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Rather, it requires a lesion method that leads to isolated disruption of specific processors along the proposed hierarchical gradient. Additionally, using the cognitive tasks we implemented in the fMRI study, we have carried out a behavioral study of patients with focal frontal lesions to test the hypothesis that there is a hierarchical organization in frontal cortex Badre et al. Specifically, we tested whether a lesion to the pre-PMd region of frontal cortex area 8 , assumed to damage a 2nd level processor, would impair performance on the Feature task as well as the Dimension and Context tasks, but would not affect performance on the Response task.
Reflections on neurotheology and neuroscience There are a number of neuroscience topics that might directly influence and be influenced by neurotheological research. An Introduction to Child Development. The focus on quantifying degree of identification with cultural values and its relationship to brain structure and function is important, as it provides validation that cultural values are controlling effects, in light of the many other sources of variance between different cultures. In this scheme, less differentiated areas such as those in rostral PFC areas 10, 9, 46 , which have more diffuse projections, are well situated to be the top of a hierarchy. For example, increasingly abstract representations of rules and goals could serve as different top-down signals that could bias particular but different action pathways over competitors allowing for flexible goal-directed behavior.
The reasoning was that disruption of the 2 nd level of a hierarchy should interfere with processing at higher levels Feature , Dimension , and Context tasks at the 3rd and 4th levels , but not at lower levels Response task, 1st level. Such a pattern of behavioral results in patients with focal frontal lesions would be direct evidence for a hierarchical organization of frontal lobe function.
We predicted that because of the asymmetric dependencies predicted by a hierarchy, deficits in higher level tasks will be more likely across patients, regardless of the site of their lesion, than deficits in lower level tasks. Thus, the presence of an impairment at any level should increase the likelihood of an impairment at all higher levels, but should not increase the odds of an impairment at a lower level. This asymmetry provides initial support for the hierarchical dependencies among behavioral deficits at the different levels of the task and the aggregation account of the group data.
Recently, this pattern of findings supporting a frontal hierarchy has been replicated in another group of patients with focal frontal lesions Azuar et al. Hierarchical organization of rules and goals has many advantages. For example, increasingly abstract representations of rules and goals could serve as different top-down signals that could bias particular but different action pathways over competitors allowing for flexible goal-directed behavior. Take the example of the seemingly simple act of hitting a golf ball.
Hitting the ball in the proper direction requires temporary maintenance of the location of the flag on the green — a relatively concrete representation. If the golf ball is in a fairway bunker, it also requires the temporary maintenance of more abstract representation of the golf rule stating that the golf club cannot touch the sand before hitting the ball, or a penalty will be assessed. Finally, throughout this act of hitting the ball it might also be beneficial to maintain an even more abstract representation of the knowledge that golf provides exercise and is a healthy behavior.
In this way, simultaneous maintenance of hierarchically organized representations within PFC can provide independent, yet likely interactive top-down bias signals that may or may not lead to a successful goal-directed behavior! The PFC has long been implicated as a source of top-down signals that can influence processing in other cortical and subcortical brain regions Duncan , Fuster , Shallice , Braver et al. One type of PFC top-down signal likely provides direct feedback to posterior cortical regions that process incoming sensory input from a particular modality e.
For example, when a person is looking into a crowd of people, the visual scene presented to the retina may include a vast array of visual information. However, if someone is searching for a friend, some top-down mechanism must exist that allows for suppressing irrelevant visual information while enhancing task-relevant information allowing for an efficient yet effective search. In this way, the maintenance and representation of the goal e. As described earlier in this review, given that the PFC represents rules and goals at multiple levels of abstraction, it is in an ideal position to influence processing in downstream brain regions that receive its anatomical projections.
In this study, during each trial of a working memory task participants observed sequences of two faces and two natural scenes presented in a randomized order. In separate blocks of trials subjects were required to Remember Faces and Ignore Scenes , Remember Scenes and Ignore Faces , or Passively View faces and scenes without attempting to remember them. Since each trial had equivalent bottom-up visual information e. Moreover, the inclusion of a passive baseline allowed for the dissociation of possible enhancement and suppression mechanisms. With both fMRI and ERP we obtained activity measures from areas of visual association cortex specialized in face and scene processing.
