Unraveling the functional attributes of the language connectome: crucial subnetworks, flexibility and variability.

Language processing is a highly integrative function, intertwining linguistic operations (processing the language code intentionally used for communication) and extra-linguistic processes (e.g., attention monitoring, predictive inference, long-term memory). This synergetic cognitive architecture requires a distributed and specialized neural substrate. Brain systems have mainly been examined at rest. However, task-related functional connectivity provides additional and valuable information about how information is processed when various cognitive states are involved. We gathered thirteen language fMRI tasks in a unique database of one hundred and fifty neurotypical adults (InLang [Interactive networks of Language] database), providing the opportunity to assess language features across a wide range of linguistic processes. Using this database, we applied network theory as a computational tool to model the task-related functional connectome of language (LANG atlas). The organization of this data-driven neurocognitive atlas of language was examined at multiple levels, uncovering its major components (or crucial subnetworks), and its anatomical and functional correlates. In addition, we estimated its reconfiguration as a function of linguistic demand (flexibility) or several factors such as age or gender (variability). We observed that several discrete networks could be specifically shaped to promote key functional features of language: coding-decoding (Net1), control-executive (Net2), abstract-knowledge (Net3), and sensorimotor (Net4) functions. The architecture of these systems and the functional connectivity of the pivotal brain regions varied according to the nature of the linguistic process, gender, or age. By accounting for the multifaceted nature of language and modulating factors, this study can contribute to enriching and refining existing neurocognitive models of language. The LANG atlas can also be considered a reference for comparative or clinical studies involving various patients and conditions.

Schema cells in the macaque hippocampus.

Concept cells in the human hippocampus encode the meaning conveyed by stimuli over their perceptual aspects. Here we investigate whether analogous cells in the macaque can form conceptual schemas of spatial environments. Each day, monkeys were presented with a familiar and a novel virtual maze, sharing a common schema but differing by surface features (landmarks). In both environments, animals searched for a hidden reward goal only defined in relation to landmarks. With learning, many neurons developed a firing map integrating goal-centered and task-related information of the novel maze that matched that for the familiar maze. Thus, these hippocampal cells abstract the spatial concepts from the superficial details of the environment and encode space into a schema-like representation.

Motor urgency is mediated by the contralateral cerebellum in Parkinson's disease.

BACKGROUND: In patients with Parkinson's disease (PD), motor performance may be dramatically improved in urgent and stressful situations. OBJECTIVE: The aim of this PET H(2)(15)O study was to determine the changes in brain activation pattern related to this unconscious increase in motor speed observed in the context of urgency in patients with PD. METHODS: Eight right-handed patients with PD, who had been off medication for at least 12 hours, without tremor, were enrolled. A reaching task with the right hand was performed under three conditions: self-initiated (SI), externally cued (EC) and externally cued-urgent (ECu). RESULTS: (1) Self-initiated movements (SI-EC) revealed activations in the prefrontal cortex bilaterally, the right lateral premotor cortex, anterior cingulate cortex and cerebellum, and the left primary motor cortex and thalamus; (2) Externally driven responses (EC-SI) did not involve any statistically detectable activation; (3) Urgent situations (ECu-EC) engaged the left cerebellum. Compared with a control group previously studied, the cerebellar activation was greater in patients with PD. CONCLUSIONS: This study demonstrates that the increase in movement speed in urgent situations in patients with PD is associated with the recruitment of the left (contralateral) cerebellum. This structure is a key node of the accessory motor circuitry typically recruited by patients with PD to compensate for basal ganglia dysfunction and by healthy subjects to increase movement velocity in urgent motor contexts.

Hand orientation for grasping depends on the direction of the reaching movement.

