29th Annual Computational Neuroscience Meeting: CNS*2020

Meeting abstracts This publication was funded by OCNS. The Supplement Editors declare that they have no competing interests. Virtual | 18-22 July 202

26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3 - Meeting Abstracts - Antwerp, Belgium. 15–20 July 2017

This work was produced as part of the activities of FAPESP Research,\ud Disseminations and Innovation Center for Neuromathematics (grant\ud 2013/07699-0, S. Paulo Research Foundation). NLK is supported by a\ud FAPESP postdoctoral fellowship (grant 2016/03855-5). ACR is partially\ud supported by a CNPq fellowship (grant 306251/2014-0)

Identification and neuromodulation of brain states to promote recovery of consciousness

Experimental and clinical studies of consciousness identify brain states (i.e., transient, relevant features of the brain associated with the state of consciousness) in a non-systematic manner and largely independent from the research into the induction of state changes. In this narrative review with a focus on patients with a disorder of consciousness (DoC), we synthesize advances on the identification of brain states associated with consciousness in animal models and physiological (sleep), pharmacological (anesthesia) and pathological (DoC) states of altered consciousness in human. We show that in reduced consciousness the frequencies in which the brain operates are slowed down and that the pattern of functional communication in the brain is sparser, less efficient, and less complex. The results also highlight damaged resting state networks, in particular the default mode network, decreased connectivity in long-range connections and in the thalamocortical loops. Next, we show that therapeutic approaches to treat DoC, through pharmacology (e.g., amantadine, zolpidem), and (non-)invasive brain stimulation (e.g., transcranial current stimulation, deep brain stimulation) have shown some effectiveness to promote consciousness recovery. It seems that these deteriorated features of conscious brain states may improve in response to these neuromodulation approaches, yet, targeting often remains non-specific and does not always lead to (behavioral) improvements. Furthermore, in silico model-based approaches allow the development of personalized assessment of the effect of treatment on brain-wide dynamics. Although still in infancy, the fields of brain state identification and neuromodulation of brain states in relation to consciousness are showing fascinating developments that, when united, might propel the development of new and better targeted techniques for DoC. For example, brain states could be identified in a predictive setting, and the theoretical and empirical testing (i.e., in animals, under anesthesia and patients with a DoC) of neuromodulation techniques to promote consciousness could be investigated. This review further helps to identify where challenges and opportunities lay for the maturation of brain state research in the context of states of consciousness. Finally, it aids in recognizing possibilities and obstacles for the clinical translation of these diagnostic techniques and neuromodulation treatment options across both the multi-modal and multi-species approaches outlined throughout the review. This paper presents interactive figures, supported by the Live Paper initiative of the Human Brain Project, enabling the interaction with data and figures illustrating the concepts in the paper through EBRAINS (go to https://wiki.ebrains.eu/bin/view/Collabs/live-paper-states-altered-consciousness and get started with an EBRAINS account).NA is research fellow, OG is Research Associate, and SL is research director at FRS-FNRS. JA is postdoctoral fellow at the FWO. The study was further supported by the University and University Hospital of Liège, the BIAL Foundation, the Belgian National Funds for Scientific Research (FRS-FNRS), the European Union's Horizon 2020 Framework Programme for Research and Innovation under the Specific Grant Agreement No. 945539 (Human Brain Project SGA3), the FNRS PDR project (T.0134.21), the ERA-Net FLAG-ERA JTC2021 project ModelDXConsciousness (Human Brain Project Partnering Project), the fund Generet, the King Baudouin Foundation, the Télévie Foundation, the European Space Agency (ESA) and the Belgian Federal Science Policy Office (BELSPO) in the framework of the PRODEX Programme, the Public Utility Foundation 'Université Européenne du Travail', "Fondazione Europea di Ricerca Biomedica", the BIAL Foundation, the Mind Science Foundation, the European Commission, the Fondation Leon Fredericq, the Mind-Care foundation, the DOCMA project (EU-H2020-MSCA–RISE–778234), the National Natural Science Foundation of China (Joint Research Project 81471100) and the European Foundation of Biomedical Research FERB Onlus

