Search

We can often anticipate the precise moment when a stimulus will be relevant for our behavioral goals. Voluntary attention, the prioritization of sensory information at relevant time points, enhances visual perception, but the underlying neural mechanisms are unknown. To determine whether and how voluntary temporal attention dynamically modulates visual cortical activity, we continuously tracked visual cortical responses using a flickering noise stimulus and MEG recording while human observers performed a temporal attention task. We found two neural signatures of voluntary temporal attention: First, cortical response reliability gradually ramped up in anticipation of the predictable onset of visual targets, with the slope of the ramp modulated by temporal attention. Second, the impact of a target on the cortical response to the flicker was larger when that target was temporally attended. These data reveal how temporal attention dynamically modulates visual cortical responses to prioritize sensory information at precise moments.

Contrary to traditional professional sports, there are few standardized metrics in professional esports (competitive multiplayer video games) for assessing a player’s skill and ability. To begin to address this, we assessed the performance of professional-level players in Aim Lab™, a first-person shooter training and assessment game, within two separate target-shooting tasks. These tasks differed primarily in the relative incentive for fast and imprecise shots versus slow and precise shots. Each player’s motor acuity was measured by characterizing the speed-accuracy trade-off in shot behavior: shot frequency and shot spatial error (distance from center of a target). We also characterized the fine-grained kinematics of players’ mouse movements. Our findings demonstrate that: 1) movement kinematics depended on task demands; and 2) individual differences in motor acuity were significantly correlated with both kinematics and the number of movements needed to hit a target. We demonstrate the importance of transforming from orientation in the virtual environment to centimeters on the mouse pad, as well as accounting for differences in mouse sensitivity across players, for characterizing human performance in first-person shooter games. This approach to measuring motor acuity has widespread application not only in esports assessment and training, but also in basic (motor psychophysics) and clinical (gamified rehabilitation) research.

The normalization model has been applied to explain neural activity in diverse neural systems including primary visual cortex (V1). The model’s defining characteristic is that the response of each neuron is divided by a factor that includes a weighted sum of activity of a pool of neurons. Despite the success of the normalization model, there are three unresolved issues. 1) Experimental evidence supports the hypothesis that normalization in V1 operates via recurrent amplification, i.e., amplifying weak inputs more than strong inputs. It is unknown how normalization arises from recurrent amplification. 2) Experiments have demonstrated that normalization is weighted such that each weight specifies how one neuron contributes to another’s normalization pool. It is unknown how weighted normalization arises from a recurrent circuit. 3) Neural activity in V1 exhibits complex dynamics, including gamma oscillations, linked to normalization. It is unknown how these dynamics emerge from normalization. Here, a family of recurrent circuit models is reported, each of which comprises coupled neural integrators to implement normalization via recurrent amplification with arbitrary normalization weights, some of which can recapitulate key experimental observations of the dynamics of neural activity in V1.

Adaptation is the process that changes a neuron’s response based on recent inputs. In the traditional model, a neuron’s state of adaptation depends on the recent input to that neuron alone, whereas in a recently introduced model (Hebbian normalization), adaptation depends on the structure of neural correlated firing. In particular, increased response correlations between pairs of neurons leads to increased mutual suppression. We test a psychophysical prediction of this model: adaptation should depend on 2nd-order statistics of input stimuli. That is, if two stimuli excite two distinct sub-populations of neurons, then presenting those stimuli simultaneously during adaptation should strengthen mutual suppression between those subpopulations. We confirm this prediction in two experiments. In the first, pairing two gratings synchronously during adaptation (i.e., a plaid) rather than asynchronously (interleaving the two gratings in time) leads to increased effectiveness of one pattern for masking the other. In the second, pairing the gratings in a center-surround configuration results in reduced apparent contrast for the central grating when paired with the same surround (as compared with a condition in which the central grating appears with a different surround at test than during adaptation). These results are consistent with the prediction that an increase in response covariance leads to greater mutual suppression between neurons. This effect is detectable both at threshold (masking) and well above threshold (apparent contrast).

