Neuroscience Stream

The stream “Neuroscience” introduces students, PhD students and young scientists to general Neuroscience and particular Computational Neuroscience fields from synaptic transmission up to neuro- & brain- computer interface, including single neuron level, small neural circuits, network and neural populations as well as overview of different structures and various functions of a brain.

The stream is positioned as an ‘introduction to’, thus it is the best opportunity for young scientists to learn about Neuroscience and Computational Neuroscience, take an overview of recent history of these fields from the ‘first hands’ as well as to be introduced to new trends such as Computational Neuropharmacology, Computational Psychiatry and Computational Social Science. The stream is oriented to ordinary audience with the background in natural sciences.

Students of the stream will get wise to the latest innovation research by distinguished world-known neuroscience specialists.

Program

Lectures:

From multicompartment models to Computational Psychiatry (6 h)
From cellular neurophysiology to nonlinear neural network and oscillations (6 h)
The neurotransmitter systems of the brain and their function. Neurotransmitters in neurological and psychiatric diseases (6 h)
Neuron-Computer Interface in Dynamic-Clamp Experiments. Models of Neuronal Populations and Visual Cortex (4 h)
Brain-Computer Interface. Technology and Its Applications (4 h)
Elements of Theory for Multi-Neuronal Systems (4 h)
Circadian clock in mammals: electrical activity and its synchronization (4 h)
Dynamical Principles of Rhythm Generation (4h)
Amazing auditory system. Nervous system from oscillatory point of view (4 h)
Models of Associative Memory: Consolidation, Reconsolidation, and Synaptic Plasticity(2 h)
Molecular Mechanisms of Pain (2h)
Fluorescent Proteins in Current Biology (1h)
Analysis of calcium regulatory networks in neurons: experimental and modeling approaches (1h)

Practice:

Practical activity with Neuron, Genesis and XPP (4 h).

Excursion:

Visit to O.O. Bohomoletz Institute of Physiology NSAU.

