This study aimed to identify neural mechanisms that underlie perceptual learning in a visual-discrimination task. We trained two monkeys (Macaca mulatta) to determine the direction of visual motion while we recorded from their middle temporal area (MT), which in trained monkeys represents motion information that is used to solve the task, and lateral intraparietal area (LIP), which represents the transformation of motion information into a saccadic choice. During training, improved behavioral sensitivity to weak motion signals was accompanied by changes in motion-driven responses of neurons in LIP, but not in MT. The time course and magnitude of the changes in LIP correlated with the changes in behavioral sensitivity throughout training. Thus, for this task, perceptual learning does not appear to involve improvements in how sensory information is represented in the brain, but rather how the sensory representation is interpreted to form the decision that guides behavior.

We recently showed that improved perceptual performance on a visual motion direction-discrimination task corresponds to changes not in how sensory information is represented in the brain but rather how that information is interpreted to form a decision that guides behaviour. Here we show that these changes can be accounted for using a reinforcement learning rule to shape functional connectivity between the sensory and decision neurons. We modelled performance based on the readout of simulated responses of direction-selective sensory neurons in the middle temporal area (MT) of monkey cortex. A reward prediction error guided changes in connections between these sensory neurons and the decision process, first establishing the association between motion direction and response direction and then gradually improving perceptual sensitivity by selectively strengthening the connections from the most sensitive neurons in the sensory population. The results suggest a common, feedback-driven mechanism for some forms of associative and perceptual learning.

Gold JI, Law C-T, Connolly P, Bennur S. The relative influences of priors and sensory evidence on an oculomotor decision variable during perceptual learning. J Neurophysiol 100: 2653-2668. First published August 27, 2008 doi:10.1152/jn.90629.2008. Choice behavior on simple sensory-motor tasks can exhibit trial-to-trial dependencies. For perceptual tasks, these dependencies reflect the influence of prior trials on choices that are also guided by sensory evidence, which is often independent across trials. Here we show that the relative influences of prior trials and sensory evidence on choice behavior can be shaped by training, such that prior influences are strongest when perceptual sensitivity to the relevant sensory evidence is weakest and then decline steadily as sensitivity improves. We trained monkeys to decide the direction of random-dot motion and indicate their decision with an eye movement. We characterized sequential dependencies by relating current choices to weighted averages of prior choices. We then modeled behavior as a drift-diffusion process, in which the weighted average of prior choices provided an additive offset to a decision variable that integrated incoming motion evidence to govern choice. The average magnitude of offset within individual training sessions declined steadily as the quality of the integrated motion evidence increased over many months of training. The trial-by-trial magnitude of offset was correlated with signals related to developing commands that generate the oculomotor response but not with neural activity in either the middle temporal area, which represents information about the motion stimulus, or the lateral intraparietal area, which represents the sensory-motor conversion. The results suggest that training can shape the relative contributions of expectations based on prior trends and incoming sensory evidence to select and prepare visually guided actions. I N T R O D U C T I O NPerformance on trial-based sensory-motor tasks can exhibit numerous forms of sequential dependence. For example, both response times and choice are sensitive to effects of the previous trial, including repeated actions, task switching, and errors (Botvinick et al. 2001;Cho et al. 2002;Laming 1979Laming 1968Luce 1986). For tasks in which reward probability depends on sequential patterns of choices, these dependencies can reflect rational strategies for choosing future outcomes based on prior history Behrens et al. 2007;Corrado et al. 2005;Davidson and McCarthy 1988;Herrnstein 1961;Kennerley et al. 2006;Lau and Glimcher 2005;Sugrue et al. 2004;Williams 1988). In contrast, for perceptual tasks in which the present stimulus is the exclusive factor determining the rewarded choice, these dependencies can only hinder performance. The goal of this study was to better understand how these dependencies evolve as perceptual sensitivity to sensory cues that instruct the rewarded choice improves with training.We trained monkeys on a one-interval, two-alternative direction-discrimination task in which they d...

Recent findings in humans and animals suggest that sleep promotes synaptic plasticity, but the underlying mechanisms have not been identified. We have demonstrated recently an important role for sleep in ocular dominance (OD) plasticity, a classic form of in vivo cortical remodeling triggered by monocular deprivation (MD) during a critical period of development. The mechanisms responsible for the effects of sleep on OD plasticity are unknown but may depend on neuronal activity in the sleeping brain. We investigated the role of cortical activity in sleep-dependent plasticity by reversibly inactivating the sleeping visual cortex (V1) after a period of MD. Critical period cats were bilaterally implanted with cannulas in V1 and standard EEG/EMG electrodes for polysomnographic recording. After a period of MD, visual cortices were infused with the sodium channel blocker lidocaine in vehicle or vehicle only during sleep. A third group of cats served as sham controls and were infused with lidocaine outside of V1 (into the CSF). Both optical imaging of intrinsic cortical signals and microelectrode recordings showed that OD plasticity was significantly reduced in cats whose visual cortices were reversibly silenced during sleep. These findings demonstrate that the mechanisms governing this form of sleep-dependent plasticity require cortical activity. They provide an important insight into how sleep modifies synaptic circuitry by narrowing the range of possible candidate mechanisms to those that are activity dependent.

