Reading by design: Evolutionary psychology and the neuropsychology of reading.
Reading is arguably one of the most important human neuropsychological processes. Language is, of course, of primordial importance; it articulates human thought and emotion, expresses intimacy, shapes the activity of others, and makes possible the development of the mind and of personhood. Written communication records the mind. All cultures develop over time, but literacy (writing and reading) makes complex cultures possible; without it, cultures are completely dependent upon oral traditions and the limits of human memory. Cumulative cultural information, preserved over time in written form, made the development of economic practices, legal practices, religious practices, literature, philosophy, mathematics, science, and technology possible. So, although the following statement deserves proper qualification (Olson, 1994), the acquisition of literacy (enhanced by the invention of the printing press and now the computer) singularly made possible human culture as we know it today.
But how did humans acquire the cognitive abilities that make literacy possible? Reading is an enormously challenging task requiring the proper functioning of a number of neurological subsystems (and pathways) working extremely quickly in concert, a task that took decades to duplicate in artificial intelligence systems (whereas, conversely, advanced mathematical computations that normal humans cannot perform have been performed by computers for decades). How are we to account for the development in our species of this degree of complexity and speed at the cognitive and neurological levels?
In our culture, naturalistic evolution provides the overwhelmingly influential causal explanatory model for biological life. Although modern psychology has, since its inception, assumed evolution, over the past decade a growing group of psychologists have sought to explain the entire structure of the human mind on the basis of evolutionary principles, and in so doing has developed an influential, new perspective within the field: evolutionary psychology (EP). The main purpose of this article is to see if EP theory coheres well with neuropsychological research on reading.
MODULES AND EVOLUTIONARY PSYCHOLOGY
EP posits that the human mind is composed of hundreds of cognitive mechanisms, called modules, each of which was naturally selected through interaction with the environment within which the first humans arose (the "Environment of Evolutionary Adaptation," EEA). Each mechanism was naturally selected because it contributed to the survival and/or reproduction of the early humans who possessed it. Fodor (1983) was one of the first thinkers influenced by cognitive science to argue that the human brain is organized into a number of "modules" or "input systems." He defined these modules as fixed, domain-specific, mandatory, stimulus-driven, and autonomous from other systems in the brain. Each module, then, encapsulates a specific type of information. Other systems can only access the output of a module. Evidence supporting modularity includes the existence of neural regions dedicated to specific psychological functions and observations of human behavior that are difficult to account for without some neurological "pre-wiring."
Visual perception provides a good example of a module. The processing of vision, from lower animals like fish to humans, occurs in the occipital lobes. The speed of visual perception acquisition, its critical period, its complexity, and the stimulus specificity of individual neurons all point to innate predispositions for vision (Cosmides & Tooby, 1992, pp. 58-59). In addition, visual perception is resistant to external input and cannot be overridden by it. For example, one still sees an optical illusion like a mirage, despite factual knowledge proving the image false. (Language offers another well-known example of a module.)
Fodor (1983) offered a fairly rigid definition of modules and believed there are relatively few of them in the human brain. More controversial is the argument of evolutionary psychologists (EPs) that the brain is composed of hundreds of modules, the "massive modularity hypothesis" (Samuels, 1998). EP argues against the notion that a domain-general intelligence could efficiently solve all the problems facing early humans (Cosmides & Tooby, 1992). Rather, they believe that many individual cognitive mechanisms arose through genetic variation, which were preserved because they solved specific adaptive problems. Those mechanisms (or "mental organs") that promoted human survival within the EEA were retained in the human genome and continue to affect human behavior today (regardless of their suitability to modern culture). EP's examples of modules are extensive, and include such things as mate preferences, jealousy, altruism, care of kin, self-awareness, justice, attachment behavior, sex differences, emotion recogni tion, cheating detection, theory of mind, basic assumptions about the physical world, and face recognition, to name a few (Barkow, Cosmides, & Tooby, 1992; Buss, 1999; Crawford & Krebs, 1998; Pinker, 1994). In addition to being domain-specific, these modules would have to be universal to all humans in all cultures and innate (i.e., largely determined by genetic factors).
The Massive Modularity Hypothesis provides one of the most distinct and defining assumptions of EP and is especially valuable since it can be subjected to some empirical investigation. For example, the universality of a psychological phenomenon can be assessed with cross-cultural research (see Buss, 1989). And domain specificity is demonstrated partly in the occurrence of the loss of specific capabilities, such as language comprehension, due to specific regional brain damage. Even though many question EP's massive modularity hypothesis (e.g. Gould, 1997; Karmiloff-Smith, 1992; Rose & Rose, 2000; Samuels, 1998), EP's growing influence is due to an impressive body of documentation that has thus far been accumulated (Buss, 1999; Buss, Haselton, Shackelford, Bleske, & Wakefield, 1998), particularly in reference to reproductive and child-rearing behavior.
But what about reading? Evolutionists commonly assert that the human mind/brain evolved into its present form somewhere between 100,000 to 300,000 years ago (Byrne, 1995; Cartwright, 2000; Pinker, 1994). As a central activity promoting this encephalization, language evolved to help hominids adapt better to their environment by making possible a complex level of cooperation. However, spoken communication was in place for thousands of years before a written symbol system developed; there is no evidence for literacy until six to eight thousand years ago. So it is inconceivable, given evolutionary assumptions, that reading abilities would be genetically wired into the brain. In fact, it is likely that most readers of this article who are committed evolutionists and have given reading much thought will find the questions driving this article implausible in the extreme. Nevertheless, we believe, at the very least, that there is sufficient evidence to show that the neuropsychology of reading poses a serious problem for evolutionary psychology that could have broad implications for the EP project.
AN OVERVIEW OF THE COGNITION OF READING
Successful reading requires the proper functioning of a number of nearly simultaneous mental activities. Reading involves the intersection of four discrete cueing systems or subprocesses: the phonological cueing system, which is used in auditory word recognition (phonemes are the sounds or auditory codes of a language, which make up spoken words); the orthographic cueing system, which is used in visual word recognition (graphemes are the written symbols of the sounds of verbal expression); the graphophonic cueing system, which are the rules for connecting graphemes with phonemes; and the semantic cueing system, which is used to understand the meaning of words and text. Reading involves the ability to recognize the words, phrases, and sentences in printed text, and to give meaning to the text based upon prior background knowledge and experience.
Reading in young children is, of course, based on exposure to oral language. By the time children are five, they have acquired a fairly large set of words learned auditorally, which is called a phonological lexicon, and it is conceptually and neurologically distinct from but closely associated with a semantic lexicon. As reading instruction is begun and children learn to match visual symbols with specific sounds (called decoding), they develop a phonological awareness of the sounds of their language. The visual stimuli are first processed by feature detectors, structures of the visual processing system that distinguish small differences in marks on the page (e.g., "c" versus an "e") and that are unique to specific language scripts (the language's orthography). Gradually, patterns of letters and words are encoded (Massaro & Sanocki, 1993; Raynor, 1996). Formal study of phonetically consistent words and memory of high frequency words with novel orthographic patterns lay the foundation for automaticity in the d ecoding process (Corcos & Willows, 1993). Greater competence in instant word recognition propels the developing reader into fluent reading as the identifying of letter and word patterns becomes routinized (Corcos & Willows, 1993), resulting in the formation of a large visually encoded, orthographic lexicon of words. Eventually, letters in words come to be perceived more readily than individual letters by themselves (called the "word superiority effect," Just & Carpenter, 1987)! Readers also learn to move their eyes in fixations and saccades that facilitate reading (Everatt, McCorquodale, Smith, Culverwell, Wilks, Evans, Kay, & Baker, 1999). Over time, proficient readers may even skip words as they skillfully skim and scan text for meaning. A number of researchers have also noted that visually-presented words can directly stimulate word meaning or they can first call up relevant phonological information and then activate word meanings. These two pathways form the "dual-process" model of reading. All in all, th e storing of thousands of letter and word patterns, the rapid identifying and processing of them, and the meaning they convey reflect extraordinary neurological, perceptual, and cognitive abilities.
EVIDENCE FOR A READING MODULE
The Neuropsychology of Normal Reading
The human mind is based in neurological activity such that every cognitive process has a corresponding neural architecture. Over the past 20 years, a number of neuroimaging, electrical stimulation, and recording methods have been used to identify the neurological substrates related specifically to the reading process through the study of the brains of normal Ss and reading disabled Ss engaged in various reading tasks. Due to the widespread use of these research technologies over the past decade, a tremendous amount of information has been recently learned about the brain's activities during reading. These techniques, which confirm earlier surgical investigations, have found generally consistent similarities in brain regions and activity patterns for reading (Black & Behrmann, 1994; Shaywitz et al., 2000; although the precise neural architecture for reading varies slightly from individual to individual; McQuillen, 2000; Robertson, 2000).
