrain Areas. PLoS Biol 2(1): e24 DOI:10.1371/journal.pbio.0020024.
  • Rusinek, H., De Santi, S., Frid, D., Tsui, W-H., Tarshish, C.Y., Convit, A., & de Leon, M.J. 2003. Regional Brain Atrophy Rate Predicts Future Cognitive Decline: 6-year Longitudinal MR Imaging Study of Normal Aging. Radiology, 229, 691-696.
  • Schoenbaum, G., Setlow, B., Saddoris, M.P. & Gallagher, M. 2003. Encoding Predicted Outcome and Acquired Value in Orbitofrontal Cortex during Cue Sampling Depends upon Input from Basolateral Amygdala. Neuron, 39, 855-867.
  • Sirota, A., Csicsvari, J., Buhl, D. & Buzsáki, G. 2003. Communication between neocortex and hippocampus during sleep in rodents. Proc. Natl. Acad. Sci. USA, 100 (4), 2065-2069.
  • Wirth, S., Yanike, M., Frank, L.M., Smith, A.C., Brown, E.N. & Suzuki, W.A. 2003. Single Neurons in the Monkey Hippocampus and Learning of New Associations. Science, 300, 1578-1581.
  • Zeineh, M.M., Engel, S.A., Thompson, P.M. & Bookheimer, S.Y. 2003. Dynamics of the Hippocampus During Encoding and Retrieval of Face-Name Pairs, Science, 299, 577-580.
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