Visuospatial coding in primate prefrontal neurons revealed by oculomotor paradigms

Unifying network model links recency and central tendency biases in working memory

The central tendency bias, or contraction bias, is a phenomenon where the judgment of the magnitude of items held in working memory appears to be biased toward the average of past observations. It is assumed to be an optimal strategy by the brain and commonly thought of as an expression of the brain's ability to learn the statistical structure of sensory input. On the other hand, recency biases such as serial dependence are also commonly observed and are thought to reflect the content of working memory. Recent results from an auditory delayed comparison task in rats suggest that both biases may be more related than previously thought: when the posterior parietal cortex (PPC) was silenced, both short-term and contraction biases were reduced. By proposing a model of the circuit that may be involved in generating the behavior, we show that a volatile working memory content susceptible to shifting to the past sensory experience - producing short-term sensory history biases - naturally leads to contraction bias. The errors, occurring at the level of individual trials, are sampled from the full distribution of the stimuli and are not due to a gradual shift of the memory toward the sensory distribution's mean. Our results are consistent with a broad set of behavioral findings and provide predictions of performance across different stimulus distributions and timings, delay intervals, as well as neuronal dynamics in putative working memory areas. Finally, we validate our model by performing a set of human psychophysics experiments of an auditory parametric working memory task.

The prefrontal cortex: from monkey to man

The prefrontal cortex is so important to human beings that, if deprived of it, our behaviour is reduced to action-reactions and automatisms, with no ability to make deliberate decisions. Why does the prefrontal cortex hold such importance in humans? In answer, this review draws on the proximity between humans and other primates, which enables us, through comparative anatomical-functional analysis, to understand the cognitive functions we have in common and specify those that distinguish humans from their closest cousins. First, a focus on the lateral region of the prefrontal cortex illustrates the existence of a continuum between rhesus monkeys (the most studied primates in neuroscience) and humans for most of the major cognitive functions in which this region of the brain plays a central role. This continuum involves the presence of elementary mental operations in the rhesus monkey (e.g. working memory or response inhibition) that are constitutive of 'macro-functions' such as planning, problem-solving and even language production. Second, the human prefrontal cortex has developed dramatically compared to that of other primates. This increase seems to concern the most anterior part (the frontopolar cortex). In humans, the development of the most anterior prefrontal cortex is associated with three major and interrelated cognitive changes: (i) a greater working memory capacity, allowing for greater integration of past experiences and prospective futures; (ii) a greater capacity to link discontinuous or distant data, whether temporal or semantic; and (iii) a greater capacity for abstraction, allowing humans to classify knowledge in different ways, to engage in analogical reasoning or to acquire abstract values that give rise to our beliefs and morals. Together, these new skills enable us, among other things, to develop highly sophisticated social interactions based on language, enabling us to conceive beliefs and moral judgements and to conceptualize, create and extend our vision of our environment beyond what we can physically grasp. Finally, a model of the transition of prefrontal functions between humans and non-human primates concludes this review.

Patricia Goldman-Rakic: a pioneer and leader in frontal lobe research

Our understanding of the organization of the frontal cortex can be traced back to the experimental studies in the late 1800s by Fritsch and Hitzig on the frontal cortex of dogs and the frontal cortex of monkeys by Ferrier. These studies and many other studies that followed focused on motor functions, but halfway through the 20th century, very little was understood about the role of the frontal lobe in the control of other functions, and it was generally thought that the frontal lobe did not play a significant role in cognition. One result was that studies of cortical functions in cognition were carried out largely on parietal and temporal cortical regions with surprisingly little interest in the frontal lobe. The first systematic studies of the effects of prefrontal lesions on non-human primates began around 1950, especially by Rosvold and Mishkin in the Laboratory of Psychology at the National Institute of Mental Health (NIMH) in the United States. With her background in development, Pat Goldman joined this laboratory in 1965 and began an examination of the effects of prefrontal lobectomy on behavior in infant rhesus monkeys, both during development and later as the animals grew into adulthood. Her developmental studies were groundbreaking as they demonstrated that the effects of early prefrontal lesions varied with precise age (including prenatal), precise lesion location, behaviors measured, and age at assessment. She also began in parallel extensive studies of the role of the prefrontal cortex for a range of functions (especially working memory) in adult monkeys, which led to an examination of factors that influenced functional outcomes after injury or disease. This research was critical in helping to identify the significant role of the prefrontal cortex in cognition in both normal brains and neurological diseases such as schizophrenia. Her pioneering study demonstrating the role of the prefrontal cortex in cognition led to a remarkable increase in the number of researchers studying prefrontal functions in both non-human primates and rodents. This review will chronicle the key findings in her 35+ years studying the prefrontal cortex and illustrate the course she set for generations to follow.

Delay-related activity in marmoset prefrontal cortex

Persistent delay-period activity in prefrontal cortex (PFC) has long been regarded as a neural signature of working memory (WM). Electrophysiological investigations in macaque PFC have provided much insight into WM mechanisms; however, a barrier to understanding is the fact that a portion of PFC lies buried within the principal sulcus in this species and is inaccessible for laminar electrophysiology or optical imaging. The relatively lissencephalic cortex of the New World common marmoset (Callithrix jacchus) circumvents such limitations. It remains unknown, however, whether marmoset PFC neurons exhibit persistent activity. Here, we addressed this gap by conducting wireless electrophysiological recordings in PFC of marmosets performing a delayed-match-to-location task on a home cage-based touchscreen system. As in macaques, marmoset PFC neurons exhibited sample-, delay-, and response-related activity that was directionally tuned and linked to correct task performance. Models constructed from population activity consistently and accurately predicted stimulus location throughout the delay period, supporting a framework of delay activity in which mnemonic representations are relatively stable in time. Taken together, our findings support the existence of common neural mechanisms underlying WM performance in PFC of macaques and marmosets and thus validate the marmoset as a suitable model animal for investigating the microcircuitry underlying WM.

Using Nonhuman Primate Models to Reverse-Engineer Prefrontal Circuit Failure Underlying Cognitive Deficits in Schizophrenia

In this chapter, I review studies in nonhuman primates that emulate the circuit failure in prefrontal cortex responsible for working memory and cognitive control deficits in schizophrenia. These studies have characterized how synaptic malfunction, typically induced by blockade of NMDAR, disrupts neural function and computation in prefrontal networks to explain errors in cognitive tasks that are seen in schizophrenia. This work is finding causal relationships between pathogenic events of relevance to schizophrenia at vastly different levels of scale, from synapses, to neurons, local, circuits, distributed networks, computation, and behavior. Pharmacological manipulation, the dominant approach in primate models, has limited construct validity for schizophrenia pathogenesis, as the disease results from a complex interplay between environmental, developmental, and genetic factors. Genetic manipulation replicating schizophrenia risk is more advanced in rodent models. Nonetheless, gene manipulation in nonhuman primates is rapidly advancing, and primate developmental models have been established. Integration of large scale neural recording, genetic manipulation, and computational modeling in nonhuman primates holds considerable potential to provide a crucial schizophrenia model moving forward. Data generated by this approach is likely to fill several crucial gaps in our understanding of the causal sequence leading to schizophrenia in humans. This causal chain presents a vexing problem largely because it requires understanding how events at very different levels of scale relate to one another, from genes to circuits to cognition to social interactions. Nonhuman primate models excel here. They optimally enable discovery of causal relationships across levels of scale in the brain that are relevant to cognitive deficits in schizophrenia. The mechanistic understanding of prefrontal circuit failure they promise to provide may point the way to more effective therapeutic interventions to restore function to prefrontal networks in the disease.