A number of specific neural regions are activated during reading. Because reading obviously relies on language, as we would expect, reading involves activity in the temporal and frontal lobes of the left hemisphere (LH) where auditory language processing occurs (Shaywitz et al., 2000). Lexical-semantic information in reading has been found to be processed in the posterior temporal-parietal LH regions, anterior cingulate, the right lateral cerebellum, the middle temporal LH regions (for comprehension tasks; Shaywitz et al., 2000), and the inferior frontal and prefrontal regions (Demb, Poldrack, & Gabrieli, 1999; Neville & Bavelier, 2000; Posner, Abdullaer, McCandliss, & Sereno, 1999; Thompson, 2000, p. 451). Individual cells in the prefrontal region have been found to be responsive to meaning during reading (Posner et al., 1999). In addition, the posterior temporo-parietal region is also implicated in phonological processing, suggesting that this region is "multifunctional" (Shaywitz et al., 2000), dealing wi th both lexical-semantic and phonological representations. Regions around Broca's area in the frontal lobe are also activated in phonological processing (Demb, Poldrack, & Gabrieli, 1999; Habib & Demonet, 2000). Strata in the left frontal lobe responsible for grammatical understanding are likewise activated in reading (Shaywitz et al., 2000).
In addition to activations in language areas, reading unsurprisingly activates the visual cortex. Regions uniquely active in reading have been identified in the striate and extrastriate cortex of both occipital lobes, specifically the inferior extrastriate region (Shaywitz et al., 2000; Habib & Demonet, 2000), the medial extrastriate region (Petersen, Fox, Snyder, & Raichle, 1990), as well as the left ventral occipital-temporal junction (Posner et al., 1999), the left posterior middle temporal gyrus (Howard, Patterson, Wise, Brown, Friston, Weller, & Frackowiak, 1992), and the left inferior temporal lobe (Habib & Demonet, 2000; Shaywitz et al., 2000) where visual stimuli like letters and words are processed and stored orthographic representations are activated, resulting in one's orthographic lexicon. These regions appear to be responsible for the "visual word-form system," a lexicon specialized for reading (Cossu, 1999, p. 218; Posner et al., 1999). The corpus callosum is also involved in reading because vi sual information from both the right and left visual fields must be integrated before being processed in the LH (Thompson, 2000).
Another region of cortex implicated in reading is the LH's angular gyrus. This area of the parietal region, the lobe generally implicated in cross-modal sensory integration, is utilized for the mapping of orthographic information on to phonological representations of language and the final organization of letters into words (Friedman, Ween, & Albert, 1995; Shaywitz et al., 2000; Thompson, 2000). In addition, a region in the superior temporal lobe just anterior to the angular gyrus has also been found to be active on phonological reading tasks (Posner et al., 1999).
Hemispheric differences in reading. Overall, auditory and expressive language processing is located in the LH, so it is no surprise that most reading processing likewise occurs in the LH. However, some qualifications regarding this LH dominance in reading should be made. Whereas right-handed adults who lose their LH suffer severe and largely permanent language and reading impairment, children without a LH can still acquire language and learn to read (Just & Carpenter, 1987). Also, Lecours (1989) found that school-educated literates were more likely to be LH dominant on linguistic tasks, while illiterates used the RH more.
Most notably, Shaywitz et al. (2000) has reported that for several tasks involving phonological decisions about visually-presented words, significant left-lateralization occurred in males, with more bilateral activation in females in left and right prestriate and prefrontal areas, suggesting some sex differences in reading. This has been explained by Pugh et al. (cited in Carr, 1999) as due to males using more whole-word analyses, which are more left-lateralized. Evolutionists like Carr suggest that there may be more individual differences, like sex differences, in reading because the visual and language systems evolved independently of each other and reading is a relatively recent, culturally-developed cognitive ability. However, there is generally no more individual variability for reading than there is for auditory and expressive language activity.
A temporal course of activation. The temporal course of cortical activation has been observed when normal Ss are presented with words, pseudo-words, and letter strings (Breier, Simos, Zouridakis, & Papanicolaou, 1999; Posner et al., 1999). Activation begins bilaterally in the visual cortex. However, LH activation occurs only with word-like stimuli, whereas the RH is activated by all types of letter strings (cf. also Chase, 1996; Demb, Poldrack, Gabrieli, 1999; Peterson, Fox, Snyder, & Raichle, 1990). And whereas numbers activate cortex bilaterally, letters primarily activate left posterior regions. In a study only of phonological processing, activation proceeded to the LH basal temporal areas, on to the LH angular gyrus and inferior frontal lobe, and ended with activity in the LH medial temporal and posterior superior temporal lobe (Breier et al., 1999). However, Posner et al. (1999) reported some continuing bilateral activation after visual stimuli is processed, in occipital, parietal, and anterior temporal sites during lexical and phonological processing.
A developmental course for the word-form system.
At least one study has found that neurological activation patterns of the word-form system normally seen in adults do not appear in 4 and 7 year olds, but only 10 year olds (McCandliss, 1997, cited in Posner et al., 1999). So the neural architecture for whole word recognition does not appear to stabilize into adult patterns until late childhood.
All the above research points to the development of identifiable neural regions dedicated to reading across Ss. Additional support in neuropsychopathology will be examined next.
The Neuropsychology of Various Reading Disabilities
Dyslexia. As with most psychological disorders, dyslexia actually refers to a family of disorders, in this case, that make reading difficult, despite a lack of deficits in overall intellectual and language functioning. Reading disorders can be acquired as a result of insults to neural regions involved in reading, or developmental, due to abnormal neurological ontogenesis (Marshall, 1989). Many different neuropsychological deficits have been found that can contribute to reading problems, including magnocellular visual processing, visuo-perceptual processes, sequencing ability, phonemic segmentation, phonological awareness, attention, and morphological processing (Castles, Coltheart, Savage, Bates, & Reid, 1996; Everatt, Corquodale, Smith, Culverwell, Wilks, Evans, Kay, & Baker, 1999; Farah, 1999; Seymour & Evans, 1993; Shaywitz et al., 2000). In general, these deficits all appear to derive from developmental or acquired damage to one of the four subcomponents of reading or to the pathways between them.
Three major types of dyslexia have been identified: (a) phonological dyslexia (i.e., poor nonword reading, e.g., /slank/, but normal auditory nonword repetition); (b) surface dyslexia (i.e., problems with unusual orthography-irregular words like "lieutenant"--and whole word storage); and (c) deep dyslexia (i.e., phonological problems--difficulties with decoding nonwords/pseudo-words and some semantic problems-saying "heavy" for /light/ though this may be simply a more extreme form of phonological dyslexia) (Friedman, Ween, & Albert, 1995; Funnell, 2000a; Funnell, 2000b; Patterson & Ralph, 1999).
A variety of neurological abnormalities have been associated with dyslexia. To begin with, most adults (70%) have bilateral asymmetry of the planum temporale in the temporal lobe, something not usually seen in those with developmental dyslexia, which could mean less neural tissue in the phonological processing area than typical (Cossu, 1999; Galaburda, Rosen & Sherman, 1989; Habib & Demonet, 2000; Hynd, 1995; though the evidence is disputed, cf. Shaywitz et al., 2000).
Galaburda and his colleagues have also repeatedly found small ectopias and displasias in brains of people with developmental dyslexia, usually located throughout the inferior left frontal, superior left temporal, and right frontal regions, as well as the lateral posterior and medial geniculate nuclei of the thalamus bilaterally (Galaburda, Sherman, Rosen, Aboitiz, & Geschwind, 1985; Rosen, Sherman, & Galaburda, 1993). Although such abnormalities are not specific to dyslexia, their prevalence in the brains of those with dyslexia suggests a possible regional neural risk factor.
Reduced blood flow in the parietal region near the angular and supramarginal gyri has been found in dyslexic Ss relative to controls (Demb, Poldrack, Gabrieli, 1999; Hynd, 1995). Similarly, reduced activity has been found in the brains of persons with dyslexia in the left inferior temporo-occipital region (Salmelin, Service, Kiesila, Uutela, & Salonen, 1996) and left temporo-parietal regions (Rumsey, Andreason, Zametkin, Aquino, King, Hamburber, Pikus, Rapoport, & Cohen, 1992; Shaywitz et al., 2000). In general, less activation is noted in persons with dyslexia in the angular gyrus (Shaywitz et al., 2000).
Studies have also found an increased degree of activity in the left premotor region of dyslexics (Habib & Demonet, 2000; Price, 2000), with a few individuals showing greater right hemispheric activity (Price, 2000). This appears to be related to strategic compensation within the frontal cortex and RH (Shaywitz, 1999). However, there appears to be a dissociation between the frontal and temporal regions on reading tasks. Paulesu, Frith, Snowling, Gallagher, Morton, Frackowiak, and Frith (1996) found brains of dyslexics activated frontal or temporal regions in different reading tasks, but not in concert, contrary to controls.
In addition, visual processing problems have been found in dyslexic brains. For example, the extrastriate regions were not activated by persons with dyslexia in response to moving stimuli (though not a stationary object; Eden, VanMeter, Rumsey, Maison, Woods, & Zeffiro, 1996). A number of studies have found some dyslexics have problems with motion detection, global form, and temporal resolution in visual processing, associated with the magno-cellular visual system (Habib & Demonet, 2000; Lehmkuhle, 1993; Lovegrove & Williams, 1993; Shaywitz et al., 2000; Watson, 2000). Shaywitz et al. (2000) found that a number of regions within the striate and extratriate cortex (as well as other regions) are not activated by dyslexics during tasks that required phonological processing.
