The PFC plays a central role in our ability to learn arbitrary rules, such as “green means go.” Previous experiments from our laboratory have used conditional association learning to show that slow, gradual changes in PFC neural activity mirror monkeys’ slow acquisition of associations. These previous experiments required monkeys to repeatedly reverse the cue–saccade associations, an ability known to be PFC-dependent. We aimed to test whether the relationship between PFC neural activity and behavior was due to the reversal requirement, so monkeys were trained to learn several new conditional cue–saccade associations without reversing them. Learning-related changes in PFC activity now appeared earlier and more suddenly in correspondence with similar changes in behavioral improvement. This suggests that learning of conditional associations is linked to PFC activity regardless of whether reversals are required. However, when previous learning does not need to be suppressed, PFC acquires associations more rapidly.
The prefrontal cortex (PFC) is important for flexible, context-dependent behavioral control. It also plays a critical role in short-term memory maintenance. Though many studies have investigated these functions independently, it is unclear how these two very different processes are realized by a single brain area. To address this we trained two monkeys on two variants of an object sequence memory task. These tasks had the same memory requirements but differed in how information was read out and used. For the “Recognition” task the monkeys had to remember two sequentially presented objects and then release a bar when a matching sequence was recognized. For the “Recall” task, the monkeys had to remember the same sequence of objects but were instead required to recall the sequence and reproduce it with saccadic eye movements when presented with an array of objects. After training we recorded the activity of PFC neurons during task performance. We recorded 222 neurons during the Recognition task, 177 neurons during the Recall task, and 248 neurons during the Switching task (interleaved blocks of Recognition and Recall). Task context had a profound influence on neural selectivity for objects. During the Recall task, the first object was encoded more strongly than the second object, while during the Recognition task the second object was encoded more strongly. In addition, most of the neurons encoded both the task and the objects, evidence for a single population responsible for these two critical prefrontal functions.
prefrontal; monkey; memory; sequence; multi-item; delay activity
Correlated firing among populations of neurons is present throughout the brain and is often rhythmic in nature, observable as an oscillatory fluctuation in the local field potential. Although rhythmic population activity is believed to be critical for normal function in many brain areas, synchronized neural oscillations are associated with disease states in other cases. In the globus pallidus (GP in rodents, homolog of the primate GPe), pairs of neurons generally have uncorrelated firing in normal animals despite an anatomical organization suggesting that they should receive substantial common input. By contrast, correlated and rhythmic GP firing is observed in animal models of Parkinson's disease (PD). Based in part on these findings it has been proposed that an important part of basal ganglia function is active decorrelation, whereby redundant information is compressed. Mechanisms that implement active decorrelation, and changes that cause it to fail in PD, are subjects of great interest. Rat GP neurons express fast, transient voltage-dependent sodium channels (NaF channels) in their dendrites, with the expression level being highest near asymmetric synapses. We recently showed that the dendritic NaF density strongly influences the responsiveness of model GP neurons to synchronous excitatory inputs. In the present study we use rat GP neuron models to show that dendritic NaF channel expression is a potential cellular mechanism of active decorrelation. We further show that model neurons with lower dendritic NaF channel expression have a greater tendency to phase lock with oscillatory synaptic input patterns like those observed in PD.
globus pallidus; basal ganglia; sodium channel; synaptic; dendritic spike; oscillation; synchrony; model; Parkinson's disease
Neural correlates of visual categories have been previously identified in the prefrontal cortex (PFC). However, whether individual neurons can represent multiple categories is unknown. Varying degrees of generalization vs. specialization of neurons in the PFC have been theorized. We recorded from lateral PFC neural activity while monkeys switched between two different and independent categorical distinctions (Cats vs. Dogs, Sports Cars vs. Sedans). We found that many PFC neurons reflected both categorical distinctions. In fact, these multitasking neurons had the strongest category effects. This stands in contrast to our lab’s recent report that monkeys switching between competing categorical distinctions (applied to the same stimulus set) showed independent representations. We suggest that cognitive demands determine whether PFC neurons function as category “multi-taskers”.
Attention regulates the flood of sensory information into a manageable stream, and so understanding how attention is controlled is central to understanding cognition. Competing theories suggest visual search involves serial and/or parallel allocation of attention, but there is little direct, neural, evidence for either mechanism. Two monkeys were trained to covertly search an array for a target stimulus under visual search (endogenous) and pop-out (exogenous) conditions. Here we present neural evidence in the frontal eye fields (FEF) for serial, covert shifts of attention during search but not pop-out. Furthermore, attention shifts reflected in FEF spiking activity were correlated with 18–34 Hz oscillations in the local field potential, suggesting a ‘clocking’ signal. This provides direct neural evidence that primates can spontaneously adopt a serial search strategy and that these serial covert shifts of attention are directed by the FEF. It also suggests that neuron population oscillations may regulate the timing of cognitive processing.
Learning from experience requires knowing whether a past action resulted in a desired outcome. The prefrontal cortex and basal ganglia are thought to play key roles in such learning of arbitrary stimulus-response associations. Previous studies have found neural activity in these areas, similar to dopaminergic neuron signals that transiently reflect whether a response is correct or incorrect. However, it is unclear how this transient activity, which fades in under a second, influences actions that occur much later. Here we report sustained outcome-related responses in single neurons of both areas, which last for several seconds until the next trial. Moreover, the outcome on a single trial influences the neural activity and behavior on the next trial: behavioral responses are more often correct and single neurons more accurately discriminate between the possible responses when the previous trial was correct. These long-lasting signals about trial outcome provide a way to link one action to the next, and may allow reward signals to be combined over time to implement successful learning.
