understanding the interplay between the morphological and functional features of neuronal circuits is a major challenge in contemporary neuroscience . while the network s morphological constraints clearly shape its activity patterns activity relationship is therefore an important yet challenging task , in particular in light of the modular and hierarchical organization of the brain ( mountcastle , 1997 ; bullmore and sporns , 2009 ; meunier et al . , 2011 ) . such investigations are particularly cumbersome in intact neural tissue owing to their overwhelming complex structure . while it is easier to examine isolated circuits with controlled inputs and outputs , in vivo circuits are extremely difficult to isolate due to the multiple activation pathways impinging on any recorded region . despite recent advances in electrophysiology , imaging , and drug delivery , the accessibility of specific in vivo circuits to visualization , recording , and manipulation is still limited and the connectivity maps of neurons in vivo are highly untraceable in a three dimensional architecture . finally , since natural circuits are not prone to design , different wiring schemes can not be systematically studied . owing to these limitations , alternative methods are needed to allow methodical investigation of morphology  activity relationships in neuronal networks . one such approach is the study of cultures which allows network engineering , mapping , and simultaneous multi - site electrical recordings . ( 1988 ) , much effort has been dedicated to constructing engineered neuronal circuits with defined connectivity patterns ( see wheeler and brewer , 2010 for review ) . although many techniques can be used to achieve patterning , two main requirements must be satisfied to guarantee their practicability for long - term investigations : stability and yield . cell migration and extension redirection , resulting from the inherent motility of cells and tension forces exerted by neurite bundles ( sorkin et al . 2009 ) , often compromise patterning quality ( ruardij et al . , 2002 ; wheeler and brewer , 2010 ) . accordingly , physically caging neurons by introducing barriers ( maher et al . , 1999 ; zeck and fromherz , 2001 ) , combining cell repelling surfaces with strongly linked adhesive chemistries ( nam et al . , 2006 ) or patterning rough surface coatings ( greenbaum et al . , 2009 ) have been used to create stable patterns . in general , the finer the patterns the less stable they are ( khatami , 2008 ; wheeler and brewer , 2010 ) . while patterns with a feature size of several microns begin to breakdown as early as 1  week in culture , patterns with feature sizes of tens of micros can be stable for several months in culture ( khatami , 2008 ) . all the above approaches aim at keeping cells at specific locations by restricting their natural motility . an alternative approach is to harness this innate motility mechanism to promote patterning . if the constraints to keep cells at specific locations are relaxed , neurons and glia in culture tend to self - organize into clusters ( segev et al . , 2003 ; rutten et al . , 2006 ; sorkin et al . , 2006 ; soussou et al . , 2007 ; , 2009 ; shein idelson et al . , 2010 ) . using simple protein or carbon - nanotube patterning , it is possible to direct cluster locations and form highly stable and well organized networks ( gabay et al . , 2005 ; sorkin et al . , 2006 ; macis et al . , 2007 ; 2009 ) which can be faithfully recorded for over 1  month in culture ( macis et al . , 2007 ; it should be noted that clustering is such a strong propensity of neuronal networks , that some degree of clustering is almost always observed for most patterning techniques after some time in culture ( ruardij et al . , 2002 ; jun et al . , 2007a ) . clustering may also be enhanced by biological substrates with ingredients similar to those found in the brain extracellular matrix ( soussou et al . , 2007 ) . cell patterning methods are especially attractive when coupled with recording elements such as transistor or multi - electrode arrays ( meas ; chang et al . , 2006 ; jun et al . , 2007a ; jungblut et al . , 2009 ; shein idelson et al . , such devices provide activity recording of many neurons simultaneously , non - invasively , and for very long times ( potter , 2001 ) . patterning also allows direct coupling of neurons to recording sites , thus increasing the fraction of recorded neurons relative to the total number of neurons in the network ( jungblut et al . , 2009 ) . alternatively , optical imaging can be used , allowing high spatial resolution at the price of low temporal resolution ( jimbo et al . , 1993 ; feinerman et al . , 2007 ; despite their attractiveness , until recently patterned networks were rarely used to address basic questions in neuroscience . most studies were limited to demonstrating recording and stimulation capacities with only basic activity analysis . however , several recent studies which have explored the electrical activity of patterned networks have been able to demonstrate the great potential of these systems . three main approaches are commonly used ( figure 1 ) . in the first ( figure 1a ) , networks of different sizes are used to study scaling properties ( segev et al . , 2002 ; rutten et al . , 2006 ; wilson et al . , 2007 ; shein idelson et al . , 2010 ) . in these networks , cells are uniformly distributed on the surface ( no preferential adhesion to any specific location ) , and neurons at different locations have the same probability to connect to other neurons in the network ( no preferential directionality or connectivity ) , similarly to the widely used uniform networks . cells are uniformly distributed without preferential adhesion to any specific location and without preferential directionality or connectivity . cells are patterned at the nodes of a grid with connections restricted to the grid lines . two or more uniform sub - networks with high intra - sub - network connectivity and low inter - sub - network connectivity . in the second approach ( figure 1b ) , single neurons are patterned at the nodes of a grid with connections restricted to grow along grid lines ( vogt et al . , 2005 ; nam et al . , 2006 ; jun et al . this setup allows convenient mapping of the connections between the neurons and recording from a large fraction of the neurons in the network . such an experimental setup is ideal for studying signal propagation between single cells and for studying plasticity within a small cell assembly ( vogt et al . , 2005 ; claverol - tinture et al . , 2007 ; suzuki and yasuda , 2007 ) . however , due to low cell density , the spontaneous activity levels of such patterned systems are usually very low ( jun et al . , 2007a ; cohen et al . , 2008 ) , making detailed , long - term statistical activity analysis difficult . the third approach ( figure 1c ) , concerns neither complete mapping nor scaling properties of a single neuronal assembly but rather aims to examine how connected sub - networks interact . such modular networks are implemented using two or more uniform networks coupled by a neurite bridge ( yvon et al . , 2005 ; berdondini et al . , 2006 ; baruchi et al . , 2008 ; feinerman et al . , , 2007 ; tsai et al . , 2008 ; shein idelson et al . , 2010 ) . to better understand how the activity of patterned networks differs from that of uniform networks , we begin by briefly summarizing the main activity features of uniform networks . large uniform neuronal networks in culture are typified by network bursts ( nbs , figures 2a , b ) . these short ( several hundreds of milliseconds ) spontaneous epochs of network - wide synchronized activity , are considered as the hallmark of developing brain circuits ( ben - ari , 2001 ) and have been observed both in vitro ( maeda et al . , 1995 ; kamioka et al . , 1996 ; corner , 2008 ) and in vivo ( leinekugel et al . , 2002 ; buzsaki , 2004 ; ikegaya et al . , 2004 ; it has been found that nbs are mostly characterized by a fast rise time ( tens of milliseconds ) and a more gradual decay ( several hundreds of milliseconds , figures 2c , d ) and are important for the morphological maturation of the network ( katz and shatz , 1996 ; hu et al . , 2004 ; spitzer , 2006 ) . an interesting question addressed by several groups is whether nbs retain their characteristics for different network sizes , cell arrangement , connectivity , and topology . results from three network morphologies are shown : uniform ( a  d ) , highly connected clustered network ( e  h ) , and loosely connected clustered network ( i  l ) . ( a , e , i ) bright field images ( distance between electrodes is 500  m ) . ( b , f , j ) raster plots of recorded activity from the networks in ( a , e , i ) , respectively . ( c , g , k ) zoom into one nb from the raster plots shown in ( b , f , j ) , respectively ( marked by the light blue rectangle ) . ( d , h , l ) average network activity for 500 consecutive nbs ( see shein idelson et al . a first interesting observation , reported by ben - jacob and co - workers is the robustness of nb patterns in networks of different sizes . it was shown that networks ranging from 50 to 10 cells can sustain network bursting with statistical features which are almost size independent ( segev et al . , 2002 ) . a similar result was reported for isolated clusters in which nb statistics did not dramatically change for networks larger than 100 cells ( shein