Common rules guide comparisons of speed and direction of motion in the dorsolateral prefrontal cortex

Effects of different exercise intensities of race-walking on brain functional connectivity as assessed by functional near-infrared spectroscopy

Introduction

Race-walking is a sport that mimics normal walking and running. Previous studies on sports science mainly focused on the cardiovascular and musculoskeletal systems. However, there is still a lack of research on the central nervous system, especially the real-time changes in brain network characteristics during race-walking exercise. This study aimed to use a network perspective to investigate the effects of different exercise intensities on brain functional connectivity.

Materials and methods

A total of 16 right-handed healthy young athletes were recruited as participants in this study. The cerebral cortex concentration of oxyhemoglobin was measured by functional near-infrared spectroscopy in the bilateral prefrontal cortex (PFC), the motor cortex (MC) and occipital cortex (OC) during resting and race-walking states. Three specific periods as time windows corresponding to different exercise intensities were divided from the race-walking time of participants, including initial, intermediate and sprint stages. The brain activation and functional connectivity (FC) were calculated to describe the 0.01-0.1 Hz frequency-specific cortical activities.

Results

Compared to the resting state, FC changes mainly exist between MC and OC in the initial stage, while PFC was involved in FC changes in the intermediate stage, and FC changes in the sprint stage were widely present in PFC, MC and OC. In addition, from the initial-development to the sprint stage, the significant changes in FC were displayed in PFC and MC.

Conclusion

This brain functional connectivity-based study confirmed that hemodynamic changes at different exercise intensities reflected different brain network-specific characteristics. During race-walking exercise, more extensive brain activation might increase information processing speed. Increased exercise intensity could facilitate the integration of neural signals such as proprioception, motor control and motor planning, which may be an important factor for athletes to maintain sustained motor coordination and activity control at high intensity. This study was beneficial to understanding the neural mechanisms of brain networks under different exercise intensities.

Effects of robot-assisted task-oriented upper limb motor training on neuroplasticity in stroke patients with different degrees of motor dysfunction: A neuroimaging motor evaluation index

Introduction

Although robot-assisted task-oriented upper limb (UL) motor training had been shown to be effective for UL functional rehabilitation after stroke, it did not improve UL motor function more than conventional therapy. Due to the lack of evaluation of neurological indicators, it was difficult to confirm the robot treatment parameters and clinical efficacy in a timely manner. This study aimed to explore the changes in neuroplasticity induced by robot-assisted task-oriented UL motor training in different degrees of dysfunction patients and extract neurological evaluation indicators to provide the robot with additional parameter information.

Materials and methods

A total of 33 adult patients with hemiplegic motor impairment after stroke were recruited as participants in this study, and a manual muscle test divided patients into muscle strength 0–1 level (severe group, n = 10), 2–3 level (moderate group, n = 14), and 4 or above level (mild group, n = 9). Tissue concentration of oxyhemoglobin and deoxyhemoglobin oscillations in the bilateral prefrontal cortex, dorsolateral prefrontal cortex (DLPFC), superior frontal cortex (SFC), premotor cortex, primary motor cortex (M1), primary somatosensory cortex (S1), and occipital cortex were measured by functional near-infrared spectroscopy (fNIRS) in resting and motor training state. The phase information of a 0.01 −0.08 Hz signal was identified by the wavelet transform method. The wavelet amplitude, lateralization index, and wavelet phase coherence (WPCO) were calculated to describe the frequency-specific cortical changes.

Results

Compared with the resting state, significant increased cortical activation was observed in ipsilesional SFC in the mild group and bilateral SFC in the moderate group during UL motor training. Patients in the mild group demonstrated significantly decreased lateralization of activation in motor training than resting state. Moreover, the WPCO value of motor training between contralesional DLPFC and ipsilesional SFC, bilateral SFC, contralesional, S1, and ipsilesional M1 showed a significant decrease compared with the resting state in the mild group.

Conclusion

Robot-assisted task-oriented UL motor training could modify the neuroplasticity of SFC and contribute to control movements and continuous learning motor regularity for patients. fNIRS could provide a variety of real-time sensitive neural evaluation indicators for the robot, which was beneficial to formulating more reasonable and effective personalized prescriptions during motor training.

The cortical connectome of primate lateral prefrontal cortex

The lateral prefrontal cortex (LPFC) of primates plays an important role in executive control, but how it interacts with the rest of the cortex remains unclear. To address this, we densely mapped the cortical connectome of LPFC, using electrical microstimulation combined with functional MRI (EM-fMRI). We found isomorphic mappings between LPFC and five major processing domains composing most of the cerebral cortex except early sensory and motor areas. An LPFC grid of ∼200 stimulation sites topographically mapped to separate grids of activation sites in the five domains, coarsely resembling how the visual cortex maps the retina. The temporal and parietal maps largely overlapped in LPFC, suggesting topographically organized convergence of the ventral and dorsal streams, and the other maps overlapped at least partially. Thus, the LPFC contains overlapping, millimeter-scale maps that mirror the organization of major cortical processing domains, supporting LPFC's role in coordinating activity within and across these domains.

