Central Executive System

The central executive system directs working memory and is responsible for focusing and shifting attention (Engle & Kane, 2003;

From: Psychology of Learning and Motivation, 2022

Cognitive Theories of Consciousness

V. de Gardelle, S. Kouider, in Encyclopedia of Consciousness, 2009

Attention and the Central Executive

Various influential models developed in the 1960s referred to a central processor, a central executive system, or a supervisory system. Processing within the central system can be considered as analogous to conscious processing, even if the word consciousness was still largely banished in the scientific community. This system is at the top of the hierarchy in the cognitive architecture: it is involved in higher-order computations (decision, monitoring, planning, etc.) and leads to selection and control over lower-level subsystems. As in many contemporary accounts of consciousness, the central system was considered the most integrative element of the cognitive system, granting flexibility and control over behavior.

Another key element was the simple but powerful metaphor of attention as a filtering mechanism that was put forward by Broadbent. In a nutshell, peripheral processors in this theory provide sensory information to the central system dealing with control and decisions. Because multiple sensory channels are continuously acting in parallel, a huge quantity of information becomes available to the rest of the system. However, the central system is very limited in terms of computational resources. Hence, a selection mechanism is needed to prevent overload. As such, attention operates by selecting the most relevant information and by filtering out that which is irrelevant. Then, the most relevant information, which is under the focus of attention, becomes the target of the central system and can thus benefit from deeper and more enriched processing. Once again, although consciousness was not the main concern, one consequence of attentional selection was that it allowed the target information to become conscious. In this perspective, attention and consciousness are two tightly related notions.

The notion of short-term memory put forward by George Miller and later extended to the notion of working memory is also an important precursor. For example, in their model of working memory, Baddeley and Hitch relied on a central executive system, which has top-down control over the distinct specific subsystems, namely the phonological loop and the visuospatial sketchpad. Here, the content of working memory may be roughly equated with the content of consciousness, an aspect that will also be important for future cognitive theories of consciousness.

Norman and Shallice, in turn, proposed a model of action selection implicating a supervisory attentional system. This central system receives sensory evidence and determines the appropriate behavior by selecting instruction schemes for action mechanisms. In addition, the supervisory attentional system can be modulated by the goals of the organism, and it is primarily involved when a new or critical situation appears. Here too, the central part of the model shares some properties that are associated with consciousness, namely flexibility, reactivity regarding unexpected situations, decision, and control over behavior.

In sum, these influential early models depicted the global architecture of the cognitive system by emphasizing the following components: sensory inputs in the periphery that are processed in parallel in multiple channels, attention that performs selection upon these sources of information, a working memory component that keeps tracks of the selected information, and finally a central system that acts as a supervisor. But one major limitation of this view is that it falls into the homunculus trap, when it comes to the question of consciousness. Indeed, if this central supervisor is governing the whole cognitive system, one may ask who is in turn governing the central supervisor! That is, if we were to rephrase this question by focusing on consciousness, it would be problematic to rely on a hypothetical little man in our head (i.e., a homunculus) that has consciousness, which is the same property we are supposed to explain. This approach unavoidably leads to an infinite regression. Because consciousness was not the main issue for these early models, this crucial issue was left out or even denied during the development of early cognitive models with a central supervisor. As we will see below, current theories of consciousness will overcome this limitation by proposing various cognitive architectures, sometimes including a central system, that take into account the homunculus issue.

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Intelligence, Working Memory, and Learning Disabilities

