@article {4099, title = {Neural Interactions Underlying Visuomotor Associations in the Human Brain}, journal = {Cerebral Cortex}, volume = {1{\textendash}17}, year = {2018}, month = {12/2018}, abstract = {

Rapid andflexible learning during behavioral choices is critical to our daily endeavors and constitutes a hallmark ofdynamic reasoning. An important paradigm to examineflexible behavior involves learning new arbitrary associationsmapping visual inputs to motor outputs. We conjectured that visuomotor rules are instantiated by translating visual signalsinto actions through dynamic interactions between visual, frontal and motor cortex. We evaluated the neuralrepresentation of such visuomotor rules by performing intracranialfield potential recordings in epilepsy subjects during arule-learning delayed match-to-behavior task. Learning new visuomotor mappings led to the emergence of specificresponses associating visual signals with motor outputs in 3 anatomical clusters in frontal, anteroventral temporal andposterior parietal cortex. After learning, mapping selective signals during the delay period showed interactions with visualand motor signals. These observations provide initial steps towards elucidating the dynamic circuits underlyingflexiblebehavior and how communication between subregions of frontal, temporal, and parietal cortex leads to rapid learning oftask-relevant choices.

}, keywords = {frontal cortex, human neurophysiology, reinforcement learning, visual cortex}, issn = {1047-3211}, doi = {10.1093/cercor/bhy333}, url = {http://klab.tch.harvard.edu/publications/PDFs/gk7766.pdf}, author = {Radhika Madhavan and Bansal, Arjun K and Joseph Madsen and Golby, Alexandra J and Travis S Tierney and Emad Eskandar and WS Anderson and Gabriel Kreiman} } @article {2262, title = {Cascade of neural processing orchestrates cognitive control in human frontal cortex [dataset]}, year = {2016}, publisher = {eLife}, abstract = {

Code and data used to create the figures of Tang et al. (2016).\  The results from this work show that there is a dynamic and hierarchical sequence of steps in human frontal cortex orchestrates cognitive control.

Used in conjunction with this mirrored CBMM Code entry

}, url = {http://klab.tch.harvard.edu/resources/tangetal_stroop_2016.html}, author = {Hanlin Tang and Hsiang-Yu Yu and Chien-Chen Chou and Crone, Nathan~E. and Joseph Madsen and WS Anderson and Gabriel Kreiman} } @article {2261, title = {Cascade of neural processing orchestrates cognitive control in human frontal cortex [code]}, year = {2016}, publisher = {eLife}, abstract = {

Code and data used to create the figures of Tang et al. (2016).\  The results from this work show that there is a dynamic and hierarchical sequence of steps in human frontal cortex orchestrates cognitive control.

Used in conjunction with this mirrored CBMM Dataset entry

}, url = {http://klab.tch.harvard.edu/resources/tangetal_stroop_2016.html}, author = {Hanlin Tang and Hsiang-Yu Yu and Chien-Chen Chou and Crone, Nathan~E. and Joseph Madsen and WS Anderson and Gabriel Kreiman} } @article {1847, title = {Cascade of neural processing orchestrates cognitive control in human frontal cortex}, journal = {eLIFE}, year = {2016}, month = {02/2016}, abstract = {
Rapid and flexible interpretation of conflicting sensory inputs in the context of current goals is a critical component of cognitive control that is orchestrated by frontal cortex. The relative roles of distinct subregions within frontal cortex are poorly understood. To examine the dynamics underlying cognitive control across frontal regions, we took advantage of the spatiotemporal resolution of intracranial recordings in epilepsy patients while subjects resolved color-word conflict.We observed differential activity preceding the behavioral responses to conflict trials throughout frontal cortex; this activity was correlated with behavioral reaction times. These signals emerged first in anterior cingulate cortex (ACC) before dorsolateral prefrontal cortex (dlPFC), followed bymedial frontal cortex (mFC) and then by orbitofrontal cortex (OFC). These results disassociate the frontal subregions based on their dynamics, and suggest a temporal hierarchy for cognitive control in human cortex.
}, doi = {10.7554/eLife.12352}, url = {http://dx.doi.org/10.7554/eLife.12352}, author = {Hanlin Tang and Yu, HY and Chou, CC and NE Crone and Joseph Madsen and WS Anderson and Gabriel Kreiman} } @article {1155, title = {Decrease in gamma-band activity tracks sequence learning}, journal = {Frontiers in Systems Neuroscience}, volume = {8}, year = {2015}, month = {01/21/2015}, abstract = {