idelson et al . , 2010 ; this suggests the existence of regulatory mechanisms that modify the network morphology to sustain specific activity patterns . indeed , such mechanisms were identified for the excitability of single cells and for the connectivity between them ( turrigiano , 1999 ; shein et al . , 2008 ; ivenshitz and segal , 2010 ) . using small rectangular networks of different sizes , it was shown that although the number of synapses per neuron increased with network size , their strength decreased , assumingly to compensate for the potential increase in excitability ( wilson et al . , 2007 ) . oscillations and master  slave relations in small isolated ( a  d ) and coupled ( e  h ) clusters . ( a , e ) bright field images ( electrode diameter , 30  m ) . ( b , f ) raster plots of recorded activity from the networks in ( a , e ) , respectively . ( c , g ) zoom into one nb from the raster plots shown in ( b , f ) , respectively ( marked by the light blue rectangle ) . ( d , h ) average nb activity for 500 consecutive nbs ( see shein idelson et al . a second important question is whether a minimum cell number is required to maintain such a compensatory mechanism . several studies have indicated that such a limit exists ( rutten et al . , 2006 ; kang et al . , 2009 ; shein idelson et al . , 2010 ) . we have recently shown that very small neuro - glia networks ( < 20 cells ) do not show synchronized activity but mostly tonic spiking ( shein idelson et al . , 2010 ) . the exact cell limit appears to vary for different preparations and different compositions of culturing medium ( lau and bi , 2005 ; kang et al . , 2009 ) . we have additionally demonstrated that small networks of few tens of cells are not only able to generate nbs but also support oscillatory behavior during bursting ( shein idelson et al . , 2010 ; figures 3c , d ) . other studies have shown that such networks sustain long lasting reverberatory activity ( lau and bi , 2005 ; zeringue et al . , 2011 ) . patterning single neurons on a grid ( figure 1b ) allows to examine activity under constraints of ordered cell arrangement and connectivity and to compare it to that of randomly arranged uniform networks . in these ordered networks , a critical cell density of 200 cells / mm is required for the network to be spontaneously active ( jun et al . , 2007a ; jungblut et al . , 2009 ; wheeler and brewer , 2010 ) . below that limit either no activity or only single asynchronous spikes are observed ( nam et al . , 2006 ; jun et al . , 2007a ; jungblut et al . , 2009 ) . this density limit appears to correspond to the cell number limit discussed above for small uniform networks and neuronal clusters . in both cases this notion is supported by the fact that no network activity is observed if the network is patterned with thin grid lines which limit the connectivity ( jungblut et al . , 2009 ; wheeler and brewer , 2010 ) . interestingly , for wide enough grid lines and high enough cell density , the activity patterns are characterized by nbs similar to those of uniform networks or isolated clusters ( jun et al . , 2007a ; jungblut et al . , 2009 this similarity is not surprising since the connectivity of these ordered networks is quite uniform ( the average connectivity level for all the neurons is similar ) . it becomes therefore apparent that in order to fundamentally change the highly synchronized activity of neuronal network , patterning approaches that radically break the network uniformity are required . a practical approach to breaking such networks are characterized by high connectivity within each sub - network and weaker connectivity between sub - networks ( figure 1c ) . at the limit of strong coupling , the two sub - networks are simply one big network for which network - wide synchrony is observed . for weaker coupling , the global synchrony is partially broken and individual features of the sub - networks begin to emerge ( figures 2i  l ) . each sub - network continues to exhibit nbs , however , these nbs do not necessary propagate to other sub - networks ( yvon et al . , 2005 ; berdondini et al . , 2006 ; baruchi et al . , 2008 ; feinerman et al . , the percentage of these propagation failures is modulated by past activity levels ( yvon et al . , 2005 ) . following a treatment of prolonged activity inhibition , the number of failures is decreased due to underdevelopment of inhibitory connections between clusters ( yvon et al . , 2005 ) . when nbs do propagate , the propagation delays between the sub - networks are much longer than those expected from axonal conductance delays or propagation delays within uniform networks ( yvon et al . , 2005 ; berdondini et al . , 2006 ) the same features are