Alexia. A particularly striking reading disability is alexia. Alexia is virtually synonymous with letter-by-letter reading in which individuals have no automatic ability to organize letters into whole words (like normal readers), so they cannot quickly say visual words presented to them. However, if given more time, they can sound out the individual letters and construct the word with conscious effort. It occurs particularly with damage to the angular gyrus, confirming its role in the formation of whole words (Friedman, Ween, & Albert, 1995; cf. Small, Flores, & Noll, 1998). Letter-by-letter reading treats the letters like individual objects (Saffran & Coslett, 2000). Pure alexics who could not do letter-by-letter reading also had object agnosia (i.e., an inability to identify objects).
Pure alexia "arises from damage to posterior regions of the brain that disconnects the major pathways that link the visual areas involved in recognizing written words with the more anterior language areas involved in comprehending and pronouncing words" (Funnell, 2000b, p. 8; cf. Black & Behrmann, 1994, p. 351). Alexics do not have direct access to the "whole word" system available through phonological processing (Black & Behrmann, 1994; even though some have access to a word recognition system in the RH, Funnell, 2000b). Significantly, depending on the precise location of the damage, some individuals can read but not write, or write but not read what they wrote, or do neither. And some alexics have difficulty with letter identification, but no problem with number identification, indicating distinct areas of cortex for these two visual pattern identification systems (Black & Behrmann, 1994).
Summary of research on the neuropsychology of reading and reading disabilities. This research raises questions about the phylogenetic development of reading ability. The human brain remains remarkably plastic throughout life until late adulthood in terms of its ability to store new information providing that the particular neuropsychological component in question has been formed. If humans have developed a normal neural substrate dedicated to a specific ability, such as language comprehension, then humans may use that ability and change their neural structure through storing new semantic information (e.g., new vocabulary words, visual objects, or musical melodies). However, if the neural substrate dedicated to that specific processing ability does not develop properly or is damaged after that structure has developed sufficiently, other parts of the brain cannot easily develop or recover that function. How is it then that the neural substrates dedicated to the specific cognitive abilities involved in reading are likewise localized and, if relatively undeveloped or damaged late enough in childhood, are similarly resistant to recovery. Does it not seem to be the case that the neural architecture involved in reading functions exactly like the neural architectures that undergird other cognitive functions, like face recognition and language, which are assumed by many evolutionists to have specifically evolved? Perhaps this is because the brain was specifically designed for reading, just as much as it was specifically designed for language, face recognition, child-rearing, and mating?
Pinker (1994), among many others, argues that the location of an identifiable neural region for language processing provides compelling evidence for a language module. Not all scholars agree with Pinker about a language module, but by Pinker's standard, does not the previously summarized reading research suggest the human brain also possesses a reading module? The contemporary research on reading and reading problems that we have examined demonstrate a degree of localization that would not be predicted by standard accounts of reading development based in naturalistic evolution. This localization would seem to imply some genetic determination, for if no genetic programming were involved, the allotment of neural tissue to reading would be based solely on individual experience and would be due strictly to chance. Consequently, there would likely be much greater variability in the location of these regions than is observed. If we compare the allotment patterns to the allotment of files/programs on a computer har d drive, which are genuinely assigned on the basis of chance, the consistency in the allotment of the reading substrates would seem to be highly statistically significant, that is, the consistency in the location of the neural strata for reading across Ss occurs with a probability far above chance.
Admittedly, we would not expect all regions of the brain to have an equal probability of being assigned by chance as reading substrata because reading is dependent upon language and language regions are basically located in the temporal and frontal lobes of the LH. Nevertheless, even within the range of neural tissue possibilities adjacent to the language sections, the consistency of location of the reading regions is significant. Moreover, it is not merely that the reading regions are located between the visual cortex and the language cortex because the angular gyrus, a pivotal structure for reading, is not on a direct route between those cortices. At the very least, this provides a puzzle that evolutionists conducting reading research have not paid sufficient attention to, likely because the assumption of evolutionary theory so constrains their inquiries.
Hyperlexia is the ability to recognize words far beyond one's ability to comprehend them (Aram & Healy, 1988). Strangely, many with hyperlexia are retarded, autistic, or have other cerebral dysfunctions. Most hyperlexics begin to demonstrate unusual word recognition ability between age 2 and 3! Many develop what looks like a compulsive preoccupation with reading, preferring it to other forms of play, even though they lack understanding of the text. Amazingly, it has been repeatedly reported that some hyperlexics have taught themselves to read (in spire of other mental limitations), and a smaller number "demonstrated reading (word recognition), either prior to or coincident with talking" (Aram & Healy, 1988, p. 82). Cossu & Marshall (1990) report a case of a severely mentally impaired boy who had great difficulty understanding speech, but nevertheless could speak and read fluently without understanding what he spoke or read. All this suggests that visual word recognition abilities can be dissociated from virtu ally all other higher cognitive abilities including semantics.
Gardner (1983, 1999) has argued that certain abilities found in advanced form in some children, even in the face of other deficits ("idiot savants"), provide evidence for a distinct intelligence (a mental "module," he calls it) based in specific neural regions genetically "hard-wired" by evolution. The condition of hyperlexia contributes a fascinating piece of evidence for a neurological substrate specifically dedicated to word recognition (Cossu, 1999), the development of which can be uniquely accelerated in spite of deficient neuronal maturation in other, related areas of the brain. This seems to suggest that brain organization for the word-form system is more similar to language acquisition (e.g., word identification can be self-taught!), may be more internally-driven than externally-driven than researchers have thought, and so may be derived more from genetic causes than standard evolutionary theory could have predicted. Also, hyperlexia (combined with research on dyslexia) calls into question a general-d omain model of reading, that is, reading is simply the application of general intelligence to written communication, since these cases show that the word-form system is functionally independent of virtually all other cognitive skills.
Symbolic Communication, Sensory Deficits, and Brain Activity
Brain activity in blind readers. Braille reading involves tactile (touch) sensory processing in the somato-sensory region of the parietal lobes, language processing in the LH, and spatial processing in the parietal and frontal lobes (Millar, 1997). Nevertheless, occipital brain activity of blind persons is higher than that of blindfolded sighted persons and equal to that of sighted persons with open eyes (Neville & Bavelier, 2000). Braille readers born blind activate the visual cortex in a tactile discrimination task and in Braille reading tasks. However, if they acquired their blindness after the age of 14, activation occurs in the normal parietal regions (Hallett, 2000; Millar, 2000). This puzzling phenomenon is not understood and warrants more research. Perhaps, because hearing is the most informative sensory modality and is still processed in the normal location (the temporal lobes), and the overall sensory input into the brain is lower than normal, the visual cortex of the young blind child comes to be d edicated to processing the second-most-important, incoming sensory information: tactile. Regardless, this constraint suggests there is some organizing principle that we do not understand, but likely the same principle that provides the other evidence of neural allotment in the brain.
But what are we to make of the recent finding that persons born blind and late-blind reading Braille words both activate the same region of the left inferior temporal lobe (BA37) as do seeing persons visually reading words (Buchel, Price, & Friston, 1998)? The location of the processing of Braille reading in this precise location is notable because tactile processing is usually processed in the parietal lobe. The incoming linguistic information mediated by touch is processed along the same pathway into the linguistic portions of the cortex as visual orthographic material. This suggests that BA37 may be a brain region dedicated to the mapping of semantically related symbol patterns, regardless of the sensory modality, on to phonological and lexical representations.
Brain activity in deaf persons using ASL. Researchers have found that the processing of American Sign Language (ASL) processing is more bilateral than usual in auditory language use, involving a greater degree of RH activity, particularly in the posterior region of the parietal lobes. The language system is broadened to include more of the RH because the lexical and syntactic symbols are expressed in movement in space and spatial orientation. However, this bilateral effect was only found in those who had learned ASL as children, not hearing signers who learned as teenagers. Again, there appears to be a critical period for co-opting atypical brain regions for language processing, after which the brain processes sign language using the previously established neural architecture (towards which the system appears to be disposed). In addition, deaf people using ASL process syntax in the anterior portions of the LH and the semantic features of language in its posterior regions, just like normal language users (Ban ich, 1997, p. 305). So the brain learns and processes language solely through visual symbols within roughly the same regions as auditory language learners, suggesting the brain is pre-wired for language in a way not tied to its normal mode of acquisition: through audition. Unfortunately, no research could be located for this article that examined whether ASL users utilized any of the neural substrata dedicated specifically to reading in normal visual readers.
Research on ASL use suggests that the human brain has a significant degree of flexibility (and plasticity) regarding the identification and processing of semantic visual codes. Evolutionists could argue that this flexibility shows the kind of general adaptability in the application of neural tissue to reading that they would expect. However, this line of argument does not help address why, in sensory intact humans, reading abilities are so localized.
