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Prefrontal and medial temporal lobe interactions in long-term memory

September 2003
Nature Reviews Neuroscience 4(8):637-48

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PubMed

Authors:

University College London

Cognitive neuroscience has made considerable progress in understanding the involvement of the medial temporal and frontal lobes in long-term memory. Whereas the medial temporal lobe has traditionally been associated with the encoding, storage and retrieval of long-term memories, the prefrontal cortex has been linked with cognitive control processes such as selection, engagement, monitoring and inhibition. However, there has been little attempt to understand how these regions might interact during encoding and retrieval, and little consideration of the anatomical connections between them. Recent advances in functional neuroimaging, neurophysiology, crossed-lesion neuropsychology and computational modelling highlight the importance of understanding how the medial temporal and frontal lobes interact to allow successful remembering, and provide an opportunity to explore these interactions.

| Medial temporal lobe function. a | Controversy concerning the effects of selective hippocampal damage on recollection and familiarity. The panel shows the performance of four patients with damage restricted to the hippocampal region on the Doors and People Test 134 of recall (based on recollection) and recognition (considered to be based on a combination of recollection and familiarity), expressed as combined scaled scores. A score of 10 (dashed line) represents the population mean for each patient's age group. Some patients, such as Jon 32 and YR 33 , have impaired recall but preserved recognition. Other patients, such as LG and PH 35 , are impaired at both recall and recognition. The reasons for this discrepancy are unclear. b | Comparison of recognition memory performance and atrophy affecting the region of the perirhinal cortex (assessed by measuring depth of collateral sulcus from magnetic resonance imaging (MRI) scans) in patients with semantic dementia. The panel shows a significant correlation between increasing atrophy and impaired recognition memory. Units are rated extent of atrophy (where zero is normal) and proportion correct for recognition memory, combining data from two experiments 38,39. c | Results of a functional MRI experiment on encoding processes. The activation in the left perirhinal cortex during encoding predicts whether words are later recognized as familiar, not whether the source of items is recollected 52. Panel c modified, with permission, from REF. 52  (2003) National Academy of Sciences, USA.

…

| Prefrontal cortex function. a | The performance of patients with frontal variant of frontotemporal dementia (fvFTD) on item recognition and source recollection 65. Although patients show no impairment relative to controls at recognizing previous occurrence of stimuli, their source recollection is at chance levels. b | Different regions of prefrontal cortex subserve different cognitive control operations in episodic memory 84. The left panel illustrates the logic of data interpretation, with a plus sign indicating significant activation and a minus sign indicating no significant activation. The right panel illustrates regions that show particular patterns of activation. The posterior ventrolateral prefrontal cortex (green) is activated during semantic encoding, item recognition and source recollection, and so is associated with lexical/phonological processing according to interpretation logic; the anterior ventrolateral prefrontal cortex (blue) is activated during semantic encoding and source recollection, and so is associated with semantic processing and cue specification; the dorsolateral prefrontal cortex (red) is activated during source recollection only, and so is associated with monitoring and evaluation. Panel b modified, with permission, from REF. 84  (2002) Elsevier Science.

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The ability of humans and other animals to remember

past experiences, which forms an integral part of our

existence, has long fascinated philosophers and scientists.

With advances in our knowledge of brain function, the

study of the contributions made by different brain

regions to memory has occupied a central position in

cognitive neuroscience. Studies involving patients with

amnesia and animals with experimental lesions have

consistently identified the medial temporal lobe and the

prefrontal cortex as being crucial for memory

1–7

The medial temporal lobe comprises the hippo-

campus,

FORNIX and amygdala, and the surrounding

entorhinal, perirhinal and parahippocampal cortices

(FIG. 1).Anatomically, much of the medial temporal lobe

is shared between humans, non-human primates and

rats, with the possible exceptions of the primate

parahippocampal cortex, which is generally termed

postrhinal cortex in the rat, and of the perirhinal cortex,

the boundaries of which are less clear in man than in

other animals

. The prefrontal cortex is divided into a

medial and a lateral surface, with the latter consisting of

ventrolateral, dorsolateral and anterior prefrontal

regions, each of which might be further divisible

The rodent prefrontal cortex is relatively smaller and

less developed than in primates

. Although in different

primate species the prefrontal cortex takes up a similar

percentage of overall brain volume, regions such as the

anterior prefrontal cortex are proportionally larger in

humans, and their underlying connectivity is greater

Damage to the medial temporal lobe or the prefrontal

cortex commonly impairs memory in humans or

animals. Perhaps because these regions are anatomically

remote from one another, their roles in memory

have largely been considered independently, with little

investigation of how they might interact to support

remembering. Although other brain regions, such as

the thalamus, mamillary bodies and retrosplenial cortex,

are also important for long-term memory, we focus on

the roles of the medial temporal lobe and prefrontal

cortex. Emerging evidence from functional neuro-

imaging, neurophysiology and computational modelling

highlights the importance of interactions between these

regions for memory function, indicating that we must

understand these interactions if we are to develop a

full account of how memory processes are represented

in the brain.

PREFRONTAL AND MEDIAL

TEMPORAL LOBE INTERACTIONS

IN LONG-TERM MEMORY

Jon S. Simons* and Hugo J. Spiers

†

Cognitive neuroscience has made considerable progress in understanding the involvement of the

medial temporal and frontal lobes in long-term memory. Whereas the medial temporal lobe has

traditionally been associated with the encoding, storage and retrieval of long-term memories, the

prefrontal cortex has been linked with cognitive control processes such as selection,

engagement, monitoring and inhibition. However, there has been little attempt to understand

how these regions might interact during encoding and retrieval, and little consideration of the

anatomical connections between them. Recent advances in functional neuroimaging,

neurophysiology, crossed-lesion neuropsychology and computational modelling highlight the

importance of understanding how the medial temporal and frontal lobes interact to allow

successful remembering, and provide an opportunity to explore these interactions.

FORNIX

A major input/output of the

hippocampus, connecting it to

prefrontal cortex and a range of

subcortical structures.

*Institute of Cognitive

Neuroscience, University

College London, Alexandra

House, 17 Queen Square,

London WC1N 3AR, UK.

†

Medical Research Council

Cognition and Brain Sciences

Unit, 15 Chaucer Road,

Cambridge CB2 2EF, UK.

e-mails:

jon.simons@ucl.ac.uk;

hugo.spiers@mrc-cbu.

cam.ac.uk

doi:10.1038/nrn1178

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FAMILIARITY-BASED MEMORY

Recognition of previously

presented items based on a

feeling of familiarity in the

absence of recollection of the

earlier study episode.

DELAYED NON-MATCHING-TO-

SAMPLE

A task in which an object/item is

presented and following a delay,

presented again along with a

new item, and the participant is

required to choose the new item.

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regions of the medial temporal lobe. Some of these

studies provided evidence that distinct regions in the

medial temporal lobe support functionally dissociable

memory systems

, although this conclusion is disputed

According to the functional dissociation view, a system

involving the hippocampus (as well as the thalamus,

mamillary bodies and retrosplenial cortex) supports the

recollection of stored memories with their associated

spatiotemporal context. Consistent with this, animals

with hippocampal or fornix lesions are impaired on tests

of spatial memory

14,15

. Electrophysiological studies have

identified hippocampal neurons that respond when ani-

mals are in particular locations in an environment

16,17

and show lasting, experience-dependent plasticity

indicating that the hippocampus might provide a spatial

context that allows different aspects of an episode to be

linked over the long term

An anatomically separate system that includes the

perirhinal cortex is thought to underlie

FAMILIARITY-BASED

RECOGNITION

of previous occurrence, as measured in

animals by tests such as

DELAYED NON-MATCHING-TO-

SAMPLE

19–21

. Whether the hippocampus is also involved in

familiarity is controversial: some studies have found no

effects of hippocampal or fornix lesions on recogni-

tion

15,22,23

whereas other researchers have reported

deficits

13,24

. The importance of the perirhinal cortex

for familiarity-based memory is less controversial.

Electrophysiological studies have found perirhinal

neurons that show diminished responses to repeated

stimuli

25,26

, whereas few such neurons have been found

in the hippocampus

27,28

. The perirhinal cortex might

have a role in perceptual as well as mnemonic processing,

with evidence that complex feature conjunctions might

be represented in this region

29,30

Clinical studies can also address whether recollection

and familiarity are supported by anatomically separate

neural systems. Although most amnesic patients are

impaired on both forms of memory, some patients that

have selective damage to the hippocampus or connecting

structures such as the fornix show impaired recollection

with relatively preserved familiarity-based memory

31–34

Again, other researchers have reported familiarity deficits

after selective hippocampal damage

(FIG. 2a). Selective

lesions of the perirhinal cortex in humans are rare, but

two patients with extensive medial temporal lobe

damage that included the perirhinal cortex showed worse

recognition memory than patients with selective

hippocampal damage

36,37

. Furthermore, there is evidence

from patients with

SEMANTIC DEMENTIA that the extent of

impairment of recognition memory correlates signifi-

cantly more highly with the degree of atrophy of the

perirhinal region than of the hippocampus

38,39

(FIG. 2b).

Another controversy centres on the involvement of

the hippocampus in the consolidation and retrieval

of memories from the past. One hypothesis is that the

hippocampus has a time-limited role in remote memory,

with the temporal neocortex becoming more important

after a certain time

2,3,40

, whereas others propose that the

hippocampus is involved in retrieving memories from

the entire lifespan

41,42

. Little is known about the effect on

retrograde memory of lesions to connecting structures

We begin by documenting what is known about the

memory processes subserved by the medial temporal

lobe and prefrontal cortex. We then characterize some

of the functional interactions between these regions,

and finally propose a unifying framework by which we

can better understand how they might work together to

support remembering.

Medial temporal lobe

The crucial role of regions of the medial temporal lobe

for memory processing became apparent with the first

reports of patient HM

1,12

, who became profoundly

amnesic after bilateral surgical resection of the medial

temporal lobes and partial removal of hippocampal

structures to relieve epilepsy. Such observations

prompted researchers to use animal models to investigate

memory impairments associated with lesions to specific

DLPFC

APFC

Hippocampus

Fornix

Lateral view

Connectionsc

Medial viewb

Neocortical association

areas

Parahippocampal

cortex

Perirhinal

cortex

Hippocampus

MPFC

Entorhinal cortex

APFC

VLPFC

MPFC

Subcortical nuclei

Fornix

DLPFC

VLPFC

Figure 1 | Anatomy of the medial temporal lobe and prefrontal cortex. a,b | The prefrontal

cortex (PFC) can be divided into anterior (APFC, Brodmann area (BA) 10), dorsolateral (DLPFC,

BA 46 and 9), ventrolateral (VLPFC, BA 44, 45 and 47) and medial (MPFC, BA 25 and 32)

regions. BAs 11, 12 and 14 are commonly referred to as orbitofrontal cortex. The medial temporal

lobe comprises the hippocampus and amygdala, as well as the entorhinal, perirhinal and

parahippocampal neocortical regions. The hippocampus includes fields CA1–CA3 of the

hippocampus proper, the dentate gyrus and the subicular complex. c | Connections. There are

large cortico-cortical direct reciprocal connections between the PFC and the medial temporal

lobe, passing through the uncinate fascicle, anterior temporal stem and anterior corpus callosum.

The orbitofrontal and dorsolateral cortices have strong reciprocal connections with the perirhinal

and entorhinal cortices

125

. There are more connections from the PFC to the perirhinal cortex than

vice versa

126

. Unidirectional projections exist from the CA1 field to the caudal region of

MPFC

127,128

. The subicular complex and neocortical medial temporal regions have reciprocal

connections with caudal MPFC

129,130

. In addition, the medial temporal lobe receives information

from a range of unimodal and polymodal sensory association areas. This information

predominantly enters through the perirhinal and parahippocampal cortices, which project back to

these regions

131

. The PFC has reciprocal connections with sensory association cortices including

temporal and parietal regions

130

and many subcortical structures

132

. Anatomical images adapted,

with permission, from REF. 133 © (1996) Appleton & Lange.