A Stable Population Code for Attention in Prefrontal Cortex Leads a Dynamic Attention Code in Visual Cortex

Attention often requires maintaining a stable mental state over time while simultaneously improving perceptual sensitivity. These requirements place conflicting demands on neural populations, as sensitivity implies a robust response to perturbation by incoming stimuli, which is antithetical to stability. Functional specialization of cortical areas provides one potential mechanism to resolve this conflict. We reasoned that attention signals in executive control areas might be highly stable over time, reflecting maintenance of the cognitive state, thereby freeing up sensory areas to be more sensitive to sensory input (i.e., unstable), which would be reflected by more dynamic attention signals in those areas. To test these predictions, we simultaneously recorded neural populations in prefrontal cortex (PFC) and visual cortical area V4 in rhesus macaque monkeys performing an endogenous spatial selective attention task. Using a decoding approach, we found that the neural code for attention states in PFC was substantially more stable over time compared with the attention code in V4 on a moment-by-moment basis, in line with our guiding thesis. Moreover, attention signals in PFC predicted the future attention state of V4 better than vice versa, consistent with a top-down role for PFC in attention. These results suggest a functional specialization of attention mechanisms across cortical areas with a division of labor. PFC signals the cognitive state and maintains this state stably over time, whereas V4 responds to sensory input in a manner dynamically modulated by that cognitive state.SIGNIFICANCE STATEMENT Attention requires maintaining a stable mental state while simultaneously improving perceptual sensitivity. We hypothesized that these two demands (stability and sensitivity) are distributed between prefrontal and visual cortical areas, respectively. Specifically, we predicted attention signals in visual cortex would be less stable than in prefrontal cortex, and furthermore prefrontal cortical signals would predict attention signals in visual cortex in line with the hypothesized role of prefrontal cortex in top-down executive control. Our results are consistent with suggestions deriving from previous work using separate recordings in the two brain areas in different animals performing different tasks and represent the first direct evidence in support of this hypothesis with simultaneous multiarea recordings within individual animals.

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.

Distributed functions of prefrontal and parietal cortices during sequential categorical decisions

Comparing sequential stimuli is crucial for guiding complex behaviors. To understand mechanisms underlying sequential decisions, we compared neuronal responses in the prefrontal cortex (PFC), the lateral intraparietal (LIP), and medial intraparietal (MIP) areas in monkeys trained to decide whether sequentially presented stimuli were from matching (M) or nonmatching (NM) categories. We found that PFC leads M/NM decisions, whereas LIP and MIP appear more involved in stimulus evaluation and motor planning, respectively. Compared to LIP, PFC showed greater nonlinear integration of currently visible and remembered stimuli, which correlated with the monkeys' M/NM decisions. Furthermore, multi-module recurrent networks trained on the same task exhibited key features of PFC and LIP encoding, including nonlinear integration in the PFC-like module, which was causally involved in the networks' decisions. Network analysis found that nonlinear units have stronger and more widespread connections with input, output, and within-area units, indicating putative circuit-level mechanisms for sequential decisions.

Brain Function Changes Induced by Intermittent Sequential Pneumatic Compression in Patients With Stroke as Assessed by Functional Near-Infrared Spectroscopy

OBJECTIVE

Intermittent sequential pneumatic compression (ISPC) can effectively promote cerebral perfusion and collateral blood supply in patients with stroke. However, the effects of ISPC on cerebral oscillations are still unclear.

METHODS

The tissue concentration of oxyhemoglobin and deoxyhemoglobin oscillations were measured by functional near-infrared spectroscopy under resting and ISPC conditions in 27 right-handed adult patients with stroke. Five characteristic frequency signals (I, 0.6-2 Hz; II, 0.145-0.6 Hz; III, 0.052-0.145 Hz; IV, 0.021-0.052 Hz; and V, 0.0095-0.021 Hz) were identified using the wavelet method. The wavelet amplitude (WA) and laterality index (LI) were calculated to describe the frequency-specific cortical activities.

RESULTS

The ISPC state of patients with ischemic stroke showed significantly increased WA values of the ipsilesional motor cortex (MC) in the frequency intervals III (F37 = 8.017), IV (F37 = 6.347), and V (F37 = 5.538). There was no significant difference in the WA values in the ISPC state compared with the resting state in patients with hemorrhagic stroke. Also, the LI values of the prefrontal cortex and MC in patients decreased more obviously in the ISPC state than in the resting state despite no significant difference.

CONCLUSION

The significantly increased WA values in the frequency intervals III, IV, and V in the MC of patients with ischemic stroke might be related to cortical activity in the MC in addition to increased cerebral perfusion. The decreased LI values in the prefrontal cortex and MC indicated that the ISPC may have had a positive effect on the functional rehabilitation of these regions.

IMPACT

This study provides a method for assessing the effects of ISPC on cerebral oscillations, and the results benefit the optimization of ISPC parameters in personalized treatment for the functional recovery of patients with stroke.

