School Induced ADHD: Is It Possible?
A Presentation for Professionals in the Fields of Medicine, Mental Health, and Education
(Note from Birth To Success, LLC --
The concepts and language used in this section are not intended for the casual reader looking to learn a
little more about ADHD. The thesis is proposed to encourage professionals involved with serving students
with ADHD to consider the extent to which school demands may contribute to the clinical presentation of
ADHD in children. It is likely to seem overwhelming to those who are not already familiar with the concepts
discussed.
Parents may wish to refer to our other discussions of ADHD to find answers to their more practical
questions regarding ADHD.)
Abstract
When the clinical picture of attention-deficit/hyperactivity disorder appears after a child enters school, the
underlying etiology may be a multi-faceted system failure induced by adverse educational conditions
rather than a pre-existing medical disorder. This paradigm asserts that the degree of "attention deficit"
experienced by a student varies as a result of at least three specific factors: (a) the abilities / skills of the
individual, (b) the demands of a particular circumstance, and (c) the residual capacity of the attention
system. An overview of the relevant literature provides the reader with a basic understanding of AD/HD,
automaticity, and learned helplessness and highlights their contributions to the emergence of inattention,
behavioral disinhibition, and chronic school failure in children and adolescents. (133 refs.)
School-induced AD/HD: Is it possible?
For professionals involved in the diagnosis and management of children with attention-deficit/hyperactivity
disorder (AD/HD), often the most refractory aspect of intervention is the persistence of academic failure.
Despite repeated adjustments in their prescribed doses of stimulant medication, many children with AD/HD
continue to be inattentive during class lectures, off-task during reading activities, unsuccessful at
completing class work and homework, and unprepared for classroom discussions or testing. Time and
again, blame eventually will be ascribed to the students' lack of effort and motivation.
The possibility that the offending behaviors might be a consequence of an induced attention deficit rather
than (or in addition to) the manifestation of a primary attention deficit disorder often may not be given
adequate consideration. Functional impairments (e.g., deficits in vision, hearing, phonemic awareness,
and graphomotor skills) frequently may be overlooked in students with AD/HD; yet such difficulties can
potentially place excessive demands on limited attention, working memory, and executive function
resources causing attention deficits to be manifest within the classroom setting.
The current article proposes that the attention-deficit/hyperactivity syndrome that appears after a child
enters school might represent the manifestations of a multi-faceted system failure fostered by an
inappropriate educational environment rather than the symptoms of a single, discrete medical disorder.
According to this paradigm, the degree of "attention deficit" experienced by a student would vary as a
result of at least three specific factors: (a) the abilities / skills of the individual, (b) the demands of a
particular circumstance, and (c) the residual capacity of the attention system.
To support this assertion, the author first reviews current issues related to the diagnosis of attention-
deficit/hyperactivity disorder. Next, the phenomenon of automaticity is studied and its close relationship to
attention revealed. This article proceeds to explore how dual-task demands and environmental stress may
hijack this relationship, overwhelm attention and working memory, and empower automaticity to run
rampant in the guise of behavioral disinhibition. As progressive academic and behavioral dysfunctions are
encountered within the inescapable confines of a classroom, learned helplessness emerges and the early
signs of school failure begin to appear.
Finally, the issue of academic disabilities in children with AD/HD is addressed. Many children who present
with the symptoms of AD/HD, especially those whose symptoms emerge following their entry into school,
may be confronted by ability-demand mismatches within the traditional classroom setting that harbor the
potential to induce attention deficits. It is asserted that many of these learning difficulties, readily
recognized as below grade level performance in the classroom, may be disregarded due to the
inadequacies inherent in the criteria currently being employed to identify learning disabilities. As a result,
true academic disabilities often may be ignored while professionals unjustly attribute ongoing classroom
dysfunction to a student's lack of effort, poor motivation, or inadequately treated AD/HD.
Defining attention-deficit/hyperactivity disorder
Attention-deficit/hyperactivity disorder (AD/HD) is a heterogeneous disorder of unknown etiology with an
estimated prevalence ranging from 2% to 12% of school-age children (Biederman, Newcorn & Sprich,
1991; American Academy of Pediatrics, 2000). The formal identification of students with AD/HD is based
on criteria published in the American Psychiatric Association's Diagnostic and Statistical Manual of Mental
Disorders, Fourth Edition (DSM-IV, 1994; DSM-IV-TR, 2000). Children meeting the criteria for AD/HD are
typically assigned to one of three descriptive subtypes:
1) AD/HD, Predominantly Inattentive Type (AD/HD-IA). This subtype requires that at least six of the nine
clinical symptoms of inattention be present for a period of at least six months to a degree that is
maladaptive and inconsistent with developmental level. Typical characteristics of inattention include: short
attention span, easy distractibility, carelessness, forgetfulness, failure to finish school work, reluctance to
engage in activities that require sustained mental effort such as schoolwork or homework, a tendency to
lose things, poor organization, and an apparent inability to listen when spoken to directly.
2) AD/HD, Predominantly Hyperactive-Impulsive Type. This subtype requires that six or more symptoms of
hyperactivity-impulsivity be present for a period of at least six months to a degree that is maladaptive and
inconsistent with developmental level. Typical characteristics of hyperactivity-impulsivity include: fidgeting,
leaving one's seat in the classroom, running or climbing excessively, experiencing difficulty playing quietly,
always being "on the go", talking excessively, blurting out answers, having difficulty awaiting one's turn,
and interrupting or intruding on others.
3) AD/HD, Combined Type. This diagnosis is employed when the assessment criteria for both of the
preceding subtypes have been fully met. In this article, AD/HD with symptoms of hyperactivity, including
both the predominantly hyperactive-impulsive type and combined type, will be designated as AD/HD-HI/C.
In addition, the DSM-IV (1994) guidelines require that: (a) some hyperactive-impulsive or inattentive
symptoms that cause impairment must have been present before age 7 years, (b) some impairment from
the symptoms must be present in two or more settings (e.g., at school and home), (c) there must be clear
evidence of clinically significant impairment in social, academic, or occupational functioning, and (d) the
symptoms must not occur exclusively during the course of a pervasive developmental disorder,
schizophrenia, or other psychotic disorder and must not be better accounted for by another mental
disorder (e.g., mood disorder, anxiety disorder, dissociative disorder, or personality disorder).
Individuals who do not fully meet the criteria for one of these three AD/HD subtypes may still be identified
with the disorder when there are prominent symptoms of inattention or hyperactivity-impulsivity present. If
the patient's condition is the result of symptom attenuation over time, a diagnosis of AD/HD, in partial
remission is employed. If full criteria have never been met, a diagnosis of AD/HD, not otherwise specified
(NOS) may be appropriate.
It should be noted that in recent years, the validity of the "age of onset" criterion has been challenged to
permit the recognition of symptoms after the age of 7 years. This movement reflects a growing awareness
that clinical dysfunction may intensify over time as changing environmental expectations place new
demands on working memory and executive function resources in adults (Faraone, Biederman, Spencer,
et al., 2000).
Because greater task complexity typically accompanies grade promotion in traditional school settings, an
increase in the severity of AD/HD symptoms that is associated with new or prolonged school exposure
should raise similar suspicions regarding the potential impact of classroom conditions and academic
adversity on the generation and expression of attention deficits. Often careful questioning will reveal that
the criteria for AD/HD within a home setting are only met when parents take into consideration their child's
attempts to complete homework assignments. This phenomenon leads to the argument that the symptoms
of AD/HD are not truly occurring within two different settings, but only in the school setting -- which,
because of homework, may be encountered both on campus and within the student's home.
The DSM-IV (1994) does acknowledge that symptoms of inattention may commonly appear when children
with low IQ are placed in academic settings that are inappropriate to their intellectual ability. It is also noted
that inattention in the classroom may occur when children with high intelligence are placed in academically
understimulating environments. However, the possibility that inappropriate academic environments may
contribute to the symptoms of inattention seen in children of average or above average intelligence who
struggle with impaired academic skills appears to have been overlooked (American Psychiatric
Association, 2000; First, Frances, & Pincus, 2000). Although learning disorder, reading disorder,
mathematics disorder, and disorder of written expression are recognized as discrete diagnostic entities,
there is no indication that the clinical manifestations of these disorders might be interrelated with the
manifestations of attention-deficit/hyperactivity disorder. This possible interaction has received greater
consideration in the American Academy of Pediatrics' The Classification of Child and Adolescent Mental
Diagnoses in Primary Care: Diagnostic and Statistical Manual for Primary Care (DSM-PC), Child and
Adolescent Version (1996).
A review of automaticity
Automaticity serves as the basis for many reflex-like neurophysiologic responses, ranging from the
relatively innate (e.g., defensive blinking), to the quickly learned (e.g., a child's fear response towards the
stove top after touching a hot burner), to responses acquired over years of practice (e.g., the rapid
reciprocal responses of two chess experts).
The formulation of invariant stimulus-response relationships (schemata) as a result of repeated practice
helps to protect limited system resources by reducing the amount of sensory input that has to be
processed whenever an individual is confronted by multiple environmental stimuli (Broadbent as cited by
Cohen, 1993). These highly automatized schemata are able to proceed without adversely impacting on the
simultaneous performance of other effortful activities and, eventually, may evolve to the point that they
operate without the subject's awareness. Fitts confirmed that skilled experts often perform tasks within their
areas of expertise so automatically that they are unable to explain how they accomplish their goals (cited in
Willingham & Goedert-Eschmann, 1999).
Shiffrin and Schneider (1977) contrasted such automatic processing (in which selected stimulus-response
pairings gradually become favored over others as the result of practice) with controlled processing (a more
naive approach to novel stimuli in which the relative likelihood of specific stimulus-response pairings is still
unknown):
Controlled search is highly demanding of attentional capacity, is usually serial in nature with a limited
comparison rate, is easily established, altered, and easily reversed by a subject, and is strongly
dependent on load. Automatic detection is relatively well-learned in long term memory, is demanding of
attention only when a target is presented, is parallel in nature, is difficult to alter, to ignore, or to suppress
once learned, and is virtually unaffected by load [italics added]. (p. 127)
Unlike intentional (controlled) tasks, which are vulnerable to disruption by both subject and environmental
influences, automatic routines tend to be highly resistant to outside interference (Anderson, 1983). This
feature of automatized tasks increases the chances that a desired course of action will be successfully
completed in the midst of competing, often adverse, environmental circumstances. Unfortunately,
automatic responses that are deemed to be "undesirable" or "inappropriate" also may be unstoppable
once they have been triggered. The author would assert that it is this latter type of automatic response,
often perceived as uncontrolled and inappropriate behaviors in the classroom setting, which typically leads
to a referral for AD/HD evaluation.
