Adrián Hernández

Neuronal correlates of parametric working memory in the prefrontal cortex

Humans and monkeys have similar abilities to discriminate the difference in frequency between two mechanical vibrations applied sequentially to the fingertips. A key component of this sensory task is that the second stimulus is compared with the trace left by the first (base) stimulus, which must involve working memory. Where and how is this trace held in the brain? This question was investigated by recording from single neurons in the prefrontal cortex of monkeys while they performed the somatosensory discrimination task. Here we describe neurons in the inferior convexity of the prefrontal cortex whose discharge rates varied, during the delay period between the two stimuli, as a monotonic function of the base stimulus frequency. We describe this as ‘monotonic stimulus encoding’, and we suggest that the result may generalize: monotonic stimulus encoding may be the basic representation of one-dimensional sensory stimulus quantities in working memory. Thus we predict that other behavioural tasks that require ordinal comparisons between scalar analogue stimuli would give rise to monotonic responses similar to those reported here.

Somatosensory discrimination based on cortical microstimulation

The sensation of flutter is produced when mechanical vibrations in the range of 5–50 Hz are applied to the skin. A flutter stimulus activates neurons in the primary somatosensory cortex (S1) that somatotopically map to the site of stimulation,. A subset of these neurons — those with quickly adapting properties, associated with Meissners corpuscles — are strongly entrained by periodic flutter vibrations, firing with a probability that oscillates at the input frequency,. Hence, quickly adapting neurons provide a dynamic representation of such flutter stimuli. However, are these neurons directly involved in the perception of flutter? Here we investigate this in monkeys trained to discriminate the difference in frequency between two flutter stimuli delivered sequentially on the fingertips,. Microelectrodes were inserted into area 3b of S1 and the second stimulus was substituted with a train of injected current pulses. Animals reliably indicated whether the frequency of the second (electrical) signal was higher or lower than that of the first (mechanical) signal, even though both frequencies changed from trial to trial. Almost identical results were obtained with periodic and aperiodic stimuli of equal average frequencies. Thus, the quickly adapting neurons in area 3b activate the circuit leading to the perception of flutter. Furthermore, as far as can be psychophysically quantified during discrimination, the neural code underlying the sensation of fluttercan be finely manipulated, to the extent that the behavioural responses produced by natural and artificial stimuli are indistinguishable.

Neuronal Correlates of a Perceptual Decision in Ventral Premotor Cortex

The ventral premotor cortex (VPC) is involved in the transformation of sensory information into action, although the exact neuronal operation is not known. We addressed this problem by recording from single neurons in VPC while trained monkeys report a decision based on the comparison of two mechanical vibrations applied sequentially to the fingertips. Here we report that the activity of VPC neurons reflects current and remembered sensory inputs, their comparison, and motor commands expressing the result; that is, the entire processing cascade linking the evaluation of sensory stimuli with a motor report. These findings provide a fairly complete panorama of the neural dynamics that underlies the transformation of sensory information into an action and emphasize the role of VPC in perceptual decisions.

Neuronal correlates of decision-making in secondary somatosensory cortex

The ability to discriminate between two sequential stimuli requires evaluation of current sensory information in reference to stored information. Where and how does this evaluation occur? We trained monkeys to compare two mechanical vibrations applied sequentially to the fingertips and to report which of the two had the higher frequency. We recorded single neurons in secondary somatosensory cortex (S2) while the monkeys performed the task. During the first stimulus period, the firing rate of S2 neurons encoded the stimulus frequency. During the second stimulus period, however, some S2 neurons did not merely encode the stimulus frequency. The responses of these neurons were a function of both the remembered (first) and current (second) stimulus. Moreover, a few hundred milliseconds after the presentation of the second stimulus, these responses were correlated with the monkeys decision. This suggests that some S2 neurons may combine past and present sensory information for decision-making.

Temporal Evolution of a Decision-Making Process in Medial Premotor Cortex

The events linking sensory discrimination to motor action remain unclear. It is not known, for example, whether the motor areas of the frontal lobe receive the result of the discrimination process from other areas or whether they actively participate in it. To investigate this, we trained monkeys to discriminate between two mechanical vibrations applied sequentially to the fingertips; here subjects had to recall the first vibration, compare it to the second one, and indicate with a hand/arm movement which of the two vibrations had the higher frequency. We recorded the activity of single neurons in medial premotor cortex (MPC) and found that their responses correlate with the diverse stages of the discrimination process. Thus, activity in MPC reflects the temporal evolution of the decision-making process leading to action selection during this perceptual task.