Long-term learning transforms prefrontal cortex representations during working memory

The role of the lateral prefrontal cortex (lPFC) in working memory (WM) is debated. Non-human primate (NHP) electrophysiology shows that the lPFC stores WM representations, but human neuroimaging suggests that the lPFC controls WM content in sensory cortices. These accounts are confounded by differences in task training and stimulus exposure. We tested whether long-term training alters lPFC function by densely sampling WM activity using functional MRI. Over 3 months, participants trained on both a WM and serial reaction time (SRT) task, wherein fractal stimuli were embedded within sequences. WM performance improved for trained (but not novel) fractals and, neurally, delay activity increased in distributed lPFC voxels across learning. Item-level WM representations became detectable within lPFC patterns, and lPFC activity reflected sequence relationships from the SRT task. These findings demonstrate that human lPFC develops stimulus-selective responses with learning, and WM representations are shaped by long-term experience, which could reconcile competing accounts of WM functioning.

The Spatiotemporal Neural Dynamics of Intersensory Attention Capture of Salient Stimuli: A Large-Scale Auditory-Visual Modeling Study

The spatiotemporal dynamics of the neural mechanisms underlying endogenous (top-down) and exogenous (bottom-up) attention, and how attention is controlled or allocated in intersensory perception are not fully understood. We investigated these issues using a biologically realistic large-scale neural network model of visual-auditory object processing of short-term memory. We modeled and incorporated into our visual-auditory object-processing model the temporally changing neuronal mechanisms for the control of endogenous and exogenous attention. The model successfully performed various bimodal working memory tasks, and produced simulated behavioral and neural results that are consistent with experimental findings. Simulated fMRI data were generated that constitute predictions that human experiments could test. Furthermore, in our visual-auditory bimodality simulations, we found that increased working memory load in one modality would reduce the distraction from the other modality, and a possible network mediating this effect is proposed based on our model.

Thunderstruck: The ACDC model of flexible sequences and rhythms in recurrent neural circuits

Adaptive sequential behavior is a hallmark of human cognition. In particular, humans can learn to produce precise spatiotemporal sequences given a certain context. For instance, musicians can not only reproduce learned action sequences in a context-dependent manner, they can also quickly and flexibly reapply them in any desired tempo or rhythm without overwriting previous learning. Existing neural network models fail to account for these properties. We argue that this limitation emerges from the fact that sequence information (i.e., the position of the action) and timing (i.e., the moment of response execution) are typically stored in the same neural network weights. Here, we augment a biologically plausible recurrent neural network of cortical dynamics to include a basal ganglia-thalamic module which uses reinforcement learning to dynamically modulate action. This “associative cluster-dependent chain” (ACDC) model modularly stores sequence and timing information in distinct loci of the network. This feature increases computational power and allows ACDC to display a wide range of temporal properties (e.g., multiple sequences, temporal shifting, rescaling, and compositionality), while still accounting for several behavioral and neurophysiological empirical observations. Finally, we apply this ACDC network to show how it can learn the famous “Thunderstruck” song intro and then flexibly play it in a “bossa nova” rhythm without further training.

How do humans flexibly adapt action sequences? For instance, musicians can learn a song and quickly speed up or slow down the tempo, or even play the song following a completely different rhythm (e.g., a rock song using a bossa nova rhythm). In this work, we build a biologically plausible network of cortico-basal ganglia interactions that explains how this temporal flexibility may emerge in the brain. Crucially, our model factorizes sequence order and action timing, respectively represented in cortical and basal ganglia dynamics. This factorization allows full temporal flexibility, i.e. the timing of a learned action sequence can be recomposed without interfering with the order of the sequence. As such, our model is capable of learning asynchronous action sequences, and flexibly shift, rescale, and recompose them, while accounting for biological data.

Delayed-matching-to-position working memory in mice relies on NMDA-receptors in prefrontal pyramidal cells

A hypofunction of N-methyl-D-aspartate glutamate receptors (NMDARs) has been implicated in the pathogenesis of schizophrenia by clinical and rodent studies. However, to what extent NMDAR-hypofunction in distinct cell-types across the brain causes different symptoms of this disease is largely unknown. One pharmaco-resistant core symptom of schizophrenia is impaired working memory (WM). NMDARs have been suggested to mediate sustained firing in excitatory neurons of the prefrontal cortex (PFC) that might underlie WM storage. However, if NMDAR-hypofunction in prefrontal excitatory neurons may indeed entail WM impairments is unknown. We here investigated this question in mice, in which NMDARs were genetically-ablated in PFC excitatory cells. This cell type-selective NMDAR-hypofunction caused a specific deficit in a delayed-matching-to-position (DMTP) 5-choice-based operant WM task. In contrast, T-maze rewarded alternation and several psychological functions including attention, spatial short-term habituation, novelty-processing, motivation, sociability, impulsivity, and hedonic valuation remained unimpaired at the level of GluN1-hypofunction caused by our manipulation. Our data suggest that a hypofunction of NMDARs in prefrontal excitatory neurons may indeed cause WM impairments, but are possibly not accounting for most other deficits in schizophrenia.

Comparative anatomy of the macaque and the human frontal oculomotor domain

In non-human primates, at the junction of the prefrontal with the premotor cortex, there is a sector designated as frontal eye field (FEF), involved in controlling oculomotor behavior and spatial attention. Evidence for at least two FEFs in humans is at the basis of the still open issue of the possible homologies between the macaque and the human frontal oculomotor system. In this review article we address this issue suggesting a new view solidly grounded on evidence from the last decade showing that, in macaques, the FEF is at the core of an oculomotor domain in which several distinct areas, including areas 45A and 45B, provide the substrate for parallel processing of different aspects of oculomotor behavior. Based on comparative considerations, we will propose a correspondence between some of the macaque and the human oculomotor fields, thus suggesting sharing of neural substrate for oculomotor control, gaze processing, and orienting attention in space. Accordingly, this article could contribute to settle some aspects of the so-called "enigma" of the human FEF anatomy.

Effects of Transcranial Direct Current Stimulation on Information Processing Speed, Working Memory, Attention, and Social Cognition in Multiple Sclerosis

Multiple Sclerosis (MS) is a chronic inflammatory disease of the central nervous system. Cognitive impairment occurs in 40-65% of patients and could drastically affect their quality of life. Deficits could involve general cognition (e.g., attention and working memory) as well as social cognition. Transcranial direct current stimulation (tDCS), is a novel brain stimulation technique that has been assessed in the context of several neuropsychiatric symptoms, including those described in the context of MS. However, very rare trials have assessed tDCS effects on general cognition in MS, and none has tackled social cognition. The aim of this work was to assess tDCS effects on general and social cognition in MS. Eleven right-handed patients with MS received two blocks (bifrontal tDCS and sham, 2 mA, 20 min, anode/cathode over left/right prefrontal cortex) of 5 daily stimulations separated by a 3-week washout interval. Working memory and attention were, respectively, measured using N-Back Test (0-Back, 1-Back, and 2-Back) and Symbol Digit Modalities Test (SDMT) at the first and fifth day of each block and 1 week later. Social cognition was evaluated using Faux Pas Test and Eyes Test at baseline and 1 week after each block. Interestingly, accuracy of 1-Back test improved following sham but not active bifrontal tDCS. Therefore, active bifrontal tDCS could have impaired working memory via cathodal stimulation of the right prefrontal cortex. No significant tDCS effects were observed on social cognitive measures and SDMT. Admitting the small sample size and the learning (practice) effect that might arise from the repetitive administration of each task, the current results should be considered as preliminary and further investigations in larger patient samples are needed to gain a closer understanding of tDCS effects on cognition in MS.