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but not source recollection, whereas activation in hippo-

campal regions predicted subsequent recollection

(FIG. 2c). Along similar lines, a meta-analysis identified a

common region of anterior medial temporal lobe, close

to the perirhinal cortex, in which activation at retrieval

was modulated by the relative familiarity of test items

Computational network models of the medial

temporal lobe have attempted to examine many of the

issues surrounding the functional roles of the medial

temporal lobes, predominantly focusing on the

hippocampal formation and its role in memory. Marr

was the first to ascribe mathematical operations to

regions in the medial temporal lobe, suggesting that the

hippocampal formation classifies and indexes incoming

information, rapidly storing it for later transfer to neo-

cortical regions where it is reorganized during sleep.

In recent models

54–56

, different medial temporal lobe

structures are represented by layers of neurons, with the

strength of the connections between neurons corre-

sponding to the association between components of

sensory information stored in other regions of cortex. A

common feature of such models is that units of sensory

information are represented as patterns of neuronal

activity primarily in entorhinal cortex, and during

encoding this activity spreads through subregions of the

hippocampus into region CA3. In CA3, strengthening

of a limited number of

RECURRENT COLLATERAL connections

allows neurons to associate and form sparser representa-

tions of the entorhinal activation patterns which, through

a process of

PATTERN SEPARATION, are kept sufficiently

distinctive to be stored discretely from other episodes.

During retrieval, the presentation of a subset of the

original information activates the hippocampus and

causes the network to reinstate the original pattern of

activity (by

PATTERN COMPLETION), allowing recall of the

stored information. Such models vary primarily in how

the learning and activation rules operate.

Recently, researchers have attempted to address in

their models some of the controversies that surround

medial temporal lobe function. The processes involved

in recollection and familiarity have been examined by

modelling the familiarity component as a slow-learning,

distributed neocortical network and the recollection

component as a rapid-learning, associative hippocampal

network

. Memory consolidation has also been

explored, with some models positing a gradual transi-

tion from information stored in connections between

hippocampus and neocortical regions to representations

stored solely between connections in neocortical

regions

56,58

, and other models indicating that new

connections between hippocampus and neocortical

areas are created every time an

EPISODIC MEMORY trace is

retrieved

. On the basis of evidence that place cells in

the hippocampus represent spatial layout, some models

have attempted to understand how medial temporal

lobe regions might support memory for the layout of

the environment

60,61

, and it has been indicated that

connections between represented locations can be used

to retrieve and reconstruct a previously experienced

scene from a particular viewpoint and to associate this

with non-spatial aspects of the experienced event

such as the fornix, but the existing evidence is consistent

with the idea that the hippocampus is more important in

the acquisition of new information than in the retrieval of

past memories

Neuropsychological evidence for the importance of

medial temporal lobe structures in memory has led to

the use of functional neuroimaging to investigate this

area. Several early studies found no memory-related

activation in the medial temporal lobe, although

whether this was due to task characteristics or limitations

in the technology is unclear. More recently, activation in

this region has been documented during both

the encoding and retrieval of information

. Echoing the

results of animal studies, hippocampal regions (primarily

on the right) are activated during spatial memory and

navigation tasks

45,46

. Similarly, hippocampal activation

has been associated with the recollection of contextual

information

47,48

, and several studies have reported greater

activation in the hippocampus for recollection than

familiarity decisions

49–51

. There is less evidence on the role

of the perirhinal cortex in familiarity-based memory, but

in one study, activation during encoding in a region iden-

tified as perirhinal cortex predicted later item recognition

SEMANTIC DEMENTIA

A degenerative neuropathological

condition that results in the

progressive loss of semantic

knowledge as revealed through

naming, description and non-

verbal tests of semantic

knowledge, resulting from

disease of the anterior and lateral

aspects of the temporal lobes.

RECURRENT COLLATERALS

Axon connections between

pyramidal cells in the CA3

region of the hippocampus.

PATTERN SEPARATION

A process by which overlapping

neural representations are

separated to keep episodes

independent of each other in

memory.

0.25

0.15

0.05

0.25

0.15

0.05

0.9

0.8

0.7

0.6

0.5

Scaled score

Recall

Recognition

Jon

0 0.5 1 1.5 2 2.5 3

YR LG PH

Recognized

Forgotten

Item + source

Item only

Forgotten

Signal change (%)

Recognition memory

Perirhinal region atrophy

r = –0.58, p < 0.005

Figure 2 | Medial temporal lobe function. a | Controversy concerning the effects of selective

hippocampal damage on recollection and familiarity. The panel shows the performance of four

patients with damage restricted to the hippocampal region on the Doors and People Test

134

recall (based on recollection) and recognition (considered to be based on a combination of

recollection and familiarity), expressed as combined scaled scores. A score of 10 (dashed line)

represents the population mean for each patient’s age group. Some patients, such as Jon

and

, have impaired recall but preserved recognition. Other patients, such as LG and PH

, are

impaired at both recall and recognition. The reasons for this discrepancy are unclear.

b | Comparison of recognition memory performance and atrophy affecting the region of the

perirhinal cortex (assessed by measuring depth of collateral sulcus from magnetic resonance

imaging (MRI) scans) in patients with semantic dementia. The panel shows a significant

correlation between increasing atrophy and impaired recognition memory. Units are rated extent

of atrophy (where zero is normal) and proportion correct for recognition memory, combining data

from two experiments

38,39

. c | Results of a functional MRI experiment on encoding processes. The

activation in the left perirhinal cortex during encoding predicts whether words are later recognized

as familiar, not whether the source of items is recollected

. Panel c modified, with permission,

from REF. 52  (2003) National Academy of Sciences, USA.

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and familiarity tasks for difficulty, so frontal lobe patients

might perform more poorly at source recollection simply

because it is more difficult and requires greater cognitive

resources than item recognition. Patients with lesions in

orbitofrontal cortex do show deficits in reward-related

familiarity-based learning

, and functional imaging

studies have identified some prefrontal regions that

show greater activation for familiarity than recollection

decisions

49,70

Clinical lesions vary considerably in both location

and extent, but lesion and neuronal recording methods

in non-human primates and functional neuroimaging in

humans can be used to localize processes more precisely.

The predominant view is that distinct regions of

prefrontal cortex are specialized for different cognitive

functions

9,71

, although it has been suggested that

prefrontal regions might be commonly recruited

together, adapting their function depending on the

nature of the task being undertaken

72,73

. According to this

latter view, the apparent regional specialization reported

by primate and human studies could reflect relative

rather than absolute differences

Several types of regional distinction in memory

processing in the prefrontal cortex have been reported.

One prominent position has been that the left and right

frontal cortices might be lateralized for the encoding

and retrieval of memories, respectively

75,76

.More recent

evidence, however, indicates that lateralization within

the prefrontal cortex might depend as much on the type

of material being remembered as on the memory

process being undertaken

77–79

. Another key distinction

has been between the memory-related processes that are

supported by medial and lateral aspects of prefrontal

cortex. The medial surface, in particular medial

orbitofrontal cortex, has been linked with the processing

of stimulus–response mappings on the basis of

reward

80,81

. By contrast, the evidence indicates that lat-

eral prefrontal cortex subserves goal-directed cognitive

control functions that support the encoding of discrete

memory traces, and the subsequent strategic search,

retrieval and evaluation of stored representations

Prefrontal cortex

Although the importance of medial temporal lobe

structures in memory has been recognized for at least

half a century, the importance of frontal lobe regions

has been appreciated only more recently. Deficits in

memory after frontal lobe damage in humans might

go unnoticed in the context of the more obvious

symptoms such as disinhibition, impulsiveness and

disorganization, but it is clear that frontal lobe damage

can markedly impair certain aspects of memory. For

example, patients with damage to lateral prefrontal

cortex often show deficits in remembering contextual

details such as the source or recency of remembered

information

63–65

(FIG. 3a), as do those patients with

predominantly temporal lobe damage who also perform

poorly on tests of frontal lobe function

63–65

. Patients with

frontal lobe dysfunction are particularly impaired when

there is significant interference between stimuli to be

recalled

. Another memory disorder associated with

frontal lobe damage, particularly in the ventromedial

prefrontal cortex, is confabulation — the production,

often during autobiographical recollection, of statements

or beliefs that involve unintentional, and sometimes

bizarre, distortions of memory

67,68

. Confabulation is

considered to be the result of impairment to memory

control processes that are responsible for the speci-

fication of retrieval task parameters and the verification

and monitoring of recollected information

, processes

that have been associated with ventrolateral and dorso-

lateral regions of prefrontal cortex, respectively (see

later discussion).

In contrast to the deficits in recall that are associated

with frontal lobe dysfunction, other aspects of memory

are typically less affected. For example, patients with

prefrontal cortex damage who perform poorly at

discriminating the source of information are often

relatively unimpaired at recognizing the information as

having been seen before

64,65

(FIG. 3a). Such evidence has

led to the view that the prefrontal cortex is crucial for

recollection but less important for familiarity-based

memory. However, few studies have matched recollection

PATTERN COMPLETION

A process by which a stored

neural representation is

reactivated by a cue that consists

of a subset of the stored pattern.

EPISODIC MEMORY

Memory for events and

episodes, which are uniquely

characterized by a specific time

and place.

Item

recognition

0.25

0.75

0.50

Source

recollection

0.2

0.6

0.4

Semantic encoding + +

–

Active

Inactive

–

Item recognition + ––

Source recognition + + +

Controlled semantic analysis/cue specification

Monitoring/evaluating

recollections

Lexical/phonological

access or maintenance

Control

fvFTD

Figure 3 | Prefrontal cortex function. a | The performance of patients with frontal variant of frontotemporal dementia (fvFTD) on

item recognition and source recollection

. Although patients show no impairment relative to controls at recognizing previous

occurrence of stimuli, their source recollection is at chance levels. b | Different regions of prefrontal cortex subserve different

cognitive control operations in episodic memory

. The left panel illustrates the logic of data interpretation, with a plus sign indicating

significant activation and a minus sign indicating no significant activation. The right panel illustrates regions that show particular

patterns of activation. The posterior ventrolateral prefrontal cortex (green) is activated during semantic encoding, item recognition

and source recollection, and so is associated with lexical/phonological processing according to interpretation logic; the anterior

ventrolateral prefrontal cortex (blue) is activated during semantic encoding and source recollection, and so is associated with

semantic processing and cue specification; the dorsolateral prefrontal cortex (red) is activated during source recollection only, and so

is associated with monitoring and evaluation. Panel b modified, with permission, from REF. 84  (2002) Elsevier Science.

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engagement of two or more brain regions in the

operation of a particular task that might involve the

unidirectional or reciprocal transmission of information

between brain regions. Interactions can also be thought

of as the action of one brain region on another to bias or

change the representation being processed in the second

region. This type of interaction is commonly described

as either top-down or bottom-up control, depending on

whether the influence derives from earlier or later stages

in the processing hierarchy. Such influences might be

excitatory or inhibitory in nature, and can be beneficial

or essential for performance. It is likely that these types

of interaction all occur in the brain in certain instances

depending on the task being undertaken, but there has

been little consideration of how such interactions might

be modulated.

An early appreciation of the importance of

frontal–temporal interactions in memory came from

Warrington and Weiskrantz

, who suggested that the

profile of memory impairments that is typical of amnesia

could be explained by a disconnection between frontal

and temporal memory systems. As described earlier, most

patients with amnesia experience difficulties with both

recognition and recall of information

1,7

, whereas patients

with prefrontal cortex lesions might have normal recog-

nition but impaired recall or contextual recollection

64,65

One patient, whose lesion included the uncinate fascicle,

an important route of connection between frontal and

temporal areas, was particularly impaired at recalling

autobiographical events from his past, but performed

normally on tests of new learning

. This indicates that in

complex, effortful retrieval situations such as recall, which

typically make greater demands on processes of organiza-

tion, strategic search, monitoring and verification, the

interactions between prefrontal and medial temporal

regions might be more important than in relatively

automatic examples of remembering, such as many

instances of familiarity-based recognition.

