Working memory capacity is enhanced by distributed prefrontal activation and invariant temporal dynamics

Ventral frontostriatal circuitry mediates the computation of reinforcement from symbolic gains and losses

Reinforcement learning (RL), particularly in primates, is often driven by symbolic outcomes. However, it is usually studied with primary reinforcers. To examine the neural mechanisms underlying learning from symbolic outcomes, we trained monkeys on a task in which they learned to choose options that led to gains of tokens and avoid choosing options that led to losses of tokens. We then recorded simultaneously from the orbitofrontal cortex (OFC), ventral striatum (VS), amygdala (AMY), and mediodorsal thalamus (MDt). We found that the OFC played a dominant role in coding token outcomes and token prediction errors. The other areas contributed complementary functions, with the VS coding appetitive outcomes and the AMY coding the salience of outcomes. The MDt coded actions and relayed information about tokens between the OFC and VS. Thus, the OFC leads the processing of symbolic RL in the ventral frontostriatal circuitry.

Timescales of learning in prefrontal cortex

The lateral prefrontal cortex (PFC) in humans and other primates is critical for immediate, goal-directed behaviour and working memory, which are classically considered distinct from the cognitive and neural circuits that support long-term learning and memory. Over the past few years, a reconsideration of this textbook perspective has emerged, in that different timescales of memory-guided behaviour are in constant interaction during the pursuit of immediate goals. Here, we will first detail how neural activity related to the shortest timescales of goal-directed behaviour (which requires maintenance of current states and goals in working memory) is sculpted by long-term knowledge and learning - that is, how the past informs present behaviour. Then, we will outline how learning across different timescales (from seconds to years) drives plasticity in the primate lateral PFC, from single neuron firing rates to mesoscale neuroimaging activity patterns. Finally, we will review how, over days and months of learning, dense local and long-range connectivity patterns in PFC facilitate longer-lasting changes in population activity by changing synaptic weights and recruiting additional neural resources to inform future behaviour. Our Review sheds light on how the machinery of plasticity in PFC circuits facilitates the integration of learned experiences across time to best guide adaptive behaviour.

Common Mechanisms of Learning in Motor and Cognitive Systems

Rapid progress in our understanding of the brain's learning mechanisms has been accomplished over the past decade, particularly with conceptual advances, including representing behavior as a dynamical system, large-scale neural population recordings, and new methods of analysis of neuronal populations. However, motor and cognitive systems have been traditionally studied with different methods and paradigms. Recently, some common principles, evident in both behavior and neural activity, that underlie these different types of learning have become to emerge. Here we review results from motor and cognitive learning, relying on different techniques and studying different systems to understand the mechanisms of learning. Movement is intertwined with cognitive operations, and its dynamics reflect cognitive variables. Training, in either motor or cognitive tasks, involves recruitment of previously unresponsive neurons and reorganization of neural activity in a low dimensional manifold. Mapping of new variables in neural activity can be very rapid, instantiating flexible learning of new tasks. Communication between areas is just as critical a part of learning as are patterns of activity within an area emerging with learning. Common principles across systems provide a map for future research.

Working memory performance is tied to stimulus complexity

Working memory is the cognitive capability to maintain and process information over short periods. Behavioral and computational studies have shown that visual information is associated with working memory performance. However, the underlying neural correlates remain unknown. To identify how visual information affects working memory performance, we conducted behavioral experiments in pigeons (Columba livia) and single unit recordings in the avian prefrontal analog, the nidopallium caudolaterale (NCL). Complex pictures featuring luminance, spatial and color information, were associated with higher working memory performance compared to uniform gray pictures in conjunction with distinct neural coding patterns. For complex pictures, we found a multiplexed neuronal code displaying visual and value-related features that switched to a representation of the upcoming choice during a delay period. When processing gray stimuli, NCL neurons did not multiplex and exclusively represented the choice already during stimulus presentation and throughout the delay period. The prolonged representation possibly resulted in a decay of the memory trace ultimately leading to a decrease in performance. In conclusion, we found that high stimulus complexity is associated with neuronal multiplexing of the working memory representation possibly allowing a facilitated read-out of the neural code resulting in enhancement of working memory performance.

