Limits...
Inevitable evolutionary temporal elements in neural processing: a study based on evolutionary simulations.

Yerushalmi U, Teicher M - PLoS ONE (2008)

Bottom Line: In repeating evolutionary sessions, there was a significant increase during evolution in the mutual information between the evolved agent's temporal neural representation and the external environment.These results suggest that in some fitness landscapes the emergence of temporal elements in neural computation is almost inevitable.Future research using similar evolutionary simulations may shed new light on various biological mechanisms.

View Article: PubMed Central - PubMed

Affiliation: The Leslie and Susan Gonda Interdisciplinary Brain Research Center, Bar-Ilan University, Ramat-Gan, Israel. uri.yerushalmi@gmail.com

ABSTRACT
Recent studies have suggested that some neural computational mechanisms are based on the fine temporal structure of spiking activity. However, less effort has been devoted to investigating the evolutionary aspects of such mechanisms. In this paper we explore the issue of temporal neural computation from an evolutionary point of view, using a genetic simulation of the evolutionary development of neural systems. We evolve neural systems in an environment with selective pressure based on mate finding, and examine the temporal aspects of the evolved systems. In repeating evolutionary sessions, there was a significant increase during evolution in the mutual information between the evolved agent's temporal neural representation and the external environment. In ten different simulated evolutionary sessions, there was an increased effect of time-related neural ablations on the agents' fitness. These results suggest that in some fitness landscapes the emergence of temporal elements in neural computation is almost inevitable. Future research using similar evolutionary simulations may shed new light on various biological mechanisms.

Show MeSH

Related in: MedlinePlus

Best estimated mutual information with static environment values of randomly selected agents during evolution.A) The rate based measure  has higher values than the other measures, but no significant correlation was observed with generation (P =  0.7087, r =  2×10−2). B) Measure based on cross correlation combined with lag . C) Measure based on cross correlation alone . D) Measure based on lag alone . All values are based on Spearman's Rank Correlation Test made on 340 randomly chosen agents from the same evolutionary session. Please note the different axis in A.
© Copyright Policy
Related In: Results  -  Collection


getmorefigures.php?uid=PMC2268971&req=5

pone-0001863-g004: Best estimated mutual information with static environment values of randomly selected agents during evolution.A) The rate based measure has higher values than the other measures, but no significant correlation was observed with generation (P =  0.7087, r =  2×10−2). B) Measure based on cross correlation combined with lag . C) Measure based on cross correlation alone . D) Measure based on lag alone . All values are based on Spearman's Rank Correlation Test made on 340 randomly chosen agents from the same evolutionary session. Please note the different axis in A.

Mentions: As shown in Figure 4, there was a significant correlation between the current generation and each of the 3 time- dependent measures: .


Inevitable evolutionary temporal elements in neural processing: a study based on evolutionary simulations.

Yerushalmi U, Teicher M - PLoS ONE (2008)

Best estimated mutual information with static environment values of randomly selected agents during evolution.A) The rate based measure  has higher values than the other measures, but no significant correlation was observed with generation (P =  0.7087, r =  2×10−2). B) Measure based on cross correlation combined with lag . C) Measure based on cross correlation alone . D) Measure based on lag alone . All values are based on Spearman's Rank Correlation Test made on 340 randomly chosen agents from the same evolutionary session. Please note the different axis in A.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2268971&req=5

pone-0001863-g004: Best estimated mutual information with static environment values of randomly selected agents during evolution.A) The rate based measure has higher values than the other measures, but no significant correlation was observed with generation (P =  0.7087, r =  2×10−2). B) Measure based on cross correlation combined with lag . C) Measure based on cross correlation alone . D) Measure based on lag alone . All values are based on Spearman's Rank Correlation Test made on 340 randomly chosen agents from the same evolutionary session. Please note the different axis in A.
Mentions: As shown in Figure 4, there was a significant correlation between the current generation and each of the 3 time- dependent measures: .

Bottom Line: In repeating evolutionary sessions, there was a significant increase during evolution in the mutual information between the evolved agent's temporal neural representation and the external environment.These results suggest that in some fitness landscapes the emergence of temporal elements in neural computation is almost inevitable.Future research using similar evolutionary simulations may shed new light on various biological mechanisms.

View Article: PubMed Central - PubMed

Affiliation: The Leslie and Susan Gonda Interdisciplinary Brain Research Center, Bar-Ilan University, Ramat-Gan, Israel. uri.yerushalmi@gmail.com

ABSTRACT
Recent studies have suggested that some neural computational mechanisms are based on the fine temporal structure of spiking activity. However, less effort has been devoted to investigating the evolutionary aspects of such mechanisms. In this paper we explore the issue of temporal neural computation from an evolutionary point of view, using a genetic simulation of the evolutionary development of neural systems. We evolve neural systems in an environment with selective pressure based on mate finding, and examine the temporal aspects of the evolved systems. In repeating evolutionary sessions, there was a significant increase during evolution in the mutual information between the evolved agent's temporal neural representation and the external environment. In ten different simulated evolutionary sessions, there was an increased effect of time-related neural ablations on the agents' fitness. These results suggest that in some fitness landscapes the emergence of temporal elements in neural computation is almost inevitable. Future research using similar evolutionary simulations may shed new light on various biological mechanisms.

Show MeSH
Related in: MedlinePlus