Alexandra Battaglia-Mayer

Parieto-frontal coding of reaching: an integrated framework

Abstract 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.

Visual Control of Hand‐reaching Movement: Activity in Parietal Area 7m

The activity of single neurons was studied in parietal area 7m while monkeys performed an instructed‐delay reaching task to visual targets under normal light conditions and in darkness. The task was aimed at assessing the influence of vision of hand position on the neural activity of 7m related either to static posture and movement of the hand or to eye position in the orbit. The results show the existence of preparatory, movement‐related and postural activity for the control of reaching, all of which are strongly modulated by vision. The activity of many 7m neurons, otherwise insensitive to pure visual stimuli, seems to reflect complex interactions between gaze angle and hand position in the visual field.

Cortical Mechanisms for Online Control of Hand Movement Trajectory: The Role of the Posterior Parietal Cortex

The parietal mechanisms for the control of hand movement trajectory were studied by recording cell activity in area 5 of monkeys making direct reaches to visual targets and online corrections of movement trajectory, after change of target location in space. The activity of hand-related cells was fitted with a linear model including hand position, movement direction, and speed. The neural activity modulation mostly led, but also followed, hand movement. When a change of hand trajectory occurred, the pattern of activity associated with the movement to the first target evolved into that typical of the movement to the second one, thus following the corresponding variations of the hand kinematics. The visual signal concerning target location in space did not influence the firing activity associated with the direction of hand movement within the first 150 ms after target presentation. This might be the time necessary for the visuo-motor transformation underlying reaching. We conclude that online control of hand trajectory not only resides in the relationships between neural activity and kinematics, but, under specific circumstances, also on the coexistence of signals about ongoing and future hand movement direction.

Diameter, Length, Speed, and Conduction Delay of Callosal Axons in Macaque Monkeys and Humans: Comparing Data from Histology and Magnetic Resonance Imaging Diffusion Tractography

Three macaque monkeys and 13 healthy human volunteers underwent diffusion tensor MRI with a 3 Tesla scanner for diffusion tract tracing (DTT) reconstruction of callosal bundles from different areas. In six macaque monkeys and three human subjects, the length of fiber tracts was obtained from histological data and combined with information on the distribution of axon diameter, so as to estimate callosal conduction delays from different areas. The results showed that in monkeys, the spectrum of tract lengths obtained with DTT closely matches that estimated from histological reconstruction of axons labeled with an anterogradely transported tracer. For each sector of the callosum, we obtained very similar conduction delays regardless of whether conduction distance was obtained from tractography or from histological analysis of labeled axons. This direct validation of DTT measurements by histological methods in monkeys was a prerequisite for the computation of the callosal conduction distances and delays in humans, which we had previously obtained by extrapolating the length of callosal axons from that of the monkey, proportionally to the brain volumes in the two species. For this analysis, we used the distribution of axon diameters from four different sectors of the corpus callosum. As in monkeys, in humans the shortest callosal conduction delays were those of motor, somatosensory, and premotor areas; the longer ones were those of temporal, parietal, and visual areas. These results provide the first histological validation of anatomical data about connection length in the primate brain based on DTT imaging.

Understanding the parietal lobe syndrome from a neurophysiological and evolutionary perspective

In human and nonhuman primates parietal cortex is formed by a multiplicity of areas. For those of the superior parietal lobule (SPL) there exists a certain homology between man and macaques. As a consequence, optic ataxia, a disturbed visual control of hand reaching, has similar features in man and monkeys. Establishing such correspondence has proven difficult for the areas of the inferior parietal lobule (IPL). This difficulty depends on many factors. First, no physiological information is available in man on the dynamic properties of cells in the IPL. Second, the number of IPL areas identified in the monkey is paradoxically higher than that so far described in man, although this issue will probably be reconsidered in future years, thanks to comparative imaging studies. Third, the consequences of parietal lesions in monkeys do not always match those observed in humans. This is another paradox if one considers that, in certain cases, the functional properties of neurons in the monkey’s IPL would predict the presence of behavioral skills, such as construction capacity, that however do not seem to emerge in the wild. Therefore, constructional apraxia, which is well characterized in man, has never been described in monkeys and apes. Finally, only certain aspects, i.e. hand directional hypokinesia and gaze apraxia (Balint’s psychic paralysis of gaze), of the multifaceted syndrome hemispatial neglect have been described in monkeys. These similarities, differences and paradoxes, among many others, make the study of the evolution and function of parietal cortex a challenging case.