It is difficult to learn much about the dynamic nature

of prefrontal–medial temporal interactions from clinical

studies because one cannot systematically examine the

effects of disconnecting in turn each of the relevant

brain regions. Transcranial magnetic stimulation has

been used to study interactions between different visual

processing areas in humans

, but the technique cannot

currently be applied to deep brain regions such as the

medial temporal lobe. In animals, anatomical discon-

nection studies have been undertaken, including the

disruption of frontal–temporal interactions by making

crossed unilateral lesions of the frontal lobe in one

hemisphere and the temporal lobe in the other hemi-

sphere

80,100

(FIG. 4a). The results show that interruption of

communication between these regions affects many

forms of conditional learning, although recent evidence

indicates that different memory impairments involving,

for example, conditional strategy implementation and

associative learning, can be observed when different

routes of interaction between temporal and prefrontal

areas are disconnected, such as those mediated by the

basal forebrain or by subcortical structures such as

the striatum

101,102

Distinctions have been made between ventral and

dorsal regions of lateral prefrontal cortex. One hypothesis

is that ventrolateral and dorsolateral areas are involved in

processing information about object form and object

location, respectively

, whereas an alternative view sug-

gests that the distinction between these regions lies in the

memory process being undertaken rather than the type

of stimulus material

(FIG. 3b). The ventrolateral region is

thought to be involved in the elaborative encoding of

information into episodic memory

70,83

, as well as in the

specification of retrieval cues

and the maintenance of

retrieved information

85,86

. This region can be further sub-

divided into anterior and posterior portions, which are

suggested to subserve semantic and lexical/phonological

control processes, respectively

84,87

. Dorsolateral prefrontal

cortex is considered to be involved in the organization of

material before encoding

, as well as the verification,

monitoring and evaluation of representations that have

been retrieved from long-term memory and are main-

tained by ventrolateral frontal cortex

84,89,90

. These post-

retrieval processes might additionally be supported by an

area of anterior prefrontal cortex near the frontal pole,

although this region might perform a higher-level

function in mnemonic control such as the processing of

internally-generated information

91–93

Most computational models of prefrontal function

have focused on the more general role of this region in

executive functions and

WORKING MEMORY

94,95

.However,one

recent model has attempted to understand the role of the

prefrontal cortex in strategic encoding and retrieval of

long-term memories

. In this model, the prefrontal

cortex develops mnemonic codes through reinforcement

learning during repeated encoding and retrieval sessions,

which are later used to aid retrieval of information from

medial temporal lobe regions. This model indicates a

defined manner in which the prefrontal cortex might

interact with the medial temporal lobe during long-term

memory processes. Evidence is accruing that such inter-

actions might be important to an understanding of the

manner in which memory processes are represented in

the brain.

Interactions

With some notable exceptions, there has been little

attempt to understand how the medial temporal lobe and

the prefrontal cortex might work together, or to construct

cognitive or neural models of their interactions.

Emerging evidence indicates that the prefrontal cortex

and the medial temporal lobe might form part of a dis-

tributed functional network of regions that are involved

in memory, in which the relative contribution of these

regions is modulated by factors such as the memory

process being undertaken, the type of material being

remembered, and the accessibility of the stored informa-

tion in memory. Although appreciation of the separate

contributions of frontal and temporal regions is useful, an

understanding of the interaction between these regions

might lie at the heart of a full account of memory

processing in the brain.

It is important to consider what is meant by ‘interac-

tion’. One example of an interaction is the concurrent

WORKING MEMORY

Short-lasting memory associated

with active maintenance and

rehearsal of information.

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Recent advances in functional neuroimaging have also

provided insights into the interactions between frontal

and temporal lobe regions in memory. Many studies have

demonstrated co-activation of prefrontal and medial

temporal regions during the performance of memory

tasks. As in the lesion studies described earlier, the nature

of these activations has been found to be modulated by

task demands, with a consistent distinction between the

networks that are engaged during the encoding of infor-

mation and those that are engaged during retrieval. A

number of studies have identified regions of prefrontal

and medial temporal cortex in which the magnitude of

activation during encoding predicts whether events will

be remembered

70,83

. Activation of this network tends to be

lateralized according to the type of material involved, with

predominantly left frontal and medial temporal regions

implicated for verbal stimuli and an analogous network

Bilateral disconnection of another route of commu-

nication between these areas, the uncinate fascicle, has

little effect on conditional learning in monkeys

103

although, as noted above, it might be important for

autobiographical retrieval in humans

. Another

connection between prefrontal and medial temporal

regions, through the medial dorsal thalamus, might

be particularly important for familiarity-based memory.

Disruption of this link impairs recognition memory in

monkeys and rats in a similar manner to lesions of

perirhinal cortex

104,105

. Combined lesion studies in ani-

mals have also identified further factors that might

modulate the interaction between prefrontal and hippo-

campal regions, such as the delay between study and

test. For example, although both regions are involved in

spatial memory, hippocampal involvement might be

essential only when a sufficient delay is introduced

106

Lexical

units

Context

units

Internal

reinforcement

Response

units

Lexical/

semantic

input/output

module

Other

cortical

modules

MTL

memory

module

PFC

module

Semantic

feature units

Pear

Apple

Vest

Jacket

c Externally presented item

Delay = 1

Lexical

units

Context

units

Internal

reinforcement

Response

units

Lexical/

semantic

input/output

module

Other

cortical

modules

MTL

memory

module

PFC

module

Semantic

feature units

Pear

Apple

Vest

Jacket

Internally generated item

Delay = 1

CUE CUE

Electrode

corpus callosum

Top-downBottom-up

Figure 4 | Techniques for systematically examining prefrontal–temporal interactions. a | Crossed-lesion neuropsychology

100

Studies involve, for example, unilateral temporal lobe ablation in one hemisphere (shown on left) and unilateral frontal lobe ablation in

another hemisphere (shown on right). b | Recording from single-unit electrodes after posterior disconnection of the cerebral

hemispheres by transection of the posterior corpus callosum

119,121

. Left: when a cue is presented to the hemisphere ipsilateral to the

recording site (‘electrode’), bottom-up sensory signals are detected (black arrow). Right: when a cue is presented to the hemisphere

contralateral to the recording site, sensory signals do not reach visual areas in the opposite hemisphere, but top-down signals (blue

arrow) from the prefrontal cortex (PFC) activate temporal neurons, permitting successful retrieval

121

. c | Computational modelling of

prefrontal and medial temporal interactions in memory

. Large blue arrows represent a modulatory reinforcement learning signal that

modulates the internal and external (input and output) connections of the prefrontal module. Arrows labelled with ‘delay = 1’ are the

pathways along which information from the previous time step are sent. Left panel: learning phase, where bottom-up activation

occurs from the presentation of an external stimulus. Right panel: retrieval phase, where top-down activation from the PFC is internally

generated. See also

BOX 1 for a description of the technique of effective connectivity. MTL, medial temporal lobe; WM, working

memory. Panel a modified, with permission, from

REF. 101  (2002) Society for Neuroscience; panel b modified, with permission, from

Nature REF. 121  (1999) Macmillan Magazines Ltd; panel c modified, with permission, from REF. 96  (2003) The MIT Press.

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detail that was termed a ‘feeling of knowing’ that the items

had been presented, or very few details. As with other

studies, medial temporal lobe responses differentiated

between successful and unsuccessful retrieval alone

111

One difficulty with standard methods of analysing

data from functional neuroimaging or single-neuron

recording is that co-activation of different brain regions

tells us nothing about the influence of one of the

regions over the other. A promising technique for

addressing this issue is the application of structural

equation modelling to functional imaging data to

examine the

EFFECTIVE CONNECTIVITY between brain

regions

112,113

(BOX 1). Such data can provide information

about how the relationship between two or more

regions changes under different conditions. Using

this technique, interactions have been observed between

prefrontal and medial temporal regions that are consis-

tent across several domains of retrieved information,

such as object identity and location

114

. Similarly, compa-

rable interactions have been observed between

prefrontal and medial temporal lobe regions during

retrieval of autobiographical memories, public event

information and general knowledge, although increased

connectivity was found between different regions

within the medial temporal lobe for autobiographical

recollection compared with other memory types

115

(see BOX 1). Of importance to the debate over retrieval

orientation and success is the evidence from effective

connectivity studies that prefrontal–medial temporal

interactions can reflect either orientation or success,

in the right hemisphere being engaged for non-verbal

stimuli

77,83

(FIG. 5a). The interaction between prefrontal

and medial temporal cortices is also modulated by the

type of elaborative processing undertaken during encod-

ing, with tasks that emphasize the processing of

lexical/semantic and phonological attributes resulting in

the recruitment of different inferior prefrontal regions to

the network

107,108

At retrieval, lateralization of the prefrontal–temporal

network is again modulated by the type of material

being remembered

78,79,109

. Beyond this distinction, there

is evidence that the interaction between frontal and

medial temporal lobe regions might vary on the basis of

factors such as the orientation of attentional processes

towards particular aspects of mnemonic informa-

tion

51,110

, the amount of cognitive effort expended during

a retrieval attempt

, and the level of success achieved in

retrieving the sought-after information

49–51,111

, although

the evidence is inconsistent. Some studies have identified

a network containing prefrontal and medial temporal

regions (as well as posterior cingulate and parietal cor-

tex) that was more strongly activated for successful than

unsuccessful episodic retrieval

49,50

. Other researchers have

suggested a more complicated pattern of interaction, with

the prefrontal cortex exhibiting activation that reflected

either the orientation of attention at retrieval

or the

amount of information that was retrieved

111

. In the latter

study, for example

(FIG. 5b), a graded level of activation in

prefrontal cortex reflected whether participants recalled

many details about studied items, an intermediate level of

EFFECTIVE CONNECTIVITY

Multivariate analysis of activity

in different regions to model the

influence that regions exert over

each other.

Signal change (%) Signal change (%)

0.5

Signal change (%)

0.9

0.7

0.5

0.3

0.1

–0.1

0.9

0.7

0.5

0.3

0.1

–0.1

HAMMER

LR LR LR

Prefrontal cortex

Medial temporal lobe

Know

FOK

Don’t know

Know

FOK

Don’t know

Figure 5 | Interactions between prefrontal cortex and medial temporal lobe. a | The prefrontal cortex–medial temporal lobe

interaction during encoding is modulated by the type of material being remembered

. The left-hemisphere network (L) is more activated

for words, there is bilateral involvement for nameable objects, and activation is predominantly in the right hemisphere (R) for unfamiliar

faces. Similar material-specific lateralization is also seen during retrieval from memory

79,109

. b | The interaction between the prefrontal

cortex and the medial temporal lobe might be more complex during retrieval

111

. The prefrontal cortex shows a graded response,

reflecting instances of full retrieval of details about studied items (know), intermediate retrieval or ‘feeling of knowing’ (FOK), or limited

retrieval of details (don’t know). The medial temporal lobe differentiates between successful (know) and unsuccessful retrieval (FOK and

don’t know) only. Panel a modified, with permission, from

REF. 77  (1998) Elsevier Science; panel b modified, with permission, from

REF. 111  (2003) Elsevier Science.

