All events, All years

Theoretical models of grid cell dynamics and coding in the rat entorhinal cortex

Lecture
Date:
Monday, January 4, 2010
Hour: 11:00
Location:
Nella and Leon Benoziyo Building for Brain Research
Dr. Yoram Burak
|
Center for Brain Science Harvard University

Grid cells in the rat entorhinal cortex display strikingly regular firing responses to the animal's position in 2-D space, and have been hypothesized to form the neural substrate for dead-reckoning. I will address two theoretical questions that arise from this remarkable experimental discovery: First, how is grid cell dynamics generated in the brain. Second, what information is conveyed in grid cell activity. In discussing the first question, I will focus on continuous-attractor models of grid cell activity, and ask whether such models can generate regular triangular grid responses based on inputs that encode only the rat's velocity and heading direction. In a recent work, we provided a proof of concept that such models can accurately integrate velocity inputs, along trajectories spanning 10-100 meters in length and lasting 1-10 minutes. The range of accurate integration depends on various properties of the continous-attractor network. After presenting these results, I will discuss possible experiments that may differentiate the continuous-attractor model from other proposed models, where activity arises independently in each cell. In the second part of the talk, I will examine the relationship between grid cell firing and rat location, asking what information is present in grid-cell activity about the rat's position. I will argue that, although the periodic response of grid cells may appear wasteful, the grid-cell code is in fact combinatorial in capacity, and allows for unambiguous position representations over ranges vastly larger than the ~0.5-10m periods of individual lattices. Further, the grid cell representation has properties that could facilitate the arithmetic computation involved in position updating during path integration. I will conclude by mentioning some of the implications for downstream readouts, and possible experimental tests.

Sound Texture Perception via Synthesis

Lecture
Date:
Sunday, January 3, 2010
Hour: 14:30
Location:
Nella and Leon Benoziyo Building for Brain Research
Dr. Josh McDermott
|
New York University

Many natural sounds, such as those produced by rainstorms, fires, and swarms of insects, result from large numbers of rapidly occurring acoustic events. Such “sound textures” are often temporally homogeneous, and in many cases do not depend much on the precise arrangement of the component events, suggesting that they might be represented statistically. To test this idea and explore the statistics that might characterize natural sound textures, we designed an algorithm to synthesize sound textures from statistics extracted from real sounds. The algorithm is inspired by those used to synthesize visual textures, in which a set of statistical measurements from a real sound are imposed on a sample of noise. This process is iterated, and converges over time to a sound that obeys the chosen constraints. If the statistics capture the perceptually important properties of the texture in question, the synthesized result ought to sound like the original sound. We tested whether rudimentary statistics computed from the responses of a bank of bandpass filters could produce compelling synthetic textures. Simply matching the marginal statistics (variance, kurtosis) of individual filter responses was generally insufficient to yield good results, but imposing various joint envelope statistics (correlations between bands, and autocorrelations within each band) greatly improved the results, frequently producing synthetic textures that sounded natural and that subjects could reliably recognize. The results suggest that statistical representations could underlie sound texture perception, and that in many cases the auditory system may rely on fairly simple statistics to recognize real world sound textures. Joint work with Andrew Oxenham and Eero Simoncelli.

PKMzeta and the core molecular mechanism of long-term memory storage and erasure

Lecture
Date:
Tuesday, December 29, 2009
Hour: 12:30
Location:
Jacob Ziskind Building
Prof. Todd Sacktor
|
SUNY Downstate Medical Center, Brooklyn, NY

How long-term memories are stored as physical traces in the brain is a fundamental question in neuroscience. Most molecular work on LTP, a widely studied physiological model of memory, has focused on the early signaling events regulating new protein synthesis that mediates initial LTP induction. But what are the newly synthesized proteins that function in LTP maintenance, how do they sustain synaptic potentiation, and do they store long-term memory? Recent studies have identified a brain-specific, autonomously active, atypical PKC isoform, PKMzeta, that is central to the mechanism maintaining the late phase of LTP. In behavioral experiments, the persistent activity of PKMzeta maintains spatial memories in hippocampus, fear-motivated memories in amygdala, and, in work performed in the Dudai lab, elementary associative memories in neocortex. This is because 1-day to several month-old memories appear to be rapidly erased after local intracranial PKMzeta inhibition. PKMzeta, a persistently active enzyme, is thus the first identified molecular component of the long-term memory trace.

