temporal spatial metaphors neural constraints on temporal

Constraints on Temporal-Spatial Metaphors 1

RUNNING HEAD: Temporal Spatial Metaphors

Neural Constraints on Temporal-Spatial Metaphors

Edward M. Hubbard1 and Ursina Teuscher2

1. INESRM Unité 562 – Cognitive Neuroimaging CEA/SAC/DSV/I2BM/NeuroSpin

Bât 145, Point courrier 156 91191 Gif-Sur-Yvette, France

2. Department of Cognitive Science University of California, San Diego 9500 Gilman Dr. La Jolla, CA USA 92093-0515 Corresponding author: Edward M. Hubbard voice: +33 (0)1 69 08 95 00 fax : +33 (0)1 69 08 79 73 e-mail: [email protected]

Word count: 13637 Body: 9490 References: 3637 Figure captions: 208 Figures: 3


ABSTRACT [149 WORDS] Metaphor theory proposes that our understanding of high-level concepts arises

through metaphorical construction and extension. One class of metaphors that has been studied extensively within metaphor theory is TIME IS SPACE. The cross-cultural existence of this metaphor has traditionally been interpreted as being a result of our common embodied experiences in the world. In addition to these experiential mechanisms, we examine data from human neuroimaging, neuropsychology and monkey physiology demonstrating that the parietal cortex houses circuitry crucial for both temporal and spatial representations to argue that these neural structures create a predisposition towards a neural mapping between the domains of time and space, and thus provide a brain-based constraint on the universal TIME IS SPACE metaphor. These considerations further suggest that cultural artifacts that best fit the pre-existing structures of the brain are most easily learned, and are therefore most likely to be passed on to future generations.


INTRODUCTION Metaphor theory proposes that our understanding of high-level concepts arises

through metaphorical construction and extension. Specifically, abstract concepts such as time or love are understood in terms of more concrete domains, such as space or physical journeys. Traditionally, this has been interpreted as being a result of our common, cross-culturally preserved embodied experiences in the world (see, e.g. Gibbs, 1994; M. Johnson, 1987; Lakoff, 1987; Lakoff & Johnson, 1999; Lakoff & Johnson, 1980; Turner, 1987). However, in this paper, we would like to explore the hypothesis that metaphorical mappings may arise not solely because of the structure of our embodied experience, but also because of the structure of our brains and the manner in which our brains interpret that experience. That is, we suggest that our conceptual structure is the result not only of our embodied experiences in the world, but also a result of the very structure of our brains.

As one example of this brain-based perspective, we consider here the close correspondence between certain cognitive-behavioral phenomena and one class of metaphors, TIME IS SPACE, that have been studied extensively in the cognitive linguistics literature. Among these phenomena are well studied numerical-spatial associations, which are likely to be mediated by map-map interactions in the parietal lobe (Hubbard, Piazza, Pinel, & Dehaene, 2005), and forms of synesthesia in which abstract sequences, such as numbers, letters, days of the week and months of the year are represented as having spatial locations (Ramachandran & Hubbard, 2001).

An emerging understanding of the neural basis of numerical (Dehaene, 1997), temporal (Buhusi & Meck, 2005), and spatial (Cohen & Andersen, 2002; Colby & Goldberg, 1999) processing suggests plausible neural mechanisms for these associations. Specifically, this research has suggested that map-map interactions between parietal brain regions involved in the processing of abstract representations of ordinal sequences and adjacent brain regions involved in the representation of space in the parietal lobe underlie behavioral mappings between number and space (Hubbard et al., 2005) and we here suggest a similar model for the linguistic mapping between time and space. Critically, numerical, temporal and spatial representations are multimodal, in that input from multiple sensory modalities is integrated in these brain regions, which is critical for the development of abstract concepts (for a similar argument see Gallese & Lakoff, 2005). We suggest that the neural structures that are involved in the representation of sequences and space are functionally linked, creating a neural mapping between the abstract, multimodal domains of ordinal sequences and space, and thus providing a brain based constraint on the development of certain classes of metaphors such as TIME IS SPACE.

A full appreciation of this point requires that we go beyond a simple nature/nurture dichotomy. Certainly, conceptual structure is acquired through cultural means, but culture, instantiated in individual brains, preserves and passes along only those conceptual systems that are best suited to the preexisting, evolutionarily defined structure of the brain (see, e.g., Deacon, 1997; Dehaene, 2005). The “neuronal recycling” hypothesis (Dehaene, 2005) suggests that neural networks, such as those for number, space, and object recognition evolved for more basic functions, such as knowing when one is outnumbered, where a predator or conspecifics are, and being able to recognize which is which in a given location. However, under cultural pressure, these pre-existing networks are “recycled” or “retrained” to take on new, culturally relevant functions in


addition to their original, evolutionarily more basic functions. We argue that such considerations can also fruitfully be applied to the case of metaphors (Gallese and Lakoff, 2005, suggest that metaphors are grounded through a process of “neural exploitation” similar to the neuronal recycling model described above). More specifically, temporal-spatial metaphors do not arise solely from linguistic customs. Rather, the linguistic customs survive, and get passed on to the next generation of speakers, because the necessary neural structures are already present in the human brain, therefore making it easier for us to learn certain mappings, such as those between time and space. A better understanding of the bottom-up constraints imposed on our conceptual structures by our neural structures has profound implications for our understanding of metaphor and cognition. The Basic Metaphor of TIME IS SPACE One of the fundamental metaphors in cognitive linguistics, which has been extensively explored, is the metaphor TIME IS SPACE. In their original formulation, Lakoff & Johnson (1980) describe the TIME IS SPACE metaphor as the TIME IS A MOVING OBJECT metaphor (p. 41-45), in which time can be seen in two different ways. First, it is possible to conceive of time as being a stationary landscape, through which we move (consider such examples as: we are fast approaching, that’s all behind us now, he’s nearing his thirtieth birthday). Alternatively, it is possible to conceive of ourselves as being stationary, and of time as moving past us (e.g., time flies, the coming weeks, the deadline is approaching). Lakoff and Johnson note that, in cases where time is conceived of as moving towards us, we furthermore conceive of time as having a front and back, so that weeks can follow other weeks, but they do not follow us. The statement, “We’re only two weeks away from Christmas.” is an example of an ego-moving time metaphor, whereas “Christmas is coming in only two weeks.” is an example of a time-moving metaphor. These basic spatial metaphors structure our everyday thinking about time, and are so common that they have even become fossilized in our language in Latinate forms such as predict (to say in advance of something) or retrospect (to look back on some past event) (Sweetser, 1990).

Although different languages have been shown to differ in the degree to which they prefer to use linear spatial dimensions to describe temporal orders (Casasanto et al., 2004), the use of spatial metaphors for time has been found in every language examined so far (e.g., Boroditsky, 2000, 2001; Evans, 2003; Núñez & Sweetser, 2006). Temporal metaphors have been studied extensively in an attempt to determine whether experimental manipulations that affect the way people think about space have consequences for their reasoning about time (Boroditsky, 2000; Boroditsky & Ramscar, 2002; Gentner, 2001; Gentner, Imai, & Boroditsky, 2002). For example, to prime either the ego- or the object- moving construal of space, Boroditsky (2000) gave participants tasks such as drawing a rolling office chair towards themselves or moving themselves on a rolling office chair. The subjects’ construal of time was then assessed, using the following ambiguous statement, “Wednesday’s meeting has been moved forward two days. What day is the meeting on?” (see also McGlone & Harding, 1998). The word “forward” means later in time on the ego-moving construal, and earlier on the object-moving construal, so that the answer to the question suggests which construal the speaker has adopted. Participants in the ego-moving picture condition tended to respond “Friday,”


consistent with the ego-moving construal of “forward,” whereas those in the object-moving condition tended to respond “Monday” (Boroditsky, 2000). Moreover, a number of studies conducted in real-world settings suggest that when people are in situations conducive to the ego-moving construal (as they board a train, once they’ve gotten to the front of a long lunch line, or before departing on an airplane), they are more likely to give the ego-moving “Friday” response to the Wednesday meeting question (Boroditsky & Ramscar, 2002). Matlock, Ramscar, & Boroditski (2005) showed that even the thought about fictive motion (a non-literal kind of motion, as in “The road runs along the coast”) could influence thought about time.

Casasanto and Boroditsky (2007) used psychophysical experiments to show asymmetric links between time and space even in low-level mental processes such as estimating brief durations. Subjects watched lines “growing” across a computer screen and estimated either how far they grew or how much time they remained on the screen. Line distances and durations were varied orthogonally, so there was no correlation between the spatial and temporal components of the stimuli. Line stimuli of the same average duration were judged to take a longer time when they grew a longer distance, and a shorter time when they grew a shorter distance, showing that spatial factors influence even our low-level, non-linguistic, non-symbolic representations of time. The links between time and space, although asymmetric, are not unidirectional. In an ERP experiment, Teuscher, Collins, & Coulson (in press) showed that sentences describing temporal motion also affected participants’ brain response to spatial motion, suggesting not only an influence of spatial motion on temporal reasoning, but also an influence in the other direction, from motion metaphors for time on the perception of spatial motion.

Recent theoretical developments suggest a more fundamental distinction of temporal metaphors than the distinction between ego-moving and time-moving metaphors (Moore, 2000; Núñez, 1999; Núñez & Sweetser, 2006), classifying metaphors according to the relevant reference point, rather than according to what moves (Ego or Time). Following this classification we have Ego-Reference-Point metaphors, where the Ego’s location always specifies the present, (and of which the above Moving-Time and Moving-Ego metaphors are sub-cases), and Time-Reference-Point metaphors, where earlier events in time are “in front of” later events, and where there the “Now” is not necessarily specified.

Figure 1. A classification of spatial metaphors for time (reprinted with permission from Núñez et al, 2006.)


Figure 1 shows this classification. Núñez, Motz and Teuscher (2006) used ego-free spatial stimuli to prime temporal reasoning, thus providing empirical evidence of the psychological reality of the Time-Reference-Point metaphor, that is, a temporal metaphor with no reference to an Ego.

