Spontaneously emerging internal models of visual sequences combine abstract and event-specific information in the prefrontal cortex.

When exposed to sensory sequences, do macaque monkeys spontaneously form abstract internal models that generalize to novel experiences? Here, we show that neuronal populations in macaque ventrolateral prefrontal cortex jointly encode visual sequences by separate codes for the specific pictures presented and for their abstract sequential structure. We recorded prefrontal neurons while macaque monkeys passively viewed visual sequences and sequence mismatches in the local-global paradigm. Even without any overt task or response requirements, prefrontal populations spontaneously form representations of sequence structure, serial order, and image identity within distinct but superimposed neuronal subspaces. Representations of sequence structure rapidly update following single exposure to a mismatch sequence, while distinct populations represent mismatches for sequences of different complexity. Finally, those representations generalize across sequences following the same repetition structure but comprising different images. These results suggest that prefrontal populations spontaneously encode rich internal models of visual sequences reflecting both content-specific and abstract information.

Severe distortion in the representation of foveal visual image locations in short-term memory.

The foveal visual image region provides the human visual system with the highest acuity. However, it is unclear whether such a high fidelity representational advantage is maintained when foveal image locations are committed to short-term memory. Here, we describe a paradoxically large distortion in foveal target location recall by humans. We briefly presented small, but high contrast, points of light at eccentricities ranging from 0.1 to 12°, while subjects maintained their line of sight on a stable target. After a brief memory period, the subjects indicated the remembered target locations via computer controlled cursors. The biggest localization errors, in terms of both directional deviations and amplitude percentage overshoots or undershoots, occurred for the most foveal targets, and such distortions were still present, albeit with qualitatively different patterns, when subjects shifted their gaze to indicate the remembered target locations. Foveal visual images are severely distorted in short-term memory.

Decoding rapidly presented visual stimuli from prefrontal ensembles without report nor post-perceptual processing.

The role of the primate prefrontal cortex (PFC) in conscious perception is debated. The global neuronal workspace theory of consciousness predicts that PFC neurons should contain a detailed code of the current conscious contents. Previous research showed that PFC is indeed activated in paradigms of conscious visual perception, including no-report paradigms where no voluntary behavioral report of the percept is given, thus avoiding a conflation of signals related to visual consciousness with signals related to the report. Still, it has been argued that prefrontal modulation could reflect post-perceptual processes that may be present even in the absence of report, such as thinking about the perceived stimulus, therefore reflecting a consequence rather than a direct correlate of conscious experience. Here, we investigate these issues by recording neuronal ensemble activity from the macaque ventrolateral PFC during briefly presented visual stimuli, either in isolated trials in which stimuli were clearly perceived or in sequences of rapid serial visual presentation (RSVP) in which perception and post-perceptual processing were challenged. We report that the identity of each stimulus could be decoded from PFC population activity even in the RSVP condition. The first visual signals could be detected at 60 ms after stimulus onset and information was maximal at 150 ms. However, in the RSVP condition, 200 ms after the onset of a stimulus, the decoding accuracy quickly dropped to chance level and the next stimulus started to be decodable. Interestingly, decoding in the ventrolateral PFC was stronger compared to posterior parietal cortex for both isolated and RSVP stimuli. These results indicate that neuronal populations in the macaque PFC reliably encode visual stimuli even under conditions that have been shown to challenge conscious perception and/or substantially reduce the probability of post-perceptual processing in humans. We discuss whether the observed activation reflects conscious access, phenomenal consciousness, or merely a preconscious bottom-up wave.

Using deep neural networks to detect complex spikes of cerebellar Purkinje cells.

One of the most powerful excitatory synapses in the brain is formed by cerebellar climbing fibers, originating from neurons in the inferior olive, that wrap around the proximal dendrites of cerebellar Purkinje cells. The activation of a single olivary neuron is capable of generating a large electrical event, called "complex spike," at the level of the postsynaptic Purkinje cell, comprising of an initial large-amplitude spike followed by a long polyphasic tail of small-amplitude spikelets. Several ideas discussing the role of the cerebellum in motor control are centered on these complex spike events. However, these events, only occurring one to two times per second, are extremely rare relative to Purkinje cell "simple spikes" (standard sodium-potassium action potentials). As a result, drawing conclusions about their functional role has been very challenging. In fact, because standard spike sorting approaches cannot fully handle the polyphasic shape of complex spike waveforms, the only safe way to avoid omissions and false detections has been to rely on visual inspection by experts, which is both tedious and, because of attentional fluctuations, error prone. Here we present a deep learning algorithm for rapidly and reliably detecting complex spikes. Our algorithm, utilizing both action potential and local field potential signals, not only detects complex spikes much faster than human experts, but it also reliably provides complex spike duration measures similar to those of the experts. A quantitative comparison of our algorithm's performance to both classic and novel published approaches addressing the same problem reveals that it clearly outperforms these approaches.NEW & NOTEWORTHY Purkinje cell "complex spikes", fired at perplexingly low rates, play a crucial role in cerebellum-based motor learning. Careful interpretations of these spikes require manually detecting them, since conventional online or offline spike sorting algorithms are optimized for classifying much simpler waveform morphologies. We present a novel deep learning approach for identifying complex spikes, which also measures additional relevant neurophysiological features, with an accuracy level matching that of human experts yet with very little time expenditure.

