Averaging Transformations of Synaptic Potentials on Networks

The problem of the transformation of microscopic information to the macroscopic level is an intriguing challenge in computational neuroscience, but also of general mathematical importance. Here, a phenomenological mathematical model is introduced that simulates the internal information processing of brain compartments. Synaptic potentials are integrated over small number of realistically coupled neurons to obtain macroscopic quantities. The striatal complex, an important part of the basal ganglia circuit in the brain for regulating motor activity, has been investigated as an example for the validation of the model

Steep, Spatially Graded Recruitment of Feedback Inhibition by Sparse Dentate Granule Cell Activity

The dentate gyrus of the hippocampus is thought to subserve important physiological functions, such as 'pattern separation'. In chronic temporal lobe epilepsy, the dentate gyrus constitutes a strong inhibitory gate for the propagation of seizure activity into the hippocampus proper. Both examples are thought to depend critically on a steep recruitment of feedback inhibition by active dentate granule cells. Here, I used two complementary experimental approaches to quantitatively investigate the recruitment of feedback inhibition in the dentate gyrus. I showed that the activity of approximately 4% of granule cells suffices to recruit maximal feedback inhibition within the local circuit. Furthermore, the inhibition elicited by a local population of granule cells is distributed non-uniformly over the extent of the granule cell layer. Locally and remotely activated inhibition differ in several key aspects, namely their amplitude, recruitment, latency and kinetic properties. Finally, I show that net feedback inhibition facilitates during repetitive stimulation. Taken together, these data provide the first quantitative functional description of a canonical feedback inhibitory microcircuit motif. They establish that sparse granule cell activity, within the range observed in-vivo, steeply recruits spatially and temporally graded feedback inhibition

Changes in the Striatal Network Connectivity in Parkinsonian and Dyskinetic Rodent Models

In Parkinson’s disease, there is a loss of dopaminergic innervation in the basal ganglia. The lack of dopamine produces substantial changes in neural plasticity and generates pathological activity patterns between basal ganglia nuclei. The treatment to relieve Parkinsonism is the administration of levodopa. However, the treatment produces dyskinesia. The question to answer is how the interactions between neurons change in the brain microcircuits under these pathological conditions. Calcium imaging is a way to record the activity of dozens of neurons simultaneously with single-cell resolution in brain slices from rodents. We studied these interactions in the striatum, since it is the nucleus of the basal ganglia that receives the major dopaminergic innervation. We used network analysis, where each active neuron is taken as a node and its coactivity with other neurons is taken as its functional connections. The network obtained represents the functional connectome of the striatal microcircuit, which can be characterized with a small set of parameters taken from graph theory. We then quantify the pathological changes at the functional histological scale and the differences between normal and pathological conditions

Specific disruption of hippocampal mossy fiber synapses in a mouse model of familial Alzheimer's disease.

The earliest stages of Alzheimer's disease (AD) are characterized by deficits in memory and cognition indicating hippocampal pathology. While it is now recognized that synapse dysfunction precedes the hallmark pathological findings of AD, it is unclear if specific hippocampal synapses are particularly vulnerable. Since the mossy fiber (MF) synapse between dentate gyrus (DG) and CA3 regions underlies critical functions disrupted in AD, we utilized serial block-face electron microscopy (SBEM) to analyze MF microcircuitry in a mouse model of familial Alzheimer's disease (FAD). FAD mutant MF terminal complexes were severely disrupted compared to control - they were smaller, contacted fewer postsynaptic spines and had greater numbers of presynaptic filopodial processes. Multi-headed CA3 dendritic spines in the FAD mutant condition were reduced in complexity and had significantly smaller sites of synaptic contact. Significantly, there was no change in the volume of classical dendritic spines at neighboring inputs to CA3 neurons suggesting input-specific defects in the early course of AD related pathology. These data indicate a specific vulnerability of the DG-CA3 network in AD pathogenesis and demonstrate the utility of SBEM to assess circuit specific alterations in mouse models of human disease

A proposal for a coordinated effort for the determination of brainwide neuroanatomical connectivity in model organisms at a mesoscopic scale

In this era of complete genomes, our knowledge of neuroanatomical circuitry remains surprisingly sparse. Such knowledge is however critical both for basic and clinical research into brain function. Here we advocate for a concerted effort to fill this gap, through systematic, experimental mapping of neural circuits at a mesoscopic scale of resolution suitable for comprehensive, brain-wide coverage, using injections of tracers or viral vectors. We detail the scientific and medical rationale and briefly review existing knowledge and experimental techniques. We define a set of desiderata, including brain-wide coverage; validated and extensible experimental techniques suitable for standardization and automation; centralized, open access data repository; compatibility with existing resources, and tractability with current informatics technology. We discuss a hypothetical but tractable plan for mouse, additional efforts for the macaque, and technique development for human. We estimate that the mouse connectivity project could be completed within five years with a comparatively modest budget.Comment: 41 page

An Integrated Micro- and Macroarchitectural Analysis of the Drosophila Brain by Computer-Assisted Serial Section Electron Microscopy

A new software package allows for dense electron microscopy reconstructions of neuronal networks in the fruit fly brain, and reveals specific differences in microcircuits between insects and vertebrates

Cortical Plasticity during Motor Learning and Recovery after Ischemic Stroke

The motor system has the ability to adapt to environmental constraints and injury to itself. This adaptation is often referred to as a form of plasticity allowing for livelong acquisition of new movements and for recovery after stroke. We are not sure whether learning and recovery work via same or similar neural mechanisms. But, all these processes require widespread changes within the matrix of the brain. Here, basic mechanisms of these adaptations on the level of cortical circuitry and networks are reviewed. We focus on the motor cortices because their role in learning and recovery has been investigated more thoroughly than other brain regions