Electrophysiology publications

A fundamental property of brain function is that the spiking activity of cortical neurons is variable and that some of this variability is correlated between neurons. Correlated activity not due to the stimulus arises from shared input but the neuronal circuit mechanisms that result in these noise correlations are not fully understood. Here we tested in the visual system if correlated variability in mid-level area V4 of visual cortex is altered following extensive lesions of primary visual cortex (V1). To this end we recorded longitudinally the neuronal correlations in area V4 of two behaving macaque monkeys before and after a V1 lesion while the monkeys fixated a grey screen. We found that the correlations of neuronal activity survived the lesions in both monkeys. In one monkey, the correlation of multi-unit spiking signals was strongly increased in the first week post-lesion, while in the second monkey, correlated activity was slightly increased, but not greater than some week-by-week fluctuations observed. The typical drop-off of inter-neuronal correlations with cortical distance was preserved after the lesion. Therefore, as V4 noise correlations remain without feedforward input from V1, these results suggest instead that local and/or feedback input seem to be necessary for correlated activity.

Bidirectional manipulations – activation and inactivation – are widely used to identify the functions supported by specific cortical interneuron types. Implicit in much of this work is the notion that tonic activation and inactivation will both produce valid, internally consistent insights into interneurons’ computational roles. Here, using single-unit recordings in auditory cortex of awake mice, we show that this may not generally hold true. Optogenetically manipulating somatostatin-positive (Sst+) or parvalbumin-positive (Pvalb+) interneurons while recording tone-responses showed that Sst+ inactivation increased response gain, while Pvalb+ inactivation weakened tuning and decreased information transfer, implying that these neurons support delineable computational functions. But activating Sst+ and Pvalb+ interneurons revealed no such differences. We used a simple network model to understand this asymmetry, and showed how relatively small changes in key parameters, such as spontaneous activity or strength of the light manipulation, determined whether activation and inactivation would produce consistent or paradoxical conclusions regarding interneurons’ computational functions.

Objective. Individual carbon fiber microelectrodes can record unit activity in both acute and semi-chronic (∼1 month) implants. Additionally, new methods have been developed to insert a 16 channel array of carbon fiber microelectrodes. Before assessing the in vivo long-term viability of these arrays, accelerated soak tests were carried out to determine the most stable site coating material. Next, a multi-animal, multi-month, chronic implantation study was carried out with carbon fiber microelectrode arrays and silicon electrodes. Approach. Carbon fibers were first functionalized with one of two different formulations of PEDOT and subjected to accelerated aging in a heated water bath. After determining the best PEDOT formula to use, carbon fiber arrays were chronically implanted in rat motor cortex. Some rodents were also implanted with a single silicon electrode, while others received both. At the end of the study a subset of animals were perfused and the brain tissue sliced. Tissue sections were stained for astrocytes, microglia, and neurons. The local reactive responses were assessed using qualitative and quantitative methods. Main results. Electrophysiology recordings showed the carbon fibers detecting unit activity for at least 3 months with average amplitudes of ∼200 μ V. Histology analysis showed the carbon fiber arrays with a minimal to non-existent glial scarring response with no adverse effects on neuronal density. Silicon electrodes showed large glial scarring that impacted neuronal counts. Significance. This study has validated the use of carbon fiber microelectrode arrays as a chronic neural recording technology. These electrodes have demonstrated the ability to detect single units with high amplitude over 3 months, and show the potential to record for even longer periods. In addition, the minimal reactive response should hold stable indefinitely, as any response by the immune system may reach a steady state after 12 weeks.