For fMRI, we used an independent functional localizer to identify both stimulus-selective face regions within the fusiform face area or FFA; Kanwisher et al. For ERP, we utilized a face-selective ERP, the N , a component localized to posterior occipital electrodes reflecting visual association cortex activity with face specificity Bentin et al.
Our fMRI and ERP data revealed top-down modulation of both activity magnitude and processing speed that occurred above and below the perceptual baseline depending on task instruction. That is, during the encoding period of the delay task, FFA activity was enhanced, and the N occurred earlier, when faces had to be remembered as compared to a condition where they were passively viewed. Likewise, FFA activity was suppressed, and the N occurred later, when faces had to be ignored compared to a condition where they were passively viewed. These results suggest that there are least two types of top-down signals, one that serves to enhance task-relevant information, and the other that serves to suppress task-relevant information.
By generating contrast via enhancing and suppressing activity magnitude and processing speed, top-down signals can bias the likelihood of successful representation of relevant information in a competitive system Hillyard et al. With fMRI or any type of neurophysiological method applied to animals or humans, there is no direct way to determine the source of top down signals. The first attempt at such an approach was performed by Joaquin Fuster and colleagues in monkeys where the effect of PFC inactivation by cooling on spiking activity in inferotemporal cortex neurons during a delayed-match-to-sample color task was investigated.
During the delay interval in this task — when persistent stimulus-specific activity in inferotemporal cortical neurons is observed — PFC inactivation caused attenuated spiking activity and a loss of stimulus-specificity of inferotemporal cortical neurons. These two alterations of inferotemporal cortex activity strongly implicated the PFC as a source of top-down signals necessary for maintaining robust sensory representations in the absence of bottom-up sensory activity.
Many years passed before any other attempt was made with animals or humans to follow-up this landmark finding by Fuster. Translating this approach to humans, Chao and Knight investigated patients with lateral PFC lesions during delayed match-to-sample tasks. It was found that when distracting stimuli are presented during the delay period the amplitude of the ERP recorded from posterior electrodes was markedly increased in patients with frontal lesions compared to controls. These results were interpreted as demonstrating disinhibition of sensory processing supporting a role of the PFC in suppressing the representation of task-irrelevant stimuli.
Recently, we investigated the causal role of the PFC in the modulation of evoked-activity in human extrastriate cortex during the encoding of faces and scenes Miller, et al.
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We employed two experimental approaches to disrupt PFC function: We then investigated the effect of disrupted PFC function on the selectivity of category representations faces or scenes in temporal cortex. Different object categories, like faces and scenes are represented by spatially distributed, yet overlapping, assemblies in extrastriate visual cortex Haxby, et al.
Thus, we reasoned that disruption of PFC function would lead to higher spatial correlations between scene- and face-evoked activity in extrastriate cortex, suggesting a decrease in category selectivity. Consistent with our predictions, following disruption of PFC function i. This work extended the findings of Fuster and colleagues in monkeys to humans and suggests that the PFC may sharpen the representations of different object categories in extrastriate cortex by increasing the distinctiveness of their distributed neural representations. Together, such causal evidence clearly supports the notion that the PFC is the source of top-down signals that act via both gain and selectivity mechanisms.
A key to understanding the role of the PFC in cognition likely rests in its connectivity with other regions Yeterian et al. Any top-down signal from a particular PFC region, representing a particular goal, could have a different influence and behavioral consequence depending on what brain regions are recipients of these signals. For example, PFC top-down signals could enhance internal representations of relevant sensory stimuli in extrastriate cortex or anticipated motor plans in premotor cortex.
It is likely that multiple top-down signals are engaged in a parallel fashion during the evolution of any goal-directed behavior. Moreover, other cortical regions, such as the parietal cortex and hippocampus have also been proposed to provide top-down signals during cognition Eichenbaum , Ruff Consideration of the mechanisms by which multiple higher-order brain regions can influence lower-order brain regions highlights the enormous complexity of the human brain, and how much further we must travel to understand it.
Another mechanism critical for working memory is the synchronization of activity among distributed brain regions. Owing to the limitations in available methodology in both animals and humans, only a limited number of studies to date have been able to assess if and how neurons and brain regions communicate and interact to support working memory. We developed a multivariate method designed specifically to characterize functional connectivity in event-related fMRI data that can measure inter-regional correlations during the individual stages of a cognitive task Rissman et al.