Volitional behavior relies on the brain’s ability to remap sensory flow to motor programs whenever demanded by a changed behavioral context. To investigate the circuit basis of such flexible behavior, we have developed a biophysically-based decision-making network model of spiking neurons for arbitrary sensorimotor mapping. The model quantitatively reproduces behavioral and prefrontal single-cell data from an experiment in which monkeys learn visuo-motor associations that are reversed unpredictably from time to time. We show that when synaptic modifications occur on multiple timescales, the model behavior becomes flexible only when needed: slow components of learning usually dominate the decision process. However, if behavioral contexts change frequently enough, fast components of plasticity take over, and the behavior exhibits a quick forget-and-learn pattern. This model prediction is confirmed by monkey data. Therefore, our work reveals a scenario for conditional associative learning that is distinct from instant switching between sets of well established sensorimotor associations.
Numerous studies of limbs and fingers propose that force-velocity properties of muscle limit maximal voluntary force production during anisometric tasks, i.e. when muscles are shortening or lengthening. Although this proposition appears logical, our study on the simultaneous production of fingertip motion and force disagrees with this commonly held notion. We asked eight consenting adults to use their dominant index fingertip to maximize voluntary downward force against a horizontal surface at specific postures (static trials), and also during an anisometric “scratching” task of rhythmically moving the fingertip along a 5.8±0.5 cm target line. The metronome-timed flexion-extension movement speed varied 36-fold from “slow” (1.0±0.5 cm/s) to “fast” (35.9±7.8 cm/s). As expected, maximal downward voluntary force diminished (44.8±15.6%; p=0.001) when any motion (slow or fast) was added to the task. Surprisingly, however, a 36-fold increase in speed did not affect this reduction in force magnitude. These remarkable results for such an ordinary task challenge the dominant role often attributed to force-velocity properties of muscle and provide insight into neuromechanical interactions. We propose an explanation that the simultaneous enforcement of mechanical constraints for motion and force reduces the set of feasible motor commands sufficiently so that force-velocity properties cease to be the force-limiting factor. While additional work is necessary to reveal the governing mechanisms, the dramatic influence that the simultaneous enforcement of motion and force constraints has on force output begins to explain the vulnerability of dexterous function to development, aging and even mild neuromuscular pathology.
Motor control; redundancy; movement; muscle; finger; Force
Our thoughts have a limited bandwidth; we can only fully process a few items in mind simultaneously. To compensate, the brain developed attention, the ability to select information relevant to the current task, while filtering out the rest. Therefore, by understanding the neural mechanisms of attention we hope to understand a core component of cognition. Here, we review our recent investigations of the neural mechanisms underlying the control of visual attention in frontal and parietal cortex. This includes the observation that the neural mechanisms that shift attention were synchronized to 25 Hz oscillatory brain rhythms, with each shift in attention falling within a single cycle of the oscillation. We generalize these findings to present a hypothesis that cognition relies on neural mechanisms that operate in discrete, periodic computations, as reflected in ongoing oscillations. We discuss the advantages of the model, experimental support, and make several testable hypotheses.
attention; cognition; synchrony; oscillations
Complex goal-directed behaviors extend over time and thus depend on the ability to serially order memories and assemble compound, temporally coordinated movements. Theories of sequential processing range from simple associative chaining to hierarchical models in which order is encoded explicitly and separately from sequence components. To examine how short-term memory and planning for sequences might be coded, we used microstimulation to perturb neural activity in the supplementary eye field (SEF) while animals held a sequence of two cued locations in memory over a short delay. We found that stimulation affected the order in which animals saccaded to the locations, but not the memory for which locations were cued. These results imply that memory for sequential order can be dissociated from that of its components. Furthermore, stimulation of the SEF appeared to bias sequence endpoints to converge toward a location in contralateral space, suggesting that this area encodes sequences in terms of their endpoints rather than their individual components.
Errors induced by microstimulation of the supplementary eye fields while monkeys performed a remembered series of saccadic eye movements give insight into the nature of sequence coding in this cortical area.
The ability to generalize behaviour-guiding principles and concepts from experience is key to intelligent, goal-directed behaviour. It allows us to deal efficiently with a complex world and to adapt readily to novel situations. We review evidence that the prefrontal cortex-the cortical area that reaches its greatest elaboration in primates-plays a central part in acquiring and representing this information. The prefrontal cortex receives highly processed information from all major forebrain systems, and neurophysiological studies suggest that it synthesizes this into representations of learned task contingencies, concepts and task rules. In short, the prefrontal cortex seems to underlie our internal representations of the 'rules of the game'. This may provide the necessary foundation for the complex behaviour of primates, in whom this structure is most elaborate.
Neuronal oscillations in the gamma frequency range have been reported in many cortical areas, but the role they play in cortical processing remains unclear. We tested a recently proposed hypothesis that the intensity of sensory input is coded in the timing of action potentials relative to the phase of gamma oscillations, thus converting amplitude information to a temporal code. We recorded spikes and local field potential (LFP) from secondary somatosensory (SII) cortex in awake monkeys while presenting a vibratory stimulus at different amplitudes. We developed a novel technique based on matching pursuit to study the interaction between the highly transient gamma oscillations and spikes with high time-frequency resolution. We found that spikes were weakly coupled to LFP oscillations in the gamma frequency range (40−80 Hz), and strongly coupled to oscillations in higher gamma frequencies. However, the phase relationship of neither low-gamma nor high-gamma oscillations changed with stimulus intensity, even with a ten-fold increase. We conclude that, in SII, gamma oscillations are synchronized with spikes, but their phase does not vary with stimulus intensity. Furthermore, high-gamma oscillations (>60 Hz) appear to be closely linked to the occurrence of action potentials, suggesting that LFP high-gamma power could be a sensitive index of the population firing rate near the microelectrode.
Secondary somatosensory cortex; gamma; high-gamma; phase coding; local field potential; matching pursuit