Comparison of Additional Evidence for a Language Module with Reading
Many within the neurolinguistic research community believe that the brain has genetically determined mechanisms (i.e., a language module) that make language acquisition and use possible (e.g., Pinker, 1994). If so, noting some similarities and differences between language acquisition, language use, and reading would help us evaluate the case for a reading module.
Genetic basis for reading ability? Pinker (1994) believes that the evidence that exists of a genetic basis for language strengthens the case for a language module. There is also a substantial body of evidence that shows that developmental reading disabilities have a genetic causality (Catts & Kamhi, 1999; Olson, Datta, Gayan, & DeFries, 1999; Pennington & Gilger, 1996). Unquestionably, because of the complexity of human development and reading, as well as the many different neurological sources for reading problems, we cannot say there is a "gene for reading." However, the same objections can be made about the genetics of language ability. The evidence that supports a genetic basis for, at least, some reading disabilities, in the absence of general intellectual deficits, suggests that specific genes may be implicated in reading, leading to the formation of a reading module in the brain.
A period of reading acquisition. Studies of feral children and abused children have demonstrated that human language abilities can only develop normally if children are exposed to a language-rich environment between birth and the age of 5. In the absence of such experiences, language structures do not develop properly, resulting in permanent damage, even though some remediation can occur later. This points to the existence of a "sensitive" period for language acquisition (Spreen, Risser, & Edgell, 1995). There does not appear to be a similar period for reading acquisition because illiterate adults can be taught to read quite well. On the other hand, one cannot accelerate the acquisition of genuine word recognition skills beyond a certain point. This ability typically begins to form during the ages of six and seven in first and second grades. Cossu (1999) cites a study of first graders in which mean errors for sounding out written words and non-words dropped from 35.8 in November to 11.6 in January (although a subgroup of children changed from 60 [out of 60 possible errors] in November to only 55.3 [in June of that year]). So, the majority of children relatively quickly mastered grapheme-to-phoneme rules as the regions of their brains responsible for sight recognition for words matured. A degree of neurological development must occur before word recognition skills can develop (forming a stage of "readiness") and during that period, decoding abilities mature fairly rapidly. However, childhood illiteracy does not permanently damage cognitive structures for reading.
Reading can of course only occur after language abilities have developed. Reading typically would have to happen later because of its dependence on oral language acquisition and the fact that the visual processes involved in reading are being integrated with the previously established auditory linguistic system. However, the existence of adults who become literate in adulthood show that neurons usually dedicated to reading but not utilized until later in life are not destroyed as non-stimulated neurons in the language regions appear to be. This is important evidence against the concept of a reading module. Cortex dedicated to language and vision must be used within a certain time period or the neurons in those regions die, but this is not the case with reading. However, this flexibility does not address the independent evidence pointing to a reading module. Perhaps some capacities are more "hard-wired" than others. It may be that the reading module does not have as rigid a sensitive period as language because reading is not necessary to mature human rationality and personhood the way that language is. Speaking illiterates are able to develop fairly complex cognitive abilities (though usually not formal logical thought). Reading is truly optional to mature human development. This optionality raises questions about a reading module, but it may just reveal reading has some "soft module" characteristics (a less rigid sensitive period) as well as some "hard" (universal location of dedicated neural tissue). Regardless, this fact alone would not provide sufficient evidence to conclusively demonstrate that there is not a reading module.
Speed of reading processing. Mature speech comprehension occurs very rapidly (over 4 words per second; Akmajian, Demers, & Harnish, 1984). This is a phenomenal pace for a highly complex cognitive process, a speed all would assume was ordered by genetics. Similarly, the reader of average intelligence is able to process written language about the same speed (as little as 50 ms and usually less than 250 ms per word; Posner, Abudllaev, McCandliss, & Sereno, 1999; Rayner & Pollatsek, 2000). This degree of processing seems surprising given evolutionary assumptions that humans were not made for this cognitive activity. This speed would seem to transcend by far the perceptual capacities necessary for animal track identification that has been alleged by a few evolutionists to be the adaptive basis for a reading module (cf. Cossu, 1999; Dawkins, 1982, p. 23; Marshall, 1989).
Brain Regions for Non-Reading Mental Modules
Neuropsychological research in the past decade has also found a number of capacities of the human mind/brain that seem to have modular form, besides language. We will take a quick look at some evidence for a few of these other modules to give a little sense of the neuropsychological phenomena that reading ability is closely related to, some of which are predicated by evolutionary theory and some not.
Mathematical abilities. In a review of research on the area, Dehaene (2000) suggests that a region within the intraparietal cortex appears to be prewired to manage specifically numerical quantities, forming "a category-specific system innately biased toward acquiring and manipulating information about numbers" (p. 996). Iacoboni (2000) cites studies of multiplication and logarithm estimation that involves frontoparietal activation. Additional research on persons with acalculia (i.e., difficulties in mathematical computation) further supports the existence of a dedicated neural system for the processing of mathematical symbols and concepts in the left parietal lobe (Levin, Goldstein, & Spiers, 1995). Interestingly, some individuals can identify numbers, but they cannot process arithmetical signs! Black & Behrmann (1994) note that "the frequent dissociation between performance on reading numbers, letters, and words in pure alexia raises the possibility that different anatomical substrates may be involved" (p. 3 52).
Music processing. Reading, playing, composing, and enjoying music occur in identifiable regions of the brain, generally favoring the RH (Batter, 1995). Singing appears to be neurologically distinct from speech (Zatorre cited in Banich, 1997). Listening to music activates regions in the right superior temporal gyrus, and reading music activates a region in the left occipitoparietal junction, dorsal to the language reading region. So, reading musical symbols occurs in a region distinct from the region where linguistic symbols are processed (Banich, 1997). Case studies of individuals, like the composer Ravel, indicate that musical ability is composed of neurologically distinct subskills (sight-reading, composing, and playing a piece). (1)
Distinctions between object, face, and visual word recognition. There also appear to be specific regions of the brain responsible for the recognition of objects (Bachevalier, 1996) as well as faces, that seem analogous to the region involved in word recognition. Neurological insults can lead to a specific deficit in object, face, or word recognition that does not affect the other types of recognition. Agnosia involves the inability to identify objects in the real world (Bauer, 1995). There are many types of agnosia. Some with agnosia have selective categorical disabilities, being unable to identify only animals, plants, or foods. Visual agnosia entails an inability to identify objects by sight. However, there are agnosias for other sensory modalities, such as auditory (inability to identify sounds), tactile (texture or weight), and olfactory (smells) (Bauer, 1995). Some individuals have developed a visual agnosia limited to an inability to label colors. Those with pure prosopagnosia can recognize voices, can assign gender to faces, know the meaning of facial expressions, but cannot recognize familiar faces (Damasio, 1989). In comparing some of these abilities, Puce, Allison, Asgari, Core, and McCarthy (1996) found distinctly different ventral extrastriate regions activated when normal adults were presented with faces, letter-strings, and textures. Object recognition and word recognition brain regions are in the same vicinity (Carr, 1999).
Clearly the development of discrete, independent cortical regions for the recognition of objects, faces, and colors would have adaptive value, and evolutionists are quick to point to these as examples of evolutionary adaptation in humans (e.g., Cosmides & Tooby, 1992). Yet, at the neurological level, there is no way to distinguish these forms of recognition from word recognition. They can only be so distinguished a priori on the basis of evolutionary presuppositions. Furthermore, as in word recognition, naturalistic evolutionary theory is unable to provide an adequate account for the existence of universal mathematical and musical regions of the brain, which are based on natural selection in the EEA (except for simple counting). Such issues deserve further exploration in other articles.
Summary of Arguments for a Reading Module
Before examining the approach evolutionists have taken to the idea of a reading module, a brief summary of the foregoing is offered below.
1. There are identifiable regions of the normal human brain (and pathways between them) dedicated specifically to reading.
2. Reading difficulties result from insults to those regions (and/or pathways) or problems in the development of those regions (and/or pathways).
3. The condition of hyperlexia suggests that the maturation of the specific area of cortex dedicated to word recognition can be accelerated.
4. Braille readers, who were born blind, process braille reading in the same locations as sighted readers process visual text. No research was found that directly compared the neuropsychology of sign language reading and word reading.
5. Research on the genetics of reading disabilities and the speed of the mature reading system compare somewhat favorably with arguments used to defend the modularity of language. There is some evidence for a "readiness" period for reading, but it is a weaker phenomenon than the "sensitive period" that has been found for language acquisition.
6. There is also evidence of other modules for distinct cognitive abilities in adjacent areas, some of which would be predicted by evolutionary theory (e.g., face and object recognition, simple numerical processing) and some of which would not (e.g., music and mathematical processing).
On the basis of these findings, the authors believe that reading ability constitutes what might be called a "soft module," involving genetic predetermination of the underlying neural architecture that makes possible the complex task of reading (particularly, word recognition skills). The consistency of dedicated neural tissue for reading across Ss suggests modularity (unlike consciousness). However, similar to musical and mathematical ability, it is a "softer" modularity than we find with language, requiring greater cultural support for its development and taking it a longer time to arise than did language.
