R OLE OF ATTENTION

Attention processes may have critical impacts on the creation of mental representations, and indirectly on the subsequent memory. I will start this section giving a short definition of attention, and will then review the effect of attention on encoding, underlying mechanisms and the effect of attention on subsequent implicit and explicit memory.

2.4.1. Definition

The environment could be overwhelming for our visual system and our memory, but attention guides our behavior by selecting relevant information to be processed. William James already described this selection function of attention in 1890: “[Attention is] the taking possession of the mind, in clear and vivid form, of one out of what seem several simultaneously possible objects or trains of thoughts. […] It implies withdrawal from some things in order to deal effectively with others” (James, 1890, pp. 403-404). Michael Posner said that there is probably no better definition than James’s one (Posner, 2004, p.3). However, a more contemporary definition would be that attention “involves selecting what deserves [processing] resources, and preventing other things from receiving them” (Chun & Turk-Browne, 2007). This selection process has been theorized in the “biased competition model”

(Desimone & Duncan, 1995), which is described in the next paragraph. Williams James also mentioned that the immediate effects of attention are to perceive, to conceive, to distinguish, to remember and also to shorten reaction-times (James, 1890, pp. 425). Here, I will concentrate on the role of attention perception and memory.

2.4.2. Effect of attention on encoding

In the context of the “biased competition model” (Desimone & Duncan, 1995), attention leads to the selection of the relevant information between competing objects. More specifically, the selection of the relevant information involves the interaction of top-down (expectation) and bottom-up (salience) components. As also proposed by Knudsen (2007), top-down and bottom-up information modulate the strength of each signal entering in a competitive selection (see Figure 12). The strongest signal is then transferred to working memory and can, in turn, send top-down modulatory signals and bias new entering signal.

In this work, I will focus on selective attention, which implies top-down processes to enhance relevant representations (for reviews, see Kastner & Ungerleider, 2000; Kanwisher &

Wojciulik, 2000). In the literature, neurophysiological studies in monkeys investigated spatial selective attention and showed enhanced activity in neurons (firing rate) when an attended

stimulus falls into the corresponding receptive field⁴ (e.g., McAdams & Maunsell, 1999).

Similarly, functional brain imaging studies in humans revealed an enhancement of processing at attended location and a suppression of processing at unattended locations (e.g., Somers et al., 1999; Eger et al., 2004).

Figure 12: Model of attention. Perceptual information about the world is processed by salience filters and activates neural representations at various levels. The representation with the highest signal wins the competitive selection and enters working memory (WM). In parallel, WM can modulate the sensitivity of representations. Source: Knudsen, 2007.

The biased competition model has been extended to competition between features, based on studies where selective attention enhanced/decreased (or even suppressed) representation of a specific feature of an object, or of a whole object, and even at the same retinotopic location (Corbetta et al., 1990; Vuilleumier et al., 2005; P. Downing et al., 2001; O'Craven et al.,

4 Neuron receptive field: part of the visual field whose stimulation induces a response in the corresponding

1999). Finally, attentional modulation of perceptual processing has been observed along the visual pathways, from primary visual cortex and extrastriate cortex (Schwartz et al., 2005; Liu et al., 2007) to higher-level areas (Eger et al., 2004; Henson & Mouchlianitis, 2007). Thus, top-down influences of selective attention can occur at all stages of visual processing.

2.4.3. Mechanisms

Mechanisms underlying the enhancement of representations of attended stimuli and the suppression of unattended stimuli remain unclear. Several models have been proposed to explain how attention bias neural response and the two ones which received most computational and neurophysiological support are “gain” and “tuning” (e.g., Boynton, 2009;

Martinez-Trujillo & Treue, 2004; Reynolds & Chelazzi, 2004). As described by Ling et al.