H. Lee Swanson, in Cognition, Intelligence, and Achievement, 2015

Theoretical Framework

The framework we used to capture WM performance as it applies to reading and math proficiency is Baddeley’s multicomponent model (1986, 1996, 2000, 2007, 2012). Baddeley (2012; Baddeley & Logie, 1999) described WM as a limited central-executive system that interacts with a set of two passive storage systems used for temporary storage of different classes of information: the speech-based phonological loop and the visual sketchpad. The phonological loop is responsible for the temporary storage of verbal information; items are held within a phonological store of limited duration, and the items are maintained within the store via the process of articulation. The visual sketchpad is responsible for the storage of visual-spatial information over brief periods and plays a key role in the generation and manipulation of mental images. Both storage systems are in direct contact with the central executive system. The central executive system is considered to be primarily responsible for coordinating activity within the cognitive system, but also devotes some of its resources to increasing the amount of information that can be held in the two subsystems (Baddeley & Logie, 1999). A recent formulation of the model (Baddeley, 2000, 2012) also includes a temporary multimodal storage component called the episodic buffer. Although the multicomponent model of Baddeley was primarily developed from research on adult samples, the model also has an excellent fit to the WM performance of children (Alloway, Gathercole, Willis, & Adams, 2004; Swanson, 1999a, 2008, 2011a).

We next briefly review some of our findings related to the components of WM and their influence on children with specific LD in reading or math.

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Learning and Memory, Neural Basis of

H.J. Markowitsch, in International Encyclopedia of the Social & Behavioral Sciences, 2001

3.1 Short-term and Working Memory

The concept of working memory derived from the earlier one of short-term (and long-term) memories. While, however, short-term memory is seen as the on-line holding of information for an initial time period after first confrontation with it, working memory refers to a multicomponent, active processing of information which also includes the transmission of already long-term stored information in a temporary buffer prior to retrieval, and which is composed of a controlling central executive system and a number of subsidiary slave systems (Baddeley 2000).

Numerous experiments using monkeys, cats, and rats have reported that bilateral damage to the prefrontal cortex interferes with the short-term storage of information and that single units in this region display working memory related neuronal firing (Goldman-Rakic et al. 2000, see also Working Memory, Neural Basis of). Results from evoked-potential recordings and functional imaging studies have confirmed the dominant role of prefrontal regions for working memory in the human brain. Some reports found that damage to parietal regions impairs the on-line processing of information. Consequently, a frontoparietal network is seen as engaged in the control of attention and in processes of on-line working with memory.

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Learning Disabilities and Memory

H. Lee Swanson, Danielle Stomel, in Learning About Learning Disabilities (Fourth Edition), 2012

Working Memory

Current perspectives on the study of memory in learning disabled samples focus on working memory. Working memory has been applied to poor performance in such academic areas as reading comprehension (e.g., Carretti, Borella, Cornoldi, & De Beni, 2009; De Jong, 1998; Savage, Lavers & Pilly, 2007; Swanson, 1999b), math (Berg, 2008; Geary, Hoard, Bryd-Craven, Nugent, & Numtee, 2007; Swanson & Beebe-Frankenberger, 2004), and writing (Richards et al., 2009; Swanson & Berninger, 1996), as well as general educational attainment (Gathercole, Durling, Evans, Jeffcock, & Stone, 2008; Gathercole, Pickering, Knight, & Stegman, 2004). More recent work has focused on the relationship between working memory and reading disabilities in English language learners (e.g., Swanson, Orosco, Lussier, Gerber, & Guzman-Orth, 2011; Swanson, Sáez, & Gerber, 2006).

The most popular framework used to describe working memory is Baddeley’s multi-component model (1986, 1996, 2000, 2007). Baddeley (1986; Baddeley & Logie, 1999) describes WM as a limited central-executive system that interacts with a set of two passive storage systems used for temporary storage of different classes of information: the speech-based phonological loop and the visual sketchpad. The phonological loop is responsible for the temporary storage of verbal information; items are held within a phonological store of limited duration, and the items are maintained within the store via the process of articulation. The visual sketchpad is responsible for the storage of visual-spatial information over brief periods and plays a key role in the generation and manipulation of mental images. Both storage systems are in direct contact with the central executive system. The central executive system is considered to be primarily responsible for coordinating activity within the cognitive system, but also devotes some of its resources to increasing the amount of information that can be held in the two subsystems (Baddeley & Logie, 1999). A recent formulation of the model (Baddeley, 2000) also includes a temporary multimodal storage component called the episodic buffer. However, the three factor structure has an excellent fit to the WM performance of children (Alloway et al., 2004; Gathercole, Pickering, Ambridge, & Wearing, 2004; Swanson, 2008).

