Narender Ramnani

Anterior prefrontal cortex: insights into function from anatomy and neuroimaging.

The anterior prefrontal cortex (aPFC), or Brodmann area 10, is one of the least well understood regions of the human brain. Work with non-human primates has provided almost no indications as to the function of this area. In recent years, investigators have attempted to integrate findings from functional neuroimaging studies in humans to generate models that might describe the contribution that this area makes to cognition. In all cases, however, such explanations are either too tied to a given task to be plausible or too general to be theoretically useful. Here, we use an account that is consistent with the connectional and cellular anatomy of the aPFC to explain the key features of existing models within a common theoretical framework. The results indicate a specific role for this region in integrating the outcomes of two or more separate cognitive operations in the pursuit of a higher behavioural goal.

Distinct and Overlapping Functional Zones in the Cerebellum Defined by Resting State Functional Connectivity

The cerebellum processes information from functionally diverse regions of the cerebral cortex. Cerebellar input and output nuclei have connections with prefrontal, parietal, and sensory cortex as well as motor and premotor cortex. However, the topography of the connections between the cerebellar and cerebral cortices remains largely unmapped, as it is relatively unamenable to anatomical methods. We used resting-state functional magnetic resonance imaging to define subregions within the cerebellar cortex based on their functional connectivity with the cerebral cortex. We mapped resting-state functional connectivity voxel-wise across the cerebellar cortex, for cerebral-cortical masks covering prefrontal, motor, somatosensory, posterior parietal, visual, and auditory cortices. We found that the cerebellum can be divided into at least 2 zones: 1) a primary sensorimotor zone (Lobules V, VI, and VIII), which contains overlapping functional connectivity maps for domain-specific motor, somatosensory, visual, and auditory cortices; and 2) a supramodal zone (Lobules VIIa, Crus I, and II), which contains overlapping functional connectivity maps for prefrontal and posterior-parietal cortex. The cortical connectivity of the supramodal zone was driven by regions of frontal and parietal cortex which are not directly involved in sensory or motor processing, including dorsolateral prefrontal cortex and the frontal pole, and the inferior parietal lobule.

Consensus Paper: The Cerebellum's Role in Movement and Cognition

While the cerebellums role in motor function is well recognized, the nature of its concurrent role in cognitive function remains considerably less clear. The current consensus paper gathers diverse views on a variety of important roles played by the cerebellum across a range of cognitive and emotional functions. This paper considers the cerebellum in relation to neurocognitive development, language function, working memory, executive function, and the development of cerebellar internal control models and reflects upon some of the ways in which better understanding the cerebellums status as a “supervised learning machine” can enrich our ability to understand human function and adaptation. As all contributors agree that the cerebellum plays a role in cognition, there is also an agreement that this conclusion remains highly inferential. Many conclusions about the role of the cerebellum in cognition originate from applying known information about cerebellar contributions to the coordination and quality of movement. These inferences are based on the uniformity of the cerebellums compositional infrastructure and its apparent modular organization. There is considerable support for this view, based upon observations of patients with pathology within the cerebellum.

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.

Variability in fMRI: A re-examination of inter-session differences

We revisit a previous study on inter‐session variability (McGonigle et al. [ 2000 ]: Neuroimage 11:708–734), showing that contrary to one popular interpretation of the original article, inter‐session variability is not necessarily high. We also highlight how evaluating variability based on thresholded single‐session images alone can be misleading. Finally, we show that the use of different first‐level preprocessing, time‐series statistics, and registration analysis methodologies can give significantly different inter‐session analysis results. Hum. Brain Mapping 24:248–257, 2005.

Evolution of the cerebellar cortex: The selective expansion of prefrontal-projecting cerebellar lobules

It has been suggested that interconnected brain areas evolve in tandem because evolutionary pressures act on complete functional systems rather than on individual brain areas. The cerebellar cortex has reciprocal connections with both the prefrontal cortex and motor cortex, forming independent loops with each. Specifically, in capuchin monkeys cerebellar cortical lobules Crus I and Crus II connect with prefrontal cortex, whereas the primary motor cortex connects with cerebellar lobules V, VI, VIIb, and VIIIa. Comparisons of extant primate species suggest that the prefrontal cortex has expanded more than cortical motor areas in human evolution. Given the enlargement of the prefrontal cortex relative to motor cortex in humans, our hypothesis would predict corresponding volumetric increases in the parts of the cerebellum connected to the prefrontal cortex, relative to cerebellar lobules connected to the motor cortex. We tested the hypothesis by comparing the volumes of cerebellar lobules in structural MRI scans in capuchins, chimpanzees and humans. The fractions of cerebellar volume occupied by Crus I and Crus II were significantly larger in humans compared to chimpanzees and capuchins. Our results therefore support the hypothesis that in the cortico-cerebellar system, functionally related structures evolve in concert with each other. The evolutionary expansion of these prefrontal-projecting cerebellar territories might contribute to the evolution of the higher cognitive functions of humans.

