The human amygdala and orbital prefrontal cortex in behavioural regulation

Survival in complex environments depends on an ability to optimize future behaviour based on past experience. Learning from experience enables an organism to generate predictive expectancies regarding probable future states of the world, enabling deployment of flexible behavioural strategies. However, behavioural flexibility cannot rely on predictive expectancies alone and options for action need to be deployed in a manner that is responsive to a changing environment. Important moderators on learning-based predictions include those provided by context and inputs regarding an organism's current state, including its physiological state. In this paper, I consider human experimental approaches using functional magnetic resonance imaging that have addressed the role of the amygdala and prefrontal cortex (PFC), in particular the orbital PFC, in acquiring predictive information regarding the probable value of future events, updating this information, and shaping behaviour and decision processes on the basis of these value representations.     

The prefrontal cortex and working memory: physiology and brain imaging

Sustained activity has been recorded in the prefrontal cortex during working memory tasks. First, we compare the anatomical distribution of this activity in humans and monkeys. Then, we show that it reflects many factors, maintenance of the items presented, preparation for the response, transformation of the items during the delay, task rules and task goals. Finally, we point out that sustained activity has also been recorded in other areas, such as the parietal cortex. We suggest that the key to prefrontal cortex lies not in the maintenance of sensory information but in the prospective use of that information for behaviour.     

The role of prefrontal cortex in working memory: examining the contents of consciousness.

Working memory enables us to hold in our ''mind''s eye'' the contents of our conscious awareness, even in the absence of sensory input, by maintaining an active representation of information for a brief period of time. In this review we consider the functional organization of the prefrontal cortex and its role in this cognitive process. First, we present evidence from brain-imaging studies that prefrontal cortex shows sustained activity during the delay period of visual working memory tasks, indicating that this cortex maintains on-line representations of stimuli after they are removed from view. We then present evidence for domain specificity within frontal cortex based on the type of information, with object working memory mediated by more ventral frontal regions and spatial working memory mediated by more dorsal frontal regions. We also propose that a second dimension for domain specificity within prefrontal cortex might exist for object working memory on the basis of the type of representation, with analytic representations maintained preferentially in the left hemisphere and image-based representations maintained preferentially in the right hemisphere. Furthermore, we discuss the possibility that there are prefrontal areas brought into play during the monitoring and manipulation of information in working memory in addition to those engaged during the maintenance of this information. Finally, we consider the relationship of prefrontal areas important for working memory, both to posterior visual processing areas and to prefrontal areas associated with long-term memory.     

Increased Firing Irregularity as an Emergent Property of Neural-State Transition in Monkey Prefrontal Cortex

Flexible behaviors are organized by complex neural networks in the prefrontal cortex. Recent studies have suggested that such networks exhibit multiple dynamical states, and can switch rapidly from one state to another. In many complex systems such as the brain, the early-warning signals that may predict whether a critical threshold for state transitions is approaching are extremely difficult to detect. We hypothesized that increases in firing irregularity are a crucial measure for predicting state transitions in the underlying neuronal circuits of the prefrontal cortex. We used both experimental and theoretical approaches to test this hypothesis. Experimentally, we analyzed activities of neurons in the prefrontal cortex while monkeys performed a maze task that required them to perform actions to reach a goal. We observed increased firing irregularity before the activity changed to encode goal-to-action information. Theoretically, we constructed theoretical generic neural networks and demonstrated that changes in neuronal gain on functional connectivity resulted in a loss of stability and an altered state of the networks, accompanied by increased firing irregularity. These results suggest that assessing the temporal pattern of neuronal fluctuations provides important clues regarding the state stability of the prefrontal network. We also introduce a novel scheme that the prefrontal cortex functions in a metastable state near the critical point of bifurcation. According to this scheme, firing irregularity in the prefrontal cortex indicates that the system is about to change its state and the flow of information in a flexible manner, which is essential for executive functions. This metastable and/or critical dynamical state of the prefrontal cortex may account for distractibility and loss of flexibility in the prefrontal cortex in major mental illnesses such as schizophrenia.     