Alterations of neural activity in the prefrontal cortex associated with deficits in working memory performance

Working memory (WM), a core cognitive function, enables the temporary holding and manipulation of information in mind to support ongoing behavior. Neurophysiological recordings conducted in nonhuman primates have revealed neural correlates of this process in a network of higher-order cortical regions, particularly the prefrontal cortex (PFC). Here, we review the circuit mechanisms and functional importance of WM-related activity in these areas. Recent neurophysiological data indicates that the absence of these neural correlates at different stages of WM is accompanied by distinct behavioral deficits, which are characteristic of various disease states/normal aging and which we review here. Finally, we discuss emerging evidence of electrical stimulation ameliorating these WM deficits in both humans and non-human primates. These results are important for a basic understanding of the neural mechanisms supporting WM, as well as for translational efforts to developing therapies capable of enhancing healthy WM ability or restoring WM from dysfunction.

The time squares sequences: a new task for assessing visuospatial working memory

Introduction

Several studies have shown that the working memory is sensitive to temporal variations. We used a new visuospatial working memory task, the "Time Squares Sequences," to investigate whether implicit variations in stimuli presentation time affect task performance.

Methods

A total of 50 healthy participants saw two sequences (S1 and S2) of seven white squares presented in a matrix of gray squares and assessed whether S2 matched S1. There were four conditions depending on the spatial position and the presentation time (i.e., timing) of the white squares in S1 and S2: two with the same (S1 fixed/S2 fixed and S1 variable/S2 variable) and two with different (S1 fixed/S2 variable and S1 variable/S2 fixed) presentation times.

Results

Findings showed impaired performance when S1 had a fixed presentation time and S2 had a variable presentation time.

Conclusion

These findings are attributed to increased cognitive load due to S2 timing difference, pointing to a monitoring process, sensitive to temporal variations.

Neuronal selectivity for stimulus information determines prefrontal LFP gamma power regardless of task execution

Local field potential (LFP) power in the gamma frequency is modulated by cognitive variables during task execution. We sought to examine whether such modulations only emerge when task rules are established. We therefore analyzed neuronal firing and LFPs in different prefrontal subdivisions before and after the same monkeys were trained to perform cognitive tasks. Prior to task rule learning, sites containing neurons selective for stimuli already exhibited increased gamma power during and after the passive viewing of stimuli compared to the baseline period. Unexpectedly, when the same monkeys learned to maintain these stimuli in working memory, the elevation of gamma power above the baseline was diminished, despite an overall increase in firing rate. Learning and executing the task further decoupled LFP power from single neuron firing. Gamma power decreased at the time when subjects needed to make a judgment about whether two stimuli were the same or not, and differential gamma power was observed for matching and nonmatching stimuli. Our results indicate that prefrontal gamma power emerges spontaneously, not necessarily tied to a cognitive task being executed.

Working memory control dynamics follow principles of spatial computing

Working memory (WM) allows us to remember and selectively control a limited set of items. Neural evidence suggests it is achieved by interactions between bursts of beta and gamma oscillations. However, it is not clear how oscillations, reflecting coherent activity of millions of neurons, can selectively control individual WM items. Here we propose the novel concept of spatial computing where beta and gamma interactions cause item-specific activity to flow spatially across the network during a task. This way, control-related information such as item order is stored in the spatial activity independent of the detailed recurrent connectivity supporting the item-specific activity itself. The spatial flow is in turn reflected in low-dimensional activity shared by many neurons. We verify these predictions by analyzing local field potentials and neuronal spiking. We hypothesize that spatial computing can facilitate generalization and zero-shot learning by utilizing spatial component as an additional information encoding dimension.