Plasticity in high level visual cortex: insights from development and fMRI-adaptation

Lecture
Date:
Tuesday, December 22, 2009
Hour: 12:30
Location:
Jacob Ziskind Building
Dr. Kalanit Grill-Spector
|
Dept of Psychology and Neurosciences Institute Stanford University, CA

The human ventral stream consists of regions in the lateral and ventral aspects of the occipital and temporal lobes and is involved in visual recognition. One robust characteristic of selectivity in the adult human ventral stream is category selectivity. Category selectivity is manifested by both a regional preference to particular object categories, such as faces, places and bodyparts, as well as in specific (and reproducible) distributed response patterns across the ventral stream for different object categories. However, it is not well understood how these representations come about throughout development and how experience modifies these representations and how do. I will describe two sets of experiments in which we addressed these important questions. First, I will describe experiments in which we examined changes in category selectivity throughout development from middle childhood (7-11 years), through adolescence (12-16) into adulthood. Surprisingly, we find that it takes more than a decade for the development of adult-like face and place-selective regions. In contrast, the lateral occipital object-selective region showed an adult-like profile by age 7. Further, recent findings from our research indicate that face-selective regions have a particularly prolonged development as they continue develop through adolescence in correlation with improved face, but not object or scene recognition memory. Development manifests as increases in the size of face-selective regions, increases in face-selectivity as well as increases in the distinctiveness of distributed response patterns to faces compared to nonfaces. Second, I will describe experiments in adults in which we examined the effect of repetition on categorical responses in the ventral stream. Repeating objects decreases responses in the human ventral stream. Repetition in lateral ventral regions manifests as a proportional effects in which responses to repeated objects are a constant fraction of nonrepeating stimuli with no change in selectivity. In contrast in medial ventral temporal cortex, we find differential effects across time scales whereby immediate repetitions produce proportional effects, but long-lagged repetitions sharpen responses, increasing category selectivity. Finally, I will discuss the implications of these results on plasticity in the ventral stream and our theoretical models linking between fMRI measurements and the underlying neural mechanisms.

Ongoing Dynamics and Brain Connectivity: From Intracellular Recordings to Human Neurophysiology

Lecture
Date:
Tuesday, December 15, 2009
Hour: 12:30
Location:
Jacob Ziskind Building
Dr. Amos Arieli
|
Department of Neurobiology, WIS

What is the temporal precision of cortical activity? It is clear that the wide range of coding schemes occur on different time scales: Millisecond scale characterizes direct sensory events, tens to hundreds of milliseconds scale characterizes attention processes, while different states of alertness can last many seconds. It seems that there is a direct relationship between the time scale and the spatial resolution in cortical activity. The activity involved in a direct sensory process is well defined in small areas; for example an orientation column. On the other hand an attention process involves huge populations and maybe even the whole cortex. In my talk I will try to bridge the gap between the recordings of single neurons (intracellular and extracellular recordings) and the recordings of large populations of neurons (EEG, LFP,VSD or fMRI) in order to understand the spatio-temporal organization underlying the function of cortical neuronal population and it's relation to brain connectivity. I will relate to the following topics: - What is the size of the neuronal population that contributes to the population activity in different cognitive states? - What is the degree of synchronization within this population? - What is the relationship between the population activity and the activity of single cortical neurons? - The dynamic of coherent activity in neuronal assemblies - ongoing & evoked activity

Long-term relationships between network activity, synaptic tenacity and synaptic remodeling in networks of cortical neurons

Lecture
Date:
Tuesday, December 8, 2009
Hour: 12:30
Location:
Jacob Ziskind Building
Dr. Noam Ziv
|
Dept of Physiology, Rappaport Faculty of Medicine Technion, Haifa

The human brain consists of a vast number of neurons interconnected by specialized communication devices known as synapses. It is widely believed that activity-dependent modifications to synaptic connections - synaptic plasticity - represents a fundamental mechanism for altering network function, giving rise to emergent phenomena commonly referred to as learning and memory. This belief also implies, however, that synapses, when not driven to change their properties by physiologically relevant stimuli, should retain these properties over time. Otherwise, physiologically relevant modifications would be gradually lost amidst spurious changes and spontaneous drift. We refer to the expected default tendency of synapses to hold onto their properties as "synaptic tenacity". We have begun to examine the degree to which synaptic structures are indeed tenacious. To that end we have developed unique, long-term imaging technologies that allow us to record the remodeling of individual synaptic specializations in networks of dissociated cortical neurons over many days and even weeks at temporal resolutions of 10-30 minutes, and at the same time record and manipulate the levels of activity in the same networks. These approaches have allowed us to uncover intriguing relationships between network activity, synaptic tenacity and synaptic remodeling. These experiments and the insights they have provided will be described.