Reading hidden intentions in the human brain

When humans are engaged in goal-related processing, activity in prefrontal cortex is increased. However, it has remained unclear whether this prefrontal activity encodes a subject's current intention. Instead, increased levels of activity could reflect preparation of motor responses, holding in mind a set of potential choices, tracking the memory of previous responses, or general processes related to establishing a new task set. Here we study subjects who freely decided which of two tasks to perform and covertly held onto an intention during a variable delay. Only after this delay did they perform the chosen task and indicate which task they had prepared. We demonstrate that during the delay, it is possible to decode from activity in medial and lateral regions of prefrontal cortex which of two tasks the subjects were covertly intending to perform. This suggests that covert goals can be represented by distributed patterns of activity in the prefrontal cortex, thereby providing a potential neural substrate for prospective memory. During task execution, most information could be decoded from a more posterior region of prefrontal cortex, suggesting that different brain regions encode goals during task preparation and task execution. Decoding of intentions was most robust from the medial prefrontal cortex, which is consistent with a specific role of this region when subjects reflect on their own mental states.     

The prefrontal cortex and cognitive control

One of the enduring mysteries of brain function concerns the process of cognitive control. How does complex and seemingly willful behaviour emerge from interactions between millions of neurons? This has long been suspected to depend on the prefrontal cortex--the neocortex at the anterior end of the brain--but now we are beginning to uncover its neural basis. Nearly all intended behaviour is learned and so depends on a cognitive system that can acquire and implement the 'rules of the game' needed to achieve a given goal in a given situation. Studies indicate that the prefrontal cortex is central in this process. It provides an infrastructure for synthesizing a diverse range of information that lays the foundation for the complex forms of behaviour observed in primates.     

Coding of cognitive magnitude: compressed scaling of numerical information in the primate prefrontal cortex

Whether cognitive representations are better conceived as language-based, symbolic representations or perceptually related, analog representations is a subject of debate. If cognitive processes parallel perceptual processes, then fundamental psychophysical laws should hold for each. To test this, we analyzed both behavioral and neuronal representations of numerosity in the prefrontal cortex of rhesus monkeys. The data were best described by a nonlinearly compressed scaling of numerical information, as postulated by the Weber-Fechner law or Stevens' law for psychophysical/sensory magnitudes. This nonlinear compression was observed on the neural level during the acquisition phase of the task and maintained through the memory phase with no further compression. These results suggest that certain cognitive and perceptual/sensory representations share the same fundamental mechanisms and neural coding schemes.     

Creating abstract topographic representations: Implications for coding,learning and reasoning

Topographic maps are a fundamental and ubiquitous feature of the sensory and motor regions of the brain. There is less evidence for the existence of conventional topographic maps in associational areas of the brain such as the prefrontal cortex and parietal cortex. The existence of topographically arranged anatomical projections is far more widespread and occurs in associational regions of the brain as well as sensory and motor regions: this points to a more widespread existence of topographically organised maps within associational cortex than currently recognised. Indeed, there is increasing evidence that abstract topographic representations may also occur in these regions. For example, a topographic mnemonic map of visual space has been described in the dorsolateral prefrontal cortex and topographically arranged visuospatial attentional signals have been described in parietal association cortex. This article explores how abstract representations might be extracted from sensory topographic representations and subsequently code abstract information. Finally a simple model is presented that shows how abstract topographic representations could be integrated with other information within the brain to solve problems or form abstract associations. The model uses correlative firing to detect associations between different types of stimuli. It is flexible because it can produce correlations between information represented in a topographic or non-topographic coordinate system. It is proposed that a similar process could be used in high-level cognitive operations such as learning and reasoning.     

Dopamine-dependent interactions between limbic and prefrontal cortical plasticity in the nucleus accumbens: disruption by cocaine sensitization

The prefrontal cortex and the hippocampus exhibit converging projections to the nucleus accumbens and have functional reciprocal connections via indirect pathways. As a result, information processing between these structures is likely to be bidirectional. Using evoked potential measures, we examined the interactions of these inputs on synaptic plasticity within the accumbens. Our results show that the direction of information flow between the prefrontal cortex and limbic structures determines the synaptic plasticity that these inputs exhibit within the accumbens. Moreover, this synaptic plasticity at hippocampal and prefrontal inputs selectively involves dopamine D1 and D2 activation or inactivation, respectively. Repeated cocaine administration disrupted this synaptic plasticity at hippocampal and prefrontal cortical inputs and goal-directed behavior in the spatial maze task. Thus, interactions of limbic-prefrontal cortical synaptic plasticity and its dysfunction within the accumbens could underlie complex information processing deficits observed in individuals following psychostimulant administration.     