There are correlates in the neuropsychological literature that complement the tripartite structure, suggesting that some functional independence exists among the systems (e.g., Jonides, 2000; Ruchkin, Berndt, Johnson, Grafman, Rotter, & Canoune, 1999). Functional magnetic resonance imaging (fMRI) studies suggest separate neural circuitry for the storage and rehearsal components of both the phonological and the visual-spatial system, with phonological system activity mainly located in the left hemisphere and visual-spatial system activity located primarily in the right hemisphere (Smith & Jonides, 1997). Executive control processes, on the other hand, are associated primarily with the prefrontal cortex (e.g., Reichle, Carpenter, & Just, 2000; Smith & Jonides, 1999). Neuropsychological evidence also suggests that children with LD in the areas of reading (RD) and/or math (MD) experience difficulties related to these structures. Based on the type of task, of course, studies suggest that children with RD have processing difficulties related to regions of the frontal lobe (e.g., Lazar & Frank, 1998), left parietal lobe (e.g., Pugh et al., 2000; Shaywitz et al., 1998), as well as problems related to the interhemispheric transfer and coordination of information across the corpus callosum (e.g., Swanson & Mullen, 1983; Swanson & Obrzut, 1985). Likewise, a casual review of the literature shows that MD has been associated with the left basal ganglia, thalamus, and the left parieto-occipito-temporal areas (e.g., Dehaene & Cohen, 1995, 1997). Damage to these regions may be associated with difficulties in accessing number facts. Clearly, the biological correlates of the various subcomponents in WM in RD and/or MD samples are just beginning to be identified with advances in technology.

How does this WM formulation help us understand LD better than the concept of STM? First, it suggests that strategies play a smaller role in learning and memory than previously thought. This is an important point because some studies do show that performance deficits of children with LD are not related to rehearsal, per se (e.g., Swanson, 1983a,b). Second, the idea of a WM system is useful because it is viewed as an active memory system directed by a central executive. This is important because the central executive can become a focus of instruction and influence on academic performance. Finally, and most importantly, WM processes are highly related to achievement (e.g., Daneman & Merikle, 1996), whereas with STM less so (Daneman & Carpenter, 1980).

We will briefly review the psychological evidence on those components of WM that underlie LD (however also see Swanson & Siegel, 2001a,b, for an earlier review).

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Adolescent executive function development

Sammy F. Ahmed, ... Natasha Chaku, in Reference Module in Neuroscience and Biobehavioral Psychology, 2023

Theories of executive function development

Before the term “executive function” debuted in the neuropsychological literature, several theoretical frameworks had already been put forward to explain the mechanisms underlying the cognitive control of behavior. For example, in their influential model of working memory, Baddeley and Hitch (1974) proposed a “central executive system” that was responsible for the control and regulation of lower-level cognitive processes, such as focusing attention, suppressing irrelevant information, and inhibiting inappropriate actions. Similarly, Norman and Shallice's (1986) model of attentional control included a “supervisory attentional system” that was integral for the purposes of planning, problem-solving, and navigating novel situations. In each of these theoretical accounts, neither the “central executive system” nor the “supervisory attentional system” was thought to contain any distinct subprocesses. As such, in the early stages of theoretical development, what would later be termed “executive function” was primarily thought of as a unitary construct.