Damage to the primary visual cortex (V1) causes homonymous visual-field loss long considered intractable. Multiple studies now show that perceptual training can restore visual functions in chronic cortically-induced blindness (CB). A popular hypothesis is that training can harness residual visual functions by recruiting intact extrageniculostriate pathways. Training may also induce plastic changes within spared regions of the damaged V1. Here, we link changes in luminance detection sensitivity with retinotopic fMRI activity before and after visual discrimination training in eleven patients with chronic, stroke-induced CB. We show that spared V1 activity representing perimetrically-blind locations prior to training predicts the amount of training-induced recovery of luminance detection sensitivity. Additionally, training results in an enlargement of population receptive fields in perilesional V1, which increases blind-field coverage and may support further recovery with subsequent training. These findings uncover fundamental changes in perilesional V1 cortex underlying training-induced restoration of conscious luminance detection sensitivity in CB., In humans, stroke damage to V1 causes large visual field defects. Spared V1 activity prior to training predicts the amount of training-induced recovery in luminance detection sensitivity. Moreover, visual training changes population receptive field properties within residual V1 circuits.

Motor learning occurs over long periods of practice during which motor acuity – the ability to execute actions more accurately, precisely, and within a shorter amount of time – improves. Laboratory-based motor learning studies are typically limited to a small number of participants and a time frame of minutes to several hours per participant. Thus, there is a need to assess the generalizability of theories and findings from lab-based motor learning studies on much larger samples across longer time scales. In addition, laboratory-based studies of motor learning use relatively simple motor tasks which participants are unlikely to be intrinsically motivated to learn, limiting the interpretation of their findings in more ecologically valid settings. We studied the acquisition and longitudinal refinement of a complex sensorimotor skill embodied in a first-person shooter video game scenario, with a large sample size (N = 7174 participants, 682,564 repeats of the 60 sec game) over a period of months. Participants voluntarily practiced the gaming scenario for as much as several hours per day up to 100 days. We found improvement in performance accuracy (quantified as hit rate) was modest over time but motor acuity (quantified as hits per second) improved considerably, with 40-60% retention from one day to the next. We observed steady improvements in motor acuity across multiple days of video game practice, unlike most motor learning tasks studied in the lab that hit a performance ceiling rather quickly. Learning rate was a nonlinear function of baseline performance level, amount of daily practice, and to a lesser extent, number of days between practice sessions. In addition, we found that the benefit of additional practice on any given day was non-monotonic; the greatest improvements in motor acuity were evident with about an hour of practice and 90% of the learning benefit was achieved by practicing 30 minutes per day. Taken together, these results provide a proof-of-concept in studying motor skill acquisition outside the confines of the traditional laboratory and provide new insights into how a complex motor skill is acquired in an ecologically valid setting and refined across much longer time scales than typically explored.

Early visual cortex exhibits widespread hemodynamic responses in the absence of visual stimulation, which are entrained to the timing of a task and not predicted by local spiking or local field potential. Such task-related responses (TRRs) covary with reward magnitude and physiological signatures of arousal. It is unknown, however, if TRRs change on a trial-to-trial basis according to behavioral performance and task difficulty. If so, this would suggest that TRRs reflect arousal on a trial-to-trial timescale and covary with critical task and behavioral variables. We measured functional magnetic resonance imaging blood-oxygen-level-dependent (fMRI-BOLD) responses in the early visual cortex of human observers performing an orientation discrimination task consisting of separate easy and hard runs of trials. Stimuli were presented in a small portion of one hemifield, but the fMRI response was measured in the ipsilateral hemisphere, far from the stimulus representation and focus of spatial attention. TRRs scaled in amplitude with task difficulty, behavioral accuracy, reaction time, and lapses across trials. These modulations were not explained by the influence of respiration, cardiac activity, or head movement on the fMRI signal. Similar modulations with task difficulty and behavior were observed in pupil size. These results suggest that TRRs reflect arousal and behavior on the timescale of individual trials.