Prefrontal Lesions Disrupt Posterior Alpha-Gamma Coordination of Visual Working Memory Representations

How does the human brain prioritize different visual representations in working memory (WM)? Here, we define the oscillatory mechanisms supporting selection of "where" and "when" features from visual WM storage and investigate the role of pFC in feature selection. Fourteen individuals with lateral pFC damage and 20 healthy controls performed a visuospatial WM task while EEG was recorded. On each trial, two shapes were presented sequentially in a top/bottom spatial orientation. A retro-cue presented mid-delay prompted which of the two shapes had been in either the top/bottom spatial position or first/second temporal position. We found that cross-frequency coupling between parieto-occipital alpha (α; 8-12 Hz) oscillations and topographically distributed gamma (γ; 30-50 Hz) activity tracked selection of the distinct cued feature in controls. This signature of feature selection was disrupted in patients with pFC lesions, despite intact α-γ coupling independent of feature selection. These findings reveal a pFC-dependent parieto-occipital α-γ mechanism for the rapid selection of visual WM representations.

Linking Neuronal Direction Selectivity to Perceptual Decisions About Visual Motion

Psychophysical and neurophysiological studies of responses to visual motion have converged on a consistent set of general principles that characterize visual processing of motion information. Both types of approaches have shown that the direction and speed of target motion are among the most important encoded stimulus properties, revealing many parallels between psychophysical and physiological responses to motion. Motivated by these parallels, this review focuses largely on more direct links between the key feature of the neuronal response to motion, direction selectivity, and its utilization in memory-guided perceptual decisions. These links were established during neuronal recordings in monkeys performing direction discriminations, but also by examining perceptual effects of widespread elimination of cortical direction selectivity produced by motion deprivation during development. Other approaches, such as microstimulation and lesions, have documented the importance of direction-selective activity in the areas that are active during memory-guided direction comparisons, area MT and the prefrontal cortex, revealing their likely interactions during behavioral tasks.

Anodal tDCS over the dorsolateral prefrontal cortex reduces Stroop errors. A comparison of different tasks and designs

In the present work, we evaluated the possibility to induce changes in the inhibitory control through non-invasive excitatory stimulation of the prefrontal cortex (PFC). To this aim, different montages of the transcranial direct current stimulation (tDCS) were adopted in three separate experiments, wherein different cognitive tasks were performed before and after the stimulation. In the first experiment, participants performed a visual Go/no-go task, and a bilateral anodic or sham stimulation was provided over the scalp area corresponding to the inferior frontal gyrus (IFG). In the second experiment, the IFG was stimulated unilaterally over the right hemisphere, and participants performed a Stroop task combined with a concurrent n-back task, which was aimed at overloading PFC activity. Since no behavioral effects of tDCS were observed in both experiments, we conducted a third experiment with different montage and paradigm. Stimulation was provided bilaterally over the dorsolateral PFC (DLPFC) in the context of a classic Stroop task: results indicated that anodal stimulation favored a reduction of errors. Present findings suggest that the bihemispheric stimulation of the DLPFC might be effective to increase inhibition in healthy subjects, and that this effect might be mediated by the implementation of sustained attention, as predicted by the attentional account of the inhibitory control.

Persistent Spiking Activity Underlies Working Memory

Persistent activity generated in the PFC during the delay period of working memory tasks represents information about stimuli held in memory and determines working memory performance. Alternative models of working memory, depending on the rhythmicity of discharges or exclusively on short-term synaptic plasticity, are inconsistent with the neurophysiological data.Dual Perspectives Companion Paper:Working Memory: Delay Activity, Yes! Persistent Activity? Maybe Not, by Mikael Lundqvist, Pawel Herman, and Earl K. Miller.

Tai Chi Chuan exercise related change in brain function as assessed by functional near-infrared spectroscopy

Early studies have shown that Tai Chi Chuan (TCC) contributes to the rehabilitation of cognitive disorders and increases blood oxygen concentration levels in the parietal and occipital brain areas; however, the mechanism of TCC training on brain function remains poorly understood. This study hypothesize that TCC has altered brain function and aims to explore the effects of TCC on functional connection and effective connection of the prefrontal cortex (PFC), motor cortex (MC), and occipital cortex (OC). The participants were 23 experienced Chen-style TCC practitioners (TCC group), and 32 demographically matched TCC-naive healthy controls (control group). Functional and effective connections were calculated using wavelet-based coherence analysis and dynamic Bayesian inference method, respectively. Results showed that beyond the intensity of activity in a particular cortical region induced by TCC, significant differences in brain activity and dynamic configuration of connectivity were observed between the TCC and control groups during resting and movement states. These findings suggested that TCC training improved the connection of PFC, MC and OC in myogenic activity, sympathetic nervous system, and endothelial cell metabolic activities; enhanced brain functional connections and relayed the ability of TCC to improve cognition and the anti-memory decline potential.