Unbalance between working memory task-activation and task-deactivation networks in epilepsy: Simultaneous EEG-fMRI study

Working memory (WM) is a cognitive function involving emergent properties of theta oscillations and large-scale network interactions. The synchronization of WM task-related networks in the brain enhanced WM performance. However, how these networks regulate WM processing is not well known, and the alteration of the interaction among these networks may play an important role in patients with cognitive dysfunction. In this study, we used simultaneous EEG-fMRI to examine the features of theta oscillations and the functional interactions among activation/deactivation networks during the n-back WM task in patients with idiopathic generalized epilepsy (IGE). The results showed that there was more enhancement of frontal theta power along with WM load increase in IGE, and the theta power was positively correlated with the accuracy of the WM tasks. Moreover, fMRI activations/deactivations correlated with n-back tasks were estimated, and we found that the IGE group had increased and widespread activations in high-load WM tasks, including the frontoparietal activation network and task-related deactivation areas, such as the default mode network and primary visual and auditory networks. In addition, the network connectivity results demonstrated decreased counteraction between the activation network and deactivation network, and the counteraction was correlated with the higher theta power in IGE. These results indicated the important role of the interactions between activation and deactivation networks during the WM process, and the unbalance among them may indicate the pathophysiological mechanism of cognitive dysfunction in generalized epilepsy.

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.

Plasticity after cognitive training reflected in prefrontal local field potentials

Learning to perform a new cognitive task induces plasticity of the prefrontal cortex generally involving activation of more neurons and increases in firing rate; however, its effects on single neurons are diverse and complex. We sought to understand how training affects global measures of neural activity by recording and analyzing local field potentials (LFPs) in monkeys before and after they learned to perform working memory tasks. LFP power after training was characterized by a reduction in power in 20-40 Hz during the stimulus presentations and delay periods of the task. Both evoked power, synchronized to task events, and induced power exhibited this decrease after training. The effect was consistent across tasks requiring memory of spatial location and stimulus shape. Error trials were characterized by a lack of LFP power ramping around the fixation onset. Our results reveal signatures of cortical plasticity in LFPs associated with learning to perform cognitive tasks.

An intelligent methodology for the use of multi-criteria decision analysis in impact assessment: the case of real-world offshore construction

Impact assessment of large-scale projects involves a plethora of technical, economic, social, and environmental factors that must be assessed along with the expectations of the stakeholders of each project. While impact assessment is required for a development project to receive regulatory approval to proceed, it is also an invaluable tool during the design phase of complex projects, providing for informed decision-making. Molding multiple perspectives of diverse stakeholders into a single collective choice is a key challenge in the process. Multi-Criteria Decision Analysis (MCDA) is the methodology used to rank a finite number of decision options based on a finite set of evaluation criteria. Different MCDA techniques, however, may lead to different decisions when applied to the same problem while different sets of criteria and weights may rank choices differently even when the same method is applied. This is a cause of concern, and even acrimony, amongst the stakeholders, often leading to protracted periods of negotiation and delaying project launching. The objective of this paper is to present an intelligent system to ameliorate the effects of the inherent subjectivity in MCDA techniques and to develop a consensus amongst the stakeholders in a data-driven setting. A case study from the field of offshore construction is used as a running example. This case study, informed by real-world experience in the field, demonstrates succinctly the issues involved and illustrates clearly the proposed intelligent methodology and its merits.

Tactile angle discriminability improvement: Contributions of working memory training and continuous attended sensory input

Perceptual learning is commonly assumed to enhance perception through continuous attended sensory input. However, learning is generalizable to performance in untrained stimuli and tasks. Although previous studies have observed a possible generalization effect across tasks as a result of working memory (WM) training, comparisons of the contributions of WM training and continuous attended sensory input to perceptual learning generalization are still rare. Therefore, we compared which factors contributed most to perceptual generalization and investigated which skills acquired during WM training led to tactile generalization across tasks. Here, a Braille-like dot pattern matching n-back WM task was used as the WM training task, with four workload levels (0, 1, 2, and 3-back levels). A tactile angle discrimination (TAD) task was used as a pre- and posttest to assess improvements in tactile perception. Between tests, four subject groups were randomly assigned to four different workload n-back tasks to consecutively complete three sessions of training. The results showed that tactile n-back WM training could enhance TAD performance, with the 3-back training group having the highest TAD threshold improvement rate. Furthermore, the rate of WM capacity improvement on the 3-back level across training sessions was correlated with the rate of TAD threshold improvement. These findings suggest that continuous attended sensory input and enhanced WM capacity can lead to improvements in TAD ability, and that greater improvements in WM capacity can predict greater improvements in TAD performance.