Although there is still significant disagreement among researchers relating to the defining characteristics of
automaticity and its underlying psychological and physiological processes (e.g., Anderson, 1982, 1992;
Logan, 1998; Logan, Taylor, & Etherton, 1999; MacKay, 1982; Nosofsky & Palmeri, 1997), such
controversies may lie with the methods of defining automaticity rather than with the concept of automaticity
itself (Logan & Klapp, 1991). The work of one research group (Logan et al.) will be primarily highlighted in
this review in an effort to help the reader achieve an elementary understanding of automaticity and its
potential role in AD/HD.
Logan's instance theory of automaticity (1988) proposes that individuals start out with an initial set of
general strategies or step-by-step algorithms for performing specific tasks. When a novel situation is
initially encountered, the resulting stimulus-response pairing is stored as a processing episode or
instance. Each subsequent encounter with the same stimulus is encoded, stored, and retrieved separately.
Increasing the number of encounters with a given stimulus will incrementally enhance familiarity and
automaticity and will result in a reduction in reaction time, load effects, and dual-task interference (Logan &
Etherton, 1994).
Instance theory asserts that there are no limits to the degree of automaticity that may be attained through
practice, because each learning trial has the same effect on memory regardless of the number of trials
that went before it. Over time, separate episodic traces derived from personal experience accumulate and
promote a transition from slow algorithmic processing to rapid memory-based retrieval. Automaticity is
complete when responses are based entirely on the retrieval of instances from memory with no reference
to step-by-step algorithms. Logan (1988) notes that a novice's need to adhere to algorithms reflects a lack
of experience rather than a scarcity of resources.
Every stimulus, whether familiar or novel, initiates the retrieval of multiple stored instances from long-term
memory. The retrieval process competes in parallel against a slower, more general algorithmic approach
that in time will also yield an acceptable solution. This quickly becomes a horserace: whichever process
arrives at a workable solution first will determine the overt response (Logan, 1988).
Logan (1988) proposes five characteristics of automaticity. These criteria serve to further clarify the
important role that automaticity may play in the clinical picture of AD/HD. According to Logan's instance
theory of automatization, automatized responses are:
1) autonomous - This term implies that automatic processes can begin and run to completion without an
individual necessarily intending for the process to occur.
2) controllable - Automatic behaviors tend to follow relatively stereotypical patterns that are constrained by
specified goals. Because these schemata evolve along an automaticity continuum as a result of rehearsal,
automaticity is a relative trait that permits responses to potentially be initiated or altered by changes in a
person's intentions. The common misperception that automatized processes are uncontrollable likely
reflects past encounters with well-rehearsed instances that proceeded to completion so quickly that slower
intentional efforts had little opportunity to intervene.
3) effortless - Automatic tasks can be performed without effort because retrieval processes proceed so
quickly and efficiently that there is virtually no utilization of system resources. Whenever capacity-limited
systems are rendered inoperable by a temporary exhaustion of system resources, unintentional
automatized processes may appear by default.
4) unconscious - Automaticity represents a shift from the slow, conscious tracking of relatively-
cumbersome algorithms to the rapid, one-step retrieval of instances from long-term memory. With
repeated experience, these automatic processes may occur so quickly that they may come to be initiated
and completed without any awareness on the part of the individual involved.
5) difficult to remember - Because automatic processing may often proceed without conscious awareness,
event specifics tend to be superficially encoded at best, making them difficult to recall.
Contrasting views of automaticity
In his Adaptive Control of Thought (ACT*) production system theory, Anderson (1983, 1992) asserts that
the transition from slow and laborious task performance to rapid skilled performance occurs in three
stages: the encoding of knowledge directly from experience, the conversion of knowledge into a production
rule form that eliminates the need to retrieve declarative instructions (termed knowledge compilation), and
the strengthening of production rules and declarative facts. Paralleling the observations made for instance
theory, Anderson's ACT* theory asserts: (a) production rules are evoked in response to a specific goal, (b)
skills speed up with practice, (c) tasks become more "automatic" if there is a consistent stimulus-to-
response mapping, (d) every time a production is practiced its strength increases by the same increment,
(e) as a skill becomes more practiced, it is less susceptible to interference from concurrent tasks and is
harder to inhibit, (f) whether an automatic skill interferes with concurrent processes will depend on the
degree of remaining overlap with concurrent productions, and (g) the selection of a production rule is
determined by a competition among production rules; stronger productions do better in this competition. In
addition, the original production rules and declarative knowledge are preserved and serve as alternative
bases for performing a task (similar perhaps to the default algorithms described by Logan).
Nosofsky and Palmeri (1997) have proposed an exemplar based random walk (EBRW) model that
combines Nosofsky's generalized context model of categorization (GCM; 1986) with Logan's instance-
based model of automaticity (1988). In this model, stimuli cause stored exemplars to race among one
another to be retrieved from memory, with rates being determined by their similarity to the presented item.
Rather than the first retrieved exemplar solely driving the response as suggested by instance theory, the
retrieved exemplars provide incremental information that feeds into a random walk decision process. The
process becomes more efficient with increased training (as reflected in faster response times) because a
greater number of exemplars race to be retrieved from memory. Increasingly, decisions become based on
one's extensive exemplar-based experience. Although simple analytic rules (possibly similar in function to
algorithms) may coexist with the exemplar retrieval system, exemplar-based retrieval processes are
hypothesized to play a more dominant role as individuals gain increased expertise in a given perceptual
domain.
MacKay (1982) proposed a theory based on nodal strengthening. Under his theory, execution of behavior
requires the activation of a hierarchy of nodes in proper serial order within an output system. While too
complex to detail here, parallels can be drawn between MacKay's findings and certain elements of Logan's
theory: (a) practice enhances automaticity by increasing the linkage strength between nodes, (b) the
expression of an outcome is determined by a competition between alternatives ("strongest-node-wins"
principle), (c) interference may lead to an unintended outcome (error) whenever activated extraneous
nodes supplant the activation of intended nodes, and (d) with practice, aspects of an action hierarchy can
become automatic, that is, highly practiced nodes are activated so quickly that reliance on conscious
awareness and effort seems out of the question. Here, again, consciousness is reserved for what is new
(non-automatic).
Although these researchers may attribute the emergence of automaticity or skilled performance to different
underlying mechanisms, they generally seem to agree on several practical differences between automatic
and non-automatic processes. Therefore, while Logan's instance theory has been chosen to help
introduce the concept of automaticity, the impact of automaticity on classroom performance would remain
essentially the same regardless of the theory espoused to explain its emergence.
Automaticity, inhibition, and interference
When one considers what is currently known about the unreliable nature of memories (Garry, Loftus, &
Brown, 1994; Zaragoza & Mitchell, 1996) and the plasticity of cortical mappings (Buonomano & Merzenich,
1998), it appears unlikely that Logan's "instances" could be preserved within memory systems in a manner
that assures their unaltered recall. Subsequent writings by Logan et al have addressed this issue by
emphasizing that instances are propositional in nature (Logan & Etherton, 1994; Logan, Taylor, &
Etherton, 1996). This feature permits stored processing episodes to be retrieved either in whole or in part
and allows for the possibility that individual components of a more complex instance may be selectively
recruited and combined with other retrieved traces during the generation of a response to specific
environmental cues.
Ultimately, however, automaticity (and AD/HD) must be explained in a manner that is consistent with the
ever-changing neuroanatomical connections and complex neurochemistry of the evolving human brain (e.
g., Buonomano & Merzenich, 1998; Classen, Liepert, Wise, Hallett, & Cohen, 1998; Lu & Figurov, 1997;
Rogeness, Javors, & Pliszka, 1992). Some of the more basic neuroanatomic and neurophysiologic
principles underlying the evolution of automaticity can be appreciated by considering Rumelhart, Hinton,
and McClelland's theory of parallel distributed processing (PDP; as cited in Cohen, Dunbar, & McClelland,
1990). According to this theory, incoming stimuli initiate patterns of activation across a series of
information processing units that are housed within larger, interconnected modules. With repeated
experience, commonly encountered sequences are reinforced; others gradually dissipate over time.
The theory of parallel distributed processing helps to explain why automaticity only emerges when learning
activities take place in an environment that provides for repeated exposures under consistent mapping
conditions (Anderson, 1992; Kramer & Strayer, 1988), and, conversely, why practice under variable
conditions does not promote the emergence of automaticity. Note that the discrete activation sequences
described above will change in order to reflect as accurately as possible the wide array of stimuli
associated with any event. Automaticity theoretically emerges when an identical pattern is reinforced again
and again over time. In keeping with Logan's (1988) assertions, this mechanism ensures that evolving
automatic pathways will be process-specific. Transfer to truly novel situations generally will be poor.
The PDP theory also provides a neuroanatomic explanation for findings that suggest it is the individual
components of a complex task that appear to undergo automatization during repeated practice rather than
the larger task as a whole (Jonides, Naveh-Benjamin, & Palmer, 1985; Kramer & Strayer, 1988). Which
specific elements are strengthened will vary with how a person's attention is distributed (Logan & Etherton,
1994). Breaking larger, more complex tasks down into a series of basic components (activation
sequences) that can be repeatedly practiced under consistent learning conditions helps to prevent system
overload while facilitating instance mapping and the emergence of automaticity. (Kramer, Strayer, &
Buckley, 1991).
The discovery that automatization tends to occur at the component level has significant implications for the
design of educational programs. Rather than requiring at-risk students to struggle with complex schemata
in their entirety, already automatized skills might be utilized to facilitate content-related learning and testing
activities, while relatively impaired skills (e.g., decoding or writing) are addressed in a remedial setting
designed to ensure environmental and stimulus consistency. In time, individuals will be able to piece
together these automatic sequences in various combinations that permit the rapid execution of complex
tasks with minimal reliance on capacity-limited attention, working memory, and executive function systems.