Probing the early phase of rapid instructed rule encoding

Humans can rapidly convert instructions about a rule into functional neural structures used to apply the rule. The early stages of this encoding process are poorly understood. We designed a stimulus-response (SR) task in which participants were first shown a SR rule on a screen for 200 ms, and then had to apply it to a test stimulus T, which either matched the S in the rule (SR trial) or not (catch trial). To investigate the early stages of rule encoding, the delay between the end of rule display and the onset of the test stimulus was manipulated and chosen between values of 50 ms to 1300 ms. Participants conducted three sessions of 288 trials each, separated by a median of 9 h. Random sequences of 20 rules were used. We then analysed the reaction times and the types of errors made by participants in the different conditions. The analysis of practice effects in session 1 suggests that the neural networks that process SR and catch trials are at least partially distinct, and improve separately during the practice of respectively SR and catch trials. The rule-encoding process, however, is common to both tasks and improves with the number of trials, irrespective of the trial type. Rule encoding shows interesting dynamic properties that last for 500 ms after the end of the stimulus presentation. The encoding process increases the response time in a non-stochastic way, simply adding a reaction time cost to all responses. The rule-retrieval system is functional before the encoding has stabilized, as early as 50 ms after the end of SR rule presentation, with low response errors. It is sensitive to masking however, producing errors with brief (100 ms) test stimulus presentations. Once encoding has stabilized, the sensitivity to masking disappears. It is suggested that participants do encode rules as a parametrized function, using the same neural encoding structure for each trial, rather than reconfiguring their brain anew for each new SR rule. This structure would have been implemented from instructions received prior to the experiment, by using a library of neural functions available in the brain. The observed errors are consistent with this view.

Neuronal signatures of a random-dot motion comparison task

The study of perceptual decision making has made significant progress owing to major contributions from two experimental paradigms: the sequential vibrotactile frequency comparison task for the somatosensory domain requiring working memory, and the random-dot motion task in the visual domain requiring evidence accumulation over time. On the one hand, electrophysiological recordings in nonhuman primates and humans have identified changes in firing rates and power modulations of beta band oscillations with the vibrotactile frequencies held in working memory, as well as with the mental operation required for decision making. On the other hand, firing rates and centro-parietal potentials were found to increase to a fixed level at the time of responding during the random-dot motion task, possibly reflecting an underlying evidence accumulation mechanism until a decision threshold is met. Here, to bridge these two paradigms, we presented two visual random-dot motion stimuli in a sequential comparison task while recording EEG from human volunteers. We identified a modulation of prefrontal beta band power that scaled with the level of dot motion coherence of the first stimulus during a short retention interval. Furthermore, beta power in premotor areas was modulated by participants' choices approximately 700 ms before responses were given via button press. At the same time, dot motion patches of the second stimulus evoked a pattern of broadband centro-parietal signal build-up till responses were made, whose peak varied with trial difficulty. Hence, we show that known modulations of beta power during working memory and decision making extend from the vibrotactile to the visual domain and provide support for the notion of evidence accumulation as an unconfined decision-making mechanism generalizing over distinct decision types.

Dopamine and Cognitive Control in Prefrontal Cortex

Cognitive control, the ability to orchestrate behavior in accord with our goals, depends on the prefrontal cortex. These cognitive functions are heavily influenced by the neuromodulator dopamine. We review here recent insights exploring the influence of dopamine on neuronal response properties in prefrontal cortex (PFC) during ongoing behaviors in primates. This review suggests three major computational roles of dopamine in cognitive control: (i) gating sensory input, (ii) maintaining and manipulating working memory contents, and (iii) relaying motor commands. For each of these roles, we propose a neuronal microcircuit based on known mechanisms of action of dopamine in PFC, which are corroborated by computational network models. This conceptual approach accounts for the various roles of dopamine in prefrontal executive functioning.

Lamina-specific cortical dynamics in human visual and sensorimotor cortices

Distinct anatomical and spectral channels are thought to play specialized roles in the communication within cortical networks. While activity in the alpha and beta frequency range (7 - 40 Hz) is thought to predominantly originate from infragranular cortical layers conveying feedback-related information, activity in the gamma range (>40 Hz) dominates in supragranular layers communicating feedforward signals. We leveraged high precision MEG to test this proposal, directly and non-invasively, in human participants performing visually cued actions. We found that visual alpha mapped onto deep cortical laminae, whereas visual gamma predominantly occurred more superficially. This lamina-specificity was echoed in movement-related sensorimotor beta and gamma activity. These lamina-specific pre- and post- movement changes in sensorimotor beta and gamma activity suggest a more complex functional role than the proposed feedback and feedforward communication in sensory cortex. Distinct frequency channels thus operate in a lamina-specific manner across cortex, but may fulfill distinct functional roles in sensory and motor processes.

Gamma and beta bursts during working memory readout suggest roles in its volitional control

Working memory (WM) activity is not as stationary or sustained as previously thought. There are brief bursts of gamma (~50–120 Hz) and beta (~20–35 Hz) oscillations, the former linked to stimulus information in spiking. We examined these dynamics in relation to readout and control mechanisms of WM. Monkeys held sequences of two objects in WM to match to subsequent sequences. Changes in beta and gamma bursting suggested their distinct roles. In anticipation of having to use an object for the match decision, there was an increase in gamma and spiking information about that object and reduced beta bursting. This readout signal was only seen before relevant test objects, and was related to premotor activity. When the objects were no longer needed, beta increased and gamma decreased together with object spiking information. Deviations from these dynamics predicted behavioral errors. Thus, beta could regulate gamma and the information in WM.

Previously, the authors have shown that working memory can be maintained by brief gamma oscillation bursts. Here, the authors use a new task to further demonstrate the dynamics of gamma and beta oscillations in working memory readout, independent of behavioral response.