Learning novel sequences constitutes an example of declarative memory formation, involving conscious recall of temporal events. Performance in sequence learning tasks improves with repetition and involves forming temporal associations over scales of seconds to minutes. To further understand the neural circuits underlying declarative sequence learning over trials, we tracked changes in intracranial field potentials (IFPs) recorded from 1142 electrodes implanted throughout temporal and frontal cortical areas in 14 human subjects, while they learned the temporal-order of multiple sequences of images over trials through repeated recall. We observed an increase in power in the gamma frequency band (30{\textendash}100 Hz) in the recall phase, particularly in areas within the temporal lobe including the parahippocampal gyrus. The degree of this gamma power enhancement decreased over trials with improved sequence recall. Modulation of gamma power was directly correlated with the improvement in recall performance. When presenting new sequences, gamma power was reset to high values and decreased again after learning. These observations suggest that signals in the gamma frequency band may play a more prominent role during the early steps of the learning process rather than during the maintenance of memory traces.

}, doi = {10.3389/fnsys.2014.00222}, url = {http://journal.frontiersin.org/article/10.3389/fnsys.2014.00222/abstract}, author = {Radhika Madhavan and Daniel Millman and Hanlin Tang and NE Crone and Fredrick A. Lenz and Travis S Tierney and Joseph Madsen and Gabriel Kreiman and WS Anderson} } @article {1154, title = {Sensitivity to timing and order in human visual cortex}, journal = {Journal of Neurophysiology}, volume = {113}, year = {2015}, month = {Jan-03-2015}, pages = {1656 - 1669}, issn = {0022-3077}, doi = {10.1152/jn.00556.2014}, url = {http://jn.physiology.org/lookup/doi/10.1152/jn.00556.2014}, author = {Jedediah Singer and Joseph Madsen and WS Anderson and Gabriel Kreiman} } @article {456, title = {A role for recurrent processing in object completion: neurophysiological, psychophysical and computational evidence.}, number = {009}, year = {2014}, month = {04/2014}, abstract = {

Recognition of objects from partial information presents a significant challenge for theories of vision because it requires spatial integration and extrapolation from prior knowledge. We combined neurophysiological recordings in human cortex with psychophysical measurements and computational modeling to investigate the mechanisms involved in object completion. We recorded intracranial field potentials from 1,699 electrodes in 18 epilepsy patients to measure the timing and selectivity of responses along human visual cortex to whole and partial objects. Responses along the ventral visual stream remained selective despite showing only 9\>25 of the object. However, these visually selective signals emerged ~100 ms later for partial versus whole objects. The processing delays were particularly pronounced in higher visual areas within the ventral stream, suggesting the involvement of additional recurrent processing. In separate psychophysics experiments, disrupting this recurrent computation with a backward mask at ~75ms significantly impaired recognition of partial, but not whole, objects. Additionally, computational modeling shows that the performance of a purely bottom\>up architecture is impaired by heavy occlusion and that this effect can be partially rescued via the incorporation of top\>down connections. These results provide spatiotemporal constraints on theories of object recognition that involve recurrent processing to recognize objects from partial information.

}, author = {Hanlin Tang and Buia, Calin and Joseph Madsen and WS Anderson and Gabriel Kreiman} } @article {440, title = {Sensitivity to Timing and Order in Human Visual Cortex.}, number = {005}, year = {2014}, month = {04/2014}, abstract = {

Visual recognition takes a small fraction of a second and relies on the cascade of signals along the ventral visual stream. Given the rapid path through multiple processing steps between photoreceptors and higher visual areas, information must progress from stage to stage very quickly. This rapid progression of information suggests that fine temporal details of the neural response may be important to the how the brain encodes visual signals. We investigated how changes in the relative timing of incoming visual stimulation affect the representation of object information by recording intracranial field potentials along the human ventral visual stream while subjects recognized objects whose parts were presented with varying asynchrony. Visual responses along the ventral stream were sensitive to timing differences between parts as small as 17 ms. In particular, there was a strong dependency on the temporal order of stimulus presentation, even at short asynchronies. This sensitivity to the order of stimulus presentation provides evidence that the brain may use differences in relative timing as a means of representing information.