Events are thus perceived either as being oriented in relation to the ego or in relation to the time sequence. To use the analogy with spatial reasoning, we argue that the Ego-Reference-Point metaphor maps onto on an ego-centric frame of reference in spatial representations, whereas the Time-Reference-Point metaphor maps onto an allo-centric frame of reference in spatial representations. For instance, expressions such as “the talk is followed by a reception” are independent of where the Ego or the “Now” is, that is, they are independent of the position of the observer. The position of “the reception” is here entirely defined by the position of “the talk” in the time sequence, in the same way that the expression “the car stands in front of the house” is independent of the position of the observer, but is entirely defined by the position and orientation of the house. Consistent with this notion, Kranjec (2006) provides experimental evidence that the 3-part spatial model (e.g. intrinsic, deictic, extrinsic) can be extended to temporal models.

Evans (2003) suggests temporal models that are in many aspects similar to and consistent with this classification, although they were developed independently. In a detailed analysis of lexical concepts associated with time, Evans argues that Moving Time and Moving Ego, as treated in conceptual metaphor theory, may constitute complex models of temporality, rather than being relatively simple sets of cross domain mappings. In addition to these two models he introduces a third model of temporality, which concerns temporal sequences. Here, events are related to each other, rather than to the Ego. Past, present, and future do therefore not occur in this model. In this sense, Evans’ temporal sequence model is similar to the Ego-RP and Time-RP distinction (Figure 1), but it is not motivated primarily by the role of reference points. As a result, it does not distinguish temporal relationships intrinsic to a sequence from those construed relative to an observer (see also Núñez et al., 2006).

Studies with people from different cultures and languages show that although the TIME IS SPACE metaphor is universal, the specifics of the spatial mappings can differ in accordance with the spoken language. For instance, Boroditsky (2001) found that Mandarin speakers, who talk about time not only in front/back metaphors as English speakers do, but also systematically use vertical metaphors to talk about time, tend to be more influenced by vertical than horizontal primes in their temporal reasoning, as opposed to English speakers (but see Chen, 2007; January & Kako, 2007). As another example of an unusual culture-specific pattern, (Núñez & Sweetser, 2006) found that Aymara language appears to have a major static model of time wherein the future is behind the ego and the past is in front of the ego. What is common to all of these findings is that time seems to be conceptualized in spatial terms, and that these spatial mappings are not only observable in our language, but are a psychological reality that manifests itself in behavioral and brain measures.

The Experiential Basis of the TIME IS SPACE Metaphor Traditional work in Cognitive Linguistics has focused on our embodied experience of the world as the source of our conceptual metaphors and cognitive mappings (see, e.g., M. Johnson, 1987; Lakoff, 1987; Lakoff & Johnson, 1980; Núñez,


1999). For example, in their original discussion, Lakoff & Johnson (1980) state, “the structure of our spatial concepts emerges from our constant spatial experience, that is, our interaction with the physical environment. Concepts that emerge in this way are concepts that we live by in the most fundamental way” (p. 56-57).

Johnson (1987) in his discussion of schemas and how they constrain metaphorical projections notes, “we are dealing with schematic structures that are constantly operating in our perception, bodily movement through space, and physical manipulation of objects” (p. 23) and that the origin of the PATH SCHEMA which structures the TIME IS SPACE metaphor arises from the fact that, “our lives are filled with paths that connect up our spatial world.” (p. 113). Johnson notes that there are three recurring images-schematic patterns, with a definite internal structure: “(1) a source, or starting point; (2) a goal, or endpoint; and (3) a sequence of contiguous locations connecting the source with the goal” (ibid). Johnson goes on to explain that, “paths can have temporal dimensions mapped onto them. I start at point A (the source) at time T1, and move to point B (the goal) at time T2. In this way, there is a time line mapped onto the path. It follows that, if point B is further down the path than point A, and I have reached point B moving along the path, then I am at a later time than when I began. Such linear spatialization of time gives rise to one important way we understand temporality” (p. 114).

The main point we want to draw from these quotes is that all of these analyses have occurred at the level of conceptual analysis, or at a level of cognitive organization removed from any discussion of neural organization. As cognitive science matures, we will need to examine these high-level conceptual mappings not only at the level of conceptual structure, but also at the level of neural structure. The current paper is one attempt to begin to address the relevant level of neural structure.

Conflation and the Neural Basis of Metaphor

Over the past twenty-five years, conceptual metaphor theory (CMT) (Lakoff & Johnson, 1980) has developed and deepened considerably, and more recent work in Cognitive Linguistics has begun to take explore the connection between the cognitive level and the neural level, for example by using computational models (sometimes referred to as the Neural Theory of Language; NTL). Lakoff and Johnson (1999) present an integrated theory of primary metaphor, based on work by Joseph Grady (1997), Christopher Johnson (1999), and Srini Narayanan (1997). Grady (1997) showed that complex metaphors arise from primary metaphors that are directly grounded in everyday experience. Johnson (1999) has argued that children learn these primary metaphors on the basis of the “conflation” of conceptual domains in everyday life. According to Johnson, conflation is the simultaneous activation of two distinct areas of our brains, each concerned with distinct aspects of our experience, like the physical experience of warmth and the emotional experience of affection. Early in our lives sensory-motor and subjective experiences tend to occur together and thus the concepts are formed in conjunction. As children gain more experience, the two domains can be distinguished, but the associations remain. As an example, Johnson studied how the KNOWING IS SEEING metaphor develops, demonstrating that children first use “see” literally, that is, only for vision. Then there is a stage when seeing and knowing are conflated, seeing occurs together with knowing. Only later do clear metaphorical uses of “see” like “see what I mean” occur. According to Narayanan’s neural theory of metaphor (1997), which he


developed using computational techniques for neural modeling, the associations made by conflation are the result of concurrent activation in separate domains. This simultaneous activity results in permanent neural pathways being developed between the two areas.

Our reading of Johnson’s argument is that cognitive schemas, and correspondingly metaphors, are not simply a result of repeated Gestalts of embodied experience in the world, but also that these repeated experiences lead to simultaneous activation of the relevant brain areas, and this simultaneous activation leads to these schemas becoming stamped into the neural circuitry of the brain. However, this view has something of a Hebbian, tabula rasa quality about it. The focus on the experiential side of conceptual development neglects the fact that, at least in some cases, we may have co-activation of brain areas that has little to do with the objective structure of the physical environment, or even the specific structure of human embodied experience. That is, not only do we learn through our experiences, but we also impose structure on them. This point has been made multiple times in the past (e.g., Lakoff, 1987) but the view of conflation seems to neglect this structuring aspect of our conceptual systems on our experiences. Importantly, some of the structure we impose on the world may come from the evolutionary structure of our brains themselves. In a recent review, Gallese and Lakoff (2005) stress the importance of neural structures involved in sensorimotor coordination for our understanding of concepts (in their example, GRASP), but do not explicitly explore the implications of their view for models of conflation. Our goal here is to integrate these lines of thinking more completely, showing how phylogenetically conserved neural circuitry may provide an additional constraint on possible conflations, and accordingly, on possible conceptual metaphors.

Our main claim in this paper is that part of the reason we conceive of temporal durations, and indeed, abstract sequences generally, in terms of spatial relations may have to do with the fact that both time and space are based on supra-modal or multi-modal neural representations. These constraints on the representation of time and space imply that, for completely non-experiential reasons, or, at least non-ontogenetic reasons, the representations of time and space will be processed in similar regions of the brain. In order to extract common supra-modal properties, time and space must be represented in brain regions that are able to abstract away from the low-level sensory properties of stimuli. The connection between time and space, therefore, may have much less to do with conflation between any two brain regions, as suggested by Johnson, but rather with conflation driven primarily by the adjacency of the relevant brain regions. In fact, this modification of Johnson’s notion of conflation can be motivated by the fact that adjacent brain regions are much more likely to be connected (and therefore to be co-activated) than are more distant regions (M. H. Johnson & Vecera, 1996; Kaas, 1997). We suggest that these neural constraints interact with our experience to create the connection between the source-path-goal schema and the representation of time.

Let us be clear here. We are not proposing that ontogenetic experience has nothing to do with how we conceive of our world, nor that experience is irrelevant in understanding the ontogenesis of conceptual metaphor. Rather we are arguing that, to date, cognitive linguistics has traditionally paid a great deal more attention to the role of embodied experience in structuring our conceptual systems and has neglected the constraints that may be imposed by the brain. It is clear that brain structure and experience may interact in interesting and unexpected ways. However, the focus on the


experiential side of the equation has led to a neglect of the phylogenetically derived structure of the human brain. Given that the phylogenetic structure of the brain is a result of evolutionary experience, the distinction between phylogenetic and ontogenetic experience may be thought of as a matter of degree.

We now turn to empirical evidence in favor of the idea that neural structure plays a critical role in constraining conceptual structure. One important piece of evidence comes from recent work suggesting phylogenetically conserved representations of temporal and spatial information in the parietal lobe. To address this question we will discuss findings demonstrating that temporal information is represented in the intraparietal sulcus (IPS) in both human and non-human primates. This brief review includes evidence from single-unit physiology studies in macaque monkeys and fMRI and neuropsychological studies in humans. In addition, we draw parallels with the neurological phenomenon of time-space synesthesia, in which subjects report that they consciously experience spatial forms representing calendars when they think of the months of the year. Based on the growing body of literature suggesting that temporal and spatial representations are processed in the parietal lobes, and behavioral evidence that these two conceptual domains are intimately intertwined, we suggest that TIME IS SPACE also arises from cross-activation (conflation) between these adjacent brain regions. THE NEURAL BASIS OF TIME PERCEPTION

In the past five to ten years, evidence has begun to accumulate for neural circuits in different regions of the brain dedicated to different aspects of time (for recent reviews, see Buhusi & Meck, 2005; Ivry & Spencer, 2004; P. A. Lewis & Miall, 2003). Subcortical circuits with long cycle times and low-variability may be involved in circadian timing (Buhusi & Meck, 2005), while the cerebellum may be involved in production and perception of specific short temporal intervals, especially in the motor domain (Ivry & Spencer, 2004). In a recent review of fMRI studies on time measurement, Lewis and Miall (2003) note that there are likely to be at least two independent systems for the estimation of time, one involved in automatic timing, and the other in controlled cognitive processing of time. For our purposes here, the most relevant are those circuits that are in the parietal cortex, which seem to be critical for temporal behavior that involves cognitive estimation of time and the estimation of discrete intervals in the range of several seconds. In contrast, automatic timing of short duration intervals tends to depend on low-level motor structures, such as the supplementary motor areas, the cerebellum and the basal ganglia.