Changes in the Human Brain during Rhythm Learning

Subjects were scanned with PET while they learned a complex arbitrary rhythm, paced by visual cues. In the comparison condition, the intervals were varied randomly. The behavioral results showed that the subjects decreased their response time with training, thus becoming more accurate in responding to the pacing cues at the appropriate time. There were learning-related increases in the posterior lateral cerebellum (lobule HVIIa), intraparietal and medial parietal cortex, presupplementary motor area (pre-SMA), and lateral premotor cortex. Learning-related decreases were found in the prestriate and inferior temporal cortex, suggesting that with practice the subjects increasingly came to depend on internal rather than external cues to time their responses. There were no learning-related increases in the basal ganglia. It is suggested that it is the neocortical-cerebellar loop that is involved in the timing and coordination of responses.

Prediction error for free monetary reward in the human prefrontal cortex

Making predictions about future rewards is an important ability for primates, and its neurophysiological mechanisms have been studied extensively. One important approach is to identify neural systems that process errors related to reward prediction (i.e., areas that register the occurrence of unpredicted rewards and the failure of expected rewards). In monkeys that have learned to predict appetitive rewards during reward-directed behaviors, dopamine neurons reliably signal both types of prediction error. The mechanisms in the human brain involved in processing prediction error for monetary rewards are not well understood. Furthermore, nothing is known of how such systems operate when rewards are not contingent on behavior. We used event-related fMRI to localize responses to both classes of prediction error. Subjects were able to predict a monetary reward or a nonreward on the basis of a prior visual cue. On occasional trials, cue-outcome contingencies were reversed (unpredicted rewards and failure of expected rewards). Subjects were not required to make decisions or actions. We compared each type of prediction error trial with its corresponding control trial in which the same prediction did not fail. Each type of prediction error evoked activity in a distinct frontotemporal circuit. Unexpected reward failure evoked activity in the temporal cortex and frontal pole (area 10). Unpredicted rewards evoked activity in the orbitofrontal cortex, the frontal pole, parahippocampal cortex, and cerebellum. Activity time-locked to prediction errors in frontotemporal circuits suggests that they are involved in encoding the associations between visual cues and monetary rewards in the human brain.

Reversible inactivations of the cerebellum with muscimol prevent the acquisition and extinction of conditioned nictitating membrane responses in the rabbit

Lesions of the cerebellum severely impair the classically conditioned nictitating membrane response (NMR) in rabbits. Thus, the cerebellum is essential for the production of conditioned responses (CRs), either because it is actively involved in NMR conditioning or because damage to it causes motor or other general deficits. To distinguish between these alternatives, the cerebellum may be inactivated during training. Inactivation of the cerebellum during acquisition training might result in the absence of CRs on initial trials of subsequent training without the neuronal blockade. The blockade may have prevented learning but it may have produced other deficits that require time or further training to overcome. This problem can be addressed by inactivating the cerebellum during extinction training. If inactivation during extinction training results in the immediate production of CRs when training is resumed without the blockade, then it may be concluded that extinction learning was prevented by the blockade — the presence of CRs argues against any deficits not associated with learning. We used muscimol to inactivate the cerebellum and test its involvement in acquisition and extinction of NMR conditioning in the same subjects. We injected muscimol close to the interpositus nucleus of the cerebellum 1 h before each of four daily training sessions of delay conditioning. Almost no CRs were produced in these training sessions — there was little or no acquisition of NMR conditioning during cerebellar inactivation. The subjects were then trained for four daily sessions without injections of muscimol. There were no CRs on initial trials of the first session of retraining, but all subjects produced CRs by the end of this session. The subjects then received four daily sessions of extinction training with muscimol inactivation of the nuclei — no CRs were produced. Extinction training then continued for four daily sessions without muscimol inactivation. On the first of these sessions, all subjects immediately produced high levels of CRs. These responses then extinguished within and between sessions with characteristic beginning-of-session spontaneous recovery. There was little or no extinction of NMR conditioning during cerebellar inactivation. After inactivation, the muscimolinactivated subjects went on to acquire and extinguish NM responses at rates similar to those of appropriate controls. We conclude that cerebellar circuitry is essential for, and actively engaged in, both acquisition and extinction of this simple form of motor learning.

The Cerebellum and Parietal Cortex Play a Specific Role in Coordination: A Pet Study

The synthesis of complex, coordinated movements from simple actions is an important aspect of motor control. Lesion studies have revealed specific brain areas, particularly the cerebellum, to be essential for a variety of coordinated movements, and lend support to the view that the cerebellum is engaged in the integration of simple movements into compound ones. A PET study was therefore conducted to show which brain areas were active specifically during the coordinated execution of an arm and finger movement to visual targets. A two-by-two factorial design was employed, in which subjects either made arm or finger movements alone, made coordinated arm-finger movements, or made no movements. Voxels were identified where activity was significantly greater during the execution of coordinated movements than when movements were made alone and in which this increased activity could not be accounted for simply by the additive effects of the activations for each movement in isolation. The behavioral results showed that subjects coordinated arm and finger movements well during coordination scans. Coordination-specific activations were found in left anterior lobe and bilaterally in the paramedian lobules of the cerebellum. These are known to receive forelimb-specific spinocerebellar proprioceptive inputs that may be related to multijoint movements. The same areas also receive corticocerebellar afference from motor areas that may convey efference copy information to the cerebellum. Coordination-specific activations were also seen in areas of the posterior parietal cortex. The results provide direct evidence in healthy human subjects of specific cerebellar engagement during the coordination of movement, over and above the control of constituent movements.