Dynamic shifts of visual and saccadic signals in prefrontal cortical regions 8Ar and FEF

Active vision is a fundamental process by which primates gather information about the external world. Multiple brain regions have been studied in the context of simple active vision tasks in which a visual target's appearance is temporally separated from saccade execution. Most neurons have tight spatial registration between visual and saccadic signals, and in areas such as prefrontal cortex (PFC), some neurons show persistent delay activity that links visual and motor epochs and has been proposed as a basis for spatial working memory. Many PFC neurons also show rich dynamics, which have been attributed to alternative working memory codes and the representation of other task variables. Our study investigated the transition between processing a visual stimulus and generating an eye movement in populations of PFC neurons in macaque monkeys performing a memory guided saccade task. We found that neurons in two subregions of PFC, the frontal eye fields (FEF) and area 8Ar, differed in their dynamics and spatial response profiles. These dynamics could be attributed largely to shifts in the spatial profile of visual and motor responses in individual neurons. This led to visual and motor codes for particular spatial locations that were instantiated by different mixtures of neurons, which could be important in PFC's flexible role in multiple sensory, cognitive, and motor tasks.NEW & NOTEWORTHY A central question in neuroscience is how the brain transitions from sensory representations to motor outputs. The prefrontal cortex contains neurons that have long been implicated as important in this transition and in working memory. We found evidence for rich and diverse tuning in these neurons, which was often spatially misaligned between visual and saccadic responses. This feature may play an important role in flexible working memory capabilities.

Unsupervised Learning of Persistent and Sequential Activity

Two strikingly distinct types of activity have been observed in various brain structures during delay periods of delayed response tasks: Persistent activity (PA), in which a sub-population of neurons maintains an elevated firing rate throughout an entire delay period; and Sequential activity (SA), in which sub-populations of neurons are activated sequentially in time. It has been hypothesized that both types of dynamics can be “learned” by the relevant networks from the statistics of their inputs, thanks to mechanisms of synaptic plasticity. However, the necessary conditions for a synaptic plasticity rule and input statistics to learn these two types of dynamics in a stable fashion are still unclear. In particular, it is unclear whether a single learning rule is able to learn both types of activity patterns, depending on the statistics of the inputs driving the network. Here, we first characterize the complete bifurcation diagram of a firing rate model of multiple excitatory populations with an inhibitory mechanism, as a function of the parameters characterizing its connectivity. We then investigate how an unsupervised temporally asymmetric Hebbian plasticity rule shapes the dynamics of the network. Consistent with previous studies, we find that for stable learning of PA and SA, an additional stabilization mechanism is necessary. We show that a generalized version of the standard multiplicative homeostatic plasticity (Renart et al., 2003; Toyoizumi et al., 2014) stabilizes learning by effectively masking excitatory connections during stimulation and unmasking those connections during retrieval. Using the bifurcation diagram derived for fixed connectivity, we study analytically the temporal evolution and the steady state of the learned recurrent architecture as a function of parameters characterizing the external inputs. Slow changing stimuli lead to PA, while fast changing stimuli lead to SA. Our network model shows how a network with plastic synapses can stably and flexibly learn PA and SA in an unsupervised manner.

How the motor system integrates with working memory

Working memory is vital for basic functions in everyday life. During working memory, one holds a finite amount of information in mind until it is no longer required or when resources to maintain this information are depleted. Convergence of neuroimaging data indicates that working memory is supported by the motor system, and in particular, by regions that are involved in motor planning and preparation, in the absence of overt movement. These "secondary motor" regions are physically located between primary motor and non-motor regions, within the frontal lobe, cerebellum, and basal ganglia, creating a functionally organized gradient. The contribution of secondary motor regions to working memory may be to generate internal motor traces that reinforce the representation of information held in mind. The primary aim of this review is to elucidate motor-cognitive interactions through the lens of working memory using the Sternberg paradigm as a model and to suggest origins of the motor-cognitive interface. In addition, we discuss the implications of the motor-cognitive relationship for clinical groups with motor network deficits.

Updating spatial working memory in a dynamic visual environment

The present review describes recent developments regarding the role of the eye movement system in representing spatial information and keeping track of locations of relevant objects. First, we discuss the active vision perspective and why eye movements are considered crucial for perception and attention. The second part focuses on the question of how the oculomotor system is used to represent spatial attentional priority, and the role of the oculomotor system in maintenance of this spatial information. Lastly, we discuss recent findings demonstrating rapid updating of information across saccadic eye movements. We argue that the eye movement system plays a key role in maintaining and rapidly updating spatial information. Furthermore, we suggest that rapid updating emerges primarily to make sure actions are minimally affected by intervening eye movements, allowing us to efficiently interact with the world around us.

Quantifying Differences Between Passive and Task-Evoked Intrinsic Functional Connectivity in a Large-Scale Brain Simulation

Establishing a connection between intrinsic and task-evoked brain activities is critical because it would provide a way to map task-related brain regions in patients unable to comply with such tasks. A crucial question within this realm is to what extent the execution of a cognitive task affects the intrinsic activity of brain regions not involved in the task. Computational models can be useful to answer this question because they allow us to distinguish task from nontask neural elements while giving us the effects of task execution on nontask regions of interest at the neuroimaging level. The quantification of those effects in a computational model would represent a step toward elucidating the intrinsic versus task-evoked connection. In this study we used computational modeling and graph theoretical metrics to quantify changes in intrinsic functional brain connectivity due to task execution. We used our large-scale neural modeling framework to embed a computational model of visual short-term memory into an empirically derived connectome. We simulated a neuroimaging study consisting of 10 subjects performing passive fixation (PF), passive viewing (PV), and delayed match-to-sample (DMS) tasks. We used the simulated blood oxygen level-dependent functional magnetic resonance imaging time series to calculate functional connectivity (FC) matrices and used those matrices to compute several graph theoretical measures. After determining that the simulated graph theoretical measures were largely consistent with experiments, we were able to quantify the differences between the graph metrics of the PF condition and those of the PV and DMS conditions. Thus, we show that we can use graph theoretical methods applied to simulated brain networks to aid in the quantification of changes in intrinsic brain FC during task execution. Our results represent a step toward establishing a connection between intrinsic and task-related brain activities.

Selective Loss of Thin Spines in Area 7a of the Primate Intraparietal Sulcus Predicts Age-Related Working Memory Impairment

Brodmann area 7a of the parietal cortex is active during working memory tasks in humans and nonhuman primates, but the composition and density of dendritic spines in area 7a and their relevance both to working memory and cognitive aging remain unexplored. Aged monkeys have impaired working memory, and we have previously shown that this age-induced cognitive impairment is partially mediated by a loss of thin spines in prefrontal cortex area 46, a critical area for working memory. Because area 46 is reciprocally connected with area 7a of the parietal cortex and 7a mediates visual attention integration, we hypothesized that thin spine density in area 7a would correlate with working memory performance as well. To investigate the synaptic profile of area 7a and its relevance to working memory and cognitive aging, we investigated differences in spine type and density in layer III pyramidal cells of area 7a in young and aged, male and female rhesus macaques (Macaca mulatta) that were cognitively assessed using the delayed response test of working memory. Area 7a shows age-related loss of thin spines, and thin spine density positively correlates with delayed response performance in aged monkeys. In contrast, these cells show no age-related changes in dendritic length or branching. These changes mirror age-related changes in area 46 but are distinct from other neocortical regions, such as V1. These findings support our hypothesis that cognitive aging is driven primarily by synaptic changes, and more specifically by changes in thin spines, in key association areas.SIGNIFICANCE STATEMENT This study advances our understanding of cognitive aging by demonstrating the relevance of area 7a thin spines to working memory performance. This study is the first to look at cognitive aging in the intraparietal sulcus, and also the first to report spine or dendritic measures for area 7a in either young adult or aged nonhuman primates. These results contribute to the hypothesis that thin spines support working memory performance and confirm our prior observation that cognitive aging is driven by synaptic changes rather than changes in dendritic morphology or neuron death. Importantly, these data show that age-related working memory changes are not limited to disruptions of the prefrontal cortex but also include an association region heavily interconnected with prefrontal cortex.

