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Studies with experimental animals have revealed a mood-regulating neural pathway linking intrinsically photosensitive retinal ganglion cells (ipRGCs) and the prefrontal cortex (PFC), involved in the pathophysiology of mood disorders. Since humans also have light-intensity–encoding ipRGCs, we asked whether a similar pathway exists in humans. Here, functional MRI was used to identify PFC regions and other areas exhibiting light-intensity–dependent signals. We report 26 human brain regions having activation that either monotonically decreases or monotonically increases with light intensity. Luxotonic-related activation occurred across the cerebral cortex, in diverse subcortical structures, and in the cerebellum, encompassing regions with functions related to visual image formation, motor control, cognition, and emotion. Light suppressed PFC activation, which monotonically decreased with increasing light intensity. The sustained time course of light-evoked PFC responses and their susceptibility to prior light exposure resembled those of ipRGCs. These findings offer a functional link between light exposure and PFC-mediated cognitive and affective phenomena.

The Center of Biomedical Research Excellence (COBRE) Center for Central Nervous System Function (CCNSF) was funded in 2013 by the National Institute for General Medical Sciences to establish a collaborative environment for basic and applied research in higher nervous system function with humans and experimental animal model systems. Since its inception, the COBRE CCNSF has funded junior faculty investigators as Project and Pilot Project Leaders and one established investigator on projects investigating fundamental properties of nervous system function using a range of tools spanning molecular genetics, neurophysiology, invasive and non-invasive brain stimulation, behavior and neuroimaging. The Administrative Core facilitates all Center activities with a focus on career development, grant proposal submission, and deployment of technology developed by our research cores. The Design and Analysis Core aims to provide principled study design expertise, statistical modeling, machine learning, inference, and computation. The Behavior and Neuroimaging Core provides project-specific collaboration and support to COBRE scientists to promote the acquisition of high quality behavioral, physiological, neuroimaging and neurostimulation data, to ensure the integrity of the data collection infrastructure and to help implement robust data processing and visualization pipelines. While the cores principally serve Center scientists, our Center and the core resources have availability to all Rhode Island researchers.

Light impacts mood and cognition of humans and other animals in ways we are only beginning to recognize. These effects are thought to depend upon a specialized retinal output signal arising from intrinsically photosensitive retinal ganglion cells (ipRGCs) that is being dedicated to a stable representation of the intensity of environmental light. Insights from animal studies now implicate a previously unknown pathway in the effects of environmental light on mood. A subset of ipRGCs transmits light-intensity information to the dorsothalamic perihabenular nucleus, which in turn, innervates the medial prefrontal cortex that plays a key role in mood regulation. While the prefrontal cortex has been implicated in depression and other mood disorders, its ability to encode the level of environmental light (luminance) has never been reported. Here, as a first step to probing for a similar retino-thalamo-frontocortical circuit in humans, we used functional magnetic resonance imaging (fMRI) to identify brain regions in which activity depended on luminance level where activity was modulated either transiently or persistently by light. Twelve brain regions altered their steady-state activity according to luminance level. Most were in the prefrontal cortex or in the classic thalamocortical visual pathway; others were found in the cerebellum, caudate, and pineal. Prefrontal cortex and pineal exhibited reduced BOLD signal in bright light, while the other centers exhibited increased BOLD signals. The light-evoked prefrontal response was affected by light history and closely resembled those of ipRGCs. Although we did not find clear correspondence between the luxotonic regions in humans and those in mice, the persistence and luxotonic nature of light-evoked responses in the human prefrontal cortex may suggest that it receives input from ipRGCs, just like in the mouse. We also found seventeen regions in which activity varied only transiently with luminance level. These regions, which are involved in visual processing, motor control, and cognition, were in the cerebral cortex, diverse subcortical structures, and cerebellum. Therefore, our results demonstrate the effects of light on diverse brain centers that contribute to motor control, cognition, emotion, and reward processing.

Humans readily learn and remember new motor skills, a process that likely underlies adaptation to changing environments. During adaptation, the brain develops new sensory-motor relationships, and if consolidation occurs, a memory of the adaptation can be retained for extended periods. Considerable evidence exists that multiple brain circuits participate in acquiring new sensory-motor memories, though the networks engaged in recalling these and whether the same brain circuits participate in their formation and recall have less clarity. To address these issues, we assessed brain activation with functional MRI while young healthy adults learned and recalled new sensory-motor skills by adapting to world-view rotations of visual feedback that guided hand movements. We found cerebellar activation related to adaptation rate, likely reflecting changes related to overall adjustments to the visual rotation. A set of parietal and frontal regions, including inferior and superior parietal lobules, premotor area, supplementary motor area and primary somatosensory cortex, exhibited non-linear learning-related activation that peaked in the middle of the adaptation phase. Activation in some of these areas, including the inferior parietal lobule, intra-parietal sulcus and somatosensory cortex, likely reflected actual learning, since the activation correlated with learning after-effects. Lastly, we identified several structures having recall-related activation, including the anterior cingulate and the posterior putamen, since the activation correlated with recall efficacy. These findings demonstrate dynamic aspects of brain activation patterns related to formation and recall of a sensory-motor skill, such that non-overlapping brain regions participate in distinctive behavioral events.