Whenever a series of activations are initiated concurrently within the PDP model, there is the possibility
that two separate sequences may eventually require the use of one specific system element at the same
moment. If the intersecting patterns of activation prove similar, then facilitation will result. However, if the
patterns prove to be incompatible, then the interaction will lead to inhibition with subsequent signal
disruption and task interference (Cohen, Dunbar, & McClelland, 1990).
MacLeod and Dunbar (1988) indicate that more automatic dimensions ought to selectively interfere with
less automatic dimensions. Accordingly, the relative strength (automaticity) of competing pathways (tasks)
at any point in time can be estimated by measuring the degree and nature of interference encountered
during dual-task activities. Automatic processes appear to be less vulnerable to the resource depletion
associated with dual-task interference than are more resource-dependent, non-automatic processes. As
noted in the next section, the resource-independent nature of automatic processes and their relative
immunity to interference may be attributable to the creation of specialized pathways that help to lessen the
chance of sequence interaction. This practice-driven remapping process serves to give automatized
sequences a distinct advantage whenever they must compete in parallel with slower, non-automatic
neuronal connections.
The anatomic basis of automaticity: PFC, ACC, MTL, and LTM
The prefrontal cortex (PFC), anterior cingulate cortex (ACC) and medial temporal lobe (MTL) play
important roles in the establishment of instances within long-term memory (LTM) (see Figure 1).
Consequently, they must also serve as the breeding ground for automaticity. During the automatization
process, reliance on these slow, effortful, resource-dependent structures is gradually supplanted by an
emergence of faster, more efficient direct neuronal connections to LTM. These changes have been
confirmed by imaging studies that look at the effect of practice on PFC, ACC, and MTL function (Jenkins,
Brooks, Nixon, Frackowiak, & Passingham, 1994; Petersson, Elfgren, & Ingvar, 1999; Raichle et al., 1994).
A basic understanding of the functions of the PFC, ACC, and MTL should help to clarify their roles in
learning, their vulnerability to resource depletion, and the potential drawbacks encountered when their
function is preempted by automatic responses. (While numerous other systems, e.g., the cerebellum and
basal ganglia, are believed to contribute to learning and response production, details relating to these
structures have been purposely excluded from the current discussion to help ensure clarity.)
The prefrontal cortex (PFC) is believed to serve as the anatomic home of working memory and to co-host
related executive function processes (Courtney, Petit, Haxby, & Ungerleider, 1998; Fuster, 1997). Because
of its many reciprocal connections to both cortical and subcortical structures, the PFC is ideally positioned
to play a pivotal role in the encoding and retrieval of memories.
The prefrontal cortex is subdivided into several specific regions designed to subserve different aspects of
working memory and executive function (see Figure 1). Whenever environmental expectations place
excessive demands on these attention-dependent areas, clinical dysfunction may result.
The orbitofrontal cortex activates early in PFC processing to help stop prepotent automatic responses to
ambiguous environmental cues (i.e., behavioral inhibition); this gives an individual time to choose a
response that may be more effortful but, ultimately, more rewarding. The OFC is strategically positioned to
serve as a convergence zone for emotional and cognitive information, given its reciprocal connections
posteriorly with the limbic system (e.g., the amygdala) and anteriorly with structures such as the
dorsolateral PFC and anterior cingulate cortex (ACC). Orbitofrontal activity decreases once the subject
has decided on a course of action, and an increasing activation of more lateral prefrontal regions follows.
The specific patterns of activation seen within the prefrontal cortex will tend to vary in accordance with the
strategies set in motion by the orbitofrontal cortex (Savage et al., 2001).
The inferior prefrontal cortex (IPFC) appears to subserve working memory by holding information online so
that active comparisons can be made to information already stored in long-term memory. This process is
characterized by lateralization with verbal semantic knowledge being primarily processed by the left IPFC
and nonverbal (visual) features being processed within the right IPFC (Golby et al., 2001). The anterior
portion of the left IPFC appears to be involved with semantic access, maintenance, and evaluation,
including the use of semantic elaboration during encoding and the subsequent handling of semantic
knowledge that is represented elsewhere within the cortex (Demb et al., 1995; Kapur et al., 1996;
Thompson-Schill, D'Esposito, Aguirre, & Farah, 1997). The posterior left IPFC seems to be involved more
with phonological access, maintenance, and evaluation (e.g. phonetic discrimination), with activation levels
reflecting the degree of phonological memory load being encountered (Buckner, 1996; Jonides,
Schumacher, et al., 1998; Wagner, 1999).
The dorsolateral prefrontal cortex (DLPFC) also supports working memory; however here information is
more likely to be actively manipulated and updated as formulated action plans are concurrently monitored
to ensure that responses are consistent with one's overall goals. Unlike the IPFC regions, which appear to
lateralize based on the nature of the stimuli being processed (i.e., verbal versus visual), the dorsolateral
areas appear to contribute to episodic memory irrespective of the nature of the material being processed.
The DLPFC does appear to maintain a strong bi-directional communication with visuospatial memory, and
bi-directional connections with the limbic system (via orbitofrontal cortex) and long-term memory (via the
medial temporal lobe). In general, however, the right DLPFC is more likely to be involved with retrieval
processes, while the left side may be activated during both encoding and retrieval activities (Savage,
2002; Wagner, 1999).
The ventromedial PFC, while not playing an important role in working memory, does play a key part in
decision-making. The poor decision-making that results from dysfunction of the ventromedial PFC has
been attributed to three possible mechanisms: (a) hypersensitivity to immediate reward, (b) reduced
sensitivity to punishment, or (c) insensitivity to future consequences so that immediate considerations
override any future concerns (Bechara, Damasio, Tranel, & Anderson, 1988). According to Bechara et al,
preliminary findings by their research team suggest that poor decision-making appears to be attributable
to the insensitivity of these individuals to the potential consequences of their actions. As a result,
individuals with ventromedial PFC impairment will be guided only by their perceptions of the immediate
consequences of their decisions (e.g., whether they are likely to experience success or failure,
achievement or humiliation) rather than by any potential benefits or punishments that they might or might
not encounter in the future.
The anterior (or fronto-polar) PFC appears to be responsible for the ability of humans to multi-task. This
region redirects attention while maintaining the goals of a main task in mind (Koechlin, Basso, Pietrini,
Panzer, & Grafman, 1999).
It is here, within the multi-faceted prefrontal cortices, that novel stimuli in the environment first interact with
one's memories of past experiences. The PFC introduces bias into decision-making processes by
permitting past experiences stored in long-term memory to exert their top-down influence on the perception
and interpretation of incoming stimuli. Previously encountered information that has been well integrated
into long-term memory generally seems to be easier to attend to than novel input temporarily being held in
short-term memory (Schneider & Fisk, 1984). Petersson, Elfgren, and Ingvar (1999) have proposed that
bilateral activation of the prefrontal cortices paves the way for free-recall (a non-automatic process) and
self-initiated behaviors.
During automatization, changes in neuronal activity within the anterior cingulate cortex (ACC) parallel
those observed in the PFC. The ACC, together with the PFC, plays an active role in the monitoring of on-
going system performance: helping to determine the need for attention shifts, adjusting the field of focus,
seeking out errors, and weighing the costs and benefits of competing alternatives (D'Esposito et al, 1995).
With continued rehearsal, an ordered restructuring of all related neuronal mappings occurs. In turn, the
need for effortful tracking decreases, responses become increasingly automatic, and ACC activation
gradually diminishes (Petersson et al., 1999).
The medial temporal lobe (MTL) consists, in part, of the amygdala, hippocampus, and
parahippocampus. The exact roles of structures within the MTL are not known, but the MTL appears to
subserve the needs of the ipsilateral prefrontal cortex. Although MTL activation can be detected whenever
long-term memories are being formed or modified, the MTL is not believed to house long-term memories.
Instead, it appears to play an important role in the structuring of long-term memory (LTM) by chunking
data to be stored elsewhere and by creating keys that help to quickly retrieve these stored memories as
they are needed (Petersson et al., 1999). (Some MTL structures, such as the amygdala, may also help to
regulate emotional tone.)
Note that over time, as the same meaningful memories (instances) are repeatedly retrieved from LTM in
response to commonly recurring environmental stimuli, more efficient direct retrieval pathways are
established that bypass the highly complex, resource dependent decision making processes that involve
the PFC, ACC, and MTL. It appears to be this evolutionary bypassing process that underlies the
emergence of automaticity and the gradual reduction in activity noted in functional imaging studies of the
PFC, ACC, and MTL during learning and trained retrieval.
The interaction of automaticity and attention
The successful performance of tasks characterized by a high degree of automaticity appears to require
little if any reliance on attention, whereas tasks that are effortful (not automatic) typically will depend
heavily on the availability of attention and attention-dependent functions within the PFC and ACC. Logan,
Taylor, and Etherton (1999) have suggested that attention and automaticity may represent opposite sides
of the same coin.
While it is possible for automaticity to be established after a single trial, it is more likely to progress
incrementally along a continuum (MacLeod & Dunbar, 1988). With repeated practice, the hierarchical
relationships among schemata will change as training selectively enhances the strength or retrieval rate of
one or more specific stimulus-response pairings. Over time, a bypassing of the resource-dependent
PFC/ACC/MTL circuitry (hereafter referred to as the PAM-circuit) likely occurs. This remapping of
commonly employed stimulus-response pairings allows beneficial automatic processes to be activated
without the need for conscious effort and reduces the load placed on limited attention and working memory
resources within the PAM-circuit (see Figure 2).
While this sparing of the capacity-limited attention and working memory systems may at first glance appear
ideal, emerging automaticity may derail future attempts by the PAM-circuit to consider incoming or stored
information in a new or different way. Direct routes to LTM will be favored over the slower, more intentional,
more resource-consuming pathways that dominate the PAM-circuit. As a result, familiar environmental
stimuli may autonomously activate relatively inflexible automatic responses causing them to race
unchallenged towards the "finish line", circumventing the top-down monitoring processes (executive
function) that operate within the PFC and ACC. Such rapid automatic responses may prove to be
inappropriate, however, especially if the emerging schemata have been prematurely activated by a few
attention-grabbing elements of a stimulus before all of its relevant characteristics can be adequately
screened by the PFC (see Figure 2).
