Ivan Toni

The time course of changes during motor sequence learning: a whole-brain fMRI study.

There is a discrepancy between the results of imaging studies in which subjects learn motor sequences. Some experiments have shown decreases in the activation of some areas as learning increased, whereas others have reported learning-related increases as learning progressed. We have exploited fMRI to measure changes in blood oxygen leve-dependent (BOLD) signal throughout the course of learning. T2*-weighted echo-planar images were acquired over the whole brain for 40 min while the subjects learned a sequence eight moves long by trial and error. The movements were visually paced every 3.2 s and visual feedback was provided to the subjects. A baseline period followed each activation period. The effect due to the experimental conditions was modeled using a square-wave function, time locked to their occurrence. Changes over time in the difference between activation and baseline signal were modeled using a set of polynomial basis functions. This allowed us to take into account linear as well as nonlinear changes over time. Low-frequency changes over time common to both activation and baseline conditions (and thus not learning related) were modeled and removed. Linear and nonlinear changes of BOLD signal over time were found in prefrontal, premotor, and parietal cortex and in neostriatal and cerebellar areas. Single-unit recordings in nonhuman primates during the learning of motor tasks have clearly shown increased activity early in learning, followed by a decrease as learning progressed. Both phenomena can be observed at the population level in the present study.

A Functional Anatomy of Anticipatory Anxiety

Anticipatory anxiety is a complex combination of a future-oriented cognitive state, negative affect, and autonomic arousal. A dual-task paradigm of anticipation of electric shocks and a motor-learning task was used to examine the changes in neural patterns of activation associated with modulation of the cognitive state in anxiety by a distracting motor task. We used positron emission tomography (PET) and 15O-water to measure regional cerebral blood flow (rcbf) in 10 healthy male volunteers. A 2x2 factorial design-(shock vs no shock) x (low vs high distraction) was used with three scans per condition. Twelve PET scans were performed on each subject. In six of these scans, subjects were given electric shocks. In all scans, subjects also simultaneously performed a motor repetition (low distraction) or learning (high distraction) task. Galvanic skin conductance (GSR), Spielberger State and Trait Anxiety Inventory (STAI), and self-report data were also collected. In comparisons between the shock and no-shock conditions, the main finding was of increased rcbf in the left insula (-38,8,8) (z = 4.85, P<0.05 corrected) and a homologous area in the right insula at a lower threshold (z =3.20, P = 0.001 uncorrected). Other areas activated were the right superior temporal sulcus, left fusiform, and left anterior cingulate. Using the STAI-state scores as a covariate of interest, significant correlations with rCBF were seen in the left orbitofrontal cortex, left insula, and left anterior cingulate cortex. There was no significant distraction effect as measured by the STAI, self-report, GSR response or interactional analysis of the PET data. These findings support the role of paralimbic structures as neural substrates of anticipatory anxiety. The failure to demonstrate behavioral and neurophysiological changes with the distractor task may reflect the modest increases in anxiety with the shock, the relatively simple distractor task, and small sample size.

Connectivity-Based Subdivisions of the Human Right “Temporoparietal Junction Area”: Evidence for Different Areas Participating in Different Cortical Networks

Controversy surrounds the role of the temporoparietal junction (TPJ) area of the human brain. Although TPJ has been implicated both in reorienting of attention and social cognition, it is still unclear whether these functions have the same neural basis. Indeed, whether TPJ is a precisely identifiable cortical region or a cluster of subregions with separate functions is still a matter of debate. Here, we examined the structural and functional connectivity of TPJ, testing whether TPJ is a unitary area with a heterogeneous functional connectivity profile or a conglomerate of regions with distinctive connectivity. Diffusion-weighted imaging tractrography-based parcellation identified 3 separate regions in TPJ. Resting-state functional connectivity was then used to establish which cortical networks each of these subregions participates in. A dorsal cluster in the middle part of the inferior parietal lobule showed resting-state functional connectivity with, among other areas, lateral anterior prefrontal cortex. Ventrally, an anterior TPJ cluster interacted with ventral prefrontal cortex and anterior insula, while a posterior TPJ cluster interacted with posterior cingulate, temporal pole, and anterior medial prefrontal cortex. These results indicate that TPJ can be subdivided into subregions on the basis of its structural and functional connectivity.

