attention has widespread effects on brain activity . from thalamus and colliculus to many regions of cortex , for example , responses to visual input are enhanced when this input is relevant to behavior ( oconnor et  al . , 2002 ; ignashchenkova et  al . , 2004 ; roelfsema et  al . , 1998 ; moran and desimone , 1985 ) . often , attentional modulations grow over time from stimulus onset as the appropriate attentional focus is established ( roelfsema et  al . , 1998 ; schall et  al . , 1995 ) . in some cases , inputs appear to compete for control of neuronal activity , for example , when two stimuli fall within the receptive field of a visual cell ( chelazzi et  al . in such cases , directing attention to one or the other stimulus determines how closely neural activity resembles the response to that stimulus presented alone ( moran and desimone , 1985 ; reynolds et  al . , 1999 ; see also reynolds and heeger , 2009 ) . such competition for control of neural activity resembles classic attentional models , in which concurrent stimuli or cognitive events compete for processing resources ( e.g. , broadbent , 1958 ; kahneman , 1973 ) . this form of competition is best established in early visual areas , where it is predominantly local . when two stimuli fall within a cell s spatial receptive field , moving attention from one to the other determines which of the two drives activity . competition and attentional modulation are much weaker when stimuli are widely separated ( moran and desimone , 1985 ; lee and maunsell , 2010 ) . in behavior , however , there are global limits on attentional capacity , such that even very dissimilar tasks can be hard to carry out together ( bourke et al . , 1996 ; neurophysiologically , attentional modulations are strong in prefrontal cortex ( rainer et  al . , 1998 ; lennert and martinez - trujillo , 2011 ) , even with stimuli in opposite visual hemifields ( everling et  al . , 2002 ) , and it is commonly proposed that prefrontal cortex plays a central role in attentional competition and control ( norman and shallice , 1980 ; dehaene et  al . , 1998 ; botvinick et  al . , 2001 ; miller and cohen , 2001 according to adaptive coding proposals ( duncan , 2001 ; duncan and miller , 2002 ) , prefrontal neurons have highly flexible response properties , allocated to coding different information in different task contexts . functional brain imaging shows that similar regions of prefrontal cortex are active during many different kinds of cognitive activity ( duncan and owen , 2000 ; miller and cohen , 2001 ) , providing a plausible basis for global limits on attentional capacity ( e.g. , dehaene et  al . , 1998 ; marois and ivanoff , 2005 ; bourke et al . , 1996 ) . on such a view , processing activity in prefrontal cortex would be flexible but limited , allocated to a currently attended stimulus or task , and providing a critical prefrontal mechanism for attentional competition and its resolution . here we examined the dynamics of attentional allocation in prefrontal cortex with widely separated visual stimuli . in the behaving monkey , we used time - resolved measures of neural population activity ( e.g. , buschman et  al . , 2012 ; kaping et  al . , 2011 ; stokes et  al . , 2013 ) to track development of the attentional focus under varying levels of attentional competition . attentional competition was manipulated using a simple form of visual search , in which the animal detected and later responded to a cued target object ( t ) . in some trials , t was presented alone , while in others , competition was introduced by an additional nontarget ( n ) in the opposite visual hemifield . it is well known from human search experiments that processing conflict in such a task is determined by training history , with strong competition from a nontarget that has often previously been experienced as a target ( inconsistent nontarget or ni ) , but much less from a nontarget that can always be ignored ( consistent nontarget or nc ) ( schneider and shiffrin , 1977 ; schneider and fisk , 1982 ) . analogous effects of training history have been shown in the frontal eye field , with a relative enhancement of response to stimuli previously trained as targets ( bichot et  al . , 1996 ; bichot and schall , 1999 ) . in our task ( figure  1a ) , each trial began with a central cue indicating this trial s target object . based on preexperimental training , , there followed a choice display containing either a single object , to left or right of fixation , or one object to either side . for single - object displays , the choice stimulus could be either the cued target ( t ) , the stimulus associated with the other cue and thus serving as a target on other trials ( ni ) , or a fixed nontarget object never serving as a target ( nc ) . in the two - object case , a target t could be accompanied by either ni or nc , or ni and nc could appear together . following the 500  ms choice display and a subsequent brief delay , the monkey was rewarded for a saccade to the t location , or if no t had been presented , maintained fixation ( no - go response ) for later reward ( see experimental procedures ) . in line with the proposal of adaptive coding , our results show how , in a prefrontal cell population , activity resembles the limited processing resource of classic attentional models . as previously described ( e.g. , freedman et  al . , 2001 ; kusunoki et  al . , 2010 ) , many cells were devoted to making task - relevant stimulus discriminations . with attentional competition , processing capacity was