seen in networks of two connected neuro - glia clusters ( shein idelson et al . , 2010 ; figures 3e  h ) . this conditional synchrony between sub - networks is important from a population - level computational perspective . it supports the possibility to gate the propagation according to activity levels ( only intense enough nbs propagate between sub - networks , see feinerman et al . , 2008 ) , to introduce variable delays ( izhikevich , 2006 ) , and to perform logical computational operations between sub - populations ( feinerman et al . , 2008 ) . an additional important feature that emerges from partitioning to sub - networks is the break down of symmetry between the sub - populations . it has been demonstrated that even if two sub - populations are constructed in a similar manner , one sub - network will initiate more nbs than the other ( baruchi et al . it has been suggested that such master  slave asymmetry emerges due to amplification of very small asymmetries in the network ( feinerman et al . , 2007 ) , or may be related to variations in the topology of each of the networks or their connecting bridge ( baruchi et al . , 2008 clearly , coupled sub - networks show unique activity patterns unseen in uniform networks . how do these features scale upon a transition to large networks of many connected sub - units ? , 2003 ; rutten et al . , 2006 ; macis et al . , 2007 ; while in all reports , these networks exhibit nbs , the degree of synchrony and time delays vary between reports . in some cases ( segev et al . , 2003 ; rutten et al . , 2006 other studies reported an age dependent increase in synchronization and confined stimulation effects in which stimulated bursts propagated only to neighboring clusters ( macis et al . , 2007 ) . in such networks , long propagation delays between clusters were observed and were shown to increase by reducing connectivity using synaptic blockers ( tsai et al . , 2008 ) . this apparent discrepancy may be related to the degree of connectivity . by systematically studying patterned networks with variable connectivity levels , it is possible to show that networks with higher connectivity exhibit highly synchronous nbs resembling those observed in uniform networks . on the other hand , lowering the degree of connectivity results in longer delays and conditional activation of adjacent clusters ( figure 2j ) . this conditional propagation is the network - level manifestation of the gating observed between two coupled networks ( figures 3e  h ) . interestingly , clustered networks exhibit repeated propagation patterns ( tsai et al . , 2008 ) . although similar repeating patterns have also been observed in uniform networks ( beggs and plenz , 2004 ; segev et al . in clustered networks these patterns are directly related to the spatial organization of the network ( tsai et al . , 2008 ) . it is widely accepted that network - level approaches are required to understand information processing in neuronal circuits . in the past few decades , a multitude of studies have addressed this issue by studying multi - site recordings from developing neuronal networks in culture ( maeda et al . , 1995 ; kamioka et al . , 1996 ; gross and kowalski , 1999 ; jimbo et al . , 1999 , 2007 ; corner , 2008 ; shein et al . , 2008 ; le feber et al . , the underlying motivation was that in vitro cultures retain many physiological features of the brain while being highly accessible to manipulation and control ( potter , 2001 ; marom and shahaf , 2002 ) . cultured neurons show similar activity patterns across different preparations ( ben - ari , 2001 ) , manifesting short events of network - wide synchronization ( figure 2b ) . consequently , most studies focused on examining the spatio - temporal patterns within these synchronous events and their statistics . these studies revealed the potential of uniform networks to regulate activity , process information , and sustain biological memory . examination of inter - burst statistics revealed that nb time series exhibit long - range temporal auto - correlations and complex temporal organization ( segev et al . , 2002 ; ayali et al . , 2004 ; hulata et al . , 2004 ) . inspired by the theory of synfire chains , the intra - burst firing patterns were investigated and were found to be far from random . highly repetitive spatio - temporal patterns with defined propagation schemes were detected in the spontaneous activity of the networks ( streit et al . , 2001 ; segev et al . , 2004 ; baruchi et al . , 2006 ; furthermore , such patterns were artificially induced by targeted electrical ( madhavan et al . , 2007 ) and chemical ( baruchi and ben - jacob , 2007 ) stimulations demonstrating a potential to imprint network - level