Both human fMRI studies and monkey single-unit physiology point towards a phylogenetically conserved mechanism of temporal estimation in the region of the parietal cortex. For example, Leon and Shadlen (2003) showed, using single-unit physiology in monkeys, that time estimation relative to a standard of either 316 ms or 800 ms modulated the firing of neurons in a region of parietal cortex, the lateral intraparietal area (LIP), that is also known to be critical for attention space, and for the execution of eye movements (Leon & Shadlen, 2003). Monkeys were trained to make either a leftward or rightward eye movement, depending on the duration of the target stimulus. They found that when the long cue was in the neuron’s response field (the location to which the monkey would saccade) the firing rate of LIP neurons increased as duration increased. To demonstrate that this was not simply due to an increase in firing rate with


duration, the authors showed that when the short cue was in the neuron’s response field, activity first increased, and then decreased, as duration approached, and then passed the short cue duration. In yet another recent monkey physiology study, Maimon et al. (2006) were able to show that neural responses in LIP were linked to the initiation of a temporally guided action, even in the absence of an external cue, showing that this region is critical for control of behavior based on internally generated temporal signals. Additional analyses demonstrated that this timing signal was not related to specific aspects of the visual stimulus or the motor action, but seemed to reflect a purely temporal signal to initiate an action.

Evidence for a similar system has been demonstrated in humans using functional neuroimaging (for reviews, see Coull, 2004; P. A. Lewis & Miall, 2003). For example, Coull and colleagues presented subjects with a rapidly changing stream of colored dots, and their task was to either report the average color of the stream of dots, to estimate its duration, or to divide their attention between the two tasks (Coull, Vidal, Nazarian, & Macar, 2004). Reaction time and error data showed that subjects were able to divide their attention between the two tasks in a graded fashion. As subjects dedicated more attention to the temporal discrimination, activity in the inferior parietal cortex increased bilaterally, demonstrating that this area is critical for temporal duration estimation. Importantly, in both cases subjects were being asked to perform attentionally demanding tasks, and the stimulus was always the same. The only difference was whether they were paying attention to time or color, so the increased activity in the inferior parietal cortex as attention to time increased must be linked to increased demands on at least one component of the temporal processing system.

Finally, studies of patients with lesions of the parietal cortex demonstrate that damage to this area leads to impaired temporal processing. The role of the parietal cortex in the perception of time was first noted by the neuropsychologist MacDonald Critchley (Critchley, 1953; see also Walsh, 2003; Walsh & Cowey, 2006), who argued that, “[p]ure temporal disorientation…occurring independently of spatial disorders, is a rarer phenomenon, for more often, the two are combined” (p. 352). More recent neuropsychological studies have demonstrated more subtle temporal deficits associated with hemispatial neglect after lesions of the right parietal lobe. Husain and colleagues (1997) demonstrated abnormal deployment of temporal attention associated with neglect using an attentional blink paradigm (see also Hillstrom, Husain, Shapiro, & Rorden, 2004; Shapiro, Hillstrom, & Husain, 2002). Similarly, Bonneh et al. (2004) showed that temporal alternation rates in binocular rivalry were altered after right parietal lesions. Finally, patients with neglect demonstrate deficits in apparent motion perception that are not attributable to spatial deficits (Battelli et al., 2001; Battelli, Cavanagh, Martini, & Barton, 2003), leading Batelli and colleagues (2007) to argue that the right inferior parietal lobule houses the “when” pathway. Consistent with our current proposal, Batelli et al. suggest that the left inferior parietal may play a critical role in timing within a linguistic context, but focus on lower-level timing functions, such as phoneme discrimination. NEURAL BASIS OF TEMPORAL SEQUENCE REPRESENTATION

The above studies suggest that at least one aspect of time perception, cognitive time estimation, depends on parietal structures in both humans and non-human primates,


consistent with an evolutionarily conserved basis for this function in the parietal cortex. Our suggestion is that temporal sequence, or "ordinal" information is crucial for temporal-spatial metaphors. The above reviewed studies suggest that the basic representation of temporal information (estimation of duration) lies in the intraparietal sulcus. In addition, fMRI studies suggest that verbal information is represented in nearby regions of the inferior parietal lobe (see e.g., Simon, Mangin, Cohen, Le Bihan, & Dehaene, 2002). By combining the basic representation of time with a verbal code, humans acquire the semantic representation of ordinal temporal sequences. Similar models have been proposed for color name knowledge in the ventral visual pathway (Martin, Haxby, Lalonde, Wiggs, & Ungerleider, 1995 ; Martin, Wiggs, Ungerleider, & Haxby, 1996; Simmons et al., 2007) and for action verbs such as kick, lick and pick, which evoke different body part representations, and correspondingly elicit activation in different regions of motor cortex (Hauk, Johnsrude, & Pulvermuller, 2004; Pulvermuller, 2005). Here we suggest that time information has a similar “basic” representation and “semantic” representation in adjacent cortical regions for the perception of time and the semantic representation of temporal sequences (for a schematic representation of this model, see Figure 2).

Figure 2. A schematic representation of the brain areas and representations that may constrain the TIME IS SPACE metaphor. Basic representations of time and space are represented along the intraparietal sulcus, with the semantic representation of temporal sequences arising through a confluence of basic temporal information and linguistic information in the inferior parietal lobule. Interactions between these three representations may provide a neural substrate that makes temporal-spatial metaphors more likely.


Evidence in favor of the claim that the parietal lobe (especially the inferior

parietal lobule) is involved in representation of abstract temporal sequences comes from several sources. In an early study, Luria, Tsvetkova, and Futer (1965) report the case of a Russian composer (V. G. Shebalin), who suffered two strokes to the temporal and temporo-parietal regions of the left hemisphere. The patient developed a profound aphasia, but showed preserved musical abilities, producing ten new compositions, and rewriting three of his previous compositions, some of which were highly regarded by his contemporaries. Relevant to our point here, Luria notes that “serial forms of speech (days of the week, months of the year)” were impaired, showing that lesions to these areas can lead to impairments in these linguistic forms. In his early textbook, Traumatic Aphasia (Luria, 1970), Luria notes that subjects with lesions of the inferior parietal lobule (including the angular and supramarginal gyri) might be able to name the days of the week in correct order, but be unable to recite them backwards or answer such questions as, "What day comes before Wednesday?" Luria regarded this as evidence that such patients could not conceptualize or operate on ordinal sequences as a whole.

More recently, Turconi and Seron (2002) report the case of a patient, CO, who demonstrated the classic symptoms of Gerstmann’s syndrome, acalculia, agraphia, left-right confusion and finger agnosia (Mayer et al., 1999) after a stroke that damaged the left parietal cortex. CO showed intact performance on a series of quantity tasks where the numerical magnitude (cardinal representation) was accessed, such as giving a number that was either smaller or larger than a target numeral. However, when tested on order tasks that tapped into the sequential (ordinal) representation of numbers such as stating whether a number came before or after 5, he was highly impaired. That is, when asked about quantity, CO was unimpaired, but when asked about order with the same stimuli, he showed a profound impairment. Furthermore, the authors note that CO’s “performance was compromised for all series, especially for ‘before’ questions” (p. 913) demonstrating that lesions that affect ordinal numerical representations can also affect other non-numerical ordinal sequences, and that this impairment is worse when subjects are asked to work backwards along the sequence, as noted by Luria above.

Martory et al. (2003) reported the case of patient HP, who also demonstrated Gerstmann’s syndrome after a more circumscribed lesion which included only the white matter underlying the left angular gyrus, sparing the inferior parietal cortex, but leaving it disconnected from other brain regions. Martory et al. note that, “HP experienced great difficulty in simply counting from one to twenty. He resorted to external help such as counting on his fingers and made numerous errors. He experienced difficulties in other sequential or linear lexicons (i.e. he showed a clear increase in response time) such as reciting the days of the week or the months of the year, as well as in positioning a day in a sequence” (p. 327) consistent with the notion that both numerical and non-numerical sequential representations are impaired together after disconnection of the inferior parietal lobe.

Conversely, Cappelletti et al. (2001) report case study of a patient with semantic dementia due marked left temporal lobe atrophy. Their patient, IH, was tested on a standard battery of neuropsychological tasks and showed severe impairments in semantic processing, such that when he was asked to come up with as many members of a specific category as possible in one minute, IH failed to produce a single exemplar (controls


produced on average 117 items). However, IH showed remarkably intact processing of ordinal sequences, including numerical and temporal sequences. For example, when asked to count, or when asked what number came next in a sequence, IH was 100% correct, as were controls. Similarly, he was 100% correct when asked to convert written number words to spoken number words, when asked to convert written Arabic numbers to written number words and vice versa, and in a magnitude comparison task. IH was also remarkably unimpaired in his knowledge of time series. In a category fluency test of the days of the week, IH was perfect (7/7) and for months of the year, he generated 9/12. Similarly, when asked to classify words, he correctly classified all 7 days of the week, and all 12 months of the year.

Taken together, this pattern of impaired and preserved abilities in patients with lesions to the temporal and parietal corticies suggests that representations of numerical information and temporal sequences, such as the months of the year and days of the week are processed by neural machinery in the region of the inferior parietal. Numerous studies, spanning over 40 years, have demonstrated an association between lesions of the inferior parietal lobule and impaired processing of sequences including numerical and temporal sequences. Conversely, in patient IH, who had semantic dementia due to degeneration of the temporal lobe, but which left the parietal lobe intact, his ability to perform sequential tasks, including numerical and temporal sequence tasks, was spared. We argue that this association between the inferior parietal and these sequences is a result of a convergence of linguistic information and basic magnitude representation in the inferior parietal cortex (for a related view of semantic knowledge, see Damasio & Damasio, 1994).