The neural basis of episodic memory: evidence from functional neuroimaging

We review some of our recent research using functional neuroimaging to investigate neural activity supporting the encoding and retrieval of episodic memories, that is, memories for unique events. Findings from studies of encoding indicate that, at the cortical level, the regions responsible for the effective encoding of a stimulus event as an episodic memory include some of the regions that are also engaged to process the event 'online'. Thus, it appears that there is no single cortical site or circuit responsible for episodic encoding. The results of retrieval studies indicate that successful recollection of episodic information is associated with activation of lateral parietal cortex, along with more variable patterns of activity in dorsolateral and anterior prefrontal cortex. Whereas parietal regions may play a part in the representation of retrieved information, prefrontal areas appear to support processes that act on the products of retrieval to align behaviour with the demands of the retrieval task.     

Differential Contributions of Dorso-Ventral and Rostro-Caudal Prefrontal White Matter Tracts to Cognitive Control in Healthy Older Adults

Prefrontal cortex mediates cognitive control by means of circuitry organized along dorso-ventral and rostro-caudal axes. Along the dorso-ventral axis, ventrolateral PFC controls semantic information, whereas dorsolateral PFC encodes task rules. Along the rostro-caudal axis, anterior prefrontal cortex encodes complex rules and relationships between stimuli, whereas posterior prefrontal cortex encodes simple relationships between stimuli and behavior. Evidence of these gradients of prefrontal cortex organization has been well documented in fMRI studies, but their functional correlates have not been examined with regard to integrity of underlying white matter tracts. We hypothesized that (a) the integrity of specific white matter tracts is related to cognitive functioning in a manner consistent with the dorso-ventral and rostro-caudal organization of the prefrontal cortex, and (b) this would be particularly evident in healthy older adults. We assessed three cognitive processes that recruit the prefrontal cortex and can distinguish white matter tracts along the dorso-ventral and rostro-caudal dimensions –episodic memory, working memory, and reasoning. Correlations between cognition and fractional anisotropy as well as fiber tractography revealed: (a) Episodic memory was related to ventral prefrontal cortex-thalamo-hippocampal fiber integrity; (b) Working memory was related to integrity of corpus callosum body fibers subserving dorsolateral prefrontal cortex; and (c) Reasoning was related to integrity of corpus callosum body fibers subserving rostral and caudal dorsolateral prefrontal cortex. These findings confirm the ventrolateral prefrontal cortex''s role in semantic control and the dorsolateral prefrontal cortex''s role in rule-based processing, in accordance with the dorso-ventral prefrontal cortex gradient. Reasoning-related rostral and caudal superior frontal white matter may facilitate different levels of task rule complexity. This study is the first to demonstrate dorso-ventral and rostro-caudal prefrontal cortex processing gradients in white matter integrity.     

From cognitive to neural models of working memory

Working memory refers to the temporary retention of information that was just experienced or just retrieved from long-term memory but no longer exists in the external environment. These internal representations are short-lived, but can be stored for longer periods of time through active maintenance or rehearsal strategies, and can be subjected to various operations that manipulate the information in such a way that makes it useful for goal-directed behaviour. Empirical studies of working memory using neuroscientific techniques, such as neuronal recordings in monkeys or functional neuroimaging in humans, have advanced our knowledge of the underlying neural mechanisms of working memory. This rich dataset can be reconciled with behavioural findings derived from investigating the cognitive mechanisms underlying working memory. In this paper, I review the progress that has been made towards this effort by illustrating how investigations of the neural mechanisms underlying working memory can be influenced by cognitive models and, in turn, how cognitive models can be shaped and modified by neuroscientific data. One conclusion that arises from this research is that working memory can be viewed as neither a unitary nor a dedicated system. A network of brain regions, including the prefrontal cortex (PFC), is critical for the active maintenance of internal representations that are necessary for goal-directed behaviour. Thus, working memory is not localized to a single brain region but probably is an emergent property of the functional interactions between the PFC and the rest of the brain.     