memory . uniform cultures were also found to support learning . following the discovery of plasticity rules in coupling between single neurons ( bi and poo , 2001 ) , a network - level analog was found in which path specific potentiation and depression were induced using electrical stimulations ( jimbo et al . , 1999 ) . other studies reported that plastic changes can be induced by controlled removal of a driving stimulus using feedback from the network activity ( shahaf and marom , 2001 ; le feber et al . , 2010 ) . interestingly , plastic changes were not restricted to coupling between neurons but were also applicable to time delays of axonal conductances ( bakkum et al . , 2008 ) . in addition to these plastic changes , a series of regulatory mechanisms constantly tune synapses and intrinsic neuronal excitability to achieve single cell and network - level homeostasis ( turrigiano , 1999 ; shein et al . , 2008 ) . overall , the wealth of information extracted from uniform networks supports the notion that they are a good model for studying mechanisms of memory , information processing , and learning . despite these advantages , foremost , the uniform organization of cells in culture is markedly different from in vivo networks . unlike the uniform topology of most culture preparations , many of the circuits involved in information processing are characterized by modular organization . namely , they are made of small sub - networks with high intra - network connectivity and low inter - network connectivity ( mountcastle , 1997 ; meunier et al . , 2011 ) . furthermore , cells in uniform networks are strongly anchored to the surface which substantially restricts their motility . . the latter is missing from the activity repertoire of uniform cultures which is marked by network - wide recruitment ( with the exception of aborted bursts , see eytan and marom , 2006 ) . such network - wide synchronization does not support parallel and hierarchical information processing ( meunier et al . , 2011 ) . it is tempting to assert that these functional limitations are strongly linked to the structural constraints discussed above . this assertion suggests that the uniform network model should be extended to incorporate structural features to make it more relevant . thanks to recent advances in cell patterning techniques and multi - site recordings , a large set of tools have become available for controlling neuronal network architecture in culture ( wheeler and brewer , 2010 ) . however , activity analysis of patterned networks has , so far , only sparsely been addressed . foremost , these reports show that nbs are highly robust ( segev et al . , 2002 ; shein idelson et al . , 2010 ) and that the network s connectivity is self - modulated on the synaptic level to sustain them ( wilson et al . , 2007 ) . in fact , even though networks of a few tens of cells with strong enough connectivity are required to spontaneously maintain nbs , they are already sufficient to support many of the activity features of large uniform networks in addition to intra - burst oscillations ( lau and bi , 2005 ; kang et al . , 2009 ; shein idelson et al . , 2010 ; this suggests that finite uniform networks may serve as a unitary system for studying network - level activity . interestingly , it has been proposed that such minimal assembly size may have a functional role in real brains , where it may serve as a basic processing module ( shaw et al . , 1982 ) . from this perspective , the self - regulatory nature of nbs is certainly a desirable property . however , at the same time it suggests that uniformly adding cells or changing connectivity levels , can not profoundly alter network - wide synchrony . only by breaking the network homogeneity , such a uniformity break can be achieved by introducing an additional hierarchy to uniform networks through implementation of a modular architecture . such studies suggested that information processing in networks benefits from a modular architecture ( volman et al . , 2005 ; fuchs et al . , 2009 ; meunier et al . , 2011 ) . firstly , modularity can give rise to time - scale separation between fast intra - modular and slow inter - modular processing ( pan and sinha , 2009 ) . secondly , modularity maintains a fine balance within the spectrum of network - wide ( integrated ) and module - restricted ( segregated ) activation ( kaiser , 2007 ; shanahan , 2008 ) . in the latter , synchronized activity is confined to isolated modules , while in the former it spreads to all other modules in the network . these two features break the network - wide synchronization in time and space and promote the network s dynamical complexity ( shanahan , 2008 ) . another benefit of modular