initially divided between competing display objects , with different neurons responding to different objects . specifically , neural events in each hemisphere were initially dominated by response to the display item in the contralateral visual field , whether t or n. the result was that neurons failed to make critical stimulus discriminations in the ipsilateral visual field , resembling poor information coding when processing resources are diverted in classic attentional models ( broadbent , 1958 ; kahneman , 1973 ) . subsequently , this initial , incoherent state was replaced by transition to a global focus on the behaviorally critical target , with this target now controlling neural activity in both hemispheres . the speed and extent of transition between these states reflected the strength of attentional competition , being more rapid and complete for t  + nc than for t  + ni displays . the results track dynamic allocation of processing resources in prefrontal cortex , with gradual establishment of a coherent and global attentional focus . behavioral data ( figure  1b ) showed high accuracy for singly presented t and nc stimuli . the comparative difficulty of ignoring ni was confirmed by much reduced accuracy for this stimulus presented alone , with the majority of errors ( 72.2% ) being saccades to the stimulus location at the time of the go signal . saccades to the ni location were also common ( 59.2% of errors ) for t  + ni displays , while for t  + nc displays , the most common form of error ( 79.1% ) was a no - go response . during performance of the task , responses of 461 single neurons were recorded on the lateral frontal surface of three hemispheres , two in monkey a ( n  = 192 right , 113 left ) and one in monkey b ( n  = 156 , right ) . pooled results are presented here , as similar patterns were seen in all three recorded hemispheres . recording locations ( figure  1c ; figure  s1 available online ) were located in dorsal and ventral regions of the posterior lateral prefrontal cortex , including the posterior third of the principal sulcus . to ask how prefrontal cortex represents task events , we examined responses to the 12 possible single - object displays ( 3  stimulus categories [ t , ni , nc ]  2 visual fields [ contralateral or ipsilateral to recording location ]  2 cues ) . for each neuron , data were examined by anova with factors stimulus category , visual field , and cue . analyses were separately conducted on firing rates from early ( 50250  ms from display onset ) and late ( 300500  ms ) response periods . in both analysis periods , many cells ( 79/461 early , 118/461 late ) showed significant ( p  < 0.05 ) main effects of stimulus category . two examples are shown on the left of figure  2a . in the first cell ( top row ) , responses were strongest to t and weakest to nc , this pattern arising much earlier for contralateral stimuli . a complementary pattern is illustrated by the second cell ( figure  2a left , bottom row ) , with a late , selective response to nontargets , especially nc . in both analysis periods , there were also many cells ( 155/461 early , 114/461 late ) showing significant main effects of visual field . an early preference for contralateral stimuli and a late preference for ipsilateral stimuli are illustrated by the two cells on the right of figure  2a . main effects of cue were less common ( 47/461 cells early , 43/461 late ) . numbers of cells showing different patterns of interaction are listed in table s1 . as shown in figure  s1 , both category- and location - selective cells were broadly distributed across recording locations , including dorsolateral and ventrolateral surfaces , as well as the posterior recording area lying between arcuate and principal sulci . though these results suggest many cells coding the behavioral category of stimuli , the data suggested little direct role in the saccadic response . of 58 cells showing an interaction of stimulus category and visual field in the late period ( see table s1 ) , there were 33 with a strong , sustained response for targets in one location ( figure  s2 ) . though such a pattern might plausibly reflect oculomotor preparation , even these cells showed little evidence of activity linked to the saccadic response ( figure  s2 ) . these results match prior findings from similar tasks , suggesting prefrontal activity linked largely to behavioral categorization rather than motor output ( everling et  al . , 2002 ; kusunoki et  al . , 2009 ) . to examine stimulus coding across the whole cell population , neural activity at each time point from stimulus onset ( see experimental procedures ) was represented as a vector of firing rates across the full sample of 461 recorded cells . twelve such vectors were obtained for each of the 12 separate single - object displays , and to measure separation of population activity for any two displays , we used euclidean distance between their activity vectors . a two - dimensional representation of the resulting similarity space , derived using multidimensional scaling ( mds ) , is shown in figure  2b . separate similarity spaces are shown for early ( 175  ms from stimulus onset ) and late ( 450  ms ) stages of processing . even early in processing , the prefrontal representation already showed discrimination of both stimulus category and hemifield . in particular there was clear separation of t , ni , and nc categories , especially in the contralateral hemifield . representations of a given behavioral category were similar for the two cues , despite actual