1. Flexible remembering and flexibility of thinking
(Aizpurua & Koutstaal, 2010, Psychology & Aging, 25, 193-207) (pdf)
Although highly specific memory is critical in many contexts, the ability to recall knowledge in a more abstract or "gist-based" manner is crucial in allowing transfer of learning to new situations and to complex forms of thought such as using analogies and drawing inferences based on the classification of events and objects. Yet it is unknown whether we can flexibly and intentionally alternate on demand between recollection at an abstract or category-based level and recollection at a very specific detailed level, particularly for events from a single context.
In earlier work, we demonstrated that both younger and older individuals could show such flexible remembering (Koutstaal, 2006, Psychonomic Bulletin & Review, 13, 84-91). Also, we found that, in older adults, the ability to show such flexible "specificity modulation" -- adaptively using category-based memory when that was required, but using detailed item-specific memory when, instead, that was required -- significantly correlated with how fluently they retrieved long-term knowledge in response to specific constraints (fluency in generating examples of animals, or English words that began with a particular letter).
Recently, we obtained more direct evidence that, across age groups, specificity modulation in episodic memory is closely tied to flexibility in thinking (Aizpurua & Koutstaal, 2010). A measure of specificity modulation (recollection rejection) was strongly correlated with a measure of fluid intelligence (combining the Cattell Culture Fair Test and the Block Design subtest of the Wechsler Adult Intelligence Scale-Revised). In addition, when we simultaneously considered each of four possible contributors (age, conceptual span, fluid intelligence, and frontal function), the only significant predictor of recollection rejection was the composite fluid intelligence measure. These results suggest that interventions that facilitate adaptive specificity modulation in episodic memory may enhance the flexibility of thinking, and vice versa, in both older and younger adults.
2. Abstraction and specificity in repetition-related decision learning
(Denkinger & Koutstaal, 2009, Journal of Experimental Psychology: Learning, Memory, & Cognition, 35, 742-756) (pdf)
Recent encounters with a stimulus often facilitate or "prime" future responses to the same or similar stimuli. However, studies are inconclusive as to whether changing the response that is required attenuates priming only for identical stimuli, or also for categorically related items. In two object priming experiments, we recently demonstrated that priming was eliminated if the initial decision associated with a stimulus changed on a later trial. This disruption of priming extended to perceptually and conceptually similar object exemplars and was found even when the classification tasks were uncorrelated with one another, many other items had intervened, and after only one prior encounter with a given stimulus. These outcomes are consistent with the rapid and automatic binding of a stimulus with a response into an episodic "instance" or "event file" and demonstrates that repetition-related decision learning is not hyperspecific but generalizes to new stimuli. Such binding is assumed to occur incidentally, entirely as a consequence of temporal contiguity. When a stimulus is repeated and the stimulus requires the same response, response times are facilitated; however, when the repeated stimulus demands a different response, response times are slowed. More broadly, these findings point to important shared processes across repetition priming for single objects and related domains such as associative tasks, negative priming, and task switching, through the fundamental--and pervasive--processes involved in binding perception with action.
3. Brain laterality differences in specific versus abstract memory for objects
(Simons, Koutstaal, et al., 2003, NeuroImage, 19, 613-626) (pdf)
We earlier reported evidence (Koutstaal et al., 2001, Neuropsychologia) that right occipito-temporal (fusiform) cortex is involved more than left fusiform in processing object-specific visual form information that differentiates between object exemplars. In this 2003 paper the above finding was replicated. There was significantly greater priming-related "neural discrimination" between different exemplars in right than left fusiform cortex, manifested in a significant interaction between region (right and left fusiform) and item type (same or different exemplars). Additional sensitivity to a lexical/semantic manipulation was observed in left fusiform cortex (as well as in left inferior prefrontal cortex), with further analyses suggesting posterior-to-anterior progression within the left occipito-temporal cortex between regions involved in processing visuoperceptual and lexical/semantic information about objects.
The right hemisphere of the brain appears to be principally involved in processing specific visual form representations about objects, whereas the left hemisphere additionally plays a role in processing lexical/semantic information. Together, these subsystems contribute to the ability which is critical to survival, to rapidly perceive and identify objects in the world around us.