Cortical stimulation through electrocorticographic (ECoG) electrodes is a potential method for providing sensory feedback in future prosthetic and rehabilitative applications. Here, we evaluate human subjects' ability to continuously modulate their motor behavior based on feedback from direct surface stimulation of the somatosensory cortex. Subjects wore a dataglove that measured their hand aperture position and received one of three stimuli over the hand sensory cortex based on their current hand position as compared to a target aperture position. Using cortical stimulation feedback, subjects adjusted their hand aperture to move towards the target aperture region. One subject was able to achieve accuracies and R2 values well above chance (best performance: R2 = 0.93; accuracy = 0.76/1). Performance dropped during the catch trial (same stimulus independent of the position) to below chance levels, suggesting that the subject had been using the varied sensory feedback to modulate their motor behavior. To our knowledge, this study represents one of the first demonstrations of using direct cortical surface stimulation of the human sensory cortex to perform a motor task, and is a first step towards developing closed-loop human sensorimotor brain-computer interfaces.

The basal ganglia, a group of subcortical nuclei, play a crucial role in decision-making by selecting actions and evaluating their outcomes. While much is known about the function of the basal ganglia circuitry in selection, how these nuclei contribute to outcome evaluation is less clear. Here we show that neurons in the habenula-projecting globus pallidus (GPh) in mice are essential for evaluating action outcomes and are regulated by a specific set of inputs from the basal ganglia. We find in a classical conditioning task that individual mouse GPh neurons bidirectionally encode whether an outcome is better or worse than expected. Mimicking these evaluation signals with optogenetic inhibition or excitation is sufficient to reinforce or discourage actions in a decision-making task. Moreover, cell-type-specific synaptic manipulations reveal that the inhibitory and excitatory inputs to the GPh are necessary for mice to appropriately evaluate positive and negative feedback, respectively. Finally, using rabies-virus-assisted monosynaptic tracing, we show that the GPh is embedded in a basal ganglia circuit wherein it receives inhibitory input from both striosomal and matrix compartments of the striatum, and excitatory input from the 'limbic' regions of the subthalamic nucleus. Our results provide evidence that information about the selection and evaluation of actions is channelled through distinct sets of basal ganglia circuits, with the GPh representing a key locus in which information of opposing valence is integrated to determine whether action outcomes are better or worse than expected.

In mammals, localization of sound sources in azimuth depends on sensitivity to interaural differences in sound timing (ITD) and level (ILD). Paradoxically, while typical ILD-sensitive neurons of the auditory brainstem require millisecond synchrony of excitatory and inhibitory inputs for the encoding of ILDs, human and animal behavioral ILD sensitivity is robust to temporal stimulus degradations (e.g., interaural decorrelation due to reverberation), or, in humans, bilateral clinical device processing. Here we demonstrate that behavioral ILD sensitivity is only modestly degraded with even complete decorrelation of left- and right-ear signals, suggesting the existence of a highly integrative ILD-coding mechanism. Correspondingly, we find that a majority of auditory midbrain neurons in the central nucleus of the inferior colliculus (of chinchilla) effectively encode ILDs despite complete decorrelation of left- and right-ear signals. We show that such responses can be accounted for by relatively long windows of bilateral excitatory-inhibitory interaction, which we explicitly measure using trains of narrowband clicks. Neural and behavioral data are compared with the outputs of a simple model of ILD processing with a single free parameter, the duration of excitatory-inhibitory interaction. Behavioral, neural, and modeling data collectively suggest that ILD sensitivity depends on binaural integration of excitation and inhibition within a ≳3 ms temporal window, significantly longer than observed in lower brainstem neurons. This relatively slow integration potentiates a unique role for the ILD system in spatial hearing that may be of particular importance when informative ITD cues are unavailable. SIGNIFICANCE STATEMENT In mammalian hearing, interaural differences in the timing (ITD) and level (ILD) of impinging sounds carry critical information about source location. However, natural sounds are often decorrelated between the ears by reverberation and background noise, degrading the fidelity of both ITD and ILD cues. Here we demonstrate that behavioral ILD sensitivity (in humans) and neural ILD sensitivity (in single neurons of the chinchilla auditory midbrain) remain robust under stimulus conditions that render ITD cues undetectable. This result can be explained by “slow” temporal integration arising from several-millisecond-long windows of excitatory-inhibitory interaction evident in midbrain, but not brainstem, neurons. Such integrative coding can account for the preservation of ILD sensitivity despite even extreme temporal degradations in ecological acoustic stimuli.