Early visual cortex exhibits widespread hemodynamic responses in the absence of visual stimulation, which are entrained to the timing of a task and not predicted by local spiking or local field potential (LFP). Such task-related responses (“TRRs”) covary with reward magnitude and physiological signatures of arousal. It is unknown, however, if TRRs change on a trial-to-trial basis according to behavioral performance and task difficulty. If so, this would suggest that TRRs reflect arousal on a trial-to-trial timescale and covary with critical task and behavioral variables. We measured fMRI-BOLD responses in the early visual cortex of human observers performing an orientation discrimination task consisting of separate easy and hard runs of trials. Stimuli were presented in a small portion of one hemifield, but the fMRI response was measured in the ipsilateral hemisphere, far from the stimulus representation and focus of spatial attention. TRRs scaled in amplitude with task difficulty, behavioral accuracy, reaction time, and lapses across trials. These modulations were not explained by the influence of respiration, cardiac activity, or head movement on the fMRI signal. Similar modulations with task difficulty and behavior were observed in pupil size. These results suggest that TRRs reflect arousal and behavior on the timescale of individual trials.

Significance The hippocampus is heavily studied in the context of spatial navigation, and the format of spatial information in the hippocampus is multifaceted and complex. Furthermore, the hippocampus is also thought to contain information about other important aspects of behavior such as running speed, although there is not agreement on the nature and magnitude of their effect. To understand how all of these variables are simultaneously represented and used to guide behavior, a theoretical framework is needed that can be directly applied to the data we record. We present a model that captures well-established spatial-encoding features of hippocampal activity and provides the opportunity to identify and incorporate novel features for our collective understanding., Spiking activity of place cells in the hippocampus encodes the animal’s position as it moves through an environment. Within a cell’s place field, both the firing rate and the phase of spiking in the local theta oscillation contain spatial information. We propose a position–theta-phase (PTP) model that captures the simultaneous expression of the firing-rate code and theta-phase code in place cell spiking. This model parametrically characterizes place fields to compare across cells, time, and conditions; generates realistic place cell simulation data; and conceptualizes a framework for principled hypothesis testing to identify additional features of place cell activity. We use the PTP model to assess the effect of running speed in place cell data recorded from rats running on linear tracks. For the majority of place fields, we do not find evidence for speed modulation of the firing rate. For a small subset of place fields, we find firing rates significantly increase or decrease with speed. We use the PTP model to compare candidate mechanisms of speed modulation in significantly modulated fields and determine that speed acts as a gain control on the magnitude of firing rate. Our model provides a tool that connects rigorous analysis with a computational framework for understanding place cell activity.

PurposeTo compare the effects of purported cognitive enhancing dietary bioactive ingredients on subjective and objective measures of cognitive and motor performance during a first-person shooter video game.MethodsUsing a placebo-controlled crossover design, nine healthy men (23.4±5.7 yr, 178.9±5.8cm, 86.0±17.1kg) completed four 20-minute gaming sessions designed to assess cognitive, motor, and perceptual skills via artificial intelligence-driven battery of tasks (Aim Lab). Participants ingested either a placebo (PL), caffeine (CAFF), or caffeine + methylliberine (Dynamine™) + theacrine (TeaCrine®) (CMT). Before and after each gaming session participants rated various feelings of affect. Data were analyzed using mixed factorial ANOVA, bootstrapping post-hoc tests with 95% confidence intervals, and effect sizes.ResultsCompared to PL, self-assessed performance was significantly increased in CMT vs. PL (p=0.035) and self-assessed jitteriness was increased by CAFF vs. PL (p=0.043). CMT was associated with a greater improvement of participants’ visuo-spatial working memory from baseline vs. PL (p=0.04) and CAFF (p=0.033). CAFF had a greater decrease in reaction time for false alarms (indicating diminished cognitive control) from baseline vs. PL (p=0.002) and CMT (p=0.001) and a greater increase for time on target tracking vs. PL (p=0.008) and CMT (p=0.047). Compared to PL, CMT was associated with a greater decrease in median kill time (indicating improved speed) (p=0.017). Compared to PL, systolic blood pressure was significantly increased by CAFF (p=0.025) and CMT (p=0.020) but remained within normal limits.ConclusionsAcute CMT supplementation improved cognitive and motor abilities in recreational gamers. The addition of theacrine and methylliberine to caffeine may lessen some undesirable effects of isolated caffeine ingestion on cognitive control and jitteriness.