Multiple brain regions participate in acquisition, retention, and expression of motor skills. These motor skills include simple practice, sensory–motor adaptations, movement sequences, and arbitrary sensory–motor associations. Similar to other skills, such as learning word lists, processes related to motor learning evolve in time and involve multiple structures across neocortex and related subcortical structures. Modification of neural properties, synchrony, and synaptic efficacy each has an impact on development and maintenance of motor skills.

We develop a statistical method for discriminating and classifying multivariate non- stationary signals. It is assumed that the processes that generate the signals are characterized by their time-evolving spectral matrix—a description of the dynamic connectivity between the time series components. Here, we address two major challenges: first, data massiveness and second, the poor conditioning that leads to numerically unstable estimates of the spectral matrix. We use the SLEX library (a collection of bases functions consisting of localized Fourier waveforms) to extract the set of time–frequency features that best separate classes of time series. The SLEX approach yields readily interpretable results since it is a time-dependent analogue of the Fourier approach to stationary time series. Moreover, it uses computationally efficient algorithms to enable handling of large data sets. We estimate the SLEX spectral matrix by shrinking the initial SLEX periodogram matrix estimator towards the identity matrix. The resulting shrinkage estimator has lower mean-squared error than the classical smoothed periodogram matrix and is more regular. A leave-one out analysis for predicting motor intent (left vs. right movement) using electroencephalograms indicates that the proposed SLEX-shrinkage method gives robust estimates of the evolutionary spectral matrix and good classification results.

Humans reach to and acquire objects by transforming visual targets into action commands. How the brain integrates goals specified in a visual framework to signals into a suitable framework for an action plan requires clarification whether visual input, per se, interacts with gaze position to formulate action plans. To further evaluate brain control of visual--motor integration, we assessed brain activation, using functional magnetic resonance imaging. Humans performed goal-directed movements toward visible or remembered targets while fixating gaze left or right from center. We dissociated movement planning from performance using a delayed-response task and manipulated target visibility by its availability throughout the delay or blanking it 500 ms after onset. We found strong effects of gaze orientation on brain activation during planning and interactive effects of target visibility and gaze orientation on movement-related activation during performance in parietal and premotor cortices (PM), cerebellum, and basal ganglia, with more activation for rightward gaze at a visible target and no gaze modulation for movements directed toward remembered targets. These results demonstrate effects of gaze position on PM and movement-related processes and provide new information how visual signals interact with gaze position in transforming visual inputs into motor goals.

We develop new statistical methods for estimating functional connectivity between components of a multivariate time series and for testing differences in functional connectivity across experimental conditions. Here, we characterize functional connectivity by partial coherence, which identifies the frequency band (or bands) that drives the direct linear association between any pair of components of a multivariate time series after removing the linear effects of the other components. Partial coherence can be efficiently estimated using the inverse of the spectral density matrix. However, when the number of components is large and the components of the multivariate time series are highly correlated, the spectral density matrix estimate may be numerically unstable and consequently gives partial coherence estimates that are highly variable. To address the problem of numerical instability, we propose a shrinkage-based estimator which is a weighted average of a smoothed periodogram estimator and a scaled identity matrix with frequency-specific weight computed objectively so that the resulting shrinkage estimator minimizes the mean-squared error criterion. Compared to typical smoothing-based estimators, the shrinkage estimator is more computationally stable and gives a lower mean squared error. In addition, we develop a randomization method for testing differences in functional connectivity networks between experimental conditions. Finally, we report results from numerical experiments and analyze an EEG data set recorded during a visually-guided hand movement task.

Humans commonly use their hands to move and to interact with their environment by processing visual and proprioceptive information to determine the location of a goal-object and the initial hand position. It remains elusive, however, how the human brain fully uses this sensory information to generate accurate movements. In monkeys, it appears that frontal and parietal areas use and combine gaze and hand signals to generate movements, whereas in humans, prior work has separately assessed how the brain uses these two signals. Here we investigated whether and how the human brain integrates gaze orientation and hand position during simple visually triggered finger tapping. We hypothesized that parietal, frontal, and subcortical regions involved in movement production would also exhibit modulation of movement-related activation as a function of gaze and hand positions. We used functional MRI to measure brain activation while healthy young adults performed a visually cued finger movement and fixed gaze at each of three locations and held the arm in two different configurations. We found several areas that exhibited activation related to a mixture of these hand and gaze positions; these included the sensory-motor cortex, supramarginal gyrus, superior parietal lobule, superior frontal gyrus, anterior cingulate, and left cerebellum. We also found regions within the left insula, left cuneus, left midcingulate gyrus, left putamen, and right tempo-occipital junction with activation driven only by gaze orientation. Finally, clusters with hand position effects were found in the cerebellum bilaterally. Our results indicate that these areas integrate at least two signals to perform visual-motor actions and that these could be used to subserve sensory-motor transformations.

