erations, respectively; and (iii) left posterior/ventral (Broca's area) and bilateral posterior/dorsal areas were more activated during WM than during ER, possibly reflecting phonological and generic WM operations, respectively. Second, hippocampal and parahippocampal regions were activated not only for ER but also for WM. This result suggests that indexing operations mediated by the medial temporal lobes apply to both long-term and short-term memory traces. Overall, our results show that direct cross-function comparisons are critical to understand the role of different brain regions in various cognitive functions. 2002 Elsevier Science (USA) INTRODUCTION During the past decade, numerous positron emission tomography (PET) and functional MRI (fMRI) studies have investigated the neural correlates of different cognitive functions (for a review, see Cabeza and Nyberg, 2000). Although most studies have focused on a single function (see however, LaBar et al., 1999; Braver et al., 2001; Ny

The authors theorize that 2 neurocognitive sequence-learning systems can be distinguished in serial reaction time experiments, one dorsal (parietal and supplementary motor cortex) and the other ventral (temporal and lateral prefrontal cortex). Dorsal system learning is implicit and associates noncategorized stimuli within dimensional modules. Ventral system learning can be implicit or explicit. It also allows associating events across dimensions and therefore is the basis of cross-task integration or interference, depending on degree of cross-task correlation of signals. Accordingly, lack of correlation rather than limited capacity is responsible for dual-task effects on learning. The theory is relevant to issues of attentional effects on learning; the representational basis of complex, sequential skills; hippocampalversus basal ganglia-based learning; procedural versus declarative memory; and implicit versus explicit memory. The ability to produce and learn sequential actions is one of the hallmarks of human cognition. Indeed, this ability has been hypothesized to constitute a fundamental adaptation that characterizes

We propose a new hypothesis concerning the lateralization of prefrontal cortex (PFC) activity during verbal episodic memory retrieval. The hypothesis states that the left PFC is differentially more involved in semantically guided information production than is the right PFC, and that the right PFC is differentially more involved in monitoring and verification than is the left PFC. This "production-monitoring hypothesis" differs from the existing "systematic -- heuristic hypothesis," which proposes that the left PFC is primarily involved in systematic retrieval operations, and the right PFC in heuristic retrieval operations. To compare the two hypotheses, we measured PFC activity using positron emission tomography (PET) during the performance of four episodic retrieval tasks: stem cued recall, associative cued recall, context recognition (source memory), and item recognition. Recall tasks emphasized production processes, whereas recognition tasks emphasized monitoring processes. Stem cued recall and context-recognition tasks underscored systematic operations, whereas associative cued recall and item-recognition tasks underscored heuristic operations. Consistent with the production-monitoring hypothesis, the left PFC was more activated for recall than for recognition tasks and the right PFC was more activated for recognition than for recall tasks. Inconsistent with the systematic -- heuristic hypothesis, the left PFC was more activated for heuristic than for systematic tasks and the right PFC showed the converse result. Additionally, the study yielded activation differences outside the PFC. In agreement with a previous recall/ recognition PET study, anterior cingulate, cerebellar, and striatal regions were more activated for recall than for recognition tasks, and the co...

common regions mediate? By comparing patterns of brain activity across different cognitive functions, answers to this question can be generated. ........ Figure 1 about here ........ The matrix in Figure 1 illustrates the difference between the traditional within-function approach and the cross-function approach we are advocating in this chapter. Let us assume that in functional neuroimaging studies Cognitive Function A typically is associated with activations in Brain Regions 1 and 3, Cognitive Function B with activations in Brain Regions 2 and 3, and Cognitive Function C with activations in Brain Regions 1 and 2. In the standard within-function approach, functional neuroimaging researchers are primarily concerned with one cognitive function and interpret activations in relation to this particular function. Thus, in a situation like the one depicted in Figure 1, researchers of Function A would attribute the activation of Region 1 to a certain aspect of Function A, whereas researchers

Functional magnetic resonance imaging (fMRI) was used to examine the role of the prefrontal cortex (PFC) in both long-term memory (LTM) encoding and working memory (WM) tasks involving a variety of material types (words, faces, and pictures). Encoding was studied in a task requiring intentional memorization of items for a later recognition test. WM was studied in the two-back condition of the n-back task. Bilateral PFC in the inferior frontal gyrus (IFG) was found to be jointly activated in both encoding and WM. This region also showed materialspecific lateralization in both tasks, with the left hemisphere more active for words and the right hemisphere more active for faces. PFC regions were also found that were selective to either encoding or WM. Right dorsolateral PFC was selectively activated during WM, but showed no material-specificity, while left anterior PFC was selectively activated during encoding of faces and pictures. Activity in medial temporal lobe was also observed, with ...