Sensing without Touching: Psychophysical Performance Based on Cortical Microstimulation

Unequivocal proof that the activity of a localized cortical neuronal population provides sufficient basis for a specific cognitive function has rarely been obtained. We looked for such proof in monkeys trained to discriminate between two mechanical flutter stimuli applied sequentially to the fingertips. Microelectrodes were inserted into clusters of quickly adapting (QA) neurons of the primary somatosensory cortex (S1), and the first or both stimuli were then substituted with trains of current pulses during the discrimination task. Psychophysical performance with artificial stimulus frequencies was almost identical to that measured with the natural stimulus frequencies. Our results indicate that microstimulation can be used to elicit a memorizable and discriminable analog range of percepts, and shows that activation of the QA circuit of S1 is sufficient to initiate all subsequent neural processes associated with flutter discrimination.

Neural codes for perceptual discrimination in primary somatosensory cortex

We sought to determine the neural code(s) for frequency discrimination of vibrotactile stimuli. We tested five possible candidate codes by analyzing the responses of single neurons recorded in primary somatosensory cortex of trained monkeys while they discriminated between two consecutive vibrotactile stimuli. Differences in the frequency of two stimuli could be discriminated using information from (i) time intervals between spikes, (ii) average spiking rate during each stimulus, (iii) absolute number of spikes elicited by each stimulus, (iv) average rate of bursts of spikes or (v) absolute number of spike bursts elicited by each stimulus. However, only a spike count code, in which spikes are integrated over a time window that has most of its mass in the first 250 ms of each stimulus period, covaried with behavior on a trial-by-trial basis, was consistent with psychophysical biases induced by manipulation of stimulus duration, and produced neurometric discrimination thresholds similar to behavioral psychophysical thresholds.

Correlated neuronal discharges that increase coding efficiency during perceptual discrimination.

During a sensory discrimination task, the responses of multiple sensory neurons must be combined to generate a choice. The optimal combination of responses is determined both by their dependence on the sensory stimulus and by their cofluctuations across trials-that is, the noise correlations. Positively correlated noise is considered deleterious, because it limits the coding accuracy of populations of similarly tuned neurons. However, positively correlated fluctuations between differently tuned neurons actually increase coding accuracy, because they allow the common noise to be subtracted without signal loss. This is demonstrated with data recorded from the secondary somatosensory cortex of monkeys performing a vibrotactile discrimination task. The results indicate that positive correlations are not always harmful and may be exploited by cortical networks to enhance the neural representation of features to be discriminated.

Decoding a Perceptual Decision Process across Cortex

Perceptual decisions arise from the activity of neurons distributed across brain circuits. But, decoding the mechanisms behind this cognitive operation across brain circuits has long posed a difficult problem. We recorded the neuronal activity of diverse cortical areas, while monkeys performed a vibrotactile discrimination task. We find that the encoding of the stimuli during the stimulus periods, working memory, and comparison periods is widely distributed across cortical areas. Notably, during the comparison and postponed decision report periods the activity of frontal brain circuits encode both the result of the sensory evaluation that corresponds to the monkeys possible choices and past information on which the decision is based. These results suggest that frontal lobe circuits are more engaged in the readout of sensory information from working memory, when it is required to be compared with other sensory inputs, than simply engaged in motor responses during this task.

Beta oscillations in the monkey sensorimotor network reflect somatosensory decision making

The neuronal correlate of perceptual decision making has been extensively studied in the monkey somatosensory system by using a vibrotactile discrimination task, showing that stimulus encoding, retention, and comparison are widely distributed across cortical areas. However, from a network perspective, it is not known what role oscillations play in this task. We recorded local field potentials (LFPs) from diverse cortical areas of the sensorimotor system while one monkey performed the vibrotactile discrimination task. Exclusively during stimulus presentation, a periodic response reflecting the stimulus frequency was observed in the somatosensory regions, suggesting that after initial processing, the frequency content of the stimulus is coded in some other way than entrainment. Interestingly, we found that oscillatory activity in the beta band reflected the dynamics of decision making in the monkey sensorimotor network. During the comparison and decision period, beta activity showed a categorical response that reflected the decision of the monkey and distinguished correct from incorrect responses. Importantly, this differential activity was absent in a control condition that involved the same stimulation and response but no decision making required, suggesting it does not merely reflect the maintenance of a motor plan. We conclude that beta band oscillations reflect the temporal and spatial dynamics of the accumulation and processing of evidence in the sensorimotor network leading to the decision outcome.