Graded lines: using genetic variation in neuronal projections to understand functional organization

In this thesis, I investigated the interactions between brain regions in mice, with an emphasis on the motor system. Whilst brain areas are typically studied in isolation, they exist to act upon one other, and we lack even relatively basic principles of how brain areas interact. Here, my colleagues and I used new genetic techniques to investigate this topic. There were two major focuses. Firstly, I investigated how thalamic pathways vary, using genetic sequencing to produce a high dimensional transcriptomic profile of forebrain communication pathways. This revealed a strikingly simple organisational system in rodent thalamus, with pathways serving diverse modalities varying in a common manner. Pathways serving systems as variable as vision, navigation, motor control and somatosensation showed a similar variation in gene expression, which was functionally relevant. This establishes a common reference frame for diverse modalities of cognition. Secondly, I began an ongoing investigation of the signals that motor cortex send to subcortical motor structures. This revealed a separation of signals that project to the basal ganglia and cerebellum, opposite to existing predictions. Basal Ganglia-projecting signals encoded motor execution, whilst cerebellar projecting pathways encoded preparation- and reward-related information. These experiments motivated further investigation of these pathways, which are described within. Together, these results demonstrate the utility of focussing upon interactions between network nodes to reveal the contribution of individual nodes.HHM

Interaction between limbic circuits and basal ganglia in behaviour inhibition

Changing behaviour in response to changing internal and external situations is crucial for survival. In particular, we need to inhibit ongoing, unwanted or inappropriate behaviour. Behavioural inhibition includes inhibition of an ongoing action, thought or emotion (in the basal ganglia; BG). But it can also involve inhibition of goals (in the limbic system) – which is much slower. A better understanding of the neural mechanisms controlling inhibition of behaviour is important for cognitive neuroscience, particularly in relation to problems of impulsivity. This thesis aims to fill a gap in our understanding of behavioural inhibition and to elucidate the parallel circuits that control its different types. Several lesion, neuroimaging, and electrophysiological studies have been conducted to understand the role of brain regions in behavioural inhibition. Previous research has identified roles for the BG, orbitofrontal cortex (OFC) and hippocampus (HPC) in generation of various frequencies of rhythmicity during behavioural inhibition. However, the interaction between these regions has not been studied in rats during simple learning, simple action inhibition and complex behavioural inhibition. The stop signal task (SST) is the most commonly used paradigm to study simple behavioural inhibition. In this study, I recorded local field potentials (LFPs) simultaneously from BG (particularly striatum; STR and subthalamic nucleus; STN), OFC and HPC while rats performed the SST to assess how simple action inhibition differs from complex behavioural inhibition linked to goal-conflict. The data show increases in the STN LFP spectral beta power and coherence with OFC after stopping an ongoing action (simple stopping). In contrast, stop failure increased HPC-STN coherent activity in the theta frequency band. In addition to the HPC, goal-conflict also activates OFC and STN during high conflict at higher theta frequency (11-12 Hz). In contrast, the conflict induced coherence effect was seen at lower theta frequencies (5-8 Hz) between two pairs of STN (HPC-STN and OFC-STN). The results from the various experiments suggest that part of BG (STR and STN) and limbic system work in parallel and in a dynamic way for learning, response inhibition and complex behavioural inhibition (approach-avoidance conflict). The HPC is not involved in simple motor learning but may receive motivational information form STR and OFC. Simple inhibition involves mainly cortex and BG, while complex inhibition during goal-conflict also involves HPC, OFC and STN. Interestingly, goal inhibition appears to access circuits involved in simple stopping via OFC. In conclusion, functional connections between limbic and BG provides an adaptive control, so that goal selection (limbic structures) and programming of motor action (BG) can operate in parallel