The pupil dilates and re-constricts following task events. It is popular to model this task-evoked pupil response as a linear transformation of event-locked impulses, the amplitudes of which are used as estimates of arousal. We show that this model is incorrect, and we propose an alternative model based on the physiological finding that a common neural input drives saccades and pupil size. The estimates of arousal from our model agreed with key predictions: arousal scaled with task difficulty and behavioral performance but was invariant to trial duration. Moreover, the model offers a unified explanation for a wide range of phenomena: entrainment of pupil size and saccade occurrence to task timing, modulation of pupil response amplitude and noise with task difficulty, reaction-time dependent modulation of pupil response timing and amplitude, a constrictory pupil response time-locked to saccades, and task-dependent distortion of this saccade-locked pupil response.

It is widely believed that the detection rates of unattended objects are low - even if they are moving. Here, we report the results of three high-powered experiments indicating that these detection rates are strongly modulated by the relative speed of the unattended object. Specifically, fast – but not slow – objects are readily detectable, whether they are attended or not. These results are consistent with a sentinel system that focuses on the task at hand unless overridden by the detection of a strong motion signature in the periphery.

Attention alters perception across the visual field. Typically, endogenous (voluntary) and exogenous (involuntary) attention similarly improve performance in many visual tasks, but they have differential effects in some tasks. Extant models of visual attention assume that the effects of these two types of attention are identical and consequently do not explain differences between them. Here, we develop a model of spatial resolution and attention that distinguishes between endogenous and exogenous attention. We focus on texture-based segmentation as a model system because it has revealed a clear dissociation between both attention types. For a texture for which performance peaks at parafoveal locations, endogenous attention improves performance across eccentricity, whereas exogenous attention improves performance where the resolution is low (peripheral locations) but impairs it where the resolution is high (foveal locations) for the scale of the texture. Our model emulates sensory encoding to segment figures from their background and predict behavioral performance. To explain attentional effects, endogenous and exogenous attention require separate operating regimes across visual detail (spatial frequency). Our model reproduces behavioral performance across several experiments and simultaneously resolves three unexplained phenomena: (1) the parafoveal advantage in segmentation, (2) the uniform improvements across eccentricity by endogenous attention and (3) the peripheral improvements and foveal impairments by exogenous attention. Overall, we unveil a computational dissociation between each attention type and provide a generalizable framework for predicting their effects on perception across the visual field.

There is considerable support for the hypothesis that perception of heading in the presence of rotation is mediated by instantaneous optic flow. This hypothesis, however, has never been tested. We introduce a novel method, termed “non-varying phase motion,” for generating a stimulus that conveys a single instantaneous optic flow field, even though the stimulus is presented for an extended period of time. In this experiment, observers viewed stimulus videos and performed a forced choice heading discrimination task. For non-varying phase motion, observers made large errors in heading judgments. This suggests that instantaneous optic flow is insufficient for heading perception in the presence of rotation. These errors were mostly eliminated when the velocity of phase motion was varied over time to convey the evolving sequence of optic flow fields corresponding to a particular heading. This demonstrates that heading perception in the presence of rotation relies on the time-varying evolution of optic flow. We hypothesize that the visual system accurately computes heading, despite rotation, based on optic acceleration, the temporal derivative of optic flow.

Autism spectrum disorder (ASD) is characterized partly by atypical attentional engagement, such as hypersensitivity to environmental stimuli. Attentional engagement is known to be regulated by the locus coeruleus (LC). Moderate baseline LC activity globally dampens neural responsivity and is associated with adaptive deployment and narrowing of attention to task-relevant stimuli. In contrast, increased baseline LC activity enhances neural responsivity across cortex and widening of attention to environmental stimuli regardless of their task relevance. Given attentional atypicalities in ASD, this study is the first to evaluate whether individuals with ASD exhibit a different profile of LC activity compared to typically developing controls under different attentional task demands. Males and females with ASD and age- and gender-matched controls participated in a one-back letter detection test while task-evoked pupillary responses—an established inverse correlate for baseline LC activity—were recorded. Participants completed this task in two conditions, either in the absence or presence of distractor auditory tones. Compared to controls, individuals with ASD evinced atypical pupillary responses in the presence versus absence of distractors. Notably, this atypical pupillary profile was evident despite the fact that both groups exhibited equivalent task performance. Moreover, between-group differences in pupillary responses were observed only in response to task-relevant and not to task-irrelevant stimuli, providing confirmation that the group differences are specifically associated with distinctions in LC activity. These findings suggest that individuals with ASD show atypical modulation of LC activity with changes in attentional demands, offering a possible mechanistic and neurobiological account for attentional atypicalities in ASD.Significance StatementIndividuals with autism spectrum disorder (ASD) exhibit atypical attentional behaviors, such as environmental hypersensitivity and atypical fixedness, but the neural mechanism underlying these behaviors remains elusive. One candidate mechanism is atypical locus coeruleus (LC) activity, as the LC has a critical role in attentional modulation. Elevated LC activity is associated with environmental exploration, while moderate LC activity is associated with focused attention on relevant stimuli. This study shows that, under tightly controlled conditions, task-evoked pupil responses—an LC activity proxy—are lower in individuals with ASD than in controls, but only in the presence of task-irrelevant stimuli. This suggests that individuals with ASD evince atypical modulation of LC activity in accordance with changes in attentional demands, offering a mechanistic account for attentional atypicalities in ASD.