Early and late components of EEG delay activity correlate differently with scene working memory performance

Sustained and elevated activity during the working memory delay period has long been considered the primary neural correlate for maintaining information over short time intervals. This idea has recently been reinterpreted in light of findings generated from multiple neural recording modalities and levels of analysis. To further investigate the sustained or transient nature of activity, the temporal-spectral evolution (TSE) of delay period activity was examined in humans with high density EEG during performance of a Sternberg working memory paradigm with a relatively long six second delay and with novel scenes as stimuli. Multiple analyses were conducted using different trial window durations and different baseline periods for TSE computation. Sensor level analyses revealed transient rather than sustained activity during delay periods. Specifically, the consistent finding among the analyses was that high amplitude activity encompassing the theta range was found early in the first three seconds of the delay period. These increases in activity early in the delay period correlated positively with subsequent ability to distinguish new from old probe scenes. Source level signal estimation implicated a right parietal region of transient early delay activity that correlated positively with working memory ability. This pattern of results adds to recent evidence that transient rather than sustained delay period activity supports visual working memory performance. The findings are discussed in relation to synchronous and desynchronous intra- and inter-regional neural transmission, and choosing an optimal baseline for expressing temporal-spectral delay activity change.

Prefrontal Neurons Represent Motion Signals from Across the Visual Field But for Memory-Guided Comparisons Depend on Neurons Providing These Signals

Visual decisions often involve comparisons of sequential stimuli that can appear at any location in the visual field. The lateral prefrontal cortex (LPFC) in nonhuman primates, shown to play an important role in such comparisons, receives information about contralateral stimuli directly from sensory neurons in the same hemisphere, and about ipsilateral stimuli indirectly from neurons in the opposite hemisphere. This asymmetry of sensory inputs into the LPFC poses the question of whether and how its neurons incorporate sensory information arriving from the two hemispheres during memory-guided comparisons of visual motion. We found that, although responses of individual LPFC neurons to contralateral stimuli were stronger and emerged 40 ms earlier, they carried remarkably similar signals about motion direction in the two hemifields, with comparable direction selectivity and similar direction preferences. This similarity was also apparent around the time of the comparison between the current and remembered stimulus because both ipsilateral and contralateral responses showed similar signals reflecting the remembered direction. However, despite availability in the LPFC of motion information from across the visual field, these "comparison effects" required for the comparison stimuli to appear at the same retinal location. This strict dependence on spatial overlap of the comparison stimuli suggests participation of neurons with localized receptive fields in the comparison process. These results suggest that while LPFC incorporates many key aspects of the information arriving from sensory neurons residing in opposite hemispheres, it continues relying on the interactions with these neurons at the time of generating signals leading to successful perceptual decisions.

SIGNIFICANCE STATEMENT

Visual decisions often involve comparisons of sequential visual motion that can appear at any location in the visual field. We show that during such comparisons, the lateral prefrontal cortex (LPFC) contains accurate representation of visual motion from across the visual field, supplied by motion processing neurons. However, at the time of comparison, LPFC neurons can only use this information to compute the differences between the stimuli, if stimuli appear at the same retinal location, implicating neurons with localized receptive fields in the comparison process. These findings show that sensory comparisons rely on the interactions between LPFC and sensory neurons that not only supply sensory signals but also actively participate in the comparison of these signals at the time of the decision.

Neuronal population coding of perceived and memorized visual features in the lateral prefrontal cortex

The primate lateral prefrontal cortex (LPFC) encodes visual stimulus features while they are perceived and while they are maintained in working memory. However, it remains unclear whether perceived and memorized features are encoded by the same or different neurons and population activity patterns. Here we record LPFC neuronal activity while monkeys perceive the motion direction of a stimulus that remains visually available, or memorize the direction if the stimulus disappears. We find neurons with a wide variety of combinations of coding strength for perceived and memorized directions: some neurons encode both to similar degrees while others preferentially or exclusively encode either one. Reading out the combined activity of all neurons, a machine-learning algorithm reliably decode the motion direction and determine whether it is perceived or memorized. Our results indicate that a functionally diverse population of LPFC neurons provides a substrate for discriminating between perceptual and mnemonic representations of visual features.

Neurons in the lateral prefrontal cortex are known to encode visual features as well as maintain them in working memory. Here the authors report that LPFC neurons encode both perceived and memorized visual features in diverse combinations and the population activity reliably decodes as well as differentiates between these two representations.

Individual differences in visual motion perception and neurotransmitter concentrations in the human brain

Recent studies have shown that interindividual variability can be a rich source of information regarding the mechanism of human visual perception. In this study, we examined the mechanisms underlying interindividual variability in the perception of visual motion, one of the fundamental components of visual scene analysis, by measuring neurotransmitter concentrations using magnetic resonance spectroscopy. First, by psychophysically examining two types of motion phenomena-motion assimilation and contrast-we found that, following the presentation of the same stimulus, some participants perceived motion assimilation, while others perceived motion contrast. Furthermore, we found that the concentration of the excitatory neurotransmitter glutamate-glutamine (Glx) in the dorsolateral prefrontal cortex (Brodmann area 46) was positively correlated with the participant's tendency to motion assimilation over motion contrast; however, this effect was not observed in the visual areas. The concentration of the inhibitory neurotransmitter γ-aminobutyric acid had only a weak effect compared with that of Glx. We conclude that excitatory process in the suprasensory area is important for an individual's tendency to determine antagonistically perceived visual motion phenomena.This article is part of the themed issue 'Auditory and visual scene analysis'.