Cohen, Dunbar and McClelland (1990) considered the possibility that: "attention is required both to
suppress the unattended channel and to enhance processing in the attended one" (p.356). If this is true,
then a portion of one's already limited attention resources within the PAM-circuit would need to be
intentionally redirected (probably via the orbitofrontal cortex) towards suppressing the premature high-
speed activation of well-established, direct connections to long-term memory in order for slower, less
automatized (intended) responses to have adequate time to be expressed.
Cohen et al. (1990) also acknowledged the possibility that: "... suppressing one [channel] requires
resources that take away from the ability to facilitate the other" (p. 356). Accordingly, redistributing
attentional resources in an effort to block the automatic release of impulsive behaviors could potentially
deplete critical attention resources and impair the controlled analysis and tracking of data within the PAM-
circuit (see Figure 3).
Pennington, Bennett, McLeer, and Roberts (1996) point out that working memory would be severely
impaired and executive function would serve little purpose without inhibition providing the necessary delay
between a stimulus and response. Unfortunately, attempts to intentionally suppress undesirable
automatized responses may be thwarted by the fact that established neuronal mappings change as task-
performance moves from reliance on algorithms to more reflexive processes. Direct-access neuronal
networks may not be inhibited by the same strategies that once effectively suppressed PFC-anchored,
algorithm-based decision processes. In addition, highly automatized responses may proceed to completion
so quickly that there is not adequate time for consciously controlled intentions to intercede.
Whether a student will succeed in inhibiting unintended automatic responses therefore would seem to
depend on: (a) the overall automaticity (or lack thereof) of any intended processes, (b) the inherent speed
or strength of any unintended automatic processes, and (c) the current availability of divertible resources
within the limited-capacity attention and working memory systems. As the total degree of discrepancy
between the intended non-automatic process and all opposing automatic (unintended) processes
increases, there likely will be an ever-greater probability that available attention-dependent resources will
prove inadequate to assure both the successful expression of the desired response and the timely
suppression of an unintended one.
Automaticity, divided attention, and induced attention deficits
The encoding and retrieval of memories occurs as an inescapable consequence of attention. Attending to
a stimulus is purported to be sufficient, in itself, to place a stimulus into long-term memory and to retrieve it
from memory. However, the quality of the encoding and the success of retrieval may vary as a
consequence of the way in which one's attention is apportioned (Logan, 1988, 1990; Logan & Etherton,
1994).
Whenever individuals are forced to divide their attention between two or more non-automatic tasks, there
is an increased likelihood that learning and performance efforts will be hampered by a progressive
depletion of attention and working memory capacities (see Figure 3). While many individuals believe that
they can do two things at once, interference typically will occur, even when the competing tasks do not
seem either intellectually challenging or physically incompatible (Pashler, 1994).
Recall that Schriffin & Schneider (1977) observed: (a) controlled search is highly demanding of attentional
capacity, is easily altered, and is strongly dependent on load, while (b) automatic detection is relatively well-
learned in long term memory, is demanding of attention only when a target is presented, is difficult to alter,
to ignore, or to suppress once learned, and is virtually unaffected by load. This suggests that controlled
search occurs via complex connections within the attention-dependent PAM-circuit, while automatic
detection is processed via more direct pathways to the LTM.
Accordingly, students will be likely to encounter dual-task interference whenever two non-automatic, PAM-
circuit dependent tasks are attempted simultaneously (e.g., reading and writing tasks by a student with
reading and writing impairments). In this situation, the resource-depleting need to consciously track each
step within the two required algorithms may overwhelm limited attention and working memory resources.
During well-rehearsed tasks, on the other hand, the need to rely on effortful step-by-step monitoring
processes within the PAM-circuit is less. Increased familiarity with a task results in its being positioned
further along the automaticity continuum where there is a lesser dependency on limited attention and
working memory resources. Highly automatized tasks, processed outside of the PAM-circuit, can potentially
proceed to completion so quickly that an individual might not even be aware that multiple unintended
schemata have been activated.
Note that instructional activities that force students to divide their attention in the classroom will lead to
attention and working memory depletion, the superficial processing of newly presented material, and the
undermining of critical encoding efforts. Such teaching methods clearly are counter-productive, as the
universal goal of instruction is to promote deeper processing and more effective encoding of new
information into LTM.
Similarly, dividing attention at the time of testing allows competing non-automatic tasks to rapidly exhaust
limited attention and working memory resources. This resource depletion typically causes students to shift
from deliberative (PAM-circuit dependent) contemplation to a more non-analytic, attention-sparing
approach to decision-making where judgments are based on feelings of familiarity (i.e. what feels right)
rather than precise recollection (Jacoby, 1991). It may well be this default mechanism, brought on by an
induced PAM-circuit dysfunction, that accounts for the "hurried" or "poorly thought out" answers that are
so often noted in the class work of children believed to have AD/HD.
Automaticity, stress effects, learned helplessness, and PAM-circuit dysfunction
While stimulus interpretation theoretically is determined by the outcome of a race between competing
instances arriving from one's long-term memory, more powerful primitive forces (e.g., fear, anxiety) that
originate from deep within subcortical structures may intervene to dramatically alter this scenario.
Research into the phenomenon of learned helplessness emphasizes the potential consequences of
inescapable environmental stress on learning and behavior.
According to Arnsten (1998), neurochemical changes in the brain during periods of stress may take the
prefrontal cortex "off line", disrupting working memory and making it more difficult for children to govern
their behavior (see Figure 3). The environmentally-induced PFC dysfunction may present clinically as poor
attention regulation, disorganization, impulsive behaviors, and increased hyperactivity. This process is
believed to be mediated by neurochemical changes involving the catecholamines dopamine (DA) and
norepinephrine (NE). Interestingly, currently employed protocols for the pharmacologic treatment of AD/HD
are designed to selectively increase the intrasynaptic concentrations of these same two neurotransmitters
(Spencer et al, 2001; Wilens & Spencer, 1998). Since much has been published about the role of
dopamine in AD/HD, this article will limit its focus to norepinephrine and its potential contribution to AD/HD
symptoms and school failure.
Under routine conditions, norepinephrine (NE) release appears to enhance PFC function and promote the
performance of working memory-based tasks, response inhibition, and planning activities (particularly
under distracting conditions) via its action at post-synaptic α2A-receptors. However, during times of
uncontrollable stress, exceedingly high levels of norepinephrine are released which stimulate low affinity
α1-noradrenergic receptors. When activated, these α1-receptors appear to disrupt PFC function, leading
to working memory impairment and behavioral disinhibition. As a result, both low levels of norepinephrine
and excessive levels of norepinephrine might be expected to impact adversely on PFC function (Arnsten,
2000).
Arnsten (1998) emphasizes that stress-related changes within the PFC most likely will occur under
conditions in which individuals feel that they are powerless to either change or escape the stress-inducing
circumstances. (Given the nature of truancy laws, teacher-student interactions within a traditional
classroom setting might reasonably be perceived as "inescapable".) The impact of such uncontrollable
stress on performance has been studied in great detail as part of the research into learned helplessness.
While the majority of these studies involve laboratory animals, two discoveries help to clarify the relevance
of these experiments to the experiences of school-age children with AD/HD.
Altenor, Kay, and Richter (1977) have confirmed that the consequences of learned helplessness are
encountered regardless of the type of aversive event experienced. In addition, Villanova and Peterson (as
cited in Peterson, Maier, & Seligman, 1993) performed a meta-analysis of learned helplessness
experiments with human subjects and found evidence that the learned helplessness phenomenon in
people may be even stronger than the analogous effect in laboratory animals.
Based on these two reports, it would seem reasonable to project that failure and humiliation within an
aversive classroom environment likely are as incapacitating to at-risk children (i.e., those with AD/HD,
learning impairments) as uncontrollable water exposures and electrical shocks are to caged animals within
a laboratory setting. Thus, the potential implications of learned helplessness research as it might relate to
learning and PFC dysfunction in school-age children should become readily apparent.
The core of the learned helplessness theory is that inescapable stress (e.g., shock) is not dependent on
the aversive nature of the stress itself but rather on its uncontrollability. When a subject learns that it has
no control over its current situation and expects this to be true in the future, it undergoes motivational and
cognitive changes that are responsible for its failure to learn. Three components to learned helplessness
thus become identifiable: a perceived noncontigency between the subject's actions and outcomes, an
expectation that the outcome will not be contingent on one's actions in the future, and the development of
passive behaviors (Peterson, Maier, & Seligman, 1993). According to Maier and Seligman (1976), as a
subject learns that it has no control over an aversive condition, there should emerge a loss of incentive to
try, an impaired ability to perceive the contingent relationship between a specific act and its outcome, and
evolving emotional changes that will progress from anxiety to depression if the experience continues.
Weiss, Stone, and Harrell (1970) showed that the NE content within the whole brains of laboratory rats is
reduced following exposure to inescapable shock; this NE depletion does not occur if the subjects are able
to avoid or escape the stressor. Subsequently, despite the apparent recovery of depleted NE stores
following termination of such a stressful experience, there appears to be a period of residual vulnerability
during which exposure to even a small amount of shock (an amount that may be insufficient to alter NE in
control animals) is able to rapidly deplete the NE stores in animals previously subjected to inescapable
shocks (Anisman & Sklar, 1979).
Similarly, Petty, Chae, Kramer, Jordan, and Wilson (1994) have demonstrated that the hippocampus in
rats becomes sensitized during learned helplessness. This leads to a disproportionate increase in the
release of norepinephrine within the hippocampus following subsequent exposure to a relatively mild form
of inescapable shock.
A study that looked at cerebral blood flow changes in the medial temporal lobe (MTL) associated with
anagram tasks revealed increased activation in the hippocampal region and decreased mamillary body
activity as a posed anagram was being successfully solved. However, unsolvable anagrams (i.e.,
stressors) were associated with a reduction in hippocampal blood flow and an increase in blood flow to the
mamillary bodies and amygdala (Schneider, Gur, et al., 1996). These findings are consistent with a
physiologic shift from the encoding of the visual and verbal elements of environmental stimuli to the limbic
processing of salient emotional features in the presence of situational stress. At these times, affected
individuals might be expected to display impaired cognitive processing and an increase in emotionally
driven behaviors.
