Abstract context representations are not just in the prefrontal cortex, they are also in the amygdala.  The authors also report that errors were associated with reduced context encoding.  Cool.

Saez, A., et al. “Abstract Context Representations in Primate Amygdala and Prefrontal Cortex.Neuron 87.4 (2015): 869-881.

Preview by Cohen and Paz:
Cohen, Yarden, and Rony Paz. “It All Depends on the Context, but Also on the Amygdala.” Neuron 87.4 (2015): 678-680.

Advance copy of our new paper:
Kornblith, S. Buschman, T.J., and Miller, E.K. (2015) Stimulus Load and Oscillatory Activity in Higher Cortex.  Cerebral Cortex.  doi: 10.1093/cercor/bhv182   Journal link

Abstract:
Exploring and exploiting a rich visual environment requires perceiving, attending, and remembering multiple objects simultaneously. Recent studies have suggested that this mental “juggling” of multiple objects may depend on oscillatory neural dynamics. We recorded local field potentials from the lateral intraparietal area, frontal eye fields, and lateral prefrontal cortex while monkeys maintained variable numbers of visual stimuli in working memory. Behavior suggested independent processing of stimuli in each hemifield. During stimulus presentation, higher-frequency power (50–100 Hz) increased with the number of stimuli (load) in the contralateral hemifield, whereas lower-frequency power (8–50 Hz) decreased with the total number of stimuli in both hemifields. During the memory delay, lower-frequency power increased with contralateral load. Load effects on higher frequencies during stimulus encoding and lower frequencies during the memory delay were stronger when neural activity also signaled the location of the stimuli. Like power, higher-frequency synchrony increased with load, but beta synchrony (16–30 Hz) showed the opposite effect, increasing when power decreased (stimulus presentation) and decreasing when power increased (memory delay). Our results suggest roles for lower-frequency oscillations in top-down processing and higher-frequency oscillations in bottom-up processing.

Fries and colleagues report that coupling between theta and gamma rhythms support attention.  The 4 Hz phase of gamma oscillations predicted the accuracy of the subject’s ability to detect stimulus dimming.

Landau, Ayelet Nina, et al. “Distributed Attention Is Implemented through Theta-Rhythmic Gamma Modulation.” Current Biology (2015).

Genovesio et al show that neurons in the prefrontal cortex can encode stimulus duration and distance.  Importantly, neural selectivity was highly context dependent.  Neurons seemed to have different, unrelated, selectivity in different behavioral contexts  This adds to growing evidence that PFC neurons are not simple filters or have single “triggers”.  Instead, PFC neurons are non-linear multitaskers that participate in many different neural ensembles.

Genovesio, Aldo, et al. “Context-Dependent Duration Signals in the Primate Prefrontal Cortex.” Cerebral Cortex (2015): bhv156.

Further reading:
Yuste, Rafael. “From the neuron doctrine to neural networks.” Nature Reviews Neuroscience (2015).

Rigotti, M., Barak, O., Warden, M.R., Wang, X., Daw, N.D., Miller, E.K., & Fusi, S. (2013) The importance of mixed selectivity in complex cognitive tasks. Nature, 497, 585-590, doi:10.1038/nature12160. View PDF

Voytek et al provide more evidence that oscillatory dynamics play a critical role in neural communication and cognitive control.  As humans performed tasks that required greater abstraction, there was an increase in theta synchrony between anterior and posterior frontal cortex.  This may allow more anterior frontal cortex is communicate the higher level goals to motor cortex.

Oscillatory dynamics coordinating human frontal networks in support of goal maintenance
Bradley Voytek, Andrew S Kayser, David Badre, David Fegen, Edward F Chang, Nathan E Crone, Josef Parvizi, Robert T Knight & Mark D’Esposito.  Nature Neuroscience

Pinto and Dan use Ca2+ imaging to identify different subtypes of inhibitory neurons in the mouse prefrontal cortex.  They found that different subtypes encode different aspects of the task. By contrast, excitatory neurons are diverse and their task-related activity by cortical layer.

Pinto, Lucas, and Yang Dan. “Cell-Type-Specific Activity in Prefrontal Cortex during Goal-Directed Behavior.” Neuron (2015).

Kozma et al report brief periods of de-synchronization followed by intense synchronization.  They speculate that this may correspond to an “aha!” moment when things “fall into place”.  Interesting.

Kozma, Robert, Jeffery Jonathan Davis, and Walter J. Freeman. “Synchronized minima in ECoG power at frequencies between beta-gamma oscillations disclose cortical singularities in cognition.” Journal of Neuroscience and Neuroengineering 1.1 (2012): 13-23.

The limited capacity of working memory has sometimes been explained as a limited number of memory “slots”.  Paul Bays argues that working memory capacity is due to sharing of a continuous resource, namely a fixed amount of neural activity.  Noise in this activity is the limiting factor.

Bays, Paul M. “Spikes not slots: noise in neural populations limits working memory.” Trends in Cognitive Sciences (2015).

The neuron doctrine – that individual neurons are the functional unit of the nervous system – has been the conceptual framework for modern neuroscience for over a century.  However, that doctrine has been dissolving under new evidence from multi-electrode recording.  Observations of multi-functional “mixed selectivity” neurons, ensembles forming from synchronized rhythmic activity between neurons, etc. is suggesting that ensembles of neurons, not individual neurons, are the functional units.  Rafel Yuste walks us through some of the evidence.

Yuste, Rafael. “From the neuron doctrine to neural networks.” Nature Reviews Neuroscience (2015).

Mirpour and Bisley provide new insights into how saccadic remapping produces perceptual stability during eye movements.