Over time, however, accumulating evidence led some to begin questioning the conceptualization of EF as a wholly unitary construct. Researchers began noticing distinguishable performance differences on tasks that were created to measure the construct of EF. For example, some individuals could successfully complete Task A but would perform poorly on Task B, while others demonstrated the opposite pattern of performance (e.g., Shallice, 1988). Similarly, low intercorrelations between EF tasks became a routine observation, leading some to wonder if EF might not be a unitary construct after all, and instead, may be comprised of separable components or subprocesses (Alexander and Stuss, 2000; Welsh and Pennington, 1988). An influential study by Miyake et al. (2000) proposed and empirically tested an alternative theoretical framework that integrated these opposing perspectives, suggesting that EF consisted of distinct but interrelated component processes with an underlying common mechanism, which they described as the “unity and diversity of EF.” To test this model, the authors conducted confirmatory factor analysis (CFA) on a range of commonly used EF measures that were administered to young adults, extracting three separate but correlated latent factors representing the core components of EF: inhibition (deliberately overriding dominant or prepotent responses), updating (holding information in storage (working memory) while performing mental manipulations), and shifting (switching attention flexibly between tasks or mental sets; Miyake et al., 2000).

Over the past two decades, researchers have aimed to replicate these findings. Many have observed results consistent with the “unity and diversity” model proposed by Miyake and colleagues across various stages of development, highlighting the stability of EF from at least adolescence through adulthood (Best and Miller, 2010; Lee et al., 2013; but see Karr et al., 2018). The “unity and diversity” model has also been expanded upon to incorporate links between the three core components of EF and higher-order cognitive processes and emotion regulation (e.g., Chaku et al., 2021). Diamond (2013), for example, proposed that the core, or “foundational,” EF components work in tandem to promote more complex self-regulation skills such as planning, problem-solving, and reasoning. Zelazo and colleagues proposed an alternative theoretical model whereby EF skills vary along an affective continuum ranging from “hot” to “cool” EF (Zelazo and Carlson, 2012; Zelazo and Müller, 2002). In this account, cool EF is made up of skills that are activated during emotionally neutral conditions, including inhibition, updating, and shifting. Hot EF, on the other hand, reflects skills that are utilized in motivationally significant contexts that require the integration of cool EF skills such as inhibition with emotion regulation. Although subsequent factor analytic studies have revealed that hot and cool EF are somewhat dissociable (e.g., Montroy et al., 2019; Willoughby et al., 2011), they generally work jointly to promote adaptive functioning (Zelazo, 2020).

In recent years, complementary theoretical models have been proposed that center on children's experiences and culture to conceptualize and understand EF development (see Zelazo and Carlson, 2023; Doebel, 2020; Munakata and Michaelson, 2021, for review). To varying degrees, these frameworks assert that EF develops and is employed within personal, social, cultural, and historical contexts. Thus, EF may be more appropriately understood as a general capacity for cognitive control in service of goal-oriented behavior rather than a set of dissociable skills that can be measured in lab contexts. In these theories, contextual factors that shape children's knowledge, beliefs, and values cannot be separated from EF itself, and are critical for understanding EF development across the lifespan (Doebel, 2020).

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Executive System and Cognitive Control

Juri D. Kropotov, in Functional Neuromarkers for Psychiatry, 2016

Models of cognitive control

There are many models of the cognitive/executive/attentional control operations. They are defined by the author’s personal experience and the corresponding perspective from which the operations are viewed. A few models are presented to illustrate this statement.

Baddeley’s model has been derived from psychological perspective in 1974 (Baddeley & Hitch, 1974) and revised by Alan Baddeley from University of Cambridge in 2012. According to the revised model a central executive system regulates three other subsystems: the phonological loop, which maintains verbal information; the visuospatial sketchpad, which maintains visual and spatial information; and episodic buffer, which integrates short- and long-term memory, holding and manipulating a limited amount of information from multiple domains in temporal and spatially sequenced episodes.

Barkley’s model was suggested by Russel Barkley from Medical University of South Carolina on the basis of his studies of behavioral control impairment in ADHD population and considered the cognitive control from perspective of self-regulation. This model published in 1997 in the book ADHD and the Nature of Self-control divides executive functions into three main elements. One element is working memory that resists interfering information. A second component is the management of emotional responses in order to achieve goal-directed behaviors. A third component is internalization of self-directed speech for control rule-governed behavior and for generating plans for problem-solving. The last component includes analysis and synthesis of information into new behavioral responses to meet the goals. Changing one’s behavioral response to meet a new goal or modify an objective is a higher level skill that requires a fusion of executive functions including self-regulation, and accessing prior knowledge and experiences.