Peterson, Maier, and Seligman (1993) note that an individual's expectations may be sufficient to induce
learned helplessness. In this case, a student would not necessarily have to experience repeated failure or
humiliation within a given setting; there would only need to be an anticipation of its inevitability. Other
researchers have shown that exposure to environmental stimuli that have become associated with specific
stressors will produce more fear than will controllable stressors and their environmental cues (Desiderato
and Newman, 1971; Mineka, Cook, and Miller, 1984; Mowrer and Viek, 1954).
The finding that associated environmental cues can impact on stimulus perception and response activation
is reminiscent of the work of Pavlov, who noted that laboratory dogs would begin salivating when his lab
assistant entered into the research laboratory. This reaction would occur long before the animal could see
or smell the meat that the assistant was carrying. Pavlov's subsequent research into classical conditioning
revealed that the initially neutral stimulus (lab assistant) had could become so closely associated with the
salivation-inducing unconditioned stimulus (meat) that subsequent encounters with the once neutral lab
assistant (now a conditioned stimulus) triggered an unintended salivation response (transformed from an
unconditioned to a conditioned response). When considered together with learned helplessness
research, Pavlov's classical conditioning (as reviewed by Ormrod, 1995) makes it easier to understand
why some students may perform well in certain academic settings, only to experience disabling increases
in stress whenever an unsympathetic instructor closes the door to a classroom.
Maier (2001) has shown that repeated exposure to an environment in which inescapable shock (stress)
has previously occurred can prolong the duration of learned helplessness indefinitely. This finding was
found to be specific for re-exposure to environmental cues that were present at the time of a previous
inescapable stress experience, not just stressful environments in general. This interference with function
was shown to last for as long as 28 days after repeated exposures to conditioned environmental stimuli
were halted. In addition, Hersch, Stone, and Ford (1996) have reported that stressed students with
learning disabilities will have significantly greater difficulty recovering from experiences with academic
failure than will their regular education peers.
These findings support the assertion that individuals with learning disabilities, who are forced to face the
same aversive classroom conditions day after day, ought to be more likely than their non-impaired
classmates to wrestle with the cognitive and behavioral consequences of learned helplessness. Maier
(2001) has proposed that the persistence of learned helplessness as the result of repeated "reminding" by
environmental cues might parallel the neurophysiologic processes that underlie the emergence of post-
traumatic stress syndrome in humans and may involve the serotinergic as well as the noradrenergic
systems.
Jackson, Maier, and Rappaport (1978) were able to demonstrate that the stress associated with exposure
to inescapable shock could interfere with an animal's ability to suppress lever-pressing behavior even
when pressing of the lever caused additional shocks. This was felt to represent an instance of poor
learning characterized by more rather than less activity. In this study, learned helplessness led to
behavioral disinhibition that persisted despite the immediate and repeated application of punishment
(behavior driven shocks). The finding that stress can induce behavioral disinhibition is of particular
importance because Barkley (1990) has emphasized that disinhibition is the hallmark of attention-
deficit/hyperactivity disorder.
Jackson, Alexander, and Maier (1980) observed that non-shocked and escapably-shocked animals made
errors on only 10 percent of trials by the end of the training session. Whereas inescapably shocked rats
remained at a random choice level of performance for 40 trials and were still beginning 30 percent of the
trials with an incorrect choice by the end of training. Minor, Jackson, and Maier (1984) subsequently
suggested that the learning impairments associated with learned helplessness might be tied to attentional-
perceptual dysfunction and an associated alteration in attention.
With the potential effects of stress on behavioral disinhibition (hyperactivity, impulsivity) and attention
having already been suggested, Minor, Pelleymounter, and Maier (1988) infused 6-hydroxydopamine
directly into the locus coeruleus and dorsal NE bundle of laboratory rats to deplete their norepinephrine
stores. (The locus coeruleus is a structure located in the brainstem region that contains roughly 80% of
the brain's norepinephrine. The dorsal NE bundle connects the locus coeruleus to the neocortex,
cerebellar cortex, hippocampus, and amygdala.) These NE depleted rats still were able to learn to escape
a Y-maze quickly -- provided that irrelevant cues were absent from the environment. In the presence of
environmental distractors, NE depleted animals experienced such severe impairment that their
performance failed to improve at all over 120 learning trials. (Interestingly, this induced cognitive
dysfunction had no effect whatsoever on the speed with which these animals responded.)
If learned helplessness (along with its associated inattention, distractibility, hyperactivity, impulsivity, and
learning impairments) is to be avoided, then it would seem that academic programs must incorporate
opportunities for students to exert some measure of control over their own learning experiences. Peterson
et al. (1993) note that learned helplessness can be prevented or reversed by providing subjects with the
opportunity to learn that outcomes are not beyond their control.
(The author routinely employs a structured student interview (Herklots, 1998) during the AD/HD evaluation
process to help provide students with an opportunity to share personal insights into their own academic
abilities, preferred learning methods, and aversive past educational experiences. Not only does this
approach empower students to alter their educational experience, it honors the timeless admonition of Sir
William Osler, M.D. to diagnosticians: "Listen to your patient [student], he [she] is telling you the
diagnosis.")
Before leaving the topic of stress in the classroom, it must be noted that not all stress is "bad". Volpicelli,
Ulm, Altenor, and Seligman (1983) have demonstrated that tasks that present subjects with escapable
stress actually promote learning, increase motivation, and augment the perception that outcome is
contingent on one's effort. Accordingly, providing students with challenges that they can surmount with
reasonable effort (based on their academic abilities and an ongoing assessment of their attention-
dependent resources) would appear to be a reasonable foundation on which to construct individualized
education programs.
It is important to recognize that providing students with opportunities to experience success is not the same
thing as handing out unearned rewards. For, as noted earlier, the learned helplessness phenomenon
does not depend on the degree of aversiveness of an experience, but on a subject's inability to exert any
control over the situation. Thus learned helplessness may ensue even when the uncontrollable event is
positive (e.g., unearned rewards) or neutral (Altenor, Kay, & Richter, 1977).
The emerging message is this: at-risk students need to succeed. It is therefore important that those who
work with students remain wary of commonly utilized classroom strategies that may prove to be counter-
productive. For example:
1) When students were told that they did poorly on a test due to their own lack of ability to problem-solve,
they did much poorer on subsequent testing than did those students who were informed that their failure
was actually due to the unsolvable nature of some of the questions (Araki, 2000). This powerful impact of
attributional style on subsequent success challenges the practice of telling at-risk students that they are
getting poor grades due to their own lack of effort and motivation.
2) When students were required to perform an academic task in public (e.g., in front of the class) after an
encounter with academic failure, they were much more likely to experience repeated failure than if they
were to be allowed to work on the task in a less public setting (Witkowski & Steinsmeier-Pelster, 1998).
While the authors explain this phenomenon using self-esteem protection theory (SEPT) rather than
learned helplessness theory, the resulting harm to a student likely would be the same regardless of the
theoretical rationale.
3) Weisenberg, Gerby, and Mukulincer (1993) showed that students who failed while attempting an
unsolvable task experienced higher levels of anxiety than those who did not experience such failure. (Note
that in the heterogeneous classroom, an easy task for one group of students might be an unsolvable task
for another group.) Remarkably, this consequence of learned helplessness was ameliorated by 10 minutes
of aerobic exercise. One must therefore question the advisability of routinely keeping at-risk students
inside during recess to finish their incomplete written class work, especially given the fact that there is an
increased incidence of writing impairments in children with AD/HD. (For children who perceive aerobic
exercise to be a stressful event, it might be useful to know that both chocolate snacks and guided imagery
were shown to be as effective as exercise in preventing subsequent stress-induced performance
decrements after an episode of unavoidable failure.)
Rosellini and Seligman (1975) have shown that healthy animals will try to escape situations where effort no
longer leads to reward. This lack of return on investment, a phenomenon referred to as extinction, is
perceived as an aversive experience within the laboratory setting. It would seem quite likely that the
increasing academic demands encountered by children as they advance through school might lead to a
similar sense of diminishing returns, especially when a child's basic academic skills have failed to keep
pace with environmental expectations. Likewise, reward systems within a classroom that are based on
graded achievement rather than demonstrated effort also may be perceived as aversive experiences to at-
risk individuals, for these struggling students may be unable to successfully produce prize-winning results
despite their best efforts.
Based on the research by Rosellini and Seligman (1975), one might predict that normal healthy students
would respond to aversive extinction experiences within the educational setting by turning their focus
towards finding effective ways to escape the inescapable. In addition, instinctual behaviors presenting as
"hot-headed" defensive posturing might unintentionally supplant more "cool-headed" reasoning whenever
stress disrupts PAM-circuit functions. During the post-exposure period, minor annoyances easily may re-
ignite smoldering conflicts, until overwhelmed students, beleaguered by the specter of inevitability, opt to
either quit school or to retreat into a state of inexorable passivity. Accordingly, angry outbursts and non-
participation during classroom activities should serve as warning signs that a child's PAM-circuit may be
succumbing to cognitive overload and learned helplessness.
Automaticity and goal orientation
The importance of goal orientation cannot be overstated. While concerned parents and professionals may
meet regularly to set performance goals for a struggling student, such well-intentioned efforts may prove
fruitless if these plans fail to respect a student's personal agenda. For the student saddled with a history
of chronic academic failure, the overriding consideration during response selection may be the individual's
intense desire to avoid any further humiliation.
According to Logan's (1988) instance theory, each stored instance contains some reference to: (a) the
goal a subject was trying to attain, (b) the stimulus encountered in pursuit of the goal, (c) the interpretation
given to the stimulus with respect to this goal, and (d) the response made to the stimulus. Chartrand and
Bargh (1996) report that how one orients to and perceives stimuli within the environment is influenced by
the individual's personal goals. Goal activation selectively biases the activation of stored instances forcing
them to compete with one another until the one with the highest activation level (or most rapid response)
elicits the overt behavior (Aarts & Dijksterhuis, 2000; Logan, 1988). The activated response will tend to
vary as a function of one's personal history; that is, the more often the activation of a goal has led to the
performance of a specific action in a specific situation, the stronger the link will be between the activated
goal and response.