EVOLUTIONARY EXPLANATIONS OF READING
Evolutionists believe that homo sapiens appeared sometime between 100,000 to 300,000 years ago. Current thinking maintains that a significant number of changes occurred within homo sapiens, including changes in bone structure, stature, and vocal cords, with the most momentous being encephalization, which is significant increase in the size of the cerebral cortex. It is believed that this increase occurred on the basis of genetic changes that enlarged the brain, which led to enhanced intelligence and language abilities. This in turn helped humans to adapt to their environment. Evolutionists disagree about how many specific genetic changes led to the increase in our rational and linguistic abilities, but the vast majority agree that a reading module could not have been specifically built into our cerebrum. This is because it is inconceivable that humans would have evolved specific cortical-mental structures, which were of no use in the EEA and would not have been used for at least 100,000 years.
Specific arguments against a reading module include the facts that alphabets have not been around very long and nearly two/thirds of people in the world are functionally illiterate (Ellis, 1987; Kamhi & Catts, 1999). These observations are believed to suggest that the human brain was not predisposed to develop literacy. Kamhi & Catts (1999) also note that most dyslexics also have language problems, suggesting that dyslexia is primarily a language problem. Yet, we think most reading specialists would strongly dispute this, noting that so many cases of serious reading disability do not involve any identifiable language deficit.
Some have pointed out that literacy acquisition is more difficult than speech acquisition because literacy requires formal instruction and the brain was not made to read; whereas it is "natural" for the brain to comprehend and express language (Bertelso & De Celder, 1989; Gleitman, Gleitman, Landau, & Wanner, 1989). In response, it should be pointed out that reading requires the more advanced cognitive abilities needed to objectify phonemes (cf. Olson, 1994). This may entail social facilitation, but in that way it would be no different from complex musical processing and formal operations, both of which require instruction. Yet, no evolutionist disputes that formal logical abilities were a product of evolution. Moreover, simply because a structure develops later does not mean it was not a product of design. Consider the late stage development of the butterfly (which, by the way, would also present problems for an evolutionary account).
Some have also pointed to the lack of a clear critical period for reading, like there is for language. This point has been registered, but given the overwhelming evidence of a neural substrate for reading, similar to language, we would conclude that there may simply be differences among modules regarding just how biologically determined they are.
Evolutionists and Modularity: Pro and Con
The noted neuropsychologist, Michael Gazzaniga (1998), argues that the brain is filled with a "staggering" number of mental devices that structure much of our thinking, for example, perception, basic understanding of physics, and social rules. "Each device solves a problem. Not to recognize this simple truth is to live in a dream world" (Gazzaniga, 1998, p. 170). And yet he is thoroughly opposed to the idea that reading was designed:
Brains were not built to read. Reading is a recent invention of human culture. That is why many people have trouble with the process and why modern brain-imaging studies show that the brain areas involved with reading move around a bit. Our brains have no place dedicated to this new invention, but there is a place that manages breathing. (Gazzaniga, 1998, p. 6)
Gazzaniga appears to use his impressive knowledge of neuropsychology in an evolution-serving way. Surely Gazzaniga is aware of the reasons for some imprecision in the exact neural location of reading processes. For one thing, differences in such things as Ss' brain structure and task designs make such identifications difficult (see Grabowski & Damasio  discussion on research on the very subjects of both language and reading). Moreover, this problem exists for all neuropsychological processes (e.g., see Watson's  acknowledgment of this point in research on face recognition, p. 284). Gazzaniga himself later acknowledges that while the "broad scaffolding" of the brain is genetically predetermined, "the details of cortical arrangements might be left to experiential effects" (p. 46)! But this point could have just as easily been made about the regions dedicated to reading. Why is it that reading gets singled out by Gazzaniga as if its brain regions are any less fixed than other neuropsychological proce sses? There really seems to be only one answer: pre-theoretical commitments to evolutionary theory.
In one way, anti-module evolutionists like Stephen J. Gould are in a better position. Gould (1991, 1997, 2000) has repeatedly indicated his skepticism regarding mental modules. He argues that some capacities of organisms are adaptive by-products of naturally selected variation ("spandrels" produced by the process of "exaptation"). He argues that human language is an example of this. Given our naturally selected, genetically-based, general intellectual competence, culture takes over and shapes the human mind in a variety of ways that only later prove to be adaptive. He believes humans simply evolved a general intellectual capacity that is very adaptive precisely because of its enormous range of applications. With reference to our problem, Gould (1997) states "reading and writing are now highly adaptive for humans, but the mental machinery for such crucial capacities must have originated as spandrels that were co-opted later" (p. 47).
The anti-module position of Gould has clear value for evolutionism. Gould then has only to argue for a single genetic mutation involving the massive encephalization that occurred once. Modular evolutionary theorists must posit multiple novel genetic mutations that ended up being naturally selected, one for every module. Even more problematic, complex cognitive processes, like language, typically involve more than one gene, therefore requiring a combination of genetic mutations--perhaps in some cases amounting to examples of irreducible complexity.
Unfortunately for Gould, he is able to argue against modularity across the board because he is a paleontologist, and not a neuropsychologist. Not being a specialist in neuropsychology, he appears to be unaware of the solid neurological evidence that exists for a number of brain/mind modules. For instance, there is even evidence for specific regions for problem-solving, at least for some tasks, in the parietal lobes (Iacoboni, 2000), which presumably constitutes a significant part of the general intellectual competence that Gould sees as the single product of encephalization. (2)
Knowing the neuropsychology field so much better, Gazzaniga (1998) strongly affirms the brain's modularity. However, Gazzaniga is unwittingly in danger of duplicity. Solely on the basis of the neuropsychological evidence, reading ability looks like a module; at least it is no different from language or object recognition ability on that score, which on the basis of such evidence he strongly argues are modular. Is there any empirical support for his rejection of a reading module or is it simply rooted in evolutionary ideology? If there are a "staggering number" of "special devices" in the brain as Gazzaniga believes, he is being grossly inconsistent to argue against a reading module on the basis of the neuropsychological evidence.
Evolutionary Psychology's Necessary Stance Against a Reading Module
The position of EP leaders to modules is, of course, very similar to Gazzaniga's. In fact, Cosmides & Tooby were invited to make two contributions on evolutionary psychology to the definitive neuropsychology reference work Gazzaniga (2000) edited, The New Cognitive Neurosciences. So, we will not repeat that position except to note that Cosmides & Tooby (1992) have specifically stated that reading abilities cannot have been naturally selected because the present state of the human brain is due solely to the selection pressures of the hunter-gatherer environments of our early ancestors, and there would have been no survival advantage to a reading module back then (cf. also Tooby & Cosmides, 2000). As in the case of Gazzaniga, the bias of evolutionary psychologists against the modularity of reading, in spite of its evidence and in light of its strong commitment to many other cognitive modules, suggests a serious inconsistency within their theoretical commitments to evolutionary theory, modularity, and empirical science.
Explaining Reading without a Reading Module
So, how do most evolutionists explain the neurological and cognitive complexity of reading ability without appealing to a module? There appear to be two approaches: one more general and speculative, and the other more derailed and research-based.
The most common approach (as seen in both Gould and Gazzinaga) is to argue that the brain's previously evolved abilities to rake in information, including linguistic information, and to operate on it, was newly applied to visual linguistic symbols. Evolution (and genetics) is not needed to explain how reading forms. When every child is exposed to visual linguistic symbols, new brain regions are developed solely on the basis of individual experience without any specific, generically-directed influence.
This deserves careful examination, because this seems quire plausible. One way to assess this proposal would be to examine the brain's general developmental plasticity and ask if it is sufficient by itself to account for reading acquisition. Unfortunately, this may be impossible to determine at present. Clearly, people continue to learn auditory and visual information and new skills throughout life once the basic acquisition abilities have been developed (e.g., the learning of a new computer program in adulthood). Yet, most linguists (following Chomsky) argue that the complexity of language requires special "prewiring." It is very difficult to objectively assess whether reading (e.g., the word form system) is more like language or more like learning a new computer program and so requires only the application of already present, general-domain cognitive abilities (e.g., associating visual words with auditory words), without assuming a position that will slant one's interpretation of the available data.
Modularity vs. plasticity. One way to evaluate if reading involves simply the application of previously evolved mental abilities would be to study the brain's normal neural assignment patterns and also its ability to recover from developmental or acquired reading disability. If the brain has a general capacity for linguistic processing not tied to reading, then damage to the regions typically involved in reading should not inhibit remediation. New neural regions will simply be applied to the reading task.