Using this method, we specifically sought to characterize the network of brain regions associated with the maintenance of a representation of face stimuli over a short delay interval. With this approach Gazzaley et al. Similarly, we have also found that posterior language-related areas involved in the maintenance of words in the absence of visual input also exhibit increased functional connectivity with the PFC Fiebach et al.
Distributed synchronized activity could occur via synaptic reverberations in recurrent circuits Wang , Durstewitz et al. In humans, electroencephalographic EEG magnetoencephalographic MEG and electrocorticographic ECoG recordings have been utilized to investigate which particular frequencies of oscillations may be related to working memory.
Roux and Uhlhaas have proposed a different functional role for each of these frequency bands. Specifically, they propose that gamma-band oscillations are involved in the active maintenance of working memory information, theta-band oscillations are specifically involved in the temporal organization of working memory items and alpha-band oscillations are involved in the inhibition of task-irrelevant information. These notions are based on studies that have demonstrated amplitude modulation of neural oscillations presumably emanating from particular brain regions involved in working memory. For example, during a delayed match to sample task while recording human EEG it was observed that occipital gamma and frontal beta oscillations were sustained across the retention interval.
Moreover, as this delay interval lengthened, these oscillations decreased in parallel with decreased performance on the task Tallon-Baudry et al. In a recent study Anderson et al. These empirical findings support the notion that neural oscillations are critical for working memory maintenance processes. It is likely that long-range synchronization of these oscillations between brain regions also plays an important role in working memory function Sauseng et al. For example, in a human MEG study, synchronized oscillations in the alpha, beta and gamma bands was observed between frontoparietal and visual areas during the retention interval of a delayed match-to-sample visual working memory task.
Moreover, these observed synchronized oscillations were sustained and stable throughout the delay period of the task, memory load dependent, and correlated with an individuals working memory capacity Palva et al. Monkey physiology data have also provided considerable insight into the possible mechanisms underlying communication between brain regions during working memory. For example, in one study Liebe et al. During the retention interval of the task, these two areas exhibited synchronization of local field potentials in the theta frequencies.
Moreover, there was phase-locking of neuronal spiking activity in these two regions to these observed theta oscillations. An intriguing recent finding suggests a critical role for the thalamus in regulating information transmission across cortical regions, at least at the local level Saalmann et al. In many models of cognition, neuromodulators such as dopamine, serotonin, norepinephrine or acetylcholine, play a limited role, if any role at all. Yet, given that brainstem neuromodulatory neurons send projections to all areas of brain, their influence on cognitive function is without question.
Dopaminergic neurons in the human brain are organized into several major subsystems mesocortical, mesolimbic and nigrostriatal. Across the cerebral cortex, the concentration of dopamine is highest within the frontal cortex Brown et al. The functional importance of dopamine to working memory and PFC function has been demonstrated in several ways.
First, in monkeys depletion of PFC dopamine or pharmacological blockade of dopamine receptors induces working memory deficits Brozoski et al. These deficits are as severe as in monkeys with PFC lesions, and are not observed in monkeys in which other neurotransmitters, such as serotonin are depleted. Furthermore, dopaminergic agonists administered to monkeys with dopamine depletion reverses their working memory deficits Brozoski et al.
An important feature of the dopaminergic system is that it exhibits a U-shaped dose-response curve which leads to specific dosages of dopaminergic drugs producing optimal performance on working memory tasks Arnsten et al. Different classes of dopamine receptors exist in varying concentrations throughout the brain. D-2 dopamine receptors are present in much lower concentrations in the cortex than D-1 receptors, and are mostly within the striatum Camps et al.
Moreover, dopamine release in the brain can be either transient phasic or sustained tonic. Grace has proposed that these two mechanisms of action of dopamine are functionally distinct and antagonistic. Specifically, it is proposed that tonic dopamine release is mediated by D1 receptors whereas D2 receptor mediated effects are phasic. In support of this notion, during performance of a working memory task in monkeys, a dopamine D2 receptor agonist selectively modulated the phasic component of the task yet had little effect on the persistent mnemonic-related activity, which was instead modulated by a D1 receptor agonist Sawaguchi et al , Wang et al.
Thus, these two dopamine receptors likely have complementary functions, which serve to modulate active memory representations stored within PFC Cohen et al. The dual-state theory of PFC dopamine function put forward by Durstewitz and Seamans states that a D1-dominated state favors robust online maintenance of information, while a D2-dominated state is beneficial for flexible and fast switching among representational states. In this way, two separate mechanisms underlie cognitive flexibility and stability that nevertheless must work together: Specifically, dopamine receptor stimulation in the PFC would promote stability by increasing distractor-resistance Durstewitz et al.