NEW & NOTEWORTHY Perceptual learning is not always specific to the trained task and stimuli. We demonstrate that both continuous attended sensory input and improved WM capacity can be used to enhance tactile angle discrimination (TAD) ability. Moreover, WM capacity improvement is important in generalizing the training effect to the TAD ability. These findings contribute to understanding the mechanism of perceptual learning generalization across tasks.

Cognitive strategies shift information from single neurons to populations in prefrontal cortex

Neurons in primate lateral prefrontal cortex (LPFC) play a critical role in working memory (WM) and cognitive strategies. Consistent with adaptive coding models, responses of these neurons are not fixed but flexibly adjust on the basis of cognitive demands. However, little is known about how these adjustments affect population codes. Here, we investigated ensemble coding in LPFC while monkeys implemented different strategies in a WM task. Although single neurons were less tuned when monkeys used more stereotyped strategies, task information could still be accurately decoded from neural populations. This was due to changes in population codes that distributed information among a greater number of neurons, each contributing less to the overall population. Moreover, this shift occurred for task-relevant, but not irrelevant, information. These results demonstrate that cognitive strategies that impose structure on information held in mind rearrange population codes in LPFC, such that information becomes more distributed among neurons in an ensemble.

Prefrontal cortical plasticity during learning of cognitive tasks

Training in working memory tasks is associated with lasting changes in prefrontal cortical activity. To assess the neural activity changes induced by training, we recorded single units, multi-unit activity (MUA) and local field potentials (LFP) with chronic electrode arrays implanted in the prefrontal cortex of two monkeys, throughout the period they were trained to perform cognitive tasks. Mastering different task phases was associated with distinct changes in neural activity, which included recruitment of larger numbers of neurons, increases or decreases of their firing rate, changes in the correlation structure between neurons, and redistribution of power across LFP frequency bands. In every training phase, changes induced by the actively learned task were also observed in a control task, which remained the same across the training period. Our results reveal how learning to perform cognitive tasks induces plasticity of prefrontal cortical activity, and how activity changes may generalize between tasks.

Differential coding of goals and actions in ventral and dorsal corticostriatal circuits during goal-directed behavior

Goal-directed behavior requires identifying objects in the environment that can satisfy internal needs and executing actions to obtain those objects. The current study examines ventral and dorsal corticostriatal circuits that support complementary aspects of goal-directed behavior. We analyze activity from the amygdala, ventral striatum, orbitofrontal cortex, and lateral prefrontal cortex (LPFC) while monkeys perform a three-armed bandit task. Information about chosen stimuli and their value is primarily encoded in the amygdala, ventral striatum, and orbitofrontal cortex, while the spatial information is primarily encoded in the LPFC. Before the options are presented, information about the to-be-chosen stimulus is represented in the amygdala, ventral striatum, and orbitofrontal cortex; at the time of choice, the information is passed to the LPFC to direct a saccade. Thus, learned value information specifying behavioral goals is maintained throughout the ventral corticostriatal circuit, and it is routed through the dorsal circuit at the time actions are selected.

Working Memory: From Neural Activity to the Sentient Mind

Working memory (WM) is the ability to maintain and manipulate information in the conscious mind over a timescale of seconds. This ability is thought to be maintained through the persistent discharges of neurons in a network of brain areas centered on the prefrontal cortex, as evidenced by neurophysiological recordings in nonhuman primates, though both the localization and the neural basis of WM has been a matter of debate in recent years. Neural correlates of WM are evident in species other than primates, including rodents and corvids. A specialized network of excitatory and inhibitory neurons, aided by neuromodulatory influences of dopamine, is critical for the maintenance of neuronal activity. Limitations in WM capacity and duration, as well as its enhancement during development, can be attributed to properties of neural activity and circuits. Changes in these factors can be observed through training-induced improvements and in pathological impairments. WM thus provides a prototypical cognitive function whose properties can be tied to the spiking activity of brain neurons. © 2021 American Physiological Society. Compr Physiol 11:1-41, 2021.