Tutor	Course
Dr. Pavel Belan Bogomolets Institute of Physiology of the NASU, Kyiv, Ukraine	Fluorescent Proteins in Current Biology The course will be devoted to a breakthrough in current biology based on the combination of genetic and optical methods to record and control specific events in targeted living cells. A brief introduction will be given to ideas and current approaches behind fluorescent proteins, optical super-resolution techniques, quantum dots and optogenetics.
Dr. Evgenia Belova A.B. Kogan Research Institute for Neurocybernetics, Southern Federal University, Rostov-on-Don, Russia	The Neurotransmitter Systems of the Brain and Their Function These lectures deal with neurotransmitters, how their activity is involved in brain function. They allow students to comprehend essential information on the main classes of neurotransmitter and neuromodulators, namely: acetylcholine, glutamate, GABA, noradrenaline, dopamine, 5-hydroxytryptamine and the neuroactive peptides. After consideration of which substances can be classified as neurotransmitter and neuromodulator, and attention concentrates on certain basic features which characterize each class of substance: the biosynthesis, storage and release, as well as process of active reuptake or degradation. An overview of the particular receptors for different neurotransmitters and mechanisms of their interaction is included in these lectures. In addition, brain location, pathways and behavioral aspects of each neurotransmitter are covered in some detail. Neurotransmitters in Neurological and Psychiatric Diseases The lecture “Neurotransmitters in neurological and psychiatric diseases” is about the nature of the brain disorders. It covers how neurotransmitter systems of the brain are involved in initiation and manifestation of particular disease states, such as: Parkinson’s disease, epilepsy, schizophrenia, depression, Alzheimer’s disease. A special part of the lecture concentrates on seeing how the drugs which are used in these conditions produce their effects by modifying appropriative neurotransmitter function. Still, the goal of this lecture remains to gain far more insightful views of the question how the brain operates. *neurotransmitters - endogenous chemicals transmitting signals from a neuron to a target cell across a synapse.
Dr. Anton Chizhov Ioffe Physical Technical Institute of the Russian Academy of Sciences, Saint Petersburg, Russia	Neuron-Computer Interface in Dynamic-Clamp Experiments. Models of Neuronal Populations and Visual Cortex The lectures describe biophysically detailed Hodgkin-Huxley-like models of neurons, their properties and reductions. The properties are essential to control a neuron in a real time during experimental intracellular registrations by dynamic-clamp technique. The technique provides a new tool for electro-physiological studies and can be considered as an example of brain-computer interface systems. Then, the statistical ensemble of neurons and its different models, starting from the detailed ones, belonging to the probability density approach, and coming to the simplest, firing-rate type models are considered. A hierarchy of models of interacting populations in the visual cortex will be described as an example.
Prof. Gennady S. Cymbalyuk Dynamical Neuroscience Laboratory, Neuroscience Institute, Georgia State University, Atlanta, USA	Dynamical Principles of Rhythm Generation The course will describe dynamics of single neurons and oscillatory neuronal networks controlling rhythmic movements, Central Pattern Generators. First lecture titled “Neurons at rest and in action” will introduce basic regimes of activity of neurons: rest states, sub-threshold oscillations, tonic spiking, and bursting and describe dynamical mechanisms supporting multistability of these regimes. The second lecture, “Dynamics of Central Pattern Generators” will discuss basic dynamical principles underlying control of rhythmic activity in oscillatory neuronal networks. We will introduce mechanisms supporting bursting activity and the laws of dynamics describing the temporal characteristics of the neuronal activity in the proximity of the bifurcations.
Prof. Prof. Witali Dunin-Barkowski Department of Neuroinformatics, Center for Optical Neural Technologies, Scientific Research Institute for System Analysis, Russian Academy of Sciences	Elements of Theory for Multi-Neuronal Systems Part 1. Representation of continuous values in neuronal systems. Inputs and outputs of neural systems as well as sometimes structures located deep inside them using the neural impulses frequency code for continuous variables. In models, the code is often substituted with continuous variables, stripped off the impulses. Two cases of multi-neuronal representation of continuous variables — the parallel and the sequential ones are examined in this part. Qualitative and quantitative properties of the multi-neuronal coding of continuous variables are considered in detail. Part 2. Informational evaluations of neuralsystems. The theory for evaluation of informational efficiency and informational capacity of neuronal systems in theoretical models and physiological experiments are presented. Finally, the plausible roadmap is shortly discussed.
Prof. Péter Érdi Center for Complex Systems Studies, Department of Physics, Department of Psychology, Kalamazoo College, USA; Budapest Complex Systems and Computational Neuroscience Group, Institute for Particle and Nuclear Physics Wigner Research Centre for Physics, Hungarian Academy of Sciences, Hungary; BCSC: Budapest Semester in Cognitive Science	The course consists of the following lectures: Multicompartment and Stochastic Models Cybernetics, AI, Cognitive Science and Computational Neuroscience: Historical Aspects Computational Psychiatry / Computational Neuropharmacology Computational Social Science
Prof. Alexander Frolov Mathematical Neurobiology of Learning Lab, Institute of Higher Nervous Activity and Neurophisiology of RAS, Moscow, Russia	Brain-Computer Interface Technology and Its Applications A brain-computer interface (BCI) provides a direct functional interaction between human brain activity and external device. Principal BCI scheme and brain signals relevant to its performance as well as two types of BCI - gradual and discrete ones are elucidated on the lectures. The consideration of the performance of BCIs based on two types of mental tasks (to get more detailed information, please, look up the course description) is given. Motor imagination known nowadays as an efficient rehabilitation procedure to restore movement in paralysis is also considered on the lectures. The application of BCI based on motor imagination to perform a rehabilitation of neurological patients is especially discussed. Detailed information
