Working Memory Load

Top-down influences are often based on our goals and expectations (e.g., Kumar, Soto & Humphreys, 2009). For instance, Duncan and Humphreys (1989) suggested that ‘the attentional template’ of a certain visual stimulus (i.e. its properties and description) held in working memory (WM), is used to bias percept selection with properties that match the ‘template’ held in memory (Downing, 2000; Hodsoll & Humphreys, 2001; see Soto et al., 2008 for a review). The relationship between visual selection and WM has been studied in several lines of research. For example, neuroimaging studies have found that attention and WM show patterns of activity with overlapping networks, including regions around the intraparietal sulcus and frontal eye fields (e.g. McCarthy, 1995; LaBar et al., 1999; Pollmann & von Cramon, 2000). Behaviorally, researchers found that WM seems to play an important and central role in the suppression of distractors and maintaining focus on the relevant information for the current task (de Fockert, 2001; Woodman et al., 2007; Woodman & Luck, 2004).

Recently, working memory has been studied in experiments investigating the underlying mechanisms behind ambiguous figure perception. These studies suggest that working memory plays a role in the rate of reversals and percept choice. For instance, although not explicitly stated, Paffen, Alais, and Verstraten (2006) found that

reduced the rate of perceived binocular rivalry reversals. They wanted to investigate the role of attention on binocular rivalry and therefore manipulated working memory by manipulating task difficulty. They presented a concurrent task while participants were presented with a binocular rivalry stimulus containing random dot motion. Paffen et al. (2006) manipulated task difficulty through the motion coherence of the dots (i.e. whether the dots presented to each eye moved in the same direction or in opposite direction). Participants were required to report which rival target was perceptually dominant indicated by a cue following presentation of the stimulus. They were also instructed to indicate whether each cue was preceded by a burst of coherent motion. The motion-detection task demands did not prevent the participants’ ability to track

perceptual reversals, as participants were capable to correctly track the perceptual changes of the rivalrous percepts (coherent versus incoherent motion) while completing the motion detection task. The motion-detection task demands did reduce the rate of reversals. However, none of the reported manipulations eliminated reversals. Therefore, Paffen, Alais, and Verstraten (2006) suggested that perceptual ambiguity involves more than an allocation of attentional resources.

Intaite, Koivisto and Castelo-Branco (2014) found that previous studies using ambiguous stimuli did not manipulate the level of working memory load, leaving open the possibility that the reductions of perceptual reversals were due to the requirement to perform two tasks simultaneously. Therefore, in their study, they investigated how perceptual decision making is affected by the recruitment of attentional resources. They also investigated the possible effects of working memory load on perceptual reversals of the Necker cube. Thus they chose a secondary working memory load task (e.g., mental

arithmetic) that is known to exhaust the available attentional resources (Kumar, Soto, & Humphreys, 2009; Singhal & Fowler, 2004). In their experiment, Intaite et al. (2014) had two types of stimuli. They had ambiguous Necker Cube stimuli that were presented at the center of the screen that were preceded by memory stimuli that appeared that the same location. The memory stimuli consisted of a memory prime (sham – load

condition: 4 asterix; letter-load condition: four to seven capital consonant letters) and a memory probe that consisted of two arrows (either pointing to the left or to the right) in the sham-load condition or of one letter in the letter-load condition. On every trial, the memory prime was presented followed by the ambiguous Necker Cube and then the memory probe was presented. The latter consisted of the sham-load condition arrows or of one letter that had either been part of the memory set (positive probe) or had not been part of it (negative probe) in the letter-load conditions. Participants had to discriminate between the direction of the arrows presented and the positive versus negative probes. They found that increasing working memory load (increasing the number of letters presented) delayed the latency and the rate of reversals. However, reversals continued to occur. This suggests that there are shared mechanisms that are responsible for working memory maintenance and for perceptual reversals or at least are tightly linked in terms of top-down control.

Other research manipulating working memory load has also shown that performing secondary tasks that require working memory load increases the time for the report of (Reisberg & O’Shaughnessy, 1984; Wallace, 1986) and decreases the rate of (Reisberg & O’Shaughnessy, 1984; Wallace & Priebe, 1985; Wallace, 1986) perceived reversals in an ambiguous figure and their interpretation of it (Resiberg, 1983).

In a further study investigating the relationship between working memory load and ambiguous images, Intaite, Duarte and Castelo-Branco (2016), used fMRI to explore the neural activity patterns in response to perceptual reversals under differing amounts of working memory load using the same dual-task design. Their findings suggest that there is an overlap in the brain regions activated during perceptual reversals and the fronto- parietal attention network (Knapen et al., 2011; Lumer et al., 1998, Lumer and Rees, 1999, Sterzer and Kleinschmidt, 2007, Weilnhammer et al., 2013). Previously, Sterzer and Rees (2008) reported activations in visual cortex along with activity in prefrontal and parietal regions for percept-specific signals in response to binocular rivalry stimuli. They also discussed comparable BOLD signal changes over visual and fronto-parietal regions in response to voluntary engagement of facial WM (Courtney et al., 1997; Haxby et al., 2000). The authors suggested a possible influence of higher-level

mechanisms on perceptual durations that share a common activation network with WM. Moreover, Intaite, Duarte and Castelo-Branco (2016) found that the right posterior Superior Parietal Lobule (pSPL) showed differences in response to perceptual reversals under different load levels, and was stronger in response to perceptual reversals than stimulus changes. The Superior Parietal Lobule (SPL) also had been found to be

involved in perception of reversals in previous studies (e.g. Baker et al., 2015; Carmel et al., 2010; Kanai et al., 2010; Kanai et al., 2011). Stimulating the right anterior SPL with transcranial magnetic stimulation (TMS) increased the rate of reported reversals whereas stimulating the right posterior SPL decreased it (Carmel et al., 2010). Right SPL seems to be also activated when participants perform WM manipulation of stimulus content (Champod and Petrides, 2007). Moreover, anterior Prefrontal (where activation is

suppressed by the highest loads) and Dorsolateral Prefrontal (where deactivation is reduced by highest loads) cortices exhibited differential BOLD signal changes in response to perceptual reversals under working memory load (Intaite, Duarte & Castelo- Branco, 2016). These findings (enhanced BOLD response in SPL) have been previously suggested by other fMRI studies (e.g. Knapen et al., 2011, Lumer et al., 1998, Lumer and Rees, 1999, Weilnhammer et al., 2013). The suggested modulatory role of the anterior Prefrontal and Dorsolateral Prefrontal cortices, showing a significant interaction between rate of reversals and load levels, suggest a more direct role of the anterior Prefrontal Cortex in reversal generation.