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brain regions is recording from extracellular electrodes

in behaving monkeys. The prefrontal cortex has been

shown to be particularly important for memory tasks

that involve the associating or integration of events over

time

117

. For example, during a delayed matching-to-

sample task, neurons in the temporal cortex increase

their response to repetition of the sample stimulus but

not to distracting stimuli, whereas prefrontal neurons

sustain activation across the intervening items

118

, indi-

cating that there might be a top-down influence in this

region. Neuronal recordings from monkeys with poste-

rior disconnection of the two cerebral hemispheres by

transection of the posterior corpus callosum have

shown, during a visual paired-associate learning task,

that when a visual cue is presented to one hemisphere,

single neurons in the disconnected contralateral

inferior temporal lobe can be activated by a top-down

signal from the prefrontal cortex, permitting successful

retrieval

119

(FIG. 4b). This prefrontal neuronal signal acts

in a prospective manner in associative learning, initially

reflecting the sample cue and then, before presentation

of a test cue, reflecting the expected target stimulus that

was previously associated with the sample

120

.Moreover,

when this prefrontal signal is removed by transecting

the remaining anterior corpus callosum, performance

on the associative memory task is severely impaired

121

These results indicate that successful memory in

these tasks is guided by top-down influences from

prefrontal cortex on temporal cortex to process

information that is relevant to particular behavioural

demands.

Insights can also be gained through the implementa-

tion of sophisticated computational models that seek to

go beyond modelling medial temporal or prefrontal

cortex function in isolation. One model

(FIG. 4c) has

been proposed in which information provided by

medial temporal and other cortical regions is rapidly

organized according to task requirements and com-

bined into mnemonic codes in the prefrontal cortex

through a process of reinforcement learning. These

mnemonic codes can be used at retrieval by the pre-

frontal cortex in a top-down manner to search for and

access stored information in the medial temporal lobe

system, evaluating the products of retrieval on the basis

of heuristic properties that vary depending on the task.

The development of mnemonic codes in this model

during learning is modulated continuously through

monitoring of present performance relative to an

intended goal state, which means that the model

essentially develops retrieval strategies dynamically

Although the interaction between frontal and tem-

poral regions in memory has typically been neglected in

cognitive neuroscience, it might be crucial for a

full understanding of how memory processes are

represented in the brain. There is a complex pattern of

interactions between the prefrontal cortex and the

medial temporal lobe. Although our understanding of

these interactions is still at an early stage, in the next

section we attempt to draw on what is known to

define theoretically the manner in which some of these

interactions might operate.

depending on the regions of cortex that are functionally

linked

112

. The analysis of effective connectivity in

functional imaging data is still in its infancy and current

models are simple, including only unidirectional connec-

tions and a lack of anatomical specificity, but ongoing

development

116

might realize the technique’s potential to

provide useful information on how brain regions interact.

Another technique that has proved informative in

understanding interactions between frontal and temporal

Box 1 |Modelling effective connectivity in functional neuroimaging

Structural equation modelling, also known as path analysis, is a correlational statistical

method that can be used to examine the influence that brain regions in a network have on

each other under a set of specific experimental conditions. These influences are referred

to as effective connectivity. Different approaches are used to construct and analyse the

models; one method is described below in a simplified form

113,115

• The brain regions activated by different experimental conditions are identified.

• An anatomical model of unidirectional connections between selected regions is

specified on the basis of existing knowledge.

• Path coefficients (numerical weights) are assigned to each connection. These represent

the change in activation level in the target region that is associated with one standard

deviation of change in the source region, with activity in all other regions kept constant.

• Two candidate models are created: one is a null model in which all path coefficients are

equal for each task condition, and one is an alternative model in which the regions of

interest are allowed to vary depending on the task conditions.

• The goodness-of-fit of the null model and the alternative model are compared.

Where path coefficients in the alternative model provide a better fit, the relationship

between the regions can be identified as being different for the two experimental

conditions. Shown are data from a study of autobiographical retrieval

115

, showing regions

(left) that were activated by a memory versus control condition, which were used to

construct an effective connectivity model (right). The illustration shows consistent

interactions (red arrows) between medial frontal (MF) and temporal lobe regions (PHG,

parahippocampal gyrus; HC, hippocampus; LT, lateral temporal lobe; TP, temporal pole)

as well as retrosplenial cortex (RSP) and temporoparietal junction (TPJ) for retrieval of

autobiographical and other forms of memory. Within the medial temporal lobe, there

was increased connectivity for autobiographical retrieval (green arrows), and for retrieval

of public events (yellow arrow) and general knowledge (blue arrow). Modified, with

permission, from

REF. 115  (2001) Oxford University Press.

Whereas this technique allows us to go beyond observation of activation, several

important issues should be considered when interpreting data from effective connectivity

studies. Several potential models might account for the data, with the one reported

perhaps representing only one of a potential set. In addition, much anatomical brain

connectivity is reciprocal, particularly in the neocortex, whereas unidirectional

connections must be assumed for models to be robust.Alternative methods of

determining the alternative model and the goodness-of-fit mean that researchers should

take care when comparing data from different studies.

PHG

RSP

TPJ

PHG

RSP

TPJ

Activations identified

Model and path

coefficients specified

Coefficients coloured blue,

yellow and green are found

to fit better with the

alternative model

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in the medial temporal lobe on the basis of current goals

and task demands, and ensuring that the representations

are sufficiently non-overlapping to be amenable for

long-term storage

70,83

The interaction will involve differential recruitment of

prefrontal regions depending on the type of top-down

processing required (for example, anterior and posterior

ventrolateral prefrontal cortex for semantic and phono-

logical processing, respectively

107,108

), and its relative

lateralization will depend on the verbal or non-verbal

nature of the information being encoded

77,83,122

Dorsolateral prefrontal regions might be engaged if,

during processing, some selection of multiple features

or organization and manipulation of the material is

required

. So the encoding of categorized lists of items

might be affected by lesions that disrupt the function or

connectivity between dorsolateral prefrontal cortex and

the medial temporal lobe. The interactions between

prefrontal and medial temporal regions that predict

different states of awareness at retrieval are unclear. For

example, will activation of similar networks at encoding

determine subsequent retrieval when memory is

assessed using tests of recollection and familiarity, or

when tasks that measure implicit rather than explicit

memory are used? Furthermore, the extent to which the

engagement of encoding-related brain regions will vary

depending on attentional factors and differences in

strategies adopted has yet to be fully elucidated.

Proposed unifying framework

Although both prefrontal and medial temporal regions

are involved in the encoding of information into

memory

77,83

, the interactions between these regions seem

to be particularly central to the retrieval of stored infor-

mation

49,50,111

. By contrast, there is evidence that the

medial temporal lobe alone is responsible for the storage

and indexing of memories (at least for some years after

encoding in humans)

3,41

. We therefore focus here on pro-

viding an outline of how prefrontal and medial temporal

regions might interact during the cognitive operations

involved in encoding and retrieval

(FIG. 6). This descrip-

tion is limited by the data available and the poorly

specified nature of these processes. Nevertheless, we

believe that a unifying overview might highlight avenues

for future research.

For information in the external world to be encoded

(transferred from a currently active representation to a

long-term store), it is processed by unimodal and poly-

modal cortical areas before being transmitted to the

medial temporal lobe. As processing proceeds along these

pathways, progressively higher-level representations of

the perceived information are formed, integrating and

associating different features of the to-be-remembered

material into a bound representation

30,54

. At this stage, the

interaction with prefrontal cortex becomes important in

providing top-down control of the encoding process,

guiding, modifying and elaborating the representations

Encoding interactions

DLPFC

Organization of

material to be remembered

VLPFC

Semantic/phonological

elaborative processing

of MTL representations

to ensure traces

are distinct

MTL

Different features

bound into episodic

representation

DLPFC

Monitoring and verification

of retrieved information

VLPFC

1. Cue specification,

strategic search of MTL

stored representations

2. Maintenance of

retrieved information

MTL

Comparison of retrieval cue

and stored representations

using pattern completion

APFC

Higher-level

mnemonic

control

operations

Retrieval interactions

Progressively higher-level

representations of

perceived information

formed in posterior cortex

Figure 6 | Summary of principal interactions between prefrontal cortex (PFC) and medial temporal lobe (MTL) in recollection.

a | Encoding. Perceived information is processed in hierarchical cortical areas, resulting in progressively higher-level representations

that are integrated and associated into a bound memory trace in the MTL. Top-down control of encoding is provided by the PFC,

involving elaborative semantic and/or phonological processing of the MTL representation in anterior and posterior ventrolateral

prefrontal cortex (VLPFC), respectively. Material is selected, manipulated and organized in the dorsolateral prefrontal cortex (DLPFC).

These control processes ensure the separation of traces so as to reduce interference between them. b | Retrieval. On the basis of the

kind of retrieval task undertaken, retrieval cues are specified and elaborated in the VLPFC, before being used to strategically search

stored representations in the MTL. Using a process of pattern completion that occurs outside cognitive control, the retrieval cue is

iteratively compared with stored representations until correspondence is achieved and a candidate memory identified. This memory

representation is retrieved and maintained online by VLPFC while various monitoring and verification processes are undertaken in the

DLPFC. The retrieved information is compared with the retrieval criteria originally specified and, if these criteria are satisfied, the

memory will be available for conscious thought and/or output. Otherwise, modification of the retrieval cues might occur in VLPFC and

further attempts at retrieval searches are undertaken. Less certain is the nature of the higher-level mnemonic control processes,

should they be required, which seem to be supported by anterior prefrontal cortex (APFC), and the processing concerning self-

relevant information, which is thought to engage medial prefrontal cortex (not shown). Anatomical images adapted, with permission,

from REF. 133 © (1996) Appleton & Lange.

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manner and, if so, what rules govern this

? Perhaps

more fundamentally, if functional activation in

prefrontal cortex is associated with a particular behav-

ioural response (such as an indication of an intermediate

level of retrieval success or ‘feeling of knowing’

111

), does

that mean that the level of activation in this region

reflects the outcome that retrieval was moderately

successful, or could this activation represent a signal to

drive further retrieval searches to recover the item?

Such questions relating to the causal nature of interac-

tions are difficult to answer with standard methods of

neuroimaging analysis, but might start to be addressed

using effective connectivity techniques.

Conclusions

A review of the literature points to the conclusion that

interactions between prefrontal cortex and the medial

temporal lobe are vital for successful memory. These

regions contribute in different ways to the processes of

encoding, storage and retrieval, but it is only by their

combined participation, and their modulatory influence

over one another, that comprehensive memory function

can be sustained. During encoding, the essence of

the interaction between prefrontal cortex and medial

temporal lobe is to provide discrete and elaborated

representations that are amenable to long-term storage.

At retrieval, interactions serve to specify retrieval cues,

interrogate the long-term store, and reactivate and

monitor stored information. Our understanding of the

nature of the interactions between these regions is still at

an early stage, and so our specification of the processes

involved is frustratingly imprecise. Further work is

needed to characterize these processes in more detail,

specifying how the interactions between prefrontal and

medial temporal regions might differ during operations

such as cue specification, maintenance and monitoring

of retrieved information. This endeavour will require the

use of analogous tasks and comparable methods across

species and techniques so that convergent evidence can

accumulate, providing information that cannot be

derived from individual fields of study in isolation. In

addition, theoretical work remains to be undertaken,

bridging the gap in understanding between cognitive

models and empirical observations such as changes in

neural connectivity. With the contribution of studies

employing the different methodologies described in this

article, and interpreting their results within common,

unified theoretical terms of reference, we might begin

to move closer to a full account of the manner in which

the prefrontal cortex and medial temporal lobe work

together to support remembering.

Prefrontal–medial temporal interactions might be

even more important during retrieval. Retrieval can

be characterized as the process by which long-term stored

information is made available for current operations or

behavioural responses, typically through the directed use

of a retrieval cue. Cognitive models of retrieval include

separate components: the specification of a retrieval cue,

the interrogation of a long-term store with that cue, the

reactivation of stored information, and the monitoring

or evaluation of this reactivated information

68,82

. The

prefrontal cortex and medial temporal lobe interact in

different ways during these stages of retrieval, with cue

specification and elaboration involving ventrolateral

prefrontal cortex

, and the verbal/non-verbal nature of

the material influencing the relative laterality of the inter-

action

78,79,109

. So, disconnection of ventrolateral prefrontal

cortex and the medial temporal lobe can be expected to

have a greater impact on tasks with poorly defined

retrieval cues (degraded pictures, for example) than on

tasks in which cues are well specified.