The 3D orientation of the hand for grasping was studied while subjects reached for objects placed at several locations on a horizontal board, with movements starting from three initial hand positions. The hand movements were recorded with electromagnetic sensors giving 3D position and orientation information. The study focused on the azimuth, which is the projection of the hand orientation in a horizontal plane. The hand azimuth for grasping was linearly correlated with the direction of the reaching movement and not with the object direction in head- or shoulder-centered coordinates. This relationship was valid regardless of the initial hand position. A control experiment with constant movement direction showed a weaker, probably postural, effect of object direction in shoulder-centered coordinates. We suggest that hand orientation for grasping is mainly controlled in relation to the reaching movement direction.

Recoding arm position to learn visuomotor transformations.

There is strong experimental evidence that guiding the arm toward a visual target involves an initial vectorial transformation from direction in visual space to direction in motor space. Constraints on this transformation are imposed (i) by the neural codes for incoming information: the desired movement direction is thought to be signalled by populations of broadly tuned neurons and arm position by populations of monotonically tuned neurons; and (ii) by the properties of outgoing information: the actual movement direction results from the collective action of broadly tuned neurons whose preferred directions rotate with the position of the arm. A neural network model is presented that computes the visuomotor mapping, given these constraints. Appropriate operations are learned by the network in an unsupervised fashion through repeated action- perception cycles by recoding the arm-related proprioceptive information. The resulting solution has two interesting properties: (i) the required transformation is executed accurately over a large part of the reaching space, although few positions are actually learned; and (ii) properties of single neurons and populations in the network closely resemble those of neurons and populations in parietal and motor cortical regions. This model thus suggests a realistic scenario for the calculation of coordinate transformations and initial motor command for arm reaching movements.

A model study of cellular short-term memory produced by slowly inactivating potassium conductances.

We analyzed the cellular short-term memory effects induced by a slowly inactivating potassium (Ks) conductance using a biophysical model of a neuron. We first described latency-to-first-spike and temporal changes in firing frequency as a function of parameters of the model, injected current and prior history of the neuron (deinactivation level) under current clamp. This provided a complete set of properties describing the Ks conductance in a neuron. We then showed that the action of the Ks conductance is not generally appropriate for controlling latency-to-first-spike under random synaptic stimulation. However, reliable latencies were found when neuronal population computation was used. Ks inactivation was found to control the rate of convergence to steady-state discharge behavior and to allow frequency to increase at variable rates in sets of synaptically connected neurons. These results suggest that inactivation of the Ks conductance can have a reliable influence on the behavior of neuronal populations under real physiological conditions.

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.

Early motor influences on visuomotor transformations for reaching: a positive image of optic ataxia.

Coding of reaching in the cerebral cortex is based on the operation of distributed populations of parietal and frontal neurons, whose main functional characteristics reside in their combinatorial power, i.e., in the capacity for combining different information related to the spatial aspects of reaching. The tangential distribution of reach-related neurons endowed with different functional properties changes gradually in the cortex and defines, in the parieto-frontal network, trends of functional properties. These visual-to-somatic gradients imply the existence of cortical regions of functional overlaps, i.e., of combinatorial domains, where the integration of different reach-related signals occurs. Studies of early coding of reaching in the mesial parietal areas show how somatomotor information, such as that related to arm posture and movement, influences neuronal activity in the very early stages of the visuomotor transformation underlying the composition of the motor command and is not added "downstream" in the frontal cortex. This influence is probably due to re-entrant signals traveling through fronto-parietal-association connections. Together with the gradient architecture of the network and the reciprocity of cortico-cortical connections, this implies that coding of reaching cannot be regarded as a top-down, serial sequence of coordinate transformation, each performed by a given cortical area, but as a recursive process, where different signals are progressively matched and further elaborated locally, due to intrinsic cortical connections. This model of reaching is also supported by psychophysical studies stressing the parallel processing of the different relevant parameters and the "hybrid" nature of the reference frame where they are combined. The theoretical frame presented here can also offer a background for a new interpretation of a well-known visuomotor disorder, due to superior parietal lesions, i.e., optic ataxia. More than a disconnection syndrome, this can now be interpreted as the consequence of the breakdown of the operations occurring in the combinatorial domains of the superior parietal segment of the parieto-frontal network.