THE NEURAL BASIS OF SPATIAL COGNITION It is well established that the parietal cortex contains multiple representations of space (Cohen & Andersen, 2002; Colby & Goldberg, 1999) and functional dissociation of these spatial maps is possible using functional neuroimaging (for a recent review see Culham & Valyear, 2006). In general, we wish to review a few important points about the neural representation of space. First, different regions of the parietal cortex are involved in representing space in different coordinate frames, such as eye-centered, head-centered or even hand-centered coordinates (Colby & Goldberg, 1999). Second, different regions of cortex are involved in representing near and far space (Colby, Duhamel, & Goldberg, 1993b; Medendorp & Crawford, 2002). Third, different parietal regions are involved in representing space in ego and allocentric based reference frames (Olson, 2003; Snyder, Grieve, Brotchie, & Andersen, 1998). Indeed, it is often possible to dissociate these reference frames in patients with spatial deficits such as neglect or extinction after damage to the parietal cortex (Halligan & Marshall, 1991; Maravita, Spence, Clarke, Husain, & Driver, 2000).

Recent work in both electrophysiology (Cohen & Andersen, 2002; Colby & Goldberg, 1999) and neuroimaging (Orban, Van Essen, & Vanduffel, 2004) has begun to converge on specific regions of the parietal lobe as the possible neural bases for the spatial representations that we discuss here. Based on architectonic criteria (J. W. Lewis & Van Essen, 2000a), connectivity patterns (Felleman & Van Essen, 1991; J. W. Lewis & Van Essen, 2000b) and neuronal response properties, the macaque intraparietal sulcus has been divided into numerous subregions which represent space in a variety of different


frames of reference. Identification of putative human homologues of macaque IPS regions is tentative, both because the parietal and frontal cortices are differentially expanded in humans compared with similar regions in macaques (Van Essen et al., 2001) and because direct comparisons between monkey and human fMRI responses to the same stimuli have suggested the presence of additional maps in the human IPS (Orban et al., 2006; Orban et al., 2003). Nevertheless, the overall pattern of posterior-to-anterior organization, with a systematic transformation from sensory to effector-specific properties, presents striking parallels with that observed in previous studies of monkey physiology (Culham & Valyear, 2006; Simon et al., 2002). We will focus on three of these putative homologies, areas hLIP, hVIP and hAIP, where the ‘h’ identifies these as putative human homologues of the aforementioned monkey areas.

Area LIP and hLIP. Many neurons in macaque area LIP are organized into a retinotopic map (Ben Hamed, Duhamel, Bremmer, & Graf, 2001), represent target position in an eye-centered frame of reference (Colby, Duhamel, & Goldberg, 1995) (but see Mullette-Gillman, Cohen, & Groh, 2005) and are highly active during memory guided saccades (Colby, Duhamel, & Goldberg, 1993a, 1996; Snyder, Batista, & Andersen, 2000). Additionally, these neurons are involved in spatial updating, even before an eye movement is made (Colby et al., 1995; Duhamel, Colby, & Goldberg, 1992). Reversible inactivation of this region leads to deficits in saccade execution, demonstrating its causal role in eye movements (Li & Andersen, 2001; Wardak, Olivier, & Duhamel, 2002).

Recent neuroimaging studies have demonstrated as many as four retinotopic maps within the posterior portion of the human intraparietal sulcus, and there is still debate as to which of these maps constitutes hLIP, and whether the additional maps are evolutionarily new (Schluppeck, Glimcher, & Heeger, 2005; Sereno, Pitzalis, & Martinez, 2001; Silver, Ress, & Heeger, 2005; Swisher, Halko, Merabet, McMains, & Somers, 2007). Despite this ambiguity, recent studies have shown that posterior IPS responds in an effector independent manner (Astafiev et al., 2003; Medendorp, Goltz, Crawford, & Villis, 2005) and is jointly active for attending, pointing, and making saccades to peripheral targets (see also Simon et al., 2002). In addition, this region demonstrates delay period activity (Schluppeck, Curtis, Glimcher, & Heeger, 2006) and is involved in spatial updating (Medendorp, Goltz, Villis, & Crawford, 2003; Merriam, Genovese, & Colby, 2003) as is macaque LIP. More recently, Morris et al. (2007) have used rTMS to show that inactivation of this region leads to deficits in a double-step saccade paradigm. Taken together, these results suggest that at least one of the maps identified in posterior parietal cortex is the human homologue of macaque LIP.

Area VIP and hVIP. Macaque area VIP contains populations of neurons that represent targets in either a head-centered or eye-centered frame of reference (Duhamel, Bremmer, BenHamed, & Graf, 1997; Duhamel, Colby, & Goldberg, 1998), although some receptive fields (RFs) are partially shifting or gain-modulated by eye position (Avillac, Deneve, Olivier, Pouget, & Duhamel, 2005). That is, when the eyes are moved around in the visual field, the best stimulus location either remains fixed relative to the position of the head (head-centered) or shifts partway between the position relative to the eyes and that relative to the head (partially-shifting receptive fields). Additionally, many VIP neurons have joint tactile and visual motion-determined receptive fields (Duhamel et al., 1998), and are strongly driven by optic flow fields (Bremmer, Duhamel, Ben Hamed,


& Graf, 2002; Zhang, Heuer, & Britten, 2004). To date, two fMRI studies have attempted to identify hVIP. Bremmer et al. (2001) tested for regions that were conjointly activated by visual, tactile and auditory motion. Only one such region was identified in the fundus of the IPS, anterior to hLIP, and consistent with the known organization in monkey. In another study, Sereno and Huang (2006) mapped visual and tactile responsiveness, and demonstrated the presence of visual and tactile maps in the mid-IPS near to, but slightly mesial and superior to the peaks of the Bremmer et al. study. They found that these maps were spatially aligned, so that RFs responding to a specific location in the visual field responded to tactile stimulation on corresponding portions of the face, further suggesting that this is the human homologue of macaque VIP.

Area AIP and hAIP. Macaque area AIP represents space in hand-centered coordinates, and is crucial for fine grasping (Iwamura, Iriki, & Tanaka, 1994; Taira, Georgopolis, Murata, & Sakata, 1990). Neurons in this area are bimodal (visual-tactile) (Murata, Gallese, Luppino, Kaseda, & Sakata, 2000; Saito, Okada, Morita, Yonekura, & Sadato, 2003; Taira et al., 1990), so that, when the hand moves, the visual receptive field remains in a fixed position relative to the hand. Neurons in this area, in combination with area CIP, which extracts 3-D shape, are critical for correctly reaching and grasping 3-D objects (Sakata et al., 1999; Shikata et al., 2001) and tools (Hihara, Obayashi, Tanaka, & Iriki, 2003; Iriki, Tanaka, & Iwamura, 1996; Obayashi et al., 2001). Neurons in monkey area AIP respond in a hand-centered manner and are involved in fine grasping, but not necessarily in the transport phase of the action. Several studies have used these properties to identify hAIP (for a review see Culham, Cavina-Pratesi, & Singhal, 2005). In the first study of this kind, regions of the IPS that responded when subjects grasped objects were identified (Binkofski et al., 1998). The region identified as hAIP overlapped nearly completely with a region that was damaged in a patient who demonstrated a selective impairment in fine grasping behavior (Binkofski et al., 1998). Other studies identified a region of the anterior IPS that responded more strongly to grasping than to reaching (Culham et al., 2003) or to finger pointing (Simon et al., 2002). As expected from monkey maps, activations in these putatively homologous regions to area AIP consistently lie anterior to the activations identified with the putative hLIP and hVIP. SYNESTHESIA, TEMPORAL COGNITION AND SPATIAL REPRESENTATIONS

One final source of evidence that may be relevant to our understanding of the neural connections between time and space comes from the study of people who experience synesthesia. Synesthesia is a condition in which perceptual and conceptual stimuli, such as letters and numbers, days of the week, or months of the year lead to involuntary, automatic, systematic and stable experiences in a second, unstimulated sensory modality (Baron-Cohen & Harrison, 1997; Cytowic, 1989/2002; Hubbard & Ramachandran, 2005; Ramachandran & Hubbard, 2001). Some synesthetes report seeing colors when viewing letters and numbers, and others report that the months of the year are arranged in a circular pattern. In recent years, a growing body of evidence has suggested that synesthesia is a genuine perceptual experience, which may affect as many as 1 in 20 people (for a recent review, see Hubbard & Ramachandran, 2005).

Particularly relevant to our purposes here are those synesthetes who report that they see months of the year, days of the week, and other abstract sequences as having a spatial layout (Figure 3). That is, for these people, TIME IS SPACE is not simply a


metaphor, but is a fundamental aspect of their daily experience (Sagiv, Simner, Collins, Butterworth, & Ward, 2006; Seron, Pesenti, Noel, Deloche, & Cornet, 1992; Smilek, Callejas, Dixon, & Merikle, 2007). These representations may have a spatial two- or, more often, three-dimensional form, and may be colored or not. Visuo-spatial forms for numerals, letters and time are particularly common in color-synesthetes (80% of grapheme-color synesthetes reporting at least one type of visuo-spatial form), and that if a synesthete has one type of form then there is a very strong tendency for them to show at least one other type of form (Flournoy, 1893; Sagiv et al., 2006), consistent with the patient data reviewed above. Sagiv et al. suggest therefore that synesthetic visuo-spatial forms are related to ordinal representations of not only number, but also time.

