Biology subjects

Aertsen, A.

Publications and source records attributed to Aertsen, A..

3 recordsLinked to original sources

bioRxiv2018

From space to time: Spatial inhomogeneities lead to the emergence of spatio-temporal activity sequences in spiking neuronal networks

Spatio-temporal sequences of neuronal activity are observed in many brain regions in a variety of tasks and are thought to form the basis of any meaningful behavior. Mechanisms by which a neuronal network can generate spatio-temporal activity sequences have remained obscure. Existing models are biologically untenable because they require manual embedding of a feedforward network within a random network or supervised learning to train the connectivity of a network to generate sequences. Here, we propose a biologically plausible, generative rule to create spatio-temporal activity sequences in a network model of spiking neurons with distance dependent connectivity. We show that the emergence of spatio-temporal activity sequences requires: (1) individual neurons preferentially project a small fraction of their axons in a specific direction, and (2) the preferential projection direction of neighboring neurons is similar. Thus, an anisotropic but correlated connectivity of neuron groups suffices to generate spatio-temporal activity sequences in an otherwise random neuronal network model.

neuroscience↗

bioRxiv2017

Sensorimotor Processing In The Basal Ganglia Leads To Transient Beta Oscillations During Behavior

Brief epochs of beta oscillations have been implicated in sensorimotor control in the basal ganglia of task-performing healthy animals. However, which neural processes underlie their generation and how they are affected by sensorimotor processing remains unclear. To determine the mechanisms underlying transient beta oscillations in the local field potential (LFP), we combined computational modeling of the subthalamo-pallidal network for the generation of beta oscillations with realistic stimulation patterns derived from single unit data. The single unit data were recorded from different basal ganglia subregions in rats performing a cued choice task. In the recordings we found distinct firing patterns in the striatum, globus pallidus and subthalamic nucleus related to sensory and motor events during the behavioral task. Using these firing patterns to generate realistic inputs to our network model lead to transient beta oscillations with the same time course as the rat LFP data. In addition, our model can account for further non-intuitive aspects of beta modulation, including beta phase resets following sensory cues and correlations with reaction time. Overall, our model can explain how the combination of temporally regulated sensory responses of the subthalamic nucleus, ramping activity of the subthalamic nucleus, and movement-related activity of the globus pallidus, leads to transient beta oscillations during behavior.\n\nSignificance StatementTransient beta oscillations emerge in the normal functioning cortico-basal ganglia loop during behavior. In this work we employ a unique approach connecting a computational model closely with experimental data. In this way we achieve a simulation environment for our model that mimics natural input patterns in awake behaving animals. Using this approach we demonstrate that a computational model for beta oscillations in Parkinsons disease can also account for complex patterns of transient beta oscillations in healthy animals. Therefore, we propose that transient beta oscillations in healthy animals share the same mechanism with pathological beta oscillations in Parkinsons disease. This important result connects functional and pathological roles of beta oscillations in the basal ganglia.

neuroscience↗

bioRxiv2016

Activity Dynamics and Signal Representation in Striatal Network Model with Distance-dependent Connectivity

Striatum is predominantly inhibitory and the main input nucleus of the basal ganglia. A functional characterization of its activity dynamics is crucial for understanding the mechanisms underlying phenomenon such as action selection and initiation. Here, we investigated the effects of the spatial connectivity structure on the emergence and maintenance of localized bumps of activity in large-scale striatal networks (~10,000 neurons). We show that in striatal network model in which the distance-dependent connection probability varies in a Gaussian fashion (Gaussian networks), the activity remains asynchronous irregular (AI) and spatially homogeneous, independent of the background input. By contrast, when the distance-dependent connectivity varies according to a Gamma distribution (Gamma networks), with short-range connectivity suppressed, a repertoire of activity dynamics can be observed: While weak background inputs induce spatially homogeneous AI activity, stronger background inputs induce stable, spatially localized activity bumps as in winner-take-all (WTA) dynamics. Interestingly, for intermediate background inputs, the networks exhibit spatially localized, but unstable activity bumps (Transition Activity, TA), resembling the experimentally observed neuronal assembly dynamics in the striatum.\n\nAmong the three main regimes of network activity (AI, WTA, TA) we found that in the AI and TA regimes, network dynamics are flexible and can be easily modified by external stimuli. Moreover, the dynamical state of the network returns to the baseline after the stimulus is removed. By contrast, the dynamics in the WTA state are rigid and can only be changed by very strong external stimuli. These results support the hypothesis that the flexibility of the striatal network state in response to stimuli is important for its normal function and the rigid network states (WTA) correspond to brain disorders such as Parkinsons disease, where the striatum looses its repertoire of dynamic states and is only receptive to very strong inputs.

neuroscience↗