Miller and Cohen’s model was suggested by Earl Miller from Massachusetts Institute of Technology and Jonathan Cohen from Princeton University in 2001. They argue that cognitive control is the primary function of the prefrontal cortex (PFC), and that control is implemented by increasing the gain of sensory or motor neurons that are engaged by task- or goal-relevant elements of the external environment. The aggregate effect of these bias signals is to guide the flow of neural activity along the pathways that establish the proper mappings between inputs, internal states, and outputs needed to perform a given task. According to this theory the selective attention mechanism is in fact just a special case of cognitive control–one in which the biasing occurs in the sensory domain.

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Short-Term Memory

Rosaleen A. McCarthy, Elizabeth K. Warrington, in Cognitive Neuropsychology, 1990

Working Memory

Baddeley and his colleagues have developed a model in which the ability to hold verbal material verbatim plays an important role in problem solving (e.g., Baddeley, 1986). The working-memory model consists of three major components: the “articulatory loop,” the “visuospatial sketchpad” (or “scratch pad,” see above), and the “central executive.” Performance on auditory-verbal span tasks requires the operation of this articulatory loop under the directing control of the central executive system. The articulatory loop is held to consist of two main components, a phonological storage system and a rehearsal loop (Baddeley, 1986; see Fig. 13.5). In the terms of this model, at least some patients with a selective impairment of auditory-verbal span can be thought of as having a deficit in the phonological store and/or the rehearsal loop (Vallar & Baddeley, 1984b).

Figure 13.5. Baddley's model of “working memory” showing the relationship between the “articulatory loop,” “visuospatial scratchpad,” and “central executive.” (Baddeley, 1986.)

In normal people, verbal problem solving is also thought to make use of the temporary storage capacities of the “articulatory loop.” Evidence in favour of this position is derived from tasks in which subjects are required to perform visually presented arithmetic or reasoning tests whilst simultaneously holding spoken lists in memory. Under these “concurrent task” conditions performance deteriorates and subjects become slower and make more errors (Baddeley & Hitch, 1974).

If the temporary storage of verbatim information is necessary for verbal problem solving, then patients with selective impairments of span should be disproportionately impaired on tests such as mental arithmetic. It is fair to say that the majority of patients with an impaired digit span have shown weak performance on graded-difficulty arithmetic tests. However, the presentation of these tasks is typically spoken and therefore places considerable demands on retention in addition to problem-solving operations. Despite these demands, some cases are on record with arithmetic scores within the normal range (Warrington et al., 1971; McCarthy & Warrington, 1984). Furthermore, in (the possibly more demanding) conditions of everyday life, patients may be entirely capable of dealing with verbal “problems” routinely. For example, patients may be capable of holding down demanding jobs, including working as a senior secretary or running a business (e.g., Warrington et al., 1971; Basso et al., 1982). Impaired span clearly does not necessarily compromise the patient's ability to perform verbal reasoning operations themselves. However, it may be still be critical for those very specific types of problem solving that require the maintenance of an exact verbatim record of the spoken input (see below).

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Executive Functions After Traumatic Brain Injury

Irene Cristofori, Jordan Grafman, in Executive Functions in Health and Disease, 2017

Working Memory

Working memory is used to hold information online during the execution of other cognitive functions. According to the Baddeley and Hitch model (Baddeley & Hitch, 1974), working memory consists of two subsystems and a central executive. The two subsystems are the visual spatial sketchpad and the phonological loop, storing and processing, temporarily, visual and verbal information. The central executive is responsible for distributing resources between the visual spatial sketchpad and the phonological loop. The central executive system has limited capacity; therefore, tasks requiring multitasking can be challenging (Baddeley & Hitch, 1974).