INTRODUCTION During the past decade, the field of functional neuroimaging of cognition has grown exponentially. From a handful of studies in the early 1990s, this research domain expanded to more than 800 studies by the early 2000s. Today, positron emission tomography (PET) and functional MRI (fMRI) studies cover almost every aspect of human cognition, from motion perception to moral reasoning. If each study is seen as a tree, the field has grown from minimal vegetation to a luxuriant tropical forest in less than 10 years. Yet, functional neuroimaging researchers sometimes focus exclusively on their own cognitive domain and do not see the forest through the trees. The goal of the present chapter is to call attention to the forest--- that is, to what many functional neuroimaging studies of cognition have in common. When we say that most researchers are focused on the trees, we refer to the fact that the vast majority of functional neuroimaging studies investigate a single cognitive fu

INTRODUCTION During the past decades, understanding the neural mechanisms of voluntary action has been one of the key issues in neuroscience. A great deal of research in this field has focused on the acquisition of arbitrary sensorimotor associations, that is, associations between sensory cues and subsequent actions that lack any systematic relationship (Kurata et al., 2000; Sakai et al., 1999; Toni and Passingham, 1999; Wise and Murray, 2000). However, the key feature of voluntary action is that these actions are commonly not prompted by sensory cues, but rather guided by intentions: The agent intends to achieve a certain goal or to produce a desired effect (Prinz, 1997). For example, musicians play the piano not because seeing the keyboard triggers keypressing movements, but because they wish to produce a particular melody. To perform an intentional action, the agent needs to know what consequences a particular movement will have. Hence, voluntary action depends on the ability to l

A model is described in which the hippocampal system functions as resource manager for the neocortex. This model is developed from an architectural concept for the brain as a whole within which the receptive fields of neocortical columns can gradually increase but with some limited exceptions tend not to decrease. The definition process for receptive fields is constrained so that they overlap as little as possible, and change as little as possible, but at least a minimum number of columns detect their fields within every sensory input state. Below this minimum, the receptive fields of some columns are increased slightly until the minimum level is reached. The columns in which this increase occurs are selected by a competitive process in the hippocampal system that identifies those in which only a relatively small increase is required, and sends signals to those columns that trigger the increase. These increases in receptive fields are the information record that forms the declarative memory of the input state. Episodic memory activates a set of columns in which receptive fields increased simultaneously at some point in the past, and the hippocampal system is therefore the appropriate source for information guiding access to such memories. Semantic memory associates columns that are often active (with or without increases in receptive fields) simultaneously. Initially, the hippocampus can guide access to such memories on the basis of initial information recording, but to avoid corruption of the information needed for ongoing resource management, access control shifts to other parts of the neocortex. The roles of the mammillary bodies, amygdala and anterior thalamic nucleus can be understood as modulating information recording in accordance with various behavioral priorities. During sleep, provisional physical connectivity is created that supports receptive field increases in the subsequent wake period, but previously created memories are not affected. This model matches a wide range of neuropsychological observation better than alternative hippocampal models. The information mechanisms required by the model are consistent with known brain anatomy and neuron physiology. 2

A model is described in which the hippocampal system functions as resource manager for the neocortex. This model is developed from an architectural concept for the neocortex in which the receptive fields of cortical columns can gradually increase but with some narrowly defined exceptions cannot decrease. The definition process for receptive fields is constrained so that they overlap as little as possible, and change as little as possible, but at least a minimum number of columns detect their fields within every sensory input state. Below this minimum, the receptive fields of some columns are increased slightly until it is reached. The columns in which this increase occurs are selected by a competitive process in the hippocampal system that identifies a group of columns for which only a relatively small increase is required, and sends signals to those columns that trigger the increase. These increases in receptive fields are the information record which forms the declarative memory of the input state. Episodic memory associates all columns in which receptive fields increased simultaneously, and the hippocampal system is therefore the appropriate source for information guiding access to such memories. Semantic memory associates columns which are often active (with or without increases in receptive fields) simultaneously. Initially, the hippocampus may guide access to such memories on the basis of initial information recording, but frequent access shifts control to other parts of the neocortex. The roles of the mammillary bodies, amygdala and anterior thalamic nucleus can be understood as modulating information recording in accordance with various behavioral priorities. Provisional physical connectivity created during sleep supports receptive field increases in the subsequent wake period. Previously created memories are not affected. This model matches a wide range of neuropsychological observation better than alternative hippocampal models. The neuron mechanisms required by the model are consistent with known neuron physiology.

The neural substrate of the ideomotor principle: An event-related fMRI analysis