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Encoding, coordination, and decision making in the primate fronto-parietal grasping network

dc.contributor.advisorScherberger, Hansjörg Prof.
dc.contributor.authorDann, Benjamin
dc.date.accessioned2017-09-22T08:32:16Z
dc.date.available2017-09-22T08:32:16Z
dc.date.issued2017-09-22
dc.identifier.urihttp://hdl.handle.net/11858/00-1735-0000-0023-3F10-3
dc.identifier.urihttp://dx.doi.org/10.53846/goediss-6497
dc.language.isoengde
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject.ddc570de
dc.titleEncoding, coordination, and decision making in the primate fronto-parietal grasping networkde
dc.typedoctoralThesisde
dc.contributor.refereeScherberger, Hansjörg Prof. Dr.
dc.date.examination2017-08-07
dc.description.abstracteng The processes taking place in our brain allow us to flexibly interact with our surrounding based on our internal demands. This requires perceptual information processing up to the generation of movements taking place in the network of neurons of the brain. In order to understand these processes, we first need a clear understanding of how information is communicated, encoded, and transformed in a decision-dependent fashion within the neuronal network. However, recording activity from many neurons in parallel is technically difficult and only possible with invasive techniques requiring an animal model, and for a limited area of the brain. To this end, we used newly developed multi-electrode arrays to record neuronal activity across the fronto-parietal grasping network (areas AIP, F5 and M1) of the macaque monkey, while monkeys performed different grasping tasks. The fronto-parietal grasping network is known to be involved in perceptual processing, sensory-motor transformation, and grasp movement planning and execution, making it an ideal candidate to investigate communication, encoding and information transformation.  A first study of my thesis (chapter 2.1) addressed the question how information is communicated and coordinated across the fronto-parietal single neuron network. To achieve a reliable estimate of the neuronal network communication between all pairs of neurons, a new statistical procedure based on crosscorrelograms was developed and tested. This procedure allowed us to analyze the network structure of communication and whether neurons were communicating rhythmically or non-rhythmically. Analyses of the single neuron network revealed a highly organized and complex structure, optimized for fast, specific, and efficient information processing. The contribution of individual neurons to network function was highly heterogeneous, revealing a core of strongly connected neurons spanning all areas and coordinating the whole network, which I show the first time in the single neuron network of behaving primates. Crucially, the core consisted of rhythmically communicating neurons, while sparsely connected neurons communicated predominantly in a non-rhythmically fashion. These findings suggest that the information flow of the fronto-parietal grasping network is coordinated by an area-spanning core of rhythmically communicating neurons forming an efficient functional network structure, which might be a general coordination mechanism across cortex, e.g., as seen in the clinical EEG.  In a second study of my thesis (chapter 2.2), I investigated how information is encoded and transformed in the fronto-parietal grasping network while monkeys were either visually instructed or freely choosing to grasp a handle with one of two grip types. Analyses of individual neurons revealed that despite the fact that a large number of neurons in the fronto-parietal grasping network were significantly modulated by the task, i.e. tuned throughout all time epochs of the task, the tuning was not stable. The specific tuning preference of the neurons changed dynamically over time across the neuronal population. When considering the whole neuronal population as one strongly interconnected network, in which neural population activity evolves dynamically through space-space over time and conditions, a clear low dimensional structure became apparent. All task specific single trial activity could be explained by an evolution through just three independent informational subspaces representing visual, planning, and movement activity, with free-choice decisions emerging directly in the planning subspace. Crucially, contributions to all three informational spaces were randomly distributed across the fronto-parietal neuronal population. These results indicate that instead of addressing the attributes of individual neurons, neuronal activity can be more completely understood at the population level, where a neuronal population can encode different processes at different and overlapping times, which can be dynamically transformed according to the behavioral demands. The innovation of such novel population analyses is that they can characterize the specific roles and functions of cortical networks in simple and holistic approach without getting stuck in the complicated and often idiosyncratic properties of individual neurons.  The third study of my thesis (chapter 2.3), addressed the neuronal population encoding in AIP and F5 at the transition between immediate and withheld movements. Single neuron tuning of both areas was complex and difficult to characterise. However, when considered at the population-level, a clearly describable temporal and conditional population dynamics became apparent. Neuronal population dynamics of both areas, AIP and F5, first followed a grip-specific trajectory that was identical for immediate and long delayed grasps, presumably representing unavoidable processing. However, after this initial phase, population activity in AIP tended to stabilize, whereas activity in F5 continued to evolve through state space, likely reflecting movement anticipation. Interestingly, grip-specific population activity of both areas evolved through two distinct and significantly separate spaces for immediate and delayed movements, suggesting a unique state for movements performed from memory. These findings suggest that the complex interplay of dynamical and static aspects of movement preparation, such as anticipation and planning of a particular grasp type, can be understood as an evolution of neuronal population activity through specific dimensions of a higher dimensional state space.  Together, the three main studies of my thesis emphasize the view that information in the fronto-parietal neuronal network is encoded and transformed as a dynamical process evolving through a limited number of population subspaces. The underlying communication structure of this network is coordinated by a core of rhythmically communicating neurons. These findings suggest that the core of rhythmically communicating neurons could be crucial for the transformation and maintenance of information between the population subspace, which offers a first, coarse picture of the processing underlying sensory-motor transformation in the fronto-parietal grasping network. de
dc.contributor.coRefereeGail, Alexander Prof. Dr.
dc.contributor.thirdRefereeGöpfert, Martin Prof. Dr.
dc.contributor.thirdRefereeEhrenreich, Hannelore Prof. Dr. Dr.
dc.contributor.thirdRefereeGollisch, Tim Prof. Dr.
dc.contributor.thirdRefereeKagan, Igor Dr.
dc.subject.engmacaque monkeyde
dc.subject.engelectrophysiologyde
dc.subject.engmulti-electrode recordingde
dc.subject.engnetwork neurosciencede
dc.subject.engstate space analysesde
dc.subject.engsingle unitsde
dc.subject.engdecision makingde
dc.subject.engmotor systemsde
dc.subject.engoscillatory activityde
dc.subject.engnetwork topologyde
dc.subject.engpopulation subspacesde
dc.identifier.urnurn:nbn:de:gbv:7-11858/00-1735-0000-0023-3F10-3-3
dc.affiliation.instituteBiologische Fakultät für Biologie und Psychologiede
dc.subject.gokfullBiologie (PPN619462639)de
dc.identifier.ppn100609105X 1000147681


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