networks is the short path length between neurons in the network , resulting in low wiring cost . however , while this benefit is shared by all small world networks ( watts and strogatz , 1998 ) , the former two benefits are exclusive to modular networks . interestingly modular networks in culture support time - scale separations ( yvon et al . , 2005 ; berdondini et al . , 2006 ; shein idelson et al . , 2010 ) the propagation delay in the activation of connected modules is of the order of several tens of milliseconds ( figures 3g , h ) . this delay is similar to the intra - module recruitment time ( eytan and marom , 2006 ; shein idelson et al . , 2010 ) , and results in temporal separation between intra and inter module activation . in fact , in large modular networks , this delay is accumulated during activity propagation in a way that removes the temporal overlap between early and late activated modules ( figure 2k ) . it is worth noting , that long delays can also be implemented without using loose connections to break uniformity ( feinerman et al . however , in these implementations the delays are due to the time it takes the activity front to propagate , and therefore requires especially large networks . in addition , this implementation does not support other features of modular networks , such as activity segregation . while connected modules have the potential to synchronize , they also exhibit segregated activity in which nbs within a module do not propagate to other modules ( yvon et al . this suggests that a gating mechanism controls the degree of synchronization and the spread of activity . interestingly , nbs with higher intensity have a greater probability to propagate to connected clusters ( feinerman et al . , 2008 ) . for example , a module connected to two other modules can be conditionally activated only if both connected modules are synchronously activated ( feinerman et al . an additional feature of modular networks is the emergence of master  slave relationships where one module drives the other ( baruchi et al . , 2008 ; shein et al . , such a feature may be utilized to control the propagation directionality in the network . in summary , the studies we have reviewed here suggest that modular cultured networks are a promising platform for studying information processing in vitro . unlike networks in vivo , in vitro systems such studies bring to light the robustness of network - wide synchrony in uniform cultures and the self - regulatory mechanisms that maintain it . this robustness suggests that even small uniform networks can serve as a unitary module which supports nbs . however , at the same time it suggests that a break in uniformity is required to enrich the network s activity patterns . indeed , coupling small highly connected uniform networks through loose connections results in modular networks with unique activity characteristics . such networks support synchronized bursting within each module , however , they also support mechanisms of activity gating and time delays between the modules . the use of this hierarchical topology further elevates the richness and complexity of activity in uniform networks . the authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest .
neuron  glia cultures serve as a valuable model system for exploring the bio - molecular activity of single cells . since neurons in culture can be conveniently recorded with great fidelity from many sites simultaneously , it has long been suggested that uniform cultured neurons may also be used to investigate network - level mechanisms pertinent to information processing , activity propagation , memory , and learning . but 
 how much of the functionality of neural circuits can be retained in vitro remains an open question . 
 recent studies utilizing patterned networks suggest that they provide a most useful platform to address fundamental questions in neuroscience . here 
 we review recent efforts in the realm of patterned networks activity investigations . 
 we give a brief overview of the patterning methods and experimental approaches commonly employed in the field , and summarize the main results reported in the literature . the general picture that emerges from these reports indicates that patterned networks with uniform connectivity do not exhibit unique activity patterns . 
 rather , their activity is very similar to that of unpatterned uniform networks . 
 however , by breaking the connectivity homogeneity , using a modular architecture , it is possible to introduce pronounced topology - related gating and delay effects . 
 these findings suggest that patterned cultured networks may serve as a new platform for studying the role of modularity in neuronal circuits .