Mirpour, Koorosh, and James W. Bisley. “Remapping, Spatial Stability, and Temporal Continuity: From the Pre-Saccadic to Postsaccadic Representation of Visual Space in LIP.” Cerebral Cortex (2015): bhv153.

Decision-making due to a gradual ramp of neural firing rates?  Nope.  There are discrete state changes that are more informative that spike counts.

Single-trial spike trains in parietal cortex reveal discrete steps during decision-making
Kenneth W. LatimerJacob L. YatesMiriam L. R. MeisterAlexander C. Hukand Jonathan W. Pillow
Science 10 July 2015: 349 (6244), 184187. [DOI:10.1126/science.aaa4056]

Matt Wilson and colleagues describe how oscillatory cycles can be viewed as functional units, how different oscillation phases can represent distinct computations, and how all this can be organized across cycles.  Phew!

Wilson, Matthew A., Carmen Varela, and Miguel Remondes. “Phase organization of network computations.” Current opinion in neurobiology 31 (2015): 250-253.

Craig and McBain review the role of oscillations in understanding the functional circuitry of the hippocampus with an eye toward bridging in vitro and in vivo studies.

Craig, Michael T., and Chris J. McBain. “Navigating the circuitry of the brain’s GPS system: Future challenges for neurophysiologists.” Hippocampus (2015).

As the authors pun, the claustrum is worthy of attention given its extensive connections with the cortex. Goll, Atlan, and Citri propose a new hypothesis for the role of inputs from the prefrontal cortex to the claustrum in top-down attentional selection.  The claustrum acts to control the output of selected cortical representations at the expense of others.

Goll, Yael, Gal Atlan, and Ami Citri. “Attention: the claustrum.” Trends in Neurosciences (2015).

Bonnefond and Jenson used MEG in humans to find coupling between alpha and gamma rhythms during an attention-demanding task.  High alpha power was associated with weak gamma power at the trough of the alpha cycle.  This may provide a mechanism for top-down control of attention.

Bonnefond, Mathilde, and Ole Jensen. “Gamma Activity Coupled to Alpha Phase as a Mechanism for Top-Down Controlled Gating.” PloS one 10.6 (2015): e0128667.

Nice review of the mechanisms and role of dopamine receptors in the prefrontal cortex.

Arnsten, Amy FT, Min Wang, and Constantinos D. Paspalas. “Dopamine’s Actions in Primate Prefrontal Cortex: Challenges for Treating Cognitive Disorders.” Pharmacological Reviews 67.3 (2015): 681-696.

The title says it all (almost).  Voloh et al found increased theta-gamma cross-frequency coupling between the anterior cingulate and prefrontal cortex during covert shifts of attention.

Theta–gamma coordination between anterior cingulate and prefrontal cortex indexes correct attention shifts
Benjamin Voloh, Taufik A. Valiante, Stefan Everling, and Thilo Womelsdorf
PNAS 2015 ; published ahead of print June 22, 2015, doi:10.1073/pnas.1500438112

Tremblay et al decode the allocation of attention, stimulus location, and saccade from local field potentials in a frequency-dependent matter.  Decoding from LFPs was more stable across time than decoding from spikes.

Siegel, M., Buschman, T.J., and Miller, E.K. (2015) Cortical information flow during flexible sensorimotor decisions.  Science19 June 2015: 1352-1355.

During flexible behavior, multiple brain regions encode sensory inputs, the current task, and choices.  It remains unclear how these signals evolve. We simultaneously recorded neuronal activity from six cortical regions (MT, V4, IT, LIP, PFC and FEF) of monkeys reporting the color or motion of stimuli. Following a transient bottom-up sweep, there was a top-down flow of sustained task information from frontoparietal to visual cortex.  Sensory information flowed from visual to parietal and prefrontal cortex. Choice signals developed simultaneously in frontoparietal regions and travelled to FEF and sensory cortex. This suggests that flexible sensorimotor choices emerge in a frontoparietal network from the integration of opposite flows of sensory and task information.

From the MIT News Office:
Uncovering a dynamic cortex
Neuroscientists show that multiple cortical regions are needed to process information.

Luo and Maunsell used a specially designed task to show that the only effect of attention in visual cortex is to improve the signal-to-noise ratio of neurons.

Neuronal Modulations in Visual Cortex Are Associated with Only One of Multiple Components of Attention
TZ Luo, JHR Maunsell – Neuron, 2015

See highlight by Timothy J. Buschman:
Paying Attention to the Details of Attention
TJ Buschman – Neuron, 2015

Working memory has long been thought to depend on sustained firing of cortical neurons.  However, single neurons showing unbroken sustained activity is rare and average population activity is often only strong near the end of a memory delay.  Mark Stokes presents the intriguing hypothesis for activity-silent working memory.  He suggests that working memory depends on patterns of functional connectivity between neurons, not sustained activity.

‘Activity-silent’working memory in prefrontal cortex: a dynamic coding framework
MG Stokes – Trends in Cognitive Sciences, 2015

Takeda et al show that layer-specific oscillatory synchrony during successful recall of memories.  Specifically, there was laminar specific feedback from area 36 to area TE that supported the recall of a paired associate object.

One person’s (John Lisman) take on the state of the art of neuroscience in 2015.
The Challenge of Understanding the Brain: Where We Stand in 2015

Woolgar et al show preferential engagement of human frontoparietal networks with an increase in the complexity of task rules.  Plus, the frontoparietal cortex adjusts representations to make rules that are more behavioral confusable easier to discriminate.

Earl Miller will discuss the dangers of multitasking today (5/23/15) live on the air on WURD 900AM at 11:20am.
http://900amwurd.com/