The elaborated retrieval cue is used to interrogate the

medial temporal lobe

, strategically searching stored

representations and seeking concordance between the

cue and stored information, possibly through pattern

completion

. When one or more candidate memories

have been identified, their representation will be main-

tained in working memory by ventrolateral prefrontal

cortex

85,86

while monitoring operations, thought to be

supported by dorsolateral prefrontal cortex, are engaged

to compare the retrieved information with the specified

retrieval criteria to allow the disambiguation of compet-

ing memories

90,123,124

. This might require source verifica-

tion and rejection of the retrieved representations because

of inconsistencies, in which case the retrieval cue might be

modified and further retrieval search interactions under-

taken.Anterior prefrontal cortex might be recruited if

particularly complex retrieval operations are required, for

example involving the processing of internally generated

information

92,93

, although the circumstances in which this

region is engaged are not understood. Similarly, interac-

tions with medial prefrontal cortex might occur during

the retrieval of reward-related or self-relevant informa-

tion, such as autobiographical memories

81,98,115

, although

the mechanisms that govern the involvement of this

region are still to be explained.

One issue that is not clear is the nature of the inter-

actions between dorsolateral prefrontal cortex and the

medial temporal lobe that facilitate the monitoring of

retrieved information. For example, what verification

criteria are used to assess the accuracy of retrieval? Does

the use of these criteria vary in a task-dependent

1. Scoville, W. B. & Milner, B. Loss of recent memory after

bilateral hippocampal lesions. J. Neurol. Neurosurg.

Psychiatry 20, 11–21 (1957).

2. Marr, D. Simple memory: a theory for archicortex. Phil.

Trans. R. Soc. Lond. B 262, 23–81 (1971).

3. Squire, L. R. Memory and the hippocampus: a synthesis

from findings with rats, monkeys, and humans. Psychol.

Rev. 99, 195–231 (1992).

4. Fuster, J. M. Memory in the Cerebral Cortex (MIT Press,

Cambridge, Massachusetts, 1995).

5. Shimamura, A. P. in The Cognitive Neurosciences (ed.

Gazzaniga, M. S.) 803–813 (MIT Press, Cambridge,

Massachusetts, 1995).

6. Cohen, N. J. & Eichenbaum, H. B. Memory, Amnesia, and

the Hippocampal System (MIT Press, Cambridge,

Massachusetts, 1993).

7. Aggleton, J. P. & Brown, M. W. Episodic memory, amnesia,

and the hippocampal-anterior thalamic axis. Behav. Brain

Sci. 22, 425–489 (1999).

An important paper providing evidence that different

anatomical circuits, including the hippocampus and

perirhinal cortex, are involved in recollection and

familiarity, respectively.

8. Van Hoesen, G. W., Augustinack, J. C. & Redman, S. J.

Ventromedial temporal lobe pathology in dementia, brain

trauma, and schizophrenia. Ann. NY Acad. Sci. 877,

575–594 (1999).

9. Petrides, M. in The Prefrontal Cortex: Executive and

Cognitive Functions (eds Roberts, A. C., Robbins, T. W. &

Weiskrantz, L.) 103–116 (Oxford Univ. Press, Oxford, 1998).

Nature

Publishing

Group

NATURE REVIEWS | NEUROSCIENCE VOLUME 4 | AUGUST 2003 | 647

REVIEWS

10. Preuss, T. M. Do rats have prefrontal cortex: The Rose-

Woolsey-Akert program reconsidered. J. Cogn. Neurosci. 7,

1–24 (1995).

11. Semendeferi, K., Lu, A., Schenker, N. & Damasio, H.

Humans and great apes share a large frontal cortex. Nature

Neurosci. 5, 272–276 (2002).

12. Corkin, S. What’s new with the amnesic patient H.M.?

Nature Rev. Neurosci. 3, 153–160 (2002).

13. Zola, S. M. et al. Impaired recognition memory in monkeys

after damage limited to the hippocampal region. J. Neurosci.

20, 451–463 (2000).

14. Morris, R. G. M., Garrud, P., Rawlins, J. P. & O’Keefe, J.

Place navigation impaired in rats with hippocampal lesions.

Nature 297, 681–683 (1982).

15. Aggleton, J. P., Hunt, P. R. & Rawlins, J. N. P. The effects of

hippocampal lesions upon spatial and non-spatial tests of

working memory. Behav. Brain Res. 40, 145–157 (1986).

16. O’Keefe, J. & Dostrovsky, J. The hippocampus as a spatial

map: preliminary evidence from unit activity in the freely-

moving rat. Brain Res. 34, 171–175 (1971).

17. O’Keefe, J. & Nadel, L. The Hippocampus as a Cognitive

Map (Oxford Univ. Press, Oxford, 1978).

18. Lever, C., Wills, T., Cacucci, F., Burgess, N. & O’Keefe, J.

Long-term plasticity in hippocampal place-cell

representation of environmental geometry. Nature 416,

90–94 (2002).

19. Meunier, M., Bachevalier, J., Mishkin, M. & Murray, E. A.

Effects on visual recognition of combined and separate

ablations of the entorhinal and perirhinal cortex in rhesus

monkeys. J. Neurosci. 13, 5418–5432 (1993).

20. Suzuki, W. A., Zola-Morgan, S., Squire, L. R. & Amaral, D. G.

Lesions of the perirhinal and parahippocampal cortices in

the monkey produce long-lasting memory impairment in the

visual and tactual modalities. J. Neurosci. 13, 2430–2451

(1993).

21. Ennaceur, A., Neave, N. & Aggleton, J. P. Neurotoxic lesions

of the perirhinal cortex do not mimic the behavioural effects

of fornix transection in the rat. Behav. Brain Res. 80, 9–25

(1996).

22. Murray, E. A. & Mishkin, M. Object recognition and location

memory in monkeys with excitotoxic lesions of the amygdala

and hippocampus. J. Neurosci. 18, 6568–6582 (1998).

23. Gaffan, D., Shields, C. & Harrison, S. Delayed matching by

fornix-transected monkeys: The sample, the push and the

bait. Q. J. Exp. Psychol. 36B, 305–317 (1984).

24. Clark, R. E., Zola, S. M. & Squire, L. R. Impaired recognition

memory in rats after damage to the hippocampus.

J. Neurosci. 20, 8853–8860 (2000).

Evidence against a functional dissociation between

the hippocampus and perirhinal cortex in memory.

25. Miller, E. K., Li, L. & Desimone, R. A neural mechanism for

working and recognition memory in inferior temporal cortex.

Science 254, 1377–1379 (1991).

26. Fahy, F. L., Riches, I. P. & Brown, M. W. Neuronal activity

related to visual recognition memory: long-term memory

and the encoding of recency and familiarity information in

the primate anterior and medial inferior temporal and rhinal

cortex. Exp. Brain Res. 96, 457–472 (1993).

27. Riches, I. P., Wilson, F. A. W. & Brown, M. W. The effects of

visual stimulation and memory on neurons of the

hippocampal formation and the neighboring

parahippocampal gyrus and inferior temporal cortex of the

primate. J. Neurosci. 11, 1763–1779 (1991).

28. Rolls, E. T., Cahusac, P. M. B., Feigenbaum, J. D. &

Miyashita, Y. Responses of single neurons in the

hippocampus of the macaque related to recognition

memory. Exp. Brain Res. 93, 299–306 (1993).

29. Buckley, M. J., Booth, M. C. A., Rolls, E. T. & Gaffan, D.

Selective perceptual impairments after perirhinal cortex

ablation. J. Neurosci. 21, 9824–9836 (2001).

30. Murray, E. A. & Bussey, T. J. Perceptual-mnemonic

functions of the perirhinal cortex. Trends Cogn. Sci. 3,

142–151 (1999).

31. Aggleton, J. P. & Shaw, C. Amnesia and recognition

memory: a re-analysis of psychometric data.

Neuropsychologia 34, 51–62 (1996).

32. Baddeley, A. D., Vargha-Khadem, F. & Mishkin, M.

Preserved recognition in a case of developmental amnesia:

implications for the acquisition of semantic memory?

J. Cogn. Neurosci. 13, 357–369 (2001).

33. Holdstock, J. S. et al. A comparison of egocentric and

allocentric spatial memory in a patient with selective

hippocampal damage. Neuropsychologia 38, 410–425

(2000).

34. Yonelinas, A. P. et al. Effects of extensive temporal lobe

damage or mild hypoxia on recollection and familiarity.

Nature Neurosci. 5, 1236–1241 (2002).

An elegant study examining whether damage to

different regions of the human medial temporal lobe

leads to differential impairment in recollection and

familiarity.

35. Manns, J. R. & Squire, L. R. Impaired recognition memory

on the Doors and People Test after damage limited to the

hippocampal region. Hippocampus 9, 495–499 (1999).

36. Buffalo, E. A., Reber, P. J. & Squire, L. R. The human

perirhinal cortex and recognition memory. Hippocampus 8,

330–339 (1998).

37. Holdstock, J. S., Gutnikov, S. A., Gaffan, D. & Mayes, A. R.

Perceptual and mnemonic matching-to-sample in

humans: contributions of the hippocampus, perirhinal and

other medial temporal lobe cortices. Cortex 36, 301–322

(2000).

38. Simons, J. S., Graham, K. S., Galton, C. J., Patterson, K. &

Hodges, J. R. Semantic knowledge and episodic memory

for faces in semantic dementia. Neuropsychology 15,

101–114 (2001).

39. Simons, J. S., Graham, K. S. & Hodges, J. R. Perceptual

and semantic contributions to episodic memory: evidence

from semantic dementia and Alzheimer’s disease. J. Mem.

Lang. 47, 197–213 (2002).

40. Graham, K. S. & Hodges, J. R. Differentiating the roles of the

hippocampal complex and the neocortex in long-term

memory storage: evidence from the study of semantic

dementia and Alzheimer’s disease. Neuropsychology 11,

77–89 (1997).

41. Nadel, L. & Moscovitch, M. Memory consolidation,

retrograde amnesia, and the hippocampal complex. Curr.

Opin. Neurobiol. 7, 217–227 (1997).

42. Cipolotti, L. et al. Long-term retrograde amnesia…the

crucial role of the hippocampus. Neuropsychologia 39,

151–172 (2001).

43. Spiers, H. J., Maguire, E. A. & Burgess, N. Hippocampal

amnesia. Neurocase 7, 357–382 (2001).

A useful reference for a description of 147 cases of

amnesia after damage to the medial temporal lobes.

44. Schacter, D. L. & Wagner, A. D. Medial temporal lobe

activations in fMRI and PET studies of episodic encoding

and retrieval. Hippocampus 9, 7–24 (1999).

45. Maguire, E. A. et al. Knowing where and getting there: a

human navigation network. Science 280, 921–924 (1998).

46. Hartley, T., Maguire, E. A., Spiers, H. J. & Burgess, N. The

well-worn route and the path less traveled: distinct neural

bases of route following and wayfinding in humans. Neuron

37, 877–888 (2003).

47. Schacter, D. L., Alpert, N. M., Savage, C. R., Rauch, S. L. &

Albert, M. S. Conscious recollection and the human

hippocampal formation: Evidence from positron emission

tomography. Proc. Natl Acad. Sci. USA 93, 321–325 (1996).

48. Burgess, N., Maguire, E. A., Spiers, H. J. & O’Keefe, J.

A temporoparietal and prefrontal network for retrieving the

spatial context of lifelike events. Neuroimage 14, 439–453

(2001).