Second Nachmansohn Memorial Symposium: Molecular Approaches to the Nervous System

Conference
Date:
Wednesday, November 25, 2009
Hour:
Location:

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Computational Model of Spatio-Temporal Cortical Activity in V1: Mechanisms Underlying Observations of Voltage Sensitive Dyes

Lecture
Date:
Thursday, October 29, 2009
Hour: 12:30
Location:
Jacob Ziskind Building
Prof. David McLaughlin
|
Provost and Professor of Mathematics and Neuroscience New York University

To investigate the existence and the characteristics of possible cortical operating points of the primary visual cortex, as manifested by the coherent spontaneous ongoing activity revealed by real-time optical imaging based on voltage-sensitive dyes, we studied numerically a very large-scale (_5 _ 105) conductancebased, integrate-and-fire neuronal network model of an _16-mm2 patch of 64 orientation hypercolumns, which incorporates both isotropic local couplings and lateral orientation-specific long-range connections with a slow NMDA component. A dynamic scenario of an intermittent desuppressed state (IDS) is identified in the computational model, which is a dynamic state of (i) high conductance, (ii) strong inhibition, and (iii) large fluctuations that arise from intermittent spiking events that are strongly correlated in time as well as in orientation domains, with the correlation time of the fluctuations controlled by the NMDA decay time scale. Our simulation results demonstrate that the IDS state captures numerically many aspects of experimental observation related to spontaneous ongoing activity, and the specific network mechanism of the IDS may suggest cortical mechanisms and the cortical operating point underlying observed spontaneous activity.In addition, we address the functional significance of the IDS cortical operating points by investigating our model cortex response to the Hikosaka linemotion illusion (LMI) stimulus—a cue of a quickly flashed stationary square followed a few milliseconds later by a stationary bar. As revealed by voltage-sensitive dye imaging, there is an intriguing similarity between the cortical spatiotemporal activity in response to (i) the Hikosaka LMI stimulus and (ii) a small moving square. This similarity is believed to be associated with the preattentive illusory motion perception. Our numerical cortex produces similar spatiotemporal patterns in response to the two stimuli above, which are both in very good agreement with experimental results. The essential network mechanisms underpinning the LMI phenomenon in our model are (i) the spatiotemporal structure of the LMI input as sculpted by the lateral geniculate nucleus, (ii) a priming effect of the long-range NMDA-type cortical coupling, and (iii) the NMDA conductance–voltage correlation manifested in the IDS state. This mechanism in our model cortex, in turn, suggests a physiological underpinning for the LMI-associated patterns in the visual cortex of anaesthetized cat.

Locust swarms and their immunity

Lecture
Date:
Sunday, October 4, 2009
Hour: 12:30
Location:
Nella and Leon Benoziyo Building for Brain Research
Gabriel Miller
|
Harvard University

Locusts are arguably the most notorious pests in history, directly affecting the livelihood of 1 in 10 people worldwide. These fascinating insects exhibit dramatic phenotypic plasticity in response to environmental fluctuation, changing from shy and cryptic 'solitarious' forms to brightly-colored and swarming 'gregarious' forms. How do these swarms form? What triggers this phenotypic switch? I will discuss how the experience of locust females influences the phenotype of her offspring, and how the 'gregarizing factor' underlying this maternal effect was isolated, purified, and partially characterized. Finally, I present field and laboratory data suggesting that swarm formation (and this gregarizing factor) affects locust immune function.