Only a few studies have examined working memory after TBI. Perlstein et al. (2004) studied parametric modulation of the working memory load on the n-back task in mild, moderate, and severe TBI patients (Perlstein et al., 2004). During the n-back task, a series of stimuli is presented and subjects have to indicate if the current stimulus matches one that appeared earlier in the series. An increase in n increases working memory load, making the task more demanding. Because a decision needs to be made after each stimulus, the n-back task requires a continuous online updating of information in working memory. The findings of this study showed that compared to mild TBI patients and healthy controls, moderate and severe TBI patients made more errors when challenged with a greater working memory load (e.g., 2- and 3-back). In the same study, functional magnetic resonance imaging (fMRI) revealed that an increased working memory load corresponded to an increase in brain activity in both TBI and controls. However, moderate and severe TBI patients showed increased activity in the dorsolateral prefrontal cortex (dlPFC) and Broca’s areas as an effect of increased working memory load. Their selective impairment at higher loads on the n-back task suggests that moderate and severe TBI patients have specific deficits in coding and maintaining sequential information.

More recently, Sanchez-Carrion et al. (2008) performed a longitudinal study on working memory impairments after TBI. In this study, the authors examined brain activation during an n-back task, while TBI patients underwent fMRI in two separate sessions at 6-month intervals. Over time, TBI patients exhibited changes in brain activation. During the first evaluation, both groups showed bilateral frontoparietal region activation during the n-back task. Activation in the right superior frontal gyrus was lower in the TBI group compared to controls. Remarkably, the neural and behavioral differences between the TBI and matched controls were reduced after 6 months. Indeed, at 6 months after the first evaluation, TBI patients showed increased activation in the right superior frontal cortex and improved performance on the n-back task (Sanchez-Carrion et al., 2008). More longitudinal studies are needed because they provide key evidence of progressive recovery of EF after brain injury.

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The Role of Working Memory in Language and Communication Disorders

Martial Van der Linden, Martine Poncelet, in Handbook of Neurolinguistics, 1998

19-1.2 Central Executive and Language Comprehension

The work of Daneman and Carpenter (1980) strongly contributed to the view that comprehension of language places demands on working memory considered as a limited pool of general-purpose resources that can be used to serve both processing and storage of information. This conception of working memory appears to correspond rather closely to the central executive component in Baddeley’s (1986) working memory model.

According to Daneman and Carpenter (1980), limitations on cognitive resources can account for many types of individual differences and processing strategies in language comprehension (see Carpenter, Miyake, & Just, 1995). Similarly, it could be argued that a deficit affecting the central executive system should impair language comprehension. However, a major difficulty in the exploration of the relations between language deficits and the central executive system is that a wide range of cognitive abilities have been ascribed to the executive system: control, processing, and even storage activities. Another problem is to find a way to specifically explore the central executive system without confounding its function with that of the slave systems.

Research conducted by Morris (see Morris, 1994) and Baddeley et al. (1986) provided some criteria indicating the existence of a specific central executive deficit (see also Van der Linden et al., 1992). Patients with an impaired central executive should show a mild reduction of span, normal effects of phonological similarity and normal length effects on span (indicating the integrity of the phonological store and the articulatory rehearsal process), and impaired performance on dual tasks.