Functional reorganisation and recovery following cortical lesions: A preliminary study in macaque monkeys

Damage following traumatic brain injury or stroke can often extend beyond the boundaries of the initial insult and can lead to maladaptive cortical reorganisation. On the other hand, beneficial cortical reorganisation leading to recovery of function can also occur. We used resting state FMRI to investigate how cortical networks in the macaque brain change across time in response to lesions to the prefrontal cortex, and how this reorganisation correlated with changes in behavioural performance in cognitive tasks. After prelesion testing and scanning, two monkeys received a lesion to regions surrounding the left principal sulcus followed by periodic testing and scanning. Later, the animals received another lesion to the opposite hemisphere and additional testing and scanning. Following the first lesion, we observed both a behavioural impairment and decrease in functional connectivity, predominantly in frontal-frontal networks. Approximately 8 weeks later, performance and connectivity patterns both improved. Following the second lesion, we observed a further behavioural deficit and decrease in connectivity that showed little recovery. We discuss how different mechanisms including alternate behavioural strategies and reorganisation of specific prefrontal networks may have led to improvements in behaviour. Further work will be needed to confirm these mechanisms.

Simulating laminar neuroimaging data for a visual delayed match-to-sample task

Invasive electrophysiological and neuroanatomical studies in nonhuman mammalian experimental preparations have helped elucidate the lamina (layer) dependence of neural computations and interregional connections. Noninvasive functional neuroimaging can, in principle, resolve cortical laminae (layers), and thus provide insight into human neural computations and interregional connections. However human neuroimaging data are noisy and difficult to interpret; biologically realistic simulations can aid experimental interpretation by relating the neuroimaging data to simulated neural activity. We illustrate the potential of laminar neuroimaging by upgrading an existing large-scale, multiregion neural model that simulates a visual delayed match-to-sample (DMS) task. The new laminar-based neural unit incorporates spiny stellate, pyramidal, and inhibitory neural populations which are divided among supragranular, granular, and infragranular laminae (layers). We simulated neural activity which is translated into local field potential-like data used to simulate conventional and laminar fMRI activity. We implemented the laminar connectivity schemes proposed by Felleman and Van Essen (Cerebral Cortex, 1991) for interregional connections. The hemodynamic model that we employ is a modified version of one due to Heinzle et al. (Neuroimage, 2016) that incorporates the effects of draining veins. We show that the laminar version of the model replicates the findings of the existing model. The laminar model shows the finer structure in fMRI activity and functional connectivity. Laminar differences in the magnitude of neural activities are a prominent finding; these are also visible in the simulated fMRI. We illustrate differences between task and control conditions in the fMRI signal, and demonstrate differences in interregional laminar functional connectivity that reflect the underlying connectivity scheme. These results indicate that multi-layer computational models can aid in interpreting layer-specific fMRI, and suggest that increased use of laminar fMRI could provide unique and fundamental insights to human neuroscience.

Attentional Changes in Either Criterion or Sensitivity Are Associated with Robust Modulations in Lateral Prefrontal Cortex

Visual attention is associated with neuronal changes across the brain, and these widespread signals are generally assumed to underlie a unitary mechanism of attention. However, using signal detection theory, attention-related effects on performance can be partitioned into changes in either the subject's criterion or sensitivity. Neuronal modulations associated with only sensitivity changes were previously observed in visual cortex, raising questions about which structures mediate attention-related changes in criterion and whether individual neurons are involved in multiple components of attention. Here, we recorded from monkey lateral prefrontal cortex (LPFC) and found that, in contrast to visual cortex, neurons in LPFC changed their firing rates, pairwise correlation, and Fano factor when subjects changed either their criterion or their sensitivity. These results indicate that attention-related neuronal modulations in separate brain regions are not a monolithic signal and instead can be linked to distinct behavioral changes.

Exploration Disrupts Choice-Predictive Signals and Alters Dynamics in Prefrontal Cortex

In uncertain environments, decision-makers must balance two goals: they must "exploit" rewarding options but also "explore" in order to discover rewarding alternatives. Exploring and exploiting necessarily change how the brain responds to identical stimuli, but little is known about how these states, and transitions between them, change how the brain transforms sensory information into action. To address this question, we recorded neural activity in a prefrontal sensorimotor area while monkeys naturally switched between exploring and exploiting rewarding options. We found that exploration profoundly reduced spatially selective, choice-predictive activity in single neurons and delayed choice-predictive population dynamics. At the same time, reward learning was increased in brain and behavior. These results indicate that exploration is related to sudden disruptions in prefrontal sensorimotor control and rapid, reward-dependent reorganization of control dynamics. This may facilitate discovery through trial and error.

Neuromodulation of Prefrontal Cortex in Non-Human Primates by Dopaminergic Receptors during Rule-Guided Flexible Behavior and Cognitive Control

The prefrontal cortex (PFC) is indispensable for several higher-order cognitive and executive capacities of primates, including representation of salient stimuli in working memory (WM), maintenance of cognitive task set, inhibition of inappropriate responses and rule-guided flexible behavior. PFC networks are subject to robust neuromodulation from ascending catecholaminergic systems. Disruption of these systems in PFC has been implicated in cognitive deficits associated with several neuropsychiatric disorders. Over the past four decades, a considerable body of work has examined the influence of dopamine on macaque PFC activity representing spatial WM. There has also been burgeoning interest in neuromodulation of PFC circuits involved in other cognitive functions of PFC, including representation of rules to guide flexible behavior. Here, we review recent neuropharmacological investigations conducted in our laboratory and others of the role of PFC dopamine receptors in regulating rule-guided behavior in non-human primates. Employing iontophoresis, we examined the effects of local manipulation of dopaminergic subtypes on neuronal activity during performance of rule-guided pro- and antisaccades, an experimental paradigm sensitive to PFC integrity, wherein deficits in performance are reliably observed in many neuropsychiatric disorders. We found dissociable effects of dopamine receptors on neuronal activity for rule representation and oculomotor responses and discuss these findings in the context of prior studies that have examined the role of dopamine in spatial delayed response tasks, attention, target selection, abstract rules, visuomotor learning and reward. The findings we describe here highlight the common features, as well as heterogeneity and context dependence of dopaminergic neuromodulation in regulating the efficacy of cognitive functions of PFC in health and disease.

Neural Coding for Action Execution and Action Observation in the Prefrontal Cortex and Its Role in the Organization of Socially Driven Behavior

The lateral prefrontal cortex (LPF) plays a fundamental role in planning, organizing, and optimizing behavioral performance. Neuroanatomical and neurophysiological studies have suggested that in this cortical sector, information processing becomes more abstract when moving from caudal to rostral and that such processing involves parietal and premotor areas. We review studies that have shown that the LPF, in addition to its involvement in implementing rules and setting behavioral goals, activates during the execution of forelimb movements even in the absence of a learned relationship between an instruction and its associated motor output. Thus, we propose that the prefrontal cortex is involved in exploiting contextual information for planning and guiding behavioral responses, also in natural situations. Among contextual cues, those provided by others' actions are particularly relevant for social interactions. Functional studies of macaques have demonstrated that the LPF is activated by the observation of biological stimuli, in particular those related to goal-directed actions. We review these studies and discuss the idea that the prefrontal cortex codes high-order representations of observed actions rather than simple visual descriptions of them. Based on evidence that the same sector of the LPF contains both neurons coding own action goals and neurons coding others' goals, we propose that this sector is involved in the selection of own actions appropriate for reacting in a particular social context and for the creation of new action sequences in imitative learning.