Spatial Remapping of Cortico-striatal Connectivity in Parkinson's Disease

Parkinsons disease (PD) is characterized by striatal dopamine depletion, especially in the posterior putamen. The dense connectivity profile of the striatum suggests that these local impairments may propagate throughout the whole cortico-striatal network. Here we test the effect of striatal dopamine depletion on cortico-striatal network properties by comparing the functional connectivity profile of the posterior putamen, the anterior putamen, and the caudate nucleus between 41 PD patients and 36 matched controls. We used multiple regression analyses of resting-state functional magnetic resonance imaging data to quantify functional connectivity across different networks. Each region had a distinct connectivity profile that was similarly expressed in patients and controls: the posterior putamen was uniquely coupled to cortical motor areas, the anterior putamen to the pre-supplementary motor area and anterior cingulate cortex, and the caudate nucleus to the dorsal prefrontal cortex. Differences between groups were specific to the putamen: although PD patients showed decreased coupling between the posterior putamen and the inferior parietal cortex, this region showed increased functional connectivity with the anterior putamen. We conclude that dopamine depletion in PD leads to a remapping of cerebral connectivity that reduces the spatial segregation between different cortico-striatal loops. These alterations of network properties may underlie abnormal sensorimotor integration in PD.

On the relationship between the “default mode network” and the “social brain”

The default mode network (DMN) of the brain consists of areas that are typically more active during rest than during active task performance. Recently however, this network has been shown to be activated by certain types of tasks. Social cognition, particularly higher-order tasks such as attributing mental states to others, has been suggested to activate a network of areas at least partly overlapping with the DMN. Here, we explore this claim, drawing on evidence from meta-analyses of functional MRI data and recent studies investigating the structural and functional connectivity of the social brain. In addition, we discuss recent evidence for the existence of a DMN in non-human primates. We conclude by discussing some of the implications of these observations.

Gait-related cerebral alterations in patients with Parkinson’s disease with freezing of gait

Freezing of gait is a common, debilitating feature of Parkinsons disease. We have studied gait planning in patients with freezing of gait, using motor imagery of walking in combination with functional magnetic resonance imaging. This approach exploits the large neural overlap that exists between planning and imagining a movement. In addition, it avoids confounds introduced by brain responses to altered motor performance and somatosensory feedback during actual freezing episodes. We included 24 patients with Parkinsons disease: 12 patients with freezing of gait, 12 matched patients without freezing of gait and 21 matched healthy controls. Subjects performed two previously validated tasks--motor imagery of gait and a visual imagery control task. During functional magnetic resonance imaging scanning, we quantified imagery performance by measuring the time required to imagine walking on paths of different widths and lengths. In addition, we used voxel-based morphometry to test whether between-group differences in imagery-related activity were related to structural differences. Imagery times indicated that patients with freezing of gait, patients without freezing of gait and controls engaged in motor imagery of gait, with matched task performance. During motor imagery of gait, patients with freezing of gait showed more activity than patients without freezing of gait in the mesencephalic locomotor region. Patients with freezing of gait also tended to have decreased responses in mesial frontal and posterior parietal regions. Furthermore, patients with freezing of gait had grey matter atrophy in a small portion of the mesencephalic locomotor region. The gait-related hyperactivity of the mesencephalic locomotor region correlated with clinical parameters (freezing of gait severity and disease duration), but not with the degree of atrophy. These results indicate that patients with Parkinsons disease with freezing of gait have structural and functional alterations in the mesencephalic locomotor region. We suggest that freezing of gait might emerge when altered cortical control of gait is combined with a limited ability of the mesencephalic locomotor region to react to that alteration. These limitations might become particularly evident during challenging events that require precise regulation of step length and gait timing, such as turning or initiating walking, which are known triggers for freezing of gait.

Pallidal dysfunction drives a cerebellothalamic circuit into Parkinson tremor.