Melamine impairs working memory and reduces prefrontal activity associated with inhibition of AMPA receptor GluR2/3 subunit expression

Recent studies have reported that melamine can accumulate in several regions of the brain including the medial prefrontal cortex (mPFC). Although melamine accumulation in the hippocampus has been verified to induce cognitive impairments, whether it can cause mPFC-dependent working memory deficits is still unknown. After chronic treatment with melamine (150 (Mel(150)) or 300 (Mel(300)) mg/kg), rats were tested during both delay nonmatching-to-sample spatial and odor discrimination tasks. Levels of AMPA receptor subunits in the mPFC were detected using western blotting. To further explore the mechanism at the cellular level, prefrontal activity was recorded during the odor discrimination. The working memory of Mel(150) rats was found to be significantly impaired in a 3-minute delay odor discrimination task (control: n = 6, Mel(150): n = 6; P < 0.05). Compared with the control group (n = 6), rats in the 300 mg/kg Mel(300)-treated group (n = 8) displayed working memory deficits in 60-second delay Y-maze task (P < 0.05), 1-minute and 3-minute delay odor discrimination tasks (both P < 0.05). The levels of AMPA receptor mGluR2/3 subunit were significantly decreased in rats of the Mel(150) (n = 7) and Mel(300) (n = 7) groups (both P < 0.05). Exposure to 150 (n = 7) or 300 mg/kg (n = 7) melamine resulted in significant inhibition of the regular-spiking neuron activity during the delay period of the memory test (both P < 0.05). Intraperitoneal (n = 7) and intra-mPFC (n = 6) infusions of GluR2/3 agonists, effectively enhanced the neural correlate (both P < 0.05) while rescuing cognitive deficits in Mel(300)-treated rats (both P < 0.05). Collectively, these findings suggested that melamine could induce prefrontal dysfunction and cause cognitive impairments.

Brain network dynamics during working memory are modulated by dopamine and diminished in schizophrenia

Dynamical brain state transitions are critical for flexible working memory but the network mechanisms are incompletely understood. Here, we show that working memory performance entails brain-wide switching between activity states using a combination of functional magnetic resonance imaging in healthy controls and individuals with schizophrenia, pharmacological fMRI, genetic analyses and network control theory. The stability of states relates to dopamine D1 receptor gene expression while state transitions are influenced by D2 receptor expression and pharmacological modulation. Individuals with schizophrenia show altered network control properties, including a more diverse energy landscape and decreased stability of working memory representations. Our results demonstrate the relevance of dopamine signaling for the steering of whole-brain network dynamics during working memory and link these processes to schizophrenia pathophysiology.

Working memory requires the brain to switch between cognitive states and activity patterns. Here, the authors show that the steering of these neural network dynamics is influenced by dopamine D1- and D2-receptor function and altered in schizophrenia.

Reward-related choices determine information timing and flow across macaque lateral prefrontal cortex

Prefrontal cortex is critical for cognition. Although much is known about the representation of cognitive variables in the prefrontal cortex, much less is known about the spatio-temporal neural dynamics that underlie cognitive operations. In the present study, we examined information timing and flow across the lateral prefrontal cortex (LPFC), while monkeys carried out a two-armed bandit reinforcement learning task in which they had to learn to select rewarding actions or rewarding objects. When we analyzed signals independently within subregions of the LPFC, we found a task-specific, caudo-rostral gradient in the strength and timing of signals related to chosen objects and chosen actions. In addition, when we characterized information flow among subregions, we found that information flow from action to object representations was stronger from the dorsal to ventral LPFC, and information flow from object to action representations was stronger from the ventral to dorsal LPFC. The object to action effects were more pronounced in object blocks, and also reflected learning specifically in these blocks. These results suggest anatomical segregation followed by the rapid integration of information within the LPFC.

Previous studies provided conflicting evidence on the functional organization of the lateral prefrontal cortex. The authors show task-specific information flows along the caudo-rostral and dorso-ventral axes, reflecting the cognitive process of identifying the location or identity of a valuable object.