Reflexive behaviors shaped by the outcome of a race among competing past experiences frequently may
result in repeated task avoidance and the emergence of school anxiety. Continued repetition and
reinforcement (the successful avoidance of humiliation serves as negative reinforcement) further
strengthens these stimulus-response linkages, promotes automaticity, and therefore increases the future
susceptibility of these goal-directed (task avoidant) automatic behaviors to spontaneous activation by a
variety of environmental cues (Aarts & Dijksterhuis, 2000).
McCormick (1997) has shown that certain cues within the environment may capture a person's attention
without the individual ever being aware that this has occurred. This tendency to alert without awareness is
noted to parallel the phenomenon of blindsight in which a patient who claims to have no awareness of a
stimulus can still orient a response to its location. McCormick's work, paired with the findings of Aarts and
Dijksterhuis (2000), appear to explain how some of the disruptive classroom behaviors displayed by
children with AD/HD might be goal-directed, yet not necessarily intentional.
A pause for review
Studies reviewed to this point set the groundwork for the proposition that symptoms typically attributed
to primary attention-deficit/hyperactivity disorder (i.e., inattention, disorganization, hyperactivity, and
impulsivity) may be mimicked by environmentally induced resource depletion within the prefrontal cortex.
The provided evidence also confirms that limited attention and working memory resources within the PFC
are especially vulnerable to divided attention conditions that are encountered whenever individuals are
required to perform two non-automatic tasks at the same time. However, the multi-system failure paradigm
proposed in the introduction indicates that, the degree of "attention deficit" experienced by a student will
vary as a result of at least three specific factors: (a) the abilities / skills of the individual, (b) the demands
of a particular circumstance, and (c) the residual capacity of the attention system.
Thus far this article has provided support for the second and third elements of this triad. It remains to be
shown that the academic skills of certain AD/HD students might actually be inadequate to meet
environmental demands during the periods of time when excessive inattention and behavioral disinhibition
are being documented by their teachers and parents.
Note that, by definition, automatized skills should not be adversely affected by low levels of attention,
because the term "automaticity" implies that skills have evolved to a point where they are no longer
dependent on the status of PAM-circuit resources. Therefore, any difficulty associated with a specified
academic skill, signifies both a relative lack of automaticity and the possible need for additional training.
This will be true regardless of whether the student in question does or does not have AD/HD.
Should instructors insist that students continue to utilize non-automatized skills during learning and testing
activities, excessive demands could be placed on limited attention stores. As these limited attention
resources become progressively depleted, at-risk students increasingly would be forced to deal with
evolving attention deficits, working memory disruption, and unrelenting academic failure.
Academic non-automaticity in students with AD/HD
The presence of school failure among AD/HD children remains one of the most reproducible findings in
studies of the AD/HD syndrome (Semrud-Clikeman et al., 1992). Despite average or above average WISC-
R (IQ) scores, students with AD/HD have repeatedly been shown to more frequently have histories of
academic dysfunction than normal controls, as evidenced by: grade retention, learning disabilities,
placement in special classes, and the need for academic tutoring (Bullock, Yurko, Solis, and Hogan, 1995;
Edelbrock, Costello, & Kessler, 1984; Faraone, Biederman, Lehman, et al., 1993; Lahey, Schaughency,
Strauss, & Frame, 1984; Silver, 1981; Weiss, Hechtman, Milroy, & Perlman, 1985). Over one-half of the
children with AD/HD who are taught in a regular classroom will likely experience school failure or grade
retention by adolescence (Barkley, Fisher, Edelbrock, & Smallish, 1990; Minde, et al., 1971), and over a
third will fail to finish high school (Weiss & Hechtman as cited by Biederman, Newcorn & Sprich, 1991).
Hinshaw (1992) proposes that early intellectual problems may, in fact, be a core component of AD/HD.
Attention deficit disorders and learning disabilities (LD) have been reported to share similar features,
especially symptoms related to inattention. In addition, the presence of comorbid learning disabilities has
been shown to exacerbate the symptoms associated with AD/HD (McGee, Williams, Share, Anderson, &
Silva, 1986; Smart, Sanson, & Prior, 1996). According to Caron and Rutter (1991), whenever these two
disorders co-occur, there is a significant risk that the neuropsychological correlates of one disorder might
be erroneously attributed to the other.
Overlap between AD/HD and LD ranges from 10% to 92% in various studies (August & Holmes, 1984;
Halperin, Gittelman, Klein, & Rudel, 1984; Silver, 1981). This disparity has been attributed to variations in
the selection criteria, sampling, and measurement instruments employed, as well as to inconsistencies in
the criteria used to define both AD/HD and learning disabilities (Biederman, Newcorn, & Sprich, 1991).
The confusion is further aggravated by the heterogeneity of these conditions and the significant academic
dysfunction commonly associated with both disorders (August & Holmes, 1984). Biederman, Newcorn, and
Sprich (1991) have made a point of emphasizing the importance of discriminating between AD/HD students
with comorbid learning disabilities and those without LD.
There also is increasing evidence that each of the AD/HD subtypes may be associated with specific
cognitive and behavioral deficits. Minde et al. (1971) found that when a selected group of hyperactive
children was matched on IQ with a control group, the hyperactive group did much poorer in class. Their
difficulties were frequently of such a magnitude that instruction within a normal class setting was unlikely to
produce any academic progress.
More recent studies confirm that children with AD/HD-IA may be at even greater risk of academic failure
than children with evidence of hyperactivity (Accardo, Blondis, & Whitman, 1990; Epstein, Shaywitz,
Shaywitz, & Woolston, 1991; Marshall, Hynd, Handwerk, & Hall, 1997). In one study (Hynd et al., 1991),
60% of AD/HD-IA students were identified with a developmental reading disorder or developmental
arithmetic disorder, whereas none of the students in the hyperactive group (AD/HD-HI/C) qualified for such
diagnoses.
Reading and AD/HD
Children with AD/HD spend more time off-task during reading activities than do non-AD/HD children
(Zentall, Smith, Lee, & Wieczorek, 1994). However, reading efforts may be further disrupted by the
presence of underlying attention-based working memory problems that interfere with their learning of the
basic underlying arbitrary symbol system necessary for the decoding of written text (Stolzenberg &
Cherkes-Julkowski, 1991).
Students who have AD/HD without a reading disability will tend to show a normal progression in the
automatization of basic reading (e.g., decoding) skills. These individuals typically can sound out words with
relative ease during reading activities and will not display significant reading difficulty until they are forced
to employ sustained and effortful processing during the comprehension and memorization of rote material
(Ackerman, Anhalt, Holcomb, & Dykman, 1986).
On the other hand, AD/HD children with a comorbid reading disability (AD/HD+RD) typically have difficulty
with the automatization of subskills such as the rapid naming of digits, letters, and objects, and the
associating of sounds with letter strings (August & Garfinkel, 1990; Felton, Wood, Brown & Campbell,
1987). While these students initially may be able to compensate for impaired reading skills by exerting
greater effort during basic decoding assessments, this excessive reliance on effortful decoding can
eventually lead to a depletion of an individual's limited attentional stores. This resource depletion, in turn,
may disrupt resource-dependent comprehension and subsequent recall efforts (Brock, 1989; Cherkes-
Julkowski, Sharp, & Stolzenberg, 1997). Researchers have suggested that the presence of impaired
performance on rapid naming tests during the assessment of children with AD/HD should be recognized as
strong evidence for a comorbid reading disability (Denckla & Rudel, 1976; Wolf, 1984).
The importance of accurately identifying reading impairments in children with AD/HD becomes evident
when one considers the potential impact of reading and attention disorders on long-term prognosis. In one
study, attention problems and internalizing behavior problems were shown to be more potent predictors of
later reading difficulty than were a child's language abilities and tests of general cognitive functioning
(Horn & Packard, 1985). In another, reading disorders exacerbated already existing behavior problems
throughout the primary school years (McGee, Williams, Share, Anderson, & Silva, 1986).
In a third study conducted over a two year period (Smart et al., 1996), the group of students with an
AD/HD-like syndrome (termed "behavior disorder" or BD in the study) and reading disability (BD+RD)
scored significantly lower than the reading disability only (RD) group in reading achievement at 9-10 years
of age; while parents and teachers consistently rated the BD+RD children to be more hyperactive than the
BD-only group at 7-8 years and 9-10 years of age. Thus, when a reading disability was present in the
children with AD/HD-like symptoms, the behavioral problems failed to get better and the reading disability
tended to become worse over the two-year study.
These results were mirrored in a study by Pisecco, Baker, Silva, and Brooke (1996) where children with
AD/HD-only or ADHD plus a reading disability (AD/HD+RD) exhibited more hyperactive and antisocial
behaviors in school than did children from a comparison group. Importantly, students with reading disability
only (RD-only), that is, children who were not felt to meet the formal criteria for ADHD, also typically
exhibited significantly more hyperactive and antisocial behaviors than did the control group. The group of
students with ADHD plus RD (AD/HD+RD) exhibited significantly more antisocial behaviors than children
from any of the other groups. Therefore, it would seem reasonable to expect that children with AD/HD,
especially those with unrecognized reading impairments, might be placed at significant risk for academic
and behavioral dysfunction whenever the education process relies heavily on an ability to efficiently
process, store, and retrieve text-based information.
These studies confirm that students who are confronted by a reading disability may be perceived as
significantly more "hyperactive" and "oppositional" within a classroom setting, features that often lead to a
referral for AD/HD evaluation in real-life. Likewise, the potential also must exist for reading impairments to
trigger increases in hyperactive and antisocial behaviors in children who previously have been diagnosed
with ADHD. If true, then the reappearance of AD/HD symptoms within a classroom setting that may be
routinely attributed to tachyphylaxis (i.e., a progressive unresponsiveness to stimulant medication) could,
in truth, be due to an unrecognized mismatch between increasing environmental expectations and a
particular student's academic abilities.
Writing and AD/HD
Denckla (1996) has confirmed that the overwhelming majority of children with AD/HD suffers from poor
handwriting and has suggested that the learning and habit formation of the very procedure of handwriting
may be problematic for children with this disorder. Similarly, Cherkes-Julkowski, Sharp and Stolzenberg
(1997) reported that 92 of 100 students referred to their practices had been documented to struggle with
significant written language disabilities.