Efficient processing of sensory input is essential to ensure an organism's survival in its natural environment. Growing evidence suggests that sensory neurons can optimally encode natural stimuli by ensuring that their tuning opposes stimulus statistics, such that the resulting neuronal response contains equal power at all frequencies (i.e., is “white”). Such temporal decorrelation or whitening has been observed across modalities, but the effects of neural heterogeneities on determining tuning and thus responses to natural stimuli have not been investigated. Here, we investigate how heterogeneities in sensory pyramidal neurons organized in three parallel maps representing the body surface determine responses to second-order electrosensory stimulus features in the weakly electric fish Apteronotus leptorhynchus . While some sources of heterogeneities such as ON- and OFF-type responses to first-order did not affect responses to second-order electrosensory stimulus features, other sources of heterogeneity within and across the maps strongly determined responses. We found that these cells effectively performed a fractional differentiation operation on their input with exponents ranging from zero (no differentiation) to 0.4 (strong differentiation). Varying adaptation in a simple model explained these heterogeneities and predicted a strong correlation between fractional differentiation and adaptation. Using natural stimuli, we found that only a small fraction of neurons implemented temporal whitening. Rather, a large fraction of neurons did not perform any significant whitening and thus preserved natural input statistics in their responses. We propose that this information is needed to properly decode optimized information sent in parallel through temporally whitened responses based on context. SIGNIFICANCE STATEMENT We demonstrate that heterogeneities in the same sensory neuron type can either have no or significant influence on their responses to second-order stimulus features. While an ON- or OFF-type response to first-order stimulus attributes has no significant influence on responses to second-order stimulus features, we found that only a small fraction of sensory neurons optimally encoded natural stimuli through high-pass filtering, thereby implementing temporal whitening. Surprisingly, a large fraction of sensory neurons performed little if no filtering of stimuli, thereby preserving natural stimulus statistics. We hypothesize that this pathway is necessary to properly decode optimized information contained in temporally whitened responses based on context.

Neural sensing and stimulation have been the backbone of neuroscience research, brain-machine interfaces and clinical neuromodulation therapies for decades. To-date, most of the neural stimulation systems have relied on sharp metal microelectrodes with poor electrochemical properties that induce extensive damage to the tissue and significantly degrade the long-term stability of implantable systems. Here, we demonstrate a flexible cortical microelectrode array based on porous graphene, which is capable of efficient electrophysiological sensing and stimulation from the brain surface, without penetrating into the tissue. Porous graphene electrodes show superior impedance and charge injection characteristics making them ideal for high efficiency cortical sensing and stimulation. They exhibit no physical delamination or degradation even after 1 million biphasic stimulation cycles, confirming high endurance. In in vivo experiments with rodents, same array is used to sense brain activity patterns with high spatio-temporal resolution and to control leg muscles with high-precision electrical stimulation from the cortical surface. Flexible porous graphene array offers a minimally invasive but high efficiency neuromodulation scheme with potential applications in cortical mapping, brain-computer interfaces, treatment of neurological disorders, where high resolution and simultaneous recording and stimulation of neural activity are crucial.

Previous research demonstrated that while selectively attending to relevant aspects of the external world, the brain extracts pertinent information by aligning its neuronal oscillations to key time points of stimuli or their sampling by sensory organs. This alignment mechanism is termed oscillatory entrainment. We investigated the global, long-timescale dynamics of this mechanism in the primary auditory cortex of nonhuman primates, and hypothesized that lapses of entrainment would correspond to lapses of attention. By examining electrophysiological and behavioral measures, we observed that besides the lack of entrainment by external stimuli, attentional lapses were also characterized by high-amplitude alpha oscillations, with alpha frequency structuring of neuronal ensemble and single-unit operations. Entrainment and alpha-oscillation-dominated periods were strongly anticorrelated and fluctuated rhythmically at an ultra-slow rate. Our results indicate that these two distinct brain states represent externally versus internally oriented computational resources engaged by large-scale task-positive and task-negative functional networks.