Response repetition biases in human perceptual decisions are explained by activity decay in competitive attractor models

Animals and humans have a tendency to repeat recent choices, a phenomenon known as choice hysteresis. The mechanism for this choice bias remains unclear. Using an established, biophysically informed model of a competitive attractor network for decision making, we found that decaying tail activity from the previous trial caused choice hysteresis, especially during difficult trials, and accurately predicted human perceptual choices. In the model, choice variability could be directionally altered through amplification or dampening of post-trial activity decay through simulated depolarizing or hyperpolarizing network stimulation. An analogous intervention using transcranial direct current stimulation (tDCS) over left dorsolateral prefrontal cortex (dlPFC) yielded a close match between model predictions and experimental results: net soma depolarizing currents increased choice hysteresis, while hyperpolarizing currents suppressed it. Residual activity in competitive attractor networks within dlPFC may thus give rise to biases in perceptual choices, which can be directionally controlled through non-invasive brain stimulation.

Determining Monkey Free Choice Long before the Choice Is Made: The Principal Role of Prefrontal Neurons Involved in Both Decision and Motor Processes

When choices are made freely, they might emerge from pre-existing neural activity. However, whether neurons in the prefrontal cortex (PF) show this anticipatory effect and, if so, in which part of the process they are involved is still debated. To answer this question, we studied PF activity in monkeys while they performed a strategy task. In this task when the stimulus changed from the previous trial, the monkeys had to shift their response to one of two spatial goals, excluding the one that had been previously selected. Under this free-choice condition, the prestimulus activity of the same neurons that are involved in decision and motor processes predicted future choices. These neurons developed the same goal preferences during the prestimulus presentation as they did later in the decision phase. In contrast, the same effect was not observed in motor-only neurons and it was present but weaker in decision-only neurons. Overall, our results suggest that the PF neuronal activity predicts upcoming actions mainly through the decision-making network that integrate in time decision and motor task aspects.

Interaction between Spatial and Feature Attention in Posterior Parietal Cortex

Lateral intraparietal (LIP) neurons encode a vast array of sensory and cognitive variables. Recently, we proposed that the flexibility of feature representations in LIP reflect the bottom-up integration of sensory signals, modulated by feature-based attention (FBA), from upstream feature-selective cortical neurons. Moreover, LIP activity is also strongly modulated by the position of space-based attention (SBA). However, the mechanisms by which SBA and FBA interact to facilitate the representation of task-relevant spatial and non-spatial features in LIP remain unclear. We recorded from LIP neurons during performance of a task that required monkeys to detect specific conjunctions of color, motion direction, and stimulus position. Here we show that FBA and SBA potentiate each other's effect in a manner consistent with attention gating the flow of visual information along the cortical visual pathway. Our results suggest that linear bottom-up integrative mechanisms allow LIP neurons to emphasize task-relevant spatial and non-spatial features.

Transitions between Multiband Oscillatory Patterns Characterize Memory-Guided Perceptual Decisions in Prefrontal Circuits

Neuronal activity in the lateral prefrontal cortex (LPFC) reflects the structure and cognitive demands of memory-guided sensory discrimination tasks. However, we still do not know how neuronal activity articulates in network states involved in perceiving, remembering, and comparing sensory information during such tasks. Oscillations in local field potentials (LFPs) provide fingerprints of such network dynamics. Here, we examined LFPs recorded from LPFC of macaques while they compared the directions or the speeds of two moving random-dot patterns, S1 and S2, separated by a delay. LFP activity in the theta, beta, and gamma bands tracked consecutive components of the task. In response to motion stimuli, LFP theta and gamma power increased, and beta power decreased, but showed only weak motion selectivity. In the delay, LFP beta power modulation anticipated the onset of S2 and encoded the task-relevant S1 feature, suggesting network dynamics associated with memory maintenance. After S2 onset the difference between the current stimulus S2 and the remembered S1 was strongly reflected in broadband LFP activity, with an early sensory-related component proportional to stimulus difference and a later choice-related component reflecting the behavioral decision buildup. Our results demonstrate that individual LFP bands reflect both sensory and cognitive processes engaged independently during different stages of the task. This activation pattern suggests that during elementary cognitive tasks, the prefrontal network transitions dynamically between states and that these transitions are characterized by the conjunction of LFP rhythms rather than by single LFP bands.

SIGNIFICANCE STATEMENT

Neurons in the brain communicate through electrical impulses and coordinate this activity in ensembles that pulsate rhythmically, very much like musical instruments in an orchestra. These rhythms change with "brain state," from sleep to waking, but also signal with different oscillation frequencies rapid changes between sensory and cognitive processing. Here, we studied rhythmic electrical activity in the monkey prefrontal cortex, an area implicated in working memory, decision making, and executive control. Monkeys had to identify and remember a visual motion pattern and compare it to a second pattern. We found orderly transitions between rhythmic activity where the same frequency channels were active in all ongoing prefrontal computations. This supports prefrontal circuit dynamics that transitions rapidly between complex rhythmic patterns during structured cognitive tasks.

