Scott T. Grafton

Automated Image Registration: I. General Methods and Intrasubject, Intramodality Validation

PURPOSE We sought to describe and validate an automated image registration method (AIR 3.0) based on matching of voxel intensities. METHOD Different cost functions, different minimization methods, and various sampling, smoothing, and editing strategies were compared. Internal consistency measures were used to place limits on registration accuracy for MRI data, and absolute accuracy was measured using a brain phantom for PET data. RESULTS All strategies were consistent with subvoxel accuracy for intrasubject, intramodality registration. Estimated accuracy of registration of structural MRI images was in the 75 to 150 microns range. Sparse data sampling strategies reduced registration times to minutes with only modest loss of accuracy. CONCLUSION The registration algorithm described is a robust and flexible tool that can be used to address a variety of image registration problems. Registration strategies can be tailored to meet different needs by optimizing tradeoffs between speed and accuracy.

Automated image registration : II. Intersubject validation of Linear and nonlinear models

PURPOSE Our goal was to validate linear and nonlinear intersubject image registration using an automated method (AIR 3.0) based on voxel intensity. METHOD PET and MRI data from 22 normal subjects were registered to corresponding averaged PET or MRI brain atlases using several specific linear and nonlinear spatial transformation models with an automated algorithm. Validation was based on anatomically defined landmarks. RESULTS Automated registration produced results that were superior to a manual nine parameter variant of the Talairach registration method. Increasing the degrees of freedom in the spatial transformation model improved the accuracy of automated intersubject registration. CONCLUSION Linear or nonlinear automated intersubject registration based on voxel intensities is computationally practical and produces more accurate alignment of homologous landmarks than manual nine parameter Talairach registration. Nonlinear models provide better registration than linear models but are slower.

Forward modeling allows feedback control for fast reaching movements

Delays in sensorimotor loops have led to the proposal that reaching movements are primarily under pre-programmed control and that sensory feedback loops exert an influence only at the very end of a trajectory. The present review challenges this view. Although behavioral data suggest that a motor plan is assembled prior to the onset of movement, more recent studies have indicated that this initial plan does not unfold unaltered, but is updated continuously by internal feedback loops. These loops rely on a forward model that integrates the sensory inflow and motor outflow to evaluate the consequence of the motor commands sent to a limb, such as the arm. In such a model, the probable position and velocity of an effector can be estimated with negligible delays and even predicted in advance, thus making feedback strategies possible for fast reaching movements. The parietal lobe and cerebellum appear to play a crucial role in this process. The ability of the motor system to estimate the future state of the limb might be an evolutionary substrate for mental operations that require an estimate of sequelae in the immediate future.

Amygdala activity related to enhanced memory for pleasant and aversive stimuli

Pleasant or aversive events are better remembered than neutral events. Emotional enhancement of episodic memory has been linked to the amygdala in animal and neuropsychological studies. Using positron emission tomography, we show that bilateral amygdala activity during memory encoding is correlated with enhanced episodic recognition memory for both pleasant and aversive visual stimuli relative to neutral stimuli, and that this relationship is specific to emotional stimuli. Furthermore, data suggest that the amygdala enhances episodic memory in part through modulation of hippocampal activity. The human amygdala seems to modulate the strength of conscious memory for events according to emotional importance, regardless of whether the emotion is pleasant or aversive.

Localization of grasp representations in humans by positron emission tomography

Positron emission tomography imaging of cerebral blood flow was used to localize brain areas involved in the representation of hand grasping movements. Seven normal subjects were scanned under three conditions. In the first, they observed precision grasping of common objects performed by the examiner. In the second, they imagined themselves grasping the objects without actually moving the hand. These two tasks were compared with a control task of object viewing. Grasp observation activated the left rostral superior temporal sulcus, left inferior frontal cortex (area 45), left rostral inferior parietal cortex (area 40), the rostral part of left supplementary motor area (SMA-proper), and the right dorsal premotor cortex. Imagined grasping activated the left inferior frontal (area 44) and middle frontal cortex, left caudal inferior parietal cortex (area 40), a more extensive response in left rostral SMA-proper, and left dorsal premotor cortex. The two conditions activated different areas of the right posterior cerebellar cortex. We propose that the areas active during grasping observation may form a circuit for recognition of hand-object interactions, whereas the areas active during imagined grasping may be a putative human homologue of a circuit for hand grasping movements recently defined in nonhuman primates. The location of responses in SMA-proper confirms the rostrocaudal segregation of this area for imagined and real movement. A similar segregation is also present in the cerebellum, with imagined and observed grasping movements activating different parts of the posterior lobe and real movements activating the anterior lobe.