Learning in Recurrent Networks with Spike-Timing Dependent Plasticity

Lecture
Date:
Wednesday, September 23, 2009
Hour: 12:30
Location:
Nella and Leon Benoziyo Building for Brain Research
Prof. Klaus Pawelzik
|
Institute for Theoretical Physics, Dept of Neuro-Physics University of Bremen, Germany

Memory contents are believed to be stored in the efficiency of synapses in recurrent networks of the brain. In prefrontal cortex it was found that short and long term memory is accompanied with persistent spike rates [1,2] indicating that reentrant activities in recurrent networks reflect the content of synaptically encoded memories [3]. It is, however, not clear which mechanisms enable synapses to sequentially accumulate information from the stream of patterned inputs which under natural conditions enter as perturbations of the ongoing neuronal activities. For successful incremental learning only novel input should alter specific synaptic efficacies while previous memories should be preserved as long as network capacity is not exhausted. In other words, synaptic learning should realise a palimpsest property with erasing the oldest memories first. Here we demonstrate that synaptic modifications which sensitively depend on /temporal changes /of pre- and the post-synaptic neural activity can enable such incremental learning in recurrent neuronal networks. We investigated a realistic rate based model and found that for robust incremental learning in a setting with sequentially presented input patterns specific adaptation mechanisms of STDP are required that go beyond the observed synaptic changes for sequences of pre- and post-synaptic spikes [4]. Our predicted pre- and post-synaptic adaptation of synaptic changes in response to respective rate changes are experimentally testable and --if confirmed-- would suggest that STDP provides an unsupervised learning mechanism particularly well suited for incremental memory acquisition by circumventing the stability-plasticity dilemma.

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Movement selectivity in the human mirror system

Lecture
Date:
Tuesday, July 28, 2009
Hour: 12:30
Location:
Jacob Ziskind Building
Ilan Dinstein New York University Visiting PhD Student – Malach Lab

Abstract: “Monkey mirror neurons are unique visuomotor neurons that respond when executing a particular movement (e.g. grasping, placing, or manipulating) and also when passively observing someone else performing that same movement. Importantly, subpopulations of mirror neurons respond in a selective manner to one preferred movement whether executed or observed. It has been proposed that the activity of mirror neurons underlies the monkey’s ability to perceive the goals and intentions of others. Human mirror neurons are thought to exist in two cortical areas, the anterior intraparietal sulcus (aIPS) and the ventral premotor (vPM), which have been called the human mirror system. A dysfunction in the responses of this system has been hypothesized to cause impairment in the ability to understand one another resulting in Autism. I will talk about three studies where we characterized the responses of the human mirror system using fMRI adaptation and classification techniques to assess their response selectivity for observed and executed hand movements. Two studies were performed with neurotypical individuals and the third with Autistic individuals.”

Role of Dopamine in Reward: Anatomical and Conceptual Issues

Lecture
Date:
Tuesday, July 14, 2009
Hour: 12:30
Location:
Jacob Ziskind Building
Dr. Satoshi Ikemoto NIDA (Nat. Inst. on Drug Abuse) Behavioral Neuroscience Research Branch NIH, USA

Abstract: The mesolimbic dopamine system from the ventral tegmental area (VTA) to the ventral striatum has been implicated in reward. Using intracranial self-administration procedures, we found that rats learn to self-administer cocaine or amphetamine into the medial portion of the ventral striatum more readily than the lateral ventral striatum. Rats learn to self-administer drugs such as opiates and cholinergic drugs into the posterior portion of the VTA more readily than the anterior VTA. Axonal tracer experiments revealed that the medial ventral striatum is preferentially innervated by dopamine neurons localized in the posterior VTA, while the lateral ventral striatum is preferentially innervated by dopamine neurons in the anterolateral VTA. Therefore, the mesolimbic dopamine system from the posterior VTA to the medial ventral striatum appears to be more responsive for rewarding effects of drugs. In addition, we have studied the nature of the rewarding effects of drugs. We found that noncontingent administration of cocaine or amphetamine into the medial ventral striatum increases leverpressing, when leverpressing contingently elicits visual signals. These results suggest that a function of dopamine in the ventral striatum is to facilitate actions in response to salient stimuli. Dopamine in the medial ventral striatum also appears to facilitate associative learning as shown by conditioned place preference of cocaine. We suggest that ventral striatal dopamine induces an arousing state that facilitates ongoing appetitive responding and reinforcement.