Figure 3. Examples of synesthetic calendars. Synesthete MPO experiences an integrated calendar, in which the year is seen as a spiral, with the weeks spiraling around the year, and the parts of the day spiraling around each day of the week. Her sister, synesthete EPO experiences the months of the year in a 3-D oval form, which rotates towards her. Interestingly, her normal position is looking upwards, towards the past. If she wishes to see the future, she must turn around, and look behind her. Finally, synesthete MP experiences the decades and the months of the year as having a curvilinear shape. Notice the upward and leftward motion in the decades in MPs calendar (MP is MPO and EPO’s mother). One concern about these synesthetic representations is that they may constitute

complex forms of learned associations. There are however several sources of evidence that argue against this. As reviewed by Cytowic (1989/2002), many studies show that synesthesia runs in families, suggesting a clear genetic basis for this phenomenon (e.g., Bailey & Johnson, 1997; Barnett et al., 2007; Baron-Cohen, Burt, Smith-Laittan, Harrison, & Bolton, 1996). Different forms of synesthesia can also occur within the same family (Barnett et al., 2007; Ward, Simner, & Auyeung, 2005). Recent studies suggest that time-space synesthesia in particular co-occurs with other forms of synesthesia (Day, 2005; Sagiv et al., 2006), which can be more easily explained by a genetically based facilitation for the development of synesthesia than by learned associations. Finally, several studies have attempted to train synesthesia-like associations in non-synesthetes.


None of them was successful in establishing synesthetic associations in non-synesthetes, even after substantial practice (e.g., Howells, 1944; Kelly, 1934). Nunn et al. (2002) trained non-synesthetes to mimic synesthetic reports of colors for words, and found that V4/V8 activation in response to spoken words was observed only in synesthetes, whereas controls failed to show such activation even after extensive training to imagine the corresponding colors. Contrary to this failure to find robust training effects in non-synesthetes, two studies have demonstrated that new synesthetic associations can be trained in someone who was already synesthetic (Mills et al., 2002; Rizzo & Eslinger, 1989), again suggesting an innate facilitation in some people for the development of synesthesia.

We have proposed that these synesthetic calendars are a result of cross-activation similar to that seen in grapheme-color synesthesia (Hubbard et al., 2005; Hubbard & Ramachandran, 2005; Ramachandran & Hubbard, 2001), which has been supported by recent data from diffusion tensor imaging (Rouw & Scholte, 2007). However, in this case, we propose that the cross-activation occurs between regions of the parietal cortex involved in the processing of temporal quantities (Coull et al., 2004; P. A. Lewis & Miall, 2002) and abstract spatial maps (Cohen & Andersen, 2002; Colby & Goldberg, 1999) as described above. Consistent with this hypothesis, Spalding and Zangwill (1950) report a patient with a gunshot wound, which entered near the right angular gyrus and lodged near the left temporal–parietal junction. Five years after the injury he complained of spatial problems and showed difficulty in number tasks. In addition, the patient, who experienced synesthesia prior to the injury, complained that his spatial synesthesia for months, days of the week, and letters of the alphabet was no longer distinct.

Although conscious synesthetic experiences are present in only a small portion of the population, they are still related to, and continuous with non-synesthetic experiences. We argue that because they reach conscious awareness, the experiences reported by synesthetes simply allow us to see more clearly the same sort of processes that are occurring in all of us (see also Ramachandran & Hubbard, 2001). To a lesser or greater degree, everyone retains a certain degree of connectivity between these brain regions, but in synesthetes, these connections are numerous enough, or strong enough, to lead to a perceptual experience (see Rouw & Scholte, 2007). However, in those of us for whom these connections do not lead to synesthetic experience, they still yield a sort of conceptual “rightness” which leads to the acquisition of specific classes of metaphorical associations, such as the TIME IS SPACE metaphor being described here.

Taken together, results from behavioral studies, reports from synesthetes and testing of semantic dementia patients suggests a close tie between spatial representations and representations of abstract sequences, including numbers, days of the week and months of the year. We therefore suggest that many of the conclusions we have drawn previously about the neural connections between numerical and spatial representations (Hubbard et al., 2005) may also apply to other abstract sequences, such as days of the week or months of the year. These temporal sequences may be exactly the right type of representation to be mapped onto spatial dimensions in the parietal lobe. POSTERIOR PARIETAL CORTEX AND TEMPORAL-SPATIAL METAPHORS Given the proximity of temporal and spatial representations, we suggest that map-map interactions similar to those that have been demonstrated for numbers and space


(Hubbard et al., 2005; Hubbard, Pinel, Jobert, Le Bihan, & Dehaene, submitted) are also important for the metaphorical connection between time and space. This brain-based constraint provides a neural mechanism whereby the acquisition of such spatial metaphors for time is facilitated, and thereby passed on to subsequent generations, but it is does not uniquely specify the eventual forms of the metaphors used in a given culture. Based on the multiplicity of reference frames in the parietal cortex, we would predict that it should be possible to map time onto to space not only in a forwards-backwards direction as is commonly seen, but also in a left-right direction, and in both an ego- or an allocentric reference frame, as discussed above (Núñez et al., 2006).

These parietal networks are not immutable, but rather must interact with experience, perhaps leading to slightly different patterns of neural connectivity depending on differing cultural contexts. Recent research has shown that even two weeks of tool use is sufficient to lead to the development of increased connectivity between relevant brain regions in macaque monkeys (Iriki, 2005). It would therefore be highly surprising if a lifetime of cultural experiences in which different metaphors are more commonly used, and in which different aspects of space are foregrounded, did not lead to selective strengthening of certain sets of parietal links over others. Experiments by Torralbo, Santiago, & Lupiáñez (2006) suggest that there is substantial flexibility in conceptual projection as a result of attentional dynamics, even within an individual subject. One interesting, although difficult to test, prediction of this model is that ego-RP metaphors might elicit increased activation of parietal regions involved in ego-centric representations of space, while allo-RP metaphors might elicit increased activation of allocentric representations of space.

Another prediction is based on the observation that although numbers are conventionally mapped onto space in a left-right frame of reference, time is conventionally mapped onto space in a front-back frame of reference. We would therefore predict that numerical and temporal representations are anatomically connected to different spatial representations (perhaps due to slight differences in the neural substrates for time and number). However, it is also possible that these differences reflect differences in the structure of experience. For example, numbers are usually encountered in a reading situation, which for Western subjects would set up a bias towards small numbers on the left and large numbers on the right (see Hubbard et al., 2005), whereas time is experienced as we traverse a front-back trajectory (see e.g., M. Johnson, 1987). Indeed, these two possibilities are not mutually exclusive, as neural differences might be phylogenetic consequences of experiential differences, such that the experience of traversing space in a front-back direction would lead to differences in the representation of time and number in the IPS. CONCLUSIONS The Neural Underpinnings of Metaphor

Taken together, these results suggest a deep neural connection between spatial representations and abstract sequences, such as numbers, days of the week and months of the year, most likely based on adjacent brain regions within the parietal lobe dedicated to high-level, multimodal representations of space, time and number. Additionally, these representations are present in many non-human animals and in human infants (Feigenson, Dehaene, & Spelke, 2004), both of whom lack language and the extended cultural


education that adult humans have received. We therefore suggest that these spatial representations should be thought of not simply as a result of our embodied experience, but also as a result of the structure of our brains themselves.

The brain is not a passive receptacle for experience, upon which conflation is free to act upon in any manner experience provides. Instead, the brain plays an active role in interpreting and constructing our perceptions of the world. These constructive processes are fundamentally constrained through our long phylogenetic experience with the world around us so that our brains have become tuned to the important features of the world. However, some of these features also lead to conflations of neural processing, such as the conflation of time and space seen in the parietal lobe. One important aspect of both temporal and spatial processing that might partially explain why they come to be represented in similar brain regions is that both time and space need to be represented in a multi-modal or supra-modal manner. The parietal lobe, with its confluence of information from vision, audition and touch seems ideally suited to perform these supra-modal computations, and extract the features of the environment that do not vary with modality, such as space, time and number (see also Walsh, 2003). These non-arbitrary features of the world may lead to conflations which structure our experience of the world, and therefore lead to systematic regularities in our conceptual systems, which may be reflected in our conventionalized metaphors.

This line of thinking, although illustrated here with the specific example of TIME IS SPACE, may have a general applicability. For example, we refer to “loud shirts” and “sharp cheddar” but not the other way around (e.g., we do not refer a pinprick as being cheesy). Why is it that specific classes of sensory stimuli serve as sources for metaphors, while others serve as targets? We propose that this may also be due to the pattern of preexisting brain wiring derived from evolutionary experience. For example, seeing colors in response to hearing sounds (sound-color synesthesia) is a fairly common form of synesthesia, and accordingly, we would predict that sound might serve as the source domain, and vision the target domain in a number of metaphors {see also \Ramachandran, 2001 #739}. Similarly, one of the most famous cases of synesthesia, the “man who tasted shapes” felt tactile shapes when he tasted foods (taste-touch synesthesia). The proximity of gustatory cortex in the insula to primary somatosensory cortex may account for this form of synesthesia, and accordingly, for the use of metaphors such as “sharp cheddar” in our everyday speech.

Detailed linguistic analyses of English and German “synesthetic” metaphors (Day, 1996; Ullmann, 1945) have provided partial support for these predictions, such that the directionality of synesthetic mappings are mostly conserved. For example, audition is often the trigger for synesthetic experiences and is also the source domain for synesthetic metaphors. On the other hand, Day notes that the most common concurrent synesthetic experience is color, while the most common target domain for synesthetic metaphors is touch. However, the neural constraints that we have argued for here are but one of many, and we would expect that they would interact with other, more traditional metaphorical constraints, such as the constraint that source domains are more concrete than target domains, that both source and target domains should be complexly structured, and that mappings should preserve inferences. Despite the high prevalence of grapheme-color synesthesia, color to letter metaphors may be absent in language because they fail to meet these other metaphorical constraints. Clearly these other constraints are also integrated


into the structure of the brain, and future research should examine how these constraints interact at the neural level. Neural Constraints on Cultural Evolution Although we have focused here on data supporting the role of parietal structures in the development of these cognitive constructs, we are not denying that culture plays a critical role. It is simply that, due to the long focus on the experiential side of the explanation, we feel that cognitive linguistics has been doing its work with only half the tools available to it. This paper is one attempt to reintroduce to cognitive linguistics additional tools for making sense of human conceptual structure. Indeed, we believe that taking the points in this paper seriously will have profound implications for how we conceive of cultural evolution generally. Until recently, culture has been treated as something independent of biology, and it has been implicitly assumed that cultural variation could be essentially limitless. However, as George Lakoff notes:

It is not the case that almost any metaphor is possible. Possible metaphors are constrained in many ways... The possibilities for what Joe Grady has called "primary metaphor" are constrained by (a) sensory-motor and other source-domain inferential mechanisms; (b) regularly repeated real-world experiences, especially in the early years, in which source and target domains are systematically correlated; (c) mechanisms of recruitment learning. (http://www.edge.org/discourse/lakoff.html)

That is, cultural variability is not limitless. Previous work in cognitive linguistics has stressed the common experiences which lead to shared metaphorical representations. Here we want to add a level of neural constraints to this. We argue that, while culture can influence and shape human cognitive systems, those cultural inventions which survive, and which are passed on to future generations are those that are best suited to the structure of our brains (Deacon, 1997; Dehaene, 2005). For example, in discussing the neuronal recycling hypothesis, Dehaene states:

[E]ach cortical region or network possesses intrinsic properties that are adapted to the function it evolved for, and are only partially modifiable during the cultural acquisition process. Cultural learning in humans may never totally overturn such preexisting biases, but rather change them minimally as needed. Thus cultural objects may not be infinitely malleable, and should in fact often reflect intrinsic constraints of the underlying neural networks. (Dehaene, 2005, p. 148).