This study investigated the potential long-term effects of cocaine exposure on brain functioning using fMRI in school-aged children. The sample included 12 children with prenatal cocaine exposure and 12 non-exposed children (8–9 years old). Groups did not differ on IQ, socioeconomic status, or perinatal risk factors. A response inhibition task was administered during an fMRI scan using a 1.5-T MRI system. Task performance did not differentiate groups, but groups were differentiated by patterns of task-related brain activity. Cocaine-exposed children showed greater activation in the right inferior frontal cortex and caudate during response inhibition, whereas non-exposed children showed greater activations in temporal and occipital regions. These preliminary findings suggest that prenatal cocaine may affect the development of brain systems involved in the regulation of attention and response inhibition.

Control of familiar visually guided movements involves internal plans as well as visual and other online sensory information, though how visual and internal plans combine for reaching movements remain unclear. Traditional motor sequence learning tasks, such as the serial reaction time task, use stereotyped movements and measure only reaction time. Here, we used a continuous sequential reaching task comprised of naturalistic movements, in order to provide detailed kinematic performance measures. When we embedded pre-learned trajectories (those presumably having an internal plan) within similar but unpredictable movement sequences, participants performed the two kinds of movements with remarkable similarity, and position error alone could not reliably identify the epoch. For such embedded movements, performance during pre-learned sequences showed statistically significant but trivial decreases in measures of kinematic error, compared to performance during novel sequences. However, different sets of kinematic error variables changed significantly between learned and novel sequences for individual participants, suggesting that each participant used distinct motor strategies favoring different kinematic variables during each of the two movement types. Algorithms that incorporated multiple kinematic variables identified transitions between the two movement types well but imperfectly. Hidden Markov model classification differentiated learned and novel movements on single trials based on the above kinematic error variables with 82 +/- 5% accuracy within 244 +/- 696 ms, despite the limited extent of changes in those errors. These results suggest that the motor system can achieve markedly similar performance whether or not an internal plan is present, as only subtle changes arise from any difference between the neural substrates involved in those two conditions.

We used a delayed response paradigm to test the hypothesis that the prolonged reaction time in patients with Parkinson's disease (PD) is related to a deficiency in their ability to store a motor program in memory while waiting to move. PD patients, both on and off medication, were compared with age-matched normal subjects during arm movements directed toward a target light. The target light was displayed either during a 3- to 9-s delay or for only 1 s followed by a 2- to 8-s delay before the go signal. At the end of the delay, subjects were required to begin movement rapidly. The reaction time of PD patients was longer than normal and increased slightly when the patients were off medication. The patients had no excessive increase in reaction time with delay in either task compared with the control subjects. We conclude that patients with PD can hold a motor program in memory storage for at least 8 s.

The ability to learn novel motor skills has fundamental importance for adaptive behavior. Neocortical mechanisms support human motor skill learning, from simple practice to adaptation and arbitrary sensory-motor associations. Behavioral and neural manifestations of motor learning evolve in time and involve multiple structures across the neocortex. Modifications of neural properties, synchrony and synaptic efficacy are all related to the development and maintenance of motor skill.

Cortical areas engaged in knowledge manipulation during reasoning were identified with functional magnetic resonance imaging (MRI) while participants performed transitive inference (TI) on an ordered list of 11 items (e.g. if A < B and B < C, then A < C). Initially, participants learned a list of arbitrarily ordered visual shapes. Learning occurred by exposure to pairs of list items that were adjacent in the sequence. Subsequently, functional MR images were acquired as participants performed TI on non-adjacent sequence items. Control tasks consisted of height comparisons (HT) and passive viewing (VIS). Comparison of the TI task with the HT task identified activation resulting from TI, termed 'reasoning', while controlling for rule application, decision processes, perception, and movement, collectively termed 'support processes'. The HT-VIS comparison revealed activation related to support processes. The TI reasoning network included bilateral prefrontal cortex (PFC), pre-supplementary motor area (preSMA), premotor area (PMA), insula, precuneus, and lateral posterior parietal cortex. By contrast, cortical regions activated by support processes included the bilateral supplementary motor area (SMA), primary motor cortex (M1), somatic sensory cortices, and right PMA. These results emphasize the role of a prefrontal-parietal network in manipulating information to form new knowledge based on familiar facts. The findings also demonstrate PFC activation beyond short-term memory to include mental operations associated with reasoning.