For individuals who struggle with the mechanics of writing, writing speed may be so slow that it disrupts
their efforts to maintain the cohesiveness of their thoughts (Graham, Harris, MacArthur & Schwartz, 1991).
Even after receiving years of remedial instruction, they often will continue to struggle with the basic
mechanics of writing, e.g., letter formation. Yet, when they are permitted to dictate their responses, these
same students have been shown to be capable of producing essays that are superior in content and form
(both qualitatively and quantitatively) to previous written efforts. In fact, the dictated essays in the Graham
et al. study were four to five times longer than previous written attempts, and they were completed at a rate
that was nine times faster than writing and twenty times faster than typing.
Spelling difficulty also can adversely affect a child's ability to produce quality written output. According to
August and Garfinkel (1990), Frith found that there were dyslexic children who could read at grade
appropriate levels but who still had very severe spelling problems. Frith proposed that severe spelling
impairment, rather than reading problems, might characterize the older patient with AD/HD plus a comorbid
reading disability (AD/HD+RD). Smart et al. (1996) confirmed that over 80% of children with reading
disabilities were also behind in spelling. Cherkes-Julkowski et al. (1997) noted that children with AD/HD
often do not attend to the important orthographic characteristics of printed words and thus fail to learn the
morpho-phonemic principles needed to spell. Consequently, spelling skills in AD/HD children frequently do
not progress beyond the awareness of a word's basic phonological features.
Denckla (1996) describes the retrieval processes in children with AD/HD as impulsive, inefficient, and
disorganized, and notes that such problems could be expected to cause even the brightest kids to do
worse as they encounter the demands of each successively higher grade level in school. According to
Denckla, even if these AD/HD children are fortunate enough to overcome their impairments and encode
information sufficiently well to recall it, they will often remain unable to demonstrate their knowledge on
written assignments and tests.
For the child with limited attentional resources, superficial processing during the learning stage may
prevent the retrieval of cohesive content when it is needed. In addition, reduced attention resources may
disrupt efforts by working memory and executive function to hold onto retrieved materials while they are
concurrently tracking spelling, punctuation, grammar, syntax, etc. during a writing activity. In the absence
of age-appropriate automaticity, attention will tend to be directed towards basic word-level or sentence-
level processes at the expense of text-level cohesion, thus potentially producing cognitive overload at the
most elementary levels of the writing process (Cherkes-Julkowski et al., 1997).
Ironically, should students manage to achieve a relative degree of automatization of their writing skills, they
will then be expected to suppress this newly attained, resource-sparing automaticity, in order to leave
language-generation procedures open to metacognitive control. McCutchen (1988), citing several joint
works by Bereiter and Scardamalia, reports that while automated writing practices may reduce cognitive
load and make writing easier, they often result in "retrieve-and-write" procedures where information
retrieved from long-term memory is recorded without any consideration being given to the specific goals of
a writing task. The written product will tend to read like a list of topic-related ideas with little or no evidence
of any true writing style. Despite encouragement from their teachers, many students with writing difficulties
will remain narrowly focused on their assigned topics because any efforts to tailor the text will place
additional demands on limited-capacity attention and working memory systems, which, in turn, may disrupt
other operating processes that have yet to be fully automatized.
Too often, AD/HD patients who struggle with both writing and reading difficulties will refuse to put any effort
into homework assignments. The explanations offered to this physician suggest that the resource-
depleting efforts employed to retrieve superficially processed text may leave at-risk students with
inadequate resources to adequately express their thoughts on paper. (The author has observed that
children with reading difficulties tend to report that they forget what they want to write before they start
writing. Students with writing impairments, on the other hand, frequently assert that they know what they
want to write and could tell the teacher their answers in a 1:1 setting if given the opportunity, but that they
suddenly forget what they want to write while they are trying to write it down. These histories are believed
to reflect (respectively) the consequences of superficial processing during effortful reading and the
depletion of attention and working memory resources by non-automatic writing skills.)
Should these children summon the courage to submit their poorly worded assignments for grading, they
will likely be criticized for continuing to hand in substandard assignments that reflect their ongoing lack of
effort and motivation. Under such circumstances, these students may perceive that increasing their efforts
has not improved past outcomes and that continued efforts are unlikely to alter future results. Should this
lead to a loss of motivation and passive behavior, then the three criteria for learned helplessness will be
fulfilled.
Note-taking and AD/HD
During the taking of lecture notes, numerous operations must run automatically and concurrently in real
time. In addition to the graphomotor, spelling, and working memory demands that make up the writing
process, the student must be able to rapidly retrieve related information from past memory to guide the
organization of newly encountered auditory input. Furthermore, the student must be able to hear,
understand, and track what the teacher is saying while quickly and accurately converting rapidly spoken
words into written text.
Although some children with AD/HD may seem to be adequate listeners under favorable circumstances,
their comprehension can break down in the presence of competing auditory stimuli. These individuals will
tend to experience difficulty with auditory memory tasks and with following sequential instructions (Willeford
& Burleigh as cited in Keith & Engineer, 1991). Even when schools purposely try to place students in
educational settings that appear appropriate to their chronological age level, children with AD/HD and
auditory processing deficits may still find themselves confronted by auditory input that is delivered faster
than they can process (Keith & Engineer, 1991). This will typically lead to a fragmentation of auditory input
that in turn can disrupt a student's learning and note-taking efforts.
Research has shown that children with AD/HD may: (a) be unable to sustain auditory attention for
prolonged periods of time, (b) have greater difficulty processing competing auditory signals, (c) experience
difficulty following through on instructions, especially when they were long and complicated and (d) have
problems related to maturation of the auditory system and hemisphere dominance (as assessed by
auditory continuous performance testing and screenings for central auditory processing disorder) (Keith &
Engineer, 1991). As is true for both reading and writing tasks, it seems likely that any difficulties (non-
automaticity) encountered during the auditory processing sequence will place excessive demands on
attention and working memory resources and increase the chances that system dysfunction will emerge as
a result of resource depletion.
Test-taking and AD/HD
When considering studying and test-taking in children with AD/HD, it is important to consider the
cumulative impact of all of the component processes previously reviewed. These processes start with the
initial processing of text-based and auditory input, and end with the effortful scribing of answers onto paper.
Denckla (1996) notes that there is no evidence to suggest that deficits in consolidation or storage play a
major role in the dysfunction experienced by children with attention-deficit/hyperactivity disorder. However,
encoding processes may be less than optimal due to a deficient application of proactive strategies during
visual and verbal tasks; that is, children with AD/HD tend to spend less time looking at and manipulating
the components of whatever has to be remembered. Students with AD/HD are noted to often fail to employ
the more complex organizing strategies that could assist with later item recall, e.g. grouping separate items
according to their shared features (strawberries and grapes associated as fruit). As a result, the memory
system appears to become overloaded with fragmented bits of information that have been encoded without
the benefit of an orderly frame of reference, making later recall difficult. Denckla suggests that working
memory may prove to be the critical zone of overlap in the cognitive profiles of AD/HD and learning
disability.
Having to divide one's attention during learning interferes with the depth of processing of new information.
The superficial processing of new information makes its subsequent retrieval more dependent on cued
recall and recognition memory and less accessible to free recall efforts (Borcherding et al., 1988;
Weingartner et al., 1980). Interestingly, the free recall difficulties experienced by children with AD/HD may
be associated exclusively with attempts to retrieve written text, as other researchers have reported that
free recall for acoustic input and picture input is not significantly impaired in children with AD/HD (Durso &
Johnson, 1979, 1980; Nelson, Reed & Walling, 1976).
These findings provoke some unsettling questions: What is the possibility that the routine use of text-
based instructional materials might actually prevent many students with attention deficits from being able to
successfully recall learned information during testing? Given the frequency of significant writing
impairments in children with ADHD, what is the possibility that the routine use of timed written tests might
actually prevent many students with AD/HD from being able to successfully demonstrate their true
understanding of course content? And finally, if printed texts and written tests remain entrenched as the
primary steppingstones to academic achievement, what is the likelihood that school failure will continue to
be one of the most reproducible findings in studies of children with the AD/HD syndrome (Semrud-
Clikeman et al., 1992)?
A potential link between AD/HD and learning disabilities
Although twin studies indicate that AD/HD and LD are transmitted independently within families (Gillis,
Gilger, Pennington & DeFries, 1992), this finding may be a moot point. Research looking at mating
patterns has discovered that parents with AD/HD are more likely than non-AD/HD parents to have selected
a spouse with learning disabilities (Faraone, Biederman, Lehman, et al., 1993). Consequently, children
who have at least one parent with AD/HD may be more likely than their non-AD/HD classmates to receive
at least half of their genetic code from a parent with potentially heritable learning impairments.
The author therefore employs a modified form of the structured student interview during his initial office
visit with parents to document any specific academic impairments that might have plagued a child's mother
and father throughout their early school years. Time and again, the personal school histories recounted by
these parents lend credence to the detailed self-reports of academic dysfunction that are provided by their
children at the next office visit.
Beware ability-achievement discrepancy determinations
Given the preceding findings, it is troubling to consider how often AD/HD students who have been noted to
have significant reading and writing delays in the elementary school classroom seem to be denied
remedial intervention and classroom accommodations because the presence of a learning disability has
been ruled out by "non-discrepant" scores derived from standardized ability-achievement testing. This
diagnostic rigidity appears to be tied to the relatively inflexible criteria of current learning disability
determination guidelines. Gunderson and Siegel (2001) cite the following two examples:
1) A specific learning disability may be found if (1) the child does not achieve commensurate with his or her
age and ability when provided with appropriate educational experiences, and (2) the child has a severe
discrepancy between achievement and intellectual ability in one or more areas relating to communication
skills and mathematical abilities. (United States Department of Education, 1977, p. 65083)
2) A learning disability exists if the student has "an IQ of 70 or higher, and a severe discrepancy between
intellectual ability and academic achievement in one or more areas" (US Individuals with Disabilities Act
(IDEA), 1990, Section 1401).