In this paper, we have explored one potential set of neural constraints, the proximity of temporal and spatial representations in the region of the parietal cortex, which may favor the development of the TIME IS SPACE metaphor, perhaps by increasing the possibility of neural conflation, but also by providing a substrate for the shared experience of time and space. Indeed our view is that these types of representations may have evolved both through the brain and for the brain. Similarly for metaphorical conceptual systems, our brains both shape and are shaped by the cultures we live in. By thinking of culture as something that co-evolves with the brain, we may view these two influences as complimentary, leading to the richness and depth of our conceptual systems. Future


research bridging these two approaches may yield much deeper insights into not only the basis of metaphor, but indeed, the neural basis of our entire conceptual system.


Acknowledgements

The authors thank Rafael Núñez, Esther Pascual and V. S. Ramachandran for many valuable discussions of the ideas contained in this article, and Lisa E. Williams, David Eagleman and two anonymous reviewers for comments on the particular arguments put forward here. This research was supported by a Marie-Curie Numeracy and Brain Development (NUMBRA) postdoctoral fellowship (E.M.H.) and a postdoctoral fellowship of the Swiss National Science Foundation (U.T.).


References

Astafiev, S. V., Shulman, G. L., Stanley, C. M., Snyder, A. Z., Van Essen, D. C., & Corbetta, M. (2003). Functional organization of human intraparietal and frontal cortex for attending, looking, and pointing. . Journal of Neuroscience, 23, 4689-4699.

Avillac, M., Deneve, S., Olivier, E., Pouget, A., & Duhamel, J. R. (2005). Reference frames for representing visual and tactile locations in parietal cortex. Nature Neuroscience, 8(7), 941-949.

Bailey, M. E. S., & Johnson, K. J. (1997). Synaesthesia: Is a genetic analysis feasible? In S. Baron-Cohen & J. E. Harrison (Eds.), Synaesthesia: Classic and contemporary readings (pp. 182-207). Oxford, England: Blackwell.

Barnett, K. J., Finucane, C., Asher, J. E., Bargary, G., Corvin, A. P., Newell, F. N., et al. (2007). Familial patterns and the origins of individual differences in synaesthesia. Cognition.

Baron-Cohen, S., Burt, L., Smith-Laittan, F., Harrison, J., & Bolton, P. (1996). Synaesthesia: prevalence and familiality. Perception, 25(9), 1073-1079.

Baron-Cohen, S., & Harrison, J. E. (Eds.). (1997). Synaesthesia: Classic and contemporary readings. Malden, MA, US: Blackwell Publishers Inc.

Battelli, L., Cavanagh, P., Intriligator, J., Tramo, M. J., Henaff, M. A., Michel, F., et al. (2001). Unilateral right parietal damage leads to bilateral deficit for high-level motion. Neuron, 32(6), 985-995.

Battelli, L., Cavanagh, P., Martini, P., & Barton, J. J. (2003). Bilateral deficits of transient visual attention in right parietal patients. Brain, 126(Pt 10), 2164-2174.

Battelli, L., Pascual-Leone, A., & Cavanagh, P. (2007). The 'when' pathway of the right parietal lobe. Trends in Cognitive Sciences, 11(5), 204-210.

Ben Hamed, S., Duhamel, J. R., Bremmer, F., & Graf, W. (2001). Representation of the visual field in the lateral intraparietal area of macaque monkeys: a quantitative receptive field analysis. Experimental Brain Research, 140(2), 127-144.

Binkofski, R., Dohle, C., Posse, S., Stephan, K. M., Hefter, H., Seitz, R. J., et al. (1998). Human anterior intraparietal area subserves prehension. Neurology, 50, 1253-1259.

Bonneh, Y. S., Pavlovskaya, M., Ring, H., & Soroker, N. (2004). Abnormal binocular rivalry in unilateral neglect: evidence for a non-spatial mechanism of extinction. Neuroreport, 15(3), 473-477.

Boroditsky, L. (2000). Metaphoric structuring: Understanding time through spatial metaphors. Cognition, 75, 1–28.

Boroditsky, L. (2001). Does language shape thought? English and Mandarin speakers' conceptions of time. Cognitive Psychology, 43(1), 1-22.

Boroditsky, L., & Ramscar, M. (2002). The roles of body and mind in abstract thought. Psychological Science, 13, 185–188.

Bremmer, F., Duhamel, J. R., Ben Hamed, S., & Graf, W. (2002). Heading encoding in the macaque ventral intraparietal area (VIP). Eurpean Journal of Neuroscience, 16(8), 1554-1568.

Bremmer, F., Schlack, A., Shah, N. J., Zafiris, O., Kubischik, M., Hoffmann, K.-P., et al. (2001). Polymodal motion processing in posterior parietal and premotor cortex: A


human fMRI study strongly implies equivalencies between humans and monkeys. Neuron, 29, 287-296.

Buhusi, C. V., & Meck, W. H. (2005). What makes us tick? Functional and neural mechanisms of interval timing. Nature Reviews Neuroscience, 6(10), 755-765.

Cappelletti, M., Butterworth, B., & Kopelman, M. (2001). Spared numerical abilities in a case of semantic dementia. Neuropsychologia, 39, 1224–1239.

Casasanto, D., & Boroditsky, L. (2007). Time in the mind: Using space to think about time. Cognition.

Casasanto, D., Boroditsky, L., Phillips, W., Greene, J., Goswami, S., Bocanegra-Thiel, S., et al. (2004). How deep are effects of language on thought? Time estimation in speakers of English, Indonesian, Greek, and Spanish. . Paper presented at the Proceedings of the 26th Annual Conference of the Cognitive Science Society, Chicago, IL.

Chen, J. Y. (2007). Do Chinese and English speakers think about time differently? Failure of replicating Boroditsky (2001). Cognition, 104(2), 427-436.

Cohen, Y. E., & Andersen, R. A. (2002). A common reference frame for movement plans in the posterior parietal cortex. Nature Reviews Neuroscience, 3, 553-562.

Colby, C. L., Duhamel, J. R., & Goldberg, M. E. (1993a). The analysis of visual space by the lateral intraparietal area of the monkey: the role of extraretinal signals. Progress in Brain Research, 95, 307-316.

Colby, C. L., Duhamel, J. R., & Goldberg, M. E. (1993b). Ventral intraparietal area of the macaque: anatomic location and visual response properties. Journal of Neurophysiology, 69(3), 902-914.

Colby, C. L., Duhamel, J. R., & Goldberg, M. E. (1995). Oculocentric spatial representation in parietal cortex. Cerebral Cortex, 5(5), 470-481.

Colby, C. L., Duhamel, J. R., & Goldberg, M. E. (1996). Visual, presaccadic, and cognitive activation of single neurons in monkey lateral intraparietal area. Journal of Neurophysiology, 76(5), 2841-2852.

Colby, C. L., & Goldberg, M. E. (1999). Space and attention in parietal cortex. Annual Review of Neuroscience, 22, 319-349.

Coull, J. T. (2004). fMRI studies of temporal attention: allocating attention within, or towards, time. Cognitive Brain Research, 21(2), 216-226.

Coull, J. T., Vidal, F., Nazarian, B., & Macar, F. (2004). Functional anatomy of the attentional modulation of time estimation. Science, 303(5663), 1506-1508.

Critchley, M. (1953). The Parietal Lobes. London: Edward Arnold. Culham, J. C., Cavina-Pratesi, C., & Singhal, A. (2005). The role of parietal cortex in

visuomotor control: What have we learned from neuroimaging? Neuropsychologia, 44(13), 2668-2684.

Culham, J. C., Danckert, S. L., DeSouza, J. F., Gati, J. S., Menon, R. S., & Goodale, M. A. (2003). Visually guided grasping produces fMRI activation in dorsal but not ventral stream brain areas. Experimental Brain Research, 153(2), 180-189.

Culham, J. C., & Valyear, K. F. (2006). Human parietal cortex in action. Current Opinion in Neurobiology, 16(2), 205-212.

Cytowic, R. E. (1989/2002). Synesthesia: A Union of the Senses. New York: Springer-Verlag.


Damasio, A. R., & Damasio, H. (1994). Cortical systems for retrieval of concrete knowledge: the convergence zone framework. In C. Koch & J. L. Davis (Eds.), Large-Scale Neuronal Theories of the Brain (pp. 61-74). Cambridge, MA: MIT Press.

Day, S. A. (1996). Synaesthesia and the synaesthetic metaphors [Electronic Version]. Psyche, 2, from http://psyche.cs.monash.edu.au/v2/psyche-2-32-day.html

Day, S. A. (2005). Some demographic and socio-cultural aspects of synesthesia. In L. C. Robertson & N. Sagiv (Eds.), Synesthesia: Perspectives from Cognitive Neuroscience. New York, NY: Oxford University Press.