Parkinson disease (PD) is characterized by striatal dopamine depletion, which explains clinical symptoms such as bradykinesia and rigidity, but not resting tremor. Instead, resting tremor is associated with increased activity in a distinct cerebellothalamic circuit. To date, it remains unknown how the interplay between basal ganglia and the cerebellothalamic circuit can result in resting tremor.

Cerebral causes and consequences of parkinsonian resting tremor: A tale of two circuits?

Tremor in Parkinsons disease has several mysterious features. Clinically, tremor is seen in only three out of four patients with Parkinsons disease, and tremor-dominant patients generally follow a more benign disease course than non-tremor patients. Pathophysiologically, tremor is linked to altered activity in not one, but two distinct circuits: the basal ganglia, which are primarily affected by dopamine depletion in Parkinsons disease, and the cerebello-thalamo-cortical circuit, which is also involved in many other tremors. The purpose of this review is to integrate these clinical and pathophysiological features of tremor in Parkinsons disease. We first describe clinical and pathological differences between tremor-dominant and non-tremor Parkinsons disease subtypes, and then summarize recent studies on the pathophysiology of tremor. We also discuss a newly proposed ‘dimmer-switch model’ that explains tremor as resulting from the combined actions of two circuits: the basal ganglia that trigger tremor episodes and the cerebello-thalamo-cortical circuit that produces the tremor. Finally, we address several important open questions: why resting tremor stops during voluntary movements, why it has a variable response to dopaminergic treatment, why it indicates a benign Parkinsons disease subtype and why its expression decreases with disease progression.

Prefrontal-basal ganglia pathways are involved in the learning of arbitrary visuomotor associations: a PET study.

Abstract Primates can learn to associate sensory cues with particular movements according to arbitrary rules. We used positron emission tomography (PET) to study the neural network involved in learning such arbitrary associations by trial and error. Ten subjects were scanned at four different stages of learning a visuomotor conditional task (VC). The subjects were required to associate four different visual patterns, presented one at a time, with four different finger movements. Scan 1 was acquired during initial learning. Scans 2, 3 and 4 were performed after further interscan training periods of 1, 3 and 5 min. In order to control for non-specific time effects that could have confounded the learning-related rCBF changes, we also acquired four sensory-matched control scans, in which no movements were performed. In order to evaluate changes over time that were specific to learning the association of visual cues with movements, we acquired four scans during the learning of a motor sequence task. The statistical model tested with SPM considered both main effects of tasks and task × time interactions independently for each of the three experimental conditions. The right lingual gyrus and the left parahippocampal cortex increased their activity over scans in the VC task as compared to the sensory control. The right inferior frontal sulcus, the body of the caudate nucleus and a left cingulate motor area were specifically implicated in learning the VC task, showing task × time interactions with the motor sequence task. These findings suggest that the learning process involves a distributed network in the ventral extrastriate and prefrontal cortex, in association with the basal ganglia and the parahippocampal gyrus.

Learning Arbitrary Visuomotor Associations: Temporal Dynamic of Brain Activity

Primates can give behavioral responses on the basis of arbitrary, context-dependent rules. When sensory instructions and behavioral responses are associated by arbitrary rules, these rules need to be learned. This study investigates the temporal dynamics of functional segregation at the basis of visuomotor associative learning in humans, isolating specific learning-related changes in neurovascular activity across the whole brain. We have used fMRI to measure human brain activity during performance of two tasks requiring the association of visual patterns with motor responses. Both tasks were learned by trial and error, either before (visuomotor control) or during (visuomotor learning) the scanning session. Epochs of tasks performance ( approximately 30 s) were alternated with a baseline period over the whole scanning session ( approximately 50 min). We have assessed both linear and nonlinear modulations in the differential signal between tasks, independently from overall task differences. The performance indices of the visuomotor learning task smoothly converged onto the values of a steady-state control condition, according to nonlinear timecourses. Specific visuomotor learning-related activity has been found over a distributed cortical network, centred on a temporo-prefrontal circuit. These cortical time-modulated activities were supported early in learning by the hippocampal/parahippocampal complex, and late in learning by the basal ganglia system. These findings suggest the inferior temporal and the ventral prefrontal cortex are critical neural nodes for integrating perceptual information with executive processes.