Predicting Working Memory Capacity Based on Glutamatergic Concentration and its Modulation of Functional Connectivity

Working memory (WM) capacity, the amount of information one can hold online in mind, has a central role in cognition. Previous electrophysiological and imaging studies revealed the pivotal role of persistent activity within parietal and frontal regions as the neural foundations underpinning WM capacity. The best candidate molecules determining persistent activity are the brain's major excitatory and inhibitory neurotransmitters, glutamate and gamma-aminobutyric acid (GABA), respectively. However, our knowledge of these neurophysiological determinants in forming WM capacity is still poor. Using magnetic resonance spectroscopy (MRS), we examined the contribution of glutamate and GABA within the left intraparietal sulcus (IPS) and the left inferior/middle frontal gyrus (FG) in tracking WM capacity. A positive association was found between glutamate within the left IPS and WM capacity. By utilising resting-state functional MRI, we identified a negative association between parieto-cingulate connectivity and WM capacity. Individual variation in parieto-cingulate connectivity was explained by glutamatergic concentration in the IPS. Moreover, we found that parieto-cingulate connectivity mediated the relationship between interparietal sulcus glutamate and WM capacity. This set of findings reveals a novel mechanistic insight by which glutamatergic concentration within the IPS shapes WM capacity via parieto-cingulate connectivity.

Plasticity of Persistent Activity and Its Constraints

Stimulus information is maintained in working memory by action potentials that persist after the stimulus is no longer physically present. The prefrontal cortex is a critical brain area that maintains such persistent activity due to an intrinsic network with unique synaptic connectivity, NMDA receptors, and interneuron types. Persistent activity can be highly plastic depending on task demands but it also appears in naïve subjects, not trained or required to perform a task at all. Here, we review what aspects of persistent activity remain constant and what factors can modify it, focusing primarily on neurophysiological results from non-human primate studies. Changes in persistent activity are constrained by anatomical location, with more ventral and more anterior prefrontal areas exhibiting the greatest capacity for plasticity, as opposed to posterior and dorsal areas, which change relatively little with training. Learning to perform a cognitive task for the first time, further practicing the task, and switching between learned tasks can modify persistent activity. The ability of the prefrontal cortex to generate persistent activity also depends on age, with changes noted between adolescence, adulthood, and old age. Mean firing rates, variability and correlation of persistent discharges, but also time-varying firing rate dynamics are altered by these factors. Plastic changes in the strength of intrinsic network connections can be revealed by the analysis of synchronous spiking between neurons. These results are essential for understanding how the prefrontal cortex mediates working memory and intelligent behavior.

Early Attentional Modulation by Working Memory Training in Young Adult ADHD Patients during a Risky Decision-Making Task

Background: Working memory (WM) deficits and impaired decision making are among the characteristic symptoms of patients affected by attention deficit/hyperactivity disorder (ADHD). The inattention associated with the disorder is likely to be due to functional deficits of the neural networks inhibiting irrelevant sensory input. In the presence of unnecessary information, a good decisional process is impaired and ADHD patients tend to take risky decisions. This study is aimed to test the hypothesis that the level of difficulty of a WM training (WMT) is affecting the top-down modulation of the attentional processes in a probabilistic gambling task. Methods: Event-related potentials (ERP) triggered by the choice of the amount wagered in the gambling task were recorded, before and after WMT with a the dual n-back task, in young ADHD adults and matched controls. For each group of participants, randomly assigned individuals were requested to perform WMT with a fixed baseline level of difficulty. The remaining participants were trained with a performance-dependent adaptive n-level of difficulty. Results: We compared the ERP recordings before and after 20 days of WMT in each subgroup. The analysis was focused on the time windows with at least three recording sites showing differences before and after training, after Bonferroni correction ( p < 0.05 ). In ADHD, the P1 wave component was selectively affected at frontal sites and its shape was recovered close to controls' only after adaptive training. In controls, the strongest contrast was observed at parietal level with a left hemispheric dominance at latencies near 900 ms, more after baseline than after adaptive training. Conclusion: Partial restoration of early selective attentional processes in ADHD patients might occur after WMT with a high cognitive load. Modified frontal sites' activities might constitute a neural marker of this effect in a gambling task. In controls, conversely, an increase in late parietal negativity might rather be a marker of an increase in transfer effects to fluid intelligence.