In the auditory system, early neural stations such as brain stem are characterized by strict tonotopy, which is used to deconstruct sounds to their basic frequencies. But higher along the auditory hierarchy, as early as primary auditory cortex (A1), tonotopy starts breaking down at local circuits. Here, we studied the response properties of both excitatory and inhibitory neurons in the auditory cortex of anesthetized mice. We used in vivo two photon-targeted cell-attached recordings from identified parvalbumin-positive neurons (PVNs) and their excitatory pyramidal neighbors (PyrNs). We show that PyrNs are locally heterogeneous as characterized by diverse best frequencies, pairwise signal correlations, and response timing. In marked contrast, neighboring PVNs exhibited homogenous response properties in pairwise signal correlations and temporal responses. The distinct physiological microarchitecture of different cell types is maintained qualitatively in response to natural sounds. Excitatory heterogeneity and inhibitory homogeneity within the same circuit suggest different roles for each population in coding natural stimuli.

The development of the cerebellar system depends in part on the emergence of functional connectivity in its input and output pathways. Characterization of spontaneous activity within these pathways provides insight into their functional status in early development. In the present study we recorded extracellular activity from the interpositus nucleus (IP) and its primary downstream target, the red nucleus (RN), in unanesthetized rats at postnatal days 8 (P8) and P12, a period of dramatic change in cerebellar circuitry. The two structures exhibited state-dependent activity patterns and age-related changes in rhythmicity and overall firing rate. Importantly, sensory feedback (i.e., reafference) from myoclonic twitches (spontaneous, self-generated movements that are produced exclusively during active sleep) drove neural activity in the IP and RN at both ages. Additionally, anatomic tracing confirmed the presence of cerebellorubral connections as early as P8. Finally, inactivation of the IP and adjacent nuclei using the GABA A receptor agonist muscimol caused a substantial decrease in neural activity in the contralateral RN at both ages, as well as the disappearance of rhythmicity; twitch-related activity in the RN, however, was preserved after IP inactivation, indicating that twitch-related reafference activates the two structures in parallel. Overall, the present findings point to the contributions of sleep-related spontaneous activity to the development of cerebellar networks.

Rapid detection and diagnosis of a traumatic brain injury (TBI) can significantly improve the prognosis for recovery. Helmet-mounted sensors that detect impact severity based on measurements of acceleration or pressure show promise for aiding triage and transport decisions in active, field environments such as professional sports or military combat. The detected signals, however, report on the mechanics of an impact rather than directly indicating the presence and severity of an injury. We explored the use of cortical somatosensory evoked electroencephalographic potentials (SSEPs) to detect and track, in real-time, neural electrophysiological abnormalities within the first hour following head injury in an animal model. To study the immediate electrophysiological effects of injury in vivo, we developed an experimental paradigm involving focused ultrasound that permits continuous, real-time measurements and minimizes mechanical artifact. Injury was associated with a dramatic reduction of amplitude over the damaged hemisphere directly after the injury. The amplitude systematically improved over time but remained significantly decreased at one hour, compared with baseline. In contrast, at one hour there was a concomitant enhancement of the cortical SSEP amplitude evoked from the uninjured hemisphere. Analysis of the inter-trial electroencephalogram (EEG) also revealed significant changes in low-frequency components and an increase in EEG entropy up to 30 minutes after injury, likely reflecting altered EEG reactivity to somatosensory stimuli. Injury-induced alterations in SSEPs were also observed using noninvasive epidermal electrodes, demonstrating viability of practical implementation. These results suggest cortical SSEPs recorded at just a few locations by head-mounted sensors and associated multiparametric analyses could potentially be used to rapidly detect and monitor brain injury in settings that normally present significant levels of mechanical and electrical noise.