stimuli exchanging roles as t or ni . it is noteworthy that hemifield coding was strong for both targets and nontargets , though for the latter it had no behavioral significance . at both stages of processing , neural representations for ni were intermediate between those for t and nc , in agreement with previous data ( kusunoki et  al . , 2010 ) and the example cells on the left side of figure  2a . as usual in lateral prefrontal cortex , these data show many cells coding current task events , with strong but not exclusive emphasis on behaviorally relevant stimulus categorizations . to examine attentional competition , we turned to two - object displays and the dynamics of information coding as the choice display is processed . on a resource model of prefrontal activity , a plausible hypothesis is that , just as attentional competition impairs behavioral accuracy , it might impair neural discrimination . such results would match classic attentional models , in which division of attentional resource reduces processing efficiency ( broadbent , 1958 ; kahneman , 1973 ) . to address this question , we used euclidean distance to measure discrimination between critical stimulus pairs , t versus ni and t versus nc . in each case , we measured discrimination either for the critical stimuli presented alone ( no - competition case ) , or in the presence of an additional nontarget in the opposite hemifield ( attentional competition ) . the design of our displays ( figure  1 ) allowed us to examine four such cases ( figure  3 ) : discrimination of t versus ni in the hemifield contralateral to the recording location ( tcon versus nicon ) , either presented alone or with a concurrent stimulus ( nc ) in the ipsilateral hemifield ; discrimination of tcon versus nccon , either presented alone or acompanied by niips ; and similarly for discrimination of tips / niips , presented alone or with nccon , and discrimination of tips / ncips , presented alone or with nicon . in each case , we selected for analysis a population of cells that were most relevant to the critical discrimination ( e.g. , tcon versus nicon ) , ensuring that this selection was unbiased for comparison of no - competition and competition cases ( see experimental procedures ) . we predicted that critical t / n discriminations might be impaired when an additional stimulus is added in the opposite hemifield . the pattern of results was strikingly different for contralateral and ipsilateral discriminations ( figure  3 ) . for single stimuli in the contralateral hemifield , t / n discrimination became significant at around 100  ms from onset and remained throughout the duration of the choice stimulus ( figure  3 , left panels ; cf . data for two - object displays closely tracked those for single objects , suggesting little change in contralateral t / n discrimination with attentional competition . ipsilateral discriminations , in contrast , showed evidence of impairment by competing contralateral stimuli ( figure  3 , right panels ) . again , t / n discrimination began at around 100  ms for single - object displays . with addition of nccon , discrimination of tips from niips remained close to zero until around 200  ms and then rapidly increased toward single - object values ( figure  3 , top right ) . this delay led to a period of strongly significant difference between discrimination strength in one- and two - object displays ( figure  3 , top right , dark gray bars ) . a larger and more extended impairment in discriminating tips from ncips was created by addition of nicon , lasting throughout most of the stimulus duration ( figure  3 , bottom right ) . the results confirm that critical neural discriminations can be impaired by competing stimuli , especially early in stimulus processing , and when training history makes a competing stimulus ( ni ) hard to ignore . the impairment , however , takes an intriguing form  impairment of ipsilateral discrimination by a contralateral competitor , but not vice versa . how might the idea of flexible resource allocation , in particular competition of inputs to drive neural responses , explain these discrimination data ? the results suggest a critical role of visual field , with a tendency at the start of processing the choice display to ignore the ipsilateral field . anatomical connections from visual cortex to frontal lobe are much stronger within than between hemispheres ( ungerleider et  al . , 1989 ) , and if competing stimuli are presented in opposite hemifields , neural activity in inferotemporal cortex is dominated by the contralateral input ( chelazzi et  al . , 1998 ) . at least early in processing a choice display , prefrontal activity may show a similar contralateral dominance , meaning that in each hemisphere , there is little information concerning a competing ipsilateral event . when a target is present , however , an accompanying nontarget has no relevance to behavior . we considered the hypothesis that , across time of processing a choice display , activity evolves to a coherent attentional state , with responses in both hemispheres controlled by the behaviorally critical target . a neural mechanism of this sort would be analogous to progressive focus of processing resources in classical attention modes ( kahneman , 1973 ) . on this hypothesis , responses to a t  + n display should be predictable from the separate responses produced by the component t and n presented alone . for tcon + nips , activity should follow response to tcon alone throughout choice stimulus processing . early in processing , tcon dominates because it is contralateral , while late in processing , the same stimulus dominates because it is the target , but in either case , response to tcon  + nips follows response to tcon alone . for tips now , an early response to ncon should be replaced by later activity based on  tips . the top left panel shows responses to tcon  + nips displays and their component single stimuli for a cell with very different tcon and nips responses . throughout choice stimulus processing , the bottom left panel shows a complementary pattern , where again , response to the two - object display resembled the suppression produced by tcon alone . the right panels show very different dynamics for tips  + ncon displays . in the top panel is a cell showing a strong , sustained response to tips alone . in the two - object display , this strong tips response was initially suppressed by the accompanying ncon . later , suppression tended to be released but earlier and more rapidly when the suppressing stimulus was nc . the bottom right shows a complementary example , with strong response to a single ncon but little response to tips . in the two - object display , again , the early response resembled that to ncon alone , but , especially when the nontarget was nc , later activity was dominated by tips . to confirm this pattern at the population level in the first , we examined mean responses in selected cell groups ( figure  4b ) with clear differences in response to the two component stimuli of a two - object display . to examine responses to tcon  + nips displays , we selected all cells with significantly different responses to tcon versus nips ( see experimental procedures ) . for tcon > nips cells ( figure  4b , top left ) , strong responses to tcon alone were matched by closely similar responses to both tcon  + niips and tcon  + ncips displays . < nips cells , with similar suppression to tcon presented alone or with an accompanying nontarget ( figure  4b , bottom left ) . a contrasting pattern was seen for tips > ncon cells responding to the tips  + ncon display ( figure  4b , top right ) . early responses to the tips  + ncon display resembled the suppression produced by ncon alone , then , beginning before 200  ms , departed to approach tips responses . for tips + nccon , activity rapidly approached the response to tips alone , while for tips  + nicon , some suppression compared to tips alone remained throughout stimulus processing . a corresponding pattern of results was seen for tips  < ncon cells ( figure  4b , bottom right ) . in a second analysis , we turned to the whole recorded cell population and asked how well single neuron responses to each two - object display were predicted by responses to the two component objects individually . results for three different analysis windows  early ( 100200  ms from choice stimulus onset ) , middle ( 250350  ms ) and late ( 400500  ms)are shown in figure  5 . responses of each neuron to the different stimulus displays were first normalized ( division by mean response to all displays ; see experimental procedures ) , and responses to two - object displays were then plotted against responses to each of the two component single stimuli . for tcon + nips displays , results were similar at all time points from stimulus onset . across neurons , there was a strong tendency for response to the two - object display to match the response given by tcon rather than nips . for tips  + ncon displays dynamics were more complex . in the early window , response to the two - object display tended to follow response to ncon alone , with response to tips unpredictive . in the middle window , the ncon response retained some influence for the case of ni , though this influence had already disappeared for nc . in contrast , response to the two - object display was increasingly predicted by response to tips . by the late window finally , to ask how closely population responses to a two - object display approached those to component single stimuli , we again used a euclidean distance measure calculated across the whole recorded sample of 461 cells . across the time course of choice stimulus processing , we measured population discrimination of each two - object display ( e.g. , tcon  + niips ; figure  6 , top left ) from its component single stimuli ( tcon , niips ) . a simple pattern of results emerged when t was contralateral . throughout stimulus processing , the population response to the two - object display was barely discriminable from response to the contralateral t presented alone ( figure  6 , left panels ) . beginning < 100  ms from stimulus onset , in contrast , response to the two - object display diverged rapidly from response to the component ipsilateral n ( figure  6 , left panels ) . when t was ipsilateral , however , events followed a more complex time course , in particular for the highest - competition case ( tips  + nicon ; figure  6 , top right ) . in the first phase of processing , the two - object display was strongly discriminated from tips presented alone , but not from nicon . only toward the end of the stimulus presentation did the curves cross , indicating a response to the two - object display that more closely resembled response to its component target . for the lower - competition case ( tips  + nccon ) , strong discrimination from the component target was short lived , with a correspondingly rapid increase in discrimination from the component nontarget ( figure  6 , bottom right ) . these results show how , as prefrontal processing evolves , there is large - scale reallocation of processing resources . early in choice stimulus processing , neural activity in each hemisphere is dominated by response to the contralateral stimulus . in different groups of neurons ( figure  4 ) , this response can be either an increase or decrease from baseline ; in either case , the response to a competition display resembles response to the contralateral stimulus alone . later , this separation between hemispheres resolves to a coherent state of activity based on the critical t stimulus , especially when the accompanying stimulus is nc . across both hemispheres , the final , global state is close to the state produced by the t stimulus alone . in further analyses , we examined the generality of attentional reallocation across recording locations and cell types . to produce an index of reallocation for each cell , we defined dt as the absolute difference between firing rates for a tips  + ncon display and for tips alone and , similarly , dn as the absolute difference between firing rates for the tips  + ncon display and its component ncon alone . in an early analysis window ( 100200  ms from stimulus onset ) , we defined a dominance index as(dtdn)(dt+dn ) . following the results shown in figure  6 , this early index was generally positive , reflecting response to tips  + ncon that was closer to ncon than to tips alone . the same dominance index calculated for a late analysis window ( 400500  ms ) was generally negative , indicating response to tips  + ncon that was closer to tips than to ncon alone . subtracting the late index from the early index gave us a final reallocation index , separately calculated for each cell and for tips  + nicon and tips  + nccon displays . across the whole recorded cell population , the mean reallocation index for tips  + nicon displays was 0.147 . by t test , this value was significantly greater than zero ( p  < 0.001 ) . for tips  + nccon displays , the mean reallocation index was 0.124 , again significantly greater than zero ( p  < 0.001 ) . to examine generality across anatomical regions , we divided the full recorded cell sample into three groups , a smaller group ( n  = 42 ) recorded in a posterior region between the principle and arcuate sulci ( see figure  s1 ) and larger groups recorded in more anterior dorsolateral ( n  = 145 ) and ventrolateral ( n  = 274 ) regions , divided by the fundus of the principal sulcus . both for tips  + nicon and tips  + nccon displays , the mean reallocation index was positive for all three cell groups . anova showed no difference between cell groups , for tips  + nicon f(2 , 456 )  = 1.17 , for tips  + nccon f(2 , 455 )  = 1.29 ( missing data for cases in which dt  = dn  = 0 ) . in a second analysis , we examined generality across cell types , defined by coding of stimulus category and/or location in single - stimulus displays . to examine category - selective cells , we took all those cells ( n  = 162 ) with a main effect of stimulus category in either early- or late - period anovas on single - stimulus activity ( see earlier section , coding of single choice stimuli ) . to examine location - selective cells , we took all cells ( n  = 210 ) with a main effect of location in either analysis period . again , the mean reallocation index was significantly positive in both groups ( category - selective cells : mean index  = 0.222 , p  < 0.005 for tips + nicon , mean index  = 0.226 , p  < 0.001 for tips  + nccon ; location - selective cells : mean index  = 0.233 , p  < 0.001 for tips + nicon , mean index  = 0.096 , p  < 0.06 for tips  + nccon ) . these results show substantial generality in the overall pattern of attentional reallocation for tips  + ncon displays . for all regions in our recording area , and whatever stimulus feature a cell coded , early response was determined largely by the contralateral n , while later response was determined largely by t. finally , we found no evidence for attentional reallocation on error trials . combining data for all cells , and for both major error types ( saccade to wrong location , no - go ) , mean reallocation index on error trials was 0.006 , t test against zero p  = 0.56 for tips  + nicon displays , and mean reallocation index 0.014 , p  = 0.49 for tips  + nccon displays . only correct trials , evidently , were associated with reallocation of prefrontal processing resources from contralateral nontarget to ipsilateral target . when stimuli or other cognitive events compete for attention , processing resources must be allocated to the most important ( broadbent , 1958 ; kahneman , 1973 ) . our results track development of an attentional focus in the population activity of prefrontal cortex . in line with the proposal of adaptive prefrontal coding of task - relevant information , we found that many prefrontal cells discriminated task - critical stimulus categories and locations . when two stimuli were present in the display , attentional competition resolved through widespread reallocation of neural resources . early processing lacked attentional coherence , with different neurons responding to different items in the display . specifically , neural activity in each hemisphere was dominated by the contralateral display item  a pattern ( figure  2 ) coding both hemifield and behavioral category of that stimulus . accordingly , critical stimulus discriminations within one visual field were impaired in the ipsilateral hemisphere , matching the classical proposal of reduced processing efficiency when processing resources are withheld ( broadbent , 1958 ; kahneman , 1973 ) . construction of this global attentional focus resembles the classical proposal that processing resources are allocated to the most important cognitive events ( broadbent , 1958 ; kahneman , 1973 ) . we found that the time course of transition depends on the attentional weight of nontargets . for nc , a stimulus never serving as a target , control of the contralateral hemisphere was released quickly and easily . for ni , a target stimulus on other trials , release was slow and incomplete . again , these results match comparable findings from human studies , showing how processing resources are rapidly allocated to targets when nontargets have been extensively practiced as task irrelevant ( schneider and shiffrin , 1977 ; schneider and fisk , 1982 ) . it is commonly proposed that , in early visual areas , stimuli within or close to the receptive field of a cell compete to control its activity ( moran and desimone , 1985 ; reynolds et  al . , 1999 ; reynolds and heeger , 2009 ) . accordingly , moving attention from one stimulus to another can have large effects when the two are close together ; with widely separated stimuli , the effect is much smaller , with only modest enhancement of response to the attended input ( moran and desimone , 1985 ; lee and maunsell , 2010 ) . in prefrontal cortex , instead , we found widespread target dominance by the end of display processing , reflecting global allocation of processing resources to the behaviorally critical stimulus . global division of prefrontal processing capacity is a plausible neural basis for many cases of attentional competition , including interference between widely separated visual stimuli and even between very dissimilar tasks ( marois and ivanoff , 2005 ; dehaene et  al . , 1998 ; . in prefrontal cortex , global processing competition , and its dynamic resolution , probably reflect the breadth of inputs from other brain regions ( pandya and yeterian , 1996 ) and the strong interconnectivity between one prefrontal region and another ( pucak et  al . , 1996 ) . our finding of early activity dominated by the contralateral visual field resembles results previously reported for inferotemporal cortex ( chelazzi et  al . , 1998 ) . in that study , pairs of stimuli were presented either within one hemifield or one to each hemifield . as in the current study , animals searched for a prespecified target , responding with an immediate saccade or lever release . when both stimuli fell in the same hemifield , neural activity was dominated by the target , but with stimuli in opposite hemifields , activity was dominated by the contralateral stimulus , whether target or nontarget . because responses in that study were immediate , data were only available for the brief period before the response was made . it is not known whether , with a longer stimulus presentation , global dominance by the attended target might develop in inferotemporal cortex , as we have shown here for prefrontal cortex . the neural mechanisms of visual search have also been examined in the frontal eye field , with some similarities to the current results . in the frontal eye field , as in early visual areas , there is response enhancement when the stimulus within the receptive field is the current target ( schall et  al . , 1995 ) . enhancement reflects training history , with earlier enhancement after long practice in searching for a given target ( bichot et  al . , 1996 ) and enhancement for stimuli that share features with a previous target ( bichot and schall , 1999 ) . as in early visual areas , however , such target enhancements are far from the widespread reallocation of processing activity we observed in prefrontal cortex . even when the target is well outside the receptive field , the nontarget within the receptive field drives strong activity up to the time of the response ( schall et  al . , 1995 ; thompson et  al . , 1997 a likely mechanism is communication between the two frontal lobes ( tomita et  al . , 1999 ) , allowing processing on both sides to be dominated by the same , critical stimulus event . on this model , target information from one hemisphere displaces nontarget information in the other ; this happens rapidly and relatively completely when nontarget status is fixed throughout training but only more slowly and partially when the nontarget to be displaced is a target on other trials . evidently , the competitive mechanisms allowing nontarget displacement must be influenced both by current behavioral status  allowing t to dominate even ni  but also by long - term learning . on the current trial , some context signal initiated by the cue ( stokes et  al . , 2013 ) must determine which stimulus is t and which is ni , thus directing the outcome of competition for control of population activity . across learning , in contrast , nc is always irrelevant , resulting in long - term reduction of competitive weight . an even stronger separation of competitive weights may be obtained with spatial cues , directly indicating which visual field should be attended in a subsequent visual display . with advance spatial cueing , information from the attended field may dominate some cells even from the outset of visual processing ( everling et  al . , 2002 ) , though even in this case , there is some response to the unattended side ( everling et  al . , again , the strength of such attentional modulations reflects the variable strength of spatial cues ( lennert and martinez - trujillo , 2011 ) . an enduring debate in the search literature