Collective Motion and Decision-Making in Animal Groups

Lecture
Date:
Thursday, July 9, 2009
Hour: 12:30
Location:
Nella and Leon Benoziyo Building for Brain Research
Prof. Iain Couzin
|
Dept of Ecology and Evolutionary Biology and Program in Computational and Mathematical Biology Princeton University USA

Grouping organisms, such as schooling fish, often have to make rapid decisions in uncertain and dangerous environments. Decision-making by individuals within such aggregates is so seamlessly integrated that it has been associated with the concept of a “collective mind”. As each organism has relatively local sensing ability, coordinated animal groups have evolved collective strategies that allow individuals to access higher-order computational abilities at the collective level. Using a combined theoretical and experimental approach involving insect and vertebrate groups, I will address how, and why, individuals move in unison and investigate the principles of information transfer in these groups, particularly focusing on leadership and collective consensus decision-making. An integrated "hybrid swarm" technology is introduced in which multiple robot-controlled replica individuals interact within real groups allowing us new insights into group coordination. These results will be discussed in the context of the evolution of collective biological systems.

Neuronal Avalanches in the Cortex:A Case for Criticality

Lecture
Date:
Tuesday, July 7, 2009
Hour: 15:00
Location:
Arthur and Rochelle Belfer Building for Biomedical Research
Prof. Dietmar Plenz
|
Laboratory of Systems Neuroscience NIMH, USA

Complex systems, when poised near a critical point of a phase transition between order and disorder, exhibit scale-free, power law dynamics. Critical systems are highly adaptive and flexibly process and store information, which prompted the conjecture that the cortex might operate at criticality. This view is supported by the recent discovery of neuronal avalanches in superficial layers of cortex. The spatiotemporal, synchronized activity patterns of avalanches form a scale-free organization that spontaneously emerges in vitro as well as in vivo in the anesthetized rat and awake monkeys. Avalanches are established at the time of superficial layer differentiation, require balanced fast excitation and inhibition, and are regulated via an inverted-U profile of NMDA/dopamine-D1 interaction. Neuronal synchronization in the form of avalanches naturally incorporates nested theta/gamma-oscillations as well as sequential activations as proposed for synfire chains. Importantly, a singleavalanche is not an isolated network event, but rather its specific occurrence in time, its spatial spread, and overall size is part of an elementary organization of the dynamics that is described by three fundamental power laws. Overall, these results suggest that neuronal avalanches indicate a critical network dynamics at which the cortex gains universal properties found at criticality. These properties constitute a novel framework that allow for a precise quantification of cortex function such as the absolute discrimination of pathological from non-pathological synchronization, and the identification of maximal dynamic range for input-output processing.

Critical thoughts on critical periods: Are children better than adults at acquiring skills?

Lecture
Date:
Tuesday, July 7, 2009
Hour: 12:30
Location:
Jacob Ziskind Building
Prof. Avi Karni
|
Department of Human Biology University of Haifa

Physiological studies of the functional architecture of the basal ganglia neural networks

Lecture
Date:
Tuesday, June 30, 2009
Hour: 12:30
Location:
Jacob Ziskind Building
Prof. Hagai Bergman
|
Dept of Physiology and The Interdisciplinary Center for Neural Computation Hebrew University, Jerusalem

The basal ganglia (BG) are commonly viewed as two functionally related subsystems. These are the neuromodulators subsystem and the main-axis subsystem, in analogy with the critic-actor division of reinforcement learning agent. We propose that the BG main axis is performing dimensionality reduction of the cortical input leading to optimal trade-off between maximization of future cumulative reward and minimization of the cost (information bottleneck). In line with the information bottleneck dimensionality reduction model, BG main axis neurons maintain flat spike crosscorrelation functions, diverse responses to behavioral events, and broadly distributed values of signal and response correlations with zero population mean. On the other hand, the spontaneous and the evoked activity of BG dopaminergic and cholinergic modulators (critics) are significantly correlated. BG plasticity and learning are therefore controlled by homogenous modulators effects associated with local coincidences of cortico-striatal activity.