Sensory processing in the lower auditory pathway is generally considered to be rigid and thus less subject to modulation than central processing. However, in addition to the powerful bottom-up excitation by auditory nerve fibers, the ventral cochlear nucleus also receives efferent cholinergic innervation from both auditory and nonauditory top–down sources. We thus tested the influence of cholinergic modulation on highly precise time-coding neurons in the cochlear nucleus of the Mongolian gerbil. By combining electrophysiological recordings with pharmacological application in vitro and in vivo , we found 55–72% of spherical bushy cells (SBCs) to be depolarized by carbachol on two time scales, ranging from hundreds of milliseconds to minutes. These effects were mediated by nicotinic and muscarinic acetylcholine receptors, respectively. Pharmacological block of muscarinic receptors hyperpolarized the resting membrane potential, suggesting a novel mechanism of setting the resting membrane potential for SBC. The cholinergic depolarization led to an increase of spike probability in SBCs without compromising the temporal precision of the SBC output in vitro . In vivo , iontophoretic application of carbachol resulted in an increase in spontaneous SBC activity. The inclusion of cholinergic modulation in an SBC model predicted an expansion of the dynamic range of sound responses and increased temporal acuity. Our results thus suggest of a top–down modulatory system mediated by acetylcholine which influences temporally precise information processing in the lower auditory pathway.

To efficiently detect a wide range of light-intensity changes, visual neurons must adapt to ambient luminance. However, how neurons in the primary visual cortex (V1) code the distribution of luminance remains unknown. We designed stimuli that represent rapid changes in luminance under different luminance distributions and investigated V1 neuron responses to these novel stimuli. We demonstrate that V1 neurons represent luminance changes by dynamically adjusting their responses when the luminance distribution changes. Many cells (35%) detected luminance changes by responding to dark stimuli when the distribution was dominated by bright stimuli, bright stimuli when dominated by dark stimuli, and both dark and bright stimuli when dominated by intermediate luminance stimuli; 13% of cells signaled the mean luminance that was varied with different distributions; the remaining 52% of cells gradually shifted the responses that were most sensitive to luminance changes when the luminance distribution varied. The remarkable response changes of the former two cell groups suggest their crucial roles in detecting luminance changes. These response characteristics demonstrate that V1 neurons are not only sensitive to luminance change, but also luminance distribution change. They encode luminance changes according to the luminance distribution. Mean cells represent the prevailing luminance and reversal cells represent the salient stimuli in the environment.

Sound recognition relies not only on spectral cues, but also on temporal cues, as demonstrated by the profound impact of time reversals on perception of common sounds. To address the coding principles underlying such auditory asymmetries, we recorded a large sample of auditory cortex neurons using two-photon calcium imaging in awake mice, while playing sounds ramping up or down in intensity. We observed clear asymmetries in cortical population responses, including stronger cortical activity for up-ramping sounds, which matches perceptual saliency assessments in mice and previous measures in humans. Analysis of cortical activity patterns revealed that auditory cortex implements a map of spatially clustered neuronal ensembles, detecting specific combinations of spectral and intensity modulation features. Comparing different models, we show that cortical responses result from multi-layered nonlinearities, which, contrary to standard receptive field models of auditory cortex function, build divergent representations of sounds with similar spectral content, but different temporal structure.