The normalization model has been applied to explain neural activity in diverse neural systems including primary visual cortex (V1). The model’s defining characteristic is that the response of each neuron is divided by a factor that includes a weighted sum of activity of a pool of neurons. In spite of the success of the normalization model, there are 3 unresolved issues. 1) Experimental evidence supports the hypothesis that normalization in V1 operates via recurrent amplification, i.e., amplifying weak inputs more than strong inputs. It is unknown how nor-malization arises from recurrent amplification. 2) Experiments have demonstrated that normalization is weighted such that each weight specifies how one neuron contributes to another’s normalization pool. It is unknown how weighted normalization arises from a recurrent circuit. 3) Neural activity in V1 exhibits complex dynamics, including gamma oscillations, linked to normalization. It is unknown how these dynamics emerge from normalization. Here, a new family of recurrent circuit models is reported, each of which comprises coupled neural integrators to implement normalization via recurrent amplification with arbitrary normalization weights, some of which can reca-pitulate key experimental observations of the dynamics of neural activity in V1.Significance StatementA family of recurrent circuit models is proposed to explain the dynamics of neural activity in primary visual cortex (V1). Each of the models in this family exhibits steady state output responses that are already known to fit a wide range of experimental data from diverse neural systems. These models can recapitulate the complex dynamics of V1 activity, including oscillations (so-called gamma oscillations, ∼30-80 Hz). This theoretical framework may also be used to explain key aspects of working memory and motor control. Consequently, the same circuit architecture is applicable to a variety of neural systems, and V1 can be used as a model system for understanding the neural computations in many brain areas.

Damage to the primary visual cortex (V1) causes profound, homonymous visual-field loss termed cortical blindness (CB). Though long considered intractable, multiple studies now show that perceptual training can recover visual functions in chronic CB. A popular hypothesis is that training recruits intact extrageniculostriate pathways. Alternatively, training may induce plastic changes within spared regions of the damaged V1. Here, we linked changes in luminance detection sensitivity with retinotopic fMRI activity in eleven chronic CB patients, before and after extensive visual discrimination training. Our results show that the strength of spared V1 activity representing perimetrically blind-field locations before training predicts the amount of training-induced recovery of luminance detection sensitivity. Additionally, training caused an enlargement of population receptive fields in perilesional V1 cortex, which increased blind-field coverage. These findings uncover fundamental changes in perilesional V1 cortex underlying training-induced restoration of conscious luminance detection sensitivity in cortically-blind patients.

Working memory is an example of a cognitive and neural process that is not static but evolves dynamically with changing sensory inputs; another example is motor preparation and execution. We introduce a theoretical framework for neural dynamics, based on oscillatory recurrent gated neural integrator circuits (ORGaNICs), and apply it to simulate key phenomena of working memory and motor control. The model circuits simulate neural activity with complex dynamics, including sequential activity and traveling waves of activity, that manipulate (as well as maintain) information during working memory. The same circuits convert spatial patterns of premotor activity to temporal profiles of motor control activity and manipulate (e.g., time warp) the dynamics. Derivative-like recurrent connectivity, in particular, serves to manipulate and update internal models, an essential feature of working memory and motor execution. In addition, these circuits incorporate recurrent normalization, to ensure stability over time and robustness with respect to perturbations of synaptic weights.