First, we should discuss some examples of the brain's normal neural designation in general. Significant neural plasticity clearly exists for visual perception early in life. Infant cats experience nearly complete recovery from the removal of their visual cortex, whereas adult cats never do (Banich, 1997). Similarly, whereas the location of brain lesions in adulthood (e.g., in the language regions) leads to specific ability deficits, lesions in childhood have no correlation with neurological deficit (Banich, 1997). This suggests that even though there is a predetermined locale for the assignment of neural substrates for specific tasks, this assignment can be altered in childhood. However, this youth advantage is not found with all abilities (e.g., motor abilities, which therefore constitutes the most "hard-wired" of modules). Furthermore, in some cases, deficits from cortical insults in childhood may not show up immediately, but may take up to ten years to surface. Theorists have suggested this may be due to t he "crowding hypothesis," in which it is suggested that after an injury the brain can be initially rewired successfully, but this rewiring leads to further cortical inflexibility later in life as new skills are needed (Banich, 1997). So, early damage can sometimes be overridden, but even then, it may result in the utilization of neural "space" designated for other processes.
Gazzaniga (1998) states that dedicated regions can only accomplish what they were dedicated to do. "The language area of your brain can't recognize faces, and the face area can't do language" (p. 36). He notes that neuroimaging studies have found that recovery of speech after cortical damage to language areas appears to be dependent on the amount of remaining cortex adjacent to the damage. In adults, specific psychological functions based in distinct neural tissue cannot be relocated in another region distant to the original site. Although he does not believe this applies to reading, one might draw from his generalization that, if true, reading also will be impaired and remediation limited to the extent that specific neural sites are damaged. And that is exactly what research on reading disabilities has found.
With regard to infant brain activity during language acquisition, during the period of 13-17 months, measurements show that when children are exposed to meaningful words, they are processed in a bilateral fashion and distributed over anterior and posterior regions. By 20 months, activation in response to such words is limited to the left temporal and parietal lobes (Stromswold, 2000). So the specification of brain tissue dedicated to language tasks unfolds over time, but it eventually becomes situated, presumably via some genetic mechanism, unless damage inhibits the normal maturation processes. If the damage occurs during childhood, then substantial, nearly complete recovery is often possible by having novel, "non-linguistic" regions of the brain co-opted to take on the lost functions. This plasticity, however, is significantly lessened in adulthood (Spreen, Risser, & Edgell, 1995). During adulthood, if there is damage to the language areas of the brain, it is only sometimes possible, and then usually only w ith significant effort, to recover some linguistic function in other regions. For example, the RH becomes activated in linguistic tasks in adult patients recovering function after damage in the LH in Wernicke's aphasia (Choller, 2000).
Less research in this area has been done on reading, but there is evidence of some neural regional plasticity regarding reading ability. Just & Carpenter (1987) cite one of the most amazing studies of this: an examination of three children born with only one hemisphere. The LH-only child had greater fluency and reading ability overall than the two RH-only children, but did better when words were in sentences than alone. The two RH-only children learned to read, but read less well and relied on visual processes more than phonological processes to recognize words. Thus, in reading, the brain can also reassign regions in children's brains when forced to, though the LH nevertheless seems to be pre-wired to promote language and reading better than the RH. Black & Behrmann (1994) also mention cases where there has been some recovery of reading in childhood after an occipital lobectomy!
Unfortunately, the authors were unable to locate very many longitudinal studies of reading recovery. Friedman & Alexander (1984) report a case of pure alexia where reading improved somewhat after initial loss of abilities, but continued to be slow and laborious. In addition, it did not return to previous levels of ability. A case study of a dyslexic found a reassignment of reading functions to new neural tissue after damage to original tissue after reading training (Small, Flores, & Noll, 1998). This suggests that there is the potential for new assignment of neural substrate for reading to be formed. More research on training needs to be done. As a result, the reflections of this paper at this point must be tentative. However, we would expect that if reading is in anyway a module like language, language deficits resulting from insult would in general have about the same likelihood of remediation as reading deficits, and from what the authors can conclude from the literature, that is the case. In summary, it appears so far that the brain's general plasticity does not easily explain the similarity between the assignment of language regions and reading regions and the similarity between the difficulty of remediating damage in language and reading regions. In both cases, there is a degree of structural predetermination and rigidity that is hard to account for with the application of more flexible, general-domain brain processes.
Modularity vs. connectionism. Connectionist models of reading probably offer the best, most detailed account of reading activity using general learning processes of the brain. A number of connectionist models of reading have been developed and modeled in computer simulations, providing valuable empiricist accounts of the development of reading that appear to accurately mimic how neurons are involved in information storage (Behrmann, Plaut, Nelson, 1998; Harm & Seidenberg, 1998; McClelland & Rumelhart, 1981; Patterson & Ralph, 1999; Plaut, 1995; Rumelhart & McClelland, 1982; Saffran, Dell, & Schwartz, 2000). Connectionist models of reading assume three levels of processing units: letter features, letters, and words. Repeated exposure to specific letter feature stimuli causes activation of stored representations of such features, which in turn activate higher-level representations of specific letters (e.g., a dot over a line will activate both an "i" and a "j"). Then, the activation of specific letters will fu rther activate specific words that make use of those letters (seeing "bri" will activate "bridge" and "bright"). Higher levels of activation also move "down" into lower levels within the network. Such models do not have to assume the existence of any "pre-wired" neurological structures. Simply the "writing" of repeated sensory experience on the stimulus-neutral neurons is enough for complex neural networks to develop that can process information like auditory and written language.
Connectionist researchers typically argue against any notion of a word-form system (e.g., Behrmann, 1999; Farah, 1999; Farah & Wallace, 1991; Farah, Stowe, & Levinson, 1996; Sekuler & Berhmann, 1996). Supporting this assumption, a few studies by connectionists have been conducted that they believe show that reading disorders are not the result of an impairment in a reading module. For example, some have found evidence of a pre-lexical visual deficit at the root of some alexia disorders that compromises the perception of visually complex non-orthographic material as well as words (Farah & Wallace, 1991; Friedman & Alexander, 1984). Another study has explained surface dyslexia as a result of a semantic memory deficit and not a reading component (Patterson & Hodges, 1992). These studies provide some empirical support for the belief that reading disorders are the result of some "general-domain" processing deficit, rather than a reading-specific deficit. However, they are unable to explain why it is that particul ar neuronal regions are responsible for this specific type of connectionist processing.
Furthermore, the conclusion that visual processing deficits associated with alexia that supposedly prove it is not a reading-specific disorder (Behrmann, 1999; Farah, 1999; Sekuler & Behrmann, 1996) can be disputed. The fact that the brains of some alexics have difficulty perceiving certain novel, complex visual stimuli cannot demonstrate that there is no reading module. It could be that the complex visual designs used in these studies are processed within a larger damaged brain region that includes the letter-processing region, or it could be that the novel designs merely tap some of the same visual processing skills needed for reading. Such findings certainly are insufficient to prove that there is not an orthography-specific region of the brain.
Regardless, one wonders about the extent to which the authors' use of connectionist theory is due simply to its obvious value or also to assumptions regarding the evolutionary impossibility of a reading module. For example Farah (1999) writes, "Only abilities that evolved can be carried out by specialized brain regions. Setting aside the example of reading, it appears a plausible empirical generalization that learning within an individual's lifetime cannot create new brain areas" (p. 239, italics added). And Farah, Stowe, & Levinson (1996) state:
Consider other known examples of functions that make use of dedicated brain regions: colour vision, motion perception, motor control, memory, aspects of language, etc. These are all functions with a strong innate component, acquired naturally in the course of development. The sounding out of (written) words is a learned ability, which could not possibly have a genetic basis because of the evolutionary recency of reading, and seems out of place in this list. If there is a brain region dedicated to orthography-to-phonology conversion, this suggests that brain architecture can be modified by learning that takes place many years postnatally. (p. 852)
Farah & Wallace (1991) compare reading to other culturally learned abilities like chess or ballet. Just as we would not expect a genetically-based neural structure for those tasks, so they say we should not expect one for reading. They conclude by suggesting, "If an ability can be impaired selectively and permanently by focal brain damage, this suggests that this ability is normally performed using dedicated hardware, that is some relatively local part of the brain that is required for that ability and is not required for any other abilities" (p. 333). Evolutionary theory renders it inconceivable that this could apply to reading. Hence, they favor viewing alexia as a function of a deficit in a "general-domain" capacity and believe that the visual impairment hypothesis is "preferable a priori to hypotheses that postulate damage to reading-specific mechanisms" (p. 333, italics added).
This tendency to assume the impossibility of a reading module seems unempirical. Farah (1999) herself acknowledges that there are cases of alexia that are letter agnosic and not number agnosic (and vice versa). This is a very subtle perceptual distinction, grounded in distinct neural substrates. If this is not modular, it is hard to say what would be. And she recognizes the problem this poses. As a result, she has begun attributing such phenomena to the results of the "self-organizing" capacities of the brain. Self-organization theory offers about the only hope to explain the modular-like evidence of reading substrates. (Because this concept is used by others who are discussed below, more elaboration on this theory is found bellow.)
Regardless, connectionist models offer a fruitful way of explaining (and modeling) feature-detection, word formation, grapheme-to-phoneme translation, and consequently some reading disability behavior patterns. Such models will also likely help to explain the flexibility of the human cognitive system in interpreting linguistic symbols in spite of sensory deficits (e.g., braille and ASL).