We examined how the brain organizes interrelated facts during learning and how the facts are subsequently manipulated in a transitive inference (TI) paradigm (e.g., if A

We examined brain activation patterns occurring during the production and encoding of a motor sequence. Participants performed a variant of the serial reaction-time task under two conditions. The first condition was designed to foster the engagement of explicit mechanisms of knowledge acquisition. The second condition was intended to encourage the engagement of implicit learning mechanisms that would be more typical of the standard serial reaction-time task. In the first condition, the acquisition of explicit knowledge about an 8-element ordered sequence led to a significant and rapid decline in reaction time. By contrast, the second condition, the task in which a sequence was presented unbeknownst to participants, did not yield changes in reaction time. Several brain regions, including prefrontal cortex, superior and inferior parietal lobules, and cerebellum, exhibited explicit learning-related activation. The prefrontal cortex and inferior parietal lobules increased their levels of activation between the beginning and end of the experiment, while primary motor, primary sensory, and cerebellar cortex decreased their levels of activation from the beginning to the end of the experiment. We propose a model in which two processes, a learning-related increase and a habituation process might interact to produce the activation patterns observed during movement sequence acquisition. In short, the prefrontal cortex and inferior parietal lobule together direct and recruit superior parietal lobule and cerebellum to encode and perform the sequence. The increased activation in prefrontal cortex and inferior parietal lobule may represent the activity of a working memory circuit that functions in the acquisition and recall of sequence information.

Selecting an optimal event distribution for experimental use in event-related fMRI studies can require the generation of large numbers of event sequences with characteristics hard to control. The use of known probability distributions offers the possibility to control event timing and constrain the search space for finding optimal event sequences. We investigated different probability distributions in terms of response estimation (estimation efficiency), detectability (detection power, parameter estimation efficiency, sensitivity to true positives), and false-positive activation. Numerous simulated event sequences were generated selecting interevent intervals (IEI) from the uniform, uniform permuted, Latin square, exponential, binomial, Poisson, chi(2), geometric, and bimodal probability distributions and fixed IEI. Event sequences from the bimodal distribution, like block designs, had the best performance for detection and the poorest for estimation, while high estimation and detectability occurred for the long-decay exponential distribution. The uniform distribution also yielded high estimation efficiency, but probability functions with a long tail toward higher IEI, such as the geometric and the chi(2) distributions, had superior detectability. The distributions with the best detection performance also had a relatively high incidence of false positives, in contrast to the ordered distributions (Latin square and uniform permuted). The predictions of improved sensitivities for distributions with long tails were confirmed with empirical data. Moreover, the Latin square design yielded detection of activated voxels similar to the chi(2) distribution. These results indicate that high detection and suitable behavioral designs have compatibility for application of functional MRI methods to experiments requiring complex designs.

Sensory and motor systems interact in complex ways; visual attention modifies behavior, neural encoding, and brain activation; and dividing attention with simultaneous tasks may impede performance while producing specific brain activation patterns. We hypothesized that combining voluntary movement with visual attention would yield unique brain representations differing from those occurring for movement or visual attention alone. Hemodynamic signals in humans were obtained with functional magnetic resonance imaging (MRI) while participants performed one of four tasks that required only a repetitive finger movement, only attending to the color of a visual stimulus, simultaneous finger movement and visual attention, or no movement and no visual attention. The movement-alone task yielded brain activation in structures commonly engaged during voluntary movement, including the primary motor cortex, supplementary motor area, and cerebellum. Visual attention alone resulted in sparse cerebral cortical and substantial bilateral cerebellar activation. Simultaneous performance of visual attention and finger movements yielded widespread cerebral cortical, cerebellar, and other subcortical activation, in many of the same sites activated for the movement or attention tasks. However, the movement-related plus attention-related activation extended beyond the movement-alone or attention-alone activation sites, indicating a novel activation pattern related to the combined performance of attention and movement. Additionally, the conjoint effects of visual attention and movement upon brain activation were probably not simple gain effects, since we found activation-related interactions in the left superior parietal lobule, the right fusiform gyrus, and left insula, indicating a potent combinatory role for visual attention and movement for activation patterns in the human brain. In conclusion, performing visual attention and movement tasks simultaneously, even though the tasks had no specific interrelationship, resulted in novel activation patterns not predicted by performing movements or visual attention alone.

Because sensory systems use different spatial coordinate frames, cross-modal sensory integration and sensory‐motor coordinate transformations must occur to build integrated spatial representations. Multimodal neurons using non-retinal body-centred reference frames are found in the posterior parietal and frontal cortices of monkeys. We used functional magnetic resonance imaging to reveal regions of the human brain using body-centred coordinates to code the spatial position of both visual and somatic sensory stimuli. Participants determined whether a visible vertical bar (visual modality) or a location touched by the right index finger (somatic sensory modality) lay to the left or to the right of their body mid-sagittal plane. This task was compared to a spatial control task having the same stimuli and motor responses and comparable difficulty, but not requiring body-centred coding of stimulus position. In both sensory modalities, the body-centred coding task activated a bilateral fronto-parietal network, though more extensively in the right hemisphere, to include posterior parietal regions around the intraparietal sulcus and frontal regions around the precentral and superior frontal sulci, the inferior frontal gyrus and the superior frontal gyrus on the medial wall. The occipito-temporal junction and other extrastriate regions exhibited bilateral activation enhancement related to body-centred coding when driven by visual stimuli. We conclude that posterior parietal and frontal regions of humans, as in monkeys, appear to provide multimodal integrated spatial representations in body-centred coordinates, and these data furnish the first indication of such processing networks in the human brain.