Conversely, dopamine receptor stimulation in the striatum would promote flexibility by allowing the updating of newly relevant representations Frank et al. In the context of real world situations, demands for cognitive flexibility and stability are reciprocal: We have tested this dopaminergic model of working memory with a human pharmacological fMRI study Cools et al. Healthy young subjects underwent fMRI scanning on two occasions, once after intake of the dopaminergic agonist bromocriptine and once after placebo in a double-blind, cross-over design. During scanning, subjects performed a working memory task that allowed the separate investigation of working memory updating and maintenance processes.
Specifically, subjects had to encode, maintain and retrieve visual stimuli over a short delay. Two faces and two scenes were always presented during the encoding period and subjects were instructed to remember either the face or scenes. During the retention period another stimulus was presented, which subjects were instructed to ignore. This distractor was either a scrambled image or a novel face or scene.
The critical measure of working memory updating was the behavioral switch-cost, which was calculated by subtracting performance error rates and reaction times measured at probe on trials where they switched to a new instruction as compared to remaining with the same instruction. The critical measure of working memory maintenance was the behavioral distractor-cost, which was calculated by subtracting performance measured at probe after scrambled as compared to non-scrambled distractors.
We predicted that bromocriptine would modulate PFC activity during the epoch of the task following distraction, but the striatum would be modulated during the instruction epoch. This is exactly what we observed which is is consistent with the hypothesis that working memory maintenance and updating processes are modulated by differential dopaminergic stimulation of the PFC and striatum, respectively.
The functional opponency between stability and flexibility of working memory representations maps well onto the neurochemical reciprocity between DA in the PFC and the striatum: Midbrain activity also correlated with PFC activity as well as with behavior. These findings support the idea that dopamine acts as a gating signal to the PFC when updating of maintained representations are required. The first type provides gating of inputs to be maintained by frontal cortex input gating and the second type of gating signal determines which of these maintained representations will have an influence on particular actions that are selected output gating.
Selective gating rather than a global mechanism arising from midbrain dopaminergic input that would update everything allows for some information to be maintained by PFC while other information is updated. The idea of selective striatal gating also allows for a hierarchy within fronto-striatal circuitry such that contextual representations in rostral frontal cortex can influence striatal gating of contextual representations in caudal frontal cortex. An MRI study using diffusion tractography has demonstrated that the proper wiring is in place for such a mechanism in that there is a rostral-caudal correspondence in the connectivity pattern between frontal and striatal regions Verstynen et al.
Working memory is a construct that has motivated research in many domains — cognitive, neuroscientific, clinical — for the past 50 years. The results from this half-century of research, cumulatively, have reinforced the centrality, articulated in seminal writings from the s, 70s, and 80s, of working memory in the control of behavior. The past decade has witnessed many exciting advances in our understanding of the mechanisms that underlie working memory, and these have necessarily prompted the near-continuous updating of our models of how working memory works. At a broader level, however, one could make the case that our current neural systems-level models were foreshadowed by a core feature of the Baddeley and Hitch multiple component model, and that is the important distinction between stimulus representation, on the one hand, and the control of behavior with those representations, on the other.
The prefrontal, basal ganglia, thalamic, and brainstem systems reviewed here can be construed as a neural substrate for this Central Executive. We believe that a conceptual error at the root of some of the systems- and cognitive-neuroscience research from the s—s was misattribution of PFC activity to the functioning of one of the storage buffers from the multicomponent model, rather than to the Central Executive. The research that we have reviewed here makes it clear that the functions of PFC and related systems are too flexible, and operate on too abstract a level, to be construed as simply performing a buffering role.
The past ten years have also witnessed considerable progress in our understanding of how the function of buffering is accomplished in the primate brain. The analogy to computer architecture may have, at least implicitly, influenced previous thinking about biological working memory.
For symbolic information, this has been captured by models of activated semantic LTM. For sensorimotor information, by sensorimotor recruitment models.
In this review, we have emphasized the fundamental importance of working memory for cognitive control. It is our belief that any understanding of the basic mechanisms of working memory leads directly to a further understanding of the most complex aspects of human cognition. The frontal cortex continues to be a primary area of focus in attempts to uncover the neural mechanisms that support component processes that are necessary for cognitive control.