Role of the posterior parietal cortex in updating reaching movements to a visual target

The exact role of posterior parietal cortex (PPC) in visually directed reaching is unknown. We propose that, by building an internal representation of instantaneous hand location, PPC computes a dynamic motor error used by motor centers to correct the ongoing trajectory. With unseen right hands, five subjects pointed to visual targets that either remained stationary or moved during saccadic eye movements. Transcranial magnetic stimulation (TMS) was applied over the left PPC during target presentation. Stimulation disrupted path corrections that normally occur in response to target jumps, but had no effect on those directed at stationary targets. Furthermore, left-hand movement corrections were not blocked, ruling out visual or oculomotor effects of stimulation.

Functional mapping of sequence learning in normal humans

The brain localization of motor sequence learning was studied in normal subjects with positron emission tomography. Subjects performed a serial reaction time (SRT) task by responding to a series of stimuli that occurred at four different spatial positions. The stimulus locations were either determined randomly or according to a 6-element sequence that cycled continuously. The SRT task was performed under two conditions. With attentional interference from a secondary counting task there was no development of awareness of the sequence. Learning-related increases of cerebral blood flow were located in contralateral motor effector areas including motor cortex, supplementary motor area, and putamen, consistent with the hypothesis that nondeclarative motor learning occurs in cerebral areas that control limb movements. Additional cortical sites included the rostral prefrontal cortex and parietal cortex. The SRT learning task was then repeated with a new sequence and no attentional interference. In this condition, 7 of 12 subjects developed awareness of the sequence. Learning-related blood flow increases were present in right dorsolateral prefrontal cortex, right premotor cortex, right ventral putamen, and biparieto-occipital cortex. The right dorsolateral prefrontal and parietal areas have been previously implicated in spatial working memory and right prefrontal cortex is also implicated in retrieval tasks of verbal episodic memory. Awareness of the sequence at the end of learning was associated with greater activity in bilateral parietal, superior temporal, and right premotor cortex. Motor learning can take place in different cerebral areas, contingent on the attentional demands of the task.

Dynamic reconfiguration of human brain networks during learning

Human learning is a complex phenomenon requiring flexibility to adapt existing brain function and precision in selecting new neurophysiological activities to drive desired behavior. These two attributes—flexibility and selection—must operate over multiple temporal scales as performance of a skill changes from being slow and challenging to being fast and automatic. Such selective adaptability is naturally provided by modular structure, which plays a critical role in evolution, development, and optimal network function. Using functional connectivity measurements of brain activity acquired from initial training through mastery of a simple motor skill, we investigate the role of modularity in human learning by identifying dynamic changes of modular organization spanning multiple temporal scales. Our results indicate that flexibility, which we measure by the allegiance of nodes to modules, in one experimental session predicts the relative amount of learning in a future session. We also develop a general statistical framework for the identification of modular architectures in evolving systems, which is broadly applicable to disciplines where network adaptability is crucial to the understanding of system performance.

Premotor Cortex Activation during Observation and Naming of Familiar Tools

Positron emission tomography was used to investigate whether observation of real objects (tools of common use) activates premotor areas in the absence of any overt motor demand. Silent naming of the presented tools and silent naming of their use were also studied. Right-handed normal subjects were employed. Tool observation strongly activated the left dorsal premotor cortex. In contrast, silent tool naming activated Brocas area without additional activity in the dorsal premotor cortex. Silent tool-use naming, in addition to activating Brocas area, increased the activity in the left dorsal premotor cortex and recruited the left ventral premotor cortex and the left supplementary motor area. These data indicate that, even in the absence of any subsequent movement, the left premotor cortex processes objects that, like tools, have a motor valence. This dorsal premotor activation, which further augments when the subject names the tool use, should reflect the neural activity related to motor schemata for object use. The presence of an activation of both dorsal premotor cortex and ventral premotor cortex during tool-use naming suggests a role for these two areas in understanding object semantics.

Functional imaging of face and hand imitation: towards a motor theory of empathy

Empathy requires the ability to map the feelings of others onto our own nervous system. Until recently, there was no plausible mechanism to explain how such a mapping might occur. The discovery of mirror neurons, however, suggests that the nervous system is capable of mapping the observed actions of others onto the premotor cortex of the self, at least for reaching and grasping movements. Is there a mirroring system for emotive actions, such as facial expression? Subjects (N = 15; all right-handed; eight men, seven women) watched movies of facial expressions (smile or frown) and hand movements (move index or middle finger) while brain activity was imaged using functional magnetic resonance imaging (fMRI). Subjects watched the movies under three different conditions: passive viewing, active imitation, and an active motor control. Subjects also performed a verb generation task to functionally identify language-processing areas. We found evidence for a common cortical imitation circuit for both face and hand imitation, consisting of Brocas area, bilateral dorsal and ventral premotor areas, right superior temporal gyrus (STG), supplementary motor area, posterior temporo-occipital cortex, and cerebellar areas. For faces, passive viewing led to significant activation in the right ventral premotor area, whereas imitation produced bilateral activation. This result is consistent with evidence for right hemisphere (RH) dominance for emotional processing, and suggests that there may be a right hemisphere mirroring system that could provide a neural substrate for empathy.