Deacon, T. (1997). The Symbolic Species: The Coevolution of Language and the Brain. New York: W. W. Norton & Company.

Dehaene, S. (1997). The number sense: How the mind creates mathematics. New York: Oxford University Press.

Dehaene, S. (2005). Evolution of human cortical circuits for reading and arithmetic: The "neuronal recycling" hypothesis. In S. Dehaene, J. R. Duhamel, M. D. Hauser & G. Rizzolatti (Eds.), From Monkey Brain to Human Brain (pp. 133-158). Boston, MA: MIT Press.

Duhamel, J. R., Bremmer, F., BenHamed, S., & Graf, W. (1997). Spatial invariance of visual receptive fields in parietal cortex neurons. Nature, 389(6653), 845-858.

Duhamel, J. R., Colby, C. L., & Goldberg, M. E. (1992). The updating of the representation of visual space in parietal cortex by intended eye movements. Science, 255(5040), 90-92.

Duhamel, J. R., Colby, C. L., & Goldberg, M. E. (1998). Ventral intraparietal area of the macaque: congruent visual and somatic response properties. Journal of Neurophysiology, 79(1), 126-136.

Evans, V. (2003). The structure of time: Language, meaning and temporal cognition. Amsterdam: John Benjamins.

Feigenson, L., Dehaene, S., & Spelke, E. (2004). Core systems of number. Trends in Cognitive Science, 8(7), 307-314.

Felleman, D. J., & Van Essen, D. C. (1991). Distributed hierarchical processing in the primate cerebral cortex. Cerebral Cortex, 1(1), 1-47.

Flournoy, T. (1893). Des phénomènes de synopsie [On the phenomena of synopsia]. Genève: Charles Eggimann & Co.

Gallese, V., & Lakoff, G. (2005). The Brain's concepts: the role of the sensory-motor system in conceptual knowledge Cognitive Neuropsychology, 22(3-4), 455-479.

Gentner, D. (2001). Spatial metaphors in temporal reasoning. In M. Gattis (Ed.), Spatial schemas in abstract thought (pp. 203–222). Cambridge: MIT Press.

Gentner, D., Imai, M., & Boroditsky, L. (2002). As time goes by: Evidence for two systems in processing space > time metaphors. Language and Cognitive Processes, 17, 537-565.

Gibbs, R. (1994). The Poetics of Mind. Cambridge: Cambridge University Press. Grady, J. (1997). Foundations of meaning: primary metaphors and primary scenes.

University of California, Berkeley., Berkeley, CA. Halligan, P. W., & Marshall, J. C. (1991). Left neglect for near but not far space in man.

Nature, 350(6318), 498-500.


Hauk, O., Johnsrude, I., & Pulvermuller, F. (2004). Somatotopic representation of action words in human motor and premotor cortex. Neuron, 41(2), 301-307.

Hihara, S., Obayashi, S., Tanaka, M., & Iriki, A. (2003). Rapid learning of sequential tool use by macaque monkeys. Physiology and Behavior, 78(3), 427-434.

Hillstrom, A. P., Husain, M., Shapiro, K. L., & Rorden, C. (2004). Spatiotemporal dynamics of attention in visual neglect: a case study. Cortex, 40(3), 433-440.

Howells, T. H. (1944). The experimental development of color-tone synesthesia. Journal of Experimental Psychology, 34, 87-103.

Hubbard, E. M., Piazza, M., Pinel, P., & Dehaene, S. (2005). Interactions between number and space in parietal cortex. Nature Reviews Neuroscience, 6(6), 435-448.

Hubbard, E. M., Pinel, P., Jobert, A., Le Bihan, D., & Dehaene, S. (submitted). The place for the SNARC: Interactions between numerical and spatial representations in parietal cortex Journal of Cognitive Neuroscience.

Hubbard, E. M., & Ramachandran, V. S. (2005). Neurocognitive mechanisms of synesthesia. Neuron, 48(3), 509-520.

Husain, M., Shapiro, K., Martin, J., & Kennard, C. (1997). Abnormal temporal dynamics of visual attention in spatial neglect patients. Nature, 385(6612), 154-156.

Iriki, A. (2005). A prototype of homo-faber. A silent precursor of human intelligence in the tool-using monkey brain. In S. Dehaene, J. R. Duhamel, G. Rizzolatti & M. D. Hauser (Eds.), From Monkey Brain to Human Brain. Cambridge, MA: MIT Press.

Iriki, A., Tanaka, M., & Iwamura, Y. (1996). Coding of modified body schema during tool use by macaque postcentral neurones. Neuroreport, 7(14), 2325-2330.

Ivry, R. B., & Spencer, R. M. (2004). The neural representation of time. Current Opinion in Neurobiology, 14(2), 225-232.

Iwamura, Y., Iriki, A., & Tanaka, M. (1994). Bilateral hand representation in the postcentral somatosensory cortex. Nature, 369(6481), 554-556.

January, D., & Kako, E. (2007). Re-evaluating evidence for linguistic relativity: Reply to Boroditsky (2001). Cognition, 104(2), 417-426.

Johnson, C. (1999). Metaphor vs. Conflation in the acquisition of polysemy: the case of SEE. In M. K. Higara, C. Sinha & S. Wilcox (Eds.), Cultural, typological and psychological issues in cognitive linguistics (Vol. 152, pp. 155-169). Amsterdam: John Benjamins.

Johnson, M. (1987). The body in the mind: The bodily basis of meaning, imagination, and reason. Chicago: University of Chicago Press.

Johnson, M. H., & Vecera, S. P. (1996). Cortical differentiation and neurocognitive development: The parcellation conjecture. Behavioural Processes, 36(2), 195-212.

Kaas, J. H. (1997). Topographic maps are fundamental to sensory processing. Brain Research Bulletin, 44(2), 107-112.

Kelly, E. L. (1934). An experimental attempt to produce artificial chromaesthesia by the technique of the conditioned response. Journal of Experimental Psychology, 17, 315-341.

Kranjec, A. (2006). Extending spatial frames of reference to temporal concepts. Paper presented at the 28th Annual Conference of the Cognitive Science Society, Vancouver, BC.


Lakoff, G. (1987). Women, Fire, and Dangerous Things: What categories reveal about the mind. Chicago: University of Chicago Press.

Lakoff, G., & Johnson, M. (1999). Philosophy in the flesh: The embodied mind and its challenge to Western thought. New York: Basic Books.

Lakoff, G., & Johnson, M. H. (1980). Metaphors We Live By. Chicago: University of Chicago Press.

Leon, M. I., & Shadlen, M. N. (2003). Representation of time by neurons in the posterior parietal cortex of the macaque. Neuron, 38(2), 317-327.

Lewis, J. W., & Van Essen, D. C. (2000a). Mapping of architectonic subdivisions in the macaque monkey, with emphasis on parieto-occipital cortex. Journal of Comparative Neurology, 428(1), 79-111.

Lewis, J. W., & Van Essen, D. C. (2000b). Corticocortical connections of visual, sensorimotor, and multimodal processing areas in the parietal lobe of the macaque monkey. Journal of Comparative Neurology, 428(1), 112-137.

Lewis, P. A., & Miall, R. C. (2002). Brain activity during non-automatic motor production of discrete multi-second intervals. Neuroreport, 13(14), 1731-1735.

Lewis, P. A., & Miall, R. C. (2003). Distinct systems for automatic and cognitively controlled time measurement: evidence from neuroimaging. Current Opinion in Neurobiology, 13(2), 250-255.

Li, C. S., & Andersen, R. A. (2001). Inactivation of macaque lateral intraparietal area delays initiation of the second saccade predominantly from contralesional eye positions in a double-saccade task. Experimental Brain Research, 137(1), 45-57.

Luria, A. R. (1970). Traumatic Aphasia. The Hague: Mouton de Gruyter. Luria, A. R., Tsvetkova, L. S., & Futer, D. S. (1965). Aphasia in a composer (V. G.

Shebalin). Journal of Neurological Science, 2(3), 288-292. Maimon, G., & Assad, J. A. (2006). A cognitive signal for the proactive timing of action

in macaque LIP. Nature Neuroscience, 9(7), 948-955. Maravita, A., Spence, C., Clarke, K., Husain, M., & Driver, J. (2000). Vision and touch

through the looking glass in a case of crossmodal extinction. Neuroreport, 11(16), 3521-3526.

Martin, A., Haxby, J. V., Lalonde, F. M., Wiggs, C. L., & Ungerleider, L. G. (1995). Discrete cortical regions associated with knowledge of color and knowledge of action. Science, 270(5233), 102-105.

Martin, A., Wiggs, C. L., Ungerleider, L. G., & Haxby, J. V. (1996). Neural correlates of category-specific knowledge. Nature, 379(6566), 649-652.

Martory, M. D., Mayer, E., Pegna, A. J., Annoni, J. M., Landis, T., & Khateb, A. (2003). Pure global acalculia following a left subangular lesion. Neurocase, 9(4), 319-328.

Matlock, T., Ramscar, M., & Boroditsky, L. (2005). The experiential link between spatial and temporal language. Cognitive Science, 29, 655-664.

Mayer, E., Martory, M.-D., Pegna, A. J., Landis, T., Delavelle, J., & Annoni, J.-M. (1999). A pure case of Gerstmann syndrome with a subangular lesion. Brain, 122(6), 1107-1120.

McGlone, M. S., & Harding, J. H. (1998). Back (or forward?) to the future: The role of perspective in temporal language comprehension. Journal of Experimental Psychology: Learning, Memory, and Cognition, 24, 1211-1223.


Medendorp, W. P., & Crawford, J. D. (2002). Visuospatial updating of reaching targets in near and far space. Neuroreport, 13(5), 633-636.

Medendorp, W. P., Goltz, H. C., Crawford, J. D., & Villis, T. (2005). Integration of target and effector information in human posterior parietal cortex for the planning of action. Journal of Neurophysiology, 93, 954-962.

Medendorp, W. P., Goltz, H. C., Villis, T., & Crawford, J. D. (2003). Gaze-centered updating of visual space in human parietal cortex. Journal of Neuroscience, 23(15), 6209-6214.