}, keywords = {Circuits for Intelligence, Pattern recognition, Visual}, author = {Jedediah Singer and Joseph Madsen and WS Anderson and Gabriel Kreiman} } @article {217, title = {Spatiotemporal Dynamics Underlying Object Completion in Human Ventral Visual Cortex}, journal = {Neuron}, volume = {83}, year = {2014}, month = {08/06/2014}, pages = {736 - 748}, abstract = {

Natural vision often involves recognizing objects from partial information. Recognition of objects from parts presents a significant challenge for theories of vision because it requires spatial integration and extrapolation from prior knowledge. Here we recorded intracranial field potentials of 113 visually selective electrodes from epilepsy patients in response to whole and partial objects. Responses along the ventral visual stream, particularly the Inferior Occipital and Fusiform Gyri, remained selective despite showing only 9-25\% of the object areas. However, these visually selective signals emerged ~100 ms later for partial versus whole objects. These processing delays were particularly pronounced in higher visual areas within the ventral stream. This latency difference persisted when controlling for changes in contrast, signal amplitude, and the strength of selectivity. These results argue against a purely feed-forward explanation of recognition from partial information, and provide spatiotemporal constraints on theories of object recognition that involve recurrent processing.

}, keywords = {Circuits for Intelligence, vision}, issn = {08966273}, doi = {10.1016/j.neuron.2014.06.017}, url = {http://linkinghub.elsevier.com/retrieve/pii/S089662731400539Xhttp://api.elsevier.com/content/article/PII:S089662731400539X?httpAccept=text/xmlhttp://api.elsevier.com/content/article/PII:S089662731400539X?httpAccept=text/plain}, author = {Hanlin Tang and Buia, Calin and Radhika Madhavan and NE Crone and Joseph Madsen and WS Anderson and Gabriel Kreiman} } @article {2812, title = {Spatiotemporal dynamics of neocortical excitation and inhibition during human sleep}, journal = {Proceedings of the National Academy of Sciences}, year = {2012}, abstract = {

Intracranial recording is an important diagnostic method routinely used in a number of neurological monitoring scenarios. In recent years, advancements in such recordings have been extended to include unit activity of an ensemble of neurons. However, a detailed functional characterization of excitatory and inhibitory cells has not been attempted in human neocortex, particularly during the sleep state. Here, we report that such feature discrimination is possible from high-density recordings in the neocortex by using 2D multielectrode arrays. Successful separation of regular-spiking neurons (or bursting cells) from fast-spiking cells resulted in well-defined clusters that each showed unique intrinsic firing properties. The high density of the array, which allowed recording from a large number of cells (up to 90), helped us to identify apparent monosynaptic connections, confirming the excitatory and inhibitory nature of regular-spiking and fast-spiking cells, thus categorized as putative pyramidal cells and interneurons, respectively. Finally, we investigated the dynamics of correlations within each class. A marked exponential decay with distance was observed in the case of excitatory but not for inhibitory cells. Although the amplitude of that decline depended on the timescale at which the correlations were computed, the spatial constant did not. Furthermore, this spatial constant is compatible with the typical size of human columnar organization. These findings provide a detailed characterization of neuronal activity, functional connectivity at the microcircuit level, and the interplay of excitation and inhibition in the human neocortex.

}, doi = {10.1073/pnas.1109895109}, url = {http://www.pnas.org/content/109/5/1731}, author = {Adrien Peyrache and Nima Dehghani and Emad Eskandar and Joseph Madsen and WS Anderson and Jacob Donoghue and Leigh Hochberg and Eric Halgren and Sydney Cash and Alain Destexhe} }