Memory-guided microsaccades.

Despite strong evidence to the contrary in the literature, microsaccades are overwhelmingly described as involuntary eye movements. Here we show in both human subjects and monkeys that individual microsaccades of any direction can easily be triggered: (1) on demand, based on an arbitrary instruction, (2) without any special training, (3) without visual guidance by a stimulus, and (4) in a spatially and temporally accurate manner. Subjects voluntarily generated instructed "memory-guided" microsaccades readily, and similarly to how they made normal visually-guided ones. In two monkeys, we also observed midbrain superior colliculus neurons that exhibit movement-related activity bursts exclusively for memory-guided microsaccades, but not for similarly-sized visually-guided movements. Our results demonstrate behavioral and neural evidence for voluntary control over individual microsaccades, supporting recently discovered functional contributions of individual microsaccade generation to visual performance alterations and covert visual selection, as well as observations that microsaccades optimize eye position during high acuity visually-guided behavior.

Human-level saccade detection performance using deep neural networks.

Saccades are ballistic eye movements that rapidly shift gaze from one location of visual space to another. Detecting saccades in eye movement recordings is important not only for studying the neural mechanisms underlying sensory, motor, and cognitive processes, but also as a clinical and diagnostic tool. However, automatically detecting saccades can be difficult, particularly when such saccades are generated in coordination with other tracking eye movements, like smooth pursuits, or when the saccade amplitude is close to eye tracker noise levels, like with microsaccades. In such cases, labeling by human experts is required, but this is a tedious task prone to variability and error. We developed a convolutional neural network to automatically detect saccades at human-level accuracy and with minimal training examples. Our algorithm surpasses state of the art according to common performance metrics and could facilitate studies of neurophysiological processes underlying saccade generation and visual processing. NEW & NOTEWORTHY Detecting saccades in eye movement recordings can be a difficult task, but it is a necessary first step in many applications. We present a convolutional neural network that can automatically identify saccades with human-level accuracy and with minimal training examples. We show that our algorithm performs better than other available algorithms, by comparing performance on a wide range of data sets. We offer an open-source implementation of the algorithm as well as a web service.

Sequential hemifield gating of α- and ß-behavioral performance oscillations after microsaccades.

Microsaccades are tiny saccades that occur during gaze fixation. Even though visual processing has been shown to be strongly modulated close to the time of microsaccades, both at central and peripheral eccentricities, it is not clear how these eye movements might influence longer term fluctuations in brain activity and behavior. Here we found that visual processing is significantly affected and, in a rhythmic manner, even several hundreds of milliseconds after a microsaccade. Human visual detection efficiency, as measured by reaction time, exhibited coherent rhythmic oscillations in the α- and ß-frequency bands for up to ~650-700 ms after a microsaccade. Surprisingly, the oscillations were sequentially pulsed across visual hemifields relative to microsaccade direction, first occurring in the same hemifield as the movement vector for ~400 ms and then the opposite. Such pulsing also affected perceptual detection performance. Our results suggest that visual processing is subject to long-lasting oscillations that are phase locked to microsaccade generation, and that these oscillations are dependent on microsaccade direction.NEW & NOTEWORTHY We investigated long-term microsaccadic influences on visual processing and found rhythmic oscillations in behavioral performance at α- and ß-frequencies (~8-20 Hz). These oscillations were pulsed at a much lower frequency across visual hemifields, first occurring in the same hemifield as the microsaccade direction vector for ~400 ms before switching to the opposite hemifield for a similar interval. Our results suggest that saccades temporally organize visual processing and that such organization can sequentially switch hemifields.

Role for serotonin2A (5-HT2A) and 2C (5-HT2C) receptors in experimental absence seizures.

Absence seizures (ASs) are the hallmark of childhood/juvenile absence epilepsy. Monotherapy with first-line anti-absence drugs only controls ASs in 50% of patients, indicating the need for novel therapeutic targets. Since serotonin family-2 receptors (5-HT2Rs) are known to modulate neuronal activity in the cortico-thalamo-cortical loop, the main network involved in AS generation, we investigated the effect of selective 5-HT2AR and 5-HT2CR ligands on ASs in the Genetic Absence Epilepsy Rats from Strasbourg (GAERS), a well established polygenic rat model of these non-convulsive seizures. GAERS rats were implanted with fronto-parietal EEG electrodes under general anesthesia, and their ASs were later recorded under freely moving conditions before and after intraperitoneal administration of various 5-HT2AR and 5-HT2CR ligands. The 5-HT2A agonist TCB-2 dose-dependently decreased the total time spent in ASs, an effect that was blocked by the selective 5-HT2A antagonist MDL11,939. Both MDL11,939 and another selective 5-HT2A antagonist (M100,907) increased the length of individual seizures when injected alone. The 5-HT2C agonists lorcaserin and CP-809,101 dose-dependently suppressed ASs, an effect blocked by the selective 5-HT2C antagonist SB 242984. In summary, 5-HT2ARs and 5-HT2CRs negatively control the expression of experimental ASs, indicating that selective agonists at these 5-HT2R subtypes might be potential novel anti-absence drugs.