These types of strict definitions persist despite the fact that numerous well-respected researchers have
challenged the validity of using such discrepancy scores to diagnose learning disabilities. For example,
Gardner (1993) notes: "...at the very time when IQ-style thinking has made unprecedented inroads into
thinking about educational programs, the slender scientific base on which it was created has almost
completely crumbled" (p. 70). Sternberg and Grigorenko (1999) share similar concerns:
The conventional way in which learning disabilities are defined and recognized -- in terms of differences
between IQ and reading skill -- is, and must be, wrong (p. 43).... Even if one accepts IQ's at face value,
they are problematic because they are confounded with verbal and reading skills (p. 52).... The
comprehension skills needed to understand the material on the IQ test overlap with the comprehension
skills measured by reading tests. Thus, subtracting reading scores from IQ scores yields an invalid result
(p. 53).... We believe, on the basis of these various arguments, that IQ has no place at all in the diagnosis
of learning disabilities (p. 64).
Francis, Fletcher, and Shaywitz (1996) emphasize that "the historically prominent role of IQ tests for
identifying children with learning and/or language disabilities is conceptually and psychometrically
unwarranted" (p. 132). Because most individuals with learning disabilities have deficiencies in one or more
of the component skills that are part of the IQ tests, their scores are an underestimate of their true
competence (Gunderson & Siegel, 2001). Gunderson and Siegel point out that there is a reciprocal
relationship between reading and IQ performance, such that children with reading impairments will tend to
read less and, therefore, will fail to develop the skills and information needed to achieve the high IQ scores
required to meet ability-achievement discrepancy criteria.
Vellutino, Scanlon, and Lyon (2000) conclude that IQ-achievement discrepancy measures do not
reliably distinguish between disabled and non-disabled readers, nor do they distinguish between children
who are difficult to remediate and those who are readily remediated. These authors argue that there is
strong research-based evidence to justify abandoning the use of the IQ-achievement discrepancy as a
basic criterion for defining reading disability.
Despite such well-documented concerns, many professionals continue to routinely accept "non-discrepant"
determinations at face value and thus fail to adequately appreciate a student's true need for classroom
accommodations and remediation services. The point here is not to assign blame; nor is there any intent
to become involved in the heated debate surrounding learning disability criteria. The goal is simply to
initiate a perceptual change: traditional perspectives relating to AD/HD and chronic academic
underachievement must be rethought.
School-induced inattention, distractibility, hyperactivity, and impulsivity
This article has reviewed research supporting the proposition that inappropriate instructional strategies
within a classroom setting have the potential to induce a clinical state of attention deficit that may be nearly
indistinguishable from classic AD/HD. According to the proposed paradigm, the likelihood of encountering
clinically significant attention deficits within the classroom becomes predicated on:
1) the abilities / skills of an individual: The better the "match" between a student's unique abilities / skills
and the elements of a presented task, the more likely it is that the appropriate response will be automatic.
Automaticity permits tasks to be performed quickly and easily while placing minimal demands on the
capacity-limited attention, working memory, and executive function systems (Cherkes-Julkowski et al.,
1997).
2) the demands of a particular circumstance: In the absence of automaticity, increasing the rate, volume,
or complexity of tasks within an environment will ultimately place a greater demand on a student's limited
attention resources (Levine, 1994).
3) the residual capacity of the attention system: The functional status of working memory and executive
function is closely tied to the availability of attention resources. Resource depletion may rapidly ensue
whenever an at-risk student is: (a) required to rely on non-automatized skills, (b) forced to divide limited
attention during dual-task activities, or (c) confronted by inescapable stress (especially fear of failure)
within the home or classroom environment.
This author asserts that any circumstances that place excessive demands on the capacity-limited
attention, working memory, and executive function systems inevitably will move a student closer to a state
of resource depletion within the PAM-circuit. In the presence of unremitting task-ability dyscongruence, an
induced attention deficit will eventually emerge and disrupt the performance of non-automatic tasks. These
attention deficits will become increasingly evident whenever a student is required to perform two or more
non-automatic tasks concurrently (e.g., decoding of written text, processing of auditory input, retrieval of
superficially processed data, legibly writing correctly-spelled words on a page, tracking and adjusting
written essays to meet the requirements of specific test questions or assignment guidelines).
The "attention deficit" phenomenon thus becomes a generic clinical state that can be caused either by a
lack of baseline attention stores or by an excessive environmental depletion of available attention
resources. While students with true primary AD/HD might be at greater risk for induced dysfunction given
their limited attention reserves, any condition capable of overwhelming an individual's existing residual
attention capacity can potentially activate the same final pathway and result in an emergent clinical
syndrome that may be indistinguishable from primary AD/HD. Characteristic symptoms typically will include:
inattention, distractibility, and, as a result of PFC-exhaustion, the disinhibition of automatic behaviors.
Given that these symptoms are incompatible with academic success within the traditional classroom,
encounters with recurring failure will become more likely. In the presence of learning difficulties (i.e., non-
automaticity) the process becomes reiterative, with increased demands leading to greater reductions in
attention stores that, in turn, further disrupt intentional learning and performance efforts while liberating
additional unintended behaviors.
As the student's encounters with recurring academic dysfunction, repeated punishments, and inevitable
humiliation within the classroom mount up, it is likely that the student will experience inescapable stress.
This may lead to an evolving learned helplessness characterized by impaired PFC function (Arnsten,
2000), alterations in attention (Minor, Jackson, et al., 1984), an increased susceptibility to environmental
distractors and impaired learning (Jackson, Alexander, et al., 1980; Minor, Pelleymounter, et al., 1988),
persistent behavioral disinhibition despite timely punishment (Jackson, Maier, et al., 1978), an increased
vulnerability to subsequent stress (Anisman & Sklar, 1979), and the emergence of escape behaviors
(Rosellini & Seligman, 1975).
Learned helplessness can potentially be triggered by a student's failure to experience reward after effort (i.
e., extinction) (Rosellini & Seligman, 1975), encounters with environmental cues that have been associated
with inescapable stress in the past (Desiderato & Newman, 1971; Mineka et al., 1984; Mowrer & Viek,
1954), the expectation of inescapable stress (Peterson et al., 1993) and even the awarding of unearned
rewards (Altenor et al., 1977). If the student continues to be exposed to aversive experiences under
inescapable conditions, there is likely to emerge a loss of incentive (i.e., a reduced motivation to try)
(Maier & Seligman, 1976), the development of passive behaviors (Peterson, et al., 1993), and evolving
emotional changes that may progress from anxiety to depression (Maier & Seligman, 1976).
Once one is able to appreciate how dual-task interference, environmental stress, and learned
helplessness can induce attention "deficits" and provoke unintended automatic responses, it then
becomes easier to perceive how inappropriate educational settings can adversely impact on the clinical
status of children with "true" AD/HD and promote an AD/HD-like syndrome in students confronted by
significant learning difficulties. Given this possibility, it is crucial that learning and testing activities be
carefully designed to assure that all students are protected from the inadvertent introduction of dual-task
interference and inescapable stress into their school experiences, especially those students who have
AD/HD, learning disabilities, or both. This principle clearly must become the cornerstone of all future
intervention strategies.
In order to achieve this goal, professionals who are involved in the care of at-risk students will need to
develop an appreciation for the dynamics at work within the educational environment of these children.
Important variables include: (a) the unique skill profile of each student under consideration, (b) the unique
teaching styles of all classroom instructors, and (c) the potential impact of overlooked learning difficulties
and inappropriate instructional methods on the emergence of attention deficits and behavioral dysfunction
in both the school and home environments.
Pharmacotherapeutic considerations
The possibility that persistent or recurring attention deficits within the classroom may be due to excessive
task demands or inappropriate instructional techniques rather than a primary attention-deficit/hyperactivity
disorder must always be considered whenever one is trying to decide whether to increase the dose of a
prescribed AD/HD medication. While clinical experience suggests, and research confirms, that the
appropriate use of stimulant medication may lead to the enhancement of reading (Cherkes-Julkowski et al.,
1997; Dykman, 1991; Richardson, Kupietz, Winsberg, Maitinsky, & Mendell, 1988;), motor coordination
and performance (Knights & Hinton, 1969), auditory processing skills (Keith & Engineer, 1991; Willeford &
Burleigh, 1985) and free recall (Weingartner et al., 1980) in students with AD/HD, the prescribing of ever-
increasing doses of psychostimulants in the presence of needless resource depletion within the
educational setting may be unjustified. For no matter how fast one pours psychostimulants into the
cognitive processing "bucket", there will be no keeping up with the losses brought about by the ever-
enlarging "hole" of progressive ability-demand discrepancy.
Despite the fact that the American Academy of Pediatrics has highlighted the MTA study's suggestion that
teacher information might be more useful than parent-derived information when titrating AD/HD medication
to derive maximum benefit (AAP, 2001), the practice of reflexively increasing a child's prescribed doses of
stimulants in response to the well-intentioned requests of educators for better AD/HD coverage needs to
be challenged. Before employing larger doses of medication, the prescribing physician needs to determine
whether a child is doing well when engaged in activities other than reading or writing (or prolonged
listening in the case of a student with a central auditory processing deficit). Confirmation that a student's
dysfunction is limited to classroom- or homework- related activities ought to prompt the physician, parents,
and educators to search for unrecognized ability-demand mismatches within the educational setting that
may be inducing the exacerbation of AD/HD symptoms displayed by a student.
Should an apparent mismatch be found, it becomes incumbent upon the prescribing physician to ensure
that the child's school appropriately addresses the identified instructional pathology. For, while it is true
that adjusting a student's medication may serve to temporarily suppress automatic behaviors and
transiently increase the ability of the PAM-circuit to perform under unfavorable classroom conditions, these
stop-gap medical interventions fail to address what this article asserts may be the true underlying problem.
As a consequence of either cognitive overload or emotional duress, environmental adversity within an
educational setting can potentially induce attention deficits and behavioral disinhibition that may be
virtually indistinguishable from the clinical signs and symptoms of attention-deficit/hyperactivity disorder. If
the injudicious use of psychostimulants is to be avoided, then physicians and educators must ensure that
all students, especially those experiencing academic failure, will be protected from the inadvertent
introduction of dual-task interference and inescapable stress into their daily classroom experiences.
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Figure Captions
Figure 1. Lateral views of the left hemisphere and sagittal view of the right hemisphere.
Figure 2. Non-automatic versus automatic processing.
Figure 3. Inhibition, interference, disinhibition, and learned helplessness.
Copyright 2002 Richard Herklots
Used with Permission: Birth To Success, LLC
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