The frontal cortex is hierarchically organized and provides critical bias signals that sculpt goal-directed behavior. Much work is still needed regarding the nature of these signals, and the mechanisms by which the frontal cortex maintains relevant information and communicates with other brain regions. Moreover, ascending brainstem neuromodulatory systems, such as the dopaminergic system, likely influence most of the cognitive processes mentioned in this review.
A consideration of all of these mechanisms together, rather than in isolation, should provide a clearer picture of the neural bases of cognitive control. We also wish to acknowledge the generous funding we have received over the years from the National Institutes of Health. National Center for Biotechnology Information , U. Author manuscript; available in PMC Mar Author information Copyright and License information Disclaimer.
The publisher's final edited version of this article is available at Annu Rev Psychol. See other articles in PMC that cite the published article. In it, the authors state: The temporary activation of LTM representations The subset of state-based models that has been formalized to the highest degree are those pertaining to working memory for information for which there exists a semantic representation in LTM.
Sensorimotor recruitment The basic premise of sensorimotor recruitment models of working memory is that the same systems and representations that are engaged in the perception of information can also contribute to the short-term retention of that information. Capacity limits of visual working memory A focus of intensive investigation for sensorimotor recruitment models has been the factors that explain capacity limitations. Working memory at the systems level Working memory does not derive from a discrete system, as do vision and motor control.
Persistent Neural Activity The study of the neural underpinnings of working memory took a significant leap forward in with the publication of two studies featuring extracellular recordings from the PFC in monkeys performing working memory tasks. Hierarchical representations in prefrontal cortex What is the nature of the neural code within PFC? For example, Fuster and Alexander [] wrote that: Top-down signaling The PFC has long been implicated as a source of top-down signals that can influence processing in other cortical and subcortical brain regions Duncan , Fuster , Shallice , Braver et al.
Long-range connectivity Another mechanism critical for working memory is the synchronization of activity among distributed brain regions. Brainstem Neuromodulators In many models of cognition, neuromodulators such as dopamine, serotonin, norepinephrine or acetylcholine, play a limited role, if any role at all. An enduring principle of the multiple-component model of working memory Baddeley and Hitch, is that the short-term retention of information a. With regard to the former, however, earlier ideas of specialized buffers have been largely superceded by state-based models.
Some recent findings from computational modeling, extracellular electrophysiology, fMRI, and EEG, suggest that working memory storage may depend on the transient reorganization of synaptic weights, rather than on sustained, elevated activity. The PFC likely represents higher-order information, such as task rules, goals, or abstract representations of categories, as compared to feature- and stimulus-specific representations in posterior cortex. Moreover, a critical mechanism for working memory function is the synchronization of PFC activity with activity in other brain regions.
One dimension of functional organization of PFC is a hierarchical caudal-to-rostral gradient of the level of abstraction of the rules and goals that guide behavior. Top-down control signals emanating from PFC likely take at least two forms: Dopamine plays a critical role in working memory function. How is the focus of attention organized? Does it have a strict capacity limit of one item or can it contain multiple items? Are there multiple distinct levels within the focus of attention or levels of activation within working memory , or is everything outside a unitary focus of attention in the same state of long-term memory?
What class of models better account for capacity limitations in visual STM — slots models, single-resource models, a hybrid of the two, or some as-yet-to-be-described alternative? Because recent MVPA studies have dissociated working-memory storage from sustained, elevated delay-period activity, what functions does the latter subserve?
Is it possible, as suggested by recent experiments, that all delay-period activity that is decodable with MVPA, even activity that is below univariate statistical thresholds, corresponds to the focus of attention, rather than the storage of information per se? If so, is that the latter accomplished via the transient reorganization of synaptic weights? Is the high dimensionality that has been ascribed to ensembles of PFC neurons a property that is unique to that region, or is the property also characteristic of other brain regions?
What are the different functional roles of particular frequencies of oscillations e. What is the role of other neurotransmitters and hormones, in addition dopamine, in working memory function? Catechol-O-methyltransferase genotype and dopamine regulation in the human brain. The capacity of visual short-term memory is set both by visual information load and by number of objects. Induced alpha rhythms track the content and quality of visual working memory representations with high temporal precision. Catecholamine regulation of the prefrontal cortex. Dopamine D1 receptor mechanisms in the cognitive performance of young adult and aged monkeys.