19-1.2.1 Alzheimer’s Disease and Language Comprehension

On the basis of these criteria, several studies suggest that patients with Alzheimer’s disease (AD patients) have impairments of the central executive component of working memory (see Morris, 1994). More specifically, it appeared that AD patients showed a deficit affecting one important component of the central executive, that is, the capacity to coordinate two or more subprocesses (Baddeley et al., 1986). Waters, Caplan, and Rochon (1995) explored the relationships between processing capacity and sentence comprehension in AD patients. Patients were administered a sentence-picture-matching task. The to-be-interpreted sentences differed in syntactic complexity and number of propositions. Subjects were tested on this task, on the one hand, with no concurrent task and, on the other hand, while concurrently remembering a digit load that was one less than their span or equivalent to their span. The AD patients met Morris’s (1994) and Baddeley et al.’s (1986) criteria indicating the existence of a central executive impairment. The results show an interaction between subject group and size of the digit load in the digit recall measurement, which indicates that the performance of AD patients was more affected by dual-task conditions than that of the controls. This is consistent with the view that AD patients have a reduced capacity of the central executive system. However, the patients were not disproportionately impaired on the sentence types that were syntactically more complex. The authors interpret this absence of dual-task effect in AD patients by postulating the existence of different processing resource pools for different types of verbal operations. More specifically, they argue that AD patients showed a reduction in central processing resources but that this reduction did not affect the availability of resources involved in syntactic processing. In addition, the results show that the patients performed more poorly on sentences with two propositions than did the controls, and more poorly on sentences with two propositions than on sentences with one proposition. The authors interpret this disproportionate “proposition” effect by suggesting that the patients have a deficit affecting postinterpretative processing (as opposed to assignment of sentence meaning itself), and more specifically the cognitive processes involved in matching propositional content to a picture. Finally, although the AD patients showed a decrement in dual-task performance, they did not show a disproportionate decrease of performance on two-proposition sentences compared to one-proposition sentences, under digit load conditions, compared to controls. This pattern of results cannot be explained by a reduction of processing resources since such a reduction should have led to a three-way interaction between size of digit load, sentence type, and group, which was not observed. According to Waters et al. (1995), the results could be interpreted by postulating that AD patients have impairments in a control mechanism that shifts attention between tasks and this control deficit could lead to a decline in performance under dual-task conditions, without this decline being greater for more demanding sentences. This study clearly suggests that the investigation of the central executive’s role in sentence comprehension requires a precise specification of the resource pools and of the resource allocation. Waters et al.’s (1995) study also indicates that different aspects of the central executive system may be affected, for example, the processing capacity or the control component (flexibility), with different consequences on performance.

19-1.2.2 Language Comprehension in Aphasic Patients

Miyake, Carpenter, and Just (1994) argued that comprehension breakdown in aphasic patients may be attributed to a severe reduction of a general-purpose verbal working memory system. This proposition was based on results issued from two sentence comprehension experiments using rapid serial visual presentation in normal subjects, which they consider simulate important features of aphasic patients’ comprehension of syntactic structures. However, this view has been challenged by Caplan and Waters (1995) and Martin (1995). These authors point out that a theory hypothesizing damage to separable components more easily accommodates findings of double dissociations in aphasic patients’ performance on different sentence types, and that Miyake et al.’s (1994) results may also be accounted for by a theory that assumes separable processing resource systems involved in language comprehension and other verbal tasks.

19-1.2.3 Aging and Language Comprehension

Finally, a large body of research also suggests that language performance differences (for example, in the comprehension of and memory for discourse) between young and old adults are due to age-associated differences in working memory capacity (see Hupet & Nef, 1994). However, other studies indicate that speed of processing and inhibitory efficiency might be more fundamental factors than working memory (e.g., Kwong See & Ryan, 1995). In this perspective, Hasher, Zacks, and their colleagues have conducted a series of studies showing that age differences in the inhibition of irrelevant internal thoughts and external stimuli underlie age difference in language performance (see Zacks & Hasher, 1994). In fact, they argue that people with inefficient inhibitory mechanisms will allow information that is off the goal path to enter into working memory. For example, older adults have been found to be less likely than young subjects to inhibit initial inferences subsequently made untenable by text context. More generally, differential ability to inhibit information has been proposed as an alternative to resource theories in interpretations of developmental and individual differences (see Dempster & Brainerd, 1995). Most of these inhibition theories seem to consider inhibition as a passive, automatic event. However, recent findings suggest that inhibition is (at least partly) a product of controlled resources and that group differences in inhibition may result from differences in controlled attentional resources, and not from inefficient inhibitory processes (Engle, Conway, Tuholski, & Shisler, 1995). This view is consistent with the idea of a central executive as being a general attentional system, whose function would be the inhibition of irrelevant information as well as activation and maintenance of information relevant to the task.

In summary, there exists some evidence relating central executive dysfunctioning to language comprehension deficits. However, the central executive is certainly not a unitary system and, as a consequence, it could be damaged in different ways. In that perspective, future research should be conducted to explore the comprehension abilities of patients with different types of central executive disorders.

