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Anina N. Rich
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Journal Articles
Publisher: Journals Gateway
Journal of Cognitive Neuroscience (2022) 34 (4): 639–654.
Published: 05 March 2022
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The human brain is extremely flexible and capable of rapidly selecting relevant information in accordance with task goals. Regions of frontoparietal cortex flexibly represent relevant task information such as task rules and stimulus features when participants perform tasks successfully, but less is known about how information processing breaks down when participants make mistakes. This is important for understanding whether and when information coding recorded with neuroimaging is directly meaningful for behavior. Here, we used magnetoencephalography to assess the temporal dynamics of information processing and linked neural responses with goal-directed behavior by analyzing how they changed on behavioral error. Participants performed a difficult stimulus–response task using two stimulus–response mapping rules. We used time-resolved multivariate pattern analysis to characterize the progression of information coding from perceptual information about the stimulus, cue and rule coding, and finally, motor response. Response-aligned analyses revealed a ramping up of perceptual information before a correct response, suggestive of internal evidence accumulation. Strikingly, when participants made a stimulus-related error, and not when they made other types of errors, patterns of activity initially reflected the stimulus presented, but later reversed, and accumulated toward a representation of the “incorrect” stimulus. This suggests that the patterns recorded at later time points reflect an internally generated stimulus representation that was used to make the (incorrect) decision. These results illustrate the orderly and overlapping temporal dynamics of information coding in perceptual decision-making and show a clear link between neural patterns in the late stages of processing and behavior.
Journal Articles
Publisher: Journals Gateway
Journal of Cognitive Neuroscience (2018) 30 (7): 999–1010.
Published: 01 July 2018
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Numerical format describes the way magnitude is conveyed, for example, as a digit (“3”) or Roman numeral (“III”). In the field of numerical cognition, there is an ongoing debate of whether magnitude representation is independent of numerical format. Here, we examine the time course of magnitude processing when using different symbolic formats. We presented participants with a series of digits and dice patterns corresponding to the magnitudes of 1 to 6 while performing a 1-back task on magnitude. Magnetoencephalography offers an opportunity to record brain activity with high temporal resolution. Multivariate pattern analysis applied to magnetoencephalographic data allows us to draw conclusions about brain activation patterns underlying information processing over time. The results show that we can cross-decode magnitude when training the classifier on magnitude presented in one symbolic format and testing the classifier on the other symbolic format. This suggests a similar representation of these numerical symbols. In addition, results from a time generalization analysis show that digits were accessed slightly earlier than dice, demonstrating temporal asynchronies in their shared representation of magnitude. Together, our methods allow a distinction between format-specific signals and format-independent representations of magnitude showing evidence that there is a shared representation of magnitude accessed via different symbols.
Journal Articles
Publisher: Journals Gateway
Journal of Cognitive Neuroscience (2017) 29 (2): 310–321.
Published: 01 February 2017
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Human cognition is characterized by astounding flexibility, enabling us to select appropriate information according to the objectives of our current task. A circuit of frontal and parietal brain regions, often referred to as the frontoparietal attention network or multiple-demand (MD) regions, are believed to play a fundamental role in this flexibility. There is evidence that these regions dynamically adjust their responses to selectively process information that is currently relevant for behavior, as proposed by the “adaptive coding hypothesis” [Duncan, J. An adaptive coding model of neural function in prefrontal cortex. Nature Reviews Neuroscience, 2, 820–829, 2001]. Could this provide a neural mechanism for feature-selective attention, the process by which we preferentially process one feature of a stimulus over another? We used multivariate pattern analysis of fMRI data during a perceptually challenging categorization task to investigate whether the representation of visual object features in the MD regions flexibly adjusts according to task relevance. Participants were trained to categorize visually similar novel objects along two orthogonal stimulus dimensions (length/orientation) and performed short alternating blocks in which only one of these dimensions was relevant. We found that multivoxel patterns of activation in the MD regions encoded the task-relevant distinctions more strongly than the task-irrelevant distinctions: The MD regions discriminated between stimuli of different lengths when length was relevant and between the same objects according to orientation when orientation was relevant. The data suggest a flexible neural system that adjusts its representation of visual objects to preferentially encode stimulus features that are currently relevant for behavior, providing a neural mechanism for feature-selective attention.
Journal Articles
Publisher: Journals Gateway
Journal of Cognitive Neuroscience (2015) 27 (10): 1895–1911.
Published: 01 October 2015
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How do our brains achieve the cognitive control that is required for flexible behavior? Several models of cognitive control propose a role for frontoparietal cortex in the structure and representation of task sets or rules. For behavior to be flexible, however, the system must also rapidly reorganize as mental focus changes. Here we used multivoxel pattern analysis of fMRI data to demonstrate adaptive reorganization of frontoparietal activity patterns following a change in the complexity of the task rules. When task rules were relatively simple, frontoparietal cortex did not hold detectable information about these rules. In contrast, when the rules were more complex, frontoparietal cortex showed clear and decodable rule discrimination. Our data demonstrate that frontoparietal activity adjusts to task complexity, with better discrimination of rules that are behaviorally more confusable. The change in coding was specific to the rule element of the task and was not mirrored in more specialized cortex (early visual cortex) where coding was independent of difficulty. In line with an adaptive view of frontoparietal function, the data suggest a system that rapidly reconfigures in accordance with the difficulty of a behavioral task. This system may provide a neural basis for the flexible control of human behavior.
Journal Articles
Publisher: Journals Gateway
Journal of Cognitive Neuroscience (2014) 26 (5): 1066–1074.
Published: 01 May 2014
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Object recognition benefits greatly from our knowledge of typical color (e.g., a lemon is usually yellow). Most research on object color knowledge focuses on whether both knowledge and perception of object color recruit the well-established neural substrates of color vision (the V4 complex). Compared with the intensive investigation of the V4 complex, we know little about where and how neural mechanisms beyond V4 contribute to color knowledge. The anterior temporal lobe (ATL) is thought to act as a “hub” that supports semantic memory by integrating different modality-specific contents into a meaningful entity at a supramodal conceptual level, making it a good candidate zone for mediating the mappings between object attributes. Here, we explore whether the ATL is critical for integrating typical color with other object attributes (object shape and name), akin to its role in combining nonperceptual semantic representations. In separate experimental sessions, we applied TMS to disrupt neural processing in the left ATL and a control site (the occipital pole). Participants performed an object naming task that probes color knowledge and elicits a reliable color congruency effect as well as a control quantity naming task that also elicits a cognitive congruency effect but involves no conceptual integration. Critically, ATL stimulation eliminated the otherwise robust color congruency effect but had no impact on the numerical congruency effect, indicating a selective disruption of object color knowledge. Neither color nor numerical congruency effects were affected by stimulation at the control occipital site, ruling out nonspecific effects of cortical stimulation. Our findings suggest that the ATL is involved in the representation of object concepts that include their canonical colors.