Neurons at higher stages of sensory processing can partially compensate for a sudden drop in peripheral input through a homeostatic plasticity process that increases the gain on weak afferent inputs. Even after a profound unilateral auditory neuropathy where >95% of afferent synapses between auditory nerve fibers and inner hair cells have been eliminated with ouabain, central gain can restore cortical processing and perceptual detection of basic sounds delivered to the denervated ear. In this model of profound auditory neuropathy, auditory cortex (ACtx) processing and perception recover despite the absence of an auditory brainstem response (ABR) or brainstem acoustic reflexes, and only a partial recovery of sound processing at the level of the inferior colliculus (IC), an auditory midbrain nucleus. In this study, we induced a profound cochlear neuropathy with ouabain and asked whether central gain enabled a compensatory plasticity in the auditory thalamus comparable to the full recovery of function previously observed in the ACtx, the partial recovery observed in the IC, or something different entirely. Unilateral ouabain treatment in adult mice effectively eliminated the ABR, yet robust sound-evoked activity persisted in a minority of units recorded from the contralateral medial geniculate body (MGB) of awake mice. Sound driven MGB units could decode moderate and high-intensity sounds with accuracies comparable to sham-treated control mice, but low-intensity classification was near chance. Pure tone receptive fields and synchronization to broadband pulse trains also persisted, albeit with significantly reduced quality and precision, respectively. MGB decoding of temporally modulated pulse trains and speech tokens were both greatly impaired in ouabain-treated mice. Taken together, the absence of an ABR belied a persistent auditory processing at the level of the MGB that was likely enabled through increased central gain. Compensatory plasticity at the level of the auditory thalamus was less robust overall than previous observations in cortex or midbrain. Hierarchical differences in compensatory plasticity following sensorineural hearing loss may reflect differences in GABA circuit organization within the MGB, as compared to the ACtx or IC.

Objective . Electrocorticography (ECoG) has become an important tool in human neuroscience and has tremendous potential for emerging applications in neural interface technology. Electrode array design parameters are outstanding issues for both research and clinical applications, and these parameters depend critically on the nature of the neural signals to be recorded. Here, we investigate the functional spatial resolution of neural signals recorded at the human cortical surface. We empirically derive spatial spread functions to quantify the shared neural activity for each frequency band of the electrocorticogram. Approach . Five subjects with high-density (4 mm center-to-center spacing) ECoG grid implants participated in speech perception and production tasks while neural activity was recorded from the speech cortex, including superior temporal gyrus, precentral gyrus, and postcentral gyrus. The cortical surface field potential was decomposed into traditional EEG frequency bands. Signal similarity between electrode pairs for each frequency band was quantified using a Pearson correlation coefficient. Main results . The correlation of neural activity between electrode pairs was inversely related to the distance between the electrodes; this relationship was used to quantify spatial falloff functions for cortical subdomains. As expected, lower frequencies remained correlated over larger distances than higher frequencies. However, both the envelope and phase of gamma and high gamma frequencies (30–150 Hz) are largely uncorrelated (<90%) at 4 mm, the smallest spacing of the high-density arrays. Thus, ECoG arrays smaller than 4 mm have significant promise for increasing signal resolution at high frequencies, whereas less additional gain is achieved for lower frequencies. Significance. Our findings quantitatively demonstrate the dependence of ECoG spatial resolution on the neural frequency of interest. We demonstrate that this relationship is consistent across patients and across cortical areas during activity.

The occurrence of tinnitus can be linked to hearing loss in the majority of cases, but there is nevertheless a large degree of unexplained heterogeneity in the relation between hearing loss and tinnitus. Part of the problem might be that hearing loss is usually quantified in terms of increased hearing thresholds, which only provides limited information about the underlying cochlear damage. Moreover, noise exposure that does not cause hearing threshold loss can still lead to "hidden hearing loss" (HHL), i.e., functional deafferentation of auditory nerve fibers (ANFs) through loss of synaptic ribbons in inner hair cells. While it is known that increased hearing thresholds can trigger increases in spontaneous neural activity in the central auditory system, i.e., a putative neural correlate of tinnitus, the central effects of HHL have not yet been investigated. Here, we exposed mice to octave-band noise at 100 and 105 dB SPL to generate HHL and permanent increases of hearing thresholds, respectively. Deafferentation of ANFs was confirmed through measurement of auditory brainstem responses and cochlear immunohistochemistry. Acute extracellular recordings from the auditory midbrain (inferior colliculus) demonstrated increases in spontaneous neuronal activity (a putative neural correlate of tinnitus) in both groups. Surprisingly, the increase in spontaneous activity was most pronounced in the mice with HHL, suggesting that the relation between hearing loss and neuronal hyperactivity might be more complex than currently understood. Our computational model indicated that these differences in neuronal hyperactivity could arise from different degrees of deafferentation of low-threshold ANFs in the two exposure groups. Our results demonstrate that HHL is sufficient to induce changes in central auditory processing, and they also indicate a non-monotonic relationship between cochlear damage and neuronal hyperactivity, suggesting an explanation for why tinnitus might occur without obvious hearing loss and conversely why hearing loss does not always lead to tinnitus.