Prefrontal Contribution to Decision-Making under Free-Choice Conditions

Executive function is thought to be the coordinated operation of multiple neural processes and allows to accomplish a current goal flexibly. The most important function of the prefrontal cortex is the executive function. Among a variety of executive functions in which the prefrontal cortex participates, decision-making is one of the most important. Although the prefrontal contribution to decision-making has been examined using a variety of behavioral tasks, recent studies using fMRI have shown that the prefrontal cortex participates in decision-making under free-choice conditions. Since decision-making under free-choice conditions represents the very first stage for any kind of decision-making process, it is important that we understand its neural mechanism. Although few studies have examined this issue while a monkey performed a free-choice task, those studies showed that, when the monkey made a decision to subsequently choose one particular option, prefrontal neurons showing selectivity to that option exhibited transient activation just before presentation of the imperative cue. Further studies have suggested that this transient increase is caused by the irregular fluctuation of spontaneous firing just before cue presentation, which enhances the response to the cue and biases the strength of the neuron's selectivity to the option. In addition, this biasing effect was observed only in neurons that exhibited sustained delay-period activity, indicating that this biasing effect not only influences the animal's decision for an upcoming choice, but also is linked to working memory mechanisms in the prefrontal cortex.

Using a Large-scale Neural Model of Cortical Object Processing to Investigate the Neural Substrate for Managing Multiple Items in Short-term Memory

Many cognitive and computational models have been proposed to help understand working memory. In this article, we present a simulation study of cortical processing of visual objects during several working memory tasks using an extended version of a previously constructed large-scale neural model [Tagamets, M. A., & Horwitz, B. Integrating electrophysiological and anatomical experimental data to create a large-scale model that simulates a delayed match-to-sample human brain imaging study. Cerebral Cortex, 8, 310-320, 1998]. The original model consisted of arrays of Wilson-Cowan type of neuronal populations representing primary and secondary visual cortices, inferotemporal (IT) cortex, and pFC. We added a module representing entorhinal cortex, which functions as a gating module. We successfully implemented multiple working memory tasks using the same model and produced neuronal patterns in visual cortex, IT cortex, and pFC that match experimental findings. These working memory tasks can include distractor stimuli or can require that multiple items be retained in mind during a delay period (Sternberg's task). Besides electrophysiology data and behavioral data, we also generated fMRI BOLD time series from our simulation. Our results support the involvement of IT cortex in working memory maintenance and suggest the cortical architecture underlying the neural mechanisms mediating particular working memory tasks. Furthermore, we noticed that, during simulations of memorizing a list of objects, the first and last items in the sequence were recalled best, which may implicate the neural mechanism behind this important psychological effect (i.e., the primacy and recency effect).

Tracking the effect of emotional distraction in working memory brain networks: Evidence from an MEG study

The active maintenance of information in visual working memory (WM) is known to rely on the sustained activity over functional networks including frontal, parietal, occipital, and temporal cortices. Previous studies have described interference-based disturbances in the functional coupling between prefrontal and posterior cortices, and that such disturbances can be restored for a successful WM performance after the presentation of the interfering stimulus. However, very few studies have applied functional connectivity measures to the analysis of the brain dynamics involved in overriding emotional distraction, and all of them have limited their analysis to the particular connections between the amygdala and prefrontal cortex. In this study, we used magnetoencephalography (MEG) to characterize the mutual information-based functional connectivity dynamics among regions of interest located over the prefrontal, the parietal, the temporal, and the occipital cortex. Our results show that the detection of emotional distraction at early latencies (50-150 ms) induces a reduction of functional connectivity involving parietal and temporal cortices that are part of the frontoposterior WM network, while functional coupling among prefrontal areas and between them and posterior cortices is strengthened during the detection of emotional distractors. Later in the processing of the distractor (250-350 and 360-460 ms), the frontoposterior coupling is reestablished for a successful performance, while the orbitofrontal and ventrolateral prefrontal cortex become strongly connected to posterior cortices as a mechanism to cope with emotional distractors.

On memories, neural ensembles and mental flexibility

Memories are assumed to be represented by groups of co-activated neurons, called neural ensembles. Describing ensembles is a challenge: complexity of the underlying micro-circuitry is immense. Current approaches use a piecemeal fashion, focusing on single neurons and employing local measures like pairwise correlations. We introduce an alternative approach that identifies ensembles and describes the effective connectivity between them in a holistic fashion. It also links the oscillatory frequencies observed in ensembles with the spatial scales at which activity is expressed. Using unsupervised learning, biophysical modeling and graph theory, we analyze multi-electrode LFPs from frontal cortex during a spatial delayed response task. We find distinct ensembles for different cues and more parsimonious connectivity for cues on the horizontal axis, which may explain the oblique effect in psychophysics. Our approach paves the way for biophysical models with learned parameters that can guide future Brain Computer Interface development.

Fixation target representation in prefrontal cortex during the antisaccade task

Neurons that discharge strongly during the time period of fixation of a visual target and cease to discharge before saccade initiation have been described in the brain stem, superior colliculus, and cortical areas. In subcortical structures, fixation neurons play a reciprocal role with saccadic neurons during the generation of eye movements. Their role in the dorsolateral prefrontal cortex is less obvious, and it is not known if they are activated by fixation, inhibit saccade generation, or play a role in more complex functions such as the inhibition of inappropriate responses. We examined the properties of prefrontal fixation neurons in the context of an antisaccade task, which requires an eye movement directed away from a prepotent visual stimulus. We tested monkeys with variants of the task, allowing us to dissociate activity synchronized on the fixation offset, presentation of the visual stimulus, and saccadic onset. Fixation neuron activity latency was most strongly tied to the offset of the fixation point across task variants. It was not well predicted by the appearance of the visual stimulus, which is essential for planning of the correct eye movement and inhibiting inappropriate ones. Activity of fixation neurons was generally negatively correlated with that of saccade neurons; however, critical differences in timing make it unlikely that they provide precisely timed signals for the generation of eye movements. These results demonstrate the role of fixation neurons in the prefrontal cortex during tasks requiring timing of appropriate eye movement and inhibition of inappropriate actions.NEW & NOTEWORTHY Properties of neurons that discharge during eye fixation and go silent before saccade initiation have been described in subcortical structures involved in eye movement generation, but their role in the dorsolateral prefrontal cortex presents a puzzle. Our results demonstrate the role of fixation neurons in the prefrontal cortex during tasks requiring precise timing of appropriate eye movement and inhibition of inappropriate actions.

