Testing the model of caudo-rostral organization of cognitive control in the human with frontal lesions.

The cascade model of cognitive control, mostly relying on functional neuroimaging studies, stipulates that the lateral frontal cortex (LFC) is organized as a cascade of executive processes involving three levels of cognitive control, implemented in distinct LFC areas from the premotor to the anterior prefrontal regions. The present experiment tested this model in patients with LFC lesions and studied the hierarchy of executive functions along the caudo-rostral axis, i.e. the respective roles of the different LFC areas in the control of behavior. Voxel-based lesion-symptom mapping and region of interest group analyses were conducted in 32 patients with focal LFC lesions who performed cognitive tasks assessing the cascade model. We first showed that three different LFC areas along the caudo-rostral axis subserved three distinct control levels, whose integrity is necessary for adaptive behavior. Second, we found that prefrontal cognitive control has an asymmetric organization: higher control processes involving more anterior prefrontal regions rely on the integrity of lower control processes in more posterior regions, while lower control processes can operate irrespective of the integrity of higher control processes. Altogether, these findings support a caudo-rostral cascade of executive processes from premotor to anterior prefrontal regions.

Dissociating the role of the medial and lateral anterior prefrontal cortex in human planning.

The anterior prefrontal cortex is known to subserve higher cognitive functions such as task management and planning. Less is known, however, about the functional specialization of this cortical region in humans. Using functional MRI, we report a double dissociation: the medial anterior prefrontal cortex, in association with the ventral striatum, was engaged preferentially when subjects executed tasks in sequences that were expected, whereas the polar prefrontal cortex, in association with the dorsolateral striatum, was involved preferentially when subjects performed tasks in sequences that were contingent on unpredictable events. These results parallel the functional segregation previously described between the medial and lateral premotor cortex underlying planned and contingent motor control and extend this division to the anterior prefrontal cortex, when task management and planning are required. Thus, our findings support the assumption that common frontal organizational principles underlie motor and higher executive functions in humans.

Differential amygdala responses to winning and losing: a functional magnetic resonance imaging study in humans.

The amygdala has been shown to respond to many distinct types of affective stimuli, including reward and punishment feedback in animals. In humans, winning and losing situations can be considered as reward and punishment experiences, respectively. In this study, we used functional magnetic resonance imaging (fMRI) to measure regional brain activity when human subjects were given feedback on their performance during a simple response time task in a fictitious competitive tournament. Lexical stimuli were used to convey positive 'win' or negative 'lose' feedback. The frequency of positive and negative trials was parametrically varied by the experimenters independently from the subjects' actual performance and unbeknownst to them. The results showed that the parametric increase of winning was associated with left amygdala activation whereas the parametric increase of losing was associated with right amygdala activation. These findings provide functional evidence that the human amygdala differentially responds to changes in magnitude of positive or negative reinforcement conveyed by lexical stimuli.

Parieto-frontal coding of reaching: an integrated framework.

In the last few years, anatomical and physiological studies have provided new insights into the organization of the parieto-frontal network underlying visually guided arm-reaching movements in at least three domains. (1) Network architecture. It has been shown that the different classes of neurons encoding information relevant to reaching are not confined within individual cortical areas, but are common to different areas, which are generally linked by reciprocal association connections. (2) Representation of information. There is evidence suggesting that reach-related populations of neurons do not encode relevant parameters within pure sensory or motor "reference frames", but rather combine them within hybrid dimensions. (3) Visuomotor transformation. It has been proposed that the computation of motor commands for reaching occurs as a simultaneous recruitment of discrete populations of neurons sharing similar properties in different cortical areas, rather than as a serial process from vision to movement, engaging different areas at different times. The goal of this paper was to link experimental (neurophysiological and neuroanatomical) and computational aspects within an integrated framework to illustrate how different neuronal populations in the parieto-frontal network operate a collective and distributed computation for reaching. In this framework, all dynamic (tuning, combinatorial, computational) properties of units are determined by their location relative to three main functional axes of the network, the visual-to-somatic, position-direction, and sensory-motor axis. The visual-to-somatic axis is defined by gradients of activity symmetrical to the central sulcus and distributed over both frontal and parietal cortices. At least four sets of reach-related signals (retinal, gaze, arm position/movement direction, muscle output) are represented along this axis. This architecture defines informational domains where neurons combine different inputs. The position-direction axis is identified by the regular distribution of information over large populations of neurons processing both positional and directional signals (concerning the arm, gaze, visual stimuli, etc.) Therefore, the activity of gaze- and arm-related neurons can represent virtual three-dimensional (3D) pathways for gaze shifts or hand movement. Virtual 3D pathways are thus defined by a combination of directional and positional information. The sensory-motor axis is defined by neurons displaying different temporal relationships with the different reach-related signals, such as target presentation, preparation for intended arm movement, onset of movements, etc. These properties reflect the computation performed by local networks, which are formed by two types of processing units: matching and condition units. Matching units relate different neural representations of virtual 3D pathways for gaze or hand, and can predict motor commands and their sensory consequences. Depending on the units involved, different matching operations can be learned in the network, resulting in the acquisition of different visuo-motor transformations, such as those underlying reaching to foveated targets, reaching to extrafoveal targets, and visual tracking of hand movement trajectory. Condition units link these matching operations to reinforcement contingencies and therefore can shape the collective neural recruitment along the three axes of the network. This will result in a progressive match of retinal, gaze, arm, and muscle signals suitable for moving the hand toward the target.

