Steven L. Bressler Cognitive Neurodynamics Laboratory Center for Complex Systems & Brain Sciences Department of Psychology Florida Atlantic University

Outline Top-down processing is a tractable problem in cognition Neurocognitive networks provide a workable theoretical framework for understanding top- down processing in the brain Novel approaches are being developed to investigate top-down processing by neurocognitive networks

Top-Down Processing in Cognitive and Brain Sciences Cognitive Science: Effect of knowledge on sensory processing Brain Science: Effect of “higher-level” neurons on “lower-level” neurons

Top-Down Cognitive Processes Where Advances are Tractable Attention: selecting items in perception Expectation: priming items for perception Inference: identifying items in perception

Top-Down Processing in Visuospatial Attention Corbetta et al., Neuron, 2008 The Dorsal Attention Network (DAN) is a system of frontal and parietal regions consistently activated by cues indicating where a visual object will appear. The DAN is postulated to exert attentional top- down control of visual cortical.

Prestimulus Processing in Visual Expectation Poststimulus Processing in Visual Inference

Prestimulus Beta-Synchronized Network in Visual Cortex Bressler et al, Stat Med, 2007 Synchronized beta rhythms between V1 & extrastriate cortex (V4, TEO) form a large-scale network in visual cortex before stimulus presentation. 1,2,3 – V1 5 – V4 6 –TEO

Top-Down Feedforward Beta Synchrony in Visual Cortex Richter et al., in prep A.Prestimulus extrastriate & V1 beta rhythms are synchronized. B.Synchronized beta rhythms support top-down extrastriate- to-V1, but not bottom-up V1-to-extrastriate, influences.

Neurocognitive Networks: Aleksandr Luria “The concept of localization of functions … has come to mean a network of complex dynamic structures or combination centers, consisting of mosaics of distant points of the nervous system, united in a common task.” Higher Cortical Functions in Man, 1962

Neurocognitive Networks NeuroCognitive Networks are large-scale systems of distributed and interconnected neuronal populations in the brain organized to perform cognitive functions. Bressler, Scholarpedia, 2008 Bressler & Menon, TICS, 2010 Fuster & Bressler, TICS, 2012 Meehan & Bressler, NBR, 2012

Top-Down Processing by Neurocognitive Networks Top-down processing in the brain involves the effect that neurons in a “higher” area have on neurons in a “lower” area. It can be observed in the brain wherever a hierarchical order exists It may involve effects within or between NeuroCognitive Networks (NCNs):  Between NCNs: FEF  V 4  Within NCN: V4  V1

Analytic Techniques A variety of analytic techniques are used to investigate top-down processing in the brain ▶ Stimulation: TMS, TACS, CMS ▶ Ablation: clinical analysis of stroke ▶ Electrophysiological Time Series Recording ▶ BOLD Time Series Recording ▶ Causal Time Series Modeling: AR models, DCM ▶ Biophysical Modeling: Neural mass models, integrate-and-fire models

Future Developments Multi-Site Recording Modalities Improved Causal Modeling Techniques Improved Large-Scale Biophysical Modeling Graph Theoretic Methods Tailored to Brain Networks

Summary Top-down processing is essential in cognition Top-down processing underlies attention, expectation, and inference – all used in perception Top-down processing in cognitive science has a parallel interpretation in neuroscience Top-down processing in the brain is readily accommodated by the concept of neurocognitive networks Numerous analytic techniques are available, or are being developed, to study top-down processing by neurocognitive networks.