We used functional magnetic resonance imaging to examine the representation pattern for repetitive voluntary finger movements in the primary motor cortex (M1) and the supplementary motor area (SMA) of humans. Healthy right-handed participants performed repetitive individuated flexion-extension movements of digits 1, 2, and 3 using the dominant hand. Contralateral functional labeling for the group indicated a largely overlapping activation pattern in M1 and SMA for the three digits. Consistent with recent findings, the geographic activation center in M1 for each finger differed, and we found some evidence of a homunculus organization pattern in M1 and SMA, but only for the central location of the representations. However, the statistical power for the homunculus pattern was weak, and the distance separating the digit geographical centers was typically less than 15% of the entire extent of digit representations in M1 or SMA. While separations for digit representations occurred, the entire data set provided more support for the concept of distributed, overlapping representations than for a classic homunculus organization for voluntary finger movements.

In the current issue of NeuroImage and an upcoming issue of Cerebral Cortex appear data relevant to a fundamental question about the functional organization of the primary motor cortex (M1) of primates (Beisteiner et al., 2001; Hlustik et al., 2001; Indovina and Sanes, 2001), that is, does there exist an orderly somatotopy in M1 and, by extension, in other major motor areas of the brain. A fundamental finding of these papers provides support for separation between representations for finger and hand movement that adheres to a somatotopic organization. The new findings extend previous reports of somatotopically ordered representations for voluntary movements of various joints of the human upper extremity, fingers, wrist, elbow, and shoulder (Grafton et al., 1993; Kleinchmidt et al., 1997; Lotze et al., 2000), but conflict with thers (Rao et al., 1995; Sanes et al., 1995). However, as others and we have noted, the degree of somatotopic representation within the upper extremity representation appears rather limited (Schieber, 1999; Sanes and Donoghue, 2000). Clearly the major body parts—lower limb (hindlimb), upper limb (forelimb), and head—have functional and largely independent subdivisions to represent the muscles and movements controlled by the respective parts of M1. These functional subdivisions of M1 are commonly laid out along the cortical surface of primates with the lower (hind) limb most medial, the head most lateral, and the upper (fore) limb in between; they have acquired the designation of “areas,” such as the “M1 arm area,” though the term “representation” might provide a more suitable functional name. No serious challenge has emerged for this basic large-scale organization pattern in M1, but

We investigated whether gaze direction modified the pattern of finger movement activation in human cerebral cortex using functional magnetic resonance imaging (MRI). Participants performed a sequential finger-tapping task or made no finger movements while maintaining gaze in the direction of the moving hand (aligned conditions) or away from the location of the moving hand. Functional MR signals, measured in the hemisphere contralateral to the moving hand, revealed finger movement-related activation in primary motor cortex, lateral and medial premotor cortex, and a wide extent of the lateral superior and inferior parietal lobules. In each area, the extent of the finger movement activation increased when static gaze was more aligned with the moving hand compared to when gaze was directed away from the moving hand. These data suggest the existence of large-scale cortical networks related to finger actions and indicate that skeletomotor processing in the cerebral cortex is consistently modified by gaze direction signals.

Visually guided, goal-directed reaching requires encoding action distance and direction from attributes of visual landmarks. We identified a cognitive mechanism that seemingly performs visual motor extension before action initiation and replicated and extended previous results that identified a mechanism for visual motor mental rotation. We find that humans systematically delay action onset while newly planning increasingly distant arm movements beyond a visual landmark, consistent with an internal representation for visual motor extension. Onset times also changed systematically during concurrent mental rotation and visual motor extension computations required to process new directions and distances. Visual motor extension associated with reaching slowed when participants needed to plan action direction within the same time frame, whereas mental rotation efficiency was unaffected by concurrent needs to prepare action distance. In contrast to parallel direction and distance computations needed for direct aiming to a visual target, the planning of new directions and distances likely occurs at distinct times. When considered with previous findings, the current results suggest the existence of an intermediate component of motor preparation that engages a covert mechanism of cognitive motor planning.

Motor cortical organization has commonly been conceived as somatotopically ordered, with single body parts controlled from individual patches of cortical tissue. An opposing viewpoint suggests that motor cortex has a distnbuted, adaptive, and dynamic organi zation that underlies movement planning, performance, adaptation, and learning. Con verging evidence from anatomic, neurophysiologic, and functional neuroimaging sources indicates that the arm area of motor cortical areas in monkeys and humans has multiple, interconnected sites that ostensibly contribute to controlling various parts of the arm. These representations can exhibit rapid and sometimes enduring modifications following injury, changes in somatic sensory input, and motor learning. Activity-dependent changes in the intrinsic motor cortical network of horizontal and vertical connections coupled with ascending thalamic and corticocortical inputs could provide a substrate for dynamic mod ulation of motor cortex functional representations. NEUROSCIENTIST 3:158-165, 1997