A neuroimaging experiment providing evidence for a

network of brain regions, including medial temporal

and prefrontal cortices, that are activated during

retrieval of different episodic contexts.

49. Eldridge, L. L., Knowlton, B. J., Furmanski, C. S.,

Bookheimer, S. Y. & Engel, S. A. Remembering episodes: a

selective role for the hippocampus during retrieval. Nature

Neurosci. 3, 1149–1152 (2000).

50. Cansino, S., Maquet, P., Dolan, R. J. & Rugg, M. D. Brain

activity underlying encoding and retrieval of source memory.

Cereb. Cortex 12, 1048–1056 (2002).

51. Dobbins, I. G., Rice, H. J., Wagner, A. D. & Schacter, D. L.

Memory orientation and success: separable neurocognitive

components underlying episodic recognition.

Neuropsychologia 41, 318–333 (2003).

52. Davachi, L., Mitchell, J. P. & Wagner, A. D. Multiple routes to

memory: distinct medial temporal lobe processes build item

and source memories. Proc. Natl Acad. Sci. USA 100,

2157–2162 (2003).

53. Henson, R. N. A., Cansino, S., Herron, J. E., Robb, W. G. K.

& Rugg, M. D. A familiarity signal in human anterior medial

temporal cortex? Hippocampus 13, 259–262 (2003).

54. Hasselmo, M. E. & Wyble, B. P. Free recall and recognition in

a network model of the hippocampus: simulating effects of

scopolamine on human memory function. Behav. Brain Res.

89, 1–34 (1997).

55. McClelland, J. L., McNaughton, B. L. & O’Reilly, R. C. Why

there are complementary learning systems in the

hippocampus and neocortex: insights from the success and

failure of connectionist models of learning and memory.

Psychol. Rev. 102, 419–457 (1995).

56. Alvarez, P. & Squire, L. R. Memory consolidation and the

medial temporal lobe: a simple network model. Proc. Natl

Acad. Sci. USA 91, 7041–7045 (1994).

57. O’Reilly, R. C. & Rudy, J. W. Conjunctive representations in

learning and memory: principles of cortical and hippocampal

function. Psychol. Rev. 108, 311–345 (2001).

58. Murre, J. M. J. TraceLink: a model of amnesia and

consolidation of memory. Hippocampus 6, 675–684

(1996).

59. Nadel, L., Samsonovich, A., Ryan, L. & Moscovitch, M.

Multiple trace theory of human memory: computational,

neuroimaging, and neuropsychological results.

Hippocampus 10, 352–368 (2000).

60. Brown, M. A. & Sharp, P. E. Simulation of spatial-learning in

the Morris water maze by a neural-network model of the

hippocampal-formation and nucleus-accumbens.

Hippocampus 5, 171–188 (1995).

61. Burgess, N., Donnett, J. G., Jeffery, K. J. & O’Keefe, J.

Robotic and neuronal simulation of the hippocampus and

rat navigation. Phil. Trans. R. Soc. Lond. B 352, 1535–1543

(1997).

62. Burgess, N., Becker, S., King, J. A. & O’Keefe, J. Memory

for events and their spatial context: models and

experiments. Phil. Trans. R. Soc. Lond. B 356, 1493–1503

(2001).

63. Shimamura, A. P., Janowsky, J. S. & Squire, L. R. Memory

for the temporal order of events in patients with frontal lobe

lesions and amnesic patients. Neuropsychologia 28,

803–813 (1990).

64. Schacter, D. L., Harbluk, J. L. & McLachlan, D. R. Retrieval

without recollection: an experimental analysis of source

amnesia. J. Verb. Learn. Verb. Behav. 23, 593–611 (1984).

65. Simons, J. S. et al. Recollection-based memory in

frontotemporal dementia: implications for theories of long-

term memory. Brain 125, 2523–2536 (2002).

Evidence that frontal lobe dysfunction can be a better

predictor than hippocampal atrophy of recollection

impairment.

66. Incisa della Rocchetta, A. & Milner, B. Strategic search and

retrieval inhibition: the role of the frontal lobes.

Neuropsychologia 31, 503–524 (1993).

67. Moscovitch, M. in Varieties of Memory and Consciousness:

Essays in Honour of Endel Tulving (eds Roediger, H. L. &

Craik, F. I. M.) 133–160 (Erlbaum, London, 1989).

68. Burgess, P. W. & Shallice, T. Confabulation and the control

of recollection. Memory 4, 359–411 (1996).

An influential model of the processes of episodic

retrieval in relation to frontal lobe function.

69. Rolls, E. T., Hornak, J., Wade, D. & McGrath, J. Emotion-

related learning in patients with social and emotional

changes associated with frontal-lobe damage. J. Neurol.

Neurosurg. Psychiatry 57, 1518–1524 (1994).

70. Henson, R. N. A., Rugg, M. D., Shallice, T., Josephs, O. &

Dolan, R. J. Recollection and familiarity in recognition

memory: an event-related functional magnetic resonance

imaging study. J. Neurosci. 19, 3962–3972 (1999).

Functional magnetic resonance imaging (fMRI)

evidence that different prefrontal patterns of activity

are characteristic of recollection and familiarity during

encoding and retrieval.

71. Wilson, F. A. W., Ó Scalaidhe, S. P. & Goldman-Rakic, P. S.

Dissociation of object and spatial processing domains in

prefrontal cortex. Science 260, 1955–1958 (1993).

72. Duncan, J. & Owen, A. M. Common regions of the human

frontal lobe recruited by diverse cognitive demands. Trends

Neurosci. 23, 475–483 (2000).

73. Freedman, D. J., Riesenhuber, M., Poggio, T. & Miller, E. K.

Categorical representation of visual stimuli in the primate

prefrontal cortex. Science 291, 312–316 (2001).

74. Duncan, J. An adaptive coding model of neural function in

prefrontal cortex. Nature Rev. Neurosci. 2, 820–829 (2001).

75. Tulving, E., Kapur, S., Craik, F. I. M., Moscovitch, M. &

Houle, S. Hemispheric encoding/retrieval asymmetry in

episodic memory: positron emission tomography findings.

Proc. Natl Acad. Sci. USA 91, 2016–2020 (1994).

76. Nyberg, L., Cabeza, R. & Tulving, E. PET studies of

encoding and retrieval: the HERA model. Psychon. Bull.

Rev. 3, 135–148 (1996).

77. Kelley, W. M. et al. Hemispheric specialization in human

dorsal frontal cortex and medial temporal lobe for verbal

and nonverbal memory encoding. Neuron 20, 927–936

(1998).

78. Wagner, A. D. et al. Material-specific lateralization of

prefrontal activation during episodic encoding and retrieval.

Neuroreport 9, 3711–3717 (1998).

79. Simons, J. S., Graham, K. S., Owen, A. M., Patterson, K. &

Hodges, J. R. Perceptual and semantic components of

memory for objects and faces: a PET study. J. Cogn.

Neurosci. 13, 430–443 (2001).

80. Baxter, M. G., Parker, A., Lindner, C. C. C., Izquierdo, A. D.

& Murray, E. A. Control of response selection by reinforcer

values requires interaction of amygdala and orbital prefrontal

cortex. J. Neurosci. 20, 4311–4319 (2000).

81. Elliott, R., Dolan, R. J. & Frith, C. D. Dissociable functions in

the medial and lateral orbitofrontal cortex: evidence from

human neuroimaging studies. Cereb. Cortex 10, 308–317

(2000).

82. Fletcher, P. C. & Henson, R. N. A. Frontal lobes and human

memory: insights from functional neuroimaging. Brain 124,

849–881 (2001).

Nature

Publishing

Group

648 | AUGUST 2003 | VOLUME 4 www.nature.com/reviews/neuro

REVIEWS

83. Wagner, A. D. et al. Building memories: remembering and

forgetting of verbal experiences as predicted by brain

activity. Science 281, 1188–1191 (1998).

84. Dobbins, I. G., Foley, H., Schacter, D. L. & Wagner, A. D.

Executive control during episodic retrieval: multiple prefrontal

processes subserve source memory. Neuron 35, 989–996

(2002).

fMRI evidence that different regions of prefrontal cortex

are involved in the cue specification, maintenance and

monitoring/evaluation stages of episodic memory.

85. D’Esposito, M., Postle, B. R., Ballard, D. & Lease, J.

Maintenance versus manipulation of information held in

working memory: an event-related fMRI study. Brain Cogn.

41, 66–86 (1999).

86. Wagner, A. D., Maril, A., Bjork, R. A. & Schacter, D. L.

Prefrontal contributions to executive control: fMRI evidence

for functional distinctions within lateral prefrontal cortex.

Neuroimage 14, 1337–1347 (2001).

87. Poldrack, R. A. et al. Functional specialization for semantic

and phonological processing in the left inferior frontal cortex.

Neuroimage 10, 15–35 (1999).

88. Fletcher, P. C., Shallice, T. & Dolan, R. J. The functional roles

of prefrontal cortex in episodic memory. I. Encoding. Brain

121, 1239–1248 (1998).

89. Petrides, M., Alivisatos, B., Evans, A. C. & Meyer, E.

Dissociation of human mid-dorsolateral from posterior

dorsolateral frontal cortex in memory processing. Proc. Natl

Acad. Sci. USA 90, 873–877 (1993).

90. Rugg, M. D., Fletcher, P. C., Chua, P. M. L. & Dolan, R. J.

The role of the prefrontal cortex in recognition memory and

memory for source: an fMRI study. Neuroimage 10,

520–529 (1999).

91. Koechlin, E., Basso, G., Pietrini, P., Panzer, S. & Grafman, J.

The role of the anterior prefrontal cortex in human cognition.

Nature 399, 148–151 (1999).

92. Christoff, K. & Gabrieli, J. D. E. The frontopolar cortex and

human cognition: evidence for a rostrocaudal hierarchical

organization within the human prefrontal cortex.

Psychobiology 28, 168–186 (2000).

A proposal that anterior prefrontal cortex might lie at

the top of a processing hierarchy in the prefrontal

cortex, operating on higher-order representations

such as internally generated information.

93. Burgess, P. W., Scott, S. K. & Frith, C. D. The role of the

rostral frontal cortex (area 10) in prospective memory: a

lateral versus medial dissociation. Neuropsychologia 41,

906–918 (2003).

94. Norman, D. A. & Shallice, T. in Consciousness and Self-

Regulation (eds Davidson, R. J., Schwartz, G. & Shapiro, D.)

1–18 (Plenum, New York, 1986).

95. Dehaene, S. & Changeux, J. P. A hierarchical neuronal

network for planning behavior. Proc. Natl Acad. Sci. USA

94, 13293–13298 (1997).

96. Becker, S. & Lim, J. A computational model of prefrontal

control in free recall: strategy memory use in the California

Verbal Learning Task. J. Cogn. Neurosci. (in the press).

A computational model of the interaction between the

prefrontal and medial temporal regions in long-term

memory.

97. Warrington, E. K. & Weiskrantz, L. Amnesia: a disconnection

syndrome? Neuropsychologia 20, 233–248 (1982).

A seminal paper suggesting that amnesia might be

caused by a disconnection between frontal and

temporal brain regions.

98. Levine, B. et al. Episodic memory and the self in a case of

isolated retrograde amnesia. Brain 121, 1951–1973 (1998).

99. Pascual-Leone, A. & Walsh, V. Fast backprojections from

the motion to the primary visual area necessary for visual

awareness. Science 292, 510–512 (2001).

100. Gaffan, D. & Harrison, S. Inferotemporal-frontal

disconnection and fornix transection in visuomotor

conditional learning by monkeys. Behav. Brain Res. 31,

149–163 (1988).

101. Gaffan, D., Easton, A. & Parker, A. Interaction of inferior

temporal cortex with frontal cortex and basal forebrain:

double dissociation in strategy implementation and

associative learning. J. Neurosci. 22, 7288–7296

(2002).