Dr. Nikolai Kononenko Department of General Physiology of Nervous System, Institute of Physiology, Kyiv, Ukraine	Searching of a Membrane Target for Mammalian Circadian Clock Responsible for Circadian Modulation of Firing Rate: Role of Subthreshold, Voltage-Dependent Cation Single Channels The lectures are devoted to the problems of cellular and molecular mechanisms of the circadian clock implementation in the mammalian organisms and are based on the experimental data obtained from longterm electrophysiological recordings in multielectrode dishes. The primary biological clock regulating circadian rhythms in mammals is discussed on this lecture.
Dr. Dmitry Nowicki Institute of Problems of Mathematical Machines and Systems, Institute of Cybernetics of NAS of Ukraine; Department of Computer Science, University of Massachusetts, USA	Models of Associative Memory: Consolidation, Reconsolidation, and Synaptic Plasticity In this course we present various memory reconsolidation models based on attractor networks of associative memory (AM). Reconsolidation is a phenomenon where memory is liable and can be updated during retrieval. The functional role of reconsolidation seems to be the ability to adapt to changing inputs and associate them with older symbols. Reconsolidation is indeed implicated in learning and adaptive behavior (when healthy) and leads to amnesia and compulsive disorders (when corrupted). Reconsolidation has been observed both in neurophysiological and psychological studies and modeled in artificial neural systems. We will describe computational models of spike-time dependent synaptic plasticity (STPD) which is closely related to reconsolidation. Also we consider a specific attractor network called Kernel Associative Memory. This network uses kernel approach that is used in support vector machines (SVM). With help of this model we demonstrate how reconsolidation works on visual stimuli and consider its applications to some practical tasks
Prof. John Rinzel Center for Neural Science, New York University, New York, USA; Tsinghua University, Beijing, China	The lectures of the course highlight: Cellular Neurophysiology and Modeling The lecture presents a well-known model of Action Potential and a method of a model dynamics analysis allowing to distinguish neuron activity into different types. The Cable Properties of Neurons The lecture introduces an area of dendrite tree spatial representation in neuron modeling. It is focused on the dendrite geometry influence on neuron somatic activity and the reason neurons have an active membrane. Nonlinear Dynamics of Network Excitability and Oscillations It is devoted to formulation of the mean field models for firing rate dynamics and applications of this theory in the phenomena of real neuronal activities description. Step by Step into the Computational Neuroscience History An additional lecture.
Dr. Elena Saftenku Department of General Physiology of Nervous System, Bogomoletz Institute of Physiology of the NASU, Kyiv, Ukraine	Analysis of Calcium Regulatory Networks in Neurons: Experimental and Modeling Approaches Importance of Ca2+ in cellular function. Ca2+ dynamics, fluxes and regulatory networks. General features and differences of Ca2+ signaling in neurons and non-neuronal cells. Classification of neuronal Ca2+ models: from microdomains to whole neurons. Distinction between phenomenological and experimentally determined description of transport and buffering. How can we separate Ca2+ fluxes? Realistic description of Ca2+ buffers. Heterogeneous distribution of Ca2+ handling systems.
Dr. Ruben Tikidji-Hamburyan A.B. Kogan Research Institute for Neurocybernetics, Southern Federal University, Rostov-on-Don, Russia; Louisiana State University, Health Sciences Center, New Orleans, USA	Amazing Auditory System The auditory sensory system may be considered as the most intriguing for animals and humans sensitivity of perceiving the surrounding space. To overcome obstacles while processing auditory signals the nerve system invented Fourier transformation, coherent analysis and many other useful tools which were later re-discovered by humans. These lectures will briefly introduce structure and function of auditory system and mainly focus on problem of sound source localization. Detailed Model of Visual Cortex The prominent model of cat visual cortex was published in 2005 by Sean Hill and Giulio Tononi. Model consists of more than 65000 neurons and several million connections. Model could sleep or awake, and showed specific neuronal activity during slow-wave sleep. We will use description of this model to talk about sleeping and waking conditions, to understand how nervous system works in different regimes, what mechanisms support these activities. Nervous System from Oscillatory Point of View In many Brain regions, we can observe oscillatory activity. Specific waves propagate through the cortex and hippocampus during sleep and main cognitive function. In this lecture we consider how to apply phase resetting theory to describe and predict an interaction of periodical processes in brain. To reach our goal we simplify neuron's behavior up to one dimension function, so called phase resetting curve (PRC). Through the concrete example of cross-frequency entrainment in feed-forward network we examine how to employ PRC approach to explain various phenomena of synchronization, phase-locking and modulation. Practical Activity with Neuron, Genesis and XPP Detailed information about the course will be available later.
Dr. Nana Voitenko Department of Molecular Physiology and Biophysics, Physics and Technology Center of the NASU, Kyiv, Ukraine	Molecular Mechanisms of Pain The importance of understanding the ways how the central nervous system can alter incoming signals that relate to pain stimulated a lot of investigations. It is found that molecular mechanisms are leading to changes in patterns of action potential generation in primary neurones, modification of synaptic transmission between primary central afferents. These mechanisms of pain are the subject of this lecture.

