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Narender Ramnani

Publications and source records attributed to Narender Ramnani.

9 recordsLinked to original sources

The primate cortico-cerebellar system: anatomy and function.

Evidence has been accumulating that the primate cerebellum contributes not only to motor control, but also to higher 'cognitive' function. However, there is no consensus about how the cerebellum processes such information. The answer to this puzzle can be found in the nature of cerebellar connections to areas of the cerebral cortex (particularly the prefrontal cortex) and in the uniformity of its intrinsic cellular organization, which implies uniformity in information processing regardless of the area of origin in the cerebral cortex. With this in mind, the relatively well-developed models of how the cerebellum processes information from the motor cortex might be extended to explain how it could also process information from the prefrontal cortex.

Animals↗

The evolution of prefrontal inputs to the cortico-pontine system: diffusion imaging evidence from Macaque monkeys and humans.

The cortico-ponto-cerebellar system is one of the largest projection systems in the primate brain, but in the human brain the nature of the information processing in this system remains elusive. Determining the areas of the cerebral cortex which contribute projections to this system will allow us to better understand information processing within it. Information from the cerebral cortex is conveyed to the cerebellum by topographically arranged fibres in the cerebral peduncle - an important fibre system in which all cortical outputs spatially converge on their way to the cerebellum via the pontine nuclei. Little is known of their anatomical organization in the human brain. New in vivo diffusion imaging and probabilistic tractography methods now offer a way in which input tracts in the cerebral peduncle can be characterized in detail. Here we use these methods to contrast their organization in humans and macaque monkeys. We confirm the dominant contribution of the cortical motor areas to the macaque monkey cerebral peduncle. However, we also present novel anatomical evidence for a relatively large prefrontal contribution to the human cortico-ponto-cerebellar system in the cerebral peduncle. These findings suggest the selective evolution of prefrontal inputs to the human cortico-ponto-cerebellar system.

Adult↗

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.

Adult↗

New approaches for exploring anatomical and functional connectivity in the human brain.

Information processing in the primate brain is based on the complementary principles of modular and distributed information processing. The former emphasizes the specialization of functions within different brain areas. The latter emphasizes the massively parallel nature of brain networks and the fact that function also emerges from the flow of information between brain areas. The localization of function to specific brain areas ("functional segregation") is the commonest approach to investigating function; however, an emerging, complementary approach ("functional integration") describes function in terms of the information flow across networks of areas. Here, we highlight recent advances in neuroimaging methodology that have made it possible to investigate the anatomical architecture of networks in the living human brain with diffusion tensor imaging (DTI). We also highlight recent thinking on the ways in which functional imaging can be used to characterize information transmission across networks in the human brain (functional and effective connectivity).

Animals↗

Distinct portions of anterior cingulate cortex and medial prefrontal cortex are activated by reward processing in separable phases of decision-making cognition.

BACKGROUND: Choosing between actions associated with uncertain rewards and punishments is mediated by neural circuitry encompassing the orbitofrontal cortex, anterior cingulate cortex (ACC), and striatum; however, the precise conditions under which these different components are activated during decision-making cognition remain uncertain. METHODS: Fourteen healthy volunteers completed an event-based functional magnetic resonance imaging protocol to investigate blood-oxygenation-level-dependent (BOLD) responses during independently modeled phases of choice cognition. In the "decision phase," participants decided which of two simultaneous visually presented gambles they wished to play for monetary reward. The gambles differed in their magnitude of gains, magnitude of losses, and the probabilities with which these outcomes were delivered. In the "outcome phase," the result of each choice was indicated on the visual display. RESULTS: In the decision phase, choices involving large gains were associated with increased BOLD responses in the pregenual ACC, paracingulate, and right posterior orbitolateral cortex compared with choices involving small gains. In the outcome phase, good outcomes were associated with increased BOLD responses in the posterior orbitomedial cortex, subcallosal ACC, and ventral striatum compared with negative outcomes. There was only limited overlap between reward-related activity in ACC and orbitofrontal cortex during the decision and outcome phases. CONCLUSIONS: Neural activity within the medial and lateral orbitofrontal cortex, pregenual ACC, and striatum mediate distinct representations of reward-related information that are deployed at different stages during a decision-making episode.

Adult↗

A system in the human brain for predicting the actions of others.

The ability to attribute mental states to others, and therefore to predict others' behavior, is particularly advanced in humans. A controversial but untested idea is that this is achieved by simulating the other person's mental processes in one's own mind. If this is the case, then the same neural systems activated by a mental function should re-activate when one thinks about that function performed by another. Here, using functional magnetic resonance imaging (fMRI), we tested whether the neural processes involved in preparing one's own actions are also used for predicting the future actions of others. We provide compelling evidence that areas within the action control system of the human brain are indeed activated when predicting others' actions, but a different action sub-system is activated when preparing one's own actions.

Adult↗

Learning of sequences of finger movements and timing: frontal lobe and action-oriented representation.

Motor sequence learning involves learning of a sequence of effectors with which to execute a series of movements and learning of a sequence of timings at which to execute the movements. In this study, we have segregated the neural correlates of the two learning mechanisms. Moreover, we have found an interaction between the two learning mechanisms in the frontal areas, which we claim as suggesting action-oriented coding in the frontal lobe. We used positron emission tomography and compared three learning conditions with a visuo-motor control condition. In two learning conditions, the subjects learned either a sequence of finger movements with random timing or a sequence of timing with random use of fingers. In the third condition the subjects learned to execute a sequence of specific finger movements at specific timing; we argue that it was only in this condition that the motor sequence was coded as an action-oriented representation. By looking for condition by session interactions (learning vs. control conditions over sessions), we have removed nonspecific time effects and identified areas that showed a learning-related increment of activation during learning. Learning of a finger sequence was associated with an increment of activation in the right intraparietal sulcus region and medial parietal cortex, whereas learning of a timing sequence was associated with an increment of activation in the lateral cerebellum, suggesting separate mechanisms for learning effector and temporal sequences. The left intraparietal sulcus region showed an increment of activation in learning of both finger and timing sequences, suggesting an overlap between the two learning mechanisms. We also found that the mid-dorsolateral prefrontal cortex, together with the medial and lateral premotor areas, became increasingly active when subjects learned a sequence that specified both fingers and timing, that is, when subjects were able to prepare specific motor action. These areas were not active when subjects learned a sequence that specified fingers or timing alone, that is, when subjects were still dependent on external stimuli as to the timing or fingers with which to execute the movements. Frontal areas may integrate the effector and temporal information of a motor sequence and implement an action-oriented representation so as to perform a motor sequence accurately and quickly. We also found that the mid-dorsolateral prefrontal cortex was distinguished from the ventrolateral prefrontal cortex and anterior fronto-polar cortex, which showed sustained activity throughout learning sessions and did not show either an increment or decrement of activation.

Adult↗