An interesting paper that used crossed-lesion

methodology to show that disruption of different

frontotemporal connections affects performance on

different memory tasks.

102. Bussey, T. J., Wise, S. P. & Murray, E. A. Interaction of

ventral and orbital prefrontal cortex with inferotemporal

cortex in conditional visuomotor learning. Behav. Neurosci.

116, 703–715 (2002).

103. Eacott, M. J. & Gaffan, D. Inferotemporal-frontal

disconnection: the uncinate fascicle and visual associative

learning in monkeys. Eur. J. Neurosci. 4, 1320–1332 (1992).

104. Hunt, P. R. & Aggleton, J. P. Medial dorsal thalamic lesions

and working memory in the rat. Behav. Neural Biol. 55,

227–246 (1991).

105. Parker, A., Eacott, M. J. & Gaffan, D. The recognition

memory deficit caused by mediodorsal thalamic lesion in

nonhuman primates: a comparison with rhinal cortex lesion.

Eur. J. Neurosci. 9, 2423–2431 (1997).

106. Lee, I. & Kesner, R. P. Time-dependent relationship between

the dorsal hippocampus and the prefrontal cortex in spatial

memory. J. Neurosci. 23, 1517–1523 (2003).

107. Kirchhoff, B. A., Wagner, A. D., Maril, A. & Stern, C. E.

Prefrontal-temporal circuitry for episodic encoding and

subsequent memory. J. Neurosci. 20, 6173–6180 (2000).

108. Otten, L. J. & Rugg, M. D. Task-dependency of the neural

correlates of episodic encoding as measured by fMRI.

Cereb. Cortex 11, 1150–1160 (2001).

109. McDermott, K. B., Buckner, R. L., Petersen, S. E., Kelley, W. M.

& Sanders, A. L. Set- and code-specific activation in the

frontal cortex: an fMRI study of encoding and retrieval of

faces and words. J. Cogn. Neurosci. 11, 631–640 (1999).

110. Nyberg, L. et al. Functional brain maps of retrieval mode and

recovery of episodic information. Neuroreport 7, 249–252

(1995).

111. Maril, A., Simons, J. S., Mitchell, J. P., Schwartz, B. L. &

Schacter, D. L. Feeling-of-knowing in episodic memory: an

event-related fMRI study. Neuroimage 18, 827–836 (2003).

112. McIntosh, A. R., Nyberg, L., Bookstein, F. L. & Tulving, E.

Differential functional connectivity of prefrontal and medial

temporal cortices during episodic memory retrieval. Hum.

Brain Mapp. 5, 323–327 (1997).

113. Büchel, C., Coull, J. T. & Friston, K. J. The predictive value of

changes in effective connectivity for human learning.

Science 283, 1538–1541 (1999).

114. Köhler, S., McIntosh, A. R., Moscovitch, M. & Winocur, G.

Functional interactions between the medial temporal lobes

and posterior neocortex related to episodic memory

retrieval. Cereb. Cortex 8, 451–461 (1998).

115. Maguire, E. A., Vargha-Khadem, F. & Mishkin, M. The effects

of bilateral hippocampal damage on fMRI regional

activations and interactions during memory retrieval. Brain

124, 1156–1170 (2001).

One of the few studies that has examined effective

connectivity associated with memory retrieval and

explored the effects of damage to one of the primary

brain regions on interactivity.

116. Frackowiak, R. S. J., Friston, K. J., Frith, C. D., Dolan, R. J.

& Price, C. J. Human Brain Function (Academic, New York,

in the press).

117. Fuster, J. M., Bodner, M. & Kroger, J. K. Cross-modal and

cross-temporal association in neurons of frontal cortex.

Nature 405, 347–351 (2000).

118. Miller, E. K., Erickson, C. A. & Desimone, R. Neural

mechanisms of visual working memory in prefrontal cortex

of the macaque. J. Neurosci. 16, 5154–5167 (1996).

119. Hasegawa, I., Fukushima, T., Ihara, T. & Miyashita, Y.

Callosal window between prefrontal cortices: cognitive

interaction to retrieve long-term memory. Science 281,

814–818 (1998).

120. Rainer, G., Rao, S. C. & Miller, E. K. Prospective coding for

objects in primate prefrontal cortex. J. Neurosci. 19,

5493–5505 (1999).

121. Tomita, H., Ohbayashi, M., Nakahara, K., Hasegawa, I. &

Miyashita, Y. Top-down signal from prefrontal cortex in

executive control of memory retrieval. Nature 401, 699–703

(1999).

A study that used extracellular electrode recordings

and cortical disconnection to examine the role

of prefrontal cortex in providing top-down control of

memory representations in temporal cortex.

122. Brewer, J. B., Zhao, Z., Desmond, J. E., Glover, G. H. &

Gabrieli, J. D. E. Making memories: brain activity that

predicts how well visual experience will be remembered.

Science 281, 1185–1187 (1998).

123. Schacter, D. L., Buckner, R. L., Koutstaal, W., Dale, A. M. &

Rosen, B. R. Late onset of anterior prefrontal activity during

true and false recognition: an event-related fMRI study.

Neuroimage 6, 259–269 (1997).

124. Henson, R. N. A., Shallice, T. & Dolan, R. J. Right prefrontal

cortex and episodic memory retrieval: a functional MRI test

of the monitoring hypothesis. Brain 122, 1367–1381

(1999).

125. Rempel-Clower, N. L. & Barbas, H. The laminar pattern of

connections between prefrontal and anterior temporal

cortices in the rhesus monkey is related to cortical structure

and function. Cereb. Cortex 10, 851–865 (2000).

126. Lavenex, P. & Amaral, D. G. Hippocampal-neocortical

interaction: a hierarchy of associativity. Hippocampus 10,

420–430 (2000).

127. Rosene, D. L. & Van Hoesen, G. W. Hippocampal efferents

reach widespread areas of cerebral cortex and amygdala in

the rhesus monkey. Science 198, 315–317 (1977).

128. Barbas, H. & Blatt, G. J. Topographically specific

hippocampal projections target functionally distinct

prefrontal areas in the rhesus monkey. Hippocampus 5,

511–533 (1995).

129. Goldman-Rakic, P. S., Selemon, L. D. & Schwartz, M. L.

Dual pathways connecting the dorsolateral prefrontal cortex

with the hippocampal formation and parahippocampal

cortex in the rhesus monkey. Neuroscience 12, 719–743

(1984).

130. Barbas, H., Ghashghaei, H., Dombrowski, S. M. &

Rempel-Clower, N. L. Medial prefrontal cortices are unified

by common connections with superior temporal cortices

and distinguished by input from memory-related areas in

the rhesus monkey. J. Comp. Neurol. 410, 343–367

(1999).

131. Suzuki, W. A. & Amaral, D. G. Perirhinal and

parahippocampal cortices of the macaque monkey: cortical

afferents. J. Comp. Neurol. 350, 497–533 (1994).

132. Thierry, A.-M., Gioanni, Y., Degenetais, E. & Glowinski, J.

Hippocampo-prefrontal cortex pathway: anatomical and

electrophysiological characteristics. Hippocampus 10,

411–419 (2000).

133. Martin, J. H. Neuroanatomy: Text and Atlas 2nd edn

(Appleton & Lange, Stamford, Connecticut, 1996).

134. Baddeley, A. D., Emslie, H. & Nimmo-Smith, I. The Doors

and People Test (Thames Valley Test Company, Bury St.

Edmunds, 1994).

Acknowledgements

We are very grateful to M. Baxter, S. Becker, N. Burgess, J. Gimpel,

R. Henson, M. Rugg and D. Schacter for valuable comments on an

earlier draft. J.S.S. is supported by a Wellcome Trust grant and

H.J.S. by the Alzheimer’s Research Trust.

Online links

FURTHER INFORMATION

Encyclopedia of Life Sciences: http://www.els.net/

memory: clinical disorders

Jon Simons’s page: http://www.icn.ucl.ac.uk/jsimons/

Hugo Spiers’s page:

http://www.icn.ucl.ac.uk/groups/JO/mempages/hugo/

Access to this interactive links box is free online.

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BRAIN STRUCT FUNCT

Crossmodal associations and correspondences play important roles in shaping perception and guiding our actions. However, we still have a limited understanding of association-induced changes in the adult human brain. An important question to address is to what extent passive exposure to crossmodal associations leads to functional and structural changes in the brain. Utilizing an audiovisual association paradigm in which motion stimuli presented in the left visual field were paired with auditory tones, we investigated experience-dependent crossmodal plasticity by examining resting-state functional connectivity and cortical thickness. Following the association phase, we observed widespread increases in functional connectivity between the trained region (e.g., right V1, V2, and V3) and higher-order frontal, temporal, and occipital areas. In contrast, functional connectivity changes in the untrained region (e.g., left V1, V2, and V3) were markedly reduced, indicating that the observed plasticity was largely specific to the cortical representation of the stimulated visual field. Consistent with the functional results, cortical thickness analysis revealed a clear hemispheric asymmetry, with significant changes observed exclusively in the right hemisphere. Moreover, both the functional and structural assessments showed widespread changes in high-level association cortices, whereas changes in low-level sensory areas were less pronounced. The overlap between functional and structural measures suggests that enhanced connectivity aligns with structural changes due to crossmodal associations. These results illustrate that associations formed without explicit training or feedback can lead to functional and structural changes in the adult human brain, providing important implications for perception and neural plasticity in daily life situations.

Network Occlusion Sensitivity Analysis Identifies Regional Contributions to Brain Age Prediction

Article

Full-text available

Jun 2025
HUM BRAIN MAPP

Deep learning frameworks utilizing convolutional neural networks (CNNs) have frequently been used for brain age prediction and have achieved outstanding performance. Nevertheless, deep learning remains a black box as it is hard to interpret which brain parts contribute significantly to the predictions. To tackle this challenge, we first trained a lightweight, fully CNN model for brain age estimation on a large sample data set (N = 3054, age range = [8,80 years]) and tested it on an independent data set (N = 555, age range = [8,80 years]). We then developed an interpretable scheme combining network occlusion sensitivity analysis (NOSA) with a fine‐grained human brain atlas to uncover the learned invariance of the model. Our findings show that the dorsolateral, dorsomedial frontal cortex, anterior cingulate cortex, and thalamus had the highest contributions to age prediction across the lifespan. More interestingly, we observed that different regions showed divergent patterns in their predictions for specific age groups and that the bilateral hemispheres contributed differently to the predictions. Regions in the frontal lobe were essential predictors in both the developmental and aging stages, with the thalamus remaining relatively stable and saliently correlated with other regional changes throughout the lifespan. The lateral and medial temporal brain regions gradually became involved during the aging phase. At the network level, the frontoparietal and the default mode networks show an inverted U‐shape contribution from the developmental to the aging stages. The framework could identify regional contributions to the brain age prediction model, which could help increase the model interpretability when serving as an aging biomarker.

Dimensions of corvid consciousness

Article

Full-text available

May 2025
ANIM COGN

Corvids have long been a target of public fascination and of scientific attention, particularly in the study of animal minds. Using Birch et al.’s (2020) 5-dimensional framework for animal consciousness we ask what it is like to be a corvid and propose a speculative but empirically informed answer. We go on to suggest future directions for research on corvid consciousness and how it can inform ethical treatment and animal welfare legislation.