Brain and Reality: How Does the Brain Generate Perceptions and Actions

Lecture
Date:
Tuesday, June 23, 2009
Hour: 12:30
Location:
Jacob Ziskind Building
Prof. Eilon Vaadia
|
Dept of Medical Neurobiology Hadassah Medical School Hebrew University, Jerusalem

Evoked neural synchrony, visual attention and grouping

Lecture
Date:
Tuesday, June 16, 2009
Hour: 12:30
Location:
Jacob Ziskind Building
Prof. Marius Usher
|
Dept of Psychology, Tel Aviv University

Neural synchrony was proposed as a mechanism for visual attention, and more controversially, for grouping and figure-ground processing. In this talk I will first present evidence showing that evoked Gamma synchrony, via 50Hz subliminal flicker produces attentional orientation in the absence of awareness. Second, I will present data on the effects of evoked synchrony on grouping and figure-ground processing. The results indicate a fast temporal resolution for these processes (<20ms), which is mediated by lateral connections and which is sensitive to synchrony, but not to sustained oscillations of a specific frequency. Collaboration with: S Cheadle, F Bauer, H Mueller.

Large-scale brain dynamics: Functional MRI of spontaneous and optically-driven neural activity

Lecture
Date:
Monday, June 15, 2009
Hour: 12:45
Location:
Arthur and Rochelle Belfer Building for Biomedical Research
Dr. Itamar Kahn
|
Howard Hughes Medical Institute Harvard University

A fundamental problem in brain research is how distributed brain systems work together to give rise to behavior. I seek to advance our understanding of principles underlying the dynamic interaction between multiple neural systems, how the different systems co-operate and/or compete to give rise to goal-directed behavior, and the dynamics of the system when one or more of its components fail. Magnetic resonance imaging (MRI) methods allow us to simultaneously measure the function of multiple brain systems. In humans we can characterize the functional organization and specialization, and compare the system between health and disease. In animal models we can further dissect the circuits underlying these dynamics. In my work I aim to identify functional networks that span multiple cortical and subcortical regions, characterize their responses in the presence and absence of overt behavior, and modulate the observed dynamics. To advance these goals, I am developing new tools that will allow us to study large-scale neural systems across species. In this talk, I will review recent studies that use functional neuroimaging in humans and animal models. I will describe how spontaneous fluctuations of the blood oxygenation level-dependent (BOLD) signal measured with MRI in awake resting humans, reveal functional subdivisions in the medial temporal lobe memory system and parietal and prefrontal cortical components linked to it. I will describe results from non-human primates demonstrating that this functional organization persists across the species, highlighting cortical components that have undergone considerable areal expansion in humans relative to non-human primates, how this method can be used to identify homologue regions, and more generally, what can be learned from a comparative perspective. In the second part of my talk I will describe recent efforts to selectively modulate system dynamics. A lentivirus was used to target excitatory neurons in the rat cortex with light-activated cation channel channelrhodopsin-2. Using photostimulation to activate these neurons we were able to drive the BOLD response locally and in regions anatomically connected to the infected site in a variety of stimulation paradigms. I will discuss implications for understanding the BOLD signal and prospects for this approach in studying the microcircuit as well as large-scale brain dynamics. Finally, I will discuss the challenges and promises of whole-brain imaging in small animals, and how this work can provide avenues to bridge between a basic understanding of human behavior, large-scale neural dynamics, and psychiatric disorders where such dynamics are disrupted.

Optical control of neural population activity and growth

Lecture
Date:
Tuesday, June 9, 2009
Hour: 12:30
Location:
Jacob Ziskind Building
Dr. Shy Shoham
|
Faculty of Biomedical Engineering Technion &#8211; I.I.T. Haifa

Retinal neuroprosthetics can potentially be used to address some of the major degenerative disorders that cause blindness, including Retinitis Pigmentosa and Macular Degeneration, by bypassing the degenerated photoreceptor layer, and interfacing directly the more viable Retinal Ganglion Cells (RGCs). I will describe the development of new optical and computational tools aimed at allowing controlled experimental emulation of activity patterns in a large population of retinal ganglion cells and their correlation structure. First, we introduce new optical systems allowing control of increasingly complex spatiotemporal activity patterns in neural populations, focusing on holographic photo-stimulation which has several fundamental advantages in this application. Next, we introduce a general new computational strategy based on correlation distortions, for controlling and analyzing the pair-wise correlation structure (defined in terms of auto- and cross-correlation functions) in multiple synthetic spike trains. This approach can be used to generate stationary or non-stationary network activity patterns with predictable spatio-temporal correlations. In a final part of the talk I will describe a new approach for exact, flexible control of neurite outgrowth in three-dimensional neural structures, and its possible applications.

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