Testing sensory evidence against mnemonic templates

Most perceptual decisions require comparisons between current input and an internal template. Classic studies propose that templates are encoded in sustained activity of sensory neurons. However, stimulus encoding is itself dynamic, tracing a complex trajectory through activity space. Which part of this trajectory is pre-activated to reflect the template? Here we recorded magneto- and electroencephalography during a visual target-detection task, and used pattern analyses to decode template, stimulus, and decision-variable representation. Our findings ran counter to the dominant model of sustained pre-activation. Instead, template information emerged transiently around stimulus onset and quickly subsided. Cross-generalization between stimulus and template coding, indicating a shared neural representation, occurred only briefly. Our results are compatible with the proposal that template representation relies on a matched filter, transforming input into task-appropriate output. This proposal was consistent with a signed difference response at the perceptual decision stage, which can be explained by a simple neural model.

DOI:http://dx.doi.org/10.7554/eLife.09000.001

Imagine searching for your house keys on a cluttered desk. Your eyes scan different items until they eventually find the keys you are looking for. How the brain represents an internal template of the target of your search (the keys, in this example) has been a much-debated topic in neuroscience for the past 30 years. Previous research has indicated that neurons specialized for detecting the sought-after object when it is in view are also pre-activated when we are seeking it. This would mean that these ‘template’ neurons are active the entire time that we are searching.

Myers et al. recorded brain activity from human volunteers using a non-invasive technique called magnetoencephalography (MEG) as they tried to detect when a particular shape appeared on a computer screen. The patterns of brain activity could be analyzed to identify the template that observers had in mind, and to trace when it became active. This revealed that the template was only activated around the time when a target was likely to appear, after which the activation pattern quickly subsided again.

Myers et al. also found that holding a template in mind largely activated different groups of neurons to those activated when seeing the same shape appear on a computer screen. This is contrary to the idea that the same cells are responsible both for maintaining a template and for perceiving its presence in our surroundings.

The brief activation of the template suggests that templates may come online mainly to filter new sensory evidence to detect targets. This mechanism could be advantageous because it lowers the amount of neural activity (and hence energy) needed for the task. Although this points to a more efficient way in which the brain searches for targets, these findings need to be replicated using other methods and task settings to confirm whether the brain generally uses templates in this way.

DOI:http://dx.doi.org/10.7554/eLife.09000.002

Hierarchical Error Representation: A Computational Model of Anterior Cingulate and Dorsolateral Prefrontal Cortex

Anterior cingulate and dorsolateral prefrontal cortex (ACC and dlPFC, respectively) are core components of the cognitive control network. Activation of these regions is routinely observed in tasks that involve monitoring the external environment and maintaining information in order to generate appropriate responses. Despite the ubiquity of studies reporting coactivation of these two regions, a consensus on how they interact to support cognitive control has yet to emerge. In this letter, we present a new hypothesis and computational model of ACC and dlPFC. The error representation hypothesis states that multidimensional error signals generated by ACC in response to surprising outcomes are used to train representations of expected error in dlPFC, which are then associated with relevant task stimuli. Error representations maintained in dlPFC are in turn used to modulate predictive activity in ACC in order to generate better estimates of the likely outcomes of actions. We formalize the error representation hypothesis in a new computational model based on our previous model of ACC. The hierarchical error representation (HER) model of ACC/dlPFC suggests a mechanism by which hierarchically organized layers within ACC and dlPFC interact in order to solve sophisticated cognitive tasks. In a series of simulations, we demonstrate the ability of the HER model to autonomously learn to perform structured tasks in a manner comparable to human performance, and we show that the HER model outperforms current deep learning networks by an order of magnitude.

Unilateral prefrontal lesions impair memory-guided comparisons of contralateral visual motion

The contribution of the lateral prefrontal cortex (LPFC) to working memory is the topic of active debate. On the one hand, it has been argued that the persistent delay activity in LPFC recorded during some working memory tasks is a reflection of sensory storage, the notion supported by some lesion studies. On the other hand, there is emerging evidence that the LPFC plays a key role in the maintenance of sensory information not by storing relevant visual signals but by allocating visual attention to such stimuli. In this study, we addressed this question by examining the effects of unilateral LPFC lesions during a working memory task requiring monkeys to compare directions of two moving stimuli, separated by a delay. The lesions resulted in impaired thresholds for contralesional stimuli at longer delays, and these deficits were most dramatic when the task required rapid reallocation of spatial attention. In addition, these effects were equally pronounced when the remembered stimuli were at threshold or moved coherently. The contralesional nature of the deficits points to the importance of the interactions between the LPFC and the motion processing neurons residing in extrastriate area MT. Delay-specificity of the deficit supports LPFC involvement in the maintenance stage of the comparison task. However, because this deficit was independent of stimulus features giving rise to the remembered direction and was most pronounced during rapid shifts of attention, its role is more likely to be attending and accessing the preserved motion signals rather than their storage.

