Individual differences in cognitive style and strategy predict similarities in the patterns of brain activity between individuals

Abstract

Neuroimaging is being used increasingly to make inferences about an individual. Yet, those inferences are often confounded by the fact that topographical patterns of task-related brain activity can vary greatly from person to person. This study examined two factors that may contribute to the variability across individuals in a memory retrieval task: individual differences in cognitive style and individual differences in encoding strategy. Cognitive style was probed using a battery of assessments focused on the individual's tendency to visualize or verbalize written material. Encoding strategy was probed using a series of questions designed to assess typical strategies that an individual might utilize when trying to remember a list of words. Similarity in brain activity was assessed by cross-correlating individual t-statistic maps contrasting the BOLD response during retrieval to the BOLD response during fixation. Individual differences in cognitive style and encoding strategy accounted for a significant portion of the variance in similarity. This was true above and beyond individual differences in anatomy and memory performance. These results demonstrate the need for a multidimensional approach in the use of fMRI to make inferences about an individual.

Introduction

One of the goals of neuroergonomics is to use neuroscientific tools to understand the individual mind at work in a naturalistic environment (Parasuraman and Wilson, 2008). But the use of functional magnetic resonance imaging (fMRI) to make an inference about an individual is particularly challenging (see Parasuraman and Jiang, 2012-this issue). Imagine a situation in which an institution (e.g., a court of law) seeks to use neuroimaging to establish the veracity of an individual's memory. They have a template based on hundreds of individuals for what that individual's pattern of brain activity should look like for a true memory. Yet, the individual in question has a very different pattern of brain activity. Are they to conclude that the individual must not be experiencing a true memory? The veracity of memory is only one dimension that may explain why this individual's pattern of brain activity is so different from the other individuals. For example, there may have been fundamental differences in the individual's cognitive style that significantly affected their pattern of activity as well. If neuroimaging will be used to make an inference about an individual, then multiple dimensions in which individuals may differ must be considered.

We have shown previously that the topographical pattern of brain activity underlying a memory retrieval task can vary greatly from individual to individual, sometimes with little to no overlap in significant activations between individuals (Miller et al., 2002, Miller et al., 2009). However, despite that extensive variability, the individual patterns of brain activity are relatively consistent over time (Miller et al., 2002, Miller et al., 2009; for review of fMRI reliability, see Bennett and Miller, 2010), suggesting that differences in the patterns of brain activity are due to systematic differences in individual characteristics and are not due to random measurement error (see Fig. 1). In order to effectively use fMRI to infer unique aspects of the individual mind, it is necessary to untangle the critical factors that can vary the individual patterns of brain activity. In this study, we examine whether individual differences in strategy and cognitive style can account for the degree of similarity between any two individual patterns of brain activity during a retrieval task.

Using neuroscience methods to gain insight into the individual mind is a common goal among many institutions, including education (Byrnes, 2001, Posner and Rothbart, 2005), the military (National Research Council, 2008), and courts of law (Brown and Murphy, 2010). Implicit in the goals of these institutions is the ability to make judgments about an individual based on neuroscientific data collected from a group of individuals. This goal is often incompatible with the general scientific goal to make an inference about a general phenomenon that applies to a population by averaging data across individuals (Faigman, 2010). For fMRI in particular, this demand to average data across individuals is compounded by the fact that the signal-to-noise ratio (SNR) of the BOLD signal is very low (Friston et al., 1999) and that false positives due to the low SNR are far too common (Bennett et al., 2010). Yet, as acquisition devices and analytical tools for fMRI become more and more sophisticated, increasing effort is being made to infer unique aspects of the individual based on the group data.

A critical question remains within functional neuroimaging: do the results of a group analysis accurately represent the individuals that make up that group? Many studies have concluded that it does not (Heun et al., 2000, Machielsen et al., 2000, McGonigle et al., 2000, Miller et al., 2002, Feredoes and Postle, 2007, Seghier et al., 2008, Miller et al., 2009, Seghier and Price, 2009, Parasuraman and Jiang, 2012). For example, we found that the observed variations in functional brain activity across the whole brain during a simple recognition task were extensive, with some individuals activating mostly prefrontal regions while others activated mostly parietal regions (Miller et al., 2002, Miller et al., 2009). This was in contrast to the group analysis, which prominently showed both regions to be equally active. Are there quantifiable factors that might help to explain this effect? We found indirect evidence in a recent study that some variations in the degree of brain activity similarity between individuals during a memory retrieval task may be due to individual differences in strategy (Miller et al., 2009). That is, the larger the difference in decision criterion the more dissimilar the two patterns of brain activity. However, a criterion measure is not a direct measure of memory strategy. Therefore, in this study we directly measure individual differences in cognitive style and strategy and test whether or not these differences can account for a significant portion of the variance in the similarity of brain activity between individuals.