The motor performance of patients with Parkinson's disease is degraded, but it is unclear whether their motor learning (adaptation learning and skill learning) ability is impaired. To assess the ability of these patients to learn motor tasks, we studied nine Parkinson's disease patients and eight age-matched normal (control) subjects who repetitively traced, as rapidly and accurately as possible, irregular geometric patterns with normal and mirror-reversed vision. The outcome was measured by statistical analysis and graphic plotting of values for actual and standardized performance variables and correlation of data from initial and final performance variables with indicators of disease severity. The results showed that, with normal vision, total movement time was reduced in both patients and normal subjects, but movement errors increased with repetition, apparently reflecting a speed-accuracy trade-off and adaptation learning. With mirror-reversed vision, total movement time and movement errors were reduced equally with repetition in both groups. These concomitant improvements in time and accuracy violate the rule of speed-accuracy trade-off and suggest that this behavior reflects true motor skill learning. We conclude that patients with Parkinson's disease do not differ from normal subjects in the processes of motor adaptation and motor skill learning.

Posteroventral pallidotomy as a treatment for Parkinson's disease (PD) has been the subject of increasing interest. We treated 4 nondemented patients with advanced PD, 2 with severe bradykinesia and a declining response to medication, and 2 with marked clinical fluctuations. All patients received 180 Gy delivered in one sitting to the right posteroventral pallidum site, used by Laitinen and colleagues, adjusted as needed, to avoid the optic tract. Only 1 patient changed significantly. Dyskinesia completely resolved on the side contralateral to the lesion in this patient. This same patient also became transiently demented and psychotic. The other 3 patients suffered no clearly identifiable beneficial or harmful effects. Follow-up magnetic resonance imaging scans of the brain at 1 year revealed lesions exactly where targeted although of unequal sizes. Our negative experience forces us to conclude that either larger volumes of tissue must be ablated, that physiologic monitoring is required for placing a lesion, that our subjects were poor candidates for the procedure, or that surgical ablation and radiation cause tissue damage of different types with different results.

An important aspect in brain activation studies is the relationship between neuronal activity and measurable indices of function. We applied functional magnetic resonance imaging (fMRI) to investigate blood flow-related MR signal changes in response to different rates of repetitive movements of the index finger. The contralateral precentral gyrus and the posterior frontomesial cortex revealed a significant increase in MR signal over baseline for 1, 2 and 3 Hz finger movements, with a linear effect of rate in the precentral gyrus. Increased firing of neuronal aggregates or recruitment of additional neuronal units within the primary motor cortex necessary for increased output to target neurons and maintaining posture of nearby distal and proximal joints may contribute to the activation pattern.

We propose a mixed-effects vector auto-regressive (ME-VAR) model for studying brain effective connectivity. One common approach to investigating inter-regional associations in brain activity is the multivariate auto-regressive (VAR) model. The standard VAR model unrealistically assumes the connectivity structure to be identical across all participants in a study and therefore, could yield misleading results. The ME-VAR model overcomes this limitation by incorporating a participant-specific connectivity structure. In addition, the ME-VAR models can capture connectivity differences across experimental conditions and patient groups. The ME-VAR model directly decomposes the connectivity matrices into (i.) the condition-specific connectivity matrix, which is shared by all participants in the study (fixed effect) and (ii.) a participant-specific component (random effect) which accounts for between-subject variation in connectivity. An advantage of our approach is that it permits the use of both theoretical results on mixed effects models and existing statistical software when fitting the model. Another advantage of the proposed approach is that it provides improved estimates of the within-subject coefficients (the random effects) by pooling information across subjects in a single-stage rather than the usual two-stage approach. We illustrate the ME-VAR model on a functional MRI data set obtained to investigate brain connectivity in the prefrontal, pre-motor and parietal cortices while humans performed a motor-related, decision-making and action selection task.

Humans learn and remember motor skills to permit adaptation to a changing environment. During adaptation, the brain develops new sensory–motor relationships that become stored in an internal model (IM) that may be retained for extended periods. How the brain learns new IMs and transforms them into long-term memory remains incompletely understood since prior work has mostly focused on the learning process. A current model suggests that basal ganglia, cerebellum, and their neocortical targets actively participate in forming new IMs but that a cerebellar cortical network would mediate automatization. However, a recent study (Marinelli et al. 2009) reported that patients with Parkinson’s disease (PD), who have basal ganglia dysfunction, had similar adaptation rates as controls but demonstrated no savings at recall tests (24 and 48 h). Here, we assessed whether a longer training session, a feature known to increase long-term retention of IM in healthy individuals, could allow PD patients to demonstrate savings. We recruited PD patients and age-matched healthy adults and used a visual-motor adaptation paradigm similar to the study by Marinelli et al. (2009), doubling the number of training trials and assessed recall after a short and a 24-h delay. We hypothesized that a longer training session would allow PD patients to develop an enhanced representation of the IM as demonstrated by savings at the recall tests. Our results showed that PD patients had similar adaptation rates as controls but did not demonstrate savings at both recall tests. We interpret these results as evidence that fronto-striatal networks have involvement in the early to late phase of motor memory formation, but not during initial learning.

Primary motor cortex has a complex, interconnected anatomical and functional architecture with dynamic properties. Recent evidence suggests that, concomitantly with regulating muscle activity and movements, the motor cortex makes key contributions to learning and remembering motor skills.