The role of the anterior prefrontal cortex in human cognition.

Complex problem-solving and planning involve the most anterior part of the frontal lobes including the fronto-polar prefrontal cortex (FPPC), which is especially well developed in humans compared with other primates. The specific role of this region in human cognition, however, is poorly understood. Here we show, using functional magnetic resonance imaging, that bilateral regions in the FPPC alone are selectively activated when subjects have to keep in mind a main goal while performing concurrent (sub)goals. Neither keeping in mind a goal over time (working memory) nor successively allocating attentional resources between alternative goals (dual-task performance) could by themselves activate these regions. Our results indicate that the FPPC selectively mediates the human ability to hold in mind goals while exploring and processing secondary goals, a process generally required in planning and reasoning.

Bayesian inference in populations of cortical neurons: a model of motion integration and segmentation in area MT.

A major issue in cortical physiology and computational neuroscience is understanding the interaction between extrinsic signals from feedforward connections and intracortical signals from lateral connections. We propose here a computational model for motion perception based on the assumption that the local cortical circuits in the medio-temporal area (area MT) implement a Bayesian inference principle. This approach establishes a functional balance between feedforward and lateral, excitatory and inhibitory, inputs. The model reproduces most of the known properties of the neurons in area MT in response to moving stimuli. It accounts for important motion perception phenomena including motion transparency, spatial and temporal integration/segmentation. While integrating several properties of previously proposed models, it makes specific testable predictions concerning, in particular, temporal properties of neurons and the architecture of lateral connections in area MT. In addition, the proposed mechanism is consistent with the known properties of local cortical circuits in area V1. This suggests that Bayesian inference may be a general feature of information processing in cortical neuron populations.

Imaging unconscious semantic priming.

Visual words that are masked and presented so briefly that they cannot be seen may nevertheless facilitate the subsequent processing of related words, a phenomenon called masked priming. It has been debated whether masked primes can activate cognitive processes without gaining access to consciousness. Here we use a combination of behavioural and brain-imaging techniques to estimate the depth of processing of masked numerical primes. Our results indicate that masked stimuli have a measurable influence on electrical and haemodynamic measures of brain activity. When subjects engage in an overt semantic comparison task with a clearly visible target numeral, measures of covert motor activity indicate that they also unconsciously apply the task instructions to an unseen masked numeral. A stream of perceptual, semantic and motor processes can therefore occur without awareness.

Dynamical computational properties of local cortical networks for visual and motor processing: a bayesian framework.

A major unsolved question concerns the interaction between the coding of information in the cortex and the collective neural operations (such as perceptual grouping, mental rotation) that can be performed on this information. A key property of the local networks in the cerebral cortex is to combine thalamocortical or feedforward information with horizontal cortico-cortical connections. Among different types of neural networks compatible with the known functional and architectural properties of the cortex, we show that there exist interesting bayesian solutions resulting in an optimal collective decision made by the neuronal population. We suggest that thalamo-cortical and cortico-cortical synaptic plasticity can be differentially modulated to optimize this collective bayesian decision process. We take two examples of cortical dynamics, one for perceptual grouping in MT, and the other one for mental rotation in M1. We show that a neural implementation of the bayesian principle is both computationally efficient to perform these tasks and consistent with the experimental data on the related neuronal activities. A major implication is that a similar collective decision mechanism should exist in different cortical regions due to the similarity of the cortical functional architecture.

Dual Population Coding in the Neocortex: A Model of Interaction between Representation and Attention in the Visual Cortex.

The text describes a model that extends the population coding principles to any multidimensional attribute. The model distinguishes between the distribution of cell activity and the overall activity of a population. The distribution of cell activity is assumed to encode attribute information, while overall activity is assumed to reflect the significance or pertinence of the encoded attribute in the cerebral cortex, according to the dual coding principle. Three basic mechanisms of interaction between the representation of attribute and pertinence are defined and are applied to the motion (MT-MST) cortical pathway in the visual cortex. This framework determines three sources of pertinence that model cognitive processing, including preattentive processing, spatial-selective attention, and object-selective attention. The model accommodates most of the published psychophysical, neurophysiological, and neuroanatomical data and makes several testable predictions about the representations of attribute and enhanced effects in these areas.