The Role of Physical Activity on Spatial and Temporal Cognitive Processing in Young Women

Article

Full-text available

Apr 2025
BSRCCS

Background/Objectives: Physical activity (PA) has many benefits for both physical and cognitive health. It has also been related to improvements in memory and executive functions. However, its impact on time estimation remains less explored. Time is a key component of episodic memory, which also involves spatial components to give a full context to events. Given the clear evidence of the benefits of PA in spatial navigation and the anatomical overlap with temporal estimation through the hippocampus, the latter could be affected in a similar way. Therefore, this study aimed to check how PA can influence time processing and spatial memory. We wanted to check if PA influenced time and space with the same directionality. Methods: Forty-two (n = 42) female university students participated in this study, divided into a Sport (n = 25) or Sedentary (n = 17) Group depending on their participation in PA for a minimum of 3 h a week. They were addressed in two different cognitive capabilities. The first was time processing, measured by the Time Comparison Task, which controlled for several key aspects of time literature in its design. Moreover, we measured spatial navigation skills, using a well-proven virtual spatial navigation task, The Boxes Room. Accuracy and mean response times were registered per task. Results: Significant correlations were observed between spatial and temporal task performance. In addition, PA influenced spatial and time processing in a similar way, with the Sport Group outperforming the Sedentary Group in accuracy and response times for both tasks. Conclusions: These findings provide evidence that PA influences time processing similarly to its established effects on spatial memory, which could help developing sports programs that further enhance this skill.

Functional connectivity reveals increased network segregation and sensorimotor processing during working memory in adolescents with Neurofibromatosis Type 1

Preprint

Full-text available

Apr 2025

Neurofibromatosis type 1 (NF1) is a rare genetic condition characterised by skin pigmentations, bone deformities, and tumours. Its cognitive phenotype shares similarities with autism spectrum disorder and attention deficit/hyperactivity disorder, including impairments in executive function and working memory processing. In this work, we conducted functional connectivity and graph theory analysis of fMRI data from a sample of neurotypical adolescents (N = 26) and a sample of adolescent NF1 - participants (N = 43). Whole brain comparisons demonstrated that during working memory conditions NF1 participants have greater connectivity in left posterior parietal regions, particularly converging at the postcentral gyrus. Comparison of communication between functional networks demonstrated that NF1 participants have increased connectivity between visual, sensorimotor, dorsal attention and limbic networks. Individual connections were weaker in NF1 participants across the brain, and we found reduced connectivity between control, dorsal attention and default networks in NF1. Furthermore, connectivity strength in these networks was predictive of accuracy and response time in NF1 participants during the task performance. Finally, graph theory analysis showed that working memory demands evoked reorganisation towards greater assortativity in NF1 participants, which was predictive of poorer accuracy and accuracy-speed trade-off. These findings highlight that NF1 participants' working memory deficits emerge from reduced engagement of executive processes, and NF1 participants demonstrate coping mechanisms such as enhanced sensorimotor processing and network reorganisation towards greater segregation, that is however detrimental to cognitive performance.

Heterosynaptic Regulation of α2A-Adrenoceptors on Glutamate/GABA Release in the Prefrontal Cortex of Rats

Article

May 2025

Background/Objectives:Norepinephrine (NE) plays a crucial role in modulating cognitive processes via α2A-adrenoceptors (α2A-ARs) within the prefrontal cortex (PFC), an essential brain region responsible for higher cognitive functions. The α2A-ARs are found on both postsynaptic and presynaptic membranes in the PFC. Previous studies have shown that presynaptic α2A-ARs, predominantly located at NE terminals, function as autoreceptors that inhibit NE release. However, the expression of α2A-ARs at non-NE terminals, such as glutamate and GABA, remains ambiguous. To clarify the expression patterns and potential roles of α2A-ARs at non-NE terminals, we investigated their presence at the axon terminals of excitatory glutamate neurons and inhibitory GABA neurons in the rat PFC using immunofluorescence double-labeling, whole-cell patch-clamp recordings, and pharmacological approaches. Methods: To clarify the expression patterns and potential roles of α2A-ARs at non-NE terminals, we investigated their presence at the axon terminals of glutamate neurons and GABA neurons in the rat PFC using immunofluorescence double-labeling, whole-cell patch-clamp recordings, and pharmacological approaches. Results: Our findings delineated the distribution of α2A-ARs at the axon terminals of both glutamate and GABA neurons, and the expression of α2A-AR in the pyramidal neurons within the rat PFC as well. Furthermore, we employed the selective α2A-AR agonist guanfacine to assess the functional role of presynaptic α2A-ARs at these non-NE terminals. Following the application of the PKA inhibitor PKI5–24 to block postsynaptic α2A-AR function, guanfacine still significantly decreased the frequency (not the amplitude) of miniature excitatory postsynaptic currents (mEPSCs) and miniature inhibitory postsynaptic currents (mIPSCs) in layer 5–6 pyramidal neurons. Notably, the frequency reduction induced by guanfacine persisted even after the depletion of presynaptic NE vesicles. Conclusions: These findings offer a comprehensive analysis of presynaptic α2A-AR expression and function in the PFC, revealing for the first time their role as heteroreceptors that modulate the release of glutamate and GABA. Our results provide morphological and electrophysiological insights into a potential mechanism through which α2A-AR stimulation enhances cognitive functions.

The macroevolution of brain size and cortical association areas in primates

Chapter

Jan 2025

Interaction of Ventral and Orbital Prefrontal Cortex With Inferotemporal Cortex in Conditional Visuomotor Learning

Article

Full-text available

Aug 2002

Five rhesus monkeys (Macaca mulatta) were trained to learn novel conditional visuomotor associations, to perform this task with familiar stimuli, and to perform a visual matching-to- sample task with the same familiar stimuli. Removal of the orbital and ventral prefrontal cortex (PFv+o) in 1 hemisphere and inferotemporal cortex (IT) in the other, thus completing a surgical disconnection of these 2 regions, yielded an impairment on all 3 tasks. Addition of a premotor cortex lesion to the hemisphere containing the PFv+o lesion did not worsen the impairments. The results indicate that PFv+o interacts with IT in both the learning and retention of conditional visuomotor associations. In addition to those associations, which might be considered lower order rules for choosing a response, frontotemporal interaction also appears to be important for higher order rules, such as those involved in the matching task.

Differentiating the Roles of the Hippocampal Complex and the Neocortex in Long-Term Memory Storage: Evidence From the Study of Semantic Dementia and Alzheimer's Disease

Article

Full-text available

Jan 1997

Several computational models suggest that the hippocampal complex plays a key role in the establishment of new memories, but over time the storage of such memories becomes independent of this region. In support of such models, the authors demonstrate that patients with semantic dementia, who have relative sparing of the hippocampal complex, show a pattern of preserved recent memories and impaired distant memories. In a group study that used the Autobiographical Memory Interview, amnesic patients with Alzheimer's disease showed the more typical temporally graded loss (poor recall of recent memories), whereas patients with semantic dementia showed the reverse pattern. In a single-case study, using the Galton-Crovitz test, a patient with semantic dementia was significantly better at producing autobiographical memories from the most recent 5 years. By contrast, controls provided similarly detailed memories across all time periods back to childhood.

Semantic Knowledge and Episodic Memory for Faces in Semantic Dementia

Article

Full-text available

Jan 2001

Previous studies have documented poor recognition memory for faces in patients with semantic dementia. Preserved face recognition memory was found in this study, however, so long as atrophy was confined predominantly to the left temporal lobe. Patients with structural damage to the right temporal lobe were typically impaired, with the status of the hippocampus and parahippocampal gyrus (including the perirhinal cortex) on the right being critical. Two single-case studies of patients with predominantly left temporal lobe pathology confirmed good recognition memory for famous faces, even if semantic knowledge about the celebrities depicted was severely degraded. An effect of semantic knowledge on recognition memory became apparent only when perceptually different photographs of the famous people were used at study and test. These results support the view that new episodic learning typically draws on information from both perceptual and semantic systems.

Memory in the Cerebral Cortex (Second Edition)

Book

Full-text available

Jan 1999

Joaquin M Fuster

Perceptual and semantic contributions to episodic memory: Evidence from semantic dementia and Alzheimer's disease

Article

Aug 2002
J MEM LANG

Previous group studies involving patients with semantic dementia, who have impaired semantic memory associated with temporal lobe atrophy, have documented the preservation of pictorial recognition memory, in contrast to patients with early Alzheimer's disease, who characteristically exhibit amnesia. The present study replicated this general pattern, although four of the semantic dementia patients with the most severe semantic deficit additionally had impaired recognition memory. Three factors that might contribute to this pattern of memory performance were examined: atrophic damage to medial temporal lobe regions, degradation of semantic representations, and disruption to visuoperceptual processes. Assessment of MRI scans revealed that atrophy affecting the perirhinal cortex region accurately predicted the recognition memory deficit seen at advanced stages of semantic dementia, but there was no evidence that it could be attributed directly either to degraded semantic knowledge or disrupted perceptual processing. In Alzhei-mer's disease, evidence suggested that visuoperceptual impairment might be involved in the poor recognition memory typically seen in the disorder. These results have implications for the differential diagnosis of semantic dementia and Alzheimer's disease and for cognitive and neural theories of human long-term memory. Ó

Recollection-based memory in frontotemporal dementia: implications for theories of long-term memory

Article

Nov 2002
BRAIN

It has been convincingly demonstrated that patients with semantic dementia (the temporal variant of fronto-temporal dementia) can show intact recognition memory for pictorial stimuli. As yet, the contribution made by recollective processes to this ability and the status of associated neural regions have not been investigated in the disease. Here, we used both a source monitoring paradigm and an associative memory test to evaluate the ability of patients with semantic dementia to use recollection-based memory processes, and a volumetric MRI technique to assess the extent of atrophy in the hippocampus. Although some patients showed impaired source and associative memory, many performed as well as control participants. Importantly, status of semantic knowledge, as measured by tests of comprehension and production, did not predict recollection-based memory ability. There was no signi®cant positive correlation between recollection and volume of the hip-pocampus; instead, both source discrimination and asso-ciative memory correlated highly with performance on a battery of frontal lobe tests. Consistent with the view that damage to the prefrontal cortex might in¯uence recollection performance, patients with the frontal variant of frontotemporal dementia, with atrophy largely con®ned to the frontal lobes, all performed at ¯oor level on source discrimination. These results provide further compelling evidence in favour of the multiple input model of long-term memory and highlight the role of frontal lobe systems in recollection-based memory. Abbreviations: fvFTD = frontal variant of frontotemporal dementia; SemDem = group of patients with semantic dementia; SPI = serial-parallel-independent; VOSP = Visual Object and Space Perception test battery

Differentiating the role of the hippocampal complex and the neocortex in long-term memory storage: evidence from the study of semantic memory and Alzheimer’s Disease.

Article

Feb 1997

John R Hodges

Hippocampal‐neocortical interaction: A hierarchy of associativity

Article

Jan 2000

The structures forming the medial temporal lobe appear to be necessary for the establishment of long-term declarative memory. In particular, they may be involved in the “consolidation” of information in higher-order associational cortices, perhaps through feedback projections. This review highlights the fact that the medial temporal lobe is organized as a hierarchy of associational networks. Indeed, associational connections within the perirhinal, parahippocampal, and entorhinal cortices enables a significant amount of integration of unimodal and polymodal inputs, so that only highly integrated information reaches the remainder of the hippocampal formation. The feedback efferent projections from the perirhinal and parahippocampal cortices to the neocortex largely reciprocate the afferent projections from the neocortex to these areas. There are, however, noticeable differences in the degree of reciprocity of connections between the perirhinal and parahippocampal cortices and certain areas of the neocortex, in particular in the frontal and temporal lobes. These observations are particularly important for models of hippocampal-neocortical interaction and long-term storage of information in the neocortex. Furthermore, recent functional studies suggest that the perirhinal and parahippocampal cortices are more than interfaces for communication between the neocortex and the hippocampal formation. These structures participate actively in memory processes, but the precise role they play in the service of memory or other cognitive functions is currently unclear. Hippocampus 10:420–430, 2000

The hippocampus as a spatial map. Preliminary evidence from unit activity in the freely-moving rat

Article

Dec 1971
BRAIN RES

A verbal mechanism for working and recognition memory in inferior temporal cortex

Article

Jan 1991

Prefrontal and medial temporal lobe interactions in long-term memory

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