Tutor

Course

Dr. Pavel Belan
Bogomolets Institute of Physiology of the NASU, Kyiv, Ukraine

Fluorescent Proteins in Current Biology

The course will be devoted to a breakthrough in current biology based on the combination of genetic and optical methods to record and control specific events in targeted living cells. A brief introduction will be given to ideas and current approaches behind fluorescent proteins, optical super-resolution techniques, quantum dots and optogenetics.

Dr. Evgenia Belova
A.B. Kogan Research Institute for Neurocybernetics, Southern Federal University, Rostov-on-Don, Russia

The Neurotransmitter Systems of the Brain and Their Function

These lectures deal with neurotransmitters, how their activity is involved in brain function. They allow students to comprehend essential information on the main classes of neurotransmitter and neuromodulators, namely: acetylcholine, glutamate, GABA, noradrenaline, dopamine, 5-hydroxytryptamine and the neuroactive peptides. After consideration of which substances can be classified as neurotransmitter and neuromodulator, and attention concentrates on certain basic features which characterize each class of substance: the biosynthesis, storage and release, as well as process of active reuptake or degradation. An overview of the particular receptors for different neurotransmitters and mechanisms of their interaction is included in these lectures. In addition, brain location, pathways and behavioral aspects of each neurotransmitter are covered in some detail.

Neurotransmitters in Neurological and Psychiatric Diseases

The lecture “Neurotransmitters in neurological and psychiatric diseases” is about the nature of the brain disorders. It covers how neurotransmitter systems of the brain are involved in initiation and manifestation of particular disease states, such as: Parkinson’s disease, epilepsy, schizophrenia, depression, Alzheimer’s disease. A special part of the lecture concentrates on seeing how the drugs which are used in these conditions produce their effects by modifying appropriative neurotransmitter function. Still, the goal of this lecture remains to gain far more insightful views of the question how the brain operates.

*neurotransmitters - endogenous chemicals transmitting signals from a neuron to a target cell across a synapse.

Dr. Anton Chizhov
Ioffe Physical Technical Institute of the Russian Academy of Sciences, Saint Petersburg, Russia

Neuron-Computer Interface in Dynamic-Clamp Experiments. Models of Neuronal Populations and Visual Cortex

The lectures describe biophysically detailed Hodgkin-Huxley-like models of neurons, their properties and reductions. The properties are essential to control a neuron in a real time during experimental intracellular registrations by dynamic-clamp technique. The technique provides a new tool for electro-physiological studies and can be considered as an example of brain-computer interface systems. Then, the statistical ensemble of neurons and its different models, starting from the detailed ones, belonging to the probability density approach, and coming to the simplest, firing-rate type models are considered.

A hierarchy of models of interacting populations in the visual cortex will be described as an example.

Prof. Gennady S. Cymbalyuk
Dynamical Neuroscience Laboratory, Neuroscience Institute, Georgia State University, Atlanta, USA

Dynamical Principles of Rhythm Generation

The course will describe dynamics of single neurons and oscillatory neuronal networks controlling rhythmic movements, Central Pattern Generators.