Sharp emergence of feature-selective sustained activity along the dorsal visual pathway

Sustained activity encoding visual working memory representations has been observed in several cortical areas of primates. Where along the visual pathways this activity emerges remains unknown. Here we show in macaques that sustained spiking activity encoding memorized visual motion directions is absent in direction-selective neurons in early visual area middle temporal (MT). However, it is robustly present immediately downstream, in multimodal association area medial superior temporal (MST), and in the lateral prefrontal cortex (LPFC). This sharp emergence of sustained activity along the dorsal pathway suggests a functional boundary between early visual areas, encoding sensory inputs, and downstream association areas, additionally encoding mnemonic representations. Moreover, local field potential oscillations in MT encoded the memorized directions and, in the low frequencies, were phase-coherent with LPFC spikes. This suggests that LPFC sustained activity modulates synaptic activity in MT, a putative top-down mechanism by which memory signals influence stimulus processing in early visual cortex.

Feature integration and object representations along the dorsal stream visual hierarchy

The visual system is split into two processing streams: a ventral stream that receives color and form information and a dorsal stream that receives motion information. Each stream processes that information hierarchically, with each stage building upon the previous. In the ventral stream this leads to the formation of object representations that ultimately allow for object recognition regardless of changes in the surrounding environment. In the dorsal stream, this hierarchical processing has classically been thought to lead to the computation of complex motion in three dimensions. However, there is evidence to suggest that there is integration of both dorsal and ventral stream information into motion computation processes, giving rise to intermediate object representations, which facilitate object selection and decision making mechanisms in the dorsal stream. First we review the hierarchical processing of motion along the dorsal stream and the building up of object representations along the ventral stream. Then we discuss recent work on the integration of ventral and dorsal stream features that lead to intermediate object representations in the dorsal stream. Finally we propose a framework describing how and at what stage different features are integrated into dorsal visual stream object representations. Determining the integration of features along the dorsal stream is necessary to understand not only how the dorsal stream builds up an object representation but also which computations are performed on object representations instead of local features.

Dynamics of neural population responses in prefrontal cortex indicate changes of mind on single trials

Decision making is a complex process in which different sources of information are combined into a decision variable (DV) that guides action [1, 2]. Neurophysiological studies have typically sought insight into the dynamics of the decision-making process and its neural mechanisms through statistical analysis of large numbers of trials from sequentially recorded single neurons or small groups of neurons [3-6]. However, detecting and analyzing the DV on individual trials has been challenging [7]. Here we show that by recording simultaneously from hundreds of units in prearcuate gyrus of macaque monkeys performing a direction discrimination task, we can predict the monkey's choices with high accuracy and decode DV dynamically as the decision unfolds on individual trials. This advance enabled us to study changes of mind (CoMs) that occasionally happen before the final commitment to a decision [8-10]. On individual trials, the decoded DV varied significantly over time and occasionally changed its sign, identifying a potential CoM. Interrogating the system by random stopping of the decision-making process during the delay period after stimulus presentation confirmed the validity of identified CoMs. Importantly, the properties of the candidate CoMs also conformed to expectations based on prior theoretical and behavioral studies [8]: they were more likely to go from an incorrect to a correct choice, they were more likely for weak and intermediate stimuli than for strong stimuli, and they were more likely earlier in the trial. We suggest that simultaneous recording of large neural populations provides a good estimate of DV and explains idiosyncratic aspects of the decision-making process that were inaccessible before.

The effect of visual salience on memory-based choices

Deciding whether a stimulus is the "same" or "different" from a previous presented one involves integrating among the incoming sensory information, working memory, and perceptual decision making. Visual selective attention plays a crucial role in selecting the relevant information that informs a subsequent course of action. Previous studies have mainly investigated the role of visual attention during the encoding phase of working memory tasks. In this study, we investigate whether manipulation of bottom-up attention by changing stimulus visual salience impacts on later stages of memory-based decisions. In two experiments, we asked subjects to identify whether a stimulus had either the same or a different feature to that of a memorized sample. We manipulated visual salience of the test stimuli by varying a task-irrelevant feature contrast. Subjects chose a visually salient item more often when they looked for matching features and less often so when they looked for a nonmatch. This pattern of results indicates that salient items are more likely to be identified as a match. We interpret the findings in terms of capacity limitations at a comparison stage where a visually salient item is more likely to exhaust resources leading it to be prematurely parsed as a match.

Linking neural activity to complex decisions

In the 1990s, seminal work from Newsome and colleagues made it possible to study the neuronal mechanisms of simple perceptual decisions. The key strength of this work was the clear and direct link between neuronal activity and choice processes. Since then, a great deal of research has extended these initial discoveries to more complex forms of decision making, with the goal of bringing the same strength of linkage between neural and psychological processes. Here, we discuss the progress of two such research programs, namely our own, that are aimed at understanding memory-guided decisions and reward-guided decisions. These problems differ in the relevant brain areas, in the progress that has been achieved, and in the extent of broader understanding achieved so far. However, they are unified by the use of theoretical insights about how to link neuronal activity to decisions.