Everyone's Blog Posts - ConeroLab - brainbook

Embodied social cognition and mirror neurons? Is the "predictive brain" a precursor to the "social brain"?

2012-07-24T00:28:51.000Z

(FREE ARTICLE DOWNLOAD)

Could the neural basis of social interaction rely on the same neural processes as having expectations and making predictions about the future? Could a predictive coding framework of action, perception and learning be used to understand how the our brains are able to understand other people?

Research has shown that the brain is constantly making predictions about future events. Theories of prediction in perception, action and learning suggest that the brain serves to reduce the discrepancies between expectation and actual experience, i.e., by reducing the prediction error. Forward models of action and perception propose the generation of a predictive internal representation of the expected sensory outcome, which is matched to the actual sensory feedback. Shared neural representations have been found when experiencing one's own and observing other's actions, rewards, errors, and emotions such as fear and pain. These general principles of the “predictive brain” are well established and have already begun to be applied to social aspects of cognition.

New article just published and would be keen to hear others' opinions:

http://www.frontiersin.org/Human_Neuroscience/10.3389/fnhum.2012.00147/abstract

Structure and Function in the Brain

2010-04-15T23:30:00.000Z

Over the past decade, scientific interest in the properties of large-scale spontaneous neural dynamics has intensified. Nowadays, morphological data available are more detailed and theoretical arguments further support the notion that brain network topology and spatial embedding should strongly influence network dynamics.
In a recent publication, Honey and coll. illustrates how computational modeling can help to better understand the relation of structural and functional architectures of the brain at different neural scales.

Link to the article: http://www.ncbi.nlm.nih.gov/pubmed/20116438

Dreaming and the brain

2010-01-19T15:46:12.000Z

A well-characterized overview the one presented by Yaval Nir and Giulio Tononi on dreaming physiology. The authors clarify some important phenomenological issues, pointing out remarkable open questions that contribute to enrich the the already increasing interest about consciousness and its links to sleep and dreaming.

Link to the article: http://tiny.cc/FcYec

The free-energy principle and the brain

2009-08-12T19:00:00.000Z

The possibility to describe brain functions according to the general laws of physics has increased the interest of many neuroscientists in last years.
In a recent review, Karl Friston explains the application of the free-energy principle ("a new perspective on old ideas") to brain physiology, underlying the importance of shaping interactions of the brain with the external environment in perception and action.

Link to the article: http://tinyurl.com/l844ac

Intentional dynamics and decision making

2009-05-18T19:30:00.000Z

During the past years, the application of non linear dynamics has made a breakthrough to brain studies, yielding to strong evidences about the existence of complex behavior, such as phase transitions, metastability, attractor landscapes in brain functioning. The identification of sudden jumps in cortical activity between different metastable brain states (“micro-states”) has led to identify cognition as a trajectory moving across convoluted attractor landscapes. In a recent paper published on Neural Network, Kozma and Freeman describe the role of such dynamics in decision making using a biologically-inspired KIV model, exploiting two different mathematical approaches (neuropercolation based on discrete random graph theory and ordinary differential equations in continuous space-time approach).

Link to paper: http://tinyurl.com/intentionalDynamics

Evolutionary Neural Gas (ENG) : A Model of Self Organizing Network from Input Categorization-Ignazio Licata & Luigi Lella

2009-04-27T16:09:37.000Z

Abstract: Despite their claimed biological plausibility, most self organizing networks have strict
topological constraints and consequently they cannot take into account a wide range of external
stimuli. Furthermore their evolution is conditioned by deterministic laws which often are not
correlated with the structural parameters and the global status of the network, as it should
happen in a real biological system. In nature the environmental inputs are noise a®ected and
\fuzzy". Which thing sets the problem to investigate the possibility of emergent behaviour in a
not strictly constrained net and subjected to di®erent inputs. It is here presented a new model of
Evolutionary Neural Gas (ENG) with any topological constraints, trained by probabilistic laws
depending on the local distortion errors and the network dimension. The network is considered
as a population of nodes that coexist in an ecosystem sharing local and global resources. Those
particular features allow the network to quickly adapt to the environment, according to its
dimensions. The ENG model analysis shows that the net evolves as a scale-free graph, and
justi¯es in a deeply physical sense- the term \gas" here used.
c°
Electronic Journal of Theoretical Physics. All rights reserved.4(14) 2007
Keywords: Self-Organizing Networks; Neural Gas; Scale-Free Graph; Information in Network
Functional Specialization
PACS (2006): 89.75.k, 89.75.Fb, 82.39.Rt,07.05.Mh, 84.35.+i, 87.23.n, 91.62.Np

