Past events

Abstract: The PNN is a specialized form of extracellular matrix, initially deposited around selected neurons during critical periods of development in specific parts of the brain, interrupted by holes where synapses occur. We postulate that the PNN comprises a longer-lived structural template and that new memories are created by cutting new holes in the PNN or by expanding existing holes to enable formation of new synapses or to strengthen existing ones. A basic premise of this hypothesis is that the PNN, should undergo very low metabolic renewal from the first age at which memories are retained until senescence, whereas the active constituents of synapses turn over much more frequently and would therefore be poorer substrates for permanent information storage, unless they are equipped with incredibly accurate copying mechanisms (R.Y.Tsien PNAS 2013). Experimental tests of the hypothesis: 1.PNN longevity; using 15N Spirulina diet for Stable Isotope Labeling in Mammals (SILAM) we compare the lifetimes of PNN proteins vs. synaptic components in Enriched Environment (EE) vs. Conventional Cages (CC), ending the pulse-chase by changing to 14N diet at P45. Analysis by Multidimensional Protein Identification Technology (MudPIT) of four different brain areas indicate: a. Low turnover rate for PNN proteins while synaptic proteins were at the noise level of 15N /14N ratio. b. Higher turnover of PNN proteins in EE vs. CC cages c.Variability in the retention of 15N in PNN proteins between brain areas. 2.Localization of the long-lasting proteins; Imaging of 15N /14N ratio using Nanoscale secondary ion mass spectrometry (nanoSIMS) localized and verified the MudPit finding that PNN turnover is very slow. 3. Spatial occupation of the PNN holes; 2 dimension electron microscopy (EM) and 3D volumes of Serial Block Face Scanning EM reveal that neurons engulfed in PNN have more than 95% of their plasma membrane surface occupied by PNN or synapses. 4. Inhibition of PNN holes modulation during strong memories acquisition; we examined the role and timing of matrix metalloproteinases (MMP) activity in memory consolidation using pharmacological inhibitors in a fear-conditioning paradigm. Our results demonstrate that MMP inhibition during fear induction: a. Does not affect acquisition b. Significantly impairs long-term memory (30 days) c. Is dose dependent d. That memory impairment increases with time. So far the hypothesis is supported by the results of the above tests.

Research in the Ben-Shahar lab at Washington University in St. Louis is focused on several integrative projects at the interface of evolution, genetics, and neuroethology. Specifically, research in the lab follows two major themes: 1) The genetic and neuronal processes that regulate the interactions between individual animals and their social environment, including the evolution and signaling mechanisms associated with pheromonal communication in insects, and the neuronal circuits that drive pheromone-induced behaviors; 2) the molecular evolution and genetics of the neuronal stress response, with a specific focus on mechanistic tradeoffs between neuronal robustness and cognition.

Many visual tasks, such as separation of figures from ground and navigation, benefit from the extraction and the usage of local motion signals. Yet, there are many ways in which local motion signals are being represented (mostly based on mathematical and computational considerations). I’ll begin this talk by presenting a computational work that explored whether specific kinds of local motion signals occur in the natural world (Nitzany&Victor, 2014, Journal of Vision). Next, I will present the results of a neurophysiological experiment where we recorded from the main visual brain areas of two visually accomplished, but very different, animals—macaque monkeys and dragonflies. We found similar responses to local motion signals across species, which may serve as neurophysiologic evidence that mammalian visual cortex and the visual centers of the dragonfly brain process motion using similar algorithms and may have converged on a common computational scheme for detecting visual motion. Finally, I’ll present our current work, which extends and manipulates a few machine learning techniques to generate novel stimuli, where specific characteristics, with regards to local motion signals, are being preserved. If time permits, I will discuss another line of work (Menda et. al., 2014, Current Biology, Shamble et. al., 2016, Current Biology), where we were able to record from neurons of jumping spiders. I will explain our approach that enables us to record from those tiny marvelous creatures and review our main findings with regards to visual and auditory cues.

Voluntary movement initiation involves the modulation of large populations of motor cortical (M1) neurons around movement onset. Despite knowledge of the temporal dynamics of cortical ensembles that lead to movement, the spatial structure of these dynamics across the cortical sheet are poorly understood. Here, we show that the timing in attenuation of the beta frequency oscillation amplitude, a neural correlate of corticospinal excitability, forms a spatial gradient across M1 prior to movement onset with a defined beta attenuation orientation (BAO) from earlier to later attenuation times. We show that a similar propagating pattern is evident in the modulation times of populations of M1 neurons. Using various spatiotemporal patterns of intracortical microstimulation, we find that movement initiation is significantly slowed when stimulation is delivered against the BAO suggesting that movement initiation requires a precise spatio-temporal recruitment pattern in M1.

Following a stroke or damage to the central nervous system, deficits in motor planning and execution may ensue, leading to a reduced capacity to use the affected upper limb to meaningfully interact with objects in the environment. A framework of disordered motor control based on reduced threshold control will be presented and considered together with cognitive and perceptual deficits underlying movement deficits.