Merriam, E. P., Genovese, G. R., & Colby, C. L. (2003). Spatial updating in human parietal cortex. Neuron, 39 361-373.

Mills, C. B., Viguers, M. L., Edelson, S. K., Thomas, A. T., Simon-Dackô, S. L., & Innis, J. A. (2002). The color of two alphabets for a multilingual synesthete. Perception, 31(11), 1371-1394.

Moore, K. E. (2000). Spatial experience and temporal metaphors in Wolof: Point of view, conceptual mapping, and linguistic practice. University of California, Berkeley, Berkeley, CA.

Morris, A. P., Chambers, C. D., & Mattingley, J. B. (2007). Parietal stimulation destabilizes spatial updating across saccadic eye movements. Proceedings of the National Academy of Sciences of the United States of America, 104(21), 9069-9074.

Mullette-Gillman, O. A., Cohen, Y. E., & Groh, J. M. (2005). Eye-centered, head-centered, and complex coding of visual and auditory targets in the intraparietal sulcus. Journal of Neurophysiology, 94(4), 2331-2352.

Murata, A., Gallese, V., Luppino, G., Kaseda, M., & Sakata, H. (2000). Selectivity for the shape, size, and orientation of objects for grasping in neurons of monkey parietal area AIP. Journal of Neurophysiology, 83(5), 2580-2601.

Narayanan, S. (1997). Embodiment in language understanding: sensory-motor representations for metaphoric reasoning about event descriptions. University of California, Berkeley, Berkeley, CA.

Núñez, R. E. (1999). Could the future taste purple? Journal of Consciousness Studies, 6(11-12), 41-60.

Núñez, R. E., Motz, B. A., & Teuscher, U. (2006). Time after time: The psychological reality of the Ego- and Time-Reference-Point distinction in metaphorical construals of time. Metaphor and Symbol.

Núñez, R. E., & Sweetser, E. (2006). With the future behind them: Convergent evidence from Aymara language and gesture in the crosslinguistic comparison of spatial construals of time. Cognitive Science, 30(3), 401-450.

Nunn, J. A., Gregory, L. J., Brammer, M., Williams, S. C. R., Parslow, D. M., Morgan, M. J., et al. (2002). Functional magnetic resonance imaging of synesthesia: Activation of V4/V8 by spoken words. Nature Neuroscience, 5(4), 371-375.

Obayashi, S., Suhara, T., Kawabe, K., Okauchi, T., Maeda, J., Akine, Y., et al. (2001). Functional brain mapping of monkey tool use. Neuroimage, 14(4), 853-861.

Olson, C. R. (2003). Brain representation of object-centered space in monkeys and humans. Annual Review of Neuroscience, 26, 331-354.


Orban, G. A., Claeys, K., Nelissen, K., Smans, R., Sunaert, S., Todd, J. T., et al. (2006). Mapping the parietal cortex of human and non-human primates. Neuropsychologia, 44(13), 2647-2667.

Orban, G. A., Fize, D., Peuskens, H., Denys, K., Nelissen, K., Sunaert, S., et al. (2003). Similarities and differences in motion processing between the human and macaque brain: evidence from fMRI. Neuropsychologia, 41(13), 1757-1768.

Orban, G. A., Van Essen, D., & Vanduffel, W. (2004). Comparative mapping of higher visual areas in monkeys and humans. Trends in Cognitive Science, 8(7), 315-324.

Pulvermuller, F. (2005). Brain mechanisms linking language and action. Nature Reviews Neuroscience, 6(7), 576-582.

Ramachandran, V. S., & Hubbard, E. M. (2001). Synaesthesia: A window into perception, thought and language. Journal of Consciousness Studies, 8(12), 3-34.

Rizzo, M., & Eslinger, P. J. (1989). Colored hearing synesthesia: An investigation of neural factors. Neurology, 39(6), 781-784.

Rouw, R., & Scholte, H. S. (2007). Increased structural connectivity in grapheme-color synesthesia. Nature Neuroscience, 10(6), 792-797.

Sagiv, N., Simner, J., Collins, J., Butterworth, B., & Ward, J. (2006). What is the relationship between synaesthesia and visuo-spatial number forms? Cognition, 101(1), 114-128.

Saito, D. N., Okada, T., Morita, Y., Yonekura, Y., & Sadato, N. (2003). Tactile-visual cross-modal shape matching: a functional MRI study. Cognitive Brain Research, 17(1), 14-25.

Sakata, H., Taira, M., Kusunoki, M., Murata, A., Tsutsui, K., Tanaka, Y., et al. (1999). Neural representation of three-dimensional features of manipulation objects with stereopsis. Experimental Brain Research, 128, 160–169.

Schluppeck, D., Curtis, C. E., Glimcher, P. W., & Heeger, D. J. (2006). Sustained activity in topographic areas of human posterior parietal cortex during memory-guided saccades. Journal of Neuroscience, 26, 5098-5108.

Schluppeck, D., Glimcher, P. W., & Heeger, D. J. (2005). Topographic organization for delayed saccades in human posterior parietal cortex. Journal of Neurophysiology, 94(2), 1372-1384.

Sereno, M. I., & Huang, R. S. (2006). A human parietal face area contains aligned head-centered visual and tactile maps. Nature Neuroscience, 9(10), 1337-1343.

Sereno, M. I., Pitzalis, S., & Martinez, A. (2001). Mapping of contralateral space in retinotopic coordinates by a parietal cortical area in humans. Science, 294, 1350-1354.

Seron, X., Pesenti, M., Noel, M.-P., Deloche, G., & Cornet, J.-A. (1992). Images of numbers: or "When 98 is upper left and 6 sky blue". Cognition, 44(1-2), 159-196.

Shapiro, K., Hillstrom, A. P., & Husain, M. (2002). Control of visuotemporal attention by inferior parietal and superior temporal cortex. Current Biology, 12(15), 1320-1325.

Shikata, E., Hamzei, F., Glauche, V., Knab, R., Dettmers, C., Weiller, C., et al. (2001). Surface orientation discrimination activates caudal and anterior intraparietal sulcus in humans: an event-related fMRI study. Journal of Neurophysiology, 85(3), 1309-1314.


Silver, M. A., Ress, D., & Heeger, D. J. (2005). Topographic maps of visual spatial attention in human parietal cortex. Journal of Neurophysiology, 94(2), 1358-1371.

Simmons, W. K., Ramjee, V., Beauchamp, M. S., McRae, K., Martin, A., & Barsalou, L. W. (2007). A common neural substrate for perceiving and knowing about color. Neuropsychologia, 45(12), 2802-2810.

Simon, O., Mangin, J. F., Cohen, L., Le Bihan, D., & Dehaene, S. (2002). Topographical layout of hand, eye, calculation, and language-related areas in the human parietal lobe. Neuron, 33(3), 475-487.

Smilek, D., Callejas, A., Dixon, M. J., & Merikle, P. M. (2007). Ovals of time: Time-space associations in synaesthesia. Consciousness and Cognition, 16(2), 507-519.

Snyder, L. H., Batista, A. P., & Andersen, R. A. (2000). Intention-related activity in the posterior parietal cortex: a review. Vision Research, 40(10-12), 1433-1441.

Snyder, L. H., Grieve, K. L., Brotchie, P., & Andersen, R. A. (1998). Separate body- and world-referenced representations of visual space in parietal cortex. Nature, 394(6696), 887-891.

Spalding, J. M. K., & Zangwill, O. (1950). Disturbance of number-form in a case of brain injury. Journal of Neurology, Neurosurgery, and Psychiatry, 12, 24-29.

Sweetser, E. (1990). From Etymology to Pragmatics: Metaphorical and Cultural Aspects of Semantic Structure. New York: Cambridge University Press.

Swisher, J. D., Halko, M. A., Merabet, L. B., McMains, S. A., & Somers, D. C. (2007). Visual topography of human intraparietal sulcus. Journal of Neuroscience, 27(20), 5326-5337.

Taira, M., Georgopolis, A. P., Murata, A., & Sakata, H. (1990). Parietal cortex neurons of the monkey related to the visual guidance of hand movement. Experimental Brain Research, 79, 155–166.

Teuscher, U., Collins, J., & Coulson, S. (in press). Congruity effects in time and space: Behavioral and ERP measures. Cognitive Science.

Torralbo, A., Santiago, J., & Lupiáñez, J. (2006). Flexible conceptual projection of time onto spatial frames of reference. Cognitive Science, 30, 745–757.

Turconi, E., & Seron, X. (2002). Dissociation between order and quantity meanings in a patient with Gerstmann syndrome. Cortex, 38, 911–914.

Turner, M. (1987). Death is the mother of beauty: Mind, metaphor, criticism. Chicago: University of Chicago Press.

Ullmann, S. (1945). Romaticism and synaesthesia: A comparative study in sense transfer in Keats and Byron. Publications of the Modern Language Association of America, 60, 811-827.

Van Essen, D. C., Lewis, J. W., Drury, H. A., Hadjikhani, N., Tootell, R. B. H., Bakircioglu, M., et al. (2001). Mapping visual cortex in monkeys and humans using surface-based atlases. Vision Research, 41, 1359-1378.

Walsh, V. (2003). A theory of magnitude: Common cortical metrics of time, space and quantity. Trends in Cognitive Sciences, 7(11), 483-488.

Walsh, V., & Cowey, A. (2006). Fifty years of the parietal cortex: What could we tell Critchley today? Cortex, 42(5), 663-665.

Ward, J., Simner, J., & Auyeung, V. (2005). A comparison of lexical-gustatory and grapheme-colour synaesthesia. Cognitive Neuropsychology, 22(1), 28-41.


Wardak, C., Olivier, E., & Duhamel, J. R. (2002). Saccadic target selection deficits after lateral intraparietal area inactivation in monkeys. Journal of Neuroscience, 22(22), 9877-9884.

Zhang, T., Heuer, H. W., & Britten, K. H. (2004). Parietal area VIP neuronal responses to heading stimuli are encoded in head-centered coordinates. Neuron, 42(6), 993-1001.

temporal spatial metaphors neural constraints on temporal

Documents