Sleep deprivation as an experimental model system for psychosis: Effects on smooth pursuit, prosaccades, and antisaccades

Current antipsychotic medications fail to satisfactorily reduce negative and cognitive symptoms and produce many unwanted side effects, necessitating the development of new compounds. Cross-species, experimental behavioural model systems can be valuable to inform the development of such drugs. The aim of the current study was to further test the hypothesis that controlled sleep deprivation is a safe and effective model system for psychosis when combined with oculomotor biomarkers of schizophrenia. Using a randomized counterbalanced within-subjects design, we investigated the effects of 1 night of total sleep deprivation in 32 healthy participants on smooth pursuit eye movements (SPEM), prosaccades (PS), antisaccades (AS), and self-ratings of psychosis-like states. Compared with a normal sleep control night, sleep deprivation was associated with reduced SPEM velocity gain, higher saccadic frequency at 0.2 Hz, elevated PS spatial error, and an increase in AS direction errors. Sleep deprivation also increased intra-individual variability of SPEM, PS, and AS measures. In addition, sleep deprivation induced psychosis-like experiences mimicking hallucinations, cognitive disorganization, and negative symptoms, which in turn had moderate associations with AS direction errors. Taken together, sleep deprivation resulted in psychosis-like impairments in SPEM and AS performance. However, diverging somewhat from the schizophrenia literature, sleep deprivation additionally disrupted PS control. Sleep deprivation thus represents a promising but possibly unspecific experimental model that may be helpful to further improve our understanding of the underlying mechanisms in the pathophysiology of psychosis and aid the development of antipsychotic and pro-cognitive drugs.

Stable population coding for working memory coexists with heterogeneous neural dynamics in prefrontal cortex

Working memory (WM) is a cognitive function for temporary maintenance and manipulation of information, which requires conversion of stimulus-driven signals into internal representations that are maintained across seconds-long mnemonic delays. Within primate prefrontal cortex (PFC), a critical node of the brain's WM network, neurons show stimulus-selective persistent activity during WM, but many of them exhibit strong temporal dynamics and heterogeneity, raising the questions of whether, and how, neuronal populations in PFC maintain stable mnemonic representations of stimuli during WM. Here we show that despite complex and heterogeneous temporal dynamics in single-neuron activity, PFC activity is endowed with a population-level coding of the mnemonic stimulus that is stable and robust throughout WM maintenance. We applied population-level analyses to hundreds of recorded single neurons from lateral PFC of monkeys performing two seminal tasks that demand parametric WM: oculomotor delayed response and vibrotactile delayed discrimination. We found that the high-dimensional state space of PFC population activity contains a low-dimensional subspace in which stimulus representations are stable across time during the cue and delay epochs, enabling robust and generalizable decoding compared with time-optimized subspaces. To explore potential mechanisms, we applied these same population-level analyses to theoretical neural circuit models of WM activity. Three previously proposed models failed to capture the key population-level features observed empirically. We propose network connectivity properties, implemented in a linear network model, which can underlie these features. This work uncovers stable population-level WM representations in PFC, despite strong temporal neural dynamics, thereby providing insights into neural circuit mechanisms supporting WM.

Spatial transformations between superior colliculus visual and motor response fields during head-unrestrained gaze shifts

We previously reported that visuomotor activity in the superior colliculus (SC)--a key midbrain structure for the generation of rapid eye movements--preferentially encodes target position relative to the eye (Te) during low-latency head-unrestrained gaze shifts (DeSouza et al., 2011). Here, we trained two monkeys to perform head-unrestrained gaze shifts after a variable post-stimulus delay (400-700 ms), to test whether temporally separated SC visual and motor responses show different spatial codes. Target positions, final gaze positions and various frames of reference (eye, head, and space) were dissociated through natural (untrained) trial-to-trial variations in behaviour. 3D eye and head orientations were recorded, and 2D response field data were fitted against multiple models by use of a statistical method reported previously (Keith et al., 2009). Of 60 neurons, 17 showed a visual response, 12 showed a motor response, and 31 showed both visual and motor responses. The combined visual response field population (n = 48) showed a significant preference for Te, which was also preferred in each visual subpopulation. In contrast, the motor response field population (n = 43) showed a preference for final (relative to initial) gaze position models, and the Te model was statistically eliminated in the motor-only population. There was also a significant shift of coding from the visual to motor response within visuomotor neurons. These data confirm that SC response fields are gaze-centred, and show a target-to-gaze transformation between visual and motor responses. Thus, visuomotor transformations can occur between, and even within, neurons within a single frame of reference and brain structure.

Embedding Task-Based Neural Models into a Connectome-Based Model of the Cerebral Cortex

A number of recent efforts have used large-scale, biologically realistic, neural models to help understand the neural basis for the patterns of activity observed in both resting state and task-related functional neural imaging data. An example of the former is The Virtual Brain (TVB) software platform, which allows one to apply large-scale neural modeling in a whole brain framework. TVB provides a set of structural connectomes of the human cerebral cortex, a collection of neural processing units for each connectome node, and various forward models that can convert simulated neural activity into a variety of functional brain imaging signals. In this paper, we demonstrate how to embed a previously or newly constructed task-based large-scale neural model into the TVB platform. We tested our method on a previously constructed large-scale neural model (LSNM) of visual object processing that consisted of interconnected neural populations that represent, primary and secondary visual, inferotemporal, and prefrontal cortex. Some neural elements in the original model were “non-task-specific” (NS) neurons that served as noise generators to “task-specific” neurons that processed shapes during a delayed match-to-sample (DMS) task. We replaced the NS neurons with an anatomical TVB connectome model of the cerebral cortex comprising 998 regions of interest interconnected by white matter fiber tract weights. We embedded our LSNM of visual object processing into corresponding nodes within the TVB connectome. Reciprocal connections between TVB nodes and our task-based modules were included in this framework. We ran visual object processing simulations and showed that the TVB simulator successfully replaced the noise generation originally provided by NS neurons; i.e., the DMS tasks performed with the hybrid LSNM/TVB simulator generated equivalent neural and fMRI activity to that of the original task-based models. Additionally, we found partial agreement between the functional connectivities using the hybrid LSNM/TVB model and the original LSNM. Our framework thus presents a way to embed task-based neural models into the TVB platform, enabling a better comparison between empirical and computational data, which in turn can lead to a better understanding of how interacting neural populations give rise to human cognitive behaviors.

Rethinking Cortical Organization

One way to understand the topography of the cerebral cortex is that “like attracts like.” The cortex is organized to maximize nearest neighbor similarity. This principle can explain the separation of the cortex into discrete areas that emphasize different information domains. It can also explain the maps that form within cortical areas. However, because the cortex is two-dimensional, when a parameter space of much higher dimensionality is reduced onto the cortical sheet while optimizing nearest neighbor relationships, the result may lack an obvious global ordering into separate areas. Instead, the topography may consist of partial gradients, fractures, swirls, regions that resemble separate areas in some ways but not others, and in not a lack of topographic maps but an excess of maps overlaid on each other, no one of which seems to be entirely correct. Like a canvas in a gallery of modern art that no two observers interpret the same way, this lack of obvious ordering of high-dimensional spaces onto the cortex might then result in some scientific controversy over the true organization. In this review, the authors suggest that at least some sectors of the cortex do not have a simple global ordering and are better understood as a result of a reduction of a high-dimensional space onto the cortical sheet. The cortical motor system may be an example of this phenomenon. The authors discuss a model of the lateral motor cortex in which a reduction of many parameters onto a simulated cortical sheet results in a complex topographic pattern that matches the actual monkey motor cortex in surprising detail. Some of the ambiguities of topography and areal boundaries that have plagued the attempt to systematize the lateral motor cortex are explained by the model. NEUROSCIENTIST the attempt to syste 13(2):138—147, 2007.