First lecture titled “Neurons at rest and in action” will introduce basic regimes of activity of neurons: rest states, sub-threshold oscillations, tonic spiking, and bursting and describe dynamical mechanisms supporting multistability of these regimes.

The second lecture, “Dynamics of Central Pattern Generators” will discuss basic dynamical principles underlying control of rhythmic activity in oscillatory neuronal networks. We will introduce mechanisms supporting bursting activity and the laws of dynamics describing the temporal characteristics of the neuronal activity in the proximity of the bifurcations.

Prof. Prof. Witali Dunin-Barkowski
Department of Neuroinformatics, Center for Optical Neural Technologies, Scientific Research Institute for System Analysis, Russian Academy of Sciences

Elements of Theory for Multi-Neuronal Systems

Part 1. Representation of continuous values in neuronal systems. Inputs and outputs of neural systems as well as sometimes structures located deep inside them using the neural impulses frequency code for continuous variables. In models, the code is often substituted with continuous variables, stripped off the impulses. Two cases of multi-neuronal representation of continuous variables — the parallel and the sequential ones are examined in this part. Qualitative and quantitative properties of the multi-neuronal coding of continuous variables are considered in detail.

Part 2. Informational evaluations of neuralsystems. The theory for evaluation of informational efficiency and informational capacity of neuronal systems in theoretical models and physiological experiments are presented. Finally, the plausible roadmap is shortly discussed.

Prof. Péter Érdi
Center for Complex Systems Studies, Department of Physics, Department of Psychology, Kalamazoo College, USA; Budapest Complex Systems and Computational Neuroscience Group, Institute for Particle and Nuclear Physics Wigner Research Centre for Physics, Hungarian Academy of Sciences, Hungary; BCSC: Budapest Semester in Cognitive Science

The course consists of the following lectures:

Multicompartment and Stochastic Models

Cybernetics, AI, Cognitive Science and Computational Neuroscience: Historical Aspects

Computational Psychiatry / Computational Neuropharmacology

Computational Social Science

Prof. Alexander Frolov
Mathematical Neurobiology of Learning Lab, Institute of Higher Nervous Activity and Neurophisiology of RAS, Moscow, Russia

Brain-Computer Interface Technology and Its Applications

A brain-computer interface (BCI) provides a direct functional interaction between human brain activity and external device. Principal BCI scheme and brain signals relevant to its performance as well as two types of BCI - gradual and discrete ones are elucidated on the lectures.

The consideration of the performance of BCIs based on two types of mental tasks (to get more detailed information, please, look up the course description) is given.

Motor imagination known nowadays as an efficient rehabilitation procedure to restore movement in paralysis is also considered on the lectures. The application of BCI based on motor imagination to perform a rehabilitation of neurological patients is especially discussed.

Detailed information

Dr. Nikolai Kononenko
Department of General Physiology of Nervous System, Institute of Physiology, Kyiv, Ukraine

Searching of a Membrane Target for Mammalian Circadian Clock Responsible for Circadian Modulation of Firing Rate: Role of Subthreshold, Voltage-Dependent Cation Single Channels

The lectures are devoted to the problems of cellular and molecular mechanisms of the circadian clock implementation in the mammalian organisms and are based on the experimental data obtained from longterm electrophysiological recordings in multielectrode dishes. The primary biological clock regulating circadian rhythms in mammals is discussed on this lecture.

Dr. Dmitry Nowicki
Institute of Problems of Mathematical Machines and Systems, Institute of Cybernetics of NAS of Ukraine; Department of Computer Science, University of Massachusetts, USA

Models of Associative Memory: Consolidation, Reconsolidation, and Synaptic Plasticity

In this course we present various memory reconsolidation models based on attractor networks of associative memory (AM). Reconsolidation is a phenomenon where memory is liable and can be updated during retrieval. The functional role of reconsolidation seems to be the ability to adapt to changing inputs and associate them with older symbols.

Reconsolidation is indeed implicated in learning and adaptive behavior (when healthy) and leads to amnesia and compulsive disorders (when corrupted). Reconsolidation has been observed both in neurophysiological and psychological studies and modeled in artificial neural systems.