Below: Selectively averaged percentage signal change (relative to fixation) for novel, repeated same, and repeated different items (combining across lexical/semantic conditions) in left and right fusiform cortex (top row) and left and right lateral occipital cortex (bottom row). Regions of interest, which were derived from the all novel > all repeated linear contrast, are displayed on axial slices of an averaged anatomical MR image. All regions showed a pattern of significantly greater activation for repeated different than repeated same items. Within fusiform cortex, a significant interaction emerged between hemispheres, with exemplar generalization in the left, and exemplar specificity in the right. No such lateralization was observed in lateral occipital cortex.
4. Depression, confidence, and decision: Evidence against depressive realism
(Fu, Koutstaal, et al., 2005, Journal of Psychopathology and Behavioral Assessment) (pdf)
According to the depressive realism hypothesis people suffering with a depressive illness are more realistic than are non-depressed individuals, who often show unrealistically positive self-evaluations, over-confidence, exaggerated perceptions of control, and unrealistic optimism. In contrast, the selective processing hypothesis suggests that, although depressed individuals may sometimes appear to show less over-confidence, this reflects a general bias towards negativity. In order to differentially test the validity of these two accounts, it is necessary to include an experimental situation in which the accuracy of confidence or self-performance assessment in the non-depressed comparison group is either realistic or under-confident. Unlike previous studies, in this study we chose to use a measure -- post-test performance estimates (PTPEs) -- on which normal controls typically show either realistic or under-confident performance. We found that normal control participants were, indeed, under-confident when asked to retrospectively assess their overall performance on various tasks. However, clinically depressed patients were not more realistic on this measure and, indeed, under-estimated their performance at least as much, or more, than did the comparison group. This is evidence against depressive realism, and in support of selective processing.
Below: Overall post-test performance estimates (yellow bars) and overall decision accuracy (green bars) shown separately for each of the individual depressed patients (upper panel), age-matched controls (lower panel left), and patients who had previously been depressed but were not currently depressed (lower panel right).
5. Intentionally -- versus unintentionally -- remembering details in older adults
(Koutstaal, 2003, Psychological Science, 14, 189-193) (pdf)
It has long been known that older adults
forget things that were actually encountered (known as errors of omission). However,
mounting evidence demonstrates that normal cognitive aging also is
associated with an increased propensity to errors of commission. That
is, older adults also are certain that something has been seen or
experienced before when, in fact, it has not. In our study,
although older adults showed greater false recognition of related lures
on a standard ("identical") old/new episodic recognition test, older
and younger adults showed parallel
effects of detail on two other types of memory test. The
first involved making judgments about the real world size of objects,
some of which had been seen previously. This was a task where it
was not necessary to intentionally remember or recall anything about
the previous encounter with the objects, but where people might be
expected to benefit unintentionally or implicitly from having viewed
the objects before (repetition priming). The second task involved
asking people to decide if they remembered seeing either exactly the
same object before or one that was similar to that object
(meaning-based episodic recognition). On these tests both age
groups showed decreased priming and decreased meaning-based recognition
for different relative to same exemplars.
These findings suggest that older adults
do, indeed, encode differentiating perceptual details -- possibly even
to the same extent as do younger adults, at least for certain types of
task-relevant features -- but the extent to which those details are used depends on the nature of the
memory probe and the participants' retrieval intentions.
Below: Performance on the
three memory tasks, repetition priming (A), identical recognition (B),
and meaning-based recognition (C). For repetition priming, the
graph shows the difference in mean response times for new versus
repeated items, separately for same exemplars (new exemplar minus same
exemplar) and different exemplars (new exemplar minus different
exemplar). For identical recognition, the graph shows the mean
proportion of "old" responses to studied items (same exemplars) and
nonstudied related lures (different exemplars), after subtracting false
alarms to new items. For meaning-based recognition, the graph
shows the mean proportion of "old" responses to studied items (same
exemplars) and nonstudied conceptually-related items (different
exemplars), after subtracting false alarms to new items. Error
bars show the standard error of the mean.