REVIEW ■ : Multiple Representations of Space in the Brain

Lesions of the posterior parietal cortex have long been known to produce visuospatial deficits in both humans and monkeys. Yet there is no known "map" of space in the parietal cortex. The posterior parietal cortex projects to a number of other areas that are involved in specialized spatial functions. In these areas, space is represented at the level of single neurons and, in many of them, there is a topographically organized map of space. These extraparietal areas include the premotor cortex and the putamen, involved in visuomotor space, the frontal eye fields and the superior colliculus, involved in oculomotor space, the hippocampus, involved in environmental space, and the dorsolateral prefrontal cortex, involved in mnemonic space. In many of these areas, space is represented by means of a coordinate system that is fixed to a particular body part. Thus, the processing of space is not unitary but is divided among several brain areas and several coordinate systems, in addition to those in the posterior parietal cortex. The Neuroscientist 1:43-50, 1995

Eye position effects on the remapped memory trace of visual motion in cortical area MST

After a saccade, most MST neurons respond to moving visual stimuli that had existed in their post-saccadic receptive fields and turned off before the saccade ("trans-saccadic memory remapping"). Neuronal responses in higher visual processing areas are known to be modulated in relation to gaze angle to represent image location in spatiotopic coordinates. In the present study, we investigated the eye position effects after saccades and found that the gaze angle modulated the visual sensitivity of MST neurons after saccades both to the actually existing visual stimuli and to the visual memory traces remapped by the saccades. We suggest that two mechanisms, trans-saccadic memory remapping and gaze modulation, work cooperatively in individual MST neurons to represent a continuous visual world.

Single Canonical Model of Reflexive Memory and Spatial Attention

Many neurons in the dorsal and ventral visual stream have the property that after a brief visual stimulus presentation in their receptive field, the spiking activity in these neurons persists above their baseline levels for several seconds. This maintained activity is not always correlated with the monkey’s task and its origin is unknown. We have previously proposed a simple neural network model, based on shape selective neurons in monkey lateral intraparietal cortex, which predicts the valence and time course of reflexive (bottom-up) spatial attention. In the same simple model, we demonstrate here that passive maintained activity or short-term memory of specific visual events can result without need for an external or top-down modulatory signal. Mutual inhibition and neuronal adaptation play distinct roles in reflexive attention and memory. This modest 4-cell model provides the first simple and unified physiologically plausible mechanism of reflexive spatial attention and passive short-term memory processes.

Prefrontal spatial working memory network predicts animal's decision making in a free choice saccade task

While neurons in the lateral prefrontal cortex (PFC) encode spatial information during the performance of working memory tasks, they are also known to participate in subjective behavior such as spatial attention and action selection. In the present study, we analyzed the activity of primate PFC neurons during the performance of a free choice memory-guided saccade task in which the monkeys needed to choose a saccade direction by themselves. In trials when the receptive field location was subsequently chosen by the animal, PFC neurons with spatially selective visual response started to show greater activation before cue onset. This result suggests that the fluctuation of firing before cue presentation prematurely biased the representation of a certain spatial location and eventually encouraged the subsequent choice of that location. In addition, modulation of the activity by the animal's choice was observed only in neurons with high sustainability of activation and was also dependent on the spatial configuration of the visual cues. These findings were consistent with known characteristics of PFC neurons in information maintenance in spatial working memory function. These results suggest that precue fluctuation of spatial representation was shared and enhanced through the working memory network in the PFC and could finally influence the animal's free choice of saccade direction. The present study revealed that the PFC plays an important role in decision making in a free choice condition and that the dynamics of decision making are constrained by the network architecture embedded in this cortical area.

Movement-related activity during goal-directed hand actions in the monkey ventrolateral prefrontal cortex

Grasping actions require the integration of two neural processes, one enabling the transformation of object properties into corresponding motor acts, and the other involved in planning and controlling action execution on the basis of contextual information. The first process relies on parieto-premotor circuits, whereas the second is considered to be a prefrontal function. Up to now, the prefrontal cortex has been mainly investigated with conditional visuomotor tasks requiring a learned association between cues and behavioural output. To clarify the functional role of the prefrontal cortex in grasping actions, we recorded the activity of ventrolateral prefrontal (VLPF) neurons while monkeys (Macaca mulatta) performed tasks requiring reaching-grasping actions in different contextual conditions (in light and darkness, memory-guided, and in the absence of abstract learned rules). The results showed that the VLPF cortex contains neurons that are active during action execution (movement-related neurons). Some of them showed grip selectivity, and some also responded to object presentation. Most movement-related neurons discharged during action execution both with and without visual feedback, and this discharge typically did not change when the action was performed with object mnemonic information and in the absence of abstract rules. The findings of this study indicate that a population of VLPF neurons play a role in controlling goal-directed grasping actions in several contexts. This control is probably exerted within a wider network, involving parietal and premotor regions, where the role of VLPF movement-related neurons would be that of activating, on the basis of contextual information, the representation of the motor goal of the intended action (taking possession of an object) during action planning and execution.

Early detection and late cognitive control of emotional distraction by the prefrontal cortex

Unpleasant emotional distraction can impair the retention of non-emotional information in working memory (WM). Research links the prefrontal cortex with the successful control of such biologically relevant distractors, although the temporal changes in this brain mechanism remain unexplored. We use magnetoencephalography to investigate the temporal dynamics of the cognitive control of both unpleasant and pleasant distraction, in the millisecond (ms) scale. Behavioral results demonstrate that pleasant events do not affect WM maintenance more than neutral ones. Neuroimaging results show that prefrontal cortices are recruited for the rapid detection of emotional distraction, at early latencies of the processing (70-130 ms). Later in the processing (360-450 ms), the dorsolateral, the medial and the orbital sections of the prefrontal cortex mediate the effective control of emotional distraction. In accordance with the behavioral performance, pleasant distractors do not require higher prefrontal activity than neutral ones. These findings extend our knowledge about the brain mechanisms of coping with emotional distraction in WM. In particular, they show for the first time that overriding the attentional capture triggered by emotional distractors, while maintaining task-relevant elements in mind, is based on the early detection of such linked-to-survival information and on its later cognitive control by the prefrontal cortex.

Functional consequences of age-related morphologic changes to pyramidal neurons of the rhesus monkey prefrontal cortex

Layer 3 (L3) pyramidal neurons in the lateral prefrontal cortex (LPFC) of rhesus monkeys exhibit dendritic regression, spine loss and increased action potential (AP) firing rates during normal aging. The relationship between these structural and functional alterations, if any, is unknown. To address this issue, morphological and electrophysiological properties of L3 LPFC pyramidal neurons from young and aged rhesus monkeys were characterized using in vitro whole-cell patch-clamp recordings and high-resolution digital reconstruction of neurons. Consistent with our previous studies, aged neurons exhibited significantly reduced dendritic arbor length and spine density, as well as increased input resistance and firing rates. Computational models using the digital reconstructions with Hodgkin-Huxley and AMPA channels allowed us to assess relationships between demonstrated age-related changes and to predict physiological changes that have not yet been tested empirically. For example, the models predict that in both backpropagating APs and excitatory postsynaptic currents (EPSCs), attenuation is lower in aged versus young neurons. Importantly, when identical densities of passive parameters and voltage- and calcium-gated conductances were used in young and aged model neurons, neither input resistance nor firing rates differed between the two age groups. Tuning passive parameters for each model predicted significantly higher membrane resistance (R m ) in aged versus young neurons. This R m increase alone did not account for increased firing rates in aged models, but coupling these R m values with subtle differences in morphology and membrane capacitance did. The predicted differences in passive parameters (or parameters with similar effects) are mathematically plausible, but must be tested empirically.