Prefrontal cortex and neural mechanisms of executive function

Executive function is a product of the coordinated operation of multiple neural systems and an essential prerequisite for a variety of cognitive functions. The prefrontal cortex is known to be a key structure for the performance of executive functions. To accomplish the coordinated operations of multiple neural systems, the prefrontal cortex must monitor the activities in other cortical and subcortical structures and control and supervise their operations by sending command signals, which is called top-down signaling. Although neurophysiological and neuroimaging studies have provided evidence that the prefrontal cortex sends top-down signals to the posterior cortices to control information processing, the neural correlate of these top-down signals is not yet known. Through use of the paired association task, it has been demonstrated that top-down signals are used to retrieve specific information stored in long-term memory. Therefore, we used a paired association task to examine the neural correlates of top-down signals in the prefrontal cortex. The preliminary results indicate that 32% of visual neurons exhibit pair-selectivity, which is similar to the characteristics of pair-coding activities in temporal neurons. The latency of visual responses in prefrontal neurons was longer than bottom-up signals but faster than top-down signals in inferior temporal neurons. These results suggest that pair-selective visual responses may be top-down signals that the prefrontal cortex provides to the temporal cortex, although further studies are needed to elucidate the neural correlates of top-down signals and their characteristics to understand the neural mechanism of executive control by the prefrontal cortex.     

Metacognition and mentalizing are associated with distinct neural representations of decision uncertainty

Metacognition and mentalizing are both associated with meta-level mental state representations. Conventionally, metacognition refers to monitoring one’s own cognitive processes, while mentalizing refers to monitoring others’ cognitive processes. However, this self-other dichotomy is insufficient to delineate the 2 high-level mental processes. We here used functional magnetic resonance imaging (fMRI) to systematically investigate the neural representations of different levels of decision uncertainty in monitoring different targets (the current self, the past self [PS], and others) performing a perceptual decision-making task. Our results reveal diverse formats of internal mental state representations of decision uncertainty in mentalizing, separate from the associations with external cue information. External cue information was commonly represented in the right inferior parietal lobe (IPL) across the mentalizing tasks. However, the internal mental states of decision uncertainty attributed to others were uniquely represented in the dorsomedial prefrontal cortex (dmPFC), rather than the temporoparietal junction (TPJ) that also represented the object-level mental states of decision inaccuracy attributed to others. Further, the object-level and meta-level mental states of decision uncertainty, when attributed to the PS, were represented in the precuneus and the lateral frontopolar cortex (lFPC), respectively. In contrast, the dorsal anterior cingulate cortex (dACC) represented currently experienced decision uncertainty in metacognition, and also uncertainty about the estimated decision uncertainty (estimate uncertainty), but not the estimated decision uncertainty per se in mentalizing. Hence, our findings identify neural signatures to clearly delineate metacognition and mentalizing and further imply distinct neural computations on internal mental states of decision uncertainty during metacognition and mentalizing.

The relationship between metacognition and mentalizing is still a matter of debate, as both are associated with meta-representations. This study adapts a task paradigm used in metacognition to apply in mentalizing and compares the neural representations of decision uncertainty in metacognition and mentalizing.     

Top-down control of motor cortex ensembles by dorsomedial prefrontal cortex

Dorsomedial prefrontal cortex is critical for the temporal control of behavior. Dorsomedial prefrontal cortex might alter neuronal activity in areas such as motor cortex to inhibit temporally inappropriate responses. We tested this hypothesis by recording from neuronal ensembles in rodent dorsomedial prefrontal cortex during a delayed-response task. One-third of dorsomedial prefrontal neurons were significantly modulated during the delay period. The activity of many of these neurons was predictive of premature responding. We then reversibly inactivated dorsomedial prefrontal cortex while recording ensemble activity in motor cortex. Inactivation of dorsomedial prefrontal cortex reduced delay-related firing, but not response-related firing, in motor cortex. Finally, we made simultaneous recordings in dorsomedial prefrontal cortex and motor cortex and found strong delay-related temporal correlations between neurons in the two cortical areas. These data suggest that functional interactions between dorsomedial prefrontal cortex and motor cortex might serve as a top-down control signal that inhibits inappropriate responding.     

Common prefrontal regions coactivate with dissociable posterior regions during controlled semantic and phonological tasks

One of the most ubiquitous findings in functional neuroimaging research is activation of left inferior prefrontal cortex (LIPC) during tasks requiring controlled semantic retrieval. Here we show that LIPC participates in the controlled retrieval of nonsemantic representations as well as semantic representations. Results also demonstrate that LIPC coactivates with dissociable posterior regions depending on the information retrieved: activating with left temporal cortex during the controlled retrieval of semantics and with left posterior frontal and parietal cortex during the controlled retrieval of phonology. Correlation of performance to LIPC activation suggests a processing role associated with mapping relatively ambiguous stimulus-to-representation relationships during both semantic and phonological tasks. These findings suggest that LIPC participates in controlled processing across multiple information domains collaborating with dissociable posterior regions depending upon the kind of information retrieved.     