We will describe computational models of spike-time dependent synaptic plasticity (STPD) which is closely related to reconsolidation.

Also we consider a specific attractor network called Kernel Associative Memory. This network uses kernel approach that is used in support vector machines (SVM). With help of this model we demonstrate how reconsolidation works on visual stimuli and consider its applications to some practical tasks

Prof. John Rinzel
Center for Neural Science, New York University, New York, USA; Tsinghua University, Beijing, China

The lectures of the course highlight:

Cellular Neurophysiology and Modeling

The lecture presents a well-known model of Action Potential and a method of a model dynamics analysis allowing to distinguish neuron activity into different types.

The Cable Properties of Neurons

The lecture introduces an area of dendrite tree spatial representation in neuron modeling. It is focused on the dendrite geometry influence on neuron somatic activity and the reason neurons have an active membrane.

Nonlinear Dynamics of Network Excitability and Oscillations

It is devoted to formulation of the mean field models for firing rate dynamics and applications of this theory in the phenomena of real neuronal activities description.

Step by Step into the Computational Neuroscience History

An additional lecture.

Dr. Elena Saftenku
Department of General Physiology of Nervous System, Bogomoletz Institute of Physiology of the NASU, Kyiv, Ukraine

Analysis of Calcium Regulatory Networks in Neurons: Experimental and Modeling Approaches

Importance of Ca2+ in cellular function.
Ca2+ dynamics, fluxes and regulatory networks.
General features and differences of Ca2+ signaling in neurons and non-neuronal cells.
Classification of neuronal Ca2+ models: from microdomains to whole neurons.
Distinction between phenomenological and experimentally determined description of transport and buffering.
1. How can we separate Ca2+ fluxes?
2. Realistic description of Ca2+ buffers.
3. Heterogeneous distribution of Ca2+ handling systems.

Dr. Ruben Tikidji-Hamburyan
A.B. Kogan Research Institute for Neurocybernetics, Southern Federal University, Rostov-on-Don, Russia; Louisiana State University, Health Sciences Center, New Orleans, USA

Amazing Auditory System

The auditory sensory system may be considered as the most intriguing for animals and humans sensitivity of perceiving the surrounding space. To overcome obstacles while processing auditory signals the nerve system invented Fourier transformation, coherent analysis and many other useful tools which were later re-discovered by humans. These lectures will briefly introduce structure and function of auditory system and mainly focus on problem of sound source localization.

Detailed Model of Visual Cortex

The prominent model of cat visual cortex was published in 2005 by Sean Hill and Giulio Tononi. Model consists of more than 65000 neurons and several million connections. Model could sleep or awake, and showed specific neuronal activity during slow-wave sleep.

We will use description of this model to talk about sleeping and waking conditions, to understand how nervous system works in different regimes, what mechanisms support these activities.

Nervous System from Oscillatory Point of View

In many Brain regions, we can observe oscillatory activity. Specific waves propagate through the cortex and hippocampus during sleep and main cognitive function. In this lecture we consider how to apply phase resetting theory to describe and predict an interaction of periodical processes in brain. To reach our goal we simplify neuron's behavior up to one dimension function, so called phase resetting curve (PRC). Through the concrete example of cross-frequency entrainment in feed-forward network we examine how to employ PRC approach to explain various phenomena of synchronization, phase-locking and modulation.

Practical Activity with Neuron, Genesis and XPP

Detailed information about the course will be available later.

Dr. Nana Voitenko
Department of Molecular Physiology and Biophysics, Physics and Technology Center of the NASU, Kyiv, Ukraine

Molecular Mechanisms of Pain

The importance of understanding the ways how the central nervous system can alter incoming signals that relate to pain stimulated a lot of investigations. It is found that molecular mechanisms are leading to changes in patterns of action potential generation in primary neurones, modification of synaptic transmission between primary central afferents. These mechanisms of pain are the subject of this lecture.

AACIMP-2012 Leaflet

AACIMP-2012 Booklet