Fronto-striatal circuitry interacts with the midbrain dopaminergic system to mediate the learning of stimulus-response associations, and these associations often guide everyday actions, but the precise role of these circuits in forming and consolidating rules remains uncertain. A means to examine basal ganglia circuit contributions to associative motor learning is to examine these process in a lesion model system, such as Parkinson's disease (PD), a basal ganglia disorder characterized by the loss of dopamine neurons. We used functional magnetic resonance imaging (MRI) to compare brain activation of PD patients with a group of healthy aged-match participants during a visual-motor associative learning task that entailed discovering and learning arbitrary associations between a set of six visual stimuli and corresponding spatial locations by moving a joystick-controlled cursor. We tested the hypothesis that PD would recruit more areas than age-matched controls during learning and also show increased activation in commonly activated regions, probably in the parietal and premotor cortices, and the cerebellum, perhaps as compensatory mechanisms for their disrupted fronto-striatal networks. PD had no effect in acquiring the associative relationships and learning-related activation in several key frontal cortical and subcortical structures. However, we found that PD modified activation in other areas, including those in the cerebellum and frontal, and parietal cortex, particularly during initial learning. These results may suggest that the basal ganglia circuits become active more so during the initial formation of rule-based behavior.

The effect of circulating levels of plasma levodopa on reaction time performance was studied in patients with Parkinson's disease and untreated normal controls when instructed to move either a shorter or longer distance. On half the movements, subjects were pre-cued on the direction and amplitude of an impending movement. On the remaining movements, only the direction was pre-specified, and the amplitude was determined only when the cue to move was presented. Reaction time performance of patients was evaluated at three infusion levels of levodopa so that the patients were optimally, moderately, or minimally medicated. Parkinsonian patients were always slower to react and move than normal subjects. Clinical state correlated with movement time, but not with reaction time. These results contrast with those in which reaction time was related to plasma levodopa levels when movement direction and initiation were processed concomitantly, but the movement amplitude was pre-cued. It is possible that specification of the amount of muscle activity is partially independent of dopaminergic transmission.

This study examined whether cerebellar dysfunction resulted in deficiencies of motor learning. Patients with cerebellar atrophy only or cerebellar atrophy combined with atrophy of the brainstem and age-matched normal subjects performed two tasks to assess improvements in skilled performance. The first task was repetitive tracing with the hand of an irregular geometric pattern with normal visual guidance, and the second task was repetitive tracing of a different geometric pattern with mirror-reversed vision. Patients with pathology limited to the cerebellum showed impairments in the skilled performance of the movement performed with normal vision that may have been related to a failure to alter movement strategy. Patients with added pathology in the brainstem exhibited impairments in adapting to mirror-reversed vision. Subsidiary experiments indicated that improvements of movements guided by mirror-reversed vision were mediated by vision. These results indicate that the cerebellum and its associated input pathways are involved in motor skill learning.

The brain uses gaze orientation to organize myriad spatial tasks including hand movements. However, the neural correlates of gaze signals and their interaction with brain systems for arm movement control remain unresolved. Many studies have shown that gaze orientation modifies neuronal spike discharge in monkeys and activation in humans related to reaching and finger movements in parietal and frontal areas. To continue earlier studies that addressed interaction of horizontal gaze and hand movements in humans (Baker et al. 1999), we assessed how horizontal and vertical gaze deviations modified finger-related activation, hypothesizing that areas throughout the brain would exhibit movement-related activation that depended on gaze angle. The results indicated finger movement-related activation related to combinations of horizontal, vertical, and diagonal gaze deviations. We extended our prior findings to observation of these gaze-dependent effects in visual cortex, parietal cortex, motor, supplementary motor area, putamen, and cerebellum. Most significantly, we found a modulation bias for increased activation toward rightward, upper-right and vertically upward gaze deviations. Our results indicate that gaze modulation of finger movement-related regions in the human brain is spatially organized and could subserve sensorimotor transformations.

Main Outcome Measure(s): Main outcome measures: The Extended CaSUN-NL (entailing the original 35 items plus items related to work (5 items) and lifestyle (4 items), MAC, HADS, QLQ-C30. Results: Respondents reported 8 (5 unmet/3 met) needs on average. Factor analyses revealed 5 factors. Total needs related significantly with MAC rZ.50, HADS anxiety rZ .55, HADS depression rZ.52, global health (QoL) rZ.54 and age rZ-.25. Test-retest correlations were low ( .93). Conclusions: The CaSUN-NL appeared to be a valid tool to investigate information needs among cancer survivors. Work related items related to original CaSUN items. Items on needs related to lifestyle (change) did not fit into this measurement instrument.