Overlapping mechanisms of attention and spatial working memory. Trends in Cognitive Sciences. Rehearsal in spatial working memory. Journal of Experimental Psychology: Testing the model of caudo-rostral organization of cognitive control in the human with frontal lesions. Recent Advances in Learning and Motivation. Cognitive control, hierarchy, and the rostrocaudal organization of the frontal lobes. Opening the gate to working memory. Functional magnetic resonance imaging evidence for a hierarchical organization of the prefrontal cortex. Is the rostrocaudal axis of the frontal lobe hierarchical?
The study of cultural differences in neurocognitive function is fraught with potential confounds and hazards that cloud interpretation of the data. The scope of this issue could easily encompass an entire volume. The focus here will be on three considerations particularly salient to neuroimaging studies. First, in conducting cross-cultural imaging work, it is important to recognize that neuroimaging data is very different from behavioral data.
The dependent measure in an MRI study consists of t values for roughly 30, to 35, voxels of data, which if collected functionally, are typically sampled every 2 s, providing literally millions of data points as outcomes. This is quite a contrast with cognitive behavioral data that often involves only a few measures of memory, reaction time, or attention. Moreover, the data are collected from two groups of participants who typically differ in many systematic ways besides their cultural values, rendering interpretation of any differences found quite difficult.
As the above review of the behavioral data indicate, there is a wealth of evidence that visuo-perceptual processes differ between East Asian and Westerners. For this reason, it made sense for the initial work our research group did on neurocultural differences to focus on the VVC, an area of the brain associated with object recognition, contextual processing, and binding of scene elements. A second issue to keep in mind when conducting cross-cultural studies of cognition is the importance of collecting some objective measure of performance suggesting groups are matched.
Figure 3 presents neuropsychological data reported by Hedden et al. The study demonstrates clearly that when numerically based tests of speed of processing digit comparison and working memory backward digit span were used, young Chinese showed superior performance to young Americans. When more neutral, spatially based tasks were used pattern comparison for speed of processing and backward Corsi blocks for working memory , young and old participants were matched, providing good evidence for equivalence in ability Fig.
When conducting studies of culture differences in cognition, it is very helpful to demonstrate that the groups selected for study are matched in basic component cognitive abilities like speed of processing and working memory Park et al. The Hedden et al. Cross-culture measures of verbal and visuospatial versions of speed of processing and working memory across the life span. Cultural equivalent performances were observed on the visuospatial measures of both working memory and speed of processing for either age group. However, the numerically based measure of both working memory and speed of processing show evidence of cultural and linguistic biases adapted from Hedden et al.
The third issue to consider when collecting neuroimaging data between cultures is the potential hazards that exist if one is collecting data from two different MRI machines, with each instrument associated with a particular culture. We have conducted some large cross cultural structural and functional imaging studies between Singapore and the United States, with both groups having identical imaging hardware and software. There was little data reported on between-scanner variability, and we wanted to be certain differences we observed between groups were due to culture differences rather than signal differences between imaging hardware.
To assess this issue, we collected functional imaging data with a visual and motor task from 4 participants who were repeatedly imaged in identical 3-Tesla MRI machines both in Singapore and the United States, with two sessions at each site Sutton et al. Data showed that there was minimal variance in BOLD signal as a function of site and that between-subject differences accounted for 10 times more variance than did site of data collection.
Task variables motor vs.
We also routinely conducted a phantom scan before testing participants to evaluate noise and stability of the two scanners and reported results to be sure the two magnets were similarly calibrated. The data provided assurance that reported differences between cultures were not due to differing signal properties of the MRI machines between two sites. There is clear evidence that cultural values and experiences shape neurocognitive processes and influence patterns of neural activation and may even effect neural structures.
An important direction for cognitive neuroscience of culture will be to develop broader frameworks that go beyond East Asian and Western cultures and to consistently consider the possibility that observed effects may not be determined by cultural values or experiences but may instead result from differences in diet, health, and even genetics. The focus on quantifying degree of identification with cultural values and its relationship to brain structure and function is important, as it provides validation that cultural values are controlling effects, in light of the many other sources of variance between different cultures.