However, reading theorists who favor the notion of a word-form system do not believe connectionist models offer a sufficient explanation for reading phenomena. Stanovich (2000), for example, suggests that connectionist models are probably best in dealing with perceptual abilities, but are unable to model categorization and conceptualization that require symbolic processes, not just associative. Also, such models cannot explain the existence of universal dedicated substrates for specific reading tasks (e.g., the angular gyrus). Moreover, if reading was simply the result of training a neural network, then chimpanzees should be able to be taught to understand and produce sentences and to read. They surely have enough neurons to duplicate a simple neural network. Vigorous training has taught primates to recognize signs (via associative learning), but they cannot use an alphabet (which requires writing) and they cannot break words down into morphemes (Morton, 1989). Apparently, this requires a level of cognitive p rocessing and analysis that transcends a simple neural network. Also, it is unachievable without the prior cognitive software necessary for higher processing within which the language and reading neural networks do their work. Hyperlexia and the difficulty of remediating reading disabilities also suggest that the connectionist models must be incomplete because they also show that it is not merely any neural structure that can make reading possible, but specific neural structures designated for reading. So, connectionist models are extremely helpful for understanding the fundamental processes involved in reading, but they cannot explain the reading system, and, thus, do not explain away the notion of a reading module.
Seriously considering the available evidence from a non-modular evolutionary standpoint, the brain's present abilities would seem at least to require that genetic variation and natural selection produced genetic programs that themselves make possible the development of unconscious, automatic metacognitive "software" systems for (a) organizing completely novel forms of information not in existence throughout the period of the EEA (e.g., numbers, musical notes, written words); (b) developing novel forms of processing that information (e.g., mathematical calculations, perceiving a melody, recognizing words); and (c) allocating roughly the same neural space for their storage and processing, which must be genetically programmed since their locales are roughly the same in all humans. One can easily see the adaptive value of problem solving and language, but the above set of meta-abilities seems hard to explain in terms of the survival needs of early hominids.
Evolutionary Explanations of Reading Modules
It is because of the weight of the empirical evidence that some reading researchers have concluded that there must be reading modules. Given their pre-commitment to evolution, these researchers have had to develop explanations that cohere with evolution.
A small number of reading researchers have been sufficiently impressed with the neurological evidence to conclude that there is a reading module, in spite of their evolutionary commitment. There are two directions for evolutionists to go at this point. One is to argue for the temporal assignment of neural tissue for reading based on experience. We might call this "very soft modularity." Farah's (1999) move in this direction by appealing to self-organization theory has already been noted. Farah (1999; Farah, Stowe, Levinson, 1996) suggests that the brain may have evolved a capacity to organize information according to categories, experientially forming dedicated neural regions in individuals. Shallice (1988) similarly believes the word-form system is not a problem for evolutionary theory because it is the individual brain that develops a modular structure based entirely on reading experiences that constrain the assignment of neural tissue dedicated to reading. Again, the chief problem with this approach (as w ell as all the foregoing evolutionary responses) is the universal assignment of roughly the same neural regions for reading, because having the same assignment for other cognitive capacities typically provides evidence for genetic influence (e.g., with vision and language).
A second move for evolutionists to make in light of the neuropsychological evidence is to go "all the way," and argue for a genetic cause of the neural assignment resulting in an exaptation, where reading was a relatively recent application of a neuropsychological capacity used in the EEA for another purpose. An increasingly popular way of making sense of the development of language that does not require one large jump is a gradualist, co-evolutionary model (Deacon, 1997; Janicki & Krebs, 1998). This model suggests that the brain changed incrementally in the direction of increasing linguistic ability, but only as human culture accommodated itself and made use of the enhanced linguistic capacity afforded to it by its gradually changing brain (particularly the brains of its developing children), thus leading to the actual adaptiveness of the genetically induced change. The strength of the model (from an evolutionary standpoint) is that it seeks to explain language development without having to posit an enormou s, relatively quick change (in evolutionary terms) in brain structure (as a punctuated equilibrium model would posit) from non-speaking hominids to the linguistic structures of modern humans, with all its syntactical, semantic, narrative, and pragmatic complexity. We leave to others the evaluation of the problems of this model for language (e.g., see Oller, 2002 in this issue), but we mention it to anticipate a possible evolutionary solution to the reading module: Perhaps the reading module evolved in concert with changes in culture and the development of symbol-use. Although no one has thus far suggested that a co-evolutionary model would be useful for reading, we want to spell out its patent inapplicability in this context. For one thing, it would require an evolutionary change around 6,000-8,000 years ago in which genetically-induced reading abilities were naturally selected because they assisted the reproductive potential of reading individuals. This seems unlikely for two reasons. First, it is not clear that reading produces significant adaptive advantage. Second, illiterates can still be found all over the globe and all of them have the same neural capacities of any of us because they (or their children) can be taught to read. In such a short amount of time (in evolutionary terms), it would be unlikely for reading genes to have completely taken over the human gene pool, so there should still be human brains around which have no capacity to read. As a result, co-evolutionary theory will offer no solution to the problem of a reading module for the evolutionist.
However, some reading researchers have concluded there may be some genetic basis for a reading module. Marshall (1989; and others, e.g., Dawkins, 1982), for example, argued that reading skills were likely derived from animal tracking capacities that evolved long ago, which required two-dimensional, semantic interpretation. "This mechanism interprets the conceptual significance of two-dimensional signs. The mechanism is modular, that is, distinct from object-recognition capacities, precisely because important constraints applicable to three-dimensional recognition are not relevant to important constraints applicable to two-dimensional interpretation" (p. 82). Because of the adaptive value of animal tracking, a two-dimensional sign-interpretation module evolved that became part of the human genome. He suggests that "the basic functional components of reading competence are performed, but their operation must be triggered from an experientially derived database" (p. 69). Nevertheless, though Marshall's willingn ess to take seriously the empirical evidence for a module is commendable, the forced nature of such an explanation of reading reminds one of the hypothesized (should we say mythological?) accounts of how the irreducible complexity of bird flight evolved, involving the simultaneous formation of hollow bones, wings, and feathers. The enormous neural and cognitive complexity of reading seems to transcend greatly the capacities needed for track identification. To call this a stretch is charitable.
Probably the reading researcher most strongly committed to modularity, Cossu (1999), views reading abilities as the result of genetically-based (and so universal), neuropsychological causal mechanisms that provide the "biological constraints" that make reading possible (p. 228). As further evidence for modularity, he cites research showing that orthographic systems throughout the world have a universal structure that cannot be accounted for solely by cultural diffusion. For example, he notes that Chinese children naturally make use of grapheme-to-phoneme translation to decipher novel Chinese characters though the ideographic characters of Chinese are much less phonologically significant than alphabetic systems (cf. also Tzeng, Lin, Hung, & Lee, 1995). He also presents a study showing that children are inclined to rely on the "alphabetic principle" to help in deciphering new words even with orthographies that are highly irregular, which thus slows down their reading fluency.
Cossu (1999) further suggests that a general capacity for "intersensory integration" may have emerged in early humans which was later refined to become a cross-modal device for integrating language sounds with information from other perceptual domains. Cossu also offers the explanation that the brain may possess a "mechanism of spontaneous order," which generated "non-adaptive neurofunctional architectures, later recruitable as adaptive tools" (p. 226), another reference to "self-organization" theory. It appears that only some self-organizing capacity of the brain can account for the regional neural assignment for reading from within a naturalistic evolutionary framework.
Self-organization theory was first developed in physics and has since been applied to biological and neural systems (Scott Kelso, 1995). "Self-organization refers to the spontaneous formation of patterns and pattern change in open, nonequilibrium systems" (Scott Kelso, 1995, p. 8). Scott Kelso argues that neurologically grounded human activity may often be the result of "self-organizing" patterns of neural activity that lead to the formation of identifiable regions of the brain. One can see evidence for self-organization at work in the brain during the neural reorganization that can occur after a stroke. However, besides for its questionable Lamarckian implications, Cossu's version of self-organization theory is more controversial than Farah's (mentioned above) because he is arguing for a self-organized (and self-organizing) structure that was selected long ago and is now passed on to subsequent generations. This may be a logically consistent move to make for an evolutionist who recognizes the modularity of reading, but it seems highly unlikely that the vast majority of evolutionists would be willing to follow Cossu here. Another serious limitation of self-organization theory at this juncture is that at present we have no understanding of how it actually works in individual brains, let alone how it could have led to such a well-developed reading system that would be passed on genetically, as Cossu maintains. Although there is indubitable evidence of neural self-organization, at present it is unclear how the term "self-organization" really says anything other than providing a novel label for a phenomenon of which we have little understanding. At present, this use of self-organization theory is no different than saying, "God did it."