Contributions of the amygdala to reward expectancy and choice signals in human prefrontal cortex

The prefrontal cortex (PFC) receives substantial anatomical input from the amygdala, and these two structures have long been implicated in reward-related learning and decision making. Yet little is known about how these regions interact, especially in humans. We investigated the contribution of the amygdala to reward-related signals in PFC by scanning two rare subjects with focal bilateral amygdala lesions using fMRI. The subjects performed a reversal learning task in which they first had to learn which of two choices was the more rewarding, and then flexibly switch their choices when contingencies changed. Compared with healthy controls, both amygdala lesion subjects showed a profound change in ventromedial prefrontal cortex (vmPFC) activity associated with reward expectation and behavioral choice. These findings support a critical role for the human amygdala in establishing expected reward representations in PFC, which in turn may be used to guide behavioral choice.     

Modelling relative recency discrimination tasks using a stochastic working memory model

Relative recency discrimination (RD) task is typically used to assess the temporal organization function of the prefrontal cortex (PFC). Subjects look at a series of cards (with words or drawings on them) and on seeing a test card determine which of the two items was seen more recently. Results show that patients with damage to the prefrontal cortex are severely impaired on this task. We propose a memory trace-priming mechanism, based on automatic time-marking process hypothesis (Schacter, D.L., 1987. Memory, amnesia, and frontal lobe dysfunction: a critique and interpretation. Psychobiology 15, 21-36), to offer a computational account of the results. In this model, successive words seen by subjects leave decaying memory traces in PFC, which subsequently prime the representations in higher sensory areas such as inferior temporal Cortex (IT) during discrimination judgements. The paper focuses on the evaluation of a probabilistic pre-frontal trace mechanism using a pool of clusters of neurons with self-sustained firing that ends at a random time. The results show that the probabilistic behavior of subjects can be accounted for by the stochasticity of the trace model. A good fit to experimental data is obtained with a PFC memory persistence probability with a decay time constant of tau = approximately 30 s. The model allows for a distributed representation in IT and PFC, but the best fit suggests a sparse representation. It is concluded that further data are needed on representations in IT and PFC, on the connectivity between these two areas, and on the statistical and dynamic properties of memory neurons in PFC.     

Decoding the different states of visual attention using functional and effective connectivity features in fMRI data

The present paper concentrates on the impact of visual attention task on structure of the brain functional and effective connectivity networks using coherence and Granger causality methods. Since most studies used correlation method and resting-state functional connectivity, the task-based approach was selected for this experiment to boost our knowledge of spatial and feature-based attention. In the present study, the whole brain was divided into 82 sub-regions based on Brodmann areas. The coherence and Granger causality were applied to construct functional and effective connectivity matrices. These matrices were converted into graphs using a threshold, and the graph theory measures were calculated from it including degree and characteristic path length. Visual attention was found to reveal more information during the spatial-based task. The degree was higher while performing a spatial-based task, whereas characteristic path length was lower in the spatial-based task in both functional and effective connectivity. Primary and secondary visual cortex (17 and 18 Brodmann areas) were highly connected to parietal and prefrontal cortex while doing visual attention task. Whole brain connectivity was also calculated in both functional and effective connectivity. Our results reveal that Brodmann areas of 17, 18, 19, 46, 3 and 4 had a significant role proving that somatosensory, parietal and prefrontal regions along with visual cortex were highly connected to other parts of the cortex during the visual attention task. Characteristic path length results indicated an increase in functional connectivity and more functional integration in spatial-based attention compared with feature-based attention. The results of this work can provide useful information about the mechanism of visual attention at the network level.     

Reward representations and reward-related learning in the human brain: insights from neuroimaging

This review outlines recent findings from human neuroimaging concerning the role of a highly interconnected network of brain areas including orbital and medial prefrontal cortex, amygdala, striatum and dopaminergic mid-brain in reward processing. Distinct reward-related functions can be attributed to different components of this network. Orbitofrontal cortex is involved in coding stimulus reward value and in concert with the amygdala and ventral striatum is implicated in representing predicted future reward. Such representations can be used to guide action selection for reward, a process that depends, at least in part, on orbital and medial prefrontal cortex as well as dorsal striatum.