A Search For Principles of Basal Ganglia Function

The basal ganglia are a group of subcortical nuclei that contain about 100 million neurons in humans. Different modes of basal ganglia dysfunction lead to Parkinson's disease and Huntington's disease, which have debilitating motor and cognitive symptoms. However, despite intensive study, both the internal computational mechanisms of the basal ganglia, and their contribution to normal brain function, have been elusive. The goal of this thesis is to identify basic principles that underlie basal ganglia function, with a focus on signal representation, computation, dynamics, and plasticity. This process begins with a review of two current hypotheses of normal basal ganglia function, one being that they automatically select actions on the basis of past reinforcement, and the other that they compress cortical signals that tend to occur in conjunction with reinforcement. It is argued that a wide range of experimental data are consistent with these mechanisms operating in series, and that in this configuration, compression makes selection practical in natural environments. Although experimental work is outside the present scope, an experimental means of testing this proposal in the future is suggested. The remainder of the thesis builds on Eliasmith & Anderson's Neural Engineering Framework (NEF), which provides an integrated theoretical account of computation, representation, and dynamics in large neural circuits. The NEF provides considerable insight into basal ganglia function, but its explanatory power is potentially limited by two assumptions that the basal ganglia violate. First, like most large-network models, the NEF assumes that neurons integrate multiple synaptic inputs in a linear manner. However, synaptic integration in the basal ganglia is nonlinear in several respects. Three modes of nonlinearity are examined, including nonlinear interactions between dendritic branches, nonlinear integration within terminal branches, and nonlinear conductance-current relationships. The first mode is shown to affect neuron tuning. The other two modes are shown to enable alternative computational mechanisms that facilitate learning, and make computation more flexible, respectively. Secondly, while the NEF assumes that the feedforward dynamics of individual neurons are dominated by the dynamics of post-synaptic current, many basal ganglia neurons also exhibit prominent spike-generation dynamics, including adaptation, bursting, and hysterses. Of these, it is shown that the NEF theory of network dynamics applies fairly directly to certain cases of firing-rate adaptation. However, more complex dynamics, including nonlinear dynamics that are diverse across a population, can be described using the NEF equations for representation. In particular, a neuron's response can be characterized in terms of a more complex function that extends over both present and past inputs. It is therefore straightforward to apply NEF methods to interpret the effects of complex cell dynamics at the network level. The role of spike timing in basal ganglia function is also examined. Although the basal ganglia have been interpreted in the past to perform computations on the basis of mean firing rates (over windows of tens or hundreds of milliseconds) it has recently become clear that patterns of spikes on finer timescales are also functionally relevant. Past work has shown that precise spike times in sensory systems contain stimulus-related information, but there has been little study of how post-synaptic neurons might use this information. It is shown that essentially any neuron can use this information to perform flexible computations, and that these computations do not require spike timing that is very precise. As a consequence, irregular and highly-variable firing patterns can drive behaviour with which they have no detectable correlation. Most of the projection neurons in the basal ganglia are inhibitory, and the effect of one nucleus on another is classically interpreted as subtractive or divisive. Theoretically, very flexible computations can be performed within a projection if each presynaptic neuron can both excite and inhibit its targets, but this is hardly ever the case physiologically. However, it is shown here that equivalent computational flexibility is supported by inhibitory projections in the basal ganglia, as a simple consequence of inhibitory collaterals in the target nuclei. Finally, the relationship between population coding and synaptic plasticity is discussed. It is shown that Hebbian plasticity, in conjunction with lateral connections, determines both the dimension of the population code and the tuning of neuron responses within the coded space. These results permit a straightforward interpretation of the effects of synaptic plasticity on information processing at the network level. Together with the NEF, these new results provide a rich set of theoretical principles through which the dominant physiological factors that affect basal ganglia function can be more clearly understood