Brain activity during a recognition memory task is a useful platform to study individual variability for two reasons: (1) the tremendous amount of previous research conducted on the relationship between recognition memory and fronto-parietal regions and (2) the widespread and distributed nature of the activity underlying the task (Miller and Van Horn, 2007). Many of the fronto-parietal regions implicated in recognition memory are known to underlie cognitive processes peripheral to the actual retrieval process (Shimamura, 1995, Fletcher et al., 1998, Moscovitch and Winocur, 2002). One potential implication of this distributed architecture is that one and the same behavioral outcome—such as an “old” response on a recognition test—could be the result of information processing and neural circuitry that are distinct to the individual but vary across individuals.

There is considerable evidence that individuals engage in a variety of strategies during the encoding phase of a standard recognition memory task (Stoff and Eagle, 1971, Battig, 1975, Weinstein et al., 1979, Paivio, 1983, Reder, 1987, Graf and Birt, 1996) and that individual differences in strategy can modulate the BOLD activity in certain brain regions (Savage et al., 2001, Casasanto et al., 2002, Speer et al., 2003, Kondo et al., 2005, Tsukiura et al., 2005). One notable study by Kirchhoff and Buckner (2006) identified the various strategies people adopt during the unconstrained encoding of an unrelated pairs of pictures. They found that verbal elaboration correlated with activity in prefrontal regions associated with controlled verbal processing, while visual inspection correlated with activity in the extrastriate cortex known to be involved in higher-order visual processing. These findings suggest that different encoding strategies may recruit different brain regions, even though the memory performance is similar between the two strategies. While the Kirchhoff and Buckner (2006) study showed how different encoding strategies can recruit different brain regions during the encoding phase, we investigated how different encoding strategies may account for the similarity in brain activity during the retrieval phase. One of the classic principles of episodic memory, the encoding specificity principle, states that encoding operations are directly related to retrieval operations (Tulving and Thomson, 1973). This relationship is illustrated by the fact that differences in encoding strategies can have a direct effect on the brain activity that occurs during retrieval (Raposo et al., 2009, Kirchhoff, 2009). From this evidence, we hypothesize that individual differences in encoding strategy will account for a significant portion of the variance that is observed in the similarity of brain activity between individuals during a retrieval task.

Aside from the particular strategy that an individual may choose to engage in during a memory task, individuals may also have a particular style of thinking or a preferred set of cognitive operations that could affect their pattern of brain activity. For example, the visualizer–verbalizer dimension of cognitive style is based on the idea that some people (who could be called visualizers) are better at processing visual material, whereas other people (who could be called verbalizers) are better at processing verbal material (Mayer and Massa, 2003, Massa and Mayer, 2006). Although individual differences in the tendency to engage in visual or verbal processing has little relationship to memory recall (Richardson, 1978, Richardson, 1998) and the search for research-based attributes that may interact with instructional methods has had a somewhat disappointing history (Cronbach and Snow, 1977, Pashler et al., 2009, Sternberg and Zhang, 2001, Zhang and Sternberg, 2009), differences in cognitive style may still be pertinent to the issue of individual differences in brain activity during a retrieval task. The likelihood of involvement of any particular process and its underlying brain region may depend a great deal on the processing style of the individual. In other words, a visualizer and verbalizer may not necessarily differ in performance on learning outcome tests but may have highly distinct patterns of regional brain activity during learning (i.e., encoding) and retrieval that achieve the same level of performance. There is evidence suggesting that this may well be the case. Two recent studies by Kozhevnikov et al. (2002)) and Kozhevnikov et al. (2005) attempted to clarify and revise the visualizer–verbalizer dimension and subsequently introduced two subtypes of visualizers: object visualizers who tended to focus on object properties such as shape and color and spatial visualizers who tended to focus on spatial properties such as location and spatial relations. A later fMRI study revealed that object visualizers activated more ventral regions of the visual processing stream while spatial visualizers activated more dorsal regions of the visual processing stream (Motes and Kozhevnikov, 2006). We hypothesize that differences in cognitive style may also be a significant contributor to the variability of the patterns of brain activity during a retrieval task.

In this study we test the hypothesis that individual differences in strategy and cognitive style will account for a significant portion of the variance in the similarity in the patterns of whole-brain activity between individuals during a memory retrieval task. To measure the variability in the patterns of brain activity across individuals we cross-correlate the unthresholded t-statistic maps contributed by each individual from the retrieval task (Miller et al., 2002, Miller et al., 2009). The more similar two individual patterns of brain activity, the higher the correlation value (see Fig. 1). Individuals were assessed on strategies and cognitive style after the fMRI scanning session using a battery of tests. In addition, strategy was implicitly manipulated within participants by varying the imageability of the word stimuli. If strategies and style depend to some degree on visualizing the word stimuli, then manipulating the imageability of the words should affect the predictability of those factors. We predict that individual differences in strategy and cognitive style will significantly account for inter-individual differences in brain activity above and beyond any factors attributable to individual differences in anatomy and memory performance.