Functions of delay-period activity in the prefrontal cortex and mnemonic scotomas revisited

Working memory (WM) is one of key concepts to understand functions of the prefrontal cortex. Delay-period activity is an important neural correlate to understand the role of WM in prefrontal functions. The importance of delay-period activity is that this activity can encode not only visuospatial information but also a variety of information including non-spatial visual features, auditory and tactile stimuli, task rules, expected reward, and numerical quantity. This activity also participates in a variety of information processing including sensory-to-motor information transformation. These mnemonic features of delay-period activity enable to perform various important operations that the prefrontal cortex participates in, such as executive controls, and therefore, support the notion that WM is an important function to understand prefrontal functions. On the other hand, although experiments using manual versions of the delayed-response task had revealed many important findings, an oculomotor version of this task enabled us to use multiple cue positions, exclude postural orientation during the delay period, and further prove the importance of mnemonic functions of the prefrontal cortex. In addition, monkeys with unilateral lesions exhibited specific impairment only in the performance of memory-guided saccades directed toward visual cues in the visual field contralateral to the lesioned hemisphere. This result indicates that memories for visuospatial coordinates in each hemifield are processed primarily in the contralateral prefrontal cortex. This result further strengthened the idea of mnemonic functions of the prefrontal cortex. Thus, the mnemonic functions of the prefrontal cortex and delay-period activity may not need to be reconsidered, but should be emphasized.

Transcranial magnetic stimulation of the prefrontal cortex in awake nonhuman primates evokes a polysynaptic neck muscle response that reflects oculomotor activity at the time of stimulation

Transcranial magnetic stimulation (TMS) has emerged as an important technique in cognitive neuroscience, permitting causal inferences about the contribution of a given brain area to behavior. Despite widespread use, exactly how TMS influences neural activity throughout an interconnected network, and how such influences ultimately change behavior, remain unclear. The oculomotor system of nonhuman primates (NHPs) offers a potential animal model to bridge this gap. Here, based on results suggesting that neck muscle activity provides a sensitive indicator of oculomotor activation, we show that single pulses of TMS over the frontal eye fields (FEFs) in awake NHPs evoked rapid (within ∼25 ms) and fairly consistent (∼50-75% of all trials) expression of a contralateral head-turning synergy. This neck muscle response resembled that evoked by subsaccadic electrical microstimulation of the FEF. Systematic variation in TMS location revealed that this response could also be evoked from the dorsolateral prefrontal cortex (dlPFC). Combining TMS with an oculomotor task revealed state dependency, with TMS evoking larger neck muscle responses when the stimulated area was actively engaged. Together, these results advance the suitability of the NHP oculomotor system as an animal model for TMS. The polysynaptic neck muscle response evoked by TMS of the prefrontal cortex is a quantifiable trial-by-trial reflection of oculomotor activation, comparable to the monosynaptic motor-evoked potential evoked by TMS of primary motor cortex. Our results also speak to a role for both the FEF and dlPFC in head orienting, presumably via subcortical connections with the superior colliculus.

Differential roles of delay-period neural activity in the monkey dorsolateral prefrontal cortex in visual-haptic crossmodal working memory

Previous studies have shown that neurons of monkey dorsolateral prefrontal cortex (DLPFC) integrate information across modalities and maintain it throughout the delay period of working-memory (WM) tasks. However, the mechanisms of this temporal integration in the DLPFC are still poorly understood. In the present study, to further elucidate the role of the DLPFC in crossmodal WM, we trained monkeys to perform visuo-haptic (VH) crossmodal and haptic-haptic (HH) unimodal WM tasks. The neuronal activity recorded in the DLPFC in the delay period of both tasks indicates that the early-delay differential activity probably is related to the encoding of sample information with different strengths depending on task modality, that the late-delay differential activity reflects the associated (modality-independent) action component of haptic choice in both tasks (that is, the anticipation of the behavioral choice and/or active recall and maintenance of sample information for subsequent action), and that the sustained whole-delay differential activity likely bridges and integrates the sensory and action components. In addition, the VH late-delay differential activity was significantly diminished when the haptic choice was not required. Taken together, the results show that, in addition to the whole-delay differential activity, DLPFC neurons also show early- and late-delay differential activities. These previously unidentified findings indicate that DLPFC is capable of (i) holding the coded sample information (e.g., visual or tactile information) in the early-delay activity, (ii) retrieving the abstract information (orientations) of the sample (whether the sample has been haptic or visual) and holding it in the late-delay activity, and (iii) preparing for behavioral choice acting on that abstract information.

Responses of monkey prefrontal neurons during the execution of transverse patterning

Recent functional imaging studies have suggested that the prefrontal cortex (PF) is engaged in the performance of transverse patterning (TP), which consists of 3 conflicting discriminations (A+/B-, B+/C-, C+/A-). However, the roles of PF in TP are still unclear. To address this issue, we examined the neuronal responses in 3 regions [the principal sulcus (PS), dorsal convexity (DC), and medial prefrontal cortex (MPF)] of the macaque PF during the performance of an oculomotor version of TP. A delayed matching-to-sample (DMS) task was used as a control task. The TP task-responsive neurons were most abundant in MPF. We analyzed the dependency of each neuronal response on the task type (TP or DMS), target shape (A, B, or C), and target location (left or right). Immediately after the choice cue presentation, many MPF neurons showed task dependency. Interestingly, some of them already exhibited differential activity between the 2 tasks before the choice cue presentation. Immediately before the saccade, the number of target location-dependent neurons increased in MPF and PS. Among them, many MPF neurons were also influenced by the task type, whereas PS neurons tended to show location dependency without task dependency. These results suggest that MPF and PS are involved in the execution of TP: MPF appears to be more important in the target selection based on the TP rule, whereas PS is apparently more related to the response preparation. In addition, some neurons showed a postsaccadic response, which may be related to the feedback mechanism.

WORKING MEMORY IMPAIRMENT AS AN ENDOPHENOTYPIC MARKER OF A SCHIZOPHRENIA DIATHESIS

This chapter focuses on the viability of working memory impairment as an endophenotypic marker of a schizophrenia diathesis. It begins with an introduction of the construct of working memory. It follows with a review of the operational criteria for defining an endophenotype. Research findings regarding the working memory performance of schizophrenia and schizophrenia-spectrum patients, first-degree relatives of schizophrenia patients and healthy controls, are reviewed in terms of the criteria for being considered an endophenotypic marker. Special attention is paid to specific components of the working memory deficit (namely, encoding, maintenance, and manipulation), in terms of which aspects are likely to be the best candidates for endophenotypes. We consider the extant literature regarding working memory performance in bipolar disorder and major depression in order to address the issue of relative specificity to schizophrenia. Despite some unresolved issues, it appears that working memory impairment is a very promising candidate for an endophenotypic marker of a schizophrenia diathesis but not for mood disorders. Throughout this chapter, we identify future directions for research in this exciting and dynamic area of research and evaluate the contribution of working memory research to our understanding of schizophrenia.

The steady-state visual evoked potential reveals neural correlates of the items encoded into visual working memory

Visual working memory (VWM) capacity limitations are estimated to be ~4 items. Yet, it remains unclear why certain items from a given memory array may be successfully retrieved from VWM and others are lost. Existing measures of the neural correlates of VWM cannot address this question because they measure the aggregate processing of the entire stimulus array rather than neural signatures of individual items. Moreover, this cumulative processing is usually measured during the delay period, thereby reflecting the allocation of neural resources during VWM maintenance. Here, we use the steady-state visual evoked potential (SSVEP) to identify the neural correlates of individual stimuli at VWM encoding and test two distinct hypotheses: the focused-resource hypothesis and the diffuse-resource hypothesis, for how the allocation of neural resources during VWM encoding may contribute to VWM capacity limitations. First, we found that SSVEP amplitudes were larger for stimuli that were later remembered than for items that were subsequently forgotten. Second, this pattern generalized so that the SSVEP amplitudes were also larger for the unprobed stimuli in correct compared to incorrect trials. These data are consistent with the diffuse-resource view in which attentional resources are broadly allocated across the whole stimulus array. These results illustrate the important role encoding mechanisms play in limiting the capacity of VWM.