No abstract

The Bienenstock, Cooper, and Munro (BCM) theory of synaptic plasticity has successfully reproduced the development of orientation selectivity and ocular dominance in kitten visual cortex in normal, as well as deprived, visual environments. To better compare the consequences of this theory with experiment, previous abstractions of the visual environment are replaced in this work by real visual images with retinal processing. The visual environment is represented by 24 gray-scale natural images that are shifted across retinal fields. In this environment, the BCM neuron develops receptive fields similar to the fields of simple cells found in kitten striate cortex. These fields display adjacent excitatory and inhibitory bands when tested with spot stimuli, orientation selectivity when tested with bar stimuli, and spatial-frequency selectivity when tested with sinusoidal gratings. In addition, their development in various deprived visual environments agrees with experimental results.In 1982 Bienenstock, Cooper, and Munro (BCM) proposed a concrete synaptic-modification hypothesis in which two regions of modification (Hebbian and anti-Hebbian) are stabilized by the addition of a sliding modification threshold (1). The theory was created originally to explain the development of orientation selectivity of visual cortical neurons in various visual environments. This theory has since proven capable of also explaining ocular dominance and selective response properties in the most diverse visual environments, one ofthe most thoroughly studied areas in neuroscience. In this paper we examine the consequences ofthe replacement ofprevious abstractions of the visual environment by real visual images with retinal processing.During a critical period of postnatal development, the response properties of neurons in striate cortex of the kitten can be modified by manipulating the visual experience of the animal (2-4). Clothiaux, Bear, and Cooper (CBC) (5) showed that simulations based on the BCM theory, with a fixed set of parameters, reproduce both the kinetics and equilibrium states of experience-dependent modifications that are observed experimentally in these neurons. The rearing conditions that they simulated include normal rearing, monocular deprivation, reverse suture, strabismus, and binocular deprivation.An important simplification used in all previous BCM simulations is the assumed activity of neurons in the lateral geniculate nucleus (LGN) resulting from visual experience. In CBC, for example, an abstract set of 12 patterns represents the activity on geniculo-cortical afferents supposedly resulting from contoured stimuli with 12 different orientations.LGN activity in a normal visual environment is modeled as this patterned input distorted by noise. In the absence of visual contours, LGN-cortical input activity is assumed to be uncorrelated noise distributed around spontaneous activity. Thejustification for this simplification is that the visual fields of neurons in primary visual cortex are small, so that reproducibl...

Perceptual decisions require the brain to weigh noisy evidence from sensory neurons to form categorical judgments that guide behavior. Here we review behavioral and neurophysiological findings suggesting that at least some forms of perceptual learning do not appear to affect the response properties of neurons that represent the sensory evidence. Instead, improved perceptual performance results from changes in how the sensory evidence is selected and weighed to form the decision. We discuss the implications of this idea for possible sites and mechanisms of training-induced improvements in perceptual processing in the brain.

Perceptual learning involves long-lasting improvements in the ability to perceive simple sensory stimuli. Some forms of perceptual learning are thought to involve an increasingly selective readout of sensory neurons that are most sensitive to the trained stimulus. Here we report novel changes in the relationship between the threshold and slope of the psychometric function during learning that are consistent with such changes in readout and can provide insights into the underlying neural mechanisms. In monkeys trained on a direction-discrimination task, perceptual improvements corresponded to lower psychometric thresholds and slightly shallower slopes. However, this relationship between threshold and slope was much weaker in comparable, ideal-observer "neurometric" functions of neurons in the middle temporal (MT) area, which represent sensory information used to perform the task and whose response properties did not change with training. We propose a linear/nonlinear pooling scheme to account for these results. According to this scheme, MT responses are pooled via linear weights that change with training to more selectively read out responses from the most sensitive neurons, thereby reducing predicted thresholds. An additional nonlinear (power-law) transformation does not change with training and causes the predicted psychometric function to become shallower as uninformative neurons are eliminated from the pooled signal. We show that this scheme is consistent with the measured changes in psychometric threshold and slope throughout training. The results suggest that some forms of perceptual learning involve improvements in a process akin to selective attention that pools the most informative neural signals to guide behavior.