There is a clear need for multimodal imaging—the integration of structural differences with functional data, as well as an understanding of neural activations that occur when eye movement differences are found. The developmental trajectory of cultural differences also seems like an extraordinarily important domain that is relatively unexplored. How early in the life span do cultural values sculpt the brain? Declaration of Conflicting Interests. The authors declared that they had no conflicts of interest with respect to their authorship or the publication of this article.
National Center for Biotechnology Information , U. Author manuscript; available in PMC Aug 1. Park 1 and Chih-Mao Huang 1, 2. Author information Copyright and License information Disclaimer. The publisher's final edited version of this article is available at Perspect Psychol Sci. See other articles in PMC that cite the published article. Abstract There is clear evidence that sustained experiences may affect both brain structure and function. Behavioral Data Demonstrating That Culture Affects Cognition There is a well-developed literature suggesting that stable differences can be observed between East Asians and Westerners with respect to attention, contextual processing, categorization, and reasoning, with evidence that East Asians are more biased to process context, utilize categories less, and rely more on intuitive rather than formal reasoning processes.
Culture Differences in Eye Fixations for Complex Visual Stimuli The culture and cognition framework discussed thus far would predict that East Asians should be more likely to fixate on contextual information than Westerners and that Westerners should tend to fixate more on central objects. Neural Function and Culture The literature on functional differences in activation patterns associated with culture is better developed than the structural literature.
Open in a separate window. Structural Differences in Brains Between Cultures There is a small literature that has developed that examines the possibility that structural differences exist between East Asian and Western brains. Methodological Considerations Associated With Neuroimaging Culture Differences The study of cultural differences in neurocognitive function is fraught with potential confounds and hazards that cloud interpretation of the data. Conclusion and New Directions There is clear evidence that cultural values and experiences shape neurocognitive processes and influence patterns of neural activation and may even effect neural structures.
Footnotes Reprints and permission: Culture shapes how we look at faces. Cultural differences in allocation of attention in visual information processing. Journal of Cross-Cultural Psychology. Training-induced brain structure changes in the elderly. Age-related changes in object processing and contextual binding revealed using fMR adaptation. Journal of Cognitive Neuroscience. Brain structure in young and old East Asians and Westerners: Comparisons of structural volume and cortical thickness.
Recall and articulation of English and Chinese words by Chinese-English bilinguals. Recall and articulation of English and Chinese words under memory preload conditions. Neural basis of individualistic and collectivistic views of self. Cultural specificity in amygdala response to fear faces. A cross-cultural comparison of cognitive styles in Chinese and American children. International Journal of Psychology.
Cultural variation in eye movements during scene perception. Source memory, aging and culture. Hippocampal system and declarative relational memory: Summarizing the data from functional neuroimaging studies. Changes in grey matter induced by training. Viewpoint-specific scene representations in human parahippocampal cortex. Age and culture modulate object processing and object-scene binding in the ventral visual area. Culture sculpts the perceptual brain. Progress in Brain Research.
Cortical areas involved in object, background, and object-background processing revealed with functional magnetic resonance adaptation. Culture modulates eye-movements to visual novelty. Exploring cross-linguistic vocabulary effects on brain structures using voxel-based morphometry.
Cultural differences in neural function associated with object processing. Categorical organization in free recall across culture and age.
Culture-sensitive neural substrates of human cognition: A transcultural neuroimaging approach. Cultural influences on neural substrates of attentional control. Cultural variation in verbal versus spatial neuropsychological function across the life span. Cultural confusions show that facial expressions are not universal. Cultural differences in the lateral occipital complex while viewing incongruent scenes. Social Cognitive and Affective Neuroscience. Is it culture or is it language? This book provides an interdisciplinary overview of what we currently know about the neural basis of human belief systems, and how different belief systems are implemented in the human brain.
The chapters in this volume explain how the neural correlates of beliefs mediate a range of explicit and implicit behaviours ranging from moral decision making, to the practice of religion.
Drawing inferences from philosophy, psychology, psychiatry, religion, and cognitive neuroscience, the book has important implications for understanding how different belief systems are implemented in the human brain, and outlines the directions which research on the cognitive neuroscience of beliefs should take in the future. Allow this favorite library to be seen by others Keep this favorite library private. Find a copy in the library Finding libraries that hold this item Frank Krueger ; Jordan Grafman Find more information about: Frank Krueger Jordan Grafman. Reviews User-contributed reviews Add a review and share your thoughts with other readers.
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