CONCLUSIONS AND CONSIDERATIONS OF DESIGN
There are three major conclusions to draw from this article. First and foremost, evolutionary psychology, as presently conceived, is faced with a fundamental contradiction to its theoretical framework in light of the empirical evidence for the modularity of reading. Given its own commitment to modularity and its willingness to embrace a modular understanding of many cognitive skills and motivational complexes with far less neurological evidence, EP should strongly affirm the modularity of reading. However, because of its evolutionary assumptions regarding when reading could and could not have formed, it must vigorously resist reading modularity. EP must come to terms with this neuropsychological evidence (and with the similar evidence for neural substrates for other non-adaptive psychological phenomena, e.g., musical ability). Taking such evidence seriously will require a basic reassessment of the explanatory power of evolutionary theory for psychology, and will help to undermine the unwarranted all-comprehe nsive claims EP's adherents have been making for evolutionary theory as the ultimate explanatory paradigm.
Second, it would appear that neuropsychologists and reading researchers who are not committed to the modular assumptions of EP are nonetheless also being biased in their research conclusions by evolutionary commitments. The evidence for reading modularity needs to be taken more seriously in spite of the difficulty it presents for evolution. Perhaps self-organization theory will someday be able to explain some features of neural assignment. But if evolutionary theory keeps researchers from following certain paths and only pursuing "orthodox" Darwinian thinking, good science will be inhibited.
Third, a significant body of evidence suggests there is a "soft" module for reading. Its existence cannot be established beyond question given the potential of connectionist explanation, the relative plasticity of the brain (e.g., in ASL acquisition), and the possibility that further research in neuropsychology (especially developmental neuropsychology), genetics, and self-organization theory may provide a better naturalistic explanation for reading ability than has been offered so far. Nevertheless, given the present available evidence, there are good reasons for accepting the existence of a genetically-based reading module. If that is the case, then one must inquire how it arose. The evidence for microevolution is indisputable, but in spite of 140 years of reflection and research, evolutionary theory is still fundamentally unable to adequately explain how certain phenomena arose such as sensation, the interdependent components of the cell (see Behe, 1996), the move from water-breathing to air-breathing, th e repeated development of flight, and many other phenomena (nor are these inadequacies typically taken with the seriousness they deserve). Critics can appreciate that EP offers a theoretical paradigm that coherently explains many otherwise puzzling phenomena (e.g., regarding reproductive behavior), yet still point out it is much less successful in explaining adequately the existence of many uniquely human capacities and abilities, like reading and music.
How else then can the existence of neural architecture dedicated to reading be explained? Dedicated neural architecture for reading provides one more piece of evidence for intelligent design (ID) theory. By being open to the possibility of an intelligent designer, an ID researcher is able to account for evidence of design that cannot be explained by chance and natural factors alone. ID theory recognizes that much of the evidence of design is mediated through natural processes. Rings in trees are produced by annual growth, not because of direct divine causal action. However, ID theory assumes that a supreme intelligence is the ultimate designer of the matter and natural laws of the universe and the sovereign, transcendent cause of all the activity within the universe. As a result, ID theory is not in principle opposed to natural explanations of phenomena, because the supreme intelligence is assumed to be free to use any variety of means in the universe, whether direct or mediated. Consequently, if research en ds up documenting natural causes for a reading module, it should be welcomed by ID researchers, for our understanding of the universe has been furthered, a blessing to be received with thanksgiving. (3)
But unlike naturalism, ID theory also views the universe as an open system into which the supreme designer is free to act directly. Consequently, the ID thinker or researcher is open to the possibilities that some features of reality may be inexplicable from a purely naturalistic standpoint and that evidence may exist which points to such transcendent intervention. Reading would seem to provide an example of such evidence. The human brain is distinguished from other primate and hominid brains by a significantly greater amount of cortical tissue that makes possible the uniqueness and complexity of human thought and experience. This uniqueness and complexity includes many specific functions, most of which would be clearly adaptive in any environment, along with a significant number of others that would seem to have no directly adaptive purpose in the EEA, including such things as musical and artistic ability, aesthetical sense, advanced mathematical understanding (algebra and beyond), a belief in supernatural beings, religious experience, and narrativity. Investigations like this one on reading need to be conducted on other psychological phenomena that are difficult for EP to explain, to better evaluate its explanatory power. At present, in the absence of a compelling naturalistic evolutionary account, the best way to explain the empirical evidence for a reading module is to assume its neurological and cognitive structures are the product of intelligent design. The current evidence for a "soft" reading module fits better with a theistic world-view than it does with a naturalistic evolutionary one, since the assumptions of Western theism would lead one to expect the transcendent designer of the universe would have created humans with an ability to read.
Admittedly, ID theory by itself necessarily plays a mostly critical role in science. It exposes problems with naturalistic causal conceptualizations, without offering any other empirical explanation. Positively, it posits the hypothesized, unobservable (by definition) activity of an intelligent designer (along with the empirical evidence of intelligent design). And such is the case with this paper. No empirical causal explanation is offered here of the precise mechanisms, if any, that a supreme intelligence used to create or bring about the brain's current structure. However, this does not undermine the value and relevance of ID theory to the science of neuropsychology. The human brain is probably the most amazing mystery in the universe. Its existence and experience seems to transcend intrinsically human understanding in many ways (e.g., mind/brain interaction, the nature of consciousness), and there is much about its abilities and development that would seem to defy a naturalistic evolutionary account. If there is an intelligent designer, it would seem to be profoundly narrow-minded to exclude a priori the possibility that this designer exists, and could have created and freely intervened in this empirical order. And if this is so, it is entirely possible that complex neural structures like reading modules may not have a better causal explanation than by reference to a transcendent, supernatural cause. If ID theory is true, the science of neuropsychology (and likely all the sciences) will necessarily be incomplete without reference to that designer. But at the very least, acknowledging an intelligent designer, given phenomena like reading, can be logically and epistemologically no worse than positing natural selection and self-organization as the ultimate explanations in the absence of a compelling evolutionary account, and in that absence an ID explanation would seem, at least to some theists, to be much better. Given the amount of evidence of intelligent design throughout the created order, the wisest and most plausible epistemological stance to take in neuropsychology would seem to be to affirm a belief in a supreme intelligence who in one way or another created and oversees all the structures and processes of the universe, including the neurocircuitry that made reading possible, while continuing to thoroughly investigate the nature of this empirical order, open to both mediated and direct supernatural design.
(1.) As an aside, one wonders how a naturalistic evolutionist can account for musical ability. How adaptive for life on the savanna would musical ability be? Enough for natural selection to favor individuals with the genes for musical ability and disfavor those without it? That seems extremely far-fetched. Dissanayake (1999) finds antecedents of music in the quasi-musical discourse of mothers and their infants, but this hardly seems sufficient to account for the genetic basis for the complex musical abilities that are hard-wired into the brain, constituting a distinct intelligence according to Gardner (1983). This subject deserves much fuller treatment from an ID perspective.
(2.) It should also be mentioned that there are psychologists like Karmiloff-Smith (1992) who are much more familiar with the neuropsychological evidence for modularity and also express reservations about a "hard" modulism, believing that the brain's self-organizing capacities, combined with a "fairly limited amount of innately specified, domain-specific predispositions (which are not strictly modular)" (p. 4), interacting with an information-rich environment are sufficient to account for the complexity of the human mind.
(3.) As the reader may suspect, the authors themselves are creationists rather than evolutionists, who acknowledge that the empirical evidence of the age of the universe suggests billions of years, rather than thousands and affirm the process of microevolution, which has lead to the significant, but relatively small changes that occur within, for example, genera and families. However, the empirical evidence also leads us to the conclusion that many of the forms of biological life (and their changes) recorded in the fossil record and present today provide extremely strong evidence of intelligent design (e.g., the origin of life, the existence of the cell, the explosion of invertebrate life in the pre-Cambrian period, the change to air-breathing, walking organisms, the origin of sensory organs, the development of flight in four different forms, the "wasteful" but complex stage-development of insects, and the encephalization of homo sapiens, to name but a few of the enormous problems that naturalistic evolutioni sts seem not to have adequately faced). Nevertheless, we also recognize the necessity of submitting to compelling empirical research of the created order wherever it leads. As a result, we are fully open (as arc all ID proponents) to the discovery of naturalistic explanations for phenomena that are not currently understood. Such understandings cannot compromise an ID position; they only elaborate it.
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JOHNSON, ERIC L. Address: Southern Baptist Theological Seminary, 2825 Lexington Road, Louisville, KY 40280.
Title: Associate Professor of Personality and Pastoral Theology, Southern Baptist Theological Seminary.
Degrees: M.A.C.S. Calvin College; M.A. and Ph.D. Michigan State University.
Specialization: Early adult development, Christian psychology, history and philosophy of psychology.
HETZEL, JUNE. Address: Biola University, 13800 Biola Avenue, La Mirada, CA 90639.
Title: Associate Professor of Education, Biola University.
Degrees: Ph.D. Claremont Graduate University.
Specialization: Reading and writing processes, children's literature, curriculum development, and homeschooling research.
We thank Michael Boivin and Sarah Reju for their helpful comments on an earlier draft. Correspondence concerning this article maybe sent to Eric L. Johnson, Southern Baptist Theological Seminary, 2825 Lexington Road, Louisville, KY 40280.
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|Publication:||Journal of Psychology and Theology|
|Date:||Mar 22, 2002|
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