Language comprehension certainly is the domain of language activities in which the role of working memory has been the most extensively explored from a neuropsychological point of view. In the last part of this chapter, we will examine, more briefly, whether neuropsychological data also suggest a contribution of working memory to other types of language deficits.

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The Parietal Lobe

Vassilios N. Christopoulos, ... Richard A. Andersen, in Handbook of Clinical Neurology, 2018

Decision making as a distinct and separate cognitive process from action planning

Imagine that you are faced with the challenge of buying a new house. Different houses may vary in their price, size, location, amenities, number of rooms, distance from work, and more. How the brain integrates information from these disparate sources to evaluate the houses and select the best option remains a central question in neuroscience. Classic studies suggest that individuals first decide which house to buy, and then plan the actions to implement the choice (Tversky and Kahneman, 1981; Padoa-Schioppa and Assad, 2006; Padoa-Schioppa, 2011) (Fig. 8.2). According to this view, there is a central executive system in the brain that integrates all of the relevant factors of the house (price, size, etc.) into a subjective economic value. Decisions are made by comparing the subjective values of the available options. Only when a decision is made is the chosen option transformed into an action plan to implement the choice (goods-to-action transformation). Hence, the central axiom in this sequential theory is that the representation of the subjective value is abstract, in the sense that it does not depend on the sensorimotor contingencies of the choice; that is, the action required to implement the choice outcome. For instance, selecting house A over house B does not depend on whether you will drive or walk to the realtor after deciding which house to buy.

Fig. 8.2

Fig. 8.2. Sequential theory of decision making in a hypothetic scenario of choosing between two houses. According to this theory, decision and action are two separate cognitive processes. The brain first integrates the decision factors of the alternative options (e.g., prize, size, amenities) into a single variable named subjective value. Subjective values are computed independently of one another, and without taking into account the sensorimotor contingencies of the choices (goods-space). The decision is made by comparing the subjective values within the goods-space. Once decided, the chosen option is transformed into an action plan to implement the choice (goods-to-action transformation in action-space).

Since the famous case of Phineas Gage – the railroad construction foreman who survived severe damage to the brain after an iron bar pierced his left frontal lobe – clinical studies have pointed out that the central executive control system, in which decisions are made, resides in the prefrontal cortex (PFC) (Shallice and Burgess, 1991; Bechara et al., 1994; Fellows, 2006). However, it was only recently that neuroscientists started revealing the functional role of PFC in decision making. Neurophysiologic studies in animals showed that orbitofrontal cortex (OFC) and ventromedial PFC (vmPFC) neurons encode the abstract representation of the subjective values of the choice alternatives (for review, see Kennerley and Walton, 2011).

For instance, a recent study in NHPs showed that neurons in the OFC encode the subjective value of the reward being offered independently of the spatial configuration and the motor actions (Padoa-Schioppa and Assad, 2006). Along similar lines, other studies showed that OFC neurons integrate information from disparate sources, such as reward magnitude, outcome probability, and physical effort to obtain the reward into subjective economic values (Kennerley and Wallis, 2009). Additionally, a recent study reported that vmPFC neurons encode the subjective incentive value of an option, which is integrated with the action cost in anterior cingulate cortex, to compute an overall value for each alternative option (Bouret and Richmond, 2010).

The role of the prefrontal cortical regions in computing and comparing the subjective values for each choice in economic decisions has also been confirmed by human functional imaging. For instance, recent studies explored the tradeoffs between monetary reward and other decision-related factors, such as outcome probability (Levy et al., 2010), ambiguity (Hsu et al., 2005), time delay (Kable and Glimcher, 2007), and food type (Plassmann et al., 2007). Consistent with the neurophysiologic studies, activity in OFC was significantly correlated with the subjective values of the alternative options. Overall, these findings indicate that economic decisions emerge via a comparison of the abstract representation of the alternative options that takes place within the PFC.

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URL: https://www.sciencedirect.com/science/article/pii/B9780444636225000085