The cortical network for eye-hand coordination and its relevance to understanding motor disorders of parietal patients

Cortical neurons in both superior (SPL) and inferior (IPL) parietal lobules are modulated by a variety of signals concerning planning and execution of eye and hand movement. Thanks to these properties, parietal neurons are ideally suited for eye-hand coordination during reaching. In SPL, a fundamental feature of neurons is the invariance of their directional tuning properties across tasks that require different forms of spatial relationships between the eye and the hand. In such conditions, the orientation of the preferred directions (PDs) of individual SPL cells cluster within a limited sector of space, the global tuning field (GTF), to be regarded as an ideal frame to dynamically match eye and hand signals on the basis of the orientation of their PDs. At the population level, the mean vectors of the GTF cover the direction continuum in a uniform fashion. These neurons are part of a parietal network richly interconnected with the premotor and motor areas of the frontal lobe. Thus, the reaching disorders of patients with optic ataxia might be interpreted as a consequence of the breakdown of the combinatorial mechanisms of the GTF of parietal neurons, and of their interplay with premotor cortex. In IPL, the main feature of eye and/or hand related neurons is the uneven distribution of their PDs, that mostly point toward the contralateral space. This anisotropy of the representation of directional motor space might explain the movement disorders that characterize directional hypokinesia in neglect patients. In conclusion, the study of the dynamic properties of parietal neurons and of their relationships with the premotor cortex via cortico-cortical connections provides a basis for an interpretation of movement disorders of parietal patients from a neurophysiological perspective.

Online Control of Hand Trajectory and Evolution of Motor Intention in the Parietofrontal System

The frontal mechanisms of motor intention were studied in dorsal premotor and motor cortex of monkeys making direct reaches to visual targets and online corrections of hand trajectory, whenever a change of the targets location occurred. This study and our previous one of parietal cortex (Archambault et al., 2009) provide a picture on the evolution of motor intention and online control of movement in the parietofrontal system. In frontal cortex, significant relationships were found between neural activity and hand kinematics (position, speed, and movement direction). When a change of motor intention occurred, the activity typical of the movement to the first target smoothly evolved into that associated with the movement toward the second one, as observed during direct reaches. Under these conditions, parietal cells remained a more accurate predictor of hand trajectory than frontal ones. The time lags of neural activity with hand kinematics showed that motor, premotor, and parietal cortex were activated sequentially. After the first targets presentation and its change of location, the population activity signaled the change of motor plan before the hand moved to the initial targets position. This signaling occurred earlier in premotor than in motor and parietal cortex. Thus, premotor cortex encodes a higher-order command for the correction of motor intention, while parietal cortex seems responsible for estimating the kinematics of the motor periphery, an essential step to allow motor cortex to modify the hand trajectory. This indicates that the parietofrontal system can update an original and not-yet-accomplished motor plan during its execution.

Statistical Analysis of Parieto-Frontal Cognitive-Motor Networks

Considerable information has been gathered on the anatomical connectivity within the parieto-frontal network of the primate brain. To examine the statistical regularities in this connectivity, we carried out hierarchical cluster analysis and found statistically significant clusters of areas: four in the parietal and six in the frontal lobe. Clusters were based on patterns of inputs from all cortical areas. Both parietal and frontal clusters were composed of sets of spatially contiguous architectonic areas. The four parietal clusters were composed of sets of anterior (somatosensory), dorsal, inferior, and medio-lateral parietal cortical areas. The six frontal clusters were composed of sets of dorsal premotor, ventral premotor, primary motor, cingulate motor, and dorsal and ventral prefrontal cortical areas. Furthermore, connectivity between frontal and parietal clusters was topographic and reciprocal. Thus we found substantial statistical structure and organization in the parieto-frontal network that gives a simplified but accurate description of this system.

Impairment of Online Control of Hand and Eye Movements in a Monkey Model of Optic Ataxia

The parietal mechanisms for online control of hand trajectory were studied by combining single-cell recording and reversible inactivation of superior parietal area 5 (PE/PEc; SPL) of monkeys while these made reaches and saccades to visual targets, when the target position changed unexpectedly. Neural activity was modulated by hand position, speed, and movement direction, and by pre- and/or postsaccadic signals. After bilateral muscimol injection, an increase in the hand reaction- and movement-time toward both the first and second targets was observed. This caused an increase in the time necessary for the trajectory correction, and therefore an elongation of the hand-path toward the first target location. Furthermore, hand trajectories were different in shape than control ones. An elongation of the eye reaction time to both first and second targets was also observed, which could partially explain the deficit of planning and correction of hand movement. These results identify the superior parietal lobule as a crucial node in the online control of hand and eye movement and highlight the role of the eye impairment in the emergence of the reaching disorder so far regarded as the hallmark of optic ataxia.

Organization and evolution of parieto-frontal processing streams in macaque monkeys and humans

The functional organization of the parieto-frontal system is crucial for understanding cognitive-motor behavior and provides the basis for interpreting the consequences of parietal lesions in humans from a neurobiological perspective. The parieto-frontal connectivity defines some main information streams that, rather than being devoted to restricted functions, underlie a rich behavioral repertoire. Surprisingly, from macaque to humans, evolution has added only a few, new functional streams, increasing however their complexity and encoding power. In fact, the characterization of the conduction times of parietal and frontal areas to different target structures has recently opened a new window on cortical dynamics, suggesting that evolution has amplified the probability of dynamic interactions between the nodes of the network, thanks to communication patterns based on temporally-dispersed conduction delays. This might allow the representation of sensory-motor signals within multiple neural assemblies and reference frames, as to optimize sensory-motor remapping within an action space characterized by different and more complex demands across evolution.