Past events

We assume that while preforming any higher brain function, multiple cortical regions interact with some fairly fixed temporal order. This type of process needs to be studied with a resolution of a few ms. Such sequences of coordinated activities amongst multiple cortical locations was revealed in ongoing activity with milliseconds accuracy. That was achieved without the need for averaging over time or frequencies. The analysis was based on recording MEG and reconstructing the cortical current-dipole-amplitudes at multiple points. In these current-dipole traces instances of brief activity undulations were automatically detected and used to reveal where and when cortical points interact.

Some of the fascinating features of voltage-sensing domains (VSD) in voltage-gated cation channels (VGCC) are their modular nature and adaptability. Here we examined the VSD promiscuity of VGCC, using non-toxin gating-modifiers, NH17 and NH29, which share closely related structures and stabilize Kv7.2 potassium channels, in the closed and open state, respectively. NH17 and NH29 exert opposite gating-modifier effects on TRPV1 channels, operating respectively, as an activator and a blocker of TRPV1 currents. Combined mutagenesis and electrophysiology, structural homology modeling, molecular docking and molecular dynamics simulation indicate that both compounds target the VSD of TRPV1 channels, which like vanilloids are involved in π-π stacking, H-bonding and hydrophobic interactions. Reflecting the VSD promiscuity, they also affect the lone VSD proton channel mVSOP. Remarkably, NH29 alleviates neuropathic pain in rats, suggesting that sometimes, promiscuous VSD ligands may be therapeutically beneficial. Thus, structurally related, yet different molecules can interact with the VSD of the same VGCC, while the same gating-modifier can promiscuously interact with different VGCC. Subtle differences at the VSD-ligand interface will dictate whether the gating-modifier stabilizes channels in either the closed or the open state.

Since the discovery of place cells in the hippocampus, a variety of experimental observations have pointed to the complexity of hippocampal circuit dynamics and their importance in memory related tasks. During spatial navigation, place cell activity predicts the upcoming animal location within the short time scale of individual cycles of theta oscillations. Sudden changes of the spatial context are followed by a bistability between population coding of past and current context, paced by the theta rhythm. During immobility, brief sequences of place cell activation encode spatial trajectories, which have been linked to learning in spatial memory tasks and goal-directed navigation. Finally, when the animal is engaged in a delayed memory task, hippocampal cells fire at specific time intervals within the delay period and the activity of a population of cells is predictive of the behavioral outcome. I will present a unified attractor network model that accounts for this wide range of experimental observations. A critical component of the model is the use of realistic synapses that exhibit short-term plasticity driven by presynaptic activity. Complexity in the network dynamics emerges due to the effect of history dependent synaptic states on the network activity. Model predictions, possible extensions of the model and its relationship to dynamics observed in other cortical areas will be discussed.

Angelman syndrome (AS) is a human neuropsychiatric disorder associated with autism, mental retardation, motor dysfunction, and epilepsy. In most cases, AS is caused by the deletion of small portions of chromosome 15, which includes the UBE3A gene. The UBE3A gene encodes an enzyme termed ubiquitin ligase E3A. A mouse model of AS has been generated and these mice exhibit abnormalities that correlate with neurological alterations observed in humans with AS. One of the prominent affected brain regions in AS is the hippocampus. We characterized the CA1 pyramidal neurons in the AS mice, and observed alterations in the intrinsic membrane properties of these cells between AS mice and their wild-type littermates. These alterations were correlated with increased expression of specific proteins, mainly related to the axon initial segment (AIS). Furthermore, the AIS morphology of these neurons in the AS mice was also found to be altered. By determining the temporal sequence for the increased expression of these proteins we have discovered the precipitating event for the observed AIS alterations which coincides with the homeostatic model of the neuron. Finally, we rescued the hippocampal pathology via a genetic manipulation based on this understanding. Taken together, our findings are the first to suggest that AIS plasticity alterations exist in mammalian brain in-vivo and could be involved in neuropsychiatric disorders such as AS. They also offer a novel conceptualization of neuropsychiatric disorders and propose the option for an innovative therapeutic strategy.

Uncertainty is inherent to any situation we encounter. Our individual attitudes towards uncertainty strongly affect our evaluation of different available options and our behavior based on these evaluations. In the talk I will describe a series of studies in which we combine experimental economics and other behavioral methods with functional MRI to study the behavioral and neural characteristics of attitudes towards uncertainty and learning under uncertainty.

In Huntington’s disease (HD) – a devastating autosomal-dominant neurodegenerative disease – the striatum displays reduced cholinergic markers, despite the resiliency of cholinergic interneurons (ChIs) – the source of striatal acetylcholine – to the neurodegeneration that decimates striatal projection neurons. Autonomous spiking of ChIs is unchanged in transgenic HD mice, suggesting a functional deficit in extrinsically driven activity. Using two transgenic mouse models of HD, we show that ChI responses to cortical input are boosted by a post-synaptic up-regulation of the persistent sodium current. This boosting is replicated by in wild-type mice by diminished activation of group I metabotropic glutamate receptors (mGluRs). Activation of group I mGluRs in HD mice counters the boosting. We propose that the recently described loss of thalamic synapses in striatum, reduces group I mGluR activation in ChIs which promotes boosting of cortical inputs. The augmentation of cortical inputs may function to compensate for the lost thalamic glutamatergic drive.

Most neurons involved in perceptual judgments are at least two synapses removed from sensory receptors. Psychophysical models that link perception to the physical qualities of external stimuli are thus black boxes. Opening these black boxes is challenging and requires comprehensive estimates of activity in many neurons carrying perceptually relevant signals. Because sensory representations are distributed over large numbers of neurons, such estimates have generally remained elusive. Here, we take advantage of the well-characterized olfactory system of fruit flies to relate knowledge of the neuronal population representations of odors to behavioral measures of odor discrimination. Flies detect odors using ~50 types of olfactory receptor neurons (ORNs). ORN axons segregate anatomically by receptor type and transmit signals via separate synaptic relays, to discrete classes of excitatory projection neurons (ePNs). Previously, ORN responses to odors and a transformation estimating PN spike rates from measured ORN spike rates were presented. ePNs project to the mushroom body, and the lateral horn (LH). The LH, thought to be responsible of naïve behavior, also receives input from a functionally uncharacterized group of GABAergic inhibitory PNs (iPNs). The fact that iPNs target exclusively the LH hints at a possible function of these inhibitory neurons in naïve behavior. We formulate and test a simple model of innate odor discrimination that takes as its input the estimated PN signals projected onto the LH and generates as its output a prediction of whether two odors can be distinguished. We show that the main determinant of discriminability is the distance between the PN activity patterns evoked by two odors. Experimental manipulations of this distance have graded predictable perceptual consequences. We further show that, inhibition by iPNs makes closely related odors easier to distinguish, in all likelihood by imposing a high-pass filter on ePN output that stretches the distances between partially overlapping odor representations.