(2009), response gain corresponds to the amplification of the firing rate of a neural population across all feature detectors, whereas tuning attenuates the response to irrelevant noise, leading to a sharpening of the population response. In parallel, Uncapher and Rugg (2009) showed, in a fMRI study, an enhancement of activity in neocortical regions related to attended features (e.g., V4 for color, superior parietal cortex for location), and in the hippocampus for attended stimuli, independently of the kind of feature. They proposed that the enhancement of cortical activity in specific regions lead to an increased input in the hippocampus and thus, indirectly, to the observed modulation of activity in the hippocampus. Thus, competition and attentional modulations of representations seem to drive which input will arrive in the hippocampus and will be subsequently encoded and consolidated.

2.4.4. Effect of attention on implicit and explicit memory

It has been clearly shown that explicit memory requires that the subjects paid attention at the stimulus to be remembered at encoding (e.g., with superimposed figures, Rock & Gutman, 1981; superimposed faces and places, Yi & Chun, 2005). By contrast, this effect remains debated for implicit memory. Some authors found that dividing or diverting attention at encoding from stimuli prevents subsequent implicit memory for these stimuli. For instance, Crabb and Dark (Crabb & Dark, 1999), using a word-stem completion task assessing perceptual implicit memory, showed high performance for words that were attended at encoding, and no difference between the unattended and the new ones. At the neural level, Yi et al. (2006) could not show any repetition attenuation effect⁵, a measure of implicit memory,

5 Neural attenuation corresponds to a decrease in the activity between the first and second exposure to one stimulus at the peak of the hemodynamic response (Turk-Browne et al., 2006). Also called repetition suppression (Grill-Spector, 2006).

for ignored faces or scenes, in the fusiform face area (Kanwisher et al., 1997) and in the parahippcampal place area (Epstein & Kanwisher, 1998), even if the stimuli were presented 16 times in a 30s study block (one face and one scene were superimposed – the subject attended to either the face stream or the scene stream. Thus, these authors suggest that attention was required for the formation of implicit memory. However, implicit memory may arise even for unattended stimuli. Strong evidence supporting this view comes from behavioral studies in healthy subjects but also in brain-damaged patients. Parkin and Russo (1990) for example, found that recognition was much poorer for unattended pictures but that picture-completion was equally good for attended and unattended stimuli. Szymanski and MacLeod (1996) obtained similar repetition priming in a lexical decision task independently of the attention condition at encoding. Finally, patients with parietal damage, responsible of spatial attention deficits, show preserved priming effect for object presented in the neglected side despite no conscious perception nor explicit recognition (Vuilleumier et al., 2001). Thus, while attention is necessary for the formation of explicit memories, it seems that its absence does not prevent the perceptual system from encoding a mnesic trace of the stimuli that can be measured indirectly. Nevertheless, the nature of this trace is still debated. In particular, a question arose on whether the preserved implicit memory for unattended stimuli implies quantitatively or qualitatively different traces from the ones underlying explicit memory.

Some studies found no explicit memory for unattended stimuli and variations in implicit memory, in particular depending on the duration of exposure at study (Ganor-Stern et al., 1998), attentional load (i.e. difficulty) (Mulligan, 1997), or delay between study and test (Ballesteros et al., 2006). These studies suggest that implicit memory is less influenced by attention than explicit memory, but that encoding conditions might modulate the level of activation of perceptual representations, and thus subsequent implicit memory. Other studies provide evidence of qualitative differences in perceptual implicit memory between attended and unattended stimuli. For example, Stankiewicz et al. (1998) found priming effects independently of the view (same or mirror-reflected) for stimuli which were encoded with attention, and priming effects only for learned views for unattended stimuli. Thus, the nature of object representations activated with or without attention might differ in the extent to which these may generalize across image transformations such as mirror-reflection. However, this hypothesis has been largely under-investigated and is the focus of one part of this work.

Taking together, the results reviewed in this section suggest that attention influences on perception and memory. However, whether attention at encoding is needed for subsequent implicit memory still remains unclear. This specific question will be addressed in the experimental part of this work.