rests on the distinction between serial and parallel processing . behavioral ( egeth and dagenbach , 1991 ; kyllingsbaek and bundesen , 2007 ) and neurophysiological ( buschman and miller , 2009 ) arguments can be assembled on both sides of this debate and , in the present case , data are not easily explained by a simple serial model . instead , processing begins with parallel coding of both display inputs , one dominating each hemisphere , then resolves over several hundred milliseconds ( figures 5 and 6 ) to a global state of target dominance . it is an open question how this conclusion relates to other kinds of task and search display , e.g. , displays containing larger numbers of stimuli ( buschman and miller , 2009 ) . a second enduring question in the cognitive literature is the extent to which the two hemispheres act as separate pools of processing capacity ( pashler and obrien , 1993 ; alvarez and cavanagh , 2005 ; see also buschman et  al . , 2011 ) . our data suggest that the answer may be dynamic , evolving with construction of the attentional focus . early in processing a two - object display , we indeed found that the two hemispheres were focused on different stimuli , like parallel processing pools . later , we found coherence , with both hemispheres focused on the same , behaviorally critical stimulus . though here we examined attentional competition between visual fields , more generally , similar processing principles may apply to many different cases of processing competition . in many such cases , prefrontal activity may move from an early , unfocused state to attentional coherence . attentional coherence is critical to organized cognition , as multiple brain systems must converge to process the stimuli , responses , reward , etc . of current behavior . through feedback to multiple brain systems ( dehaene et  al . , 1998 ; miller and cohen , 2001 ; desimone and duncan , 1995 ; moore and armstrong , 2003 ) , the construction of globally consistent prefrontal activity patterns may be critical in assembly of distributed yet coherent attentional episodes . subjects were two male rhesus monkeys ( macaca mulatta ) weighing 11 ( monkey a ) and 10 ( monkey b ) kg . all experimental procedures were approved by the uk home office and were in compliance with the guidelines of the european community for the care and use of laboratory animals ( euvd , european union directive 86/609/eec ) . task events were controlled by a pentium pc running cortex software , with displays presented on a 19 inch led screen placed in front of the monkey s chair . each trial began with onset of a red dot at screen center , which the animal was required to fixate ( window 5   5 for monkey a , 4  4 for monkey b ) until the final saccadic response at the end of the trial . a premature saccade away from screen center immediately terminated the trial without reward ( trials discarded from all data analyses ) . once fixation had been held for 1,000  ms , a central cue stimulus ( 500  ms ) indicated the target for the current trial . based on preexperimental training , each of two alternative cue stimuli was associated with a different target ( see figure  1a inset for cue - target pairs for monkey a ; different cue , target , and nontarget images were used for monkey b ) . a randomly varying delay of 400600 ( monkey a ) or 400800 ( monkey b ) ms was followed by a 500  ms choice display . the display contained either a single object , centered on the horizontal meridian randomly 6 to left or right of fixation , or two objects , one to either side . for single - object displays , the stimulus object was either the cued target t , the object associated with the alternative cue ( inconsistent nontarget , ni ) , or a third object never used as a target ( consistent nontarget , nc ) . for two - object displays , major trial types were t  + ni , t  + nc , and ni  + nc ( in randomly varying left - right or right - left configuration ) , though in some sessions , small numbers of ni  + ni trials were also included ( data not shown ) . to avoid response biases , we adjusted frequencies of individual trial types to ensure that t was present in half of all single - object and half of all two - object displays ; otherwise , frequencies of all major trial types were the same . following choice stimulus offset , there was a further random delay of 100150 ( monkey a ) or 300500 ( monkey b ) ms , after which the fixation point turned green to indicate the monkey s response interval . for go trials ( t present in choice display ) , the monkey was immediately rewarded with a drop of liquid for a saccade to the remembered t location ( target window 6  6 for monkey a , 3.5  3.5 for monkey b ) . for no - go trials ( t absent ) , the monkey was required to hold fixation for the whole 1,000  ms response interval and was then either given immediate reward ( monkey b ) or rewarded for a further saccadic response ( monkey a ) . for monkey a , some sessions had cues randomly varying between trials , while others had alternating brief ( 1520 trials ) blocks of fixed cues . physiological data were very similar in the two cases and were combined . for monkey b , cues always varied randomly between trials . each monkey was implanted with a custom - designed titanium head holder and recording chamber(s ) ( max planck institute for biological cybernetics ) , fixed on the skull with stainless steel screws . chambers were placed over the lateral prefrontal cortex of the left ( ap  = 25.3 , ml  = 20.0 ; ap , anterior - posterior ; ml , medio - lateral ) and right ( ap  = 31.5 , ml  = 22.5 ) hemispheres for monkey a and the right hemisphere ( ap  = 30.0 , ml  = 24.0 ) for monkey b. recording locations for each animal are shown in figure  s1 . we used arrays of tungsten microelectrodes ( fhc ) mounted on a grid ( crist instrument ) with 1  mm spacing between adjacent locations inside the recording chamber . the electrodes were independently controlled by a hydraulic , digitally controlled microdrive ( electrodes drive , nan for monkey a ; multidrive 8 channel system , fhc for monkey b ) . neural activity was amplified , filtered , and stored for offline cluster separation and analysis with the plexon map system ( plexon ) . eye position was sampled using an infrared eye tracking system ( 120  hz , asl for monkey a ; 60  hz , iscan for monkey b ) and stored for offline analysis . we did not preselect neurons for task - related responses ; instead , we advanced microelectrodes until we could isolate neuronal activity before starting the task . at the end of the experiments , animals were deeply anaesthetized with barbiturate and then perfused through the heart with heparinized saline followed by 10% formaldehyde in saline . the brains were removed for histology and recording locations confirmed on dorsal and ventral frontal convexities and within the principal sulcus . physiological data were analyzed just from successfully completed trials , on average including 17 repetitions for each combination of cue , choice stimulus type , and hemifield / spatial arrangement . for all analyses , spike data were smoothed with a gaussian kernel of sd 20  ms , cutoffs  1.5 sd . to measure neural discrimination between any two choice stimuli x and y for each cell in the population , we measured the difference in absolute firing rate for x and y. as is standard , euclidean distance was defined as the square root of the sum of these squared differences . for mds ( figure  2b ) , we used raw euclidean distances . for quantitative analysis ( figures 3 and 6 ) , we used a correction for the fact that euclidean distance must always be positive and scales with absolute firing rate . for each distance measure , we calculated the expected chance value by randomly permuting x , y labels across trials , then subtracted the median permuted value ( across 1,000 permutations ) from the obtained raw value . analyses were repeated at each 1  ms time point from 100  ms to 600  ms from choice stimulus onset . to measure discrimination between two - object displays and their component single stimuli ( figure  6 ) , we used activity vectors based on the full cell sample ( n  = 461 ) . to compare discrimination of the same stimulus pairs ( x ,  y ) in single- versus two - object displays ( figure  3 ) , we selected just those cells most sensitive to the critical discrimination , giving equal weight to single- and two - object data . for this purpose we used anova on activity of each cell over the full ( 0500  ms ) period of choice stimulus presentation , with factors critical stimulus ( x , y )  accompanying stimulus ( absent , present )  cue , and selected just those cells with a significant ( p  < 0.05 ) effect of critical stimulus . permutation testing was used to compare distances in single- and two - object cases ( figure  3 ) . on each permutation , for each cell we randomly maintained or switched single- and two - object labels ; when labels were switched , they were switched for all of that cell s data . after this permutation of labels the true difference in distances ( figure  3 ) was compared with the distribution of permuted values across 1,000 permutations . for comparison of mean neural activities for two - object displays and their component single stimuli ( figure  4b ) , we selected all cells with a significant difference between responses to singly presented targets on one side and nontargets on the other . significance ( p  < 0.05 ) was again determined by anova on activity across the full period of choice stimulus presentation , with factors stimulus ( e.g. , tcon , nips )  cue . < nips ; tips > ncon ; tips  < ncon ) as shown in figure  4b . for calculation of mean activity across cells ( figure  4b , figure  s2 ) , responses of each cell were first normalized by dividing by mean firing rate across all choice displays , calculated across the full 0500  ms display period . the same normalization was used to create scatterplots of response to each two - object display as a function of response to component single stimuli ( figure  5 ) .
summaryprefrontal cortex has been proposed to show highly adaptive information coding , with neurons dynamically allocated to processing task - relevant information . to track this dynamic allocation in monkey prefrontal cortex 
 , we used time - resolved measures of neural population activity in a simple case of competition between target ( behaviorally critical ) and nontarget objects in opposite visual hemifields . early in processing , there were parallel responses to competing inputs , with neurons in each hemisphere dominated by the contralateral stimulus . 
 later , the nontarget lost control of neural activity , with emerging global control by the behaviorally critical target . 
 the speed of transition reflected the competitive weights of different display elements , occurring most rapidly when relative behavioral significance was well established by training history . in line with adaptive coding , the results show widespread reallocation of prefrontal processing resources as an attentional focus is established .