Unlabelled: In many sensory pathways, central neurons serve as temporal filters for timing patterns in communication signals. However, how a population of neurons with diverse temporal filtering properties codes for natural variation in communication signals is unknown. Here we addressed this question in the weakly electric fish Brienomyrus brachyistius, which varies the time intervals between successive electric organ discharges to communicate. These fish produce an individually stereotyped signal called a scallop, which consists of a distinctive temporal pattern of ∼8-12 electric pulses. We manipulated the temporal structure of natural scallops during behavioral playback and in vivo electrophysiology experiments to probe the temporal sensitivity of scallop encoding and recognition. We found that presenting time-reversed, randomized, or jittered scallops increased behavioral response thresholds, demonstrating that fish's electric signaling behavior was sensitive to the precise temporal structure of scallops. Next, using in vivo intracellular recordings and discriminant function analysis, we found that the responses of interval-selective midbrain neurons were also sensitive to the precise temporal structure of scallops. Subthreshold changes in membrane potential recorded from single neurons discriminated natural scallops from time-reversed, randomized, and jittered sequences. Pooling the responses of multiple neurons improved the discriminability of natural sequences from temporally manipulated sequences. Finally, we found that single-neuron responses were sensitive to interindividual variation in scallop sequences, raising the question of whether fish may analyze scallop structure to gain information about the sender. Collectively, these results demonstrate that a population of interval-selective neurons can encode behaviorally relevant temporal patterns with millisecond precision. Significance statement: The timing patterns of action potentials, or spikes, play important roles in representing information in the nervous system. However, how these temporal patterns are recognized by downstream neurons is not well understood. Here we use the electrosensory system of mormyrid weakly electric fish to investigate how a population of neurons with diverse temporal filtering properties encodes behaviorally relevant input timing patterns, and how this relates to behavioral sensitivity. We show that fish are behaviorally sensitive to millisecond variations in natural, temporally patterned communication signals, and that the responses of individual midbrain neurons are also sensitive to variation in these patterns. In fact, the output of single neurons contains enough information to discriminate stereotyped communication signals produced by different individuals.

The neural mechanisms that take place during learning and adaptation can be directly probed with brain-machine interfaces (BMIs). We developed a BMI controlled paradigm that enabled us to enforce learning by introducing perturbations which changed the relationship between neural activity and the BMI's output. We introduced a uniform perturbation to the system, through a visuomotor rotation (VMR), and a non-uniform perturbation, through a decorrelation task. The controller in the VMR was essentially unchanged, but produced an output rotated at 30° from the neurally specified output. The controller in the decorrelation trials decoupled the activity of neurons that were highly correlated in the BMI task by selectively forcing the preferred directions of these cell pairs to be orthogonal. We report that movement errors were larger in the decorrelation task, and subjects needed more trials to restore performance back to baseline. During learning, we measured decreasing trends in preferred direction changes and cross-correlation coefficients regardless of task type. Conversely, final adaptations in neural tunings were dependent on the type controller used (VMR or decorrelation). These results hint to the similar process the neural population might engage while adapting to new tasks, and how, through a global process, the neural system can arrive to individual solutions.