Studies of movement coding have indicated a relationship between functional MRI signals and increasing frequency of movement in primary motor cortex and other motor-related structures. However, prior work has typically used block-designs and fixed-time intervals across the varying movements frequencies that may prevent ready distinction of brain mechanisms related to movement quantity and, especially, movement frequency. Here, we obtained functional MRI signals from humans working in an event-related design to extract independent activation related to movement quantity or movement frequency. Participants tapped once, twice, or thrice at 1, 2, or 3 Hz, and the tapping evoked activation related to movement quantity in the precentral and postcentral gyri, supplementary motor area, cerebellum, putamen, and thalamus. Increasing movement frequency failed to yield activation in these motor-related areas, although linear movement frequency affects occurred in nonmotor regions of cortex and subcortex. Our results do not replicate prior data suggesting movement frequency encoding in motor-related areas; instead we observed movement quantity coding in motor-related brain areas. The discrepancy between prior studies and this study likely relates to methodology concerns. We suggest that the movement quantity relationships in human motor areas and encoding of movement frequency in nonmotor areas may reflect a functional anatomical substrate for mediating distinct movement parameters.

Multiple brain regions, including parietal and frontal cortical areas, seem to participate in learning and rehearsing associations between spatially defined visual cues and appropriate motor responses. However, because most previous studies have related learning to changes in brain activation according to elapsed time or number of trials but not categories based on performance, it remains unclear how and when areas implicated in learning sensory-motor associations actually participate in the process. The current experiment used functional magnetic resonance imaging to examine changes in brain activation when participants learned to associate an arbitrarily located visual cue with a finger movement. Associative trials were categorized as incorrect, first correct, or subsequent correct. Participants also performed a spatially compatible visual-motor control task. A group analysis revealed four major findings addressing the behavioral processes occurring during forming and rehearsing visual-motor rules. First, brain networks related to processing associative information, through initial learning to rehearsal, yielded more activation in a myriad of neocortical structures than did a simple motor task. Second, we revealed frontal and parietal areas that differentially processed errors and correct responses. Third, we found frontal-parietal networks that seemed to mediate the transition of learning to rehearsing arbitrary visual-motor associations and that this activation exhibited dynamic characteristics. Last, we found a frontal-parietal network that appeared to have a key role in expressing the learned sensory-motor association. The current results provide a foundation for understanding how neocortical structures participate in the various behavioral processes that combine to form and consolidate novel and arbitrary sensory-motor associations.

2mapping) that directly calculates T* by a linear combination of images obtained at three or more different echo times was developed. NumART*, linear least-squares, and nonlinear regression techniques were applied to multiecho planar images of the human brain and to simulated data. Although NumART* 2 may overestimate T*, it yields comparable values to regression techniques in cortical and subcortical areas, with only moderate deviations for echo spacings between 18 and 40 ms. NumART* 2, like linear regression, requires 2% of the computational time needed for nonlinear regression and compares favorably with linear regression due to its higher precision. The use of NumART* 2 for continuous on-line T* mapping in real time fMRI studies is shown. Magn Reson Med 48:877– 882, 2002. © 2002 Wiley-Liss, Inc. 2; real-time In blood oxygenation level-dependent (BOLD) functional MRI (fMRI), the major source of contrast is the effective transverse relaxation time, T* 2, which is sensitive to the presence of paramagnetic deoxyhemoglobin molecules. In most fMRI studies, relative T* 2 changes are detected by EPI (echo planar imaging) at a fixed echo time, TE, and, typically, experimenters chose a TE close to the resting tissue T* 2 to produce maximal BOLD signal change (1,2). However, the use of a fixed, single TE does not necessarily guarantee the best contrast, since baseline T* 2 values may have spatial heterogeneity within and between individuals. The resulting contrast variation may cause inconsistent activation patterns and detectability, as shown for somatosensory-related activation in rats at 7 T (3) and motor activation in human subjects at 1.5 T (4). Consequently, it may be advantageous to measure several echoes instead of a single echo in fMRI studies and quantify T* 2, with a possible added advantage of reducing the variability of activation patterns. Recent developments of the EPI technique have made multiple-echo measurements possible, encompassing the acquisition of several images at different echo times in a single shot (5‐11). With these new techniques, whole brain coverage can be obtained in a time-frame comparable to conventional single echo methods. Consequently, limits in imaging time no longer prevent T* 2 mapping in fMRI studies, although excessive postprocessing times could restrict their use. Available methods for T* 2 quantification currently use voxel-wise nonlinear regression of the signal relaxation observed from single-echo images. These techniques are computationally intensive and may not be readily implemented on many currently available MRI scanners deployed at clinical sites. A proposed method to overcome this limit is weighted averaging of the echo images, with weights based on expected T* 2 values in the resting condition (5). This method is fast and can be implemented in real-time but, similar to single-echo acquisition techniques, may also be affected by differences in baseline T* 2. Here, we propose an alternative numerical method, NumART* 2 (numerical algorithm for real-time T* 2 mapping) that, to our knowledge, has not been previously used in the context of MRI. The method is based on the acquisition of MR images with three or more echo times and then performing a linear image combination to obtain quantitative T* 2 maps. THEORY

Control of voluntary movement involves the central nervous system from the spinal cord to the cerbral cortex. Keywords: motor cortex; muscles; spinal cord; cerebellum; basal ganglia