Link: http://www.ejtp.com/articles/ejtpv4i14p31.pdf

Mathematics & Neuroscience

2009-04-16T19:54:35.000Z

As a mathematician I pose the following question:

Which one of your activities requires nontrivial mathematics?

In particular I will be happy to help if your activities involve discrete and nonlinear mathematics (for example in discrete time processes). Feel free to write me please

Nevio

Neuronal synchrony: Peculiarity and generality

2009-04-10T10:30:00.000Z

In this review, Nowotny and collaborators describe main concepts of neural synchrony in an elegant and accurate overview, highlighting the essential role of non-linear dynamics application to brain studies.

Link to paper: http://scitation.aip.org/getabs/servlet/GetabsServlet?prog=normal&id=CHAOEH000018000003037119000001&idtype=cvips&gifs=yes

Omaggio a Mauro Mancia "Psicoanalisi e neuroscienze" / Tribute to Mauro Mancia "Psychoanalysis and Neuroscience"

2009-04-02T12:00:00.000Z

Per chi è interessato alla 'neuropsicoanalisi' è consultabile on line il libro di Mauro Mancia "Psicoanalisi e neuroscienze".

A Mauro Mancia's book, "Psychoanalysis and Neuroscience", is available on-line to members who are interested to relationship between psychoanalysis and neuroscience.

Long-Term homeostasis of extracellular Glutamate across sleep and waking states

2009-03-27T18:36:57.000Z

Tononi and colleagues have investigated extracellular glutamate concentration in rat cortex during sleep, wake and sleep deprivation. They found that levels of glutamate increase progressively during wake and REM sleep and decrease in NREM sleep. Moreover, glutamate continues to increase in the first phase of sleep deprivation reaching a plateau and/or starting decrementing after a certain period of time. Glu levels and rate of change are also dependent on previous wake-sleep history.

http://www.jneurosci.org/cgi/content/abstract/29/3/620

A pseudo-equilibrium thermodynamic model of information processing in nonlinear brain dynamics.

2009-03-27T18:30:00.000Z

In recent years, there has been growing interest in the neuroscience community concerning application of non-linear dynamics to brain studies, in particular those concepts relating to the analysis of dissipative systems. In the following paper, Freeman presents a novel brain model that employs the properties of thermodynamic systems operating far from equilibrium, and that is analyzed by linearization near adaptive operating points using root locus techniques.

http://www.ncbi.nlm.nih.gov/pubmed/18249088?ordinalpos=13&itool=EntrezSystem2.PEntrez.Pubmed.Pubmed_ResultsPanel.Pubmed_DefaultReportPanel.Pubmed_RVDocSum

Explosive percolation in random networks

2009-03-13T10:30:00.000Z

Phase transitions are common phenomena in nature, but the underlying dynamics are matter of intense debate among scientists. Networks whose connections between elements are formed by a random process often undergo an abrupt phase transition called percolation, wherein around a critical point, the addition of a small number of connections leads a large fration of the network to be quickly bound together. Comprehending this process may have important applications, for example, it could be useful to understand brain dynamics occuring at the seizures onset.
http://www.sciencemag.org/cgi/content/abstract/323/5920/1453

Sleep and neuronal cell assemblies

2009-03-09T18:00:00.000Z

In a recent review, Kreuger e coll. claimed that sleep might be a property of nervous cell assemblies, which could be regulated at a local level in the brain, suggesting the intriguing hypothesis that whole-organism sleep could emerge as an